Abstract: A semiconductor device includes a substrate, an interfacial layer formed on the semiconductor substrate, and a high-k dielectric layer formed on the interfacial layer. At least one of the high-k dielectric layer and the interfacial layer is doped with: a first dopant species, a second dopant species, and a third dopant species. The first dopant species and the second dopant species form a plurality of first dipole elements having a first polarity. The third dopant species forms a plurality of second dipole elements having a second polarity. A first concentration ratio of the first concentration of the first dopant species to the second concentration of the second dopant species of the p-type transistor is different from a second concentration ratio of the first concentration of the first dopant species to the second concentration of the second dopant species of the n-type transistor.

Abstract: A semiconductor structure includes a substrate and a semiconductor channel layer over the substrate. The semiconductor structure includes a high-k gate dielectric layer over the semiconductor channel layer, a work function metal layer over the high-k gate dielectric layer, and a bulk metal layer over the work function metal layer. The work function metal layer includes a first portion and a second portion over the first portion. Both the first portion and the second portion are conductive. Materials included in the second portion are also included in the first portion. The first portion is doped with silicon at a first dopant concentration, and the second portion is not doped with silicon or is doped with silicon at a second dopant concentration lower than the first dopant concentration.

Abstract: A smart wearable device has a signal calibration function executed by a signal calibration method and applied to a finger, a limb and/or a neck of a user. The smart wearable device includes at least one physiological signal detector, at least one pressure detector and an operation processor. The at least one physiological signal detector is adapted to abut against a detection area of the user for detecting a physiological signal. The at least one pressure detector is disposed around the at least one physiological signal detector and adapted to detect a pressure value of the detection area. The operation processor is electrically connected with the at least one physiological signal detector and the at least one pressure detector. The operation processor is adapted to optimize the physiological signal when the pressure value exceeds a predefined pressure threshold.

Abstract: A computer implemented method is provided for automatically determining a response to an input query. The method includes searching at a first stage a data repository using the input query. The data repository is configured to store historical queries and their corresponding responses. The search is adapted to determine a plurality of historical queries related to the input query and historical responses corresponding to the related historical queries. The method also includes clustering the plurality of historical responses into one or more response groups, where each response group includes one or more similar historical responses. The method additionally includes searching at a second stage a content management system (CMS) to determine if there is at least one similar response to at least one historical response in each response group. The CMS is configured to store standard responses to anticipated queries.

Abstract: Provided are a memory device and a method of forming the same. The memory device includes: a selector; a magnetic tunnel junction (MTJ) structure, disposed on the selector; a spin orbit torque (SOT) layer, disposed between the selector and the MTJ structure, wherein the SOT layer has a sidewall aligned with a sidewall of the selector; a transistor, wherein the transistor has a drain electrically coupled to the MTJ structure; a word line, electrically coupled to a gate of the transistor; a bit line, electrically coupled to the SOT layer; a first source line, electrically coupled to a source of the transistor; and a second source line, electrically coupled to the selector, wherein the transistor is configured to control a write signal flowing between the bit line and the second source line, and control a read signal flowing between the bit line and the first source line.

Abstract: A dynamic random access memory applied to an embedded display port includes a memory core unit, a peripheral circuit unit, and an input/output unit. The memory core unit is used for operating in a first predetermined voltage. The peripheral circuit unit is electrically connected to the memory core unit for operating in a second predetermined voltage, where the second predetermined voltage is lower than 1.1V. The input/output unit is electrically connected to the memory core unit and the peripheral circuit unit for operating in a third predetermined voltage, where the third predetermined voltage is lower than 1.1V.

Abstract: Methods, systems, and computer programs are presented for generating workflows, by a computer program, for a desired task. One system includes a workflow engine and a workflow recommender. The workflow engine is to train a machine-learning algorithm (MLA) utilizing a plurality of learning sequences, each learning sequence comprising a learning context, at least one learning step, and a learning result; receive a workflow definition that includes at least one input context and a desired result, the input context including at least one input constraint; generate, utilizing the MLA, at least one result sequence that implements the workflow definition, each result sequence including a plurality of steps; and select one of the at least one result sequence. The workflow recommender is to cause the selected result sequence to be presented on a display.

Abstract: An embodiment of a semiconductor package apparatus may include technology to test a target query for one or more similarity metrics over a range of parameters for one or more sets of sequence related information, a multi-domain sequence model, and one or more training routines, select a set of parameters based on a result of the test, and automatically configure the multi-domain sequence model to adapt to one or more of respective data sets, respective prediction tasks, and respective recommendation tasks based on the selected parameters. Other embodiments are disclosed and claimed.

Abstract: Analogies among entities may be detected by obtaining associative counts among the entities and computing similarity measures among given entities and other entities, using the associative counts. First and second entities are then identified as being analogies if the first entity has a strongest similarity measure with respect to the second entity and the second entity also has a strongest similarity measure with respect to the first entity. The similarity measures may be calculated using a normalized entropy inverted among a given entity and other entities.

Abstract: Systems, methods and computer program products are provided for a distributed associative memory base. Such methods may include providing a distributed memory base that includes a network of networks of associative memory networks. The memory base may include a network of associative memory networks, a respective associative memory network comprising associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity. Ones of the associative memory networks are physically and/or logically independent from other ones of the associative memory networks. Methods include imagining associations from the associative memory base using a plurality of streaming queues that correspond to ones of a plurality of rows of ones of the associative memory networks.

Abstract: Systems, methods and computer program products are provided for a distributed associative memory base. Such methods may include providing a distributed memory base that includes a network of networks of associative memory networks. The memory base may include a network of associative memory networks, a respective associative memory network comprising associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity. Ones of the associative memory networks are physically and/or logically independent from other ones of the associative memory networks. Methods include imagining associations from the associative memory base using a plurality of streaming queues that correspond to ones of a plurality of rows of ones of the associative memory networks.

Abstract: Systems, methods and computer program products are provided for a distributed associative memory base. Such methods may include providing a distributed memory base that includes a network of networks of associative memory networks. The memory base may include a network of associative memory networks, a respective associative memory network comprising associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity. Ones of the associative memory networks are physically and/or logically independent from other ones of the associative memory networks. Methods include imagining associations from the associative memory base using a plurality of streaming queues that correspond to ones of a plurality of rows of ones of the associative memory networks.

Abstract: Analogies among entities may be detected by obtaining associative counts among the entities and computing similarity measures among given entities and other entities, using the associative counts. First and second entities are then identified as being analogies if the first entity has a strongest similarity measure with respect to the second entity and the second entity also has a strongest similarity measure with respect to the first entity. The similarity measures may be calculated using a normalized entropy inverted among a given entity and other entities.

Abstract: Analogies among entities may be detected by obtaining associative counts among the entities and computing similarity measures among given entities and other entities, using the associative counts. First and second entities are then identified as being analogies if the first entity has a strongest similarity measure with respect to the second entity and the second entity also has a strongest similarity measure with respect to the first entity. The similarity measures may be calculated using a normalized entropy inverted among a given entity and other entities.

Abstract: Analogies among entities may be detected by obtaining associative counts among the entities and computing similarity measures among given entities and other entities, using the associative counts. First and second entities are then identified as being analogies if the first entity has a strongest similarity measure with respect to the second entity and the second entity also has a strongest similarity measure with respect to the first entity. The similarity measures may be calculated using a normalized entropy inverted among a given entity and other entities.

Abstract: A method and apparatus for preventing exchange of viruses. Preexisting content is maintained for a device in a first location. New content associated with the device is placed in a second location, wherein the new content is an update to the preexisting content. The preexisting content and the new content are combined in a third location to form merged content. A check for viruses is performed on the merged content prior to performing a transfer of the new content.

Abstract: A method, system, and computer program product for establishing security parameters that are used to exchange data on a secure connection. A piggy-backed key exchange protocol is defined, with which these security parameters are advantageously exchanged. By piggy-backing the key exchange onto other already-required messages (such as a client's HTTP GET request, or the server's response thereto), the overhead associated with setting up a secure browser-to-server connection is minimized. This technique is defined for a number of different scenarios, where the client and server may or may not share an encoding scheme, and is designed to maintain the integrity of application layer communication protocols. In one scenario, a client requests a server to propose a message encoding scheme. If the client has security-sensitive data to transmit with its request, it waits for the proposed scheme before sending this sensitive data to the server.

Abstract: A method, system, and computer program product for establishing security parameters that are used to exchange data on a secure connection. A piggy-backed key exchange protocol is defined, with which these security parameters are advantageously exchanged. By piggy-backing the key exchange onto other already-required messages (such as a client's HTTP GET request, or the server's response thereto), the overhead associated with setting up a secure browser-to-server connection is minimized. This technique is defined for a number of different scenarios, where the client and server may or may not share an encoding scheme, and is designed to maintain the integrity of application layer communication protocols. In one scenario, a client and server share a common message encoding scheme.

Abstract: A method, system, and computer program product for establishing security parameters that are used to exchange data on a secure connection. A piggy-backed key exchange protocol is defined, with which these security parameters are advantageously exchanged. By piggy-backing the key exchange onto other already-required messages (such as a client's HTTP GET request, or the server's response thereto), the overhead associated with setting up a secure browser-to-server connection is minimized. This technique is defined for a number of different scenarios, where the client and server may or may not share an encoding scheme, and is designed to maintain the integrity of application layer communication protocols. In one scenario, a client proposes a message encoding scheme, but the server will not use this proposed scheme. The server proposes a different scheme, after which the client re-issues its request for secure content.

Abstract: Artificial neural networks include a plurality of artificial neurons and a plurality of Boolean-complete compartments, a respective one of which couples a respective pair of artificial neurons. By providing Boolean-complete compartments, spurious complement memories can be avoided. A Boolean-complete compartment includes a collection of at least four Boolean functions that represent input vectors to the respective pair of artificial neurons. The collection of at least four Boolean functions are selected from sixteen possible Boolean functions that can represent input vectors to the respective pair of artificial neurons. A count for each of the at least four Boolean functions is also provided. The count represents a number of occurrences of each of the at least four Boolean functions in input vectors to the respective pair of artificial neurons.