Abstract: An approach is provided for removing outliers from road lane marking data (e.g., using two-phase filtering). The approach involves processing spatial data points representing a road lane into clusters, and filtering cluster(s) away from a main cluster from the clusters to generate an initial filtered data point set. The approach also involves calculating a degree of relationship among the data points of the initial filtered set based on a distance metric to generate group node(s) of the initial filtered set. The approach further involves for each group node, determining a probability that a spatial data point belongs in said each group node by comparing the spatial data point to a center of said each group node, and filtering the spatial data point from said each group node based on determining that the probability is less than a threshold to generate a final filtered data point set.

Abstract: An approach is provided for semantic filtering to filter an input data stream of a data system to reduce an amount of data processed by the data system. The approach, for example, involves retrieving training data comprising a plurality of training data items responsive to a plurality of training queries conducted in a data system. The approach also involves performing a vectorization and a tokenization of the training data to generate a plurality of vectors comprising a plurality of tokens extracted from the plurality of training data items. The approach also involves computing a plurality of reference semantic scores for the plurality of vectors based on a semantic distance between the plurality of tokens. The approach also involves transforming the plurality of reference semantic scores into a plurality of transformed reference semantic scores based on a modulation function. The approach also involves fitting a filtering function to the plurality of transformed reference semantic scores.

Abstract: An approach is provided for removing outliers from road lane marking data (e.g., using two-phase filtering). The approach involves processing spatial data points representing a road lane into clusters, and filtering cluster(s) away from a main cluster from the clusters to generate an initial filtered data point set. The approach also involves calculating a degree of relationship among the data points of the initial filtered set based on a distance metric to generate group node(s) of the initial filtered set. The approach further involves for each group node, determining a probability that a spatial data point belongs in said each group node by comparing the spatial data point to a center of said each group node, and filtering the spatial data point from said each group node based on determining that the probability is less than a threshold to generate a final filtered data point set.

Abstract: An approach is provided for a homomorphic cryptosystem for use in resource-constrained environments (e.g., vehicle-based use cases) or when computer resources are to be conserved. The approach involves, for example, generating a nonce at a first device (e.g., vehicle engine control unit (ECU)). The approach also involves performing a homomorphic operation on the nonce and a ciphertext to generate a resulting cipher. The ciphertext is provided by a second device (e.g., a data server). The approach further involves attaching the resulting cipher to a request payload (e.g., to request secure data from the data server). The approach further involves transmitting the request payload including the nonce to the second device (e.g., the server).

Abstract: An approach is provided for automatically identifying abandoned applications and services. The approach includes determining application management data related to the application. The application management data includes characteristics indicating a lifecycle of the application within a computing infrastructure. The approach also includes extracting one or more features from the application management data. The approach further includes processing the one or more features using a trained machine learning model to classify the abandonment status of the application, wherein the abandonment status includes an abandoned state and a non-abandoned state.

Abstract: An approach is provided for estimating cloud utilization and recommending instance type. The approach involves receiving resource usage data for an instance of an application. The instance is executed on a cloud computing infrastructure, and the resource usage relates to one or more resources of the cloud computing infrastructure. The approach also involves processing the resource usage data to calculate average and maximum usage values of the resources of the instance. The approach further involves calculating an upper usage bound and a lower usage bound between which the instance is estimated to operate based on the average and maximum usage values of the resources. The approach further involves determining a recommended instance type for instantiating the application in the cloud computing infrastructure based on the upper usage bound and the lower usage bound. The approach further involves providing the recommended instance type as an output.

Abstract: An approach is provided for a homomorphic cryptosystem for use in resource-constrained environments (e.g., vehicle-based use cases) or when computer resources are to be conserved. The approach involves, for example, generating a nonce at a first device (e.g., vehicle engine control unit (ECU)). The approach also involves performing a homomorphic operation on the nonce and a ciphertext to generate a resulting cipher. The ciphertext is provided by a second device (e.g., a data server). The approach further involves attaching the resulting cipher to a request payload (e.g., to request secure data from the data server). The approach further involves transmitting the request payload including the nonce to the second device (e.g., the server).

Abstract: An approach is provided for semantic filtering to filter an input data stream of a data system to reduce an amount of data processed by the data system. The approach, for example, involves retrieving training data comprising a plurality of training data items responsive to a plurality of training queries conducted in a data system. The approach also involves performing a vectorization and a tokenization of the training data to generate a plurality of vectors comprising a plurality of tokens extracted from the plurality of training data items. The approach also involves computing a plurality of reference semantic scores for the plurality of vectors based on a semantic distance between the plurality of tokens. The approach also involves transforming the plurality of reference semantic scores into a plurality of transformed reference semantic scores based on a modulation function. The approach also involves fitting a filtering function to the plurality of transformed reference semantic scores.

Abstract: An approach is provided for automatically identifying abandoned applications and services. The approach includes determining application management data related to the application. The application management data includes characteristics indicating a lifecycle of the application within a computing infrastructure. The approach also includes extracting one or more features from the application management data. The approach further includes processing the one or more features using a trained machine learning model to classify the abandonment status of the application, wherein the abandonment status includes an abandoned state and a non-abandoned state.

Abstract: A medicine ball comprises a cover made of a sheet of aramid fibers, having an exterior surface and an interior surface, that each comprise a coating of a polychloroprene compound. The coating is spread unevenly and is calendered across both the exterior surface of the cover and the interior surface of the cover. The exterior surface of the cover is embossed, which in addition to vulcanization, provides extra grip strength. The ball further comprises an interior space, which is filled with crushed pieces of ethylene vinyl acetate foam and rocks.

Abstract: A method for representing decision trees that avoids the common problem of congestion and overlapping of the nodes in the tree. This problem has traditionally limited the number of nodes and uncertainties that can be represented using decision trees. The approach provides a method and formulation for plotting the coordinates of the decision tree in a way that avoids the problem of congestion of the nodes by drawing the tree in reverse chronological order.

Abstract: In some examples, a method includes determining, with an Uninterruptible Power Supply (UPS), a power state of the UPS; determining, with the UPS, a power state of a device attached to the UPS; determining, with the UPS, whether an action to modify an operating state of the device attached to the UPS should be initiated based on the determined power state of the UPS and the power state of the device attached to the UPS; and initiating, with the UPS, the action to modify the operating state of the device attached to the UPS when it is determined by the UPS that the action should be initiated.

Abstract: A method for representing decision trees that avoids the common problem of congestion and overlapping of the nodes in the tree. This problem has traditionally limited the number of nodes and uncertainties that can be represented using decision trees. The approach provides a method and formulation for plotting the coordinates of the decision tree in a way that avoids the problem of congestion of the nodes by drawing the tree in reverse chronological order.

Abstract: A method for making a decision includes receiving a first decision question from a first user, providing a database of information regarding elements of decision quality, populating the database with data corresponding to each element of decision quality as applied to the first decision question, and providing a decision recommendation for the first decision question based at least in part on the data.

Abstract: A method for making a decision includes receiving a first decision question from a first user, providing a database of information regarding elements of decision quality, populating the database with data corresponding to each element of decision quality as applied to the first decision question, and providing a decision recommendation for the first decision question based at least in part on the data.