Abstract: Disclosed is a flame-retardant composition comprising (i) 40-66 wt. % alkenyl aromatic resin, (ii) 9-33 wt. % ammonium polyphosphate and (iii) 14-40 wt. % cellulosic material, wherein all weights are based on the total weight of the composition and wherein ammonium polyphosphate and cellulosic material are present in a weight % ratio effective to provide molded articles exhibiting at least V-1 flame rating as determined according to the UL-94 protocol. A process to prepare the composition and articles comprising a composition of the invention and/or made by the process of the invention described herein are also disclosed.

Abstract: Disclosed is a flame-retardant composition comprising (i) 40-65 wt. % ABS, (ii) 12-20 wt. % ammonium polyphosphate and (iii) 15-40 wt. % cellulosic material, wherein all weights are based on the total weight of the composition and wherein ammonium polyphosphate and cellulosic material are present in a weight % ratio effective to provide molded articles exhibiting at least V-1 flame rating as determined according to the UL-94 protocol. A process to prepare the composition and articles comprising a composition of the invention and/or made by the process of the invention described herein are also disclosed.

Abstract: The present invention provides a method for incorporating features from heterogeneous auxiliary datasets into input text data for use in classification, a plurality of heterogeneous auxiliary datasets, such as labeled datasets and unlabeled datasets, are accessed after receiving input text data. A plurality of features are extracted from each of the plurality of heterogeneous auxiliary datasets. The plurality of features are combined with the input text data to generate a set of features which may potentially be used to classify the input text data. Classification features are then extracted from the set of features and used to classify the input text data. In one embodiment, the classification features are extracted by calculating a mutual information value associated with each feature in the set of features and identifying features having a mutual information value exceeding a threshold value.

Abstract: The present invention provides a method for using stored data associated with simple actions to identify and classify an observed composite action which comprises a combination of simple actions. Image data comprising the composite action is received and used to generate a feature vector, such as a combination of a horizontal translation, a vertical translation, a scale value and a skin detection value, that is associated with the composite action. Baseline reference vectors representing combinations of simple actions represented by stored reference data are then generated. The generated feature vector is then preprocessed to modify the feature vector towards a baseline reference vector describing a combination of simple actions. Each of the baseline reference vectors is then compared to the modified feature vector to determine the baseline reference vector and corresponding combination of simple actions that most accurately describes the composite action.

Abstract: The present invention provides a method for tracking entities, such as people, in an environment over long time periods. A region-based model is generated to model beliefs about entity locations. Each region corresponds to a discrete area representing a location where an entity is likely to be found. Each region includes one or more positions which more precisely specify the location of an entity within the region so that the region defines a probability distribution of the entity residing at different positions within the region. A region-based particle filtering method is applied to entities within the regions so that the probability distribution of each region is updated to indicate the likelihood of the entity residing in a particular region as the entity moves.

Abstract: A room temperature crosslinkable polymer system comprising an anhydride containing polymer and an oxyalkylene amine and a polymer electrolyte derived therefrom are prepared and employed as ion conducting materials for batteries such as lithium ion battery, solar cells and electrochromic devices is disclosed.

Abstract: The present invention provides a system and method associating the freeform speech commands with one or more predefined commands from a set of predefined commands. The set of predefined commands are stored and alternate forms associated with each predefined command are retrieved from an external data source. The external data source receives the alternate forms associated with each predefined command from multiple sources so the alternate forms represent paraphrases of the predefined command. A representation including words from the predefined command and the alternate forms of the predefined command, such as a vector representation, is generated for each predefined command. A similarity value between received speech data and each representation of a predefined command is computed and the speech data is classified as the predefined command whose representation has the highest similarity value to the speech data.

Abstract: A test framework for automating multi-user, multi-step and/or multi-machine test cases for electronic calendaring application objects is provided. Test cases may be automated where coordination between a number of machines is required to test electronic calendaring application user scenarios. In addition, automation of multifold interaction between two electronic calendaring application users is provided.

Abstract: A method and system for storing episodic sequences (events and actions). The system learns episodic sequencing by observing real-world events and actions or by receiving fact data from a database storing common sense facts. The episodic sequences are classified into events and actions, processed to indicate correlations and causality between the events and actions, and generated into linked graphs. The linked graphs may then be used to draw inferences, recognize patterns, and make decisions.

Abstract: Secure sharing of bound information is enabled in client applications associated with a backend LOB service. Bound item IDs are assigned to newly created bound items by a client, the items synchronized with the LOB system, a correlation ID received in response to the synchronization, and the two IDs mapped. A reverse sequence of actions is performed when the LOB service creates the bound item. In response to an attempt by a client to exchange bound information, the item is placed in a pending state and allowed to be received by a receiver upon successful completion of data transfer and LOB system permission of the exchange passing the bound item ID and the correlation ID. If the LOB system rejects the exchange, the item is placed in an unbound state and the receiver not allowed to receive the bound information.

Abstract: Recurring appointment items in a calendaring application are synchronized and recorded in a backend Line Of Business (LOB) service. Items marked in the calendaring application for time recording are used to create a recurring bound item with extended properties. A sweeper module scans on every run the mailbox for such recurring bound items. Occurrences of bound recurring appointments, which occur between the last scan and the current scan are determined and detached from the corresponding recurring series such that standalone bound items are created for such occurrences that can be recognized by an LOB application. Entries for bound items are retrieved from a client data store and synchronized it with the backend LOB service through a create-, update-, or delete-operation request.

Abstract: A method and system of Digital Rights Management (DRM) in a consumer environment where the DRM agent and the rendering application are implemented on separate devices is provided. A first control message is transmitted from the rendering application to notify the DRM agent about the details of a content consumption pattern. The DRM agent receives the first control message, and determines whether the consumption operation detailed in the first control message is a permitted operation. The DRM agent responds with a second control message that either indicates that the operation is permitted or indicates that the operation is not permitted. The rendering application in response to the second control message either halts the consumption operation or if the operation is allowed, performs the consumption operation.

Abstract: A system and a method are disclosed that provide plans for autonomous machines such as humanoid robots to perform indoor task. Human subjects contribute plans to a knowledge database. Information in the knowledge database is pre-processed to identify task steps and characterize them as action-object pairs, from which a plan database is created. A discriminative technique uses hierarchical agglomerative clustering to select an existing plan from the plan database. A generative technique formulates new plans from the plan database using first-order Markov chains, and may take into account information about the operational environment. Experimentation and evaluation by human subjects confirm the efficacy of both techniques.

Abstract: The present invention provides a method for extracting relationships between words in textual data. Initially, a classifier is trained to identify text data having a specific format, such as situation-response or cause-effect, using a training corpus. The classifier receives input identifying components of the text data having the specified format and then extracts features from the text data having the specified format, such as the part of speech for words in the text data, the semantic role of words within the text data and sentence structure. These extracted features are then applied to text data to identify components of the text data which have the specified format. Rules are then extracted from the text data having the specified format.

Abstract: The present invention provides a method for extracting relationships between words in textual data. Initially, training relationship data, such as word triplets describing a cause-effect relationship, is received and used to collect additional textual data including the training relationship data. Distributed data collection is used to receive the training data and collect the additional textual data, allowing a broad range of data to be acquired from multiple sources. Syntactic patterns are extracted from the additional textual data and a distributed data source is scanned to extract additional relationship data describing one or more causal relationships using the extracted syntactic patterns. The extracted additional relationship data is then stored, and can be validated by a supervised learning algorithm before storage and used to train a classifier for automatic validation of additional relationship data.

Abstract: Systems and methods are presented that enable logical reasoning even in the presence of noisy (inconsistent) data. The knowledge base is processed in order to make it consistent and is also compiled. This processing includes checking and correcting spelling, removing stopwords, performing, grouping words of similar and related meaning, and compacting the knowledge base. A robot can use the processed knowledge base to perform many different types of tasks, such as answering a query, determining a course of action that is designed to achieve a particular goal, and determining its own location.

Abstract: Disclosed are multicomponent fibers derived from a blend of a sulfopolyester with a water non-dispersible polymer wherein the as-spun denier is less than about 6 and wherein the water dispersible sulfopolyester exhibits a melt viscosity of less than 12,000 poise measured at 240° C. at a strain rate of 1 rad/sec, wherein the sulfopolyester comprising less than about 25 mole % of residues of at least one sulfomonomer, based on the total moles of diacid or diol residues, and wherein said poly(ethylene) terephthalate has an inherent viscosity of less than 0.55 dL/g. The multicomponent fiber is capable of being drawn at a relatively high fiber speed, particularly at least about 2000 m/min, and may be used to produce microdenier fibers. Fibrous articles may be produced from the multicomponent fibers and microdenier fibers. Also disclosed is a process for multicomponent fibers, nonwoven fabrics, and microdenier webs.

Abstract: The present invention provides a method for using stored data associated with simple actions to identify and classify an observed composite action which comprises a combination of simple actions. Image data comprising the composite action is received and used to generate a feature vector, such as a combination of a horizontal translation, a vertical translation, a scale value and a skin detection value, that is associated with the composite action. Baseline reference vectors representing combinations of simple actions represented by stored reference data are then generated. The generated feature vector is then preprocessed to modify the feature vector towards a baseline reference vector describing a combination of simple actions. Each of the baseline reference vectors is then compared to the modified feature vector to determine the baseline reference vector and corresponding combination of simple actions that most accurately describes the composite action.

Abstract: Extraction of data employing a sequence of remote function calls in form of a synchronous multi-batch call chain is provided. Sequencing of calls is enabled by generating parameters associated with the extraction of a next batch of data. The parameterized, dynamic generation of queries allows for optimization of memory utilization by batching result sets and data conversion. Each subsequent call retrieves a packet of data, picking up where the previous call left off without an overlap. Parameters are updated after each call based on extracted data, available memory, and the like.

Abstract: A system and a method are disclosed for automatic question classification and answering. A multipart artificial neural network (ANN) comprising a main ANN and an auxiliary ANN classifies a received question according to one of a plurality of defined categories. Unlabeled data is received from a source, such as a plurality of human volunteers. The unlabeled data comprises additional questions that might be asked of an autonomous machine such as a humanoid robot, and is used to train the auxiliary ANN in an unsupervised mode. The unsupervised training can comprise multiple auxiliary tasks that generate labeled data from the unlabeled data, thereby learning an underlying structure. Once the auxiliary ANN has trained, the weights are frozen and transferred to the main ANN. The main ANN can then be trained using labeled questions. The original question to be answered is applied to the trained main ANN, which assigns one of the defined categories.