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Analyzing the Impact of scene Transitions on Indoor Camera Localization through scene Change Detection in Real-Time

Intelligent Automation & soft Computing 2024年第3期39卷 417-436页

作者： muhammad s.alam Farhan B.Mohamed Ali selamat Faruk Ahmed AKM B.Hossain Department of Emergent Computing School of ComputingUniversiti Teknologi MalaysiaJohor Bahru81310Malaysia Malaysia-Japan International Institute of Technology(MJIIT) Universiti Teknologi MalaysiaKuala Lumpur54100Malaysia Media and Game Innovation Centre of Excellence(MaGICX) Universiti Teknologi MalaysiaJohor Bahru81310Malaysia Department of Engineering Technology University of MemphisMemphisTN38152USA Department of Computer science and Artificial Intelligence College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia school of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaJohor Bahru81310Malaysia Department of Information system and Cyber security College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia

Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance *** scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and *** research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image *** annotated image dataset trains the proposed system and predicts the camera pose in *** system mainly improved the localization performance of indoor cameras by more accurately predicting the camera *** also recognizes the scene changes during the sequence and evaluates the effects of these *** system achieved high accuracy and real-time *** scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact ***,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.

关键词： Camera pose estimation indoor camera localization real-time localization scene change detection simultaneous localization and mapping(sLAM)

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A systematic Literature Review of Machine Learning and Deep Learning Approaches for spectral Image Classification in Agricultural Applications Using Aerial Photography

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Computers, Materials & Continua 2024年第3期78卷 2967-3000页

作者： Usman Khan muhammad Khalid Khan muhammad Ayub Latif muhammad Naveed muhammad Mansoor alam salman A.Khan Mazliham Mohd su’ud College of Computing and Information sciences Karachi Institute of Economics and TechnologyKarachi75190Pakistan Faculty of Computing and Informatics(FCI) Multimedia UniversityCyberjaya63100Malaysia Faculty of Computing Riphah International UniversityIslamabad46000Pakistan Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneySydneyAustralia

Recently,there has been a notable surge of interest in scientific research regarding spectral *** potential of these images to revolutionize the digital photography industry,like aerial photography through Unmanned Aerial Vehicles(UAVs),has captured considerable *** encouraging aspect is their combination with machine learning and deep learning algorithms,which have demonstrated remarkable outcomes in image *** a result of this powerful amalgamation,the adoption of spectral images has experienced exponential growth across various domains,with agriculture being one of the prominent *** paper presents an extensive survey encompassing multispectral and hyperspectral images,focusing on their applications for classification challenges in diverse agricultural areas,including plants,grains,fruits,and *** meticulously examining primary studies,we delve into the specific agricultural domains where multispectral and hyperspectral images have found practical ***,our attention is directed towards utilizing machine learning techniques for effectively classifying hyperspectral images within the agricultural *** findings of our investigation reveal that deep learning and support vector machines have emerged as widely employed methods for hyperspectral image classification in ***,we also shed light on the various issues and limitations of working with spectral *** comprehensive analysis aims to provide valuable insights into the current state of spectral imaging in agriculture and its potential for future advancements.

关键词： Machine learning deep learning unmanned aerial vehicles multi-spectral images image recognition object detection hyperspectral images aerial photography

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sNR and RssI Based an Optimized Machine Learning Based Indoor Localization Approach:Multistory Round Building scenario over LoRa Network

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Computers, Materials & Continua 2024年第8期80卷 1927-1945页

作者： muhammad Ayoub Kamal muhammad Mansoor alam Aznida Abu Bakar sajak Mazliham Mohd su’ud Malaysian Institute of Information Technology(MIIT) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Computing and Informatics Multimedia UniversityCyberjaya63100Malaysia Depertment of Computer science DHA Suffa UniversityKarachiSindh75500Pakistan Riphah Institute of system Engineering(RIsE) Faculty of ComputingRiphah International UniversityIslamabad46000Pakistan Malaysian France Institute(MFI) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneyUltimoNSW 2007Australia

In situations when the precise position of a machine is unknown,localization becomes *** research focuses on improving the position prediction accuracy over long-range(LoRa)network using an optimized machine learning-based *** order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting method over LoRa technology,this study proposed an optimized machine learning(ML)based *** signal strength indicator(RssI)data from the sensors at different positions was first gathered via an experiment through the LoRa network in a multistory round layout *** noise factor is also taken into account,and the signal-to-noise ratio(sNR)value is recorded for every RssI *** study concludes the examination of reference point accuracy with the modified KNN method(MKNN).MKNN was created to more precisely anticipate the position of the reference *** findings showed that MKNN outperformed other algorithms in terms of accuracy and complexity.

关键词： Indoor localization MKNN LoRa machine learning classification RssI sNR localization

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AI-Driven Learning Management systems:Modern Developments, Challenges and Future Trends during theAge of ChatGPT

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Computers, Materials & Continua 2024年第8期80卷 3289-3314页

作者： sameer Qazi muhammad Bilal Kadri muhammad Naveed Bilal AKhawaja sohaib Zia Khan muhammad Mansoor alam Mazliham Mohd su’ud Department of Computer science Faculty of EngineeringScience and TechnologyIQRA UniversityKarachi75500Pakistan College of Computer and Information sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Engineering Department of Electrical EngineeringIslamic University of MadinahP.O.BOX 170Madinah41411Saudi Arabia Faculty of Engineering Department of Mechanical EngineeringIslamic University of MadinahP.O.BOX 170Madinah41411Saudi Arabia Faculty of Computing Riphah International UniversityIslamabad46000Pakistan Faculty of Computing and Informatics(FCI)Multimedia University Cyberjaya63100Malaysia Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneySydneyNSW 2007Australia

COVID-19 pandemic restrictions limited all social activities to curtail the spread of the *** foremost and most prime sector among those affected were schools,colleges,and *** education system of entire nations had shifted to online education during this *** shortcomings of Learning Management systems(LMss)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of *** paper presents a detailed survey of the different enhancements to LMss,which are led by key advances in the area of AI to enhance the real-time and non-real-time user *** AI-based enhancements proposed to the LMss start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMs utilities and resources,including AI-based *** layer enhancements are also required,such as AI-based online proctoring and user authentication using *** extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of *** also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of software-Defined Networks(sDN)for optimum Quality of service(Qos).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.

关键词： Learning management systems chatbots ChatGPT online education Internet of Things(IoT) artificial intelligence(AI) convolutional neural networks natural language processing

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Implications of electrode modifications in aqueous organic redox flow batteries

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Journal of Energy Chemistry 2024年第8期95卷 499-510,I0011页

作者： Zahid Manzoor Bhat Mohammad Furquan muhammad Aurang Zeb Gul sial Umair alam Atif saeed Alzahrani Mohammad Qamar Interdisciplinary Research Center for Hydrogen Technologies and Carbon Management(IRC-HTCM) King Fahd University of Petroleum&Minerals(KFUPM)Dhahran 31261Saudi Arabia Department of Materials science and Engineering King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia Interdisciplinary Research Center for sustainable Energy systems(IRC-sEs) King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia

Aqueous organic redox flow batteries(RFBs)exhibit favorable characteristics,such as tunability,multielectron transfer capability,and stability of the redox active molecules utilized as anolytes and catholytes,making them very viable contenders for large-scale grid storage *** attention has been paid on the development of efficient redox-active molecules and their performance optimization through chemical substitutions at various places on the backbone as part of the pursuit for high-performance *** the fact that electrodes are vital to optimal performance,they have not garnered significant *** research has been conducted on the effects of electrode modifications to improve the performance of *** primary emphasis has been given on the impact of electrode engineering to augment the efficiency of aqueous organic *** overview of electron transfer at the electrode-electrolyte interface is *** implications of electrode modification on the performance of redox flow batteries,with a particular focus on the anodic and cathodic half-cells separately,are then *** each section,significant discrepancies surrounding the effects of electrode engineering are thoroughly examined and ***,we have presented a comprehensive assessment along with our perspectives on the future trajectory.

关键词： Redox flow batteries Electrode modification Organic redox molecules Outer sphere and inner sphere

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Developing Lexicons for Enhanced sentiment Analysis in software Engineering:An Innovative Multilingual Approach for social Media Reviews

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Computers, Materials & Continua 2024年第5期79卷 2771-2793页

作者： Zohaib Ahmad Khan Yuanqing Xia Ahmed Khan muhammad sadiq Mahmood alam Fuad AAwwad Emad A.A.Ismail school of Automation Beijing Institute of TechnologyBeijing100081China Department of Computer science and Technology University of Science and Technology BannuKPKBannu28100Pakistan school of Computer science and Engineering Central South UniversityChangsha410083China Department of Quantitative Analysis College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh11587Saudi Arabia

sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significantsource of user-generated content. The development of sentiment lexicons that can support languages other thanEnglish is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existingsentiment analysis systems focus on English, leaving a significant research gap in other languages due to limitedresources and tools. This research aims to address this gap by building a sentiment lexicon for local languages,which is then used with a machine learning algorithm for efficient sentiment analysis. In the first step, a lexiconis developed that includes five languages: Urdu, Roman Urdu, Pashto, Roman Pashto, and English. The sentimentscores from sentiWordNet are associated with each word in the lexicon to produce an effective sentiment score. Inthe second step, a naive Bayesian algorithm is applied to the developed lexicon for efficient sentiment analysis ofRoman Pashto. Both the sentiment lexicon and sentiment analysis steps were evaluated using information retrievalmetrics, with an accuracy score of 0.89 for the sentiment lexicon and 0.83 for the sentiment analysis. The resultsshowcase the potential for improving software engineering tasks related to user feedback analysis and productdevelopment.

关键词： Emotional assessment regional dialects sentiWordNet naive bayesian technique lexicons software engineering user feedback

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Enhancing PDF Malware Detection through Logistic Model Trees

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Computers, Materials & Continua 2024年第3期78卷 3645-3663页

作者： muhammad Binsawad Department of Information systems King Abdulaziz UniversityP.O.Box 80217Jeddah21589Saudi Arabia

Malware is an ever-present and dynamic threat to networks and computer systems in cybersecurity,and because of its complexity and evasiveness,it is challenging to identify using traditional signature-based detection *** study article discusses the growing danger to cybersecurity that malware hidden in PDF files poses,highlighting the shortcomings of conventional detection techniques and the difficulties presented by adversarial *** article presents a new method that improves PDF virus detection by using document analysis and a Logistic Model *** a dataset from the Canadian Institute for Cybersecurity,a comparative analysis is carried out with well-known machine learning models,such as Credal Decision Tree,Naïve Bayes,Average One Dependency Estimator,Locally Weighted Learning,and stochastic Gradient *** traditional structural and Javascript-centric PDF analysis,the research makes a substantial contribution to the area by boosting precision and resilience in malware *** use of Logistic Model Tree,a thorough feature selection approach,and increased focus on PDF file attributes all contribute to the efficiency of PDF virus *** paper emphasizes Logistic Model Tree’s critical role in tackling increasing cybersecurity threats and proposes a viable answer to practical issues in the *** results reveal that the Logistic Model Tree is superior,with improved accuracy of 97.46%when compared to benchmark models,demonstrating its usefulness in addressing the ever-changing threat landscape.

关键词： Malware detection PDF files logistic model tree feature selection cybersecurity

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Neural network study of the nuclear ground-state spin distribution within a random interaction ensemble

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Nuclear science and Techniques 2024年第3期35卷 216-227页

作者： Deng Liu alam Noor A Zhen-Zhen Qin Yang Lei school of Mathematics and Physics Southwest University of Science and TechnologyMianyang 621010China school of Nuclear science and Technology Southwest University of Science and TechnologyMianyang 621010China

The distribution of the nuclear ground-state spin in a two-body random ensemble(TBRE)was studied using a general classification neural network(NN)model with two-body interaction matrix elements as input features and the corresponding ground-state spins as labels or output *** quantum many-body system problem exceeds the capability of our optimized NNs in terms of accurately predicting the ground-state spin of each sample within the ***,our NN model effectively captured the statistical properties of the ground-state spin because it learned the empirical regularity of the ground-state spin distribution in TBRE,as discovered by physicists.

关键词： Neural network Two-body random ensemble spin distribution of nuclear ground state

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Consequences of Rényi entropy on the thermal geometries and Hawking evaporation of topological dyonic dilaton black hole

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Communications in Theoretical Physics 2024年第2期76卷 102-110页

作者： muhammad Yasir Xia Tiecheng muhammad Usman shahid Chaudhary Department of Mathematics Shanghai University and Newtouch Center for Mathematics of Shanghai UniversityShanghai200444China Department of Natural sciences and Humanities University of Engineering and Technology LahoreNew CampusPakistan

The thermodynamics of black holes(BHs)has had a profound impact on theoretical physics,providing insight into the nature of gravity,the quantum structure of spacetime and the fundamental laws governing the *** this study,we investigate thermal geometries and Hawking evaporation of the recently proposed topological dyonic dilaton BH in anti-de sitter(Ad s)*** consider Rényi entropy and obtain the relations for pressure,heat capacity and Gibbs free energy and observe that the Rényi parameter and dilaton field play a vital role in the phase transition and stability of the ***,we use Weinhold,Ruppeiner and Hendi Panahiyah Eslam Momennia models to evaluate the scalar curvature of the BH and find out that the divergence points of the scalar curvature coincides with the zero of specific ***,using stefan–Boltzmann law,we determine that the BH without a dilaton field evaporates far more quickly compared to the dilaton BH in Ad s space.

关键词： topological dyonic dilaton black hole phase transition thermal geometry Hawking evaporation

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Tuning structural,electrical,dielectric and magnetic properties of Mg-Cu-Co ferrites via dysprosium(Dy^(3+))doping

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Journal of Rare Earths 2024年第1期42卷 137-146,I0005页

作者： Maria Akhtar M.s.Hasan Nasir Amin N.A.Morley muhammad Imran Arshad Department of Physics Government College UniversityFaisalabad38000Pakistan Department of Physics The University of Lahore53700Pakistan Department of Materials science and Engineering The University of SheffieldS13JDUK Department of Physics&Astronomy University College LondonUK

In current research work,Dy3+substituted Mg0.5Cu0.25Co0.25Fe2-xDyxO4(0.0≤x≤0.04 with the step interval of 0.01)soft ferrites were synthesized by the sol-gel auto combustion *** prepared samples were characterized by the techniques using X-ray diffraction(XRD),scanning electron microscopy(sEM),energy dispersive X-ray spectroscopy(EDs),Fourier transform infrared(FTIR)spectroscopy,curre nt-voltage(Ⅰ-Ⅴ)measurement,LCR meter,vibrating sample magnetometer(VsM)and *** data reveal that the average crystallite size is 49.71 nm and the lattice constant is 0.83703 nm for sample x=*** non-uniform grain growth was demonstrated by micrographs and impurity-free elemental composition was observed from EDX *** DC resistivity has an increasing and decreasing trend in ferromagnetic and paramagnetic regions with an increase in ***,the high resistivity is observed with the order of 1010Ω·cm,and the activation energy is 0.944 eV for samples x=*** dielectric parameters including dielectric constant,dielectric losses,and impedance gradually decrease with the increase in frequency from 8 Hz to 8 *** minimum dielectric loss at high frequency is found for sample x=*** coercivity(Hc)and saturation magnetization(Ms)are found in the ranges of 520.82-544.02 Oe and 20.5841-21.1473 emu/g,*** observations confirm that dysprosium(x=0.03)doped MCC-soft ferrites may be applicable in transformer cores,microwave absorbance,and telecommunication devices.

关键词： soft ferrites DC resistivity Dielectric loss Impedance Coercivity Rare earths

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