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The role of green industrial transformation in mitigating carbon emissions:Exploring the channels of technological innovation and environmental regulation

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Energy and Built Environment 2024年第3期5卷 464-479页

作者： Saima mehmood khalid Zaman Shiraz Khan Zohaib Ali Haroon ur Rashid Khan Department of Economics The University of HaripurHaripurKhyber Pakhtunkhwa 22620Pakistan Department of Management Sciences The University of HaripurHaripurKhyber Pakhtunkhwa 22620Pakistan Department of Energy and Process Engineering(EPT) Norwegian University of Science and TechnologyHøgskoleringen 1Trondheim 7034Norway Faculty of Business The University of Wollongong in DubaiDubai 20183United Arab Emirates

The industrial sector is vital to economic progress,yet industrial pollution poses environmental and economic *** purpose of the study was to investigate the influence of green industrial transformation in re-ducing Pakistan’s carbon intensity between 1975 and *** emissions are considered an endogenous construct,while foreign direct investment(FDI)inflows,technological innovation,green industrial transforma-tion,environmental legislation,and research and development(R&D)investment are possible *** association between variables is assessed using the robust least-squares *** industrial transforma-tion is connected with lower carbon emissions,yet technical innovation,R&D investment,and inbound FDI raise a country’s carbon *** findings support the pollution haven hypothesis in a *** causality esti-mates indicate that inward FDI contributes to environmental regulations;green industrial transformation directly relates to inbound FDI and R&D expenditures;and technological innovations correspond to inbound FDI,R&D ex-penditures,industrial ecofriendly progression,and environmental *** to the impulse response function,environmental policies are anticipated to have a differential effect on carbon emissions in 2023,2024,2028-2030,while they are likely to decrease in the years 2025-2027 and 2031 ***,inward FDI and technology advancements would almost certainly result in a rise in carbon emissions over *** industrial transitions are projected to result in a ten-year reduction in carbon *** variance decomposi-tion analysis indicates that eco-friendly industrial adaptations would likely have the largest variance error shock on carbon emissions(11.747%),followed by inbound FDI,technological advancements,and regulatory changes,with R&D spending having a minimal impact over ***’s economy should foster a green industrial revolution to avoid pollution and increase environm

关键词： Carbon intensity Industrial green transformation Environmental regulations Technological innovations Robust least squares regression

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Characteristics of biomass ashes from different materials and their ameliorative effects on acid soils

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Journal of Environmental Sciences 2017年第5期29卷 294-302页

作者： Renyong Shi Jiuyu Li Jun Jiang khalid mehmood Yuan Liu Renkou Xu Wei Qian State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences Nanjing 210008 China. University of Chinese Academy of Sciences Beijing 100049 China

The chemical characteristics,element contents,mineral compositions,and the ameliorative effects on acid soils of five biomass ashes from different materials were analyzed. The chemical properties of the ashes varied depending on the source biomass material. An increase in the concrete shuttering contents in the biomass materials led to higher alkalinity,and higher Ca and Mg levels in biomass ashes,which made them particularly good at ameliorating effects on soil acidity. However,heavy metal contents,such as Cr,Cu,and Zn in the ashes,were relatively high. The incorporation of all ashes increased soil p H,exchangeable base cations,and available phosphorus,but decreased soil exchangeable acidity. The application of the ashes from biomass materials with a high concrete shuttering content increased the soil available heavy metal contents. Therefore,the biomass ashes from wood and crop residues with low concrete contents were the better acid soil amendments.

关键词： Biomass ashes Raw materials Element composition Chemical properties Amelioration of acidic soils Available heavy metals

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Early Detection of Diabetic Retinopathy Using Machine Intelligence throughDeep Transfer and Representational Learning

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Computers, Materials & Continua 2021年第2期66卷 1631-1645页

作者： Fouzia Nawaz Muhammad Ramzan khalid mehmood Hikmat Ullah Khan Saleem Hayat Khan Muhammad Raheel Bhutta Department of Computer Science and Information Technology University of SargodhaSargodha40100Pakistan and School of Systems and TechnologyUniversity of Management and TechnologyLahore54782Pakistan Department of Computer Science COMSATS University IslamabadWah CampusIslamabadPakistan University Hospital Birmingham BirminghamUK Shifa International Hospital IslamabadPakistan Department of Computer Science and Engineering Sejong UniversitySeoulKorea

Diabetic retinopathy (DR) is a retinal disease that causes irreversible *** occurs due to the high blood sugar level of the patient, and it is clumsy tobe detected at an early stage as no early symptoms appear at the initial level. To preventblindness, early detection and regular treatment are needed. Automated detectionbased on machine intelligence may assist the ophthalmologist in examining thepatients’ condition more accurately and efficiently. The purpose of this study is toproduce an automated screening system for recognition and grading of diabetic retinopathyusing machine learning through deep transfer and representational *** artificial intelligence technique used is transfer learning on the deep neural network,Inception-v4. Two configuration variants of transfer learning are applied onInception-v4: Fine-tune mode and fixed feature extractor mode. Both configurationmodes have achieved decent accuracy values, but the fine-tuning method outperformsthe fixed feature extractor configuration mode. Fine-tune configuration modehas gained 96.6% accuracy in early detection of DR and 97.7% accuracy in gradingthe disease and has outperformed the state of the art methods in the relevant literature.

关键词： Diabetic retinopathy artificial intelligence automated screening system machine learning deep neural network transfer and representational learning

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Water-filling algorithm based approach for management of responsive residential loads

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Journal of Modern Power Systems and Clean Energy 2018年第1期6卷 118-131页

作者： Zunaib Maqsood HAIDER Khawaja khalid mehmood Muhammad Kashif RAFIQUE Saad Ullah KHAN Soon-Jeong LEE Chul-Hwan KIM College of Information and Communication Engineering Sungkyunkwan University

Integration of large number of electric vehicles(EVs)with distribution networks is devastating for conventional power system devices such as transformers and power lines *** paper proposes a methodology for management of responsive household appliances management and EVs with water-filling *** the proposed scheme,the load profile of a transformer is retained below its rated capacity while minimally affecting the associated *** the instantaneous demand at transformer increases beyond its capacity,the proposed methodology dynamically allocates demand curtailment limit(DCL)to each home served by *** DCL allocation takes convenience factors,load profile and information of flexible appliances into account to assure the comfort of all the *** proposed scheme is verified by modeling and simulating five houses and a distribution *** smart appliances such as an HVAC,a water heater,a cloth dryer and an EV are also modeled for the *** show that the proposed scheme performs to reduce overloading effects of the transformer efficiently and assures comfort of the consumers at the same time.

关键词： Water-filling(WF) algorithm Responsive household appliances management(RHAM) Electric vehicle(EV) Demand curtailment limit(DCL) Convenience factor Load profile

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DeBERTa-GRU: Sentiment Analysis for Large Language Model

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Computers, Materials & Continua 2024年第6期79卷 4219-4236页

作者： Adel Assiri Abdu Gumaei Faisal mehmood Touqeer Abbas Sami Ullah Department of Informatics for Business College of BusinessKing Khalid UniversityAbha61421Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou450001China Department of Computer Science and Technology Beijing University of Chemical TechnologyBeijing100029China Department of Computer Science Government College University FaisalabadFaisalabadPunjab38000Pakistan

Modern technological advancements have made social media an essential component of daily *** media allow individuals to share thoughts,emotions,and *** analysis plays the function of evaluating whether the sentiment of the text is positive,negative,neutral,or any other personal emotion to understand the sentiment context of the *** analysis is essential in business and society because it impacts strategic *** analysis involves challenges due to lexical variation,an unlabeled dataset,and text distance *** execution time increases due to the sequential processing of the sequence ***,the calculation times for the Transformer models are reduced because of the parallel *** study uses a hybrid deep learning strategy to combine the strengths of the Transformer and Sequence models while ignoring their *** particular,the proposed model integrates the Decoding-enhanced with Bidirectional Encoder Representations from Transformers(BERT)attention(DeBERTa)and the Gated Recurrent Unit(GRU)for sentiment *** the Decoding-enhanced BERT technique,the words are mapped into a compact,semantic word embedding space,and the Gated Recurrent Unit model can capture the distance contextual semantics *** proposed hybrid model achieves F1-scores of 97%on the Twitter Large Language Model(LLM)dataset,which is much higher than the performance of new techniques.

关键词： DeBERTa GRU Naive Bayes LSTM sentiment analysis large language model

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Microbiome analysis reveals soil microbial community alteration with the effect of animal excretion contamination and altitude in Tibetan Plateau of China

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International Soil and Water Conservation Research 2021年第4期9卷 639-648页

作者： Aoyun Li Yaping Wang Yajing Wang Hailong Dong Qingxia Wu khalid mehmood Zhenyu Chang Ying Li Yung-Fu Chang Lijun Shi Zhaoxin Tang Hui Zhang College of Veterinary Medicine South China Agricultural UniversityGuangzhou510642China College of Veterinary Medicine Huazhong Agricultural UniversityWuhan430070China Tibet Agriculture and Animal Husbandry College Linzhi860000TibetChina Faculty of Veterinary and Animal Sciences The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Population Medicine and Diagnostic Sciences College of Veterinary MedicineCornell UniversityIthacaNYUSA Institute of Animal Sciences Chinese Academy of Agricultural SciencesBeijing100193China

The fertile forages in the Tibetan Plateau provide natural conditions for animal husbandry,whereas it is still unclear that whether animal excretion can result in the alteration of soil microbial ***,this study was performed to investigate the impact of animal excretion contamination and land altitude on the soil microbial community in different grazing areas of Tibetan Plateau.A total of 1160,190 high-quality valid sequences and 25,478 operational taxonomic units were achieved from 18 samples at three different altitude sites(Linzhi,Rikaze and Shannan).Here,we found excremental contamination did not alter the richness and diversity of soil microbial community,but it resulted in a significant alteration in the proportion of some ***,the proportion of Proteobacteria in the LZa was obviously increased,whereas Gemmatimonadetes was significantly decreased as compared to ***,significant difference can also be observed in Verrucomicrobia between RKZe and ***,we also found that excremental contamination significantly decreased the abundance of some bacterial genera,such as Sphingopyxis,Polycyclovorans,Singulisphaera Cohnella,Polycyclovorans,Defluviicoccus,and Arthrobacter,which were closely related to soil health,pollutant degradation,and nutrient ***,excremental contamination increased the proportion of harmful and beneficial bacteria in soil,such as the percentage of Acidibacter,Gemmatimonadaceae and Pajaroellobacter increased,while the ratio of Pontibacter,Flavisolibacter,Parasegetibacter,and Niastella ***,soil samples collected from different altitude sites also displayed different soil microbial community *** results demonstrated that excremental contamination could alter the soil microbial community structure and affect the normal function of the soil by affecting the proportion of harmful bacteria to beneficial ***,this study can also provide a theoret

关键词： Soil microbial community High-throughput sequencing Excremental contamination Tibet

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Caching Strategies in NDN Based Wireless Ad Hoc Network:A Survey

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Computers, Materials & Continua 2024年第7期80卷 61-103页

作者： Ahmed khalid Rana Asif Rehman Byung-Seo Kim Department of Computer Science FAST School of ComputingNational University of Computer and Emerging SciencesLahore54000Pakistan Department of Software and Communications Engineering Hongik UniversitySejong City30016Republic of Korea

Wireless Ad Hoc Networks consist of devices that are wirelessly *** Ad Hoc Networks(MANETs),Internet of Things(IoT),and Vehicular Ad Hoc Networks(VANETs)are the main domains of wireless ad hoc *** is used in wireless ad hoc *** is based on Transmission Control Protocol(TCP)/Internet Protocol(IP)network where clients and servers interact with each other with the help of IP in a pre-defined *** fetches data from a fixed *** redundancy,mobility,and location dependency are the main issues of the IP network *** these factors result in poor performance of wireless ad hoc *** main disadvantage of IP is that,it does not provide in-network ***,there is a need to move towards a new network that overcomes these *** Data Network(NDN)is a network that overcomes these *** is a project of Information-centric Network(ICN).NDN provides in-network caching which helps in fast response to user *** NDN in wireless ad hoc network provides many benefits such as caching,mobility,scalability,security,and *** considering the certainty,in this survey paper,we present a comprehensive survey on Caching Strategies in NDN-based Wireless *** cachingmechanism-based results are also *** the last,we also shed light on the challenges and future directions of this promising field to provide a clear understanding of what caching-related problems exist in NDN-based wireless ad hoc networks.

关键词： Content centric network Internet of Things mobile ad hoc network named data network vehicular ad hoc network

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Hydrometallurgy two stage process for preparation of (Nd,La,Ce)_(2)O_(3) from end-of-life NiMH batteries

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Journal of Rare Earths 2024年第2期42卷 415-423,I0007页

作者： Karim Tanji khalid Ouzaouit Mohamed Belghiti Isam Lamsayety Hakim Faqir Intissar Benzakour Centre de recherche REMINEX-Groupe MANAGEM MarrakechMorocco

The present work aims to investigate the recovery of light rare earth elements(LREEs) oxides from end-oflife NiMH batteries using a hydro metallurgical process followed by effective *** operational leaching parameters such as phosphoric acid concentration,temperature,and the solid-liquid ratio were first optimized by Box-Behnken *** results reveal that under optimum conditions([H_(3)PO_(4)]=2 mol/L,T=80℃,and S/L=1:10 g/mL) the leaching efficiencies of Ni,Co reach 98.1% and99.3%.While La,Ce,and Nd elements remain in the leaching residue as(La,Ce,Nd)PO_(4) with yields of 98.2%,98.6%,and 99.6% for La,Ce,and Nd,***,the(La,Ce,Nd)PO_(4) is leached with HCl acid,then the rare earth oxalate was precipitated using oxalic acid at a pH of 1.8 and then the product was calcined at 800℃ for 2 h in order to synthesize the(Nd,La,Ce)_(2)O_(3).The analysis using scanning electron microscopy(SEM) coupled with energy dispersive X-ray spectroscopy(EDX) confirms the homogeneity of(Nd,La,Ce)_(2)O_(3) particles that have two morphologies,i.e.,flower and sticks with a particle size between 3and 6 μ*** unit cell parameters of(Nd,La,Ce)_(2)O_(3) were calculated after Rietveld refinement of the XRD patterns,in the space group of Fm-3m are a=b=c=0.57921 nm and the volume equal to 0.194322 nm^(3).

关键词： NiMH batteries Hydrometallurgical process Leaching Phosphoric acid Box-Behnken Light rare earth oxides

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Machine Learning Techniques Using Deep Instinctive Encoder-Based Feature Extraction for Optimized Breast Cancer Detection

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Computers, Materials & Continua 2024年第2期78卷 2441-2468页

作者： Vaishnawi Priyadarshni Sanjay Kumar Sharma Mohammad khalid Imam Rahmani Baijnath Kaushik Rania Almajalid Department of Computer Science Gautam Buddha UniversityGreater NoidaUttar PradeshIndia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia School of Computer Science Shri Vaishno Devi UniversityKatraIndia

Breast cancer(BC)is one of the leading causes of death among women worldwide,as it has emerged as the most commonly diagnosed malignancy in *** detection and effective treatment of BC can help save women’s *** an efficient technology-based detection system can lead to non-destructive and preliminary cancer detection *** paper proposes a comprehensive framework that can effectively diagnose cancerous cells from benign cells using the Curated Breast Imaging Subset of the Digital Database for Screening Mammography(CBIS-DDSM)data *** novelty of the proposed framework lies in the integration of various techniques,where the fusion of deep learning(DL),traditional machine learning(ML)techniques,and enhanced classification models have been deployed using the curated *** analysis outcome proves that the proposed enhanced RF(ERF),enhanced DT(EDT)and enhanced LR(ELR)models for BC detection outperformed most of the existing models with impressive results.

关键词： Autoencoder breast cancer deep neural network convolutional neural network image processing machine learning deep learning

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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

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