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4th International Conference on Advanced Electrical and Energy Systems, AEES 2023

作者： Aly, Rabab Hamed M. Hussein, Aziza I. The Higher Institute for Management and Information Technology Minya Egypt Faculty of Computer Science Nahda University Computer Science Department Beni Suef Egypt College of Engineering Effat University Electrical and Computer Engineering Department Jeddah Saudi Arabia

ISBN: (纸本)9798350342659

Each photovoltaic (PV) system demonstrates a specific point on the current-voltage (IV) curve characteristics where the power generated reaches its maximum value which is referred to as the maximum power point (MPP). The maximum power point tracking (MPPT) system is designed to sample the output of solar cells and adjust the load in order to achieve maximum power output under various environmental conditions. In this paper, a design of a boost converter with MPPT based on a PID controller is proposed. The goal is to optimize the extraction of the highest attainable power from photovoltaic systems. The extracted power is subsequently directed to the load through a boost converter, which elevates the voltage to the necessary level. The PID controller is calibrated by Neural Gas Network (NGN) and utilized to achieve a consistent output voltage irrespective of fluctuations in the power source or the connected load. Moreover, an NGN technique is applied to generate the optimal PID parameters before using the PID. The comprehensive system design depicted has been simulated using MATLAB Simulink to verify the functionality of the system. © 2023 IEEE.

关键词： Controllers

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P-ACOHONEYBEE: A Novel Load Balancer for Cloud Computing Using Mathematical Approach

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computers, Materials & Continua 2022年第10期73卷 1943-1959页

作者： Sunday Adeola Ajagbe Mayowa O.Oyediran Anand Nayyar Jinmisayo A.Awokola Jehad F.Al-Amri Computer Engineering Department Ladoke Akintola University of TechnologyLAUTECHOgbomosoNigeria Computer Science Department Ajayi Crowther UniversityOyoNigeria Graduate School Faculty of Information TechnologyDuy Tan UniversityDa NangVietnam Department of Computer Sciences Precious Cornerstone UniversityIbadanNigeria Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Cloud computing is a collection of disparate resources or services,a web of massive infrastructures,which is aimed at achieving maximum utilization with higher availability at a minimized *** of the most attractive applications for cloud computing is the concept of distributed information ***,privacy,energy saving,reliability and load balancing are the major challenges facing cloud computing and most information technology *** balancing is the process of redistributing workload among all nodes in a network;to improve resource utilization and job response time,while avoiding overloading some nodes when other nodes are underloaded or idle is a major ***,this research aims to design a novel load balancing systems in a cloud computing *** research is based on the modification of the existing approaches,namely;particle swarm optimization(PSO),honeybee,and ant colony optimization(ACO)with mathematical expression to form a novel approach called *** experiments were conducted on response time and *** results of the response time of honeybee,PSO,SASOS,round-robin,PSO-ACO,and P-ACOHONEYBEE are:2791,2780,2784,2767,2727,and 2599(ms)*** outcome of throughput of honeybee,PSO,SASOS,round-robin,PSO-ACO,and P-ACOHONEYBEE are:7451,7425,7398,7357,7387 and 7482(bps)*** is observed that P-ACOHONEYBEE approach produces the lowest response time,high throughput and overall improved performance for the 10 *** research has helped in managing the imbalance drawback by maximizing throughput,and reducing response time with scalability and reliability.

关键词： ACO cloud computing load balancing swarm intelligence PSO P-ACOHONEYBE honeybee swarm

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Optimizing User Data Privacy and Confidentiality in Cloud Storage Systems Through Advanced Obfuscrypt Encryption Methods for Enhanced Security and Efficient Data Protection

Optimizing User Data Privacy and Confidentiality in Cloud St...

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2024 IEEE International Conference on Recent Advances in science and engineering technology, ICRASET 2024

作者： Ramesh, P.S. Sudha, I. Jagannathan, J. Pandiarajan, Rajkumar Ponmalar, A. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Saveetha Institute of Medical and Technical Sciences Simats University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Katpadi Vellore India Kalasalingam Academy Of Research and Education School of Computing Department of Information and Technology Krishnankoil Virudhunagar India R.M.K. Engineering College Tamilnadu Chennai India

ISBN: (纸本)9798350388602

With a steady increase in the adoption of cloud storage systems, the client's data are at risk of being leaked. There are several methods of encrypting data which are quite useful but they lack some of the features of today's sophisticated threats. The methodology used in this research propose an encryption framework known as Obfuscrypt to improve the issues of data privacy as well as confidentiality of data stored in cloud storage systems. Obfuscrypt uses conventional encryption strategies incorporated with obfuscation and post-quantum cryptographic algorithms to provide a complex security plan immune to classic and quantum approaches. Some of the proposed other innovations include the decentralised key management with multi-factor authentication and RBAC-ABE as the fine-grained access control techniques. These features make it possible for only the authorized personnel to be in a position to be in a position of decrypting and retrieving the stored data thereby minimizing the possibility of the data being accessed by unauthorized people. The work also considers the issue of performance efficiency of the cloud storage systems. Similar to other symmetric encryption programs, Obfuscrypt uses light encryption algorithms and brings in to play the hardware acceleration so that it may infuse lesser computational overhead in the process of encryption and decryption. As can be clearly seen from the results, the actual work proves that the proposed framework not only offers a higher level of security but does not affect the system performance to a great extent. Also, the study addresses the post-quantum cryptographic algorithm for making the system resistant to an attack that can be posed by quantum computing systems. With the help of these improved algorithms, Obfuscrypt guarantees the permanent data security in the world of constantly emerging cyber threats. © 2024 IEEE.

关键词： Data obfuscation

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Two-Mode Biomedical Sensor Build-up:Characterization of Optical Amplifier

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computers, Materials & Continua 2022年第3期70卷 5487-5501页

作者： Usman Masud Fathe Jeribi Mohammed Alhameed Faraz Akram Ali Tahir Mohammad Yousaf Naudhani Faculty of Electrical and Electronics Engineering University of Engineering and TechnologyTaxila47050Pakistan Department of Electrical Communication Engineering University of KasselKassel34127Germany College of Computer Science&Information Technology Jazan UniversityJazan45142Saudi Arabia Faculty of Engineering and Applied Sciences Riphah International UniversityIslamabad44000Pakistan Faculty of Information&Communication Technology Balochistan University of Information TechnologyEngineering and Management SciencesQuetta

Intracavity absorption spectroscopy is a strikingly sensitive technique that has been integrated with a two-wavelength setup to develop a sensor for human *** factors are considered in such a scenario,out of which Relative Intensity Noise(RIN)has been exploited as an important parameter to characterize and calibrate the said *** the performance of an electrical based assessment arrangement which has been developed in the laboratory as an alternative to the expensive Agilent setup,the optical amplifier plays a pivotal role in its development and operation,along with other components and their ***,the investigation and technical analysis of the amplifier in the system has been explored in *** algorithm developed for the automatic measurements of the system has been effectively deployed in terms of the laser’s *** this in perspective,a frequency dependent calibration has been pursued in depth with this scheme which enhances the sensor’s efficiency in terms of its *** this way,our investigation helps us in a better understanding and implementation perspective of the proposed system,as the outcomes of our analysis adds to the precision and accuracy of the entire system.

关键词： Biomedical sensor cavity optomechanics spectroscopy relative intensity noise semiconductor laser diode

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Two-Stream Deep Learning Architecture-Based Human Action Recognition

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computers, Materials & Continua 2023年第3期74卷 5931-5949页

作者： Faheem Shehzad Muhammad Attique Khan Muhammad Asfand E.Yar Muhammad Sharif Majed Alhaisoni Usman Tariq Arnab Majumdar Orawit Thinnukool Department of Computer Science COMSATS University IslamabadWah CampusPakistan Department of Computer Science HITEC UniversityTaxilaPakistan Department of Computer Science Bahria UniversityIslamabadPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer Engineering and Science Prince Sattam Bin Abdulaziz UniversityAl-Kharaj11942Saudi Arabia Faculty of Engineering Imperial College LondonLondonSW72AZUK College of Arts Mediaand TechnologyChiang Mai UniversityChiang Mai50200Thailand

Human action recognition(HAR)based on Artificial intelligence reasoning is the most important research area in computer *** breakthroughs in this field have been observed in the last few years;additionally,the interest in research in this field is evolving,such as understanding of actions and scenes,studying human joints,and human posture *** HAR techniques are introduced in the ***,the challenge of redundant and irrelevant features reduces recognition *** also faced a few other challenges,such as differing perspectives,environmental conditions,and temporal variations,among *** this work,a deep learning and improved whale optimization algorithm based framework is proposed for *** proposed framework consists of a few core stages i.e.,frames initial preprocessing,fine-tuned pre-trained deep learning models through transfer learning(TL),features fusion using modified serial based approach,and improved whale optimization based best features selection for final *** pre-trained deep learning models such as InceptionV3 and Resnet101 are fine-tuned and TL is employed to train on action recognition *** fusion process increases the length of feature vectors;therefore,improved whale optimization algorithm is proposed and selects the best *** best selected features are finally classified usingmachine learning(ML)*** publicly accessible datasets such as Ut-interaction,Hollywood,Free Viewpoint Action Recognition usingMotion History Volumes(IXMAS),and centre of computer vision(UCF)Sports,are employed and achieved the testing accuracy of 100%,99.9%,99.1%,and 100%*** with state of the art techniques(SOTA),the proposed method showed the improved accuracy.

关键词： Human action recognition deep learning transfer learning fusion of multiple features features optimization

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Success Factors of Requirement Elicitation in the Field of software engineering 4

Success Factors of Requirement Elicitation in the Field of S...

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Attanayaka, Buddhima Nawinna, Dasuni Manathunga, Kalpani Abeygunawardhana, Pradeep K.W. Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka Department of Computer Systems & Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (纸本)9798350398090

Requirement elicitation (RE) is a cognitively challenging and time-consuming task in software development due to the numerous challenges associated with it including conflicting requirements, unspoken, or assumed requirements, difficulty meeting with relevant stakeholders, stakeholder resistance to change, and not enough time set aside for meetings with all stakeholders. The prime causes of software implementation failure have been identified as inadequacies in the treatment of requirements. Without collecting the quality requirement, cannot achieve the goal of a quality software product. Through identifying the success factors affecting requirement elicitation, the paths to the quality requirements can be identified. The success factors identify through this research are experience, business analyst skills, stakeholder relationship, organizational elicitation process. This study aims to identify the factors affecting requirement elicitation based on the data collected from business analysts and similar positions in the software industry through a survey, interviews, and analyzed data to provide the initial validation for the identified factors. Through the analysis, we identified the main factors affecting successful requirement elicitation with a perfect significance value of less than 0.05 for all factors. © 2022 IEEE.

关键词： Requirements engineering

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Enhancing Healthcare Data Security in Cloud Computing Systems through Advanced Homomorphic Encryption Techniques Integrated with Cuckoo Search Optimization Algorithm

Enhancing Healthcare Data Security in Cloud Computing System...

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2024 IEEE International Conference on Recent Advances in science and engineering technology, ICRASET 2024

作者： Sudha, I. Ramesh, P.S. Ponmalar, A. Jagannathan, J. Pandiarajan, Rajkumar Saveetha Institute of Medical and Technical Sciences Simats University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India R.M.K. Engineering College Tamilnadu Chennai India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Katpadi Vellore India Kalasalingam Academy of Research and Education School of Computing Department of Information and Technology Krishnankoil Virudhunagar India

ISBN: (纸本)9798350388602

The studies in this research are focused on the mix of homomorphic encryption mechanisms and the Cuckoo Search Optimization Algorithm to promote the security of the healthcare data in the cloud computing system. I have observed that cloud solutions are now at the center of the contemporary health care systems, and security of patient's data remains a top priority. Earlier used encryption techniques, though secure if implemented, have problems in the way that data is to be processed first it has to be decrypted and then made ready for use - it is in this phase that data can be easily hacked into. Homomorphic encryption provides solution to this issue since it enables one to perform computations on encrypted data while maintaining its confidentiality. However, it takes a lot of computation which presents a lot of problems even in terms of simple performance. The Cuckoo Search Algorithm, a new nature-inspired metaheuristic, is incorporated into the encryption process to provide further optimization, whilst preserving the security benefits of the algorithm. The use of the proposed methodology takes place employing Python and its deployment at the cloud platform with elaborated dataset containing anonymized records extracted from electronic health records. The outcome proves that there are great enhancements in encryption and decryption time, computational complexity, and capacity, and thereby making the system appropriate for real-world healthcare solutions. This research offers a strong base for protection of healthcare data in cloud and is useful for the enhancement of adaptive, comprehensive and secure cloud computing systems. © 2024 IEEE.

关键词： Electronic health record

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Learning-Based Artificial Algae Algorithm with Optimal Machine Learning Enabled Malware Detection

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computer Systems science & engineering 2023年第9期46卷 3103-3119页

作者： Khaled M.Alalayah Fatma S.Alrayes Mohamed K.Nour Khadija M.Alaidarous Ibrahim M.Alwayle Heba Mohsen Ibrahim Abdulrab Ahmed Mesfer Al Duhayyim Department of Computer Science College of Science and ArtsNajran UniversitySharurahSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Computer Department Applied CollegeNajran UniversityNajran66462Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Malware is a‘malicious software program that performs multiple cyberattacks on the Internet,involving fraud,scams,nation-state cyberwar,and *** malicious software programs come under different classifications,namely Trojans,viruses,spyware,worms,ransomware,Rootkit,botnet malware,*** is a kind of malware that holds the victim’s data hostage by encrypting the information on the user’s computer to make it inaccessible to users and only decrypting it;then,the user pays a ransom procedure of a sum of *** prevent detection,various forms of ransomware utilize more than one mechanism in their attack flow in conjunction with Machine Learning(ML)*** study focuses on designing a Learning-Based Artificial Algae Algorithm with Optimal Machine Learning Enabled Malware Detection(LBAAA-OMLMD)approach in computer *** presented LBAAA-OMLMDmodelmainly aims to detect and classify the existence of ransomware and goodware in the *** accomplish this,the LBAAA-OMLMD model initially derives a Learning-Based Artificial Algae Algorithm based Feature Selection(LBAAA-FS)model to reduce the curse of dimensionality ***,the Flower Pollination Algorithm(FPA)with Echo State Network(ESN)Classification model is *** FPA model helps to appropriately adjust the parameters related to the ESN model to accomplish enhanced classifier *** experimental validation of the LBAAA-OMLMD model is tested using a benchmark dataset,and the outcomes are inspected in distinct *** comprehensive comparative examination demonstrated the betterment of the LBAAAOMLMD model over recent algorithms.

关键词： computer networks machine learning security malware detection feature selection ransomware

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Automated Grading of Breast Cancer Histopathology Images Using Multilayered Autoencoder

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computers, Materials & Continua 2022年第5期71卷 3407-3423页

作者： Shakra Mehak M.Usman Ashraf Rabia Zafar Ahmed M.Alghamdi Ahmed S.Alfakeeh Fawaz Alassery Habib Hamam Muhammad Shafiq Knowledge Unit of System and Technology University of Management&TechnologySialkot Campus51310Pakistan Department of Computer Science University of Management and TechnologySialkot Campus51310Pakistan Faculty of Computing and Technology University of Engineering&TechnologyNarowal51610Pakistan College of Computer Science and Engineering University of Jeddah21493Saudi Arabia Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia Faculty of Engineering Moncton UniversityNBE1A3E9Canada Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Breast cancer(BC)is the most widely recognized cancer in women *** 2018,627,000 women had died of breast cancer(World Health Organization Report 2018).To diagnose BC,the evaluation of tumours is achieved by analysis of histological *** present,the Nottingham Bloom Richardson framework is the least expensive approach used to grade BC *** contemplate three elements,*** count,*** formation,and *** atypia,which is a laborious process that witness’s variations in expert’s ***,some algorithms have been proposed for the detection of mitotic cells,but nuclear atypia in breast cancer histopathology has not received much *** atypia analysis is performed not only to grade BC but also to provide critical information in the discrimination of normal breast,non-invasive breast(usual ductal hyperplasia,atypical ductal hyperplasia)and pre-invasive breast(ductal carcinoma in situ)and invasive breast *** proposed a deep-stacked multi-layer autoencoder ensemble with a softmax layer for the feature extraction and classification *** classification results show the value of the multilayer autoencoder model in the evaluation of nuclear *** proposed method has indicated promising results,making them more fit in breast cancer grading.

关键词： Breast cancer nuclear atypia autoencoder

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Advanced Multi-Spectral Image Processing Techniques for Enhanced Remote Sensing and Comprehensive Environmental Monitoring in Diverse Ecosystems

Advanced Multi-Spectral Image Processing Techniques for Enha...

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2024 IEEE International Conference on Recent Advances in science and engineering technology, ICRASET 2024

作者： Jagannathan, J. Ponmalar, A. Pandiarajan, Rajkumar Sudha, I. Ramesh, P.S. Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Katpadi Vellore India R.M.K. Engineering College Tamilnadu Chennai India School of Computing Kalasalingam Academy Of Research and Education Department of Information and Technology Krishnankoil Virudhunagar India Saveetha Institute of Medical and Technical Sciences Simats University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350388602

The research is aimed at improvement of multi-spectral image analysis for remote sensing and monitoring the environment at various ecosystems. A combined spectral imagery encompasses several spectrums at a time compared to single spectral imagery that takes only one spectrum at an instance or at a given area to cover all these spectrums. The study employs digital high resolution satellite images and ground based data to quantify the vegetation vigour, water quality, soil characteristics and changes in land cover. Features, indexes, and classification routines are employed to process the data that is collected with the aid of avionics and other peripherals. This provincial level modelling highlights important gains in environmental status, which includes the general improvement in vegetation condition, water quality as well as physical properties of the soil in the province. This study focuses on the complementary possibilities of integration of multi-spectral imaging with other remote sensing technologies and the high performance of data processing. These techniques play significant roles if used to give current and comprehensive information in the management and conservation of the environment as highlighted in the study. © 2024 IEEE.

关键词： data analysis environmental monitoring image processing techniques machine learning Multi-spectral imaging remote sensing soil properties vegetation health water quality

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