KINDI Center for Computing Research: Recent submissions
Now showing items 61-80 of 250
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Online dynamic ensemble deep random vector functional link neural network for forecasting
( Elsevier , 2023 , Article)This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). The edRVFL stacks multiple randomized layers to enhance the single-layer RVFL's ... -
A spectral-ensemble deep random vector functional link network for passive brain-computer interface
( Elsevier , 2023 , Article)Randomized neural networks (RNNs) have shown outstanding performance in many different fields. The superiority of having fewer training parameters and closed-form solutions makes them popular in small datasets analysis. ... -
Online learning using deep random vector functional link network
( Elsevier , 2023 , Article)Deep neural networks have shown their promise in recent years with their state-of-the-art results. Yet, backpropagation-based methods may suffer from time-consuming training process and catastrophic forgetting when performing ... -
A problem-specific knowledge based artificial bee colony algorithm for scheduling distributed permutation flowshop problems with peak power consumption
( Elsevier , 2023 , Article)A distributed permutation flowshop scheduling problem (DPFSP) with peak power consumption is addressed in this work. The instantaneous energy consumption of each factory cannot exceed a threshold. First, a mathematical ... -
Problem feature based meta-heuristics with Q-learning for solving urban traffic light scheduling problems
( Elsevier , 2023 , Article)An urban traffic light scheduling problem (UTLSP) is studied by using problem feature based meta-heuristics with Q-learning. The goal is to minimize the network-wise total delay time within a time window by finding a ... -
An evolutionary multiobjective method based on dominance and decomposition for feature selection in classification
( Science China Press , 2024 , Article)Feature selection in classification can be considered a multiobjective problem with the objectives of increasing classification accuracy and decreasing the size of the selected feature subset. Dominance-based and ... -
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 ... -
UNIFIED DISCRETE DIFFUSION FOR SIMULTANEOUS VISION-LANGUAGE GENERATION
( International Conference on Learning Representations, ICLR , 2023 , Conference)The recently developed discrete diffusion models perform extraordinarily well in the text-to-image task, showing significant promise for handling the multi-modality signals. In this work, we harness these traits and present ... -
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. ... -
Support Vector Machine Based Models with Sparse Auto-encoder Based Features for Classification Problem
( Springer Science and Business Media Deutschland GmbH , 2023 , Conference)Auto-encoder is a special type of artificial neural network (ANN) that is used to learn informative features from data. In the literature, the generalization performance of several machine learning models have been improved ... -
Double Regularization-Based RVFL and edRVFL Networks for Sparse-Dataset Classification
( Springer Science and Business Media Deutschland GmbH , 2023 , Conference)In our previous work, the random vector functional link network (RVFL) and the ensemble deep RVFL network (edRVFL) have been proven to be competitive for tabular-dataset classification, and their sparse pre-trained versions ... -
Adaptive Scaling for U-Net in Time Series Classification
( Springer Science and Business Media Deutschland GmbH , 2023 , Conference)Convolutional Neural Networks such as U-Net are recently getting popular among researchers in many applications, such as Biomedical Image Segmentation. U-Net is one of the popular deep Convolutional Neural Networks which ... -
Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring
( IEEE , 2024 , Article)The traditional healthcare system is increasingly challenged by its dependence on inperson consultations and manual monitoring, struggling with issues of scalability, the immediacy of care, and efficient resource allocation. ... -
The Future of Aerial Communications: A Survey of IRS-Enhanced UAV Communication Technologies
( IEEE , 2024 , Conference)The advent of Intelligent Reflecting Surfaces (IRS) and Unmanned Aerial Vehicles (UAVs) is setting a new benchmark in the field of wireless communications. IRS, with their groundbreaking ability to manipulate electromagnetic ... -
Security-Driven Performance Analysis of Lightweight Cryptography for Energy Efficiency Applications
( IEEE , 2024 , Conference)This paper provides a comprehensive analysis of the security-centric performance of the Lightweight Cryptography (LWC) algorithms ASCON, TinyJambu, and Xoodyak, finalists in the NIST standardization process, through their ... -
Improved Handshaking Procedures for Transport Layer Security in Software Defined Networks
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference)Software defined networking (SDN) has emerged as a new technology to enhance the flexibility, resilience, and automated centralized management of a network. Recently several reports have identified possible vulnerabilities, ... -
A Blockchain-Based Security Scheme for Vehicular Ad Hoc Networks in Smart Cities
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference)The development of Vehicular Ad Hoc Networks (VANET) has brought many advantages to facilitate the deployment of the Intelligent Transportation System (ITS). However, without proper protection, VANETs can be vulnerable to ... -
Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey
( Elsevier , 2024 , Article)Mobile devices have become an essential element in our day-to-day lives. The chances of mobile attacks are rapidly increasing with the growing use of mobile devices. Exploiting vulnerabilities from devices as well as ... -
Securing Aggregate Queries for DNA Databases
( Institute of Electrical and Electronics Engineers Inc. , 2019 , Article)This paper addresses the problem of sharing person-specific genomic sequences without violating the privacy of their data subjects to support large-scale biomedical research projects. The proposed method builds on the ... -
Battery-Induced Load Hiding and Its Utility Consequences
( Institute of Electrical and Electronics Engineers Inc. , 2024 , Conference)The introduction of smart grids allows utility providers to collect detailed data about consumers, which can be utilized to enhance grid efficiency and reliability. However, this data collection also raises privacy concerns. ...
