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Небесная энциклопедия

Космические корабли и станции, автоматические КА и методы их проектирования, бортовые комплексы управления, системы и средства жизнеобеспечения, особенности технологии производства ракетно-космических систем

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Мониторинг СМИ

Мониторинг СМИ и социальных сетей. Сканирование интернета, новостных сайтов, специализированных контентных площадок на базе мессенджеров. Гибкие настройки фильтров и первоначальных источников.

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Поддерживает ввод нескольких поисковых фраз (по одной на строку). При поиске обеспечивает поддержку морфологии русского и английского языка
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Применить Всего найдено 215869. Отображено 100.
09-06-2017 дата публикации

Малогабаритное устройство "электронный нос" для распознавания образа запаха широкого класса химических веществ

Номер: RU0000171691U1
Автор: Александр Викторович Шустров, Александр Иванович Иванов, Владимир Петрович Кулагин, Роман Игоревич Курочкин
Принадлежит: федеральное государственное автономное образовательное учреждение высшего образования "Национальный исследовательский университет "Высшая школа экономики"

Использование: для обнаружения и распознавания многокомпонентных газовых сред. Сущность полезной модели заключается в том, что малогабаритное устройство «электронный нос» для распознавания образа запаха состоит из матрицы газочувствительных датчиков, выход которой подключен к блоку предварительной обработки с использованием искусственных нейронных сетей, выход блока предварительной обработки подключен ко входу блока распознавания запахов, а его выход соединен со входом блока индикации, входы управления режимами работы матрицы газочувствительных датчиков подключены к выходам блока управления нагревом датчиков, входы управления блока распознавания и блока управления нагревом датчиков подключены к выходам блока управления устройством, блок распознавания запахов включает модуль с, по меньшей мере, шестнадцатью искусственными нейронными сетями, каждая из которых предварительно обучена распознавать образ одного запаха, модуль базы данных таблиц искусственных нейронных сетей, каждая из которых предварительно обучена распознавать образ одного запаха, преобразуя его в уникальный выходной код, модуль с, по меньшей мере, одной необученной искусственной нейронной сетью и модулем базы данных таблиц необученных искусственных нейронных сетей, блок распознавания снабжен постоянным машиночитаемым носителем данных с программным обеспечением, сконфигурированным с возможностью реализации функций распознавания газов или паров веществ по их "запаховым образам". Технический результат: обеспечение возможности увеличения числа образов распознаваемых запахов. 1 з.п. ф-лы, 3 ил. РОССИЙСКАЯ ФЕДЕРАЦИЯ (19) RU (11) (13) 171 691 U1 (51) МПК G01N 27/27 (2006.01) G06F 15/18 (2006.01) ФЕДЕРАЛЬНАЯ СЛУЖБА ПО ИНТЕЛЛЕКТУАЛЬНОЙ СОБСТВЕННОСТИ (12) ФОРМУЛА ПОЛЕЗНОЙ МОДЕЛИ К ПАТЕНТУ РОССИЙСКОЙ ФЕДЕРАЦИИ (21)(22) Заявка: 2016152067, 28.12.2016 (24) Дата начала отсчета срока действия патента: 28.12.2016 09.06.2017 Приоритет(ы): (22) Дата подачи заявки: 28.12.2016 1 7 1 6 9 1 R U (56) Список документов ...

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Номер записи: 1
12-01-2012 дата публикации

System and method for remote melanoma screening

Номер: US20120008838A1
Автор: Isabelle Guyon, Stephen D. Barnhill
Принадлежит: Health Discovery Corp

A system and method are provided for diagnosing diseases or conditions from digital images taken by a remote user with a smart phone or a digital camera and transmitted to an image analysis server in communication with a distributed network. The image analysis server includes a trained learning machine for classification of the images. The user-provided image is pre-processed to extract dimensional, shape and color features then is processed using the trained learning machine to classify the image. The classification result is postprocessed to generate a risk score that is transmitted to the remote user. A database associated with the server may include referral information for geographically matching the remote user with a local physician. An optional operation includes collection of financial information to secure payment for analysis services.

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Номер записи: 2
26-01-2012 дата публикации

Robust information fusion methods for decision making for multisource data

Номер: US20120023062A1
Автор: Akshay Vashist
Принадлежит: Telcordia Technologies Inc

Methods and systems are provided for developing decision information relating to a single system based on data received from a plurality of sensors. The method includes receiving first data from a first sensor that defines first information of a first type that is related to a system, receiving second data from a second sensor that defines second information of a second type that is related to said system, wherein the first type is different from the second type, generating a first decision model, a second decision model, and a third decision model, determining whether data is available from only the first sensor, only the second sensor, or both the first and second sensors, and selecting based on the determination of availability an additional model to apply the available data, wherein the additional model is selected from a plurality of additional decision models including the third decision model.

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Номер записи: 3
02-02-2012 дата публикации

Method and system for assessing data classification quality

Номер: US20120030151A1
Автор: Douglass Huang, K. Bradley Paxton, Steven Paul Spiwak
Принадлежит: ADI LLC

Production data classified from a data source, such as a plurality of handprinted forms, is compared to provisional truth data independently classified from the same data source for constructing master truth data. The production data is compared to the master truth data for evaluating the quality with which the production data was classified.

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Номер записи: 4
02-02-2012 дата публикации

Method for quantifying amplitude of a response of a biological network

Номер: US20120030162A1
Автор: Dexter Roydon Pratt, Ty Matthew Thomson, William M. Ladd
Принадлежит: Selventa Inc

One or more measurement signatures are derived from a knowledge base of casual biological facts, where a signature is a collection of measured node entities and their expected directions of change with respect to a reference node. The knowledge base may be a directed network of experimentally-observed casual relationships among biological entities and processes, and a reference node represents a perturbation. A degree of activation of a signature is then assessed by scoring one or more “differential” data sets against the signature to compute an amplitude score. The amplitude score quantifies fold-changes of measurements in the signature. In one particular embodiment, the amplitude score is a weighted average of adjusted log-fold changes of measured node entities in the signature, wherein an adjustment applied to the log-fold changes is based on their expected direction of change. In an alternative embodiment, the amplitude score is based on quantity effects.

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Номер записи: 5
09-02-2012 дата публикации

Brain information output apparatus, robot, and brain information output method

Номер: US20120035765A1
Автор: Akihiro Toda, Kentaro Yamada, Masaaki Sato, Masahiro Kimura, Mitsuo Kawato, Okito Yamashita, Takahito Tamagawa, Tatsuya Okabe, Yusuke Takeda
Принадлежит: ATR Advanced Telecommunications Research Institute International, Honda Motor Co Ltd

A brain information output apparatus includes an intention determination information storage unit in which two or more pieces of intention determination information can be stored, with each intention determination information including a pair of an intention identifier, and a learning feature amount group including one or more feature amounts extracted from second learning data that is obtained by converting first learning data into intracerebral brain activity data, the first leaning data being acquired from the outside of the cranium of a user when the user performs a trial according to one intention; a first brain activity data acquiring unit that acquires first brain activity data from the outside of the cranium of a user; a second brain activity data acquiring unit that converts the first brain activity data to intracerebral brain activity data, and acquires second brain activity data; a feature amount group acquiring unit that acquires, from the second brain activity data, an input feature amount group including one or more feature amounts; an intention identifier acquiring unit that acquires an intention identifier corresponding to the input feature amount group based on the two or more pieces of intention determination information; and an intention identifier output unit that outputs the intention identifier.

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Номер записи: 6
01-03-2012 дата публикации

Method for classification of objects in a graph data stream

Номер: US20120054129A1
Автор: Charu Aggarwal
Принадлежит: International Business Machines Corp

A method for classifying objects in a graph data stream, including receiving a training stream of graph data, the training stream including a plurality of objects along with class labels that are associated with each of the objects, first determining discriminating sets of edges in the training stream for the class labels, wherein a discriminating set of edges is one that is indicative of the object that contains these edges having a given class label, receiving an incoming data stream of the graph data, wherein class labels have not yet been assigned to objects in the incoming data stream, second determining, based on the discriminating sets of edges, class labels that are associated with the objects in the incoming data stream; and outputting to an information repository object class label pairs based on the second determining.

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Номер записи: 7
01-03-2012 дата публикации

Traffic situation prediction apparatus

Номер: US20120054145A1
Автор: Takamitsu Suzuki
Принадлежит: Denso Corp

A traffic situation prediction apparatus for predicting a traffic situation based on a traffic situation statistical data is disclosed. The traffic situation prediction apparatus includes a map information storage and a controller. The apparatus determines, in response to an update of the map information, whether a specific factor affecting a traffic flow has emerged based on a difference between the map information before and after the update. The apparatus identifies an effect on the traffic flow resulting from emergence of the specific when the specific traffic flow effect factor has emerged. The apparatus predicts the traffic situation by incorporating the identified effect into the traffic situation predicted based on the traffic situation statistical data.

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Номер записи: 8
29-03-2012 дата публикации

Energy efficient heterogeneous systems

Номер: US20120079298A1
Автор: Abhinandan Majumdar, Srihari Cadambi, Srimat Chakradhar
Принадлежит: NEC Laboratories America Inc

Low-power systems and methods are disclosed for executing an application software on a general purpose processor and a plurality of accelerators with a runtime controller. The runtime controller splits a workload across the processor and the accelerators to minimize energy. The system includes building one or more performance models in an application-agnostic manner; and monitoring system performance in real-time and adjusting the workload splitting to minimize energy while conforming to a target quality of service (QoS).

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Номер записи: 9
19-04-2012 дата публикации

Activating Applications Based on Accelerometer Data

Номер: US20120096249A1
Автор: Andrew E. Rubin, David P. Conway
Принадлежит: Google LLC

In some implementations, a computer-implemented method includes storing a plurality of acceleration profiles in a mobile device; receiving accelerometer data from an accelerometer in the mobile device; correlating the accelerometer data with one accelerometer profile in the plurality of accelerometer profiles; and activating a user application of the mobile device that is associated with the correlated accelerometer profile. Each acceleration profile can correspond to a sequence of acceleration forces a mobile device would be subjected to when carried with a user during an activity that corresponds to the correlated acceleration profile.

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Номер записи: 10
26-04-2012 дата публикации

Topic models

Номер: US20120101965A1
Автор: David Stern, Philipp Hennig, Ralf Herbrich, Thore Graepel
Принадлежит: Microsoft Corp

Machine learning techniques may be used to train computing devices to understand a variety of documents (e.g., text files, web pages, articles, spreadsheets, etc.). Machine learning techniques may be used to address the issue that computing devices may lack the human intellect used to understand such documents, such as their semantic meaning. Accordingly, a topic model may be trained by sequentially processing documents and/or their features (e.g., document author, geographical location of author, creation date, social network information of author, and/or document metadata). Additionally, as provided herein, the topic model may be used to predict probabilities that words, features, documents, and/or document corpora, for example, are indicative of particular topics.

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Номер записи: 11
03-05-2012 дата публикации

Information processing apparatus, processing method therefor, and non-transitory computer-readable storage medium

Номер: US20120109861A1
Автор: Hiroto Yoshii
Принадлежит: Canon Inc

An information processing apparatus creates, for each of a plurality of nodes, a query to be executed for a learning pattern input to the node; inputs a plurality of learning patterns to a root node of the plurality of nodes; executes, for the learning pattern input to each node, the query created for the node; determines whether the query has been effectively executed for the individual learning pattern input to each node; distributes and inputs, to a lower node of each node, an individual learning pattern for which it has been determined in the determining that the query was effectively executed in the node; deletes a learning pattern for which it has been determined in the determining that the query was not effectively executed in each node; and stores an attribute of the learning pattern input to a terminal node of the plurality of nodes in association with the node.

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Номер записи: 12
10-05-2012 дата публикации

System and method for providing distributed intelligent assistance

Номер: US20120117005A1
Автор: Nova T. Spivack
Принадлежит: Individual

A system and a method for a service engine providing distributed intelligent assistance to a user are described herein. The method comprising steps of receiving and displaying a user inquiry from the user, the user inquiry having a linguistic pattern including a verb; generating and displaying a follow up question based on the user inquiry; receiving and displaying a follow up answer from the user; and generating and displaying a response based on the user inquiry and the follow up answer.

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Номер записи: 13
10-05-2012 дата публикации

Method and apparatus for building a user behavior model

Номер: US20120117006A1
Автор: Sailesh Kumar Sathish
Принадлежит: Nokia Oyj

An apparatus may include a monitoring module configured to monitor user interactions by a user with applications. A contextual characteristics determiner may determine one or more contextual characteristics relating to the user interactions, and the contextual characteristics may be categorized based on an ontology model. Thereby, a data model builder may build a user behavior model for the user based at least in part on the user interactions and the contextual characteristics. The apparatus may provide for private storage of the user behavior module. A recommendation module may issue a recommendation, which may be mapped to one of the applications, based at least in part on the user behavior model. The recommendation may be issued in response to a query from a query module. The query may include current contextual characteristics of the user and/or the apparatus.

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Номер записи: 14
24-05-2012 дата публикации

Controlling quarantining and biasing in cataclysms for optimization simulations

Номер: US20120130929A1
Автор: Jason F. Cantin
Принадлежит: International Business Machines Corp

Some embodiments are directed to generating a first probability value that represents a percentage of times that first bit values for a given bit position of a first plurality of candidate solutions equate to a pre-defined number, where the first plurality of candidate solutions has converged on a sub-optimal solution during a simulation of an optimization problem using an optimization algorithm. Some embodiments are further directed to generating a second probability value that is inversely biased from the first probability value; and generating a second plurality of candidate solutions with the second probability value, where the second plurality of candidate solutions are inversely biased from the first bit values for the given bit position.

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Номер записи: 15
07-06-2012 дата публикации

System and method for terrain analysis

Номер: US20120139325A1
Автор: Eric Nettleton, Hugh Durrant-Whyte, Johan Norberg, Paul Thompson
Принадлежит: UNIVERSITY OF SYDNEY

Described herein is a computerised method for identifying and classifying edges in a dataset representative of an open-pit mine terrain. The method includes the step of identifying one or more surfaces of the terrain having common topological attributes ( 306 ). Then, for each surface identified, edges of the identified surface are detected ( 308 ) and each of the detected edges are classified ( 316 ) as one of a toe, crest, or other than a crest or a toe. The method also includes the step of updating the dataset ( 208 ) with the edges classified as toes or crests.

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Номер записи: 16
14-06-2012 дата публикации

Systems and techniques for utilizing resource aware queues and/or service sharing in a multi-server environment

Номер: US20120151063A1
Автор: Manoj Cheenath, Ronald Yang, Vijayanth Devadhar
Принадлежит: Salesforce com Inc

Systems and techniques for utilizing resource aware queues and/or service sharing in a multi-server environment. Requests directed to an application server are received into one or more queues in front of the application server. An acknowledgement of the requests is provided in response to the requests being received by the one or more queues. Metadata associated with the requests is utilized to manage the one or more queues. The requests from the one or more queues are processed based on the metadata.

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Номер записи: 17
28-06-2012 дата публикации

Hierarchical classification system

Номер: US20120166366A1
Автор: Dengyong Zhou, Lin Xiao, Mingrui Wu
Принадлежит: Microsoft Corp

The claimed subject matter provides a method for hierarchical classification. The method includes receiving a hierarchical structure with a first level comprising a parent node and a sibling node. The structure also includes a second level comprising two child nodes. The method further includes receiving training examples. Each training example may be associated with a class of the parent node, the sibling node, or the two child nodes. The method also includes generating a first classifier for the first level. The first classifier includes a first hyperplane distinguishing the parent and sibling nodes. A first vector is normal to the first hyperplane. Additionally, the method includes generating a second classifier for the second level. The second classifier includes a second hyperplane distinguishing the two child nodes. A second vector is normal to the second hyperplane. An orthogonality of the second vector in relation to the first vector is maximized.

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Номер записи: 18
28-06-2012 дата публикации

System and Method for Classifying Data Streams with Very Large Cardinality

Номер: US20120166382A1
Автор: Charu C. Aggarwal, Philip S. Yu
Принадлежит: International Business Machines Corp

An object and attributes that describe that object are identified. The attributes are grouped into attribute patterns, and classification classes are identified. For each identified class a sketch table containing a plurality of parallel hash tables is created. For the object to be classified, each attribute pattern is processed using the all of the hash functions for each sketch table, resulting in a plurality of values under each sketch table for a single attribute pattern. The lowest value is selected for each sketch table. The distribution of values across all sketch tables is evaluated for each attribute pattern, producing a discriminatory power for each attribute pattern. Attribute patterns having a discriminatory power above a given threshold are selected and added to the associated sketch table values. The sketch table with the largest overall sum is identified, and the associated class is assigned to the object belonging to the attribute patterns.

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Номер записи: 19
19-07-2012 дата публикации

Tool performance by linking spectroscopic information with tool operational parameters and material measurement information

Номер: US20120185813A1
Автор: Kenji Sugishima, Sanjeev Kaushal, Sukesh Janubhai Patel
Принадлежит: Tokyo Electron Ltd

System(s) and method(s) are provided for adjustment and analysis of performance of a tool through integration of tool operational data and spectroscopic data related to the tool. Such integration results in consolidated data that enable, in part, learning at least one relationship amongst selected portions of the consolidated data. Learning is performed autonomously without human intervention. Adjustment of performance of the tool relies at least in part on a learned relationship and includes generation of process recipe parameter(s) that can adjust a manufacturing process in order to produce a satisfactory tool performance in response to implementation of the manufacturing process. A process recipe parameter can be generated by solving an inverse problem based on the learned relationship. Analysis of performance of the tool can include assessment of synthetic performance scenarios, identification of spectroscopic condition(s) that affect performance, and extraction of endpoints based at least on time dependence spectroscopic data.

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Номер записи: 20
09-08-2012 дата публикации

Systems and methods for generating missing rules matching a minimal set of objects

Номер: US20120203585A1
Автор: Ulrich M. Junker
Принадлежит: International Business Machines Corp

A method ( 1500 ) for generating a Generalized Missing Rule (GMR). The method involves receiving descriptions of First Scopes (FSs) that are admissible for a First Rule Project (FRP). FRP comprises first rules. Each FS is defined by at least one object characterizing a case. An Expanded Set of Scope Descriptions (ESSD) is generated by adding descriptions of Second Scopes (SSs) covered by FRP to the descriptions of FSs. An Implicit Description (ID) of FSs and SSs is produced. An Incomplete Most-General Scope (IMGS) is identified from FSs and SSs using ID. IMGS is a scope which is defined by a minimal set of objects, is admissible for FRP and covers at least one case which is not treated by a Second Rule Project (SRP). A Missing Case (MC) of IMGS is identified. MC is not treated by FRP. GMR is generated using MC and IMGS.

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Номер записи: 21
16-08-2012 дата публикации

Attention focusing model for nexting based on learning and reasoning

Номер: US20120209796A1
Автор: Akshay Vashist, Shoshana Loeb
Принадлежит: Telcordia Technologies Inc

A system and method for nexting is presented. The method comprises computing an expected event, observing a new event, when the expected event matches the new event, processing the new event and performing action in accordance with given concepts, when the expected event does not match the new event and the new event can be explained based on the given concepts, processing the new event and performing action in accordance with the given concepts, and when the expected event does not match the new event and the new event cannot be explained based on the given concepts, employing learning mechanism and performing action decided on by the learning mechanism. In one aspect, the method comprises generating new concepts using reasoning or learning. In one aspect, the method comprises converting sensed numerical data into events of interest via the application of learned functions operating on the numerical data.

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Номер записи: 22
16-08-2012 дата публикации

Autonomous biologically based learning tool

Номер: US20120209798A1
Автор: Kenji Sugishima, Sanjeev Kaushal, Sukesh Janubhai Patel
Принадлежит: Tokyo Electron Ltd

An autonomous biologically based learning tool system and a method that the tool system employs for learning and analysis are provided. The autonomous biologically based learning tool system includes (a) one or more tool systems that perform a set of specific tasks or processes and generate assets and data related to the assets that characterize the various processes and associated tool performance; (b) an interaction manager that receives and formats the data, and (c) an autonomous learning system based on biological principles of learning. The autonomous learning system comprises a memory platform and a processing platform that communicate through a network. Both the memory platform and the processing platform include functional components and memories that can be defined recursively. Knowledge generated and accumulated in the autonomous learning system(s) can be cast into semantic networks that can be employed for learning and driving tool goals based on context.

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Номер записи: 23
16-08-2012 дата публикации

Classification device and classification method

Номер: US20120209799A1
Автор: Hiroki Arimura, Iku Ohama, Takuya Kida, Toshihisa Abe
Принадлежит: Panasonic Corp

Provided is a classification device capable of classifying time series data of location information into groups in which continuity of time is secured. The classification device ( 100 ) includes a data storage unit ( 110 ) that stores time-of-day information and location information corresponding to the time-of-day information, a sorting unit ( 120 ) that sorts the location information in order of time using the time-of-day information, a hidden Markov model storage unit ( 130 ) storing therein a left-to-right hidden Markov model containing a plurality of states and in which a parameter is undetermined, a Markov model output unit ( 140 ) that determines the parameter by inputting the location information sorted in order of time into the hidden Markov model, and a classification unit ( 150 ) that classifies each location information in one of the plurality of states by inputting the location information sorted in order of time into the hidden Markov model containing the determined parameter.

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Номер записи: 24
30-08-2012 дата публикации

Measurement-only topological quantum computation

Номер: US20120221268A1
Автор: Chetan Nayak, Michael Freedman, Parsa Bonderson
Принадлежит: Microsoft Corp

Measurement-only topological quantum computation using both projective and interferometrical measurement of topological charge is described. Various issues that would arise when realizing it in fractional quantum Hall systems are discussed.

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Номер записи: 25
30-08-2012 дата публикации

Method for quantifying amplitude of a response of a biological network

Номер: US20120221506A1
Автор: Dexter Roydon Pratt, Ty Matthew Thomson, William M. Ladd
Принадлежит: Selventa Inc

One or more measurement signatures are derived from a knowledge base of casual biological facts, where a signature is a collection of measured node entities and their expected directions of change with respect to a reference node. The knowledge base may be a directed network of experimentally-observed casual relationships among biological entities and processes, and a reference node represents a perturbation. A degree of activation of a signature is then assessed by scoring one or more “differential” data sets against the signature to compute an amplitude score. The amplitude score quantifies fold-changes of measurements in the signature. In one particular embodiment, the amplitude score is a weighted average of adjusted log-fold changes of measured node entities in the signature, wherein an adjustment applied to the log-fold changes is based on their expected direction of change. In an alternative embodiment, the amplitude score is based on quantity effects.

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Номер записи: 26
27-09-2012 дата публикации

Contextually-Appropriate Task Reminders

Номер: US20120242482A1
Автор: Aaron Tinling, Arulkumar Elumalai, Eran Shtiegman, Steve Chang, Thomas Bouchard
Принадлежит: Microsoft Corp

A computing device learns over time how to identify task reminders that are most likely to be helpful to a user in different contexts. The task reminders can remind the user of activities that the user needs to do. The computing device displays a graphical user interface (GUI) that contains the task reminders identified as being most likely to be helpful to the user in the user's current context. The computing device updates the task reminders in the GUI as the user's context changes. In this way, the computing device can present task reminders that are likely to be currently helpful to the user while suppressing task reminders that are less likely to be helpful to the user at the current time.

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Номер записи: 27
27-09-2012 дата публикации

Biologically based chamber matching

Номер: US20120242667A1
Автор: Jessie Burger, Kenji Sugishima, Orion Wolfe, Robert Filman, Sanjeev Kaushal, Sukesh Janubhai Patel, Wolfgang Polak
Принадлежит: Tokyo Electron Ltd

The subject disclosure relates to automatically learning relationships among a plurality of manufacturing tool parameters as applied to arbitrary semiconductor manufacturing tools and a graphical user interface that is supported, at least in part, by an autonomous learning system. The graphical user interface can create one or more matrixes based on received data and can further generate additional matrices by transforming the one or more matrixes. A series of windows can be output, wherein the series of windows, provide performance analysis that comprises a matching between a focus chamber and a reference chamber. In an aspect, the focus chamber and the reference chamber can be different chambers. In another aspect, the focus chamber and the reference chamber can be the same chamber, which provides analysis of the deterioration in performance of the same chamber over time.

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Номер записи: 28
04-10-2012 дата публикации

Managing operations of a system

Номер: US20120254092A1
Автор: Denis Malov, Sricharan Poundarikapuram
Принадлежит: SAP SE

A computer-implemented method for managing operations of a system includes deriving a nonlinear modeling function from a nonlinear response function, defining an allowed range for output values of the nonlinear modeling function, determining a range of a first set of input values of the nonlinear modeling function based on the allowed range of the output values, deriving a nonlinear probability function from the nonlinear response function, receiving the first set of input values, calculating the output values by processing each input value in the first set of input values through the nonlinear modeling function, determining, using the probability function, a relative probability of performing a first future system operation for each input value of the first set of input values and displaying, for each input value in the first set of input values, the corresponding output value and the corresponding probability.

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Номер записи: 29
04-10-2012 дата публикации

Expertise Discovery Methods and Systems

Номер: US20120254095A1
Автор: Naomi Felina Moneypenny, Steven Dennis Flinn
Принадлежит: ManyWorlds Inc

A computer-implemented expertise discovery method and system generates recommendations of people in accordance with inferences of levels of expertise from behavioral information. The generation of the recommendations may be in accordance with comparisons of two or more expertise vectors and associated correlations between the vectors. The inferences of expertise may be with respect to specified topical neighborhoods. Explanations as to why recommendations were made are delivered to the recommendation recipients, and may include references to the inferred levels of expertise, the behavioral bases for the inferences, and/or the confidence in the inferences.

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Номер записи: 30
04-10-2012 дата публикации

Automated detection of deception in short and multilingual electronic messages

Номер: US20120254333A1
Автор: Koduvayur P. Subbalakshmi, Na Cheng, Peng Hao, Rajarathnam Chandramouli, Rohan Perera, Xiaoling Chen
Принадлежит: Stevens Institute of Technology

A method and apparatus for automatically identifying harmful electronic messages, such as those presented in emails, on Craigslist or on Twitter, Facebook and other social media websites, features methodology for discriminating unwanted garbage communications (spam) and unwanted deceptive messages (scam) from wanted, truthful communications based upon patterns discernable from samples of each type of electronic communication. Methods are proposed that enable discrimination of wanted from unwanted communications in short electronic messages, such as on Twitter and for multilingual application.

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Номер записи: 31
11-10-2012 дата публикации

Transfer of learning for query classification

Номер: US20120259801A1
Автор: Jun Yan, Lei Ji, Ning Liu, Zheng Chen
Принадлежит: Microsoft Corp

Transfer of learning trains a new domain for the classification of search queries according to different tasks, as well as the generation of a corresponding domain-specific query classifier that may be used to classify the search queries according to the different tasks in the new domain. The transfer of learning may include preparing a new domain to receive classification knowledge from one or more source domains by populating the new domain with preliminary query patterns extracted for a search engine log. The transfer of learning may further include preparing the classification knowledge in each source domain for transfer to the new domain. The classification knowledge in each source domain may then be transferred to the new domain.

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Номер записи: 32
11-10-2012 дата публикации

Active learning of record matching packages

Номер: US20120259802A1
Автор: Arvind Arasu, Michaela Götz, Shriraghav Kaushik
Принадлежит: Microsoft Corp

An active learning record matching system and method for producing a record matching package that is used to identify pairs of duplicate records. Embodiments of the system and method allow a precision threshold to be specified and then generate a learned record matching package having precision greater than this threshold and a recall close to the best possible recall. Embodiments of the system and method use a blocking technique to restrict the space of record matching packages considered and scale to large inputs. The learning method considers several record matching packages, estimates the precision and recall of the packages, and identifies the package with maximum recall having precision greater than equal to the given precision threshold. A human domain expert labels a sample of record pairs in the output of the package as matches or non-matches and this labeling is used to estimate the precision of the package.

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Номер записи: 33
25-10-2012 дата публикации

Method and apparatus for event detection permitting per event adjustment of false alarm rate

Номер: US20120271782A1
Автор: Chad Salisbury, Misty Blowers
Принадлежит: Individual

Method and apparatus for object or event of interest detection which minimizes the level of false alarms and maximizes the level of detections as defined on a per event or object basis by the analyst. The invention allows for the minimization of false alarms for objects or events of interest which have a close resemblance to all other objects or events mapped to the same multidimensional feature space, and allows for the per event or per object adjustment on false alarms for objects or events of higher interest.

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Номер записи: 34
08-11-2012 дата публикации

Predictive Analytical Modeling Accuracy Assessment

Номер: US20120284212A1
Автор: Gang Fu, Gideon S. Mann, Robert Kaplow, Travis Green, Wei-Hao Lin
Принадлежит: Google LLC

A system includes a computer(s) coupled to a data storage device(s) that stores a training function repository and a predictive model repository that includes includes updateable trained predictive models each associated with an accuracy score. A series of training data sets are received, being training samples each having output data that corresponds to input data. The training data is different from initial training data that was used with training functions from the repository to train the predictive models initially. Upon receiving a first training data set included in the series and for each predictive model in the repository, the input data in the first training set is used to generate predictive output data that is compared to the output data. Based on the comparison and previous comparisons determined from the initial training data and from previously received training data sets, an updated accuracy score for each predictive model is determined.

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Номер записи: 35
15-11-2012 дата публикации

Methods for predicting affective response from stimuli

Номер: US20120290514A1
Автор: Anat Thieberger Ben-Haim, Ari M. Frank, Gil Thieberger
Принадлежит: Affectivon Ltd

Creating a machine learning-based affective response predictor to predict a user's emotional state after being exposed to tokens representing stimuli that influence the user's affective state, comprising: receiving samples comprising temporal windows of token instances to which the user was exposed; the token instances are spread over a long period of time, and a subset of the token instances originate from same source and have overlapping instantiation periods; receiving target values, which represent affective response annotations of the user and correspond to the temporal windows of token instances; and creating the machine learning-based affective response predictor for the user, which compensates for non-linear effects resulting from the user being exposed to the subset of token instances originating from the same source and having overlapping instantiation periods, by running a machine learning training procedure on input data comprising the samples and the corresponding target values.

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Номер записи: 36
15-11-2012 дата публикации

Method and apparatus for associating micro-blogs with media programs

Номер: US20120291070A1
Автор: Bernard S. Renger, Hisao Chang, Junlan Feng, Luciano De Andrade Barbosa, Ovidiu Dan
Принадлежит: AT&T INTELLECTUAL PROPERTY I LP

A system that incorporates teachings of the present disclosure may operate, for example, according to a method for identifying subsets of blogs from a collection of blogs according to a relevance of each subset of blogs to one of a plurality of media programs deliverable to a plurality of subscriber devices, determining for each subset of blogs one or more trends, detecting a subscriber device from the plurality of subscriber devices, selecting a media program from the plurality of media programs, selecting one of the subsets of blogs that is relevant to the media program, and supplying the subscriber device the selected subset of blogs with the one or more trends determined for the select subset of blogs. Other embodiments are disclosed.

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Номер записи: 37
06-12-2012 дата публикации

Simulated Fermentation Process

Номер: US20120310413A1
Автор: David Bluck, Prahsant R. Karbhari, Wen-Jing Lin
Принадлежит: Invensys Systems Inc

A method of modeling a fermentation process comprises providing a first principles model of a fermentation process; determining the concentration of at least one substrate in a fermentation composition at a first time; and predicting the concentration of at least one component of the fermentation composition at a second time using the first principles model, wherein the second time is after the first time.

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Номер записи: 38
06-12-2012 дата публикации

Systems And Methods For Clustering Time Series Data Based On Forecast Distributions

Номер: US20120310939A1
Автор: David Rawlins Duling, Taiyeong Lee
Принадлежит: SAS Institute Inc

In accordance with the teachings described herein, systems and methods are provided for clustering time series based on forecast distributions. A method for clustering time series based on forecast distributions may include: receiving time series data relating to one or more aspects of a physical process; applying a forecasting model to the time series data to generate forecasted values and confidence intervals associated with the forecasted values, the confidence intervals being generated based on distribution information relating to the forecasted values; generating a distance matrix that identifies divergence in the forecasted values, the distance matrix being generated based the distribution information relating to the forecasted values; and performing a clustering operation on the plurality of forecasted values based on the distance matrix. The distance matrix may be generated using a symmetric Kullback-Leibler divergence algorithm.

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Номер записи: 39
13-12-2012 дата публикации

Systems, devices, and methods for parameter optimization

Номер: US20120317060A1
Автор: Tony Jebara
Принадлежит: Columbia University of New York

A computerized method for optimizing parameters is described. A system can initialize a group of parameters to respective values within a set of allowable models and bound a partition function across a number of variable pairs to generate a plurality of bounds. The system can also determine new values for the group of parameters that minimize a sum of the plurality of bounds. The system can set the group of parameters to the new values and optimize the parameters by iteratively performing the bounding, determining and setting. The system can stop optimizing when a termination condition is reached.

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Номер записи: 40
27-12-2012 дата публикации

Systems and methods for large-scale randomized optimization for problems with decomposable loss functions

Номер: US20120330867A1
Автор: John Sismanis, Peter Jay Haas, Rainer Gemulla
Принадлежит: International Business Machines Corp

Systems and methods directed toward processing optimization problems using loss functions, wherein a loss function is decomposed into at least one stratum loss function, a loss is decreased for each stratum loss function to a predefined stratum loss threshold individually using gradient descent, and the overall loss is decreased to a predefined threshold for the loss function by appropriately ordering the processing of the strata and spending appropriate processing time in each stratum. Other embodiments and aspects are also described herein.

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Номер записи: 41
24-01-2013 дата публикации

Supplementing a trained model using incremental data in making item recommendations

Номер: US20130024318A1
Автор: Biswadeep Nag, Jessi Dong, Qiong Zhang, Wei Du, Wei Yu
Принадлежит: Individual

Incremental training data is used to supplement a trained model to provide personalized recommendations for a user. The personalized recommendations can be made by taking into account the user's behavior, such as, without limitation, the user's short and long term web page interactions, to identify item recommendations. A trained model is generated from training data indicative of the web page interaction data collected from a plurality of users. Incremental training data indicative of other web page interaction data can be used to supplement the trained model, or in place of the trained model. Incremental training data can be indicative of user behavior collected more recently than the data used to train the model, for example.

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Номер записи: 42
31-01-2013 дата публикации

Method and system for computer question-answering

Номер: US20130029307A1
Автор: Lei Zhang, Yuan Ni, Zhao Ming Qiu
Принадлежит: International Business Machines Corp

A method and system for computer question-answering. The method includes: receiving a plurality of the questions to be trained, and obtaining a candidate answer set for each question; determining part of the questions to which the candidate answer sets include correct answers, and using first feature sets of the candidate; obtaining a first mathematical model, which is used to compute a first confidence degree that the candidate answer is a correct answer; computing first confidence degrees of the candidate answers of all the questions to be trained, and for each question, extracting a second feature set related to the first confidence degrees and the first feature set; and obtaining a second mathematic model, which is used to compute a second confidence degree that the candidate answer is a correct answer based on the second feature set.

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Номер записи: 43
31-01-2013 дата публикации

System and methodology providing automation security analysis and network intrusion protection in an industrial environment

Номер: US20130031037A1
Автор: Craig D. Anderson, David D. Brandt, George Bradford Collins, Kenwood Hall, Mark Burton Anderson
Принадлежит: Rockwell Automation Technologies Inc

The present invention relates to a system and methodology facilitating automation security in a networked-based industrial controller environment. Various components, systems and methodologies are provided to facilitate varying levels of automation security in accordance with security analysis tools, security validation tools and/or security learning systems. The security analysis tool receives abstract factory models or descriptions for input and generates an output that can include security guidelines, components, topologies, procedures, rules, policies, and the like for deployment in an automation security network. The validation tools are operative in the automation security network, wherein the tools perform security checking and/or auditing functions, for example, to determine if security components are in place and/or in suitable working order. The security learning system monitors/learns network traffic patterns during a learning phase, fires alarms or events based upon detected deviations from the learned patterns, and/or causes other automated actions to occur.

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Номер записи: 44
31-01-2013 дата публикации

Method and system for tracking objects

Номер: US20130031045A1
Автор: Michael Edward Samples, Michael Robert James
Принадлежит: Toyota Motor Engineering and Manufacturing North America Inc

An object tracking system and method operable to minimize processing time for tracking objects is provided. The system includes a pair of filters operable to make associations between dynamic objects newly detected and previously detected. One of the pair of filters makes an association when the predicted location of the previously detected objects is within a predetermined distance of the newly detected object. The other of the pair of filters makes an association based upon the probability that a newly detected dynamic object is a previously detected dynamic object. The remaining unassociated dynamic objects are then localized so as to form discrete matrices for optimization filters.

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Номер записи: 45
31-01-2013 дата публикации

Method and apparatus for predictive enrichment of search in an enterprise

Номер: US20130031081A1
Автор: Gangadharan KUMAR, Ravi Vijayaraghavan
Принадлежит: 24/7 Customer Inc

With regard to searches and, more particularly, to searches performed on information repositories belonging to an enterprise, a centralized management system is used by the enterprise to manage the predictive search experience for users. A system offers a rich resolution experience to the end users based on user intent as determined from a variety of mechanisms, such as keywords, end user journey, clustered journey, etc. Also disclosed herein is a system that derives and offers various suggestions to end users to help them accomplish their objectives.

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Номер записи: 46
31-01-2013 дата публикации

System and methods for adaptive model generation for detecting intrusion in computer systems

Номер: US20130031633A1
Автор: Andrew Honig, Andrew Howard, Eleazar Eskin, Salvatore J. Stolfo
Принадлежит: Columbia University of New York

A system and methods for detecting intrusions in the operation of a computer system comprises a sensor configured to gather information regarding the operation of the computer system, to format the information in a data record having a predetermined format, and to transmit the data in the predetermined data format. A data warehouse is configured to receive the data record from the sensor in the predetermined data format and to store the data in a SQL database. A detection model generator is configured to request data records from the data warehouse in the predetermined data format, to generate an intrusion detection model based on said data records, and to transmit the intrusion detection model to the data warehouse according to the predetermined data format. A detector is configured to receive a data record in the predetermined data format from the sensor and to classify the data record in real-time as one of normal operation and an attack based on said intrusion detection model. A data analysis engine is configured to request data records from the data warehouse according to the predetermined data format and to perform a data processing function on the data records.

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Номер записи: 47
07-02-2013 дата публикации

Denoising and Artifact Removal in Image Upscaling

Номер: US20130034311A1
Автор: Jen-Chan Chien, Jianchao Yang, Sarah A. Kong, Scott D. Cohen, Zhe Lin
Принадлежит: Adobe Systems Inc

Methods and systems for denoising and artifact removal in image upscaling are disclosed. In one embodiment, a low frequency band image intermediate is obtained from an input image. An upsampled image intermediate is obtained from the input image by upsampling. A result image is estimated, based at least in part on the upsampled image intermediate, the low frequency band image intermediate, and the input image. The input image is of a smaller scale than the result image. The estimating the result image further includes eliminating from the result image noise that is present in the input image.

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Номер записи: 48
07-02-2013 дата публикации

Method And Apparatus For A Predictive Tracking Device

Номер: US20130036080A1
Автор: Yana Kane-Esrig
Принадлежит: Alcatel Lucent USA Inc

A predictive tracking method and apparatus utilizing objective and subjective data in order to predict user states is provided herein. For example, some such embodiments may allow a user to track their mood or health symptoms in relation to retrieved data regarding their environmental in order to reveal patterns that can help forecast and proactively manage mood or health symptoms.

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Номер записи: 49
14-02-2013 дата публикации

Neural network frequency control

Номер: US20130041859A1
Автор: Jonh Esterlilne
Принадлежит: Greenray Industries Inc

Systems and methods for controlling frequency output of an electronic oscillator to compensate for effects of a parameter experienced by the oscillator incorporate artificial neural network processing functionality for generating correction signals. A neural network processing module includes one or more neurons which receive one or more inputs corresponding to a parameter of an electronic oscillator, such as temperature. Weights are calculated and applied to inputs to the neurons of the neural network as part of a training process, wherein the weights help shape the output of the neural network processing module. The neural network may include a linear summation module configured to provide an output signal that is at least partially based on outputs of the one or more neurons.

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Номер записи: 50
14-02-2013 дата публикации

Method and system for providing recommendations in a social network

Номер: US20130041862A1
Автор: Xiwang Yang, Yang Guo, Yong Liu
Принадлежит: Thomson Licensing SAS

A Bayesian Inference based recommendation system in a social network is provided. The method and system utilizes content ratings from a querying initiator's friends and their friends depending on the time to live (TTL) and other factors. Receiving users send to the querying initiator recommendation ratings from their friends and a conditional probability of distribution of the recommendation ratings given by the recommender's rooted at the friend. Once this information has been obtained from the friend/hopped friend network, the querying initiator's recommendation query engine constructs the QI's own rating response using the Bayesian Inference Network.

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Номер записи: 51
28-02-2013 дата публикации

Encoding of data for processing in a spatial and temporal memory system

Номер: US20130054495A1
Автор: Anosh Raj, II Ronald Marianetti, Jeffrey C. Hawkins
Принадлежит: Numenta Inc

A spatial and temporal memory system (STMS) processes input data to detect whether spatial patterns and/or temporal sequences of spatial patterns exist within the data, and to make predictions about future data. The data processed by the STMS may be retrieved from, for example, one or more database fields and is encoded into a distributed representation format using a coding scheme. The performance of the STMS in predicting future data is evaluated for the coding scheme used to process the data as performance data. The selection and prioritization of STMS experiments to perform may be based on the performance data for an experiment. The best fields, encodings, and time aggregations for generating predictions can be determined by an automated search and evaluation of multiple STMS systems.

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Номер записи: 52
28-02-2013 дата публикации

Automated search for detecting patterns and sequences in data using a spatial and temporal memory system

Номер: US20130054552A1
Автор: Anosh Raj, II Ronald Marianetti, Jeffrey C. Hawkins, Subutai Ahmad
Принадлежит: Numenta Inc

A spatial and temporal memory system (STMS) processes input data to detect whether spatial patterns and/or temporal sequences of spatial patterns exist within the data, and to make predictions about future data. The data processed by the STMS may be retrieved from, for example, one or more database fields and is encoded into a distributed representation format using a coding scheme. The performance of the STMS in predicting future data is evaluated for the coding scheme used to process the data as performance data. The selection and prioritization of STMS experiments to perform may be based on the performance data for an experiment. The best fields, encodings, and time aggregations for generating predictions can be determined by an automated search and evaluation of multiple STMS systems.

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Номер записи: 53
28-02-2013 дата публикации

Identifying events

Номер: US20130054746A1
Автор: John Reimer
Принадлежит: Individual

Events may be identified by storing information in response to activating an event stamp function. As a result of activating the event function, the information collected may immediately be compared to event information in a database. Alternatively, the information collected may later be compared to event information in a database. One or more candidates for the event of interest may be automatically or manually retrieved, and the user may decide whether a candidate event of the one or more candidates correspond to the event of interest. Alternatively, a purchase of an item related to the event may be automatically made in response to activating the event stamp.

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Номер записи: 54
28-03-2013 дата публикации

Engine catalyst diagnostics

Номер: US20130078725A1
Автор: Adam Banker, Imad Hassan Makki, James Michael Kerns, Michael James Uhrich, Pankaj Kumar, Stephen B. Smith
Принадлежит: FORD GLOBAL TECHNOLOGIES LLC

Embodiments for predicting catalyst function are disclosed. One example embodiment includes applying a set of parameter readings for a given sample to a support vector machine to generate a classification output, recording a plurality of classification outputs for a plurality of successive samples over a first duration, and indicating catalyst degradation if a threshold percentage of the classification outputs indicates degraded catalyst performance. In this way, catalyst degradation may be indicated using a simplified model that does not require extensive calibration.

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Номер записи: 55
28-03-2013 дата публикации

Method for Adaptively Building a Baseline Behavior Model

Номер: US20130080631A1
Автор: YeeJang James Lin
Принадлежит: YeeJang James Lin

A method for generating an auto-adaptive baseline model for profiling individual and collective behavior of a plurality of network users. The method comprises the steps of creating a model, defining a plurality of members and a plurality of collective variables, each member corresponding to a user, and including a plurality of individual variables, defining conditions for each collective variable and individual variable, upon detecting an activity by a user, updating corresponding individual variables and collective variables, and comparing updated individual variables and collective variables against corresponding conditions. If a condition is met, an alert event is issued to notify designated personnel; otherwise, returning to the step of upon detecting activity. Finally, upon receiving an alert event, the designated personnel decides whether to manually redefine the conditions or to ignore the alert event. If the alert event is ignored, said conditions are automatically redefined in accordance with system defined mechanisms.

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Номер записи: 56
11-04-2013 дата публикации

Probabilistic model checking of systems with ranged probabilities

Номер: US20130091080A1
Автор: Aarti Gupta, Franjo Ivancic, Khalil GHORBAL, Parasara Sridhar Duggirala, Vineet Kahlon
Принадлежит: NEC Laboratories America Inc

Systems and methods for model checking of live systems are shown that include learning an interval discrete-time Markov chain (IDTMC) model of a deployed system from system logs; and checking the IDTMC model with a processor to determine a probability of violating one or more probabilistic safety properties. Checking the IDTMC model includes calculating a linear part exactly using affine arithmetic; and over-approximating a non-linear part using interval arithmetic.

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Номер записи: 57
25-04-2013 дата публикации

Integrating sensing systems into thermostat housing in manners facilitating compact and visually pleasing physical characteristics thereof

Номер: US20130099124A1
Автор: Brian Huppi, Eric B. Daniels, John Benjamin Filson
Принадлежит: Nest Labs Inc

An occupancy sensing electronic thermostat is described that includes a thermostat body having a curved exterior front surface, a dot matrix display mounted within the body viewable by a user in front of the front surface, a passive infrared sensor for measuring infrared energy and a shaped Fresnel lens having a smooth outer surface that extends across only a portion of the exterior front surface of the thermostat body. The Fresnel lens is shaped and curved so as to conform to and form a part of the curved exterior front surface of the thermostat body. A second downwardly directed passive infrared sensor can also be provided to aid in the detection of an approaching user who intends to interact with the thermostat.

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Номер записи: 58
25-04-2013 дата публикации

Composite production rules

Номер: US20130103632A1
Автор: Hugues Citeau, Jean Louis Ardoint, Phillipe Bonnard
Принадлежит: International Business Machines Corp

A method for forming and using a composite production rule may include compiling, by a computer system, a decision table or a decision tree to generate a composite production rule. The method may also include generating the composite production rule and selecting, by the computer system, an algorithm for compiling the composite production rule. The method may additionally include compiling, by the computer system, the composite production rule into an executable program based on pattern matching of the selected algorithm. The method may further include executing, by the computer system, the composite production rule to provide an output based on the composite production rule.

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Номер записи: 59
02-05-2013 дата публикации

Short-term Load Forecast Using Support Vector Regression and Feature Learning

Номер: US20130110756A1
Автор: Amit Chakraborty, Fabian Moerchen, Kai Zhang
Принадлежит: Siemens Corp

In a support vector regression approach to forecasting power load in an electrical grid, a feature learning scheme weights each feature in the input data with its correlation with the predicted load, increasing the prediction accuracy. The kernel matrix for the input training data is computed such that features that align better with the target variable are given greater weight. The resulting load forecast may be used to compute commands sent to demand response modules.

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Номер записи: 60
09-05-2013 дата публикации

Method of identifying a protocol giving rise to a data flow

Номер: US20130117205A1
Автор: Mathieu Morel, Paul Gompel, Renaud Dubois
Принадлежит: Thales SA

Method of identifying a protocol at the origin of a data flow. The method of identifying a protocol giving rise to a packet flow comprises the following steps: a capture of the flow of the protocol to be identified, statistical classification of the flow, comprising an extraction of the classification parameters and a comparison of the classification parameters with statistical models constructed during a learning phase. The statistical classification comprises: a first phase of global statistical classification; and a step of synthesis of the results of the first and second classification phases so as to identify the protocol giving rise to the flow.

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Номер записи: 61
09-05-2013 дата публикации

Predictive Service for Third Party Application Developers

Номер: US20130117208A1
Автор: Juha K. Laurila, Nikolai Nefedov, Olivier Dousse, Taneli Mielikainen
Принадлежит: Nokia Oyj

Disclosed is an apparatus, method and computer program device which send a prediction request to a prediction service to construct a prediction result, receives a prediction result and an estimation of accuracy of the prediction result from the prediction service and configures an application to adapt to at least one of user preferences, behavior and habits based upon the prediction result and estimation of accuracy of the prediction result. The prediction service can include an over-the-air server which is coupled to a prediction server or a dedicated API residing on one or more user devices and configured to access a prediction server.

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Номер записи: 62
16-05-2013 дата публикации

Recommendations in a computing advice facility

Номер: US20130124449A1
Автор: Christopher Dixon, Matthew Ryan GATTIS, Thomas Pinckney
Принадлежит: eBay Inc

According to various embodiments, a ratings matrix including matrix values is generated, each row of the ratings matrix identifying one of a plurality of users, each column of the ratings matrix identifying one of a plurality of items, and each of the matrix values corresponding to a known affinity rating describing a degree of affinity associated with one of the users and one of the items. The ratings matrix may include a missing entry representing an unknown affinity rating. According to various embodiments, a revised ratings matrix is generated by factoring the ratings matrix into a user matrix and an item matrix, the revised ratings matrix being the product of the user matrix and the item matrix and including at least one entry representing a predicted affinity rating in place of the missing entry.

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Номер записи: 63
23-05-2013 дата публикации

System and method for crowd-sourced data labeling

Номер: US20130132080A1
Автор: Barbara B. Hollister, Ilya Dan MELAMED, Jason Williams, Tirso Alonso
Принадлежит: AT&T INTELLECTUAL PROPERTY I LP

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for crowd-sourced data labeling. The system requests a respective response from each of a set of entities. The set of entities includes crowd workers. Next, the system incrementally receives a number of responses from the set of entities until at least one of an accuracy threshold is reached and m responses are received, wherein the accuracy threshold is based on characteristics of the number of responses. Finally, the system generates an output response based on the number of responses.

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Номер записи: 64
13-06-2013 дата публикации

Adaptive pattern recognition based controller apparatus and method and human-interface therefore

Номер: US20130147598A1
Автор: Linda I. Hoffberg-Borghesani, Steven M. Hoffberg
Принадлежит: Individual

A system and method of predicting items likely to appeal to a user, based on data received from a remote site. One or more local systems are provided, along with a remote system, said local systems communicating with said remote system over a network connection. Each local system maintains a set of characterized items. A local processor predicts an appeal of an item to a user based on the comparison with the set of characterized items with, e.g., user preferences. The user may interact through graphical user interface. At least one user-preference predictive algorithm may be employed to present items predicted to appeal to the user.

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Номер записи: 65
13-06-2013 дата публикации

Reduction Of Classification Error Rates And Monitoring System Using An Artificial Class

Номер: US20130151166A1
Автор: David Snyder
Принадлежит: Neurovista Corp

Systems and methods for enhancing the accuracy of classifying a measurement by providing an artificial class. Seizure prediction systems may employ a classification system including an artificial class and a user interface for signaling uncertainty in classification when a measurement is classified in the artificial class.

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Номер записи: 66
13-06-2013 дата публикации

Recommender engine for collections treatment selection

Номер: US20130151383A1
Автор: Gregory Gancarz, Jenny Zhang, Kathleen Marie Crowe
Принадлежит: Opera Solutions LLC

A system for automatically recommending treatments for delinquent accounts in collections is provided. The system includes one or more sub-models for analyzing and scoring delinquent accounts and comparing them to historical accounts to identify similar historical accounts. The system can select and recommend one or more treatments for the delinquent account based on treatments for the historical accounts that may have previously provided a favorable outcome for a similar account. The system may test the efficacy of new treatments and incorporate the results into the memory, thereby learning and adapting to new treatments and account behavior.

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Номер записи: 67
13-06-2013 дата публикации

Weather comfort forecasting for riders of motorcycles and other exposed-rider vehicles

Номер: US20130151454A1
Автор: Wil McCarthy
Принадлежит: Individual

A method for predicting and reporting rider comfort on exposed-rider vehicles uses weather report data and riding speeds to calculate an effective temperature. Personal preferences may also be set and considered to provide predictive information and recommendations particular to sensibilities of individual riders. This method may be used as an aid to planning ride times, durations, and wardrobe choices as a function of time of day and planned riding speeds.

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Номер записи: 68
20-06-2013 дата публикации

Method for identifying and ranking news sources

Номер: US20130159295A1
Автор: John Nicholas Gross
Принадлежит: Individual

A search engine and/or news aggregator considers events and stories described in electronic documents, a location of a searcher/reviewer, and a situs associated with content of the document to determine how/if they should be presented to users.

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Номер записи: 69
20-06-2013 дата публикации

Action-oriented user experience based on prediction of user response actions to received data

Номер: US20130159408A1
Автор: Fernando Garcia, James Edelen, John Winn, Tore Sundelin
Принадлежит: Microsoft Corp

A system is provided for automatically notifying a user of predicted action. The system may be configured to monitor and observe a user's interactions with incoming data, identify patterns of actions the user may take in response to the incoming data and generate a notification associated with the action. A trainer component and a classifier component determine the probability a user may take a particular action and to make predictions of likely user actions based on the observations of the user. A notifier may communicate with the classifier to generate a particular user notification associated with a user action response generated by the classifier. The notifier component utilizes a logic device to compare the received user prediction from the classifier with a plurality of user notifications stored in a database. The notifier component sends the user notification to one or more user devices associated with a user.

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Номер записи: 70
27-06-2013 дата публикации

Making estimations or predictions about databases based on data trends

Номер: US20130166486A1
Автор: Sung Jin Kim
Принадлежит: Teradata Corp

Data trends that are based on historical data of a database can be used to make estimations and/or predications about the database. In other words, historical trends of a database can be used to make estimation about the data of the database. By way of example, a prediction can be made regarding the data change in the data since the Statistics has been collected. An estimation about data in a database can be used instead of actual data that would have to be collected as Statistics for the database. As a result, Statistics can be collected less frequently but estimation and/or predictions about the database can be used to optimize the execution of queries of the database. Also, collection of Statistics for database can be altered by using estimation about the Statistics of the database by collecting Statistics less frequently or for longer periods of time.

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Номер записи: 71
27-06-2013 дата публикации

Methods and systems for selecting and presenting content based on a comparison of preference signatures from multiple users

Номер: US20130167169A1
Автор: Ajit Rajasekharan, Kajamalai G. Ramakrishnan, Murali Aravamudan
Принадлежит: Veveo LLC

A method of selecting and presenting content based on a comparison of preference signature from multiple users is provided. The method includes providing a set of content items having associated descriptive terms and receiving search input from users. The method includes presenting a subset of content items, receiving content selection actions, and learning users' preferences, wherein the preferences are weighted based on content items usage so that the user preferences are specified as a set of descriptive terms and associated weights. The method includes identifying users with similar preferences by comparing sets of learned user preferences and presenting content items to at least one user of the plurality of users by identifying for presentation content items selected by users identified as having learned user preferences that are similar to the learned user preferences of said at least one user.

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Номер записи: 72
04-07-2013 дата публикации

Automated And Intelligent Structure Design Generation And Exploration

Номер: US20130173223A1
Автор: Augusto Roman, Bradley Schumitsch, Eric Teller, Jennifer Carlile, Nicholas Chim
Принадлежит: Google LLC

Computational systems and methods are disclosed that learn about and assist with appropriate structure-based design choices. The systems and methods autonomously explore design states, and suggest to a user one or more optimize design states. Constraints are provided to limit exploration to valid design states. Systems and methods are disclosed that assist groups of users with coordinating their efforts in producing a cohesive design. Systems and methods are disclosed for learning from past optimizations in order to provide more rapid convergence on an optimized design, avoid local maxima and other hurdles to optimization, avoid undesired optimizations, and so on.

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Номер записи: 73
11-07-2013 дата публикации

Method for closed-loop controlling a laser processing operation and laser material processing head using the same

Номер: US20130178952A1
Автор: Ingo Stork Genannt Wersborg, Thibault BAUTZE
Принадлежит: Precitec Itm Gmbh, Precitec KG

The present invention relates to a method for closed-loop controlling a processing operation of a workpiece, comprising the steps of: (a) recording a pixel image at an initial time point of an interaction zone by means of a camera, wherein the workpiece is processed using an actuator having an initial actuator value; (b) converting the pixel image into a pixel vector; (c) representing the pixel vector by a sum of predetermined pixel mappings each multiplied by a corresponding feature value; (d) classifying the set of feature values on the basis of learned feature values into at least two classes of a group of classes comprising a first class of a too high actuator value, a second class of a sufficient actuator value and a third class of a too low actuator value at the initial time point; (e) performing a control step for adapting the actuator value by minimizing the error e t between a quality indicator y e and a desired value; and (f) repeating the steps (a) to (e) for further time points to perform a closed-loop controlled processing operation.

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Номер записи: 74
11-07-2013 дата публикации

Systems, methods, and media for generating sanitized data, sanitizing anomaly detection models, and/or generating sanitized anomaly detection models

Номер: US20130179968A1
Автор: Angelos D. Keromytis, Angelos Stavrou, Gabriela F. Ciocarlie, Salvatore J. Stolfo
Принадлежит: The Trustees of Columbia University in the City of New York

Systems, methods, and media for generating sanitized data, sanitizing anomaly detection models, and generating anomaly detection models are provided. In some embodiments, methods for sanitizing anomaly detection models are provided. The methods including: receiving at least one abnormal anomaly detection model from at least one remote location; comparing at least one of the at least one abnormal anomaly detection model to a local normal detection model to produce a common set of features common to both the at least one abnormal anomaly detection model and the local normal detection model; and generating a sanitized normal anomaly detection model by removing the common set of features from the local normal detection model.

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Номер записи: 75
08-08-2013 дата публикации

Fault Prediction of Monitored Assets

Номер: US20130204808A1
Автор: Eric Gebhardt, Michael Bernard, Steven Hartman, Xiaomo Jiang
Принадлежит: General Electric Co

Systems and methods for fault prediction are described to reduce equipment failure by effectively monitoring equipment, removing anomalous data, and reducing false alarms. Such systems and methods can be used to receive monitoring data, extract information from the data, and combine extracted information for establishing prediction models. Additionally, fault probabilities may be quantified and faults may be predicted based on the probabilities.

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Номер записи: 76
08-08-2013 дата публикации

Discriminant model learning device, method and program

Номер: US20130204810A1
Автор: Ryohei Fujimaki, Satoshi Morinaga, Yoshinobu Kawahara
Принадлежит: NEC Corp

To provide a discriminant model learning device capable of efficiently learning a discriminant model on which domain knowledge indicating user's knowledge or analysis intention for a model is reflected while keeping fitting to data. A query candidate storage means 81 stores candidates of a query as a model to be given with domain knowledge indicating a user's intention. A regularization function generation means 82 generates a regularization function indicating compatibility with domain knowledge based on the domain knowledge to be given to the query candidates. A model learning means 83 learns a discriminant model by optimizing a function defined by a loss function and the regularization function predefined per discriminant model.

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Номер записи: 77
08-08-2013 дата публикации

Self-learning, context aware virtual assistants, systems and methods

Номер: US20130204813A1
Автор: Demitrios Leo Master, Farzad Ehsani, Silke Maren Witt-Ehsani
Принадлежит: Fluential LLC

A virtual assistant learning system is presented. A monitoring device, a cell phone for example, observes user interactions with an environment by acquiring sensor data. The monitoring device uses the sensor data to identify the interactions, which in turn is provided to an inference engine. The inference engine leverages the interaction data and previously stored knowledge elements about the user to determine if the interaction exhibits one or more user preferences. The inference engine can use the preferences and interactions to construct queries targeting search engines to seek out possible future interactions that might be of interest to the user.

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Номер записи: 78
29-08-2013 дата публикации

Adapting the Operation of an Appliance

Номер: US20130226849A1
Автор: Fano Ramparany, Jérémie Gadeyne, Philippe Beaune, Yazid Benazzouz
Принадлежит: France Telecom SA

A method for adapting the operation of an apparatus connected to a network deployed in an environment, including the steps of: collecting data relating to the environment from a plurality of sources; identifying usual environmental situations from an analysis of the collected data; detecting a deviation from at least one identified usual situation; and sending a control to the apparatus for adapting the operation thereof to the detected deviation.

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Номер записи: 79
29-08-2013 дата публикации

Context-based Search Query Formation

Номер: US20130226935A1
Автор: Jian-Tao Sun, Peng Bai, Xiaochuan Ni, Xuedong David Huang, Zheng Chen, Zhimin Zhang
Принадлежит: Microsoft Corp

Searching is assisted by recognizing a selection of text from a document as an indication that a user wishes to initiate a search based on the selected text. The user is provided with query suggestions based on the selected text and the query suggestions are ranked based on a context provided by the document. The user may select the text by using a mouse, drawing a circle around the text on a touch screen, or by other input techniques. The query suggestions may be based on query reformulation or query expansion techniques applied to the selected text. Context provided by the document is used by a language model and/or an artificial intelligence system to rank the query suggestions in predicted order of relevance based on the selected text and the context.

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Номер записи: 80
05-09-2013 дата публикации

Dynamic phase machine automation of oil & gas processes

Номер: US20130231787A1
Автор: Clinton D. Chapman, Han Yu, Hector Arismendi Sanchez, Jacques Bourque, Jan Morley, Jose Luis Sanchez Flores, Mochammad Faisal Wingky
Принадлежит: Schlumberger Technology Corp

A method, apparatus, and program product facilitate the automation of an oil & gas process, e.g., a drilling process, through the use of a dynamic phase machine incorporating multiple autonomous agents.

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Номер записи: 81
12-09-2013 дата публикации

Machine learning methods and systems for identifying patterns in data

Номер: US20130238533A1
Автор: Hemant VIRKAR, Jacob Borgman, Karen Stark
Принадлежит: DIGITAL INFUZION Inc

Methods for training machines to categorize data, and/or recognize patterns in data, and machines and systems so trained. More specifically, variations of the invention relates to methods for training machines that include providing one or more training data samples encompassing one or more data classes, identifying patterns in the one or more training data samples, providing one or more data samples representing one or more unknown classes of data, identifying patterns in the one or more of the data samples of unknown class(es), and predicting one or more classes to which the data samples of unknown class(es) belong by comparing patterns identified in said one or more data samples of unknown class with patterns identified in said one or more training data samples. Also provided are tools, systems, and devices, such as support vector machines (SVMs) and other methods and features, software implementing the methods and features, and computers or other processing devices incorporating and/or running the software, where the methods and features, software, and processors utilize specialized methods to analyze data.

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Номер записи: 82
12-09-2013 дата публикации

Sensor detection device, corresponding detection method and computer program

Номер: US20130238543A1
Автор: Pierre Jallon
Принадлежит: Commissariat a lEnergie Atomique et aux Energies Alternatives CEA

A device detecting at least one scenario from predetermined scenarios wherein a physical system observed by at least one sensor is likely to be found, including: at least one sensor providing a physical system observation data sequence; a storage storing at least one statistical model associating possible observation data values with the predetermined scenarios; a computer programmed to select at least one of the scenarios based on the observation data sequence and at least one statistical model. The storage includes plural statistical models broken down into plural ordered levels between an input level, wherein each statistical model associates possible values of at least a portion of the observation data with intermediate states for the statistical model, and an output level, wherein each statistical model associating possible values of at least a portion of the intermediate states of a lower level with at least a portion of the predetermined scenarios.

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Номер записи: 83
19-09-2013 дата публикации

System and method for concurrently conducting cause-and-effect experiments on content effectiveness and adjusting content distribution to optimize business objectives

Номер: US20130246162A1
Автор: Brian E. Brooks, Brian J. Stankiewicz, Brian L. Linzie, Craig G. Markell, Jonathan B. Arthur
Принадлежит: 3M Innovative Properties Co

The present invention is directed to systems, articles, and computer-implemented methods for assessing effectiveness of communication content and optimizing content distribution to enhance business objectives. Embodiments of the present invention are directed to computer-implemented methods for a computer-implemented method, comprising conducting an experiment using experimental content to determine effectiveness of communication content and executing, while conducting the experiment, a machine learning routine (MLR) using MLR content to enhance an effectiveness metric.

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Номер записи: 84
19-09-2013 дата публикации

Methods and systems for selecting and presenting content based on dynamically identifying microgenres associated with the content

Номер: US20130246408A1
Автор: Ajit Rajasekharan, Kajamalai G. Ramakrishnan, Murali Aravamudan
Принадлежит: Veveo LLC

A method of selecting and presenting content based on learned user preferences is provided. The method includes providing a content system including a set of content items organized by genre characterizing the content items, and wherein the set of content items contains microgenre metadata further characterizing the content items. The method also includes receiving search input from the user for identifying desired content items and, in response, presenting a subset of content items to the user. The method further includes receiving content item selection actions from the user and analyzing the microgenre metadata within the selected content items to learn the preferred microgenres of the user. The method includes, in response to receiving subsequent user search input, selecting and presenting content items in an order that portrays as relatively more relevant those content items containing microgenre metadata that more closely match the learned microgenre preferences of the user.

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Номер записи: 85
10-10-2013 дата публикации

Methods and systems for computer-based selection of identifying input for class differentiation

Номер: US20130268465A1
Автор: Robert K. McConnell
Принадлежит: Individual

In systems and methods for computer-based selection of identifying input for differentiating classes, training regions (each of which is associated with a defined class) are specified in a training space that is organized by data bands according to selected definitions. Windows are defined in training elements associated with data locations in the training regions. Multiple training windows are defined in the training elements in a known band in the training data. Relevance measures for training windows represent an extent of likelihood of correctly identifying class for a test location based on data band, window position within the training element, and the frequency of occurrence of data symbols in training windows at the window position. The window having the highest value relevance measure is selected as the most relevant window. Multiple most relevant windows, together with their parameters, are selected as identifying input to facilitate class differentiation in test spaces.

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Номер записи: 86
17-10-2013 дата публикации

Comprehensive Glaucoma Determination Method Utilizing Glaucoma Diagnosis Chip And Deformed Proteomics Cluster Analysis

Номер: US20130275349A1
Автор: Katsumi Yagi, Kazuhiko Mori, Kei Tashiro, Kengo YOSHII, Masahiro Fuwa, Masakazu Nakano, Morio Ueno, Shigeru Kinoshita, Tomohito Yagi, Yoko Ikeda, Yuichi Tokuda
Принадлежит: Santen Pharmaceutical Co Ltd

Provided is a technique for determining a physiological attribute in a mammal, including the onset or progression of human glaucoma, with high accuracy. The results of the determination of genotype date and the results of the determination of cytokine date are consolidated by a consolidated determination unit ( 114 ); comparison is made for determining as to which is larger, the number of Case determination procedures or the number of control determination procedures (S 330 ); and it is determined as Case (glaucoma) when the number of Case determination procedures is larger and it is determined as Control (normal person) when the number of Control determination procedures is larger.

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Номер записи: 87
17-10-2013 дата публикации

Methods and systems for identifying patients with mild congnitive impairment at risk of converting to alzheimer's

Номер: US20130275350A1
Автор: Caitlyn Marie CHIOFOLO, James David Schaffer
Принадлежит: Koninklijke Philips NV

Methods and systems for selecting a cohort group or a patient at risk from a population of patients with mild cognitive impairment. The methods include using a computer configured to perform the steps: receiving normalized learning data from a portion of the population of patients; tuning a set of decision trees on the normalized learning data; receiving patient data from one or more patients of the population, wherein the patient data is independent from the learning data; classifying the patient data with the tuned set of decision trees to obtain patient threshold values; and displaying the patient threshold values.

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Номер записи: 88
17-10-2013 дата публикации

Controlling quarantining and biasing in cataclysms for optimization simulations

Номер: US20130275351A1
Автор: Jason F. Cantin
Принадлежит: International Business Machines Corp

Some examples are directed to determining a frequency of occurrence of a first value in a component of a first plurality of candidate solutions for an optimization problem where the first plurality of candidate solutions has converged on a sub-optimal solution during a computer simulation that tests fitness of the first plurality of candidate solutions. Some examples are further directed to determining a second value that is inversely biased from the frequency of occurrence of the first value. Some examples are further directed to including the second value in a component of at least a portion of a second plurality of candidate solutions, where the component of the at least the portion of the second plurality of candidate solutions corresponds to the component of the first plurality of candidate solutions.

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Номер записи: 89
24-10-2013 дата публикации

Method and Apparatus for Performing Dynamic Textual Complexity Analysis Using Machine Learning Artificial Intelligence

Номер: US20130282628A1
Автор: Benjamin Bengfort, Katie Palencsar, William Voorhees
Принадлежит: Unbound Concepts Inc

A data processing system including one or more client devices, wherein each client device is connected to a network system and a data center unit. The data center unit includes a network interface unit, a user interface, one or more storage devices, wherein the one or more storage devices comprise one or more databases. Further, the data center unit includes a storage device controller and database manager for controlling the operation of storage devices and databases, a web server for providing web services to clients, a database server for providing database services to the one or more clients and a machine learning artificial intelligence application server for predicting textual complexity of data. The machine learning artificial intelligence application server includes one or more databases for storing data used to refine textual complexity analysis for improved accuracy of textual complexity predictions.

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Номер записи: 90
31-10-2013 дата публикации

Gripping-feature learning authentication system and gripping-feature learning authentication method

Номер: US20130290229A1
Автор: Manabu Ota, Masakatsu Tsukamoto, Takeshi Higuchi, Yasuo Morinaga
Принадлежит: NTT DOCOMO INC

A gripping-feature learning authentication system preventing impersonation. A mobile information terminal includes a trigger monitor outputting a gripping-feature acquisition signal, a gripping-feature sample acquisition part acquiring a gripping-feature sample, a template learning part learning a user authentication template, a template sending part sending the user authentication template, an authentication request part sending and receiving an authentication request, an authentication data sending part sending a terminal identification number or gripping-feature sample, and a determination result receiver receiving a determination result. A server includes a template receiver receiving a user authentication template, a member template storage storing a user authentication template and member information, an authentication data receiver receiving a terminal identification number and gripping-feature sample, a member authenticator determining probability users corresponding to terminal identification numbers and gripping-feature samples belong to same member group, and a determination result sending part sending a determination result.

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Номер записи: 91
31-10-2013 дата публикации

Identifying news events that cause a shift in sentiment

Номер: US20130290232A1
Автор: Maria G. Castellanos, Meichun Hsu, Mikalai Tsytsarau, Themis Palpanas, Umeshwar Dayal
Принадлежит: Hewlett Packard Development Co LP

A method identifies news events that cause shifts in sentiments. The method includes compiling a sentiment time series, the sentiment time series expressing a shift in sentiment; compiling a news events time series; correlating the sentiment and news events time series; identifying from the correlation news events that caused a shift in sentiment and predicting if a selected news event may cause a shift in sentiment in the future.

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Номер записи: 92
31-10-2013 дата публикации

Method and Device for Program Identification Based on Machine Learning

Номер: US20130291111A1
Автор: Hongyi Zhou, Hui Zhou, YI Dong
Принадлежит: Beijing Qihoo Technology Co Ltd

The invention discloses a method and device for programidentification based on machine learning. The method comprises: analyzing an inputted unknown program, and extracting a feature of the unknown program; coarsely classifying the unknown program according to the extracted feature; judging by inputting the unknown program into a corresponding decision-making machine generated by training according to a result of the coarse classification; and outputting an identification result of the unknown program, wherein the identification result is a malicious program or a non-malicious program. The embodiments of the invention adopt the machine learning technology, achieve the decision-making machine for identifying a malicious program by analyzing a large number of program samples, and can save a lot of manpower and improve the identification efficiency for a malicious program by using the decision-making machine; and furthermore, can find an inherent law of programs based on data mining for massive programs, prevent a malicious program that has not happened and make it difficult for a malicious program to avoid killing.

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Номер записи: 93
14-11-2013 дата публикации

On-device real-time behavior analyzer

Номер: US20130304676A1
Автор: Anil GATHALA, Rajarshi Gupta, Vinay Sridhara, Xuetao WEI
Принадлежит: Qualcomm Inc

Methods, systems and devices for generating data models in a communication system may include applying machine learning techniques to generate a first family of classifier models using a boosted decision tree to describe a corpus of behavior vectors. Such behavior vectors may be used to compute a weight value for one or more nodes of the boosted decision tree. Classifier models factors having a high probably of determining whether a mobile device behavior is benign or not benign based on the computed weight values may be identified. Computing weight values for boosted decision tree nodes may include computing an exclusive answer ratio for generated boosted decision tree nodes. The identified factors may be applied to the corpus of behavior vectors to generate a second family of classifier models identifying fewer factors and data points relevant for enabling the mobile device to determine whether a behavior is benign or not benign.

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Номер записи: 94
21-11-2013 дата публикации

Determining and Predicting Popularity of Content

Номер: US20130311408A1
Автор: Amit Bagga, Jan Neumann, Scot Zola, Xiaodong Yu
Принадлежит: COMCAST CABLE COMMUNICATIONS LLC

Processes and systems are described herein that may be used to predict which content (e.g., programs, series, movies, channels etc.) will be popular in the future. The processes and systems may use a model that is trained using historical data reflecting information about past showings of programs, such as rating information, viewer behaviors (e.g., channel changes and DVR recordings), online social activity (e.g., Facebook likes and relevant Twitter messages), and/or other data. Accordingly, it may be possible to provide predictive recommendations of popular content before, for example, the content is scheduled or otherwise planned to be distributed or made available to viewers. The results of such prediction may be integrated with, for example, a program guide available to viewers.

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Номер записи: 95
05-12-2013 дата публикации

Methods and apparatus for performing transformation techniques for data clustering and/or classification

Номер: US20130325759A1
Автор: Bhuvana Ramabhadran, Dimitri Kanevsky, Leonid Rachevsky
Принадлежит: Nuance Communications Inc

Some aspects include transforming data for which at least one constraint has been specified on a portion of the data, the at least one constraint relating to a similarity and/or dissimilarity of at least some of the portion of the data. Techniques comprise determining a first transformation that approximates the at least one constraint using a cosine similarity as a measure of the similarity and/or dissimilarity of the at least a portion of the data, applying at least the first transformation to the data to obtain transformed data, and fitting a plurality of clusters to the transformed data to obtain a plurality of established clusters. Some aspects include classifying input data by transforming the input data using at least the first transformation and comparing the transformed input data to the established clusters.

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Номер записи: 96
19-12-2013 дата публикации

Occupancy detection for managed lane enforcement based on localization and classification of windshield images

Номер: US20130336538A1
Автор: Beilei Xu, Craig Saunders, Florent Perronnin, Peter Paul, Sandra Skaff
Принадлежит: Xerox Corp

A system for detecting a vehicle occupancy violation includes an image capture module that acquires an image including a vehicle cabin from a camera positioned to view oncoming traffic. The system includes a violation determination device, which includes a feature extraction module that processes the image pixels for determining an image descriptor. The process is selected from a group consisting of a Successive Mean Quantization Transform; a Scale-Invariant Feature Transform; a Histogram of Gradients; a Bag-of-Visual-Words Representation; a Fisher Vector Representation; and, a combination of the above. The system further includes a classifier that determines a distance that the vehicle image descriptor/representation is positioned in the projected feature space relative to a hyper-plane. The classifier determines whether the distance meets a threshold and classifies the image when the threshold is met. A processor implements the modules. A graphic user interface outputs the classification.

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Номер записи: 97
26-12-2013 дата публикации

Assessing accuracy of trained predictive models

Номер: US20130346351A1
Автор: Gang Fu, Gideon S. Mann, Robert Kaplow, Travis H. K. Green, Wei-Hao Lin
Принадлежит: Google LLC

A system includes a computer(s) coupled to a data storage device(s) that stores a training data repository and a predictive model repository. The training data repository includes retained data samples from initial training data and from previously received data sets. The predictive model repository includes at least one updateable trained predictive model that was trained with the initial training data and retrained with the previously received data sets. A new data set is received. A richness score is assigned to each of the data samples in the set and to the retained data samples that indicates how information rich a data sample is for determining accuracy of the trained predictive model. A set of test data is selected based on ranking by richness score the retained data samples and the new data set. The trained predictive model is accuracy tested using the test data and an accuracy score determined.

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Номер записи: 98
02-01-2014 дата публикации

Method and system for robot understanding, knowledge, conversation, volition, planning, and actuation

Номер: US20140006320A1
Автор: Michael S. P. Miller, Sheldon O. Linker, Toni M. Poper
Принадлежит: LINKER SYSTEMS Inc

A system for understanding and storing knowledge and plans in a speakable, formal class of languages, allowing querying and retrieving of that knowledge and plan (conversation), and of deciding and acting (volition) upon such plans is provided. The system further allows the users to input data, instructions, questions, queries, imperatives, and plans without structure or rules over and above the actual grammar of the class of languages. The system responds in words, phrases, complete sentences, or actions, as applicable, and its output is bound by the rules of logic, rather than correlation or likely meaning.

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Номер записи: 99
02-01-2014 дата публикации

Extensible adaptive classification framework

Номер: US20140006323A1
Автор: Alex Nugent
Принадлежит: Knowmtech LLC

An extensible adaptive classification framework and method can include multiple feature detection modules, and a platform for integrating the multiple feature detection modules utilizing a plurality of AHaH nodes as adaptive classifiers over a feature space of multiple and extensible feature factory modules, thereby configuring the platform as an extensible and continuously adaptive pattern recognition platform.

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Номер записи: 100