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Traffic Management in Internet of Vehicles Using Improved Ant Colony Optimization

computers, Materials & Continua 2023年第6期75卷 5379-5393页

作者： Abida Sharif Imran Sharif Muhammad Asim Saleem Muhammad Attique Khan Majed Alhaisoni Marriam Nawaz Abdullah Alqahtani Ye Jin Kim Byoungchol Chang Department of Computer Science COMSATS University IslamabadPakistan Faculty of Computing Riphah International UniversityFaisalabadPakistan Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science UET TaxilaTaxilaPakistan Department of Software Engineering UET TaxilaTaxilaPakistan Software Engineering Department College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942KSA Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

The Internet of Vehicles(IoV)is a networking paradigm related to the intercommunication of vehicles using a *** a dynamic network,one of the key challenges in IoV is traffic management under increasing vehicles to avoid ***,optimal path selection to route traffic between the origin and destination is *** research proposed a realistic strategy to reduce traffic management service response time by enabling real-time content distribution in IoV systems using heterogeneous network ***,this work proposed a novel use of the Ant Colony Optimization(ACO)algorithm and formulated the path planning optimization problem as an Integer Linear Program(ILP).This integrates the future estimation metric to predict the future arrivals of the vehicles,searching the optimal *** the mobile nature of IOV,fuzzy logic is used for congestion level estimation along with the ACO to determine the optimal *** model results indicate that the suggested scheme outperforms the existing state-of-the-art methods by identifying the shortest and most cost-effective ***,this work strongly supports its use in applications having stringent Quality of Service(QoS)requirements for the vehicles.

关键词： Internet of vehicles internet of things fuzzy logic optimization path planning

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Human brain computing and brain-inspired intelligence

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National Science Review 2024年第5期11卷 8-9页

作者： Jianfeng Feng Viktor Jirsa Wenlian Lu Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence(Fudan University) Ministry of Education Shanghai Center for Mathematical Sciences Fudan University Department of Computer Science University of Warwick Zhangjiang Fudan International Innovation Center Institut de Neurosciences des Systèmes Faculté de Medécine

The relationship between structure, neural activity dynamics and intelligent human brain function is complex and multifaceted with deep roots in several academic disciplines. Its understanding is a fundamental goal of brain research [1] and may indicate the way towards the next generation of artificial intelligence [2]. There are major challenges on the way, several of which are addressed in this Special Topic of National Science Review.

关键词： intelligence human brain-inspired computing

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Feedforward Regulation of Interneuronal Communication 63

Feedforward Regulation of Interneuronal Communication

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Gambrell, Oliver Vahdat, Zahra Singh, Abhyudai University of Delaware Department of Electrical and Computer Engineering NewarkDE19716 United States University of Delaware Biomedical Engineering Mathematical Sciences Center for Bioinformatics and Computational Biology Department of Electrical and Computer Engineering NewarkDE19716 United States

ISBN: (纸本)9798350316339

We formulate a mechanistic model capturing the dynamics of neurotransmitter release in a chemical synapse. The proposed modeling framework captures key aspects such as the random arrival of action potentials (AP) in the presynaptic (input) neuron, probabilistic docking and release of neurotransmitter-filled vesicles, and clearance of the released neurotransmitter from the synaptic cleft. Analysis of the model results in analytical expressions for the statistical moments of docked vesicle count and the number of neurotransmitters in the cleft as a function of model parameters, and the frequency of presynaptic APs. We next consider a postsynaptic (output) neuron that fires an AP based on integrating upstream neurotransmitter activity. Our results show the existence of an optimal presynaptic AP frequency that maximizes the probability of a postsynaptic AP firing. We extend these results to consider feedforward regulation where in addition to a direct excitatory synapse, the input neuron also impacts the output indirectly via an inhibitory interneuron, and identify parameter regimes where the feedforward neuronal networks result in band-pass filtering, i.e., the output neuron frequency is maximized at intermediate input neuron frequencies. © 2024 IEEE.

关键词： Feedforward neural networks

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Quantifying statistics of gene product copy-number fluctuations: A stochastic hybrid systems approach 63

Quantifying statistics of gene product copy-number fluctuati...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Vahdat, Zahra Singh, Abhyudai University of Delaware Department of Electrical and Computer Engineering NewarkDE19716 United States University of Delaware Department of Electrical and Computer Engineering Biomedical Engineering Mathematical Sciences Center for Bioinformatics and Computational Biology NewarkDE19716 United States

ISBN: (纸本)9798350316339

Across diverse cell types, genes are often expressed at low levels resulting in significant stochastic fluctuations (noise) in intracellular copy number of mRNAs and proteins over time. Motivated by single-cell experiments, we capture this stochasticity by considering a given gene that toggles between transcriptionally active and inactive states with the time spent in each state being an arbitrary random variable. mRNAs are synthesized from the active state as per a Poisson process and each molecule degrades after a random lifespan (i.e., random time from birth to death). Modeling this process using the Stochastic Hybrid System (SHS) formalism we derive exact analytical results for the statistical moments of molecular counts. Our results show that for fixed mean mRNA numbers, fluctuations in mRNA levels are amplified with decreasing noise in mRNA lifespan. Relaxing the Poisson process assumption, we next consider a scenario where transcription events occur such that the time between successive events is an arbitrarily distributed random variable. In this case, we show that decreasing noise in mRNA lifespan can both increase/decrease mRNA count fluctuations depending on the underlying transcriptional process. Finally, we extend these results to the protein level, where increasing noise in mRNA counts is sometimes associated with decreasing noise in protein copy numbers. © 2024 IEEE.

关键词： Stochastic systems

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EFFICIENT SPECTRAL METHODS FOR EIGENVALUE PROBLEMS OF THE INTEGRAL FRACTIONAL LAPLACIAN ONABALLOFANYDIMENSION

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Journal of computational Mathematics 2024年第4期42卷 1032-1062页

作者： Suna Ma Huiyuan Li Zhimin Zhang Hu Chen Lizhen Chen College of Science Nanjing University of Posts and TelecommunicationsNanjingChina State Key Laboratory of Computer Science/Laboratory of Parallel Computing Institute of SoftwareChinese Academy of SciencesBeijingChina Department of Mathematics Wayne State UniversityDetroitUSA School of Mathematical Sciences Ocean University of ChinaQingdaoChina Beijing Computational Science Research Center BeijingChina

An efficient spectral-Galerkin method for eigenvalue problems of the integral fractional Laplacian on a unit ball of any dimension is proposed in this *** symmetric positive definite linear system is retained explicitly which plays an important role in the numerical *** a sharp estimate on the algebraic system's condition number is established which behaves as N4s with respect to the polynomial degree N,where 2s is the fractional derivative *** regularity estimate of solutions to source problems of the fractional Laplacian in arbitrary dimensions is firstly investigated in weighted Sobolev *** the regularity of eigenfunctions of the fractional Laplacian eigenvalue problem is readily ***,rigorous error estimates of the eigenvalues and eigenvectors are *** experiments are presented to demonstrate the accuracy and efficiency and to validate the theoretical results.

关键词： Integral fractional Laplacian Spectral method Eigenvalue problem Regularity analysis Error estimate

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Know-Thy-Basis: Decomposing F26 for Lightweight S-box Implementation

IACR Transactions on Cryptographic Hardware and Embedded Sys...

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IACR Transactions on Cryptographic Hardware and Embedded Systems 2024年第4期2024卷 763-794页

作者： Sau, Dilip Sarkar, Sumanta Saha, Dhiman Mandal, Kalikinkar Center for Computational & Data Sciences Indian Institute of Technology Kharagpur India University of Warwick Coventry United Kingdom de.ci.phe.red Lab Department of Computer Science and Engineering Indian Institute of Technology Bhilai India University of New Brunswick FrederictonNB Canada

A recent trend has shown constructions of 6-bit S-boxes that are mostly focused on their cryptographic elegance, while their lightweight aspects have not really been addressed well. This paper attempts to plug-in this existing research gap where we show how the composite structure of the extension field F26 could be leveraged. An earlier well-known example is an efficient implementation of AES S-box using the tower field extension of F28. The case of F2ab is completely different from any tower field as the implementation varies as per the choice of extension – for instance, F(2a)b or F(2b)a, where a and b are prime. Thus, it makes the implementation of S-boxes over F26 = F2(2×3) very interesting. In this work, we systematically study the composite field structure of F26 from a hardware standpoint for a class of S-boxes that are power mapping or their affine equivalents. We analyze the hardware efficiency with respect to different representations of the field extension, i.e., F(22)3or F(23)2. Furthermore, for each extension, we investigate the impact of various choices of bases – for instance, we present the evidence of the effect that normal or polynomial bases have on the implementation. This gives us further insight on the choice of basis with respect to the field extension. In the process, we present a special normal basis, when used in conjunction with F(23)2 results in the least (or very close to least) area in terms of GE for the 18 (6 quadratic and 12 cubic) S-boxes studied in this work. The special normal basis reported here has some algebraic properties which make it inherently hardware friendly and allow us to predict the area reduction, without running a tool. Overall, this work constitutes an extensive hardware characterization of a class of cryptographically significant 6-bit S-boxes giving us interesting insights into the systematic lightweight implementation of S-boxes without relying on an automated tool. © 2024, Ruhr-University of Bochum. All rights

关键词： Cryptography

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A Multi-Layers Information Fused Deep Architecture for Skin Cancer Classification in Smart Healthcare

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computers, Materials and Continua 2025年第3期83卷 5299-5321页

作者： Dillshad, Veena Khan, Muhammad Attique Nazir, Muhammad Ahmad, Jawad AlHammadi, Dina Abdulaziz Houda, Taha Cho, Hee-Chan Chang, Byoungchol Department of Computer Science HITEC University Taxila47080 Pakistan Department of Artificial Intelligence College of Computer Engineering and Science Prince Mohammad Bin Fahd University Al-Khobar31952 Saudi Arabia Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh11671 Saudi Arabia Center for Computational Social Science Hanyang University Seoul01000 Korea Republic of Department of Computer Science Hanynag University Seoul01000 Korea Republic of

Globally, skin cancer is a prevalent form of malignancy, and its early and accurate diagnosis is critical for patient survival. Clinical evaluation of skin lesions is essential, but several challenges, such as long waiting times and subjective interpretations, make this task difficult. The recent advancement of deep learning in healthcare has shown much success in diagnosing and classifying skin cancer and has assisted dermatologists in clinics. Deep learning improves the speed and precision of skin cancer diagnosis, leading to earlier prediction and treatment. In this work, we proposed a novel deep architecture for skin cancer classification in innovative healthcare. The proposed framework performed data augmentation at the first step to resolve the imbalance issue in the selected dataset. The proposed architecture is based on two customized, innovative Convolutional neural network (CNN) models based on small depth and filter sizes. In the first model, four residual blocks are added in a squeezed fashion with a small filter size. In the second model, five residual blocks are added with smaller depth and more useful weight information of the lesion region. To make models more useful, we selected the hyperparameters through Bayesian Optimization, in which the learning rate is selected. After training the proposed models, deep features are extracted and fused using a novel information entropy-controlled Euclidean Distance technique. The final features are passed on to the classifiers, and classification results are obtained. Also, the proposed trained model is interpreted through LIME-based localization on the HAM10000 dataset. The experimental process of the proposed architecture is performed on two dermoscopic datasets, HAM10000 and ISIC2019. We obtained an improved accuracy of 90.8% and 99.3% on these datasets, respectively. Also, the proposed architecture returned 91.6% for the cancer localization. In conclusion, the proposed architecture accuracy is compared with

关键词： Patient treatment

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Generalising Violence Detection with a New Near-Real-World Violence Dataset 3

Generalising Violence Detection with a New Near-Real-World V...

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3rd International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2024

作者： Haque, Mahmudul Nyeem, Hussain Ovi, Tareque Bashar Nahid, Al Molla, Md. Sabbir Hossain Tuhin, Md. Tanjim Mahmud Shahab, Fardin Alam, Ayat Subah Alam, Saadia Binte Mirpur Cantonment Dhaka1216 Bangladesh Independent University Department of Computer Science and Engineering Dhaka1229 Bangladesh Independent University Bangladesh Center for Computational & Data Sciences Dhaka1229 Bangladesh

ISBN: (纸本)9798350388282

Detecting and classifying violence is crucial for public safety and addressing societal violence. DL models have greatly improved the automation of violence detection systems by effectively capturing intricate visual patterns. However, the quality and diversity of the training data greatly impact the effectiveness of these models. Existing datasets may be biased towards specific situations, limiting their practical use. To address this limitation, we introduce the Movie Clip (MC) dataset to enhance the generalisability of Automated Violence Detection and Classification (AVDC) systems. The MC dataset encompasses a broad spectrum of near-real-world violent actions, incorporating diverse demographics, environmental circumstances, and cultural elements extracted from movies. Consequently, it accurately reflects the complexity and diversity of real-world violent scenarios. The potential of the new dataset is investigated against its existing counterparts, like Hockey Fight (HF) and AIRTLab datasets. These datasets are used to train the ConvLSTM models based on the VGG16 and VGG19 architectures. The proposed dataset significantly improves AVDC model generalisation, outperforming the generalisability of current datasets, thereby advancing violence detection and facilitating the development of more robust and efficient AVDC systems. © 2024 IEEE.

关键词： Long short-term memory

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WiMA:Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks

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computers, Materials & Continua 2023年第5期75卷 2347-2363页

作者： Sohaib Manzoor Hira Manzoor Saddaf Rubab Muhammad Attique Khan Majed Alhaisoni Abdullah Alqahtani Ye Jin Kim Byoungchol Chang Department of Electrical Engineering Mirpur University of Science and Technology(MUST)Mirpur-10250(AJK)Pakistan Faculty of Electronics Telecommunications and InformaticsGdansk University of Technology80-233 GdanskPoland Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates National University of Sciences and Technology(NUST) Islamabad44000Pakistan Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

Despite the planned installation and operations of the traditional IEEE 802.11 networks,they still experience degraded performance due to the number of *** of the main reasons is the received signal strength indicator(RSSI)association problem,in which the user remains connected to the access point(AP)unless the RSSI becomes too *** this paper,we propose a multi-criterion association(WiMA)scheme based on software defined networking(SDN)in Wi-Fi *** association solution based on multi-criterion such as AP load,RSSI,and channel occupancy is proposed to satisfy the quality of service(QoS).SDNhaving an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput *** implementWiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network *** performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30%and enhances the throughput by 20%–50%,hence maintaining user fairness and accommodating more wireless devices and traffic load in the network,when compared to traditional client-driven(CD)approach and state of the art Wi-Balance approach.

关键词： Association multi-criterion SDN Wi-Fi

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SMOTE Oversampling and Near Miss Undersampling Based Diabetes Diagnosis from Imbalanced Dataset with XAI visualization 28

SMOTE Oversampling and Near Miss Undersampling Based Diabete...

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28th IEEE Symposium on computers and Communications, ISCC 2023

作者： Nayan, Nasim Mahmud Islam, Ashraful Islam, Muhammad Usama Ahmed, Eshtiak Hossain, Mohammad Mobarak Alam, Md Zahangir University of Information Technology and Sciences Department of Computer Science and Engineering Bangladesh Independent University Center for Computational and Data Sciences Bangladesh School of Computing and Informatics University of Louisiana at Lafayette United States Independent University Department of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350300482

This study investigated the predictive ability of ten different machine learning (ML) models for diabetes using a dataset that was not evenly distributed. Additionally, the study evaluated the effectiveness of two oversampling and undersampling methods, namely the Synthetic Minority Oversampling Technique (SMOTE) and the Near-Miss algorithm. Explainable Artificial Intelligence (XAI) techniques were employed to enhance the interpretability of the model's predictions. The results indicate that the extreme gradient boosting (XGB) model combined with SMOTE oversampling technique exhibited the highest accuracy and an F1-score of 99% and 1.00 respectively. Furthermore, the utilization of XAI methods increased the dependability of the model's decision-making process, rendering it more appropriate for clinical use. These results imply that integrating XAI with ML and oversampling techniques can enhance the early detection and management of diabetes, leading to better diagnosis and intervention. © 2023 IEEE.

关键词： Machine learning

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