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An Improved Image Steganography Security and Capacity Using Ant Colony Algorithm Optimization

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Computers, Materials & Continua 2024年第9期80卷 4643-4662页

作者： Zinah Khalid jasim jasim Sefer Kurnaz Department of Electrical and Computer Engineering Altinbas UniversityIstanbul34000Turkey

This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)*** steganography,a technique of embedding hidden information in digital photographs,should ideally achieve the dual purposes of maximum data hiding and maintenance of the integrity of the cover media so that it is least *** contemporary methods of steganography are at best a compromise between these *** this paper,we present our approach,entitled Ant Colony Optimization(ACO)-Least Significant Bit(LSB),which attempts to optimize the capacity in steganographic *** approach makes use of a grayscale cover image to hide the confidential data with an additional bit pair per byte,both for integrity verification and the file checksumof the secret *** approach encodes confidential information into four pairs of bits and embeds it within uncompressed grayscale *** ACO algorithm uses adaptive exploration to select some pixels,maximizing the capacity of data embedding whileminimizing the degradation of visual *** evaporation is introduced through iterations to avoid stagnation in solution *** levels of pheromone are modified to reinforce successful pixel *** results obtained through the ACO-LSB method reveal that it clearly improves image steganography capabilities by providing an increase of up to 30%in the embedding capacity compared with traditional approaches;the average Peak Signal to Noise Ratio(PSNR)is 40.5 dB with a Structural Index Similarity(SSIM)of *** approach also demonstrates very high resistance to detection,cutting down the rate by 20%.Implemented in MATLAB R2023a,the model was tested against one thousand publicly available grayscale images,thus providing robust evidence of its effectiveness.

关键词： Steganography steganalysis capacity optimization ant colony algorithm

Review of construction and demolition waste management tools and frameworks with the classification,causes,and impacts of the waste

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Waste Disposal and Sustainable Energy 2024年第1期6卷 95-121页

作者： Dewan Sabbir Ahammed Rayhan Iftekhar uddin Bhuiyan Institute of Appropriate Technology(IAT) Bangladesh University of Engineering and Technology(BUET)DhakaBangladesh Department of Industrial and Production Engineering(IPE) National Institute of Textile Engineering and Research(NITER)NayarhatSavarDhakaBangladesh

This review looks over the current construction and demolition waste management(C&DWM)situations by scrutinizing the definition,classification,components,compositions,generated sources and causes,impacts of generated construction and demolition wastes(C&DWs),waste management hierarchy(WMH),3R principles(Reduce,Reuse,and Recycle),Circular Economy(CE),frameworks,tools,and approaches of C&*** reviewing the literature this study contributes to the literature by the following means:(a)suitable working definitions of C&DW and C&DWM are provided,(b)an expanded WMH for construction and demolition operations is presented,(c)frameworks of C&DWM are identified and listed as follows:frameworks based on WMH,including 3R principles and CE concept,frameworks focusing on the quantification,estimation,and prediction of generated C&DW,frameworks focusing on effective and sustainable C&DWM,frameworks focusing economic,social,and environmental performance assessment,frameworks based on multi-criteria analysis(MCA),frameworks based on post-disaster recovery period,and other miscellaneous frameworks,and(d)four categories of tools utilized in C&DWM are identified and explained,namely,approaches employed in C&DWM,information technology(IT)tools employed in C&DWM,multi-criteria decision analysis(MCDA)tools employed in C&DWM,and C&DWM ***,this study also found that CE,and green rating system(GRS)are widely used approaches,Building Information Modeling(BIM),Radio Frequency Identification(RFID),Geographic Information System,and Big Data are the extensively used IT tools,Analytical Hierarchy Process,FUZZY,TOPSIS(Technique for Order Preference by Similarity to the Ideal Solution),Weighted Summation,Elimination and Choice Expressing the Reality II,Elimination and Choice Expressing the Reality III,Evaluation of Mixed Data,and REGIME(REG)are the widely used MCA tools in C&DWM,and Prefabricated Construction and Modular Construction are broadly used C&DWM ***

关键词： Construction and demolition waste Construction and demolition waste management Frameworks and tools 3R principles(Reduce,Reuse,&Recycle) Waste management hierarchy

Novel Framework for an Intrusion Detection System Using Multiple Feature Selection Methods Based on Deep Learning

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Tsinghua Science and Technology 2024年第4期29卷 948-958页

作者： A.E.M.Eljialy Mohammed Yousuf uddin Sultan Ahmad Department of Information Systems College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabiaand also with University Center for Research and Development(UCRD)Department of Computer Science and EngineeringChandigarh UniversityPunjabIndia

Intrusion detection systems (IDSs) are deployed to detect anomalies in real time. They classify a network’s incoming traffic as benign or anomalous (attack). An efficient and robust IDS in software-defined networks is an inevitable component of network security. The main challenges of such an IDS are achieving zero or extremely low false positive rates and high detection rates. Internet of Things (IoT) networks run by using devices with minimal resources. This situation makes deploying traditional IDSs in IoT networks unfeasible. Machine learning (ML) techniques are extensively applied to build robust IDSs. Many researchers have utilized different ML methods and techniques to address the above challenges. The development of an efficient IDS starts with a good feature selection process to avoid overfitting the ML model. This work proposes a multiple feature selection process followed by classification. In this study, the Software-defined networking (SDN) dataset is used to train and test the proposed model. This model applies multiple feature selection techniques to select high-scoring features from a set of features. Highly relevant features for anomaly detection are selected on the basis of their scores to generate the candidate dataset. Multiple classification algorithms are applied to the candidate dataset to build models. The proposed model exhibits considerable improvement in the detection of attacks with high accuracy and low false positive rates, even with a few features selected.

关键词： random forest feature selection decision tree software-defined network logistic regression intrusion detection system XGB classifier AdaBoost

Machine Fault Diagnosis Using Audio Sensors Data and Explainable AI Techniques-LIME and SHAP

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Computers, Materials & Continua 2024年第9期80卷 3463-3484页

作者： Aniqua Nusrat Zereen Abir Das Jia uddin School of Data and Sciences Brac UniversityDhaka1212Bangladesh JW KIM College of Future Studies Endicott CollegeWoosong UniversityDaejeon300-718Republic of Korea AI and Big Data Department Endicott CollegeWoosong UniversityDaejeon300-718Republic of Korea

Machine fault diagnostics are essential for industrial operations,and advancements in machine learning have significantly advanced these systems by providing accurate predictions and expedited *** learning models,especially those utilizing complex algorithms like deep learning,have demonstrated major potential in extracting important information fromlarge operational *** their efficiency,machine learningmodels face challenges,making Explainable AI(XAI)crucial for improving their understandability and *** importance of feature contribution and selection using XAI in the diagnosis of machine faults is examined in this *** technique is applied to evaluate different machine-learning *** Gradient Boosting,Support Vector Machine,Gaussian Naive Bayes,and Random Forest classifiers are used alongside Logistic Regression(LR)as a baseline model because their efficacy and simplicity are evaluated thoroughly with empirical *** XAI is used as a targeted feature selection technique to select among 29 features of the time and frequency *** XAI approach is lightweight,trained with only targeted features,and achieved similar results as the traditional *** accuracy without XAI on baseline LR is 79.57%,whereas the approach with XAI on LR is 80.28%.

关键词： Explainable AI feature selection machine learning machine fault diagnosis

Study on Employees' Adoption of Artificial Intelligence in Pakistan Banking Sector

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Study on Employees' Adoption of Artificial Intelligence in P...

作者： uddin Ihsan 山东财经大学

学位级别：硕士

The rapid pace of technological evolution is reshaping the landscape of business operations,prompting organizations to invest substantially in digital innovations such as artificial intelligence(AI)to maintain ***,the banking sector has emerged as an early adopter of AI technologies,reflecting its proactive stance toward technological *** the banking industry navigates through accelerated technological shifts,this research endeavors to explore the intention of employees within the Pakistan banking sector to embrace *** upon qualitative interviews with banking personnel,grounded theory approach was employed to identify five critical factors shaping AI adoption: perceived usefulness,perceived ease of use,personal well-being concern,personal development concern,and top management ***,a conceptual model was proposed by extending the Technology Acceptance Model(TAM)*** a quantitative approach,Structural Equation Modeling(SEM)was applied to analyze data collected from a sample of 255 employees across multiple banks in *** findings underscore the direct impact of all identified factors on AI adoption,albeit with varying degrees of ***,personal development concern and personal well-being concern were found to exert a negative influence on employees' intention to adopt AI,aligning with the formulated *** findings hold significant implications for organizations seeking to assess their workforce's readiness for AI *** illuminating the key factors influencing AI adoption,this study provides valuable insights for organizations striving to navigate the evolving technological landscape effectively.

关键词： Artificial Intelligence AI Adoption TAM Model Banking sector AI Technologies

Investigating and predicting the role of photovoltaic, wind, and hydrogen energies in sustainable global energy evolution

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Global Energy Interconnection 2024年第4期7卷 429-445页

作者： Mahmood Swadi Dheyaa jasim Kadhim Mohamed Salem Firas Mohammed Tuaimah Ammar Sabri Majeed Ali Jawad Alrubaie Department of Electrical Engineering College of EngineeringUniversity of BaghdadBaghdad 10001Iraq Libyan Authority for Scientific Research Tripoli 80045Libya School of Electrical and Electronic Engineering Universiti Sains Malaysia(USM)Nibong Tebal 14300PenangMalaysia Continuing Education Center University of BaghdadBaghdad 10001Iraq Al-Furat Al-Awsat Technical University AL-Mussaib Technical CollegeBabylonIraq

The global shift toward next-generation energy systems is propelled by the urgent need to combat climate change and the dwindling supply of fossil *** review explores the intricate challenges and opportunities for transitioning to sustainable renewable energy sources such as solar,wind,and *** transition economically challenges traditional energy sectors while fostering new industries,promoting job growth,and sustainable economic *** transition to renewable energy demands social equity,ensuring universal access to affordable energy,and considering community *** environmental benefits include a significant reduction in greenhouse gas emissions and a lesser ecological *** study highlights the rapid growth of the global wind power market,which is projected to increase from$112.23 billion in 2022 to$278.43 billion by 2030,with a compound annual growth rate of 13.67%.In addition,the demand for hydrogen is expected to increase,significantly impacting the market with potential cost reductions and making it a critical renewable energy source owing to its affordability and zero *** 2028,renewables are predicted to account for 42%of global electricity generation,with significant contributions from wind and solar photovoltaic(PV)technology,particularly in China,the European Union,the United States,and *** developments signify a global commitment to diversifying energy sources,reducing emissions,and moving toward cleaner and more sustainable energy *** review offers stakeholders the insights required to smoothly transition to sustainable energy,setting the stage for a resilient future.

关键词： Next energy Renewable energy Sustainability Environmental benefits Economic opportunities

Is atmospheric pathway a significant contributor to microplastics in the marine environment?

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Emerging Contaminants 2024年第2期10卷 26-32页

作者： Nazima Habibi Saif uddin Montaha Behbehani Jin-Yong Lee Environment and Life Sciences Research Center Kuwait Institute for Scientific ResearchKuwait Department of Geology Kangwon National UniversityChuncheon24341Republic of Korea

Transmission of microplastics(MPs)through aerosolization has been recently realized as an important *** of the reports of the ubiquitous MP presence in aerosols,the spatio-temporal information is inadequate and has very limited practicality in assessing if aerosol can be a significant source of MPs to the marine *** on marine contribution to atmospheric MPs is exceptionally scarce,and the ocean-air exchange is considered an emerging research *** of MPs entering the oceans via atmospheric deposition has been recently *** idea of ocean-air exchange emanates from the fact that beach sediments can get suspended under sand and dust storms,bubble bursts and sea sprays due to wind and waves in surf zones can lead to the ejection of particles into *** this succinct review,we have tried compiling the data on atmospheric MPs that can shed some light on the flux from and to the aquatic *** the information is too limited never the less its incorporation into the marine MP cycle cannot be neglected.

关键词： Marine-atmospheric flux Aerosols Microplastics MP load MP inventories

Improved Dynamic Johnson Sequencing Algorithm(DJS)in Cloud Computing Environment for Efficient Resource Scheduling for Distributed Overloading

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Journal of Systems Science and Systems Engineering 2024年第4期33卷 391-424页

作者： Anurag Sinha Pallab Banerjee Sharmistha Roy Nitasha Rathore Narendra Pratap Singh Mueen uddin Maha Abdelhaq Raed Alsaqour Department of Computer Science Engineering ICFAI Tech SchoolICFAI UniversityJharkhandRanchi834004India Department of Computer Science Engineering Amity UniversityJharkhandRanchi835303India Department of Computing and Information Technology Usha Martin UniversityRanchi835103India Department of Information Technology Bharti Vidyapeeth’s College of EngineeringPaschim ViharNew DelhiIndia Department of CSE Delhi UniversityNew DelhiIndia College of Computing and Information Technology University of Doha for Science and TechnologyDoha24449Qatar Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdurrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Technology College of Computing and InformaticsSaudi Electronic University93499RiyadhSaudi Arabia

This study introduces an innovative approach to optimize cloud computing job distribution using the Improved Dynamic Johnson Sequencing Algorithm(DJS).Emphasizing on-demand resource sharing,typical to Cloud Service Providers(CSPs),the research focuses on minimizing job completion delays through efficient task *** Johnson’s rule from operations research,the study addresses the challenge of resource availability post-task *** advocates for queuing models with multiple servers and finite capacity to improve job scheduling models,subsequently reducing wait times and queue *** Dynamic Johnson Sequencing Algorithm and the M/M/c/K queuing model are applied to optimize task sequences,showcasing their efficacy through comparative *** research evaluates the impact of makespan calculation on data file transfer times and assesses vital performance indicators,ultimately positioning the proposed technique as superior to existing approaches,offering a robust framework for enhanced task scheduling and resource allocation in cloud computing.

关键词： First come first served(FCFS)scheduling round robin task scheduling queuing model Johnson scheduling algorithm

Physical properties and maximum allowable mass-radius relation of complexity-free compact stellar objects within modified f(R,T)gravity formalism

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Chinese Physics C 2024年第7期48卷 273-288页

作者： M.K.jasim S.K.Maurya Abdelghani Errehymy Ali Khalid Jassim Kottakkaran Sooppy Nisar Abdel-Haleem Abdel-Aty Department of Mathematical and Physical Sciences College of Arts and SciencesUniversity of NizwaNizwa 616Sultanate of Oman Astrophysics Research Centre School of MathematicsStatistics and Computer ScienceUniversity of KwaZulu-NatalPrivate Bag X54001Durban 4000South Africa Electrical Engineering Department College of EngineeringMustansiriyah UniversityBaghdadIraq Department of Mathematics College of Science and Humanities in AlkharjPrince Sattam bin Abdulaziz UniversityAl KharjSaudi Arabia Department of Physics College of SciencesUniversity of BishaP.O.Box 344Bisha 61922Saudi Arabia

This paper investigates the physical properties and predicted radii of compact stars generated by the Tolman-IV complexity-free model within the background of modified gravity theory,particularly the f(R,T)-gravity theory,under complexity formalism for a spherically symmetric spacetime proposed by ***[Phys Rev D 97:044010,2018].By solving the resulting set of differential equations,we obtain the explicit forms of the energy-momentum(EM)tensor components,including the density,radial pressure,and tangential *** influence of the parameterχon various physical properties of the star is thoroughly *** model undergoes a series of rigorous tests to determine its physical *** findings indicate that the model exhibits regularity,stability,and a surface with vanishing *** boundary of this surface is determined by carefully selecting the parameter *** complexity method employed in f(R,T)gravity offers an interesting approach for developing astrophysical models that are consistent with observable events as demonstrated by recent *** this regard,we use observational data from the GW190814 event,detected by the LIGO and Virgo observatories,to investigate the validity of the Tolman-IV model in f(R,T)*** analysis includes comparing the model's predictions with the observed characteristics of the compact object involved in the *** addition,data from two-millisecond pulsars,PSR J1614-2230 and PSR J0952-0607,are incorporated to further constrain the theoretical ***,we present a diagram depicting the relationship between the total mass and radius of the compact object candidates for different values ofχ.

关键词： complexity modified gravity compact Stars