Abstract: An abnormal behavior detection model building apparatus and an abnormal behavior detection model building method thereof are provided. The abnormal behavior detection model building apparatus analyzes the parts of speech of a plurality of program operation sequences in a plurality of program operation sequence data associated with abnormal behaviors to generate a plurality of word vectors and cluster the word vectors. Based on the result of the clustering, the abnormal behavior detection model building apparatus obtains a feature vector of each of the program operation sequence data, and perform a supervised learning for a classification algorithm by using the feature vectors so as to build an abnormal behavior detection model.

Abstract: A processor includes a front end to decode an instruction, an allocator to pass the instruction to a nearest neighbor logic unit (NNLU) to execute the instruction, and a retirement unit to retire the instruction. The NNLU includes logic to determine input of the instruction for which nearest neighbors will be calculated, transform the input, retrieve candidate atoms for which the nearest neighbors will be calculated, compute distance between the candidate atoms and the input, and determine the nearest neighbors for the input based upon the computed distance.

Abstract: An abnormal behavior detection model building apparatus and an abnormal behavior detection model building method thereof are provided. The abnormal behavior detection model building apparatus analyzes the parts of speech of a plurality of program operation sequences in a plurality of program operation sequence data associated with abnormal behaviors to generate a plurality of word vectors and cluster the word vectors. Based on the result of the clustering, the abnormal behavior detection model building apparatus obtains a feature vector of each of the program operation sequence data, and perform a supervised learning for a classification algorithm by using the feature vectors so as to build an abnormal behavior detection model.

Abstract: Detailed herein are embodiments of systems, methods, and apparatuses to be used for feature searching using an entry-based searching structure.

Abstract: Detailed herein are embodiments of systems, methods, and apparatuses to be used for feature searching using an entry-based searching structure.

Abstract: A system and a method for predicting a remaining useful life (RUL) of a component of an equipment are provided. The system for predicting the RUL of the component of the equipment includes a data acquisition unit, a feature capturing unit, a mapping function generating unit, a similarity analyzing unit and a RUL calculating unit. The feature capturing unit obtains an estimation feature according to a real time sensing record, and obtains a plurality of training features according to a set of history sensing records. The similarity analyzing unit obtains k similar features which are similar to the estimation feature according to the training features. The RUL calculating unit obtains at least one of k predicting information via a mapping function according to the k similar features and calculates an estimation RUL according to at least one predicting value.

Abstract: System and techniques for sparse coding based classification are described herein. A sample of a first type of data may be obtained and encoded to create a sparse coded sample. A dataset may be searched using the sparse coded sample to locate a segment set of a second type of data. An instance of the second type of data may then be created using the segment set.

Abstract: Methods and systems for operating a sensor network comprising a plurality of nodes and at least one resource, where a resource can be a sensing device (e.g., a camera or microphone) or other peripheral devices (e.g., a storage or recording system). In at least one embodiment of the present invention, at least one node in a network determines at least one resource available to it and the type of the resource or its capabilities. Based on the type or capabilities of the resource, the node associates with one or more logical node names and acquires instructions for performing at least one function.

Abstract: Methods and systems for operating a sensor network comprising a plurality of nodes and at least one resource, where a resource can be a sensing device (e.g., a camera or microphone) or other peripheral devices (e.g., a storage or recording system). In at least one embodiment of the present invention, at least one node in a network determines at least one resource available to it and the type of the resource or its capabilities. Based on the type or capabilities of the resource, the node associates with one or more logical node names and acquires instructions for performing at least one function.

Abstract: An apparatus is described herein. The apparatus includes a clustering mechanism that is to partition a dictionary into a plurality of clusters. The apparatus also includes a feature-matching mechanism that is to pre-compute feature matching results for each cluster of the plurality of clusters. Moreover, the apparatus includes a selector that is to locate a best representative feature from the dictionary in response to an input vector.

Abstract: A system and a method for predicting a remaining useful life (RUL) of a component of an equipment are provided. The system for predicting the RUL of the component of the equipment includes a data acquisition unit, a feature capturing unit, a mapping function generating unit, a similarity analyzing unit and a RUL calculating unit. The feature capturing unit obtains an estimation feature according to a real time sensing record, and obtains a plurality of training features according to a set of history sensing records. The similarity analyzing unit obtains k similar features which are similar to the estimation feature according to the training features. The RUL calculating unit obtains at least one of k predicting information via a mapping function according to the k similar features and calculates an estimation RUL according to at least one predicting value.

Abstract: Methods and systems for operating a sensor network comprising a plurality of nodes and at least one resource, where a resource can be a sensing device (e.g., a camera or microphone) or other peripheral devices (e.g., a storage or recording system). In at least one embodiment of the present invention, at least one node in a network determines at least one resource available to it and the type of the resource or its capabilities. Based on the type or capabilities of the resource, the node associates with one or more logical node names and acquires instructions for performing at least one function.

Abstract: A processor includes a front end to decode an instruction, an allocator to pass the instruction to a nearest neighbor logic unit (NNLU) to execute the instruction, and a retirement unit to retire the instruction. The NNLU includes logic to determine input of the instruction for which nearest neighbors will be calculated, transform the input, retrieve candidate atoms for which the nearest neighbors will be calculated, compute distance between the candidate atoms and the input, and determine the nearest neighbors for the input based upon the computed distance.

Abstract: Circuitry, systems and methods for testing integrated circuits for the presence of anomalies. Techniques include applying a plurality of inputs to an integrated circuit under test to obtain a first plurality of measurements at least partially characterizing power leakage in the integrated circuit under test, encode the first plurality of measurements, by computing a plurality of random linear combinations of measurements in the first plurality of measurements, to obtain a second plurality of encoded measurements determining whether the integrated circuit under test contains at least one anomaly based, at least in part, on the second plurality of encoded measurements.

Abstract: A channel information feedback method for multi-antenna system, and a wireless communication device using the same method are provided. The proposed method could reduce feedback overhead for multiple-input multiple-output (MIMO) wireless channel information, and is based on compressive sensing technique. Prior to sending back channel information, a receiver estimates the channel and multiplies the vectorized channel with a random matrix to generate compressed feedback content. Upon receiving the compressed feedback content at a transmitter, the channel information could be restored with signal recovery algorithms of compressive sensing technique. In the other embodiment, the proposed method further adaptively adjusts compression ratio of the compressed feedback content in accordance to the prevailing channel quality. Further, for slow-varying MIMO channels, there is proposed another channel information feedback method which switches between a fixed sparcifying-basis and a signal-dependent sparcifying-basis.

Abstract: Detailed herein are embodiments of systems, methods, and apparatuses to be used for feature searching using an entry-based searching structure.

Abstract: Detailed herein are embodiments of systems, methods, and apparatuses to be used for feature searching using an entry-based searching structure.

Abstract: Techniques for data synchronization between a first computing device coupled to at least one memory storing current data and a second computing device coupled to at least a second memory storing first encoded data and a copy of prior data. The first device may perform a method comprising: encoding the current data using a compressive sensing encoding technique to obtain second encoded data; and transmitting the second encoded data to the second computing device. The second device may perform a method comprising receiving second encoded data from the first computing device; decoding the second encoded data using a compressive sensing decoding technique to obtain decoded data; and obtaining a copy of the current data by using the decoded data and the copy of prior data.

Abstract: Techniques for medium access control. Some techniques include receiving, at a first computing device, a solicitation for at least a first medium access request that specifies at least one time period for transmitting the first medium access request to the second computing device; encoding the first medium access request at least in part by using a compressive sensing encoding technique to obtain a first encoded medium access request; and transmitting the first encoded medium access request to the second computing device during the at least one time period specified in the received solicitation.

Abstract: A context-showing and power-saving display information converting system and a corresponding apparatus are provided for lowering the power consumption of displaying images on a pixel self-emissive display device. The display information converting system includes a context-showing module and a power-saving conversion module. The context-showing module receives display information that describes the content of an image, wherein the display information includes one or more elements, and each element corresponds to a plurality of pixels displayed by a display device. In addition, the context-showing module determines a relevance of the one or more elements according to the viewing interest of the user. The power-saving conversion module converts the display information in unit of the one or more elements according to the relevance and provides the converted display information to the display device.