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A Multi-Objective Clustered Input Oriented Salp Swarm Algorithm in Cloud Computing

computers, Materials & Continua 2024年第12期81卷 4659-4690页

作者： Juliet A.Murali Brindha T. Department of Computer Science and Engineering Noorul Islam Centre for Higher EducationKumaracoil629180India Department of Information Technology Noorul Islam Centre for Higher EducationKumaracoil629180India

Infrastructure as a Service(IaaS)in cloud computing enables flexible resource distribution over the Internet,but achieving optimal scheduling remains a *** resource allocation in cloud-based environments,particularly within the IaaS model,poses persistent *** methods often struggle with slow opti-mization,imbalanced workload distribution,and inefficient use of available *** limitations result in longer processing times,increased operational expenses,and inadequate resource deployment,particularly under fluctuating *** overcome these issues,a novel Clustered Input-Oriented Salp Swarm Algorithm(CIOSSA)is *** approach combines two distinct strategies:Task Splitting Agglomerative Clustering(TSAC)with an Input Oriented Salp Swarm Algorithm(IOSSA),which prioritizes tasks based on urgency,and a refined multi-leader model that accelerates optimization processes,enhancing both speed and *** continuously assessing system capacity before task distribution,the model ensures that assets are deployed effectively and costs are *** dual-leader technique expands the potential solution space,leading to substantial gains in processing speed,cost-effectiveness,asset efficiency,and system throughput,as demonstrated by comprehensive *** a result,the suggested model performs better than existing approaches in terms of makespan,resource utilisation,throughput,and convergence speed,demonstrating that CIOSSA is scalable,reliable,and appropriate for the dynamic settings found in cloud computing.

关键词： Cloud computing clustering resource allocation scheduling swam algorithms optimization common with in the subject discipline

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Integration of Blockchain and IPFS: healthcare data management & sharing for IoT Environment

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Multimedia Tools and Applications 2024年 1-22页

作者： Mishra, Rajiv Kumar Yadav, Rajesh Kumar Nath, Prem Department of Computer Science & amp Engineering Jaypee Institute of Information Technology Noida India Department of Computer Science & amp Engineering Delhi Technological University Delhi India Department of Computer Science HNB Garhwal University Srinagar India

The immense volume of data generated and collected by smart devices has significantly enhanced various aspects of our daily lives. However, safeguarding the sensitive information shared among these devices is crucial. Ensuring the security of the Internet of Things (IoT) ecosystem from unauthorized access is imperative. Blockchain technology emerges as a promising solution to address these security concerns. Nevertheless, the effectiveness of Blockchain in handling the extensive data generated by smart devices is challenged by the rapid pace of IoT data generation and the slower transaction validation speed within Blockchain networks. This research aims to resolve these issues by integrating Blockchain with the Inter-Planetary File System (IPFS), creating a robust framework for secure data recording on a distributed storage network while enabling authorized access to the stored data. The proposed mechanism involves defining and recording access policies and cryptographic hash content on the Blockchain network, while storing the actual IoT-generated data on IPFS to enhance the confidentiality, integrity, and availability (CIA) triad. Performance assessments of the proposed scheme demonstrate its security and practicality, validating its potential for real-world application. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Electronic health record

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Polycystic ovary syndrome detection using optimized SVM and DenseNet

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International Journal of information technology (Singapore) 2024年第2期17卷 1039-1047页

作者： Silambarasan, E. Nirmala, G. Mishra, Ishani Department of CSE - Cyber Security Indian Institute of Information Technology Kottayam India Department of Electronics and Communication Engineering Mahendra Institute of Technology Namakkal (Dt) India Department of Electronics and Communication New Horizon College of Engineering Bangalore India

Polycystic ovary syndrome (PCOS) is a complicated endocrine disease that significantly impacts the health of women, affecting fertility and leading to various critical conditions. Unfortunately, around 70% of PCOS cases remain undiagnosed, emphasizing the importance of early detection. Ultrasound imaging has emerged as a valuable tool for detecting polycystic ovaries, providing crucial details such as follicle count, size, and position. However, manual diagnosis through ultrasound imaging is laborious and prone to errors, highlighting the need for more objective diagnostic methods. In this study, we propose two distinct predictive models for PCOS detection, utilizing both text and image based datasets. Firstly, an Optimized Support Vector Machine based PCOS detection model is developed using text-based datasets. Secondly, we introduce an image dataset based PCOS detection model using DenseNet. Experimental results demonstrated the suggested models’ effectiveness in accuracy, recall, F-score, and precision for both developed methods. The results showed that the present approaches offer superior performance compared to other methods. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Classification DenseNet Optimized Support Vector Machine PCOS detection Polycystic ovary syndrome

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Dynamic Indian Sign Language Sentence Captioning System Using Machine Learning 5th

Dynamic Indian Sign Language Sentence Captioning System Usin...

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5th International Conference on Electrical and Electronics engineering, ICEEE 2024

作者： Kulkarni, Vedant Dattatray Bajaj, Anushree Shrigopal Marathe, Himanshu Deshmukh, Mandar Sreemathy, R. Jagdale, Jayashree Department of Information Technology Pune Institute of Computer Technology Pune India Department of Electronics and Telecommunication Engineering Pune Institute of Computer Technology Pune India

ISBN: (纸本)9789819791118

Sign language serves as a vital mode of communication for the deaf and hard of hearing community, yet access to sign language content remains limited due to the lack of accurate and timely captioning. In this paper, a comprehensive comparison has been made between Long Short-Term Memory (LSTM)- and Support Vector Machine (SVM)-based neural networks for sign language recognition. Our approach uses LSTM networks to effectively recognize and translate sign language gestures into textual descriptions. We leverage a large dataset of sign language videos paired with English captions for training and evaluation. Through extensive experimentation, we demonstrate the effectiveness of our system in accurately captioning sign language videos, thereby enhancing accessibility for individuals with hearing impairments. Our self-curated dataset includes 28 unique sentences on which our LSTM-based model achieved an accuracy of 90% whereas it was 97% for SVM-based approach. Our research contributes to advancing the field of accessibility technology and holds promise for real-world applications in education, entertainment, and communication for the deaf and hard of hearing community. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Support vector machines

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Analysis of channel capacity for UWB antenna for improvements in the data rates and low Power transmission over wireless application

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International Journal of information technology (Singapore) 2024年第7期16卷 4343-4349页

作者： Bhopale, Nitin I. Pawar, Sunil N. Department of Electronics and Computer Engineering Sanjivani College of Engineering National Institute of Electronics and Information Technology (NIELIT) Chhattrapati Sambhaji Nagar Department of Electronics and Computer Engineering JNEC

Multiple input- Multiple output- Ultra-wideband (MIMO-UWB) is a wireless communication approach that combines multiple antennas at the transmitter and receiver with ultra-wideband frequency spectra to increase data speeds, dependability and spatial diversity in communication systems. The purpose of this research is to study the hybridization of MIMO-UWB over the Rayleigh fading channel using various antenna designs. Convolution encoders are used to encode binary data. The bit interleaver records the encrypted data that is sent to the mapper. The Inverse Fast Fourier Transform is used to handle information from Parallel subcarriers two,four, and eight. To prevent Inter symbol interference, a cyclic prefix is subsequently added. A Fast Fourier transform is used to synchronize signals after they are distorted and two, four, and eight antennas. The cyclic prefix is then deleted. Once the interleaving is done, the data received through various antennas are transformed into serial, demodulated, and decoded. Bit Error Rate (BER) and data rates are used to assess the hybridization system for MIMO-UWB sectorial antenna designs of 2x2,4x4, and *** results obtained indicate that both traditional MIMO and combined MIMO-UWB have higher data rates as SNR increases, with hybridized MIMO-UWB having higher data rates than conventional MIMO and achieving low transmission power. In the same way, hybridized MIMO-UWB yields lower BER values than standard MIMO. This suggests that hybrid MIMO-UWB outperforms traditional MIMO in terms of Rayleigh fading. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Bit error rate (BER) Multiple input- multiple output (MIMO) Quadrature amplitude modulation (QAM) Rayleigh fading Ultra-wideband antenna (UWB)

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An Efficient Quantum Enabled Machine Algorithm by Universal Features for Predicting Botnet Attacks in Digital Twin Enabled IoT Networks

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清华大学学报自然科学版（英文版） 2025年第3期30卷 947-956页

作者： Katta Rajesh Babu Naramula Venkatesh K.Shashidhar Yellampalli Dasaratha Rami Reddy K.Naga Prakash Department of ECE Koneru Lakshmaiah Education FoundationVijayawada 520002India School of Computer Science and Artificial Intelligence SR UniversityWarangal 506371India Department of Electronics & Communication Engineering Siddhartha Institute of Technology & SciencesHyderabad 500091India Department of CSE Chaitanya Bharathi Institute of TechnologyProddatur 520002India Department of ECE Seshadri Rao Gudlavalleru Engineering CollegeProddatur 520002India

In this manuscript,the authors introduce a quantum enabled Reinforcement Algorithm by Universal Features(REMF)as a lightweight solution designed to identify and assess the impact of botnet attacks on 5G Internet of Things(IoT)***'s primary objective is the swift detection of botnet assaults and their effects,aiming to prevent the initiation of such *** algorithm introduces a novel adaptive classification boosting through reinforcement learning,training on values derived from universal features extracted from network transactions within a given training *** the prediction phase,REMF assesses the Botnet attack confidence of feature values obtained from unlabeled network *** then compares these botnet attack confidence values with the botnet attack confidence of optimal features derived during the training phase to predict the potential impact of the botnet attack,categorizing it as high,moderate,low,or not-an-attack(normal).The performance evaluation results demonstrate that REMF achieves the highest decision accuracy,displaying maximum sensitivity and specificity in predicting the scope of botnet attacks at an early *** experimental study illustrates that REMF outperforms existing detection techniques for predicting botnet attacks.

关键词： botnet reinforcement learning 5G-enabled Internet of Things(IoT) network security machine learning

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Drug-Target Interactions Prediction Based on Signed Heterogeneous Graph Neural Networks

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Chinese Journal of Electronics 2024年第1期33卷 231-244页

作者： Ming CHEN Yajian JIANG Xiujuan LEI Yi PAN Chunyan JI Wei JIANG College of Information Science and Engineering Hunan Normal University School of Computer Science Shaanxi Normal University Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Computer Science Department BNU-HKBU United International College

Drug-target interactions(DTIs) prediction plays an important role in the process of drug *** computational methods treat it as a binary prediction problem, determining whether there are connections between drugs and targets while ignoring relational types information. Considering the positive or negative effects of DTIs will facilitate the study on comprehensive mechanisms of multiple drugs on a common target, in this work, we model DTIs on signed heterogeneous networks, through categorizing interaction patterns of DTIs and additionally extracting interactions within drug pairs and target protein pairs. We propose signed heterogeneous graph neural networks(SHGNNs), further put forward an end-to-end framework for signed DTIs prediction, called SHGNN-DTI,which not only adapts to signed bipartite networks, but also could naturally incorporate auxiliary information from drug-drug interactions(DDIs) and protein-protein interactions(PPIs). For the framework, we solve the message passing and aggregation problem on signed DTI networks, and consider different training modes on the whole networks consisting of DTIs, DDIs and PPIs. Experiments are conducted on two datasets extracted from Drug Bank and related databases, under different settings of initial inputs, embedding dimensions and training modes. The prediction results show excellent performance in terms of metric indicators, and the feasibility is further verified by the case study with two drugs on breast cancer.

关键词： Drug-target interactions Signed heterogeneous network Link sign prediction Graph neural networks

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Heart rate variability analysis in controls and epilepsy patients with or without receiving treatment: a clinical review and meta-analysis

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Neural Computing and Applications 2024年第29期36卷 18043-18063页

作者： Shahnawaz, Muhammad Bilal Dawooda, Hassan Iqbal, Uzair Department of Information Engineering Technology National Skills University Islamabad Islamabad4400 Pakistan Software Engineering Department University of Engineering and Technology Taxila Pakistan Department of Artificial Intelligence and Data Science National University of Computer and Emerging Sciences Islamabad44000 Pakistan

The malfunctioning of cardiac autonomic control in epileptic patients develops ventricular tachyarrhythmia and causes sudden unexpected death in epilepsy patients (SUDEP). Various clinical studies investigated the effect of epilepsy on cardiac autonomic control by performing heart rate variability (HRV) analysis;however, results are unclear regarding whether sympathetic, parasympathetic, or both branches of the autonomic nervous system (ANS) are affected in epilepsy and also the impact of anticonvulsant treatment on the ANS. This study follows the systematic protocols to investigate epilepsy and its anticonvulsant treatment on cardiac autonomic control by using linear and nonlinear HRV analysis measures. The electronic databases of PubMed, Embase, and Cochrane Library were used for the collection of studies. Initially, 1475 articles were identified whereas after 2-staged exclusion criteria, 33 studies were selected for execution of the review process and meta-analysis. For meta-analysis, four comparisons were performed (epilepsy patients): (1) controls (healthy subject with no history of epilepsy) versus untreated patients;(2) treated (patients under treatment that have a seizure) versus untreated patients;(3) controls versus treated patients;and (4) refractory versus well-controlled (epilepsy patients that were seizure-free for last 1 year). For treated and untreated patients, there was no significant difference whereas well-controlled patients presented higher values as compared to refractory patients. Meta-analysis was performed for the time-domain, frequency-domain, and nonlinear parameters. Untreated patients in comparison with controls presented significantly lower HF (high-frequency) and LF (low-frequency) values. These LF (g = − 0.9;95% CI − 1.48 to − 0.37) and HF (g = − 0.69;95% confidence interval (CI) − 1.24 to − 0.16) values were affirming suppressed both, vagal and sympathetic activity, respectively. Additionally, LF and HF value was increased in most o

关键词： Heart

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Optimizing Broadcast Utilization for Efficient Disaster Management Using Wireless Ad Hoc Networks and Novel Energy-Saving Algorithms

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2024年第20期18卷 142-156页

作者： Alzyoud, Faisal Y. Tarawneh, Monther Almaghthawi, Ahmed Altalidi, Askar Asiri, Layla Alrehaili, Meaad Department of Computer Science Faculty of Information Technology Isra University Amman Jordan Department of Information Technology College of Information Technology and Communications Tafila TechnicaUniversity Tafila Jordan Department of Computer Science College of Science & Art at Mahayil King Khalid University Abha Saudi Arabia Department of Information Science College of Science & Art at Mahayil King Khalid University Abha Saudi Arabia Departement of Computer Information System Applied college at Mahayil King Khalid University Abha Saudi Arabia Department of Computer Sciences and Artificial Intelligence Collège of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia

Globalization, industry, and population growth is considered the main reasons for climate change, so when some natural calamity or disaster occurs in any area, it leads to isolating this area from the rest of the region. Wireless ad hoc networks are important in disaster management to reduce losses and costs as they reduce the response, aiding time to save lives. However, they suffer from limited energy, which controls the lifetime of the sensor. Different methods are applied to save energy and increase battery life, such as sleep-awake schedules which assume similar initial energy for all nodes. Domestic partition in a unit disk graph is the production of the maximum possible number of such disjoint dominants. However, it assumes different initial energy levels for all nodes, which is another problem. In this paper, a new broadcast approach based on minimum set data broadcasting is proposed to mini-mize the number of broadcasting messages to increase the battery life during disasters and enhance rescue operations. The proposed minimum rebroadcast algorithm (MSRA) method balances coverage and utilization efficiency by dynamically adjusting node selection based on network conditions. The results show that MSRA significantly reduces power consumption and transmission latency, opening the way to find a new solution for disaster management using wireless ad hoc networks. © 2024 by the authors of this article.

关键词： Mobile ad hoc networks

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Harmonic Beam Steering with 2-Bit Equivalent Phases Using a 1-Bit Time-Domain Coding Metasurface

Harmonic Beam Steering with 2-Bit Equivalent Phases Using a ...

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2024 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2024

作者： Sahoo, Deepak Kumar Kundu, Debidas Patnaik, Amalendu Department of Electronics and Communication Engineering Indian Institute of Technology Roorkee Roorkee India Department of Electronics and Communication Engineering Indraprastha Institute of Information Technology Delhi New Delhi India

ISBN: (纸本)9798350379693

This paper presents harmonic beam steering by employing 2-bit equivalent phases from a 1-bit time-coding element. The space-time-coding (STC) matrix is computed based on the fundamental frequency (fc), the desired mth harmonic, and the desired beam angle (θd). Scattering pattern plots illustrate the radiation pattern at θd for the frequency fc+mf0, and at -θd for fc-mf0, where f0 is the modulation frequency. The symmetry observed in the radiation patterns for ±mth harmonics is attributed to the symmetry between their corresponding optimized 2-bit phase equivalents. However, while using the original 1-bit STC matrix, each harmonic produces symmetrically deflected dual beams directed at ±θd. The proposed concept and design can be applied to millimeter-wave (mmWave) sensing, communications, and imaging. © 2024 IEEE.

关键词： Millimeter waves

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