Abstract: A connector assembly includes two electric connectors that are configured to be plugged together in a plug-in direction and rotated relative to one another in a direction of rotation into a coupled state, wherein one of the two electric connectors includes a contact and the other one of the two electric connectors includes a mating contact. A mechanical guiding system guides the movement of the two electric connectors relative one another in the plug-in direction and the movement of the two electric connectors relative to one another in the direction of rotation. The mechanical guiding system mechanically couples the movement in the direction of rotation with a movement against the plug-in direction. In the coupled state, the contact and the mating contact are pressed against each other against the plug-in direction.

Abstract: A computerized method for implementing a neural architecture for hierarchical sequence labelling comprising: providing a neural architecture comprising a set of labelling layers, wherein the neural architecture uses a multi-pass approach on the set of labelling layers, receiving an input sentence; parsing the input sentence; embedding the input sentence into a corresponding character vector and a corresponding word vector to generate a feature vector; passing the feature vector through the neural architecture; and performing a multi-layer labelling procedure on the feature vector with the neural architecture comprising: augmenting a set of corresponding bits of the feature vector, wherein the feature vector is passed through the set of labelling layers of neural architecture.

Abstract: A computerized method includes receiving a dialog session. The dialog session comprises a set of new inbound messages. The method feeds the dialog session into tokenizer. The method, with the tokenizer, generates a set of tokens by breaking the new inbound messages into a sequence of tokens. The method provides the tokens to a DAG frame labeler cascade. With the DAG frame labeler cascade, the method uses a sequence of tokens to generate a set of token labels. The method passes the token labels and tokens to an entity interpreter. With the entity interpreter, the method generates a DAG frame. With the DAG frame, the method outputs a structured information from a multiturn dialogue.

Abstract: In one aspect, method useful for goal-oriented dialog automation comprising includes the step of receiving an input message. The method includes the step of implementing an entity tagging operation on the input message. The method includes the step of tagging the message context of the input message to generate a tagged message context. The method includes the step of implementing semantic frame extraction from the tagged message context. The method includes the step of implementing an entity interpretation on the extracted frame. The method includes the step of accessing a database to determine a business schedule and a client profile. The business schedule and the client profile are related to the input message. The method includes the step of implementing a retrieval engine. The retrieval engine obtains one or more response templates. The method includes the step of generating a ranked list of candidate templates from the output of the retrieval engine.

Abstract: In one aspect, method useful for goal-oriented dialog automation comprising incudes the step of receiving an input message. The method includes the step of implementing an entity tagging operation on the input message. The method includes the step of tagging the message context of the input message to generate a tagged message context. The method includes the step of implementing semantic frame extraction from the tagged message context. The method includes the step of implementing an entity interpretation on the extracted frame. The method includes the step of accessing a database to determine a business schedule and a client profile. The business schedule and the client profile are related to the input message. The method includes the step of implementing a retrieval engine. The retrieval engine obtains one or more response templates. The method includes the step of generating a ranked list of candidate templates from the output of the retrieval engine.

Abstract: In one aspect, a computer system includes an application implemented with a computer processor that automatically discovers a list items from a set of user data sources, wherein the list items correspond to automatic recommendations for a set of calendar events and tasks, and wherein the list items are discovered programmatically in a set of email conversations and a set of calendar updates. The application extracts the list of items and metadata about the list items from the set of user data sources. The application identifies a type of each list item, wherein a set of types comprises a mandatory-action type and an informative type. The application receives a user created list of items. The application creates an electronic agenda view of the auto-recommended list of items and the user created list of items, and organizes these lists by date.

Abstract: A process identifies a person in image data. The process first executes a training phase, and thereafter a detection phase. The training phase learns body parts using body part detectors, generates classifiers, and determines a spatial distribution and a set of probabilities. The execution phase applies the body part detector to an image, combines output of several body part detectors, and determines maxima of the combination of the output.

Abstract: A system tracks multiple moving objects in a stream of video data. In an embodiment, the system uses a combination of video motion detection data and color based data. In another embodiment, the system combines this data into a condensation framework. In yet another embodiment, the integration of the video motion data and the color-based data is done is real time. In further embodiments, the robustness of the tracking is enhanced by applying heuristics.

Abstract: There is provided a system and method for facilitating shipping. An exemplary method comprises automatically detecting that a user at a front-end of a computer system has booked a shipping service. The exemplary method also comprises obtaining shipping information associated with the shipping service. The exemplary method additionally comprises, based on the shipping information, automatically scheduling a pick-up service for the shipment being the object of the shipping service and sending an email message or an instant message incorporating the pick-up schedule information to the user.

Abstract: There is provided a system and method for facilitating shipping. An exemplary method comprises providing a shipping bill form at a front-end of a computer system. The exemplary method also comprises enabling a user at the front-end to fill in shipping information associated with the shipping bill form and to send an email message or an instant message incorporating the filled in shipping bill form to a back-end of the computer system.

Abstract: A process identifies a person in image data. The process first executes a training phase, and thereafter a detection phase. The training phase learns body parts using body part detectors, generates classifiers, and determines a spatial distribution and a set of probabilities. The execution phase applies the body part detector to an image, combines output of several body part detectors, and determines maxima of the combination of the output.

Abstract: A system tracks multiple moving objects in a stream of video data. In an embodiment, the system uses a combination of video motion detection data and color based data. In another embodiment, the system combines this data into a condensation framework. In yet another embodiment, the integration of the video motion data and the color-based data is done is real time. In further embodiments, the robustness of the tracking is enhanced by applying heuristics.

Abstract: A system and method processes compressed video data. Motion vectors are extracted from the compressed video data, and minimum bounded regions of a moving object are identified. An inverse discrete cosine transform is applied to the minimum bounded region, and background information is subtracted out from the moving object.