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A Secure Method for Data Storage and Transmission in Sustainable Cloud Computing

Computers, Materials & Continua 2023年第5期75卷 2741-2757页

作者： Muhammad Usman Sana Zhanli Li Tayybah Kiren Hannan Bin Liaqat Shahid Naseem atif Saeed College of Computer Science and Technology Xi’an University of Science and TechnologyXi’anShaanxi710054China Department of Computer Science(RCET Campus) University of Engineering and TechnologyLahore39161Pakistan Department of Information Sciences Division of Science&TechnologyUniversity of EducationLahore54700Pakistan Department of Computer Science COMSATS UniversityIslamabadLahore54700Pakistan

Cloud computing is a technology that provides secure storage space for the customer’s massive data and gives them the facility to retrieve and transmit their data efficiently through a secure network in which encryption and decryption algorithms are being *** cloud computation,data processing,storage,and transmission can be done through laptops andmobile *** Storing in cloud facilities is expanding each day and data is the most significant asset of *** important concern with the transmission of information to the cloud is security because there is no perceivability of the client’s *** have to be dependent on cloud service providers for assurance of the platform’s *** security and privacy issues reduce the progression of cloud computing and add ***;most of the data that is stored on cloud servers is in the form of images and photographs,which is a very confidential form of data that requires secured *** this research work,a public key cryptosystem is being implemented to store,retrieve and transmit information in cloud computation through a modified Rivest-Shamir-Adleman(RSA)algorithm for the encryption and decryption of *** implementation of a modified RSA algorithm results guaranteed the security of data in the cloud *** enhance the user data security level,a neural network is used for user authentication and ***;the proposed technique develops the performance of detection as a loss function of the bounding *** Faster Region-Based Convolutional Neural Network(Faster R-CNN)gets trained on images to identify authorized users with an accuracy of 99.9%on training.

关键词： Cloud computing data security RSA algorithm Faster R-CNN

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Offshore Software Maintenance Outsourcing Process Model Validation:A Case Study Approach

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Computers, Materials & Continua 2023年第3期74卷 5035-5048页

作者： atif Ikram Masita Abdul Jalil Amir Bin Ngah Adel Sulaiman Muhammad Akram Ahmad Salman Khan Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan

The successful execution and management of Offshore Software Maintenance Outsourcing(OSMO)can be very beneficial for OSMO vendors and the OSMO *** a lot of research on software outsourcing is going on,most of the existing literature on offshore outsourcing deals with the outsourcing of software development *** frameworks have been developed focusing on guiding software systemmanagers concerning offshore software ***,none of these studies delivered comprehensive guidelines for managing the whole process of *** is a considerable lack of research working on managing OSMO from a vendor’s ***,to find the best practices for managing an OSMO process,it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s *** study validated the preliminary OSMO process model via a case study research *** results showed that the OSMO process model is applicable in an industrial setting with few *** industrial data collected during the case study enabled this paper to extend the preliminary OSMO process *** refined version of the OSMO processmodel has four major phases including(i)Project Assessment,(ii)SLA(iii)Execution,and(iv)Risk.

关键词： Offshore outsourcing process model model validation vendor challenges case study

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Ultrathin organic polymer with p-πconjugated structure for simultaneous photocatalytic disulfide bond generation and CO_(2)reduction

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Journal of Energy Chemistry 2023年第1期76卷 639-647,I0016页

作者： Linquan Hou Zhunyun Tang Guojiang Mao Shiheng Yin Bei Long Tao Ouyang Guo-Jun Deng atif Ali Ting Song Key Laboratory for Green Organic Synthesis and Application of Hunan Province Key Laboratory of Environmentally Friendly Chemistry and Application of Ministry of EducationCollege of ChemistryXiangtan UniversityXiangtan 411105HunanChina Hunan Key Laboratory for Micro-Nano Energy Materials and Device School of Physics and OptoelectronicsXiangtan UniversityXiangtan 411105HunanChina School of Chemistry and Chemical Engineering Henan Normal UniversityXinxiang 453007HenanChina Analytical and Testing Center South China University of TechnologyGuangzhou 510640GuangdongChina Department of Chemistry and State Key Laboratory of Synthetic Chemistry The University of Hong KongPokfulam RoadHong Kong 999077China

Combining photocatalytic organic reactions with CO_(2)reduction is an efficient solar energy utilization mode,but it is still limited by the organic species that can be matched and the low ***,ultrathin organic polymer with p-πconjugated structure(TPP)was rationally designed and prepared,and showed a high yield of CO(15.2 mmol g^(-1))and conversion of SAS coupled products(100%),far exceeding the organic polymer with P=O *** enhanced photoredox activity of TPP is ascribed to the orbital interaction between the p-orbital on phosphorus and theπ-orbitals of aromatic,which can accelerate the photoinduced charge carrier separation and improve the CO_(2)adsorption *** can also be used for the dehydrocoupling of various benzyl mercaptans to the corresponding SAS bond *** work provides a new concept for the efficient synthesis of disulfide bonds combined with CO_(2)reduction in a photoreaction system.

关键词： Photocatalytic coupled reaction Disulfide bond CO_(2)reduction High activity Organic polymer

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Efficient Cloud Resource Scheduling with an Optimized Throttled Load Balancing Approach

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Computers, Materials & Continua 2023年第11期77卷 2179-2188页

作者： V.Dhilip Kumar J.Praveenchandar Muhammad Arif Adrian Brezulianu Oana Geman atif Ikram Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India Department of Computer Science and Engineering Karunya Institute of Technology and SciencesCoimbatoreTamil Nadu641114India Department of Computer Science Superior UniversityLahorePakistan Faculty of Electronics Telecommunications and Information Technology Gheorghe Asachi Technical University of IasiIa¸si700050Romania Department of Health and Human Development Stefan cel Mare University of SuceavaSuceava720229Romania Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala NerusMalaysia

Cloud Technology is a new platform that offers on-demand computing Peripheral such as storage,processing power,and other computer system *** is also referred to as a system that will let the consumers utilize computational resources like databases,servers,storage,and intelligence over the *** a cloud network,load balancing is the process of dividing network traffic among a cluster of available servers to increase *** is also known as a server pool or server *** a single node is overwhelmed,balancing the workload is needed to manage unpredictable *** load balancer sends the load to another free node in this *** focus on the Balancing of workflows with the proposed approach,and we present a novel method to balance the load that manages the dynamic scheduling *** of the preexisting load balancing techniques is considered,however it is somewhat modified to fit the scenario at *** on the experimentation’s findings,it is concluded that this suggested approach improves load balancing consistency,response time,and throughput by 6%.

关键词： Load balancing throttled algorithm efficient resource allocation

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From Molecular Pathology of COVID-19 to Nigella Sativum as a Treatment Option:Scientific Based Evidence of Its Myth or Reality

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Chinese Journal of Integrative Medicine 2022年第1期28卷 88-95页

作者： Muhammad atif Farrah Naz Junaid Akhtar Muhammad Imran Sidrah Saleem Javed Akram Muhammad Imran Muhammad Ikram Ullah Department of Clinical Laboratory Sciences College of Applied Medical SciencesJouf UniversitySakaka(75471)Saudi Arabia Department of Microbiology Government College UniversityFaisalabad(38000)Pakistan Department of Microbiology University of Health SciencesLahore(54600)Pakistan Department of Allied Health Sciences Sargodha Medical CollegeUniversity of SargodhaSargodha(40100)Pakistan University of Health Sciences Lahore(54600)Pakistan University Institute of Diet and Nutritional Sciences Faculty of Allied Health SciencesThe University of LahoreLahore(54590)Pakistan

COVID-19 virus is a causative agent of viral pandemic in human beings which specifically targets respiratory system of humans and causes viral *** unusual viral pneumonia is rapidly spreading to all parts of the world,currently affecting about 105 million people with 2.3 million *** review described history,genomic characteristics,replication,and pathogenesis of COVID-19 with special emphasis on Nigella sativum(***)as a treatment *** seeds are historically and religiously used over the centuries,both for prevention and treatment of different *** review summarizes the potential role of *** seeds against COVID-19 infection at levels of in silico,cell lines and animal models.

关键词： coronavirus nCoV-19 COVID-19 Nigella sativum review

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Improving resource-constrained IoT device lifetimes by mitigating redundant transmissions across heterogeneous wireless multimedia of things

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Digital Communications and Networks 2022年第5期8卷 778-790页

作者： Muhammad Salah ud din Muhammad atif Ur Rehman Rehmat Ullah Chan-Won Park Dae Ho Kim Byung-seo Kim Department of Electronics&Computer Engineering Hongik UniversitySejong City30016South Korea Department of Computing&Mathematics Manchester Metropolitan University United Kingdom Cardiff School of Technologies Cardiff Metropolitan UniversityCardiffCF52YBUnited Kingdom Electronics and Telecommunications Research Institute Daejeon34129South Korea Department of Software and Communications Engineering Hongik UniversitySejong City30016South Korea

In Wireless Multimedia Sensor Networks(WMSNs),nodes capable of retrieving video,audio,images,and small scale sensor data,tend to generate immense traffic of various *** energy-efficient transmission of such a vast amount of heterogeneous multimedia content while simultaneously ensuring the quality of service and optimal energy consumption is ***,we propose a Power-Efficient Wireless Multimedia of Things(PE-WMoT),a robust and energy-efficient cluster-based mechanism to improve the overall lifetime of *** a PE-WMoT,nodes declare themselves Cluster Heads(CHs)based on available *** cluster formation and CH declaration processes are completed,the Sub-Cluster(SC)formation process triggers,in which application base nodes within close vicinity of each other organize themselves under the administration of a Sub-Cluster Head(SCH).The SCH gathers data from member nodes,removes redundancies,and forwards miniaturized data to its respective ***-WMoT adopts a fuzzy-based technique named the analytical hierarchical process,which enables CHs to select an optimal SCH among available SCs.A PE-WMoT also devises a robust scheduling mechanism between CH,SCH,and child nodes to enable collision-free data *** results revealed that a PE-WMoT significantly reduces the number of redundant packet transmissions,improves energy consumption of the network,and effectively increases network throughput.

关键词： Clustering WMSN WSN IoTs Resource-constrained Fuzzy AHP Sub clustering MAC Energy efficiency Network lifetime

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Multiple Deep-Belief-Network-Based Spectral-Spatial Classification of Hyperspectral Images

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Tsinghua Science and Technology 2019年第2期24卷 183-194页

作者： atif Mughees Linmi Tao Pervasive Computing Division Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University

A deep-learning-based feature extraction has recently been proposed for HyperSpectral Images(HSI)classification. A Deep Belief Network(DBN), as part of deep learning, has been used in HSI classification for deep and abstract feature extraction. However, DBN has to simultaneously deal with hundreds of features from the HSI hyper-cube, which results into complexity and leads to limited feature abstraction and performance in the presence of limited training data. Moreover, a dimensional-reduction-based solution to this issue results in the loss of valuable spectral information, thereby affecting classification performance. To address the issue, this paper presents a Spectral-Adaptive Segmented DBN(SAS-DBN) for spectral-spatial HSI classification that exploits the deep abstract features by segmenting the original spectral bands into small sets/groups of related spectral bands and processing each group separately by using local DBNs. Furthermore, spatial features are also incorporated by first applying hyper-segmentation on the HSI. These results improved data abstraction with reduced complexity and enhanced the performance of HSI classification. Local application of DBN-based feature extraction to each group of bands reduces the computational complexity and results in better feature extraction improving classification accuracy. In general, exploiting spectral features effectively through a segmented-DBN process and spatial features through hyper-segmentation and integration of spectral and spatial features for HSI classification has a major effect on the performance of HSI classification. Experimental evaluation of the proposed technique on well-known HSI standard data sets with different contexts and resolutions establishes the efficacy of the proposed techniques,wherein the results are comparable to several recently proposed HSI classification techniques.

关键词： hyperspectral image classification segmentation deep belief network support vector machine

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AI-Based Hybrid Models for Predicting Loan Risk in the Banking Sector

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Big Data Mining and Analytics 2023年第4期6卷 478-490页

作者： Vikas Kumar Shaiku Shahida Saheb Preeti atif Ghayas Sunil Kumari Jai Kishan Chandel Saroj Kumar Pandey Santosh Kumar Humanities and Management Department Dr.B.R.Ambedkar National Institute of Technology JalandharJalandhar 144027India. Mittal School of Business Lovely Professional UniversityPhagwara 144402India. Department of Commerce&Business Administration Kanya Maha Vidyalaya(KMV)Jalandhar 144004India School of Management Gitam(to be deemed university)Bangalore 561203India Government College for Women Indra Gandhi UniversityAteli 123021India. Institute of Management Studies Kurukshetra UniversityKurukshetra 136119India Department of Computer Engineering and Applications GLA UniversityMathura 281406India Department of Management Jaipuriya Institute of ManagementJaipur 302033India

Every real-world scenario is now digitally replicated in order to reduce paperwork and human labor *** Learning(ML)models are also being used to make predictions in these *** forecasting requires knowledge of these machine learning models and their distinguishing *** datasets we use as input for each of these different types of ML models,yielding different *** choice of an ML model for a dataset is critical.A loan risk model is used to show how ML models for a dataset can be linked *** purpose of this study is to look into how we could use machine learning to quantify or forecast mortgage credit *** phrase refers to the process of evaluating massive amounts of data in order to derive useful information for making decisions in a variety of *** credit risk is considered,a method based on an examination of what caused and how mortgage credit risk affected credit defaults during the still-current economic crisis of 2021 will be *** approaches to credit risk calculation will be examined,ranging from the most basic to the most *** addition,we will conduct a case study on a sample of mortgage loans and compare the results of three different analytical approaches,logistic regression,decision tree,and gradient boost to see which one produced the most commercially useful insights.

关键词： Artificial Intelligence(AI) Machine Learning(ML) loan prediction Support Vector Machine(SVM) Random Forest(RF) accuracy

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De-Noising Brain MRI Images by Mixing Concatenation and Residual Learning(MCR)

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Computer Systems Science & Engineering 2023年第5期45卷 1167-1186页

作者： Kazim Ali Adnan N.Qureshi Muhammad Shahid Bhatti Abid Sohail Muhammad Hijji atif Saeed Department of Computer Science Faculty of Information TechnologyUniversity of Central Punjab LahoreLahore54000Pakistan Department of Computer Science COMSAT University IslamabadLahore CampusLahore54000Pakistan Faculty of Computers and Information Technology Computer Science DepartmentUniversity of TabukTabuk47711Saudi Arabia

Brain magnetic resonance images(MRI)are used to diagnose the different diseases of the brain,such as swelling and tumor *** quality of the brain MR images is degraded by different noises,usually salt&pepper and Gaussian noises,which are added to the MR images during the acquisition *** the presence of these noises,medical experts are facing problems in diagnosing diseases from noisy brain MR ***,we have proposed a de-noising method by mixing concatenation,and residual deep learning techniques called the MCR de-noising *** proposed MCR method is to eliminate salt&pepper and gaussian noises as much as possible from the brain MRI *** MCR method has been trained and tested on the noise quantity levels 2%to 20%for both salt&pepper and gaussian *** experiments have been done on publically available brain MRI image datasets,which can easily be accessible in the experiments and result *** Structure Similarity Index Measure(SSIM)and Peak Signal-to-Noise Ratio(PSNR)calculate the similarity score between the denoised images by the proposed MCR method and the original clean ***,the Mean Squared Error(MSE)measures the error or difference between generated denoised and the original *** proposed MCR denoising method has a 0.9763 SSIM score,84.3182 PSNR,and 0.0004 MSE for salt&pepper noise;similarly,0.7402 SSIM score,72.7601 PSNR,and 0.0041 MSE for Gaussian noise at the highest level of 20%*** the end,we have compared the MCR method with the state-of-the-art de-noising filters such as median and wiener de-noising filters.

关键词： MR brain images median filter wiener filter concatenation learning residual learning MCR de-noising method

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Smart Devices Based Multisensory Approach for Complex Human Activity Recognition

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Computers, Materials & Continua 2022年第2期70卷 3221-3234页

作者： Muhammad atif Hanif Tallha Akram Aamir Shahzad Muhammad Attique Khan Usman Tariq Jung-In Choi Yunyoung Nam Zanib Zulfiqar Department of Electrical and Computer Engineering COMSATS University IslamabadWah Campus47040Pakistan Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad Campus22040Pakistan Department of Computer Science HITEC University TaxilaTaxilaPakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Applied Artificial Intelligence Ajou UniversitySuwonKorea Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea Department of Electrical and Computer Engineering CUISahiwalPakistan

Sensors based Human Activity Recognition(HAR)have numerous applications in eHeath,sports,fitness assessments,ambient assisted living(AAL),human-computer interaction and many *** human physical activity can be monitored by using wearable sensors or external *** usage of external devices has disadvantages in terms of cost,hardware installation,storage,computational time and lighting conditions ***,most of the researchers used smart devices like smart phones,smart bands and watches which contain various sensors like accelerometer,gyroscope,GPS etc.,and adequate processing *** the task of recognition,human activities can be broadly categorized as basic and complex human *** of complex activities have received very less attention of researchers due to difficulty of problem by using either smart phones or smart *** reasons include lack of sensor-based labeled dataset having several complex human daily life *** of the researchers have worked on the smart phone’s inertial sensors to perform human activity recognition,whereas a few of them used both pocket and wrist *** this research,we have proposed a novel framework which is capable to recognize both basic and complex human activities using builtin-sensors of smart phone and smart *** have considered 25 physical activities,including 20 complex ones,using smart device’s built-in *** the best of our knowledge,the existing literature consider only up to 15 activities of daily life.

关键词： Complex human activities human daily life activities features extraction data fusion multi-sensory smartwatch smartphone

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