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Articles 1 - 3 of 3
Full-Text Articles in Databases and Information Systems
E-Transcript Web Services System Supporting Dynamic Conversion Between Xml And Edi, Myungjae Kwak '11, Woohyun Kang '14, Gondy Leroy, Samir Chatterjee
E-Transcript Web Services System Supporting Dynamic Conversion Between Xml And Edi, Myungjae Kwak '11, Woohyun Kang '14, Gondy Leroy, Samir Chatterjee
CGU Faculty Publications and Research
As XML becomes a standard for communications between distributed heterogeneous machines, many schools plan to implement Web Services systems using the XML e-transcript (electronic transcript) standard. We propose a framework that supports both XML e-transcript Web Services and existing EDI e-transcript systems. The framework uses the workflow engine to exploit the benefits of workflow management mechanisms. The workflow engine manages the e-transcript business process by enacting and completing the tasks and sub-processes within the main business process. We implemented the proposed framework by using various open source projects including Java, Eclipse, and Apache Software Foundation’s Web Services projects. Compared with …
Location-Based Hashing For Querying And Searching, Felix Ching
Location-Based Hashing For Querying And Searching, Felix Ching
Computer Science and Computer Engineering Undergraduate Honors Theses
The rapidly growing information technology in modern days demands an efficient searching scheme to search for desired data. Locality Sensitive Hashing (LSH) is a method for searching similar data in a database. LSH achieves high accuracy and precision for locating desired data, but consumes a significant amount of memory and time. Based on LSH, this thesis presents two novel schemes for efficient and accurate data searching: Locality Sensitive Hashing-SmithWaterman (LSH-SmithWaterman) and Secure Min-wise Locality Sensitive Hashing (SMLSH). Both methods dramatically reduce the memory and time consumption and exhibit high accuracy in data searching. Simulation results demonstrate the efficiency of the …
Integrating Temporal Difference Methods And Self‐Organizing Neural Networks For Reinforcement Learning With Delayed Evaluative Feedback, Ah-Hwee Tan, Ning Lu, Dan Xiao
Integrating Temporal Difference Methods And Self‐Organizing Neural Networks For Reinforcement Learning With Delayed Evaluative Feedback, Ah-Hwee Tan, Ning Lu, Dan Xiao
Research Collection School Of Computing and Information Systems
This paper presents a neural architecture for learning category nodes encoding mappings across multimodal patterns involving sensory inputs, actions, and rewards. By integrating adaptive resonance theory (ART) and temporal difference (TD) methods, the proposed neural model, called TD fusion architecture for learning, cognition, and navigation (TD-FALCON), enables an autonomous agent to adapt and function in a dynamic environment with immediate as well as delayed evaluative feedback (reinforcement) signals. TD-FALCON learns the value functions of the state-action space estimated through on-policy and off-policy TD learning methods, specifically state-action-reward-state-action (SARSA) and Q-learning. The learned value functions are then used to determine the …