Abstract: An example method includes detecting, using sensors, packets throughout a datacenter. The sensors can then send packet logs to various collectors which can then identify and summarize data flows in the datacenter. The collectors can then send flow logs to an analytics module which can identify the status of the datacenter and detect an attack.

Abstract: Provided is a system and method that can identify whether an item is a dangerous good. The system can determine whether a product belongs in any of a number of different classes of dangerous goods from among a plurality of different regulations based on a machine learning algorithm which performs a text-based classification. In one example, the method may include receiving an identification of an object, retrieving a plurality of descriptive attributes of the object from a data store and converting the plurality of descriptive attributes into an input string, predicting whether the object is a dangerous object via execution of a text-based machine learning algorithm that receives the input string as an input, and outputting information about the prediction of the object for display via a user interface.

Abstract: Provided is a voltage level shifter that operates in sub-threshold voltages. The level shifter includes a level shifting stage. The level shifting stage receives a first signal from a first voltage domain and outputs a second signal to a second voltage domain. The level shifter includes a first auxiliary stage. In response to the first signal having a first voltage level corresponding to a first logical state and a first node of the level shifting stage having a supply voltage level, the first auxiliary stage sources current to a second node of the level shifting stage. Sourcing the current to the second node accelerates a transition of the first node to a reference voltage. The level shifting stage outputs a second signal to a second voltage domain.

Abstract: Provided is a system and method that can identify whether an item is a dangerous good. The system can determine whether a product belongs in any of a number of different classes of dangerous goods from among a plurality of different regulations based on a machine learning algorithm which performs a text-based classification. In one example, the method may include receiving an identification of an object, retrieving a plurality of descriptive attributes of the object from a data store and converting the plurality of descriptive attributes into an input string, predicting whether the object is a dangerous object via execution of a text-based machine learning algorithm that receives the input string as an input, and outputting information about the prediction of the object for display via a user interface.

Abstract: A device includes input data lines associated with a first time domain and output data lines associated with a second time domain. Synchronizing circuitry is coupled between the input data lines and output data lines. The synchronizing circuitry is driven by a synchronizing clock signal generated by clock generating circuitry. The clock generating circuitry is coupled to the input data lines and the synchronizing circuitry. In operation, the clock generating circuitry detects signal transitions on the plurality of input data lines. The clock generating circuitry generates the synchronizing clock signal that drives the synchronizing circuitry based on detected transitions, a clock signal of the first time domain, and a clock signal of the second time domain.

Abstract: System, method, and various embodiments for providing contextualized character recognition system are described herein. An embodiment operates by determining a plurality of predicted words of an image. An accuracy measure or each of the plurality of predicted words is identified and a replaceable word with an accuracy measure below a threshold is identified. A plurality of candidate words associated with the replaceable word are identified and a probability for each of the candidate words is calculated based on a contextual analysis. One of the candidate words with a highest probability is selected. The plurality of predicted words including the selected candidate word with the highest probability replacing the replaceable word is output.

Abstract: In an example embodiment, a deep neural network may be utilized to determine matches between candidate pairs of entities, as well as confidence scores that reflect how certain the deep neural network is about the corresponding match. The deep neural network is also able to find these matches without requiring domain knowledge that would be required if features for a machine-learned model were handcrafted, which is a drawback of prior art machine-learned models used to match entities in multiple tables. Thus, the deep neural network improves on the functioning of prior art machine learned models designed to perform the same tasks. Specifically, the deep neural network learns the relationships of tabular fields and the patterns that define a match from historical data alone, making this approach generic and applicable independent of the context.

Abstract: System, method, and various embodiments for providing contextualized character recognition system are described herein. An embodiment operates by determining a plurality of predicted words of an image. An accuracy measure or each of the plurality of predicted words is identified and a replaceable word with an accuracy measure below a threshold is identified. A plurality of candidate words associated with the replaceable word are identified and a probability for each of the candidate words is calculated based on a contextual analysis. One of the candidate words with a highest probability is selected. The plurality of predicted words including the selected candidate word with the highest probability replacing the replaceable word is output.

Abstract: The present invention provides a sustainable stain resistant composition 102 that includes (a) about 3% to 8% of at least one silicon nano particle surface functionalized with (Pentafluorophenyl)triethoxysilane 104, and (b) about 3% to 8% of at least one hydrophobic agent 106 selected from a group comprising polymer of (a) methacrylic esters of aliphatic C1 to C18 alcohols, or (b) vinyl acetate, or (c) acrylonitrile. The stain resistant composition further includes (a) at least one softening agent 110, (b) an extending agent 108, (c) at least one of (i) a wetting agent or (ii) a re-wetting agent 112, and (d) a microencapsulated odour neutralizing agent 114. The present invention also relates to a process for producing stain resistant textile 118 using the sustainable stain resistant composition 102.

Abstract: Provided is a system and method that can assign a product to a regulatory group via a machine learning algorithm. The system can predict whether a product belongs in any of a number of different groups and retrieve regulations for the predicted groups. In one example, the method may include receiving an alphanumeric identifier of an object, predicting that the object is included within one or more regulatory categories via execution of a regulatory-based machine learning algorithm that receives the identifier of the object as an input and classifies the object into the one or more regulatory categories, retrieving regulation information about the one or more predicted regulatory categories for at least one jurisdiction associated with the object, and outputting the retrieved regulation information about the one or more predicted regulations for display via a user interface.

Abstract: Provided is a system and method that can identify whether an item is a dangerous good. The system can determine whether a product belongs in any of a number of different classes of dangerous goods from among a plurality of different regulations based on a machine learning algorithm which performs a text-based classification. In one example, the method may include receiving an identification of an object, retrieving a plurality of descriptive attributes of the object from a data store and converting the plurality of descriptive attributes into an input string, predicting whether the object is a dangerous object via execution of a text-based machine learning algorithm that receives the input string as an input, and outputting information about the prediction of the object for display via a user interface.

Abstract: Techniques for use in network incident identification are described. In response to an occurrence of an unknown network incident, a plurality of log messages (e.g. syslog messages) are received from a plurality of network components in one or more networks. In one illustrative example, a plurality of relationships between interfaces and events are derived from the received log messages and characterized as a plurality of graphical component relationships. One or more groups of connected components are determined from the graphical component relationships and network component connection data which indicate interface relationships of the network components. Here, groups of connected components may be logically joined based on the network component connection data indicating one or more interface relationships.

Abstract: Techniques for use in network incident identification are described. In response to an occurrence of an unknown network incident, a plurality of log messages (e.g. syslog messages) are received from a plurality of network components in one or more networks. In one illustrative example, a plurality of relationships between interfaces and events are derived from the received log messages and characterized as a plurality of graphical component relationships. One or more groups of connected components are determined from the graphical component relationships and network component connection data which indicate interface relationships of the network components. Here, groups of connected components may be logically joined based on the network component connection data indicating one or more interface relationships.

Abstract: An engineering method and an engineering management system are provided with a token database connected to a plurality of external sources via a communication network. The engineering management system determines a connection of at least one engineering object into a communication network of a plurality of engineering objects by obtaining token data associated with the engineering object. The engineering management system determines an automation function instance of the engineering object, from a plurality of automation function instances stored in an engineering database, based on the token data. The engineering management system generates an engineering recommendation based on the automation function instance, comprising proposed connections of the automation function instance with other automation function instances. The engineering management system performs engineering based on the engineering recommendation for the automation function instance of the engineering object.

Abstract: A device and a method facilitating generation of one or more intuitive gesture sets for the interpretation of a specific purpose are disclosed. Data is captured in a scalar and a vector form which is further fused and stored. The intuitive gesture sets generated after the fusion are further used by one or more components/devices/modules for one or more specific purpose. Also incorporated is a system for playing a game. The system receives one or more actions in a scalar and a vector from one or more user in order to map the action with at least one pre stored gesture to identify a user in control amongst a plurality of users and interpret the action of user for playing the game. In accordance with the interpretation, an act is generated by the one or more component of the system for playing the game.

Abstract: A system for operating an on-load tap changer (OLTC) includes a plurality of legs that include mechanical switches. At least one leg switches from a first to a second tap of the OLTC on receipt of a tap change signal. At least one mechanical switch is activated to establish an electrical connection between one of the first and the second tap and a power terminal of the OLTC. Further, the system includes semiconductor switches that are parallel to the mechanical switches and when activated electrically couple one of the first and the second tap and the power terminal. The system includes a processing unit that selectively activates and deactivates the mechanical and semiconductor switches in such a way that electrical contact is maintained between at least one of the taps and the power terminal during the transition of at least one leg from the first tap to the second tap.

Abstract: A method of switching taps of an on-load tap changer includes providing a main finger, a first side finger including a first solid state switch and a second side finger including a second solid state switch. The main finger, the first side finger and the second side finger are utilized to provide a connection between the taps and a power terminal of the on-load tap changer. The method also includes triggering the on-load tap changer to shift the fingers from a first tap to a second tap of the on-load tap changer when a tap change signal is received and utilizing the first solid state switch and the second solid state switch to commutate a current during the tap change operation.

Abstract: A method and system for tracking of objects in a video is disclosed. The method of the present invention enables user to indicate a boundary-box to the identified object of interest in the broadcast video on television or any other communication media. The object indicted in the boundary-box is than tracked by the users connected in a social community network in the upcoming video frames of the broadcasted video. The tracked object is then tagged by the users in the social community network. Further, the present invention enables augmentation of the tracked object in the video by extracting additional information from the online service providers. The augmentation and tagging of the object generates metadata related to the object. The metadata generated is stored on a server to track the object in future based on the metadata related to the object.

Abstract: A method of switching taps of an on-load tap changer includes providing a main finger, a first side finger including a first solid state switch and a second side finger including a second solid state switch. The main finger, the first side finger and the second side finger are utilized to provide a connection between the taps and a power terminal of the on-load tap changer. The method also includes triggering the on-load tap changer to shift the fingers from a first tap to a second tap of the on-load tap changer when a tap change signal is received and utilizing the first solid state switch and the second solid state switch to commutate a current during the tap change operation.

Abstract: A system for operating an on-load tap changer (OLTC) includes a plurality of legs that include mechanical switches. At least one leg switches from a first to a second tap of the OLTC on receipt of a tap change signal. At least one mechanical switch is activated to establish an electrical connection between one of the first and the second tap and a power terminal of the OLTC. Further, the system includes semiconductor switches that are parallel to the mechanical switches and when activated electrically couple one of the first and the second tap and the power terminal. The system includes a processing unit that selectively activates and deactivates the mechanical and semiconductor switches in such a way that electrical contact is maintained between at least one of the taps and the power terminal during the transition of at least one leg from the first tap to the second tap.