Abstract: Techniques and systems for cross-trace scalable issue detection and clustering that scale-up trace analysis for issue detection and root-cause clustering using a machine learning based approach are described herein. These techniques enable a scalable performance analysis framework for computing devices addressing issue detection, which is designed as a multiple scale feature for learning based on issue detection, and root cause clustering. In various embodiments the techniques employ a cross-trace similarity model, which is defined to hierarchically cluster problems detected in the learning based issue detection via butterflies of trigram stacks. The performance analysis framework is scalable to manage millions of traces, which include high problem complexity.

Abstract: A method and an apparatus for protecting data carried on an Un interface between a eNB and a relay node are disclosed. Three types of radio bearers (RBs) are defined over the Un interface: signaling radio bearers (SRBs) for carrying control plane signaling data, signaling-data radio bearers (s-DRBs) for carrying control plane signaling date; and data-data radio bearers (d-DRBs) for carrying user plane data. An integrity protection algorithm and an encryption algorithm are negotiated for control plane signaling data on an SRB, control plane signaling data carried on an s-DRB, and user plane data carried on a d-DRB. With the respective integrity protection algorithm and encryption algorithm, the data over the Un interface can be protected respectively. Therefore, the security protection on the Un interface is more comprehensive, and the security protection requirements of data borne over different RBs can be met.

Abstract: Techniques for obtaining a reaction of an individual to content and outputting the reaction of the individual with the content are described herein. The techniques may include obtaining the reaction of the individual as the content is displayed to the individual. The reaction may be obtained by capturing a video of the individual. The reaction of the individual and the content may be output at a same time to another individual. These techniques may also include obtaining the reaction of another individual as the content and the reaction of the individual are output to another individual.

Abstract: This application describes a system and method for diagnosing performance problems on a computing device or a network of computing devices. The application describes identifying common execution patterns between a plurality of execution paths being executed by a computing device or by a plurality of computing device over a network. The common execution pattern being based in part on common operations being performed by the execution paths, the commonality being independent of timing of the operations or the sequencing of the operations and individual executions paths can belong to one or more common execution patterns. Using lattice graph theory, relationships between the common execution patterns can be identified and used to diagnose performance problems on the computing device(s).

Abstract: An exemplary method for online character recognition of characters includes acquiring time sequential, online ink data for a handwritten character, conditioning the ink data to produce conditioned ink data where the conditioned ink data includes information as to writing sequence of the handwritten character and extracting features from the conditioned ink data where the features include a tangent feature, a curvature feature, a local length feature, a connection point feature and an imaginary stroke feature. Such a method may determine neighborhoods for ink data and extract features for each neighborhood. An exemplary character recognition system may use various exemplary methods for training and character recognition.

Abstract: Described is a technology by which online recognition of handwritten input data is combined with offline recognition and processing to obtain a combined recognition result. In general, the combination improves overall recognition accuracy. In one aspect, online and offline recognition is separately performed to obtain online and offline character-level recognition scores for candidates (hypotheses). A statistical analysis-based combination algorithm, an AdaBoost algorithm, and/or a neural network-based combination may determine a combination function to combine the scores to produce a result set of one or more results. Online and offline radical-level recognition may be performed. For example, a HMM recognizer may generate online radical scores used to build a radical graph, which is then rescored using the offline radical recognition scores. Paths in the rescored graph are then searched to provide the combined recognition result, e.g., corresponding to the path with the highest score.

Abstract: Embodiments of the present invention disclose a relay node authentication method, apparatus, and system. The method provided in an embodiment of the present invention includes: sending, by a relay node, an authentication request message to a peer node, where the authentication request message includes a certificate of the relay node, so that the peer node authenticates the relay node according to the certificate of the relay node, where the peer node is a network side node or a security gateway in a security domain where the network side node is located; and receiving, by the relay node, an authentication response message sent by the peer node, where the authentication response message includes a certificate of the peer node, and authenticating the peer node according to the certificate of the peer node.

Abstract: Described is a technology that provides an integrated platform for users to use different kinds of digital ink (e.g., handwritten characters, sketched shapes, handwritten formulas) when interacting with computer programs. The platform interprets the user's digital ink input and outputs one or more associated items into an application program. The output items can be customized for different application programs. In one aspect, the platform includes an ink panel having different operating modes for receiving digital ink, and a recognition service that recognizes different types of digital ink. The recognition service may include a unified recognizer that recognizes different types of digital ink, e.g., characters and shapes. Another recognizer may be included such as an equation recognizer. If the recognition result is text while in a non-text mode, the text may be used in a keyword search to locate items; otherwise, the recognition result may be used without keyword searching.

Abstract: Execution traces are collected from multiple execution instances that exhibit performance issues such as slow execution. Call stacks are extracted from the execution traces, and the call stacks are mined to identify frequently occurring function call patterns. The call patterns are then clustered, and used to identify groups of execution instances whose performance issues may be caused by common problematic program execution patterns.

Abstract: A system for frequent pattern mining uses two layers of processing: a plurality of computing nodes, and a plurality of processors within each computing node. Within each computing node, the data set against which the frequent pattern mining is to be performed is stored in shared memory, accessible concurrently by each of the processors. The search space is partitioned among the computing nodes, and sub-partitioned among the processors of each computing node. If a processor completes its sub-partition, it requests another sub-partition. The partitioning and sub-partitioning may be performed dynamically, and adjusted in real time.

Abstract: A call pattern database is mined to identify frequently occurring call patterns related to program execution instances. An SVM classifier is iteratively trained based at least in part on classifications provided by human analysts; at each iteration, the SVM classifier identifies boundary cases, and requests human analysis of these cases. The trained SVM classifier is then applied to call pattern pairs to produce similarity measures between respective call patterns of each pair, and the call patterns are clustered based on the similarity measures.

Abstract: A method for identifying data related to a software security issue is provided. The method includes accessing a software security issue and determining one or more attributes associated with the software security issue. The method also includes accessing aggregated software security data retrieved from a plurality of on-line sources and searching the aggregated software security data for the attributes associated with the security issue. The method further includes associating a portion of the aggregated data with the security issue based on matching the attributes associated with the security issue with contents of the portion of the aggregated data.

Abstract: An exemplary method for online character recognition of characters includes acquiring time sequential, online ink data for a handwritten character, conditioning the ink data to produce conditioned ink data where the conditioned ink data includes information as to writing sequence of the handwritten character and extracting features from the conditioned ink data where the features include a tangent feature, a curvature feature, a local length feature, a connection point feature and an imaginary stroke feature. Such a method may determine neighborhoods for ink data and extract features for each neighborhood. An exemplary character recognition system may use various exemplary methods for training and character recognition.

Abstract: A method for researching and developing a recognition model in a computing environment, including gathering one or more data samples from one or more users in the computing environment into a training data set used for creating the recognition model, receiving one or more training parameters defining a feature extraction algorithm configured to analyze one or more features of the training data set, a classifier algorithm configured to associate the features to a template set, a selection of a subset of the training data set, a type of the data samples, or combinations thereof, creating the recognition model based on the training parameters, and evaluating the recognition model.

Abstract: A method and a device for obtaining a security key in a relay system are disclosed in the embodiment of the present invention. A node in the relay system obtains an initial key, according to the initial key, the node obtains a root key of an air interface protection key between the node and another node that is directly adjacent to the node, and according to the root key, the node obtains the air interface protection key between the node and said another node that is directly adjacent to the node. Therefore, according to the initial key, each lower-level node obtains a root key of an air interface protection key between each lower-level node, so that data of a UE on a Un interface link may be respectively protected, that is, each active UE has a set of security parameters on the Un interface link, and effective security protection is performed on data on each segment of an air interface.

Abstract: A method for identifying a portion of aggregated software security data is described. The method includes accessing aggregated data associated with software vulnerabilities retrieved from a plurality of on-line sources. The method further includes searching a portion of the aggregated data for an exact match to a particular attribute of the data and searching the portion of the aggregated data for one or more partial matches associated with the particular attribute. The method also includes associating the portion of the data with the particular attribute based on the exact match of one or more of the partial matches.

Abstract: A method for enabling access to software security data is provided. The method includes accessing data associated with software vulnerabilities from a plurality of on-line sources. The method further includes aggregating the data from the plurality of on-line sources and identifying attributes associated with the data. The method also includes enabling access to the aggregated data through a graphical user interface that can be used to analyze the data according to the attributes.

Abstract: Embodiments of the present invention disclose a method, an apparatus, and a system for data transmission. The method for data transmission includes: determining that data to be transmitted is control plane signaling related to a user equipment that camps on a relay node; and transmitting the data through a first user data bearer established between the relay node and a donor base station, where the first user data bearer provides integrity protection for the data. According to the embodiments of the present invention, when the control plane signaling related to the user equipment that camps on the relay node is transmitted between the relay node and the donor base station, integrity protection is provided for the control plane signaling, and therefore attacks such as the denial of a service attack are prevented.

Abstract: Described is a technology by which online recognition of handwritten input data is combined with offline recognition and processing to obtain a combined recognition result. In general, the combination improves overall recognition accuracy. In one aspect, online and offline recognition is separately performed to obtain online and offline character-level recognition scores for candidates (hypotheses). A statistical analysis-based combination algorithm, an AdaBoost algorithm, and/or a neural network-based combination may determine a combination function to combine the scores to produce a result set of one or more results. Online and offline radical-level recognition may be performed. For example, a HMM recognizer may generate online radical scores used to build a radical graph, which is then rescored using the offline radical recognition scores. Paths in the rescored graph are then searched to provide the combined recognition result, e.g., corresponding to the path with the highest score.

Abstract: A code verification system is described herein that provides augmented code review with code clone analysis and visualization to help software developers automatically identify similar instances of the same code and to visualize differences in versions of software code over time. The system uses code clone search technology to identify code clones and to present the user with information about similar code as the developer makes changes. The system may provide automated notification to the developer or to other teams as changes are made to code segments with one or more related clones. The code verification system also helps the developer to understand architectural evolution of a body of software code. The code verification system provides an analysis component for determining architectural differences based on the code clone detection result between the two versions of the software code base.