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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

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

Fabrication of MXene-Bi_(2)WO_(6)heterojunction by Bi_(2)Ti_(2)O_(7)hinge for extraordinary LED-light-driven photocatalytic performance

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Nano Research 2024年第6期17卷 4729-4736页

作者： Zhiwen Li Liangliang Xu Zaheer ud Din Babar Ali Raza Yifei Zhang Xinrui gu Yu-Xin Miao Zhen Zhao gao Li Institute of Catalysis for Energy and Environment College of Chemistry and Chemical EngineeringShenyang Normal UniversityShenyang 110034China State Key Laboratory of Catalysis Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023China Scuola Superiore Meridionale(SSM) University of Naples Federico IILargo S.Marcellino1080138Italy Department of Chemical and Biomolecular Engineering Korea Advanced Institute of Science and Technology(KAIST)Daejeon 34141Republic of Korea University of Chinese Academy of Sciences Beijing 100049China

Heterojunction composites with intimate interfaces can shorten the diffusion distance,which leads to a shorter path for photogenerated carriers,thereby increasing photocatalytic ***,we report the fabrication of Ti_(3)C_(2)-Bi_(2)WO_(6)(TC-BW)heterojunctions hinged by Bi_(2)Ti_(2)O_(7)joints via an in situ hydrothermal reaction of Ti_(3)C_(2)in the presence of Na_(2)WO_(4)and Bi(NO_(3))_(3).The TC-BW was characterized using X-ray diffraction(XRD),scanning transmission electron microscopy(STEM),and Raman ***-BW showed superior photocatalytic activity(productivity over 15TC-WB reaches up to 5.0 mmolreacted BA·gcat.^(−1)·h^(−1))in the oxidation of benzyl alcohol using light-emitting diode(LED)light,arising from the surface defects and intimate heterojunction interface between the Ti_(3)C_(2)MXene and Bi_(2)WO_(6)***-BW heterojunctions provide an enhanced separation efficiency of photogenerated charges,which in turn yields superior photocatalytic ***,it is well substantiated by density functional theory(DFT)*** summary,this study elucidates the preparation of heterojunction composites with intimate interfaces for highly efficient photooxidation.

关键词： MXene-Bi_(2)WO_(6) heterojunction LED-light-driven photocatalysis Bi_(2)Ti_(2)O_(7) photooxidation

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

Straw return influences the structure and functioning of arbuscular mycorrhizal fungal community in a rice-wheat rotation system

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Pedosphere 2024年第2期34卷 339-350页

作者： Silong ZHAI Junjie XIE Zongyi TONg Bing YANg Weiping CHEN Roger TKOIDE Yali MENg Xiaomin HUANg Atta Mohi ud DIN Changqing CHEN Haishui YANg College of Agriculture Nanjing Agricultural UniversityNanjing 210095China Department of Biology Brigham Young UniversityProvo UT 84602USA Jiangsu Key Laboratory of Crop genetics and Physiology/Jiangsu Key Laboratory of Crop Cultivation and Physiology Agricultural College of Yangzhou UniversityYangzhou 225009China National Research Center of Intercropping The Islamia University of BahawalpurBahawalpur 63100Pakistan Jiangsu Collaborative Innovation Center for Modern Crop Production Nanjing Agricultural UniversityNanjing 210095China

Straw return is a sustainable soil fertility-building practice,which can affect soil microbial ***,how straw return affects arbuscular mycorrhizal fungi(AMF)is not well ***,we studied the impacts of different straw management treatments over eight years on the structure and functioning of AMF communities in a rice-wheat rotation *** straw management treatments included no tillage with no straw(NTNS),rotary tillage straw return(RTSR),and ditch-buried straw return(DBSR).The community structure of AMF was characterized using high-throughput sequencing,and the mycorrhizal functioning was quantified using an in situ mycorrhizal-suppression *** straw management treatments formed unique AMF community structure,which was closely related to changes in soil total organic carbon,available phosphorus,total nitrogen,ammonium,and *** compared with NTNS,RTSR significantly increased Shannon diversity in 0–10 cm soil layer,while DBSR increased it in 10–20 cm soil layer;DBSR significantly increased hyphal length density in the whole ploughing layer(0–20 cm),but RTSR only increased it in the subsurface soil layer(10–20 cm).The mycorrhizal responses of shoot biomass and nutrient(N and P)uptake were positive under both straw return treatments(RTSR and DBSR),but negative under *** community composition of AMF was significantly correlated to hyphal length density,and the latter was further a positive predictor for the mycorrhizal responses of plant growth and nutrient *** findings suggest that straw return can affect AMF community structure and functioning,and farmers should manage mycorrhizas to strengthen their beneficial effects on crop production.

关键词： community structure hyphal length density shoot biomass shoot N uptake shoot P uptake soil physicochemical properties straw management tillage

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柔性条状基热电织物的设计及织造（英文）

Journal of Donghua University(English Edition) 2024年

作者： AHMAAD Hasib ud Din 杜敏芝韩雪景媛媛杨晓娜张娟陈馨逸 SYED Rashedul Islam 黄夫力徐金川张坤东华大学纺织学院东华大学纺织面料技术教育部重点实验室

可将热量转化为电能的柔性热电（thermoelectric,TE）材料已广泛应用于可穿戴电子设备和其他柔性设备中。该研究将无机TE柱与热塑性聚氨酯（thermoplastic polyurethane,TPU）结合,组装成柔性条状热电器（thermoelectric generator,TEg... 详细信息

可将热量转化为电能的柔性热电（thermoelectric,TE）材料已广泛应用于可穿戴电子设备和其他柔性设备中。该研究将无机TE柱与热塑性聚氨酯（thermoplastic polyurethane,TPU）结合,组装成柔性条状热电器（thermoelectric generator,TEg）,进一步用于热电织物（thermoelectric fabric,TEF）的织造。采用有限元分析（finite element analysis,FEA）优化柔性TE条的尺寸并评估其性能。FEA的结果显示,TE条的间距对温差、输出电压和内阻有显著影响。当TE条直径为3.5 mm、条间距为2 mm时,可获得最大功率密度,达到3.43μW·cm-2（在温差ΔT=10.5 K的条件下）。在实验条件下,热板接触以及铜线-TE条连接处存在倾斜度,导致所织造的三维TEF的功率密度只能达到模拟结果的29%。尽管如此,在经过450次弯曲测试后,TE条仍展现出优异的柔韧性和稳定的机械性能。这一研究不仅为今后开发更高效的TEF奠定了基础,还为可穿戴式能量采集应用提供了更加舒适、合身的选择方案。

关键词：热电织物(TEF) 热电柱(TE柱) 热塑性聚氨酯(TPU) 有限元分析(FEA)

Human Verification over Activity Analysis via Deep data Mining

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Computers, Materials & Continua 2023年第4期75卷 1391-1409页

作者： Kumar Abhishek Sheikh Badar ud din Tahir Senior Member IEEESeattle98103USA Department of Software Engineering Capital University of Science and Technology(CUST)Islamabad44000Pakistan

Human verification and activity analysis(HVAA)are primarily employed to observe,track,and monitor human motion patterns using redgreen-blue(RgB)images and *** human interaction using RgB images is one of the most complex machine learning tasks in recent *** models rely on various parameters,such as the detection rate,position,and direction of human body components in RgB *** paper presents robust human activity analysis for event recognition via the extraction of contextual intelligence-based *** use human interaction image sequences as input data,we first perform a few denoising ***,human-to-human analyses are employed to deliver more precise *** phase follows feature engineering techniques,including diverse feature ***,we used the graph mining method for feature optimization and AdaBoost for *** tested our proposed HVAA model on two benchmark *** testing of the proposed HVAA system exhibited a mean accuracy of 92.15%for the Sport Videos in theWild(SVW)*** second benchmark dataset,UT-interaction,had a mean accuracy of 92.83%.Therefore,these results demonstrated a better recognition rate and outperformed other novel techniques in body part tracking and event *** proposed HVAA system can be utilized in numerous real-world applications including,healthcare,surveillance,task monitoring,atomic actions,gesture and posture analysis.

关键词： AdaBoost classification deep features mining graph mining human detection human verification

Energy-Efficient Scheduling Based on Task Migration Policy Using DPM for Homogeneous MPSoCs

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Computers, Materials & Continua 2023年第1期74卷 965-981页

作者： Hamayun Khan Irfan ud din Arshad Ali Sami Alshmrany Department of Electrical Engineering Faculty of Engineering&Technology Superior University Lahore54000Pakistan Department of Computer Science Faculty of Computer Science&IT Superior University Lahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahAl Madinah Al Munawarah42351Saudi Arabia

Increasing the life span and efficiency of Multiprocessor System on Chip(MPSoC)by reducing power and energy utilization has become a critical chip design challenge for multiprocessor *** the advancement of technology,the performance management of central processing unit(CPU)is *** densities and thermal effects are quickly increasing in multi-core embedded technologies due to shrinking of chip *** energy consumption reaches a threshold that creates a delay in complementary metal oxide semiconductor(CMOS)circuits and reduces the speed by 10%–15%because excessive on-chip temperature shortens the chip’s life *** this paper,we address the scheduling&energy utilization problem by introducing and evaluating an optimal energy-aware earliest deadline first scheduling(EA-EDF)based technique formultiprocessor environments with task migration that enhances the performance and efficiency in multiprocessor systemon-chip while lowering energy and power *** selection of core andmigration of tasks prevents the system from reaching itsmaximumenergy utilization while effectively using the dynamic power management(DPM)*** in the execution of tasks the temperature and utilization factor(u_(i))on-chip increases that dissipate more *** proposed approach migrates such tasks to the core that produces less heat and consumes less power by distributing the load on other cores to lower the temperature and optimizes the duration of idle and sleep times across multiple *** performance of the EA-EDF algorithm was evaluated by an extensive set of experiments,where excellent results were reported when compared to other current techniques,the efficacy of the proposed methodology reduces the power and energy consumption by 4.3%–4.7%on a utilization of 6%,36%&46%at 520&624 MHz operating frequency when particularly in comparison to other energy-aware methods for *** are running and accurately scheduled to make an energy-efficient

关键词： Dynamic power management dynamic voltage&frequency scaling dynamic thermal management multiprocessor system on chip complementary metal oxide semiconductor reliability

Output Linearization of Single-Input Single-Output Fuzzy System to Improve Accuracy and Performance

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Computers, Materials & Continua 2023年第5期75卷 2413-2427页

作者： Salah-ud-din Khokhar QinKe Peng Muhammad Yasir Noor Department of Automation Science and Technology(System Engineering Institute) School of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’anShaanxi710049China Department of Computer Science G.C.UniversityLahore54000PunjabPakistan Department of Physics(Electronics) G.C.UniversityLahore54000PunjabPakistan

For fuzzy systems to be implemented effectively,the fuzzy membership function(MF)is essential.A fuzzy system(FS)that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output(SISO)FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s *** a variety of non-linear techniques,a SISO FS is *** results of FS experiments conducted in comparable conditions are then *** simulated results and the results of the experimental setup agree fairly *** findings of the suggested model demonstrate that the relative error is abated to a sufficient range(≤±10%)and that the mean absolute percentage error(MPAE)is reduced by around 66.2%.The proposed strategy to reduceMAPE using an FS improves the system’s performance and control *** using the best input and output MFs protocol,the energy and financial efficiency of every SISO FS can be improved with very little tuning of *** proposed fuzzy system performed far better than other modern days approaches available in the literature.

关键词： Mean absolute percentage error membership functions relative error fuzzy system