检索结果-南通市图书馆

MayGAN:Mayfly Optimization with Generative Adversarial Network-Based Deep Learning Method to Classify Leukemia form Blood Smear Images

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第8期46卷 2039-2058页

作者： Neenavath Veeraiah Youseef Alotaibi ahmad f.subahi Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharlaA.P.521180India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al-Qura UniversityMakkah21421Saudi Arabia

Leukemia,often called blood cancer,is a disease that primarily affects white blood cells(WBCs),which harms a person’s tissues and *** condition may be fatal when if it is not diagnosed and recognized at an early *** physical technique and lab procedures for Leukaemia identification are considered *** is crucial to use a quick and unexpected way to identify different forms of *** screening of the morphologies of immature cells is essential for reducing the severity of the disease and reducing the number of people who require *** deep-learning(DL)model-based segmentation and categorization techniques have already been introduced,although they still have certain *** order to enhance feature extraction and classification in such a practical way,Mayfly optimization with Generative Adversarial Network(MayGAN)is introduced in this ***,Generative Adversarial System(GAS)is integrated with Principal Component Analysis(PCA)in the feature-extracted model to classify the type of blood cancer in the *** semantic technique and morphological procedures using geometric features are used to segment the cells that makeup *** lymphocytic Leukaemia(ALL),acute myelogenous Leukaemia(AML),chronic lymphocytic Leukaemia(CLL),chronic myelogenous Leukaemia(CML),and aberrant White Blood Cancers(WBCs)are all successfully classified by the proposed MayGAN *** proposed MayGAN identifies the abnormal activity in the WBC,considering the geometric *** with the state-of-the-art methods,the proposed MayGAN achieves 99.8%accuracy,98.5%precision,99.7%recall,97.4%f1-score,and 98.5%Dice similarity coefficient(DSC).

关键词： Leukemia blood smear images optimization classification neural networks

Wind Speed Prediction Using Chicken Swarm Optimization with Deep Learning Model

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第9期46卷 3371-3386页

作者： R.Surendran Youseef Alotaibi ahmad f.subahi Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennaiIndia Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al-Qura UniversityMakkah21421Saudi Arabia

High precision and reliable wind speed forecasting have become a challenge for *** events,namely,strong winds,thunderstorms,and tornadoes,along with large hail,are natural calamities that disturb daily *** accurate prediction of wind speed and overcoming its uncertainty of change,several prediction approaches have been presented over the last few *** wind speed series have higher volatility and nonlinearity,it is urgent to present cutting-edge artificial intelligence(AI)*** this aspect,this paper presents an intelligent wind speed prediction using chicken swarm optimization with the hybrid deep learning(IWSP-CSODL)*** presented IWSP-CSODL model estimates the wind speed using a hybrid deep learning and hyperparameter *** the presented IWSP-CSODL model,the prediction process is performed via a convolutional neural network(CNN)based long short-term memory with autoencoder(CBLSTMAE)*** optimally modify the hyperparameters related to the CBLSTMAE model,the chicken swarm optimization(CSO)algorithm is utilized and thereby reduces the mean square error(MSE).The experimental validation of the IWSP-CSODL model is tested using wind series data under three distinct *** comparative study pointed out the better outcomes of the IWSP-CSODL model over other recent wind speed prediction models.

关键词： Weather wind speed predictive model chicken swarm optimization hybrid deep learning

Packet Drop Battling Mechanism for Energy Aware Detection in Wireless Networks

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第2期66卷 2077-2086页

作者： ahmad f.subahi Youseef Alotaibi Osamah Ibrahim Khalaf f.Ajesh Department of Computer Science University College of Al JamoumUmm Al Qura UniversityMakkah21421Saudi Arabia Department of Computer Science College of Computer and Information SystemsUmm Al Qura UniversityMakkah21421Saudi Arabia Al-Nahrain University Al-Nahrain Nanorenewable Energy Research CentreBaghdad70030Iraq Department of Computer Science and Engineering Musalair College of EngineeringKeralaIndia

Network security and energy consumption are deemed to be two important components of wireless and mobile ad hoc networks(WMANets).There are various routing attacks which harm Ad Hoc *** is because of the unsecure wireless communication,resource constrained capabilities and dynamic *** order to cope with these issues,Ad Hoc On-Demand Distance Vector(AODV)routing protocol can be used to remain the normal networks functionality and to adjust data transmission by defending the networks against black hole *** proposed system,in this work,identifies the optimal route from sender to collector,prioritizing the number of jumps,the battery life,and security,which are fundamental *** have proposed various plans for detecting the shortest route,as well as ensuring energy conversions and defense against threats and *** this regard,the packet drop attack is one of the most destructive attack against WMANet communication and hence merits special *** type of attack may allow the attacker to take control of the attacked hubs,which may lost packets or transmitted information via a wrong route during the packets journey from a source hub to a target ***,a new routing protocol method has been proposed in this *** applies the concept of energy saving systems to conserve energy that is not required by the *** proposed method for energy aware detection and prevention of packet drop attacks in mobile ad hoc networks is termed the Ad Hoc On-Demand and Distance Vector–Packet Drop Battling Mechanism(AODV–PDBM).

关键词： Wireless and mobile ad hoc networks(WMANet) packet drop attack(PDA) ad hoc on-demand distance vector(AODV) dynamic source routing(DSR) packet drop battling mechanism(PDBM)

Lens-Oppositional Wild Geese Optimization Based Clustering Scheme for Wireless Sensor Networks Assists Real Time Disaster Management

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第7期46卷 835-851页

Recently,wireless sensor networks(WSNs)find their applicability in several real-time applications such as disaster management,military,surveillance,healthcare,*** utilization of WSNs in the disaster monitoring process has gained significant attention among research communities and ***-time monitoring of disaster areas using WSN is a challenging process due to the energy-limited sensor ***,the clustering process can be utilized to improve the energy utilization of the nodes and thereby improve the overall functioning of the *** this aspect,this study proposes a novel Lens-Oppositional Wild Goose Optimization based Energy Aware Clustering(LOWGO-EAC)scheme for WSN-assisted real-time disaster *** major intention of the LOWGO-EAC scheme is to perform effective data collection and transmission processes in disaster *** achieve this,the LOWGOEAC technique derives a novel LOWGO algorithm by the integration of the lens oppositional-based learning(LOBL)concept with the traditional WGO algorithm to improve the convergence *** addition,the LOWGO-EAC technique derives a fitness function involving three input parameters like residual energy(RE),distance to the base station(BS)(DBS),and node degree(ND).The proposed LOWGO-EAC technique can accomplish improved energy efficiency and lifetime of WSNs in real-time disaster management *** experimental validation of the LOWGO-EAC model is carried out and the comparative study reported the enhanced performance of the LOWGO-EAC model over the recent approaches.

关键词： Disaster management real-time applications wireless sensor networks clustering bioinspired algorithms

Analyzing the Implications of COVID-19 Pandemic through an Intelligent-Computing Technique

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2022年第6期41卷 959-974页

作者： Abhishek Kumar Pandey Jehad f.Al-Amri ahmad f.subahi Rajeev Kumar Raees ahmad Khan Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025India Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al Qura UniversityMakkah21421Saudi Arabia Department of Computer Applications Shri Ramswaroop Memorial UniversityBarabanki225003India

The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2 virus or COVID-19) disease was declared pandemic by the WorldHealth Organization (WHO) on March 11, 2020. COVID-19 has already affectedmore than 211 nations. In such a bleak scenario, it becomes imperative to analyzeand identify those regions in Saudi Arabia that are at high risk. A preemptivestudy done in the context of predicting the possible COVID-19 hotspots wouldfacilitate in the implementation of prompt and targeted countermeasures againstSARS-CoV-2, thus saving many lives. Working towards this intent, the presentstudy adopts a decision making based methodology of simulation named Analytical Hierarchy Process (AHP), a multi criteria decision making approach, forassessing the risk of COVID-19 in different regions of Saudi Arabia. AHP givesthe ability to measure the risks numerically. Moreover, numerical assessments arealways effective and easy to understand. Hence, this research endeavour employsfuzzy based computational method of decision making for its empirical *** in the proposed paper suggest that Riyadh and Makkah are the mostsusceptible regions, implying that if sustained and focused preventive measuresare not introduced at the right juncture, the two cities could be the worst afflictedwith the infection. The results obtained through fuzzy based computationalmethod of decision making are highly corroborative and would be very usefulfor categorizing and assessing the current COVID-19 situation in the Kingdomof Saudi Arabia. More specifically, identifying the cities that are likely to beCOVID-19 hotspots would help the country’s health and medical fraternity toreinforce intensive containment strategies to counter the ills of the pandemic insuch regions.

关键词： COVID-19 Saudi Arabian regions risk assessment dynamics of infection fuzzy AHP

Healthcare Device Security Assessment through Computational Methodology

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2022年第5期41卷 811-828页

作者： Masood ahmad Jehad f.Al-Amri ahmad f.subahi Sabita Khatri Adil Hussain Seh Mohd Nadeem Alka Agrawal Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al Qura UniversityMakkah21421Saudi Arabia

The current study discusses the different methods used to secure healthcare devices and proposes a quantitative framework to list them in order of *** study uses the Hesitant fuzzy(Hf),Analytic Hierarchy Process(AHP)integrated with fuzzy Technical for Order Preference by Similarities to Ideal Solution(TOPSIS)to classify the best alternatives to security techniques for healthcare devices to securing the *** technique is enlisted to rate the alternatives based on the degree of satisfaction of their *** ranks of the alternatives consequently decide the order of priority for the techniques.A1 was the most probable alternative of all the alternatives,according to the ranks of the alternatives *** means that the security of A2 healthcare devices is the greatest of all the alternatives picked.A corroborative guide for the developers and the makers in quantitatively determining the security of healthcare devices to engineer efficacious devices will be the findings drawn up with the assistance of the proposed *** assessments performed using the proposed framework are systematic,precise,and ***,the results of the present empirical analysis are a stronger and accurate choice than the manual assessment of the device’s security.

关键词： Healthcare devices Hf-AHP.TOPSIS device security

An Analysis of Integrating Machine Learning in Healthcare for Ensuring Confidentiality of the Electronic Records

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in Engineering & Sciences 2022年第3期130卷 1387-1422页

作者： Adil Hussain Seh Jehad f.Al-Amri ahmad f.subahi Alka Agrawal Nitish Pathak Rajeev Kumar Raees ahmad Khan Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025India Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science Umm Al-Qura UniversityMakkah21421Saudi Arabia Department of Information Technology Guru Gobind Singh Indraprastha UniversityDelhi110078India Department of Computer Applications Shri Ramswaroop Memorial UniversityBarabanki225003India Department of Computer Science and Engineering Babu Banarasi Das UniversityLucknow226028India

The adoption of sustainable electronic healthcare infrastructure has revolutionized healthcare services and ensured that E-health technology caters efficiently and promptly to the needs of the stakeholders associated with *** the phenomenal advancement in the present healthcare services,the major obstacle that mars the success of E-health is the issue of ensuring the confidentiality and privacy of the patients’data.A thorough scan of several research studies reveals that healthcare data continues to be the most sought after entity by cyber *** approaches and methods have been practiced by researchers to secure healthcare digital ***,there are very few from the Machine learning(ML)domain even though the technique has the proactive ability to detect suspicious accesses against Electronic Health Records(EHRs).The main aim of this work is to conduct a systematic analysis of the existing research studies that address healthcare data confidentiality issues through ML *** guidelines have been practiced as a manual to conduct this *** well-known digital libraries namely IEEE Xplore,Science Direct,Springer Link,ACM Digital Library,Willey Online Library,PubMed(Medical and Bio-Science),and MDPI have been included to performan exhaustive search for the existing pertinent *** of this study depict that machine learning provides a more robust security mechanism for sustainable management of the EHR systems in a proactive fashion,yet the specified area has not been fully explored by the researchers.K-nearest neighbor algorithm and KNIEM implementation tools are mostly used to conduct experiments on EHR systems’log *** and performance measure of practiced techniques are not sufficiently outlined in the primary *** research endeavour depicts that there is a need to analyze the dynamic digital healthcare environment more *** accuracy and effective implementation of

关键词： EHRs healthcare machine learning systematic analysis

Multi-Tier Sentiment Analysis of Social Media Text Using Supervised Machine Learning

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第3期74卷 5527-5543页

作者： Hameedur Rahman Junaid Tariq M.Ali Masood ahmad f.subahi Osamah Ibrahim Khalaf Youseef Alotaibi Department of Creative Technologies Air UniversityE-9 Islamabad44230Pakistan Department of Computer Science National University of Modern LanguagesRawalpindiPakistan Department of Computer Science University College of Al JamoumUmm Al-Qura UniversityMakkah21421Saudi Arabia Al-Nahrain Nano-Renewable Energy Research Center Al-Nahrain UniversityBaghdad10072Iraq Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia

Sentiment Analysis(SA)is often referred to as opinion *** is defined as the extraction,identification,or characterization of the sentiment from ***,the sentiment of a textual document is classified into binary classes i.e.,positive and ***,fine-grained classification provides a better insight into the *** downside is that fine-grained classification is more challenging as compared to *** the contrary,performance deteriorates significantly in the case of multi-class *** this study,pre-processing techniques and machine learning models for the multi-class classification of sentiments were *** augment the performance,a multi-layer classification model has been *** to similitude with social media text,the movie reviews dataset has been used for the *** machine learning models namely Decision Tree,Support Vector Machine,and Naive Bayes models have been implemented for the task of sentiment *** have compared the models of single-layer architecture with multi-tier *** results of Multi-tier model have slight improvement over the single-layer ***,multi-tier models have better recall which allow our proposed model to learn more *** have discussed certain shortcomings of the model that will help researchers to design multi-tier models with more contextual information.

关键词： Sentiment analysis machine learning multi-class classification svm decision tree naive bayes

Hybrid Computational Modeling for Web Application Security Assessment

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第1期70卷 469-489页

作者： Adil Hussain Seh Jehad f.Al-Amri ahmad f.subahi Md Tarique Jamal Ansari Rajeev Kumar Mohammad Ubaidullah Bokhari Raees ahmad Khan Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al Qura UniversityMakkah21421Saudi Arabia Department of Computer Applications Shri Ramswaroop Memorial UniversityBarabanki225003Uttar PradeshIndia Department of Computer Science Aligarh Muslim UniversityAligarh202002Uttar PradeshIndia

Transformation from conventional business management systems to smart digital systems is a recurrent trend in the current *** has led to digital revolution,and in this context,the hardwired technologies in the software industry play a significant role However,from the beginning,software security remains a serious issue for all levels of *** vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data,compromising the organizations’reputation that translates into,financial losses as *** of the data breaches are financially motivated,especially in the healthcare *** cyber invaders continuously penetrate the E-Health data because of the high cost of the data on the dark ***,security assessment of healthcare web-based applications demands immediate intervention mechanisms to weed out the threats of *** aim of this work is to provide efficient and effective healthcare web application security *** study has worked with the hybrid computational model of Multi-Criteria Decision Making(MCDM)based on Analytical Hierarchy Process(AHP)and Technique for Order of Preference by Similarity to Ideal-Solutions(TOPSIS)under the Hesitant fuzzy(Hf)*** fuzzy sets provide effective solutions to address decision making problems where experts counter hesitation to make a *** proposed research endeavor will support designers and developers in identifying,selecting and prioritizing the best security attributes for web applications’*** empirical analysis concludes that Robustness got highest priority amongst the assessed security attributes set followed by Encryption,Authentication,Limit Access,Revoke Access,Data Validation,and Maintain Audit *** results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the web application *** study also establishes g

关键词： Healthcare web application security assessment hesitant fuzzy sets AHP-TOPSIS