Abstract: There is provided an energy transaction platform to facilitate a wholesale?distribution?DER owner marketplace for DER-based energy products, including contracting, delivery, and settlement, for example, based on blockchain technology. The platform provides components to enrol and verify DER owners having a DER device. Platform components define and communicate contracts for energy services for bidding by DER owners to facilitate e.g. EV charging, GHG reduction, or demand response goals. Contracts are cleared in response to bidding, for example, by DER owners. The platform triggers contract delivery, which delivery is monitored and confirmed. Settlement is made between contract parties according to confirmed participation. Participation rewards and/or credit tokens are transferrable to DER owners, which can be further transferred. DER owner credibility measures can encourage participation and assist with clearing contracts.

Abstract: Presented herein are systems and methods for merging and manipulating data from different sources of clinical trial data. Clinical trial data is collected using multiple different ‘forms’ and can be from either a single clinical trial or from multiple clinical trials. In certain embodiments, the systems and methods described herein are provided in the form of an intuitive graphical user interface (GUI) that enables a user to merge and manipulate data from two or more source tables of clinical trial data associated with one or more clinical studies to produce a custom merged table, without having to rely upon complex computer code.

Abstract: Systems and methods are described for providing a predictive session-based search engine. A predictive session-based search engine may identify and pre-fetch data from various data sources that is likely to be accessed during a particular session. Data sources may include other search engines, databases, web servers, and other sources of information. A plug-in controller architecture, which may include templates, computer-executable instructions, application programming interface (API) calls, or other information that enables access to a particular data source, may be used to allow the predictive session-based search engine to obtain data from the data sources. The predictive session-based search engine may store and index the data it obtains, and may answer search queries during the session with data that is stored and indexed locally rather than retrieving data from the original sources.

Abstract: Techniques for offering an item that may be otherwise unavailable from an electronic marketplace may be provided. For example, based on receiving information about the item from a consumer, a template describing the item may be generated. Information based on the template may be transmitted to subscribed merchants and may allow one or more of the subscribed merchants to offer the item. If an offer is received, a data exchange between a corresponding merchant and the consumer may be facilitated. The data exchange may allow the merchant to offer the item to the consumer.

Abstract: Presented herein are systems and methods for merging and manipulating data from different sources of clinical trial data. Clinical trial data is collected using multiple different ‘forms’ and can be from either a single clinical trial or from multiple clinical trials. In certain embodiments, the systems and methods described herein are provided in the form of an intuitive graphical user interface (GUI) that enables a user to merge and manipulate data from two or more source tables of clinical trial data associated with one or more clinical studies to produce a custom merged table, without having to rely upon complex computer code.

Abstract: Presented herein are systems, methods, and architectures related to a scalable and platform-agnostic framework that leverages multiple pluggable connectors to retrieve clinical trial data from different data sources (e.g. corresponding to different systems used to collect and manage data collected over the course of a clinical trial). The clinical connector technology described herein transforms the retrieved data to one or more standardized representations using one or more pre-defined data models. By providing clinical trial data to the client applications of stakeholders in one or more standardized formats (e.g. represented according to a standardize pre-defined data model), irrespective of the source of the clinical trial data, the systems, methods, and architectures described herein obviate the need for stakeholders to modify their workflow depending on the particular source.

Abstract: Presented herein are systems and methods to automatically and periodically retrieve clinical trial data from an EDC source, process the data to transform it from its initial representation as retrieved from the EDC source into table-based format, and store the resultant transformed data in an intermediate data storage layer for access by stakeholders. Accordingly, instead of accessing source data, such as EDC ODM-XML data directly from an EDC source, a stakeholder may retrieve clinical trial data from the transformed data stored in the data storage layer. The systems and methods provide transformed data that better serves the needs of stakeholders during a clinical trial.

Abstract: Biometric authentication technology, in which biometric data is maintained for a group of people. The biometric data includes sorted similarity scores, where each of the sorted similarity scores is computed to represent similarity between a corresponding biometric image and a reference image. A biometric verification system accesses a biometric image of at least a portion of a person, accesses the reference image, and computes a similarity score that represents similarity between the accessed biometric image and the reference image. The biometric verification system searches the sorted similarity scores included in the biometric data using the computed similarity score and outputs a result based on the searching.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: Biometric authentication technology, in which biometric data is maintained for a group of people. The biometric data includes sorted similarity scores, where each of the sorted similarity scores is computed to represent similarity between a corresponding biometric image and a reference image. A biometric verification system accesses a biometric image of at least a portion of a person, accesses the reference image, and computes a similarity score that represents similarity between the accessed biometric image and the reference image. The biometric verification system searches the sorted similarity scores included in the biometric data using the computed similarity score and outputs a result based on the searching.

Abstract: Biometric authentication technology, in which biometric data is maintained for a group of people. The biometric data includes sorted similarity scores, where each of the sorted similarity scores is computed to represent similarity between a corresponding biometric image and a reference image. A biometric verification system accesses a biometric image of at least a portion of a person, accesses the reference image, and computes a similarity score that represents similarity between the accessed biometric image and the reference image. The biometric verification system searches the sorted similarity scores included in the biometric data using the computed similarity score and outputs a result based on the searching.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.

Abstract: Biometric matching technology, in which a watch list is managed, multiple images of a potential suspect are accessed, and parallel pre-processing of the multiple images is controlled. Based on the pre-processing, an image of the potential suspect to use in matching against the watch list is determined and the determined image is used to search sorted biometric data included in the watch list. A subset of persons from the watch list is identified based on the search and parallel analysis of the determined image of the potential suspect against detailed biometric data associated with the subset of persons in the watch list is controlled. Based on the parallel analysis, it is determined whether the potential suspect matches a person in the watch list and a result is outputted based on the determination.