Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize transformation and projection layers to implement neural networks in tabular data environments. For example, the disclosed systems identify tabular data sets and segregate measured tabular data values and placeholder tabular data values. In one or more embodiments, the disclosed systems transform the measured tabular data values to a neural network value range based on the distribution of the measured tabular data values. Moreover, the disclosed systems replace placeholder tabular data values with a constant value within the neural network value range. In addition, the disclosed systems identify numerical values and utilize a projection layer to generate feature vectors within a high-dimensionality feature space. In one or more embodiments, the disclosed systems utilize the resulting high-dimensionality tabular data set with a neural network to generate prediction results (e.g.

Abstract: A method, apparatus, system, and computer program code for forecasting a data anomaly to a supply chain. A plurality of data records is identified for a plurality of entities. The data records include import records and export records. The data fields in the data records are categorized into generic field types. The generic field types include numeric fields, categorical fields, and date fields. For each of the plurality of entities, an entity-specific model is constructed for forecasting imports and exports based on the generic field types. The entity-specific model for each of the plurality of entities is combined into a global supply chain model. Based on the global supply chain model, a data anomaly is forecast to a supply chain that is associated with a particular entity.

Abstract: A method for identifying a parent company in a corporate hierarchy is provided. A neural network embeds a number of company names into respective numeric vectors and then indexes the vectors into an approximate nearest neighbors (ANN) index according to euclidean distances between them. In response to a query regarding a parent company of a specified query company, a top N number of nearest neighbor companies to the query company is extracted from the ANN index. A machine learning voting model determines which, if any, of the extracted nearest neighbor companies has a parent company that best corresponds to the query company. If an extracted nearest neighbor company has a parent company that best corresponds to the query company, the parent company is displayed to a user through a user interface.

Abstract: A method, apparatus, system, and computer program code for forecasting a data anomaly to a supply chain. A plurality of data records is identified for a plurality of entities. The data records include import records and export records. The data fields in the data records are categorized into generic field types. The generic field types include numeric fields, categorical fields, and date fields. For each of the plurality of entities, an entity-specific model is constructed for forecasting imports and exports based on the generic field types. The entity-specific model for each of the plurality of entities is combined into a global supply chain model. Based on the global supply chain model, a data anomaly is forecast to a supply chain that is associated with a particular entity.

Abstract: According to one embodiment, an electronic apparatus includes a first unit, a second unit, a shaft, a first engaging portion, a moving portion, a second engaging portion, a first magnet, a second magnet, and a metal member. The second engaging portion is movable in a vicinity of the moving portion and configured to restrict a movement of the moving portion when the second engaging portion is engaged with the first engaging portion. The second magnet is configured to act repulsively against the first magnet. The metal member is configured to release engagement between the first engaging portion and the second engaging portion by attracting the second engaging portion when the metal member is inserted between the first magnet and the second magnet.

Abstract: According to one embodiment, an electronic apparatus includes a housing, a switch, a button member and a supporting portion. The housing has an opening. The button member includes an operating portion, a rocker shaft and an acting portion. The operating portion is exposed through the opening. The shaft is coupled to the operating portion and pivotable. The acting portion is coupled to the shaft, configured to face the switch and to pivot about the shaft, thereby pressing the switch. The supporting portion is configured to support the button member, the supporting portion being configured to be elastically deformed by part of the button member and to return the button member.

Abstract: According to one embodiment, an electronic apparatus includes a first unit, a second unit, a shaft, a first engaging portion, a moving portion, a second engaging portion, a first magnet, a second magnet, and a metal member. The second engaging portion is movable in a vicinity of the moving portion and configured to restrict a movement of the moving portion when the second engaging portion is engaged with the first engaging portion. The second magnet is configured to act repulsively against the first magnet. The metal member is configured to release engagement between the first engaging portion and the second engaging portion by attracting the second engaging portion when the metal member is inserted between the first magnet and the second magnet.

Abstract: According to one embodiment, an electronic apparatus includes a housing, a switch, a button member and a supporting portion. The housing has an opening. The button member includes an operating portion, a rocker shaft and an acting portion. The operating portion is exposed through the opening. The shaft is coupled to the operating portion and pivotable. The acting portion is coupled to the shaft, configured to face the switch and to pivot about the shaft, thereby pressing the switch. The supporting portion is configured to support the button member, the supporting portion being configured to be elastically deformed by part of the button member and to return the button member.

Abstract: Methods, systems, and computer program products are provided for deploying an application.

Abstract: Methods, systems, and computer program products are provided for deploying an application.

Abstract: A method and apparatus to obtain unique study content that is selected based on user's study goals and unique preferences includes having a user input a study goal and study preference. Then a first database of learning content, that may be traditional learning content prepared by an education institution, is queried based on the input study goal and preferences and study items are extracted from the first database. Then, the study items extracted from the first database are stored in a second database, the study items stored in the second database are then used to query a third database of potential learning content, which may include non-traditional learning content, and by matching the study items stored in the second database to content in the third database, study content that has been specifically tailored and personalized based on the user's input study goals and preferences is extracted and presented to the user for study and learning.