Browsing KINDI Center for Computing Research by Publisher "IEEE Computer Society"
Now showing items 1-6 of 6
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A model driven framework for secure outsourcing of computation to the cloud
( IEEE Computer Society , 2014 , Conference)This paper presents a model driven approach to define then coordinate the execution of protocols for secure outsourcing of computation of large datasets in cloud computing environments. First we present our Outsourcing ... -
Analysis of Predictive Models for Revealing Household Characteristics using Smart Grid Data
( IEEE Computer Society , 2023 , Conference)The Smart Grid Advanced Metering Infrastructure (AMI) has revolutionized the smart grid network, generating vast amounts of data that can be utilized for diverse objectives, one of which is Household Characteristics ... -
Orthogonal Experimental Design Based Binary Optimization Without Iteration for Fault Section Diagnosis of Power Systems
( IEEE Computer Society , 2024 , Article)Fault section diagnosis (FSD) is considerably indispensable for the continuous and reliable electricity supply. In general, the analytical model of FSD is solved by derivative-free intelligent metaheuristic algorithms. ... -
Probabilistic Wind Power Forecasting Using Optimized Deep Auto-Regressive Recurrent Neural Networks
( IEEE Computer Society , 2023 , Article)Wind power forecasting is very crucial for power system planning and scheduling. Deep neural networks (DNNs) are widely used in forecasting applications due to their exceptional performance. However, the DNNs' architectural ... -
Similarity Group-by Operators for Multi-Dimensional Relational Data
( IEEE Computer Society , 2016 , Conference)The SQL group-by operator plays an important role in summarizing and aggregating large datasets in a data analytics stack. While the standard group-by operator, which is based on equality, is useful in several applications, ... -
Wireless Network Slice Assignment with Incremental Random Vector Functional Link Network
( IEEE Computer Society , 2022 , Article)This paper presents an artificial intelligence-assisted network slice prediction method, which utilizes a novel incremental random vector functional link (IRVFL) network to deal with the wireless network slice assignment ...