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Deep Learning Approach for Hand Gesture Recognition:Applications in Deaf Communication and Healthcare

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Computers, Materials & Continua 2024年第1期78卷 127-144页

作者： Khursheed Aurangzeb khalid Javeed Musaed Alhussein Imad Rida syed Irtaza Haider Anubha Parashar Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Kingdom of Saudi Arabia Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Laboratory Biomechanics and Bioengineering University of Technology of CompiegneCompiegne60200France Department of Computer Science and Engineering Manipal University JaipurJaipur303007India

Hand gestures have been used as a significant mode of communication since the advent of human *** facilitating human-computer interaction(HCI),hand gesture recognition(HGRoc)technology is crucial for seamless and error-free *** technology is pivotal in healthcare and communication for the deaf *** significant advancements in computer vision-based gesture recognition for language understanding,two considerable challenges persist in this field:(a)limited and common gestures are considered,(b)processing multiple channels of information across a network takes huge computational time during discriminative feature ***,a novel hand vision-based convolutional neural network(CNN)model named(HVCNNM)offers several benefits,notably enhanced accuracy,robustness to variations,real-time performance,reduced channels,and ***,these models can be optimized for real-time performance,learn from large amounts of data,and are scalable to handle complex recognition tasks for efficient human-computer *** proposed model was evaluated on two challenging datasets,namely the Massey University Dataset(MUD)and the American Sign Language(ASL)Alphabet Dataset(ASLAD).On the MUD and ASLAD datasets,HVCNNM achieved a score of 99.23% and 99.00%,*** results demonstrate the effectiveness of CNN as a promising HGRoc *** findings suggest that the proposed model have potential roles in applications such as sign language recognition,human-computer interaction,and robotics.

关键词： Computer vision deep learning gait recognition sign language recognition machine learning

Comparative analysis of CO_(2)emissions and economic performance in the United States and China:Navigating sustainable development in the climate change era

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Geoscience Frontiers 2024年第5期15卷 239-255页

作者： khalid Mehmood syed Tauseef Hassan Xuchun Qiu Shahid Ali Institute of Environmental Health and Ecological Security School of the Environment and Safety EngineeringJiangsu UniversityZhenjiangJiangsu 212013China Department of Trade and Finance Faculty of Economics and ManagementCzech University of Life Sciences PragueKamycka 129PrahaZIP 16500Czechia School of Economics and Management Anhui Polytechnic UniversityWuhu 241000China Jiangsu Collaborative Innovation Center of Technology and Material of Water Treatment Suzhou University of Science and TechnologySuzhou 215009China

Economic growth has brought a global climate change into the spotlight,and CO_(2)emissions demonstrate significant challenges in reducing environmental shifts ***,the United States and China contribute the largest amount of CO_(2)*** purpose of this study is to examine the relationship between different types of CO_(2)emissions and economic growth by using a modeling *** analyze total CO_(2)emissions,coal CO_(2)emissions,oil CO_(2)emissions,the global share of coal CO_(2)emissions,the global share of oil CO_(2)emissions,and economic *** study provides unique insights into how to simultaneously reduce CO_(2)emissions and sustain economic growth.A bootstrap autoregressive distributed lag(BARDL)simulation method is utilized to examine the long-and short-run effects of predictors on CO_(2)*** CO_(2)emissions are found to have a significant positive effect on economic growth in the short run but a negative impact on economic growth over the long run in the United *** United States needs to implement stronger measures to balance coal CO_(2)emissions with economic growth for sustainable *** contrast,oil CO_(2)emissions have positive effect for China in both the long run and short ***,China can continue to reduce CO_(2)emissions from oil while maintaining positive economic *** China’s policies promoting cleaner energy alternatives can be adapted and implemented to maintain a balance between economic growth and carbon *** study has valuable insights for policymakers seeking to balance economic growth with carbon reduction *** emphasizes the need to better understand the complex relationship between CO_(2)emissions and economic growth.

关键词： CO_(2)emission Sustainable development Climate change United States China BARDL

Model Agnostic Meta-Learning(MAML)-Based Ensemble Model for Accurate Detection of Wheat Diseases Using Vision Transformer and Graph Neural Networks

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Computers, Materials & Continua 2024年第5期79卷 2795-2811页

作者： Yasir Maqsood syed Muhammad Usman Musaed Alhussein Khursheed Aurangzeb Shehzad khalid Muhammad Zubair Department of Creative Technologies Faculty of Computing and Artificial IntelligenceAir UniversityIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Engineering Bahria School of Engineering and Applied SciencesBahria UniversityIslamabad44000Pakistan Laboratory for Neuro&Psychophysiology KU LeuvenLeuven3000Belgium

Wheat is a critical crop,extensively consumed worldwide,and its production enhancement is essential to meet escalating *** presence of diseases like stem rust,leaf rust,yellow rust,and tan spot significantly diminishes wheat yield,making the early and precise identification of these diseases vital for effective disease *** advancements in deep learning algorithms,researchers have proposed many methods for the automated detection of disease pathogens;however,accurately detectingmultiple disease pathogens simultaneously remains a *** challenge arises due to the scarcity of RGB images for multiple diseases,class imbalance in existing public datasets,and the difficulty in extracting features that discriminate between multiple classes of disease *** this research,a novel method is proposed based on Transfer Generative Adversarial Networks for augmenting existing data,thereby overcoming the problems of class imbalance and data *** study proposes a customized architecture of Vision Transformers(ViT),where the feature vector is obtained by concatenating features extracted from the custom ViT and Graph Neural *** paper also proposes a Model AgnosticMeta Learning(MAML)based ensemble classifier for accurate *** proposedmodel,validated on public datasets for wheat disease pathogen classification,achieved a test accuracy of 99.20%and an F1-score of 97.95%.Compared with existing state-of-the-art methods,this proposed model outperforms in terms of accuracy,F1-score,and the number of disease pathogens *** future,more diseases can be included for detection along with some other modalities like pests and weed.

关键词： Wheat disease detection deep learning vision transformer graph neural network model agnostic meta learning

Interpretable Detection of Malicious Behavior in Windows Portable Executables Using Multi-Head 2D Transformers

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Big Data Mining and Analytics 2024年第2期7卷 485-499页

作者： Sohail Khan Mohammad nauman Computer Science Department Effat College of EngineeringEffat UniversityJeddah 23341Kingdom of Saudi Arabia

Windows malware is becoming an increasingly pressing problem as the amount of malware continues to grow and more sensitive information is stored on *** of the major challenges in tackling this problem is the complexity of malware analysis,which requires expertise from human *** developments in machine learning have led to the creation of deep models for malware ***,these models often lack transparency,making it difficult to understand the reasoning behind the model’s decisions,otherwise known as the black-box *** address these limitations,this paper presents a novel model for malware detection,utilizing vision transformers to analyze the Operation Code(OpCode)sequences of more than 350000 Windows portable executable malware samples from real-world *** model achieves a high accuracy of 0.9864,not only surpassing the previous results but also providing valuable insights into the reasoning behind the *** model is able to pinpoint specific instructions that lead to malicious behavior in malware samples,aiding human experts in their analysis and driving further advancements in the *** report our findings and show how causality can be established between malicious code and actual classification by a deep learning model,thus opening up this black-box problem for deeper analysis.

关键词： machine learning malware vision transformers Windows Protable Executable(PE)

Deep Learning Based Efficient Crowd Counting System

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Computers, Materials & Continua 2024年第6期79卷 4001-4020页

作者： Waleed khalid Al-Ghanem Emad Ul Haq Qazi Muhammad Hamza Faheem syed Shah Amanullah Quadri Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Centre of Excellence in Cybercrime and Digital Forensics Naif Arab University for Security SciencesRiyadh14812Saudi Arabia Center of Excellence for Information Assurance(COEIA) King Saud UniversityRiyadh12372Saudi Arabia

Estimation of crowd count is becoming crucial nowadays,as it can help in security surveillance,crowd monitoring,and management for different *** is challenging to determine the approximate crowd size from an image of the crowd’s *** in this research study,we proposed a multi-headed convolutional neural network architecture-based model for crowd counting,where we divided our proposed model into two main components:(i)the convolutional neural network,which extracts the feature across the whole image that is given to it as an input,and(ii)the multi-headed layers,which make it easier to evaluate density maps to estimate the number of people in the input image and determine their number in the *** employed the available public benchmark crowd-counting datasets UCF CC 50 and ShanghaiTech parts A and B for model training and testing to validate the model’s *** analyze the results,we used two metrics Mean Absolute Error(MAE)and Mean Square Error(MSE),and compared the results of the proposed systems with the state-of-art models of crowd *** results show the superiority of the proposed system.

关键词： Crowd counting EfficientNet multi-head attention convolutional neural network transfer learning

In-cylinder in-depth combustion investigation for a heavy-duty diesel engine

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Propulsion and Power Research 2024年第3期13卷 335-359页

作者： Anam Ali khalid Saifullah syed Centre for Advanced Studies in Pure and Applied Mathematics(CASPAM) Bahauddin Zakariya University(BZU)MultanPunjab 60800Pakistan

t This present study is part of the design improvement process of a specified high torque low-speed *** work aims at carrying out an in-depth analysis of in-cylinder combustion,mesh sensitivity,and engine performance at supercharge conditions to provide a foundation for the design improvement process of the given *** computational fluid dynamic(CFD)simulations are carried out on a 3D sector from-130°to 130°crank angle(CA)by employing appropriate models to represent the different physical and chemical processes and using the finite volume method for solving the governing differential *** extensive investigation has been carried out for the choice of base mesh size and the number of local and temporal refinements to capture the phenomena happening in the combustion chamber at diverse temporal and local *** present results have been validated against available literature experimental and simulation *** field variables and the wellknown four phases of combustion have been studied for gaining in-depth insight into these *** average pressure,mean temperature,heat release rate(HRR),integrated heat release rate(IHRR),and emissions of CO2,CO,NOx,HC and soot are presented to assess the quality of *** performance analysis has been done in terms of combustion ef-ficiency,gross work,power,torque,and integrated mean effective pressure(IMEP).The base mesh of 1.4 mm may be an appropriate choice during the injection and combustion process spanning throughout around 40CA from the start of injection while in the remaining simulation duration of around 220CA base mesh of 2 mm gives a sufficient *** has been found that maximum heat release takes place in Phase-III,the mixing-controlled phase,of the combustion *** than 98%combustion efficiency has been achieved in all the *** 99%of the total heat release and emissions production takes place within 60CA after top dead center(ATD

关键词： Phases of combustion Heat release rate(HRR) Integrated heat release rate(IHRR) Emissions Performance parameters

Coupling of reduced inorganic fertilizer with plant-based organic fertilizer as a promising fertilizer management strategy for colored rice in tropical regions

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Journal of Integrative Agriculture 2024年第1期23卷 93-107页

作者： Tingcheng Zhao Aibin He Mohammad nauman Khan Qi Yin Shaokun Song Lixiao Nie Research Center for Physiology and Ecology and Green Cultivation of Tropical Crops School of Breeding and Multiplication(Sanya Institute of Breeding and Multiplication)Hainan UniversitySanya 572000China

Colored rice is a type of high-quality,high-added-value rice that has attracted increasing attention in recent *** use of large amounts of inorganic nitrogen fertilizer in rice fields results in low fertilizer use efficiency and high environmental *** fertilizer is a promising way to improve soil quality and sustain high ***,most studies focus on the effect of animal-based organic *** effects of different ratios of plantbased organic fertilizer and inorganic fertilizer on the grain yield and quality of colored rice have rarely been ***,a two-year field experiment was conducted in 2020 and 2021 to study the effects of replacing inorganic N fertilizers with plant-based organic fertilizers on the yield,nitrogen use efficiency(NUE),and anthocyanin content of two colored rice varieties in a tropical region in *** experimental treatments included no nitrogen fertilization(T1),100% inorganic nitrogen fertilizer(T2),30%inorganic nitrogen fertilizer substitution with plant-based organic fertilizer(T3),60%inorganic nitrogen fertilizer substitution with plant-based organic fertilizer(T4),and 100% plantbased organic fertilizer(T5).The total nitrogen provided to all the treatments except T1 was the same at 120 kg *** results showed that the T3 treatment enhanced the grain yield and anthocyanin content of colored rice by increasing nitrogen use efficiency compared with *** average,grain yields were increased by 9 and 8%,while the anthocyanin content increased by 16 and 10% in the two colored rice varieties under T3 across the two years,respectively,as compared with *** study of the residual effect of partial substitution of inorganic fertilizers showed that the substitution of inorganic fertilizer with plant-based organic fertilizer improved the soil physiochemical properties,and thus increased the rice grain yield,in the subsequent *** highest grain yield of the subsequent rice crop was observe

关键词： colored rice organic fertilizer soil quality grain yield anthocyanin

Effect of Light Emitting Diodes (LEDs) on Growth, Mineral Composition, and Nutritional Value of Wheat & Lentil Sprouts

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Phyton-International Journal of Experimental Botany 2024年第6期93卷 1117-1128页

作者： Abdul Momin Amana Khatoon Wajahat Khan Dilsat Bozdoğan Konuşkan Muhammad Mudasar Aslam Muhammad Jamil Shafiq Ur Rehman Baber Ali Alevcan Kaplan Sana Wahab Muhammad nauman Khan Sezai Ercisli Mohammad khalid Al-Sadoon Department of Botany Kohat University of Science&TechnologyKohat26000Pakistan Department of Food Engineering Faculty of AgricultureHatay Mustafa Kemal UniversityHatay31000Türkiye Department of Botany University of Science&TechnologyBannu28100Pakistan Department of Biotechnology and Genetic Engineering Kohat University of Science&TechnologyKohat26000Pakistan Department of Biology University of HaripurKhyber Pakhtunkhwa22620Pakistan School of Science Western Sydney UniversityPenrithNew South Wales2151Australia Department of Crop and Animal Production Sason Vocational SchoolBatman UniversityBatman72060Türkiye Department of Plant Sciences Quaid-i-Azam UniversityIslamabad45320Pakistan Department of Botany Islamia College PeshawarPeshawar25120Pakistan Department of Horticulture Agricultural FacultyAtaturk UniversityErzurum25240Türkiye HGF Agro Ata TeknokentErzurumTR-25240Türkiye Department of Zoology College of ScienceKing Saud UniversityRiyadh11451Saudi Arabia

Sprouts are ready-to-eat and are recognized worldwide as functional components of the human *** advances in innovative agricultural techniques could enable an increase in the production of healthy *** use of light-emitting diode(LED)in indoor agricultural production could alter the biological feedback loop,increasing the functional beneﬁts of plant foods such as wheat and lentil sprouts and promoting the bioavailability of *** effects of white(W),red(R),and blue(B)light were investigated on the growth parameters and nutritional value of wheat and lentil *** the laboratory,seeds were sown under three different LED treat-ments:white,red,and blue light,while normal incandescent light served as a *** seed germina-tion improved by 18.34%and 12.67%for wheat and 18.34%and 12.67%for lentil sprouts under LED treatments R and B,*** increase in total soluble protein and sugar by 33.4%and 9.23%in wheat and by 31.5%and 5.87%in lentils was observed under the R LED *** C concentrations in wheat and lentils were signiﬁcantly increased by R LED compared to all other *** parameters,including potassium and sodium concentrations,were signiﬁcantly increased under red and blue light compared to the control;white light,on the other hand,signiﬁcantly decreased all these *** to the experimental data,red and blue LED light could be beneﬁcial in the production of functional wheat and lentil sprouts with high nutrient concentrations.

关键词： Growth parameters LED nutritional value sprouts total soluble proteins

A Framework to Assess Possible Sources of Stakeholder Exploitation:A Developing Country Case

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International Journal of Disaster Risk Science 2024年第1期15卷 32-44页

作者： Kamran Shafique syed Shams Tapan Sarker School of Business University of Southern QueenslandSpringfeldQLD 4300Australia Business School University of QueenslandSt LuciaQLD 4072Australia

Solving complex post-disaster reconstruction challenges requires the altruistic involvement of heterogeneous stakeholder ***,small,more organized groups,such as government parastatals,private developers,and contractors often exploit large,unorganized groups,such as affected communities,leaving them more vulnerable to future *** on data collected from a case study in Pakistan,this study proposed a framework to assess,anticipate,and mitigate the exploitation of vulnerable stakeholders in post-disaster reconstruction *** framework draws on influential management theories and utilizes reciprocal relationships between stakeholder attributes(power,legitimacy,and urgency),participation,and *** study also argued for non-binary treatment of stakeholder *** framework will allow practitioners to address issues around the exploitation of stakeholder interests in future post-disaster reconstruction projects.

关键词： Collective action Pakistan Post-disaster reconstruction-Stakeholder participation Stakeholder exploitation