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Subsurface geological model of sedimentary and metasedimentary wedge from Mansehra to Battal based on gravity data,Hazara area,Pakistan

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Energy Geoscience 2021年第4期2卷 229-237页

作者： Rizwan sarwar Awan Ashar Khan Chenglin Liu Shangfeng Yang Qibiao Zang Yuping Wu Guoxiong Li Khawaja Hasnain Iltaf Muhammad Tahir Sajjad Ali College of Geosciences China University of PetroleumBeijing102249China State Key Laboratory of Petroleum Resource and Prospecting China University of PetroleumBeijing102249China The University of Azad Jammu and Kashmir Muzaffarabad Pakistan Water and Power Development Authority Pakistan Research Institute of Unconventional Petroleum China University of PetroleumBeijing102249China

This study is aimed to delineate the subsurface structural elements using geophysical techniques in the Haraza area of *** investigated the Oghi and Battal thrust faults,sedimentary and metasedimentary wedge,and the absolute crustal thickness based on terrestrial gravity *** seismic survey relying on wave propagation,magnetic survey is based on both attraction and repulsion,and electrical and electromagnetics on *** attractive gravity field produces relatively simpler patterns of anomalies,like a series of highs and lows over regions with undulating basements and buried structures.A qualitative interpretation of gravity data reveals a good deal of *** the collision of Indian and Eurasian Plates,compressional structures were developed in the Lesser Himalayas or northwest of the Hazara Kashmir *** study mainly focuses on the western limb of the Hazara Kashmir *** regional and local Bouguer anomalies were incorporated to delineate the regional structural *** gravity model is computed through geophysical technique along with profile A-A'from Mansehra to the Battal area that demarcates the blind Oghi Thrust and emergent Battal *** Formation of Precambrian age demarcates the Oghi Thrust near Kotli Pine while the Battal Thrust is demarcated within the Mansehra Granite of Cambrian to Ordovician age near *** with the Battal Thrust,fault gouge and breccias have been observed during the field *** total thickness of the sedimentary/metasedimentary wedge in the Mansehra and Battal areas was estimated to be 13.6 km and 14.2 *** comparison,the total thickness of crust in the Mansehra and Battal areas was 51.6 km and 52.2 km,respectively.

关键词： Gravity Metasedimentary Geophysical anomaly Hazara Autograv

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Metaheuristic with Deep Learning Enabled Biomedical Bone Age Assessment and Classification Model

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Computers, Materials & Continua 2022年第12期73卷 5473-5489页

作者： Mesfer Al Duhayyim Areej A.Malibari Marwa Obayya Mohamed K.Nour Ahmed S.Salama Mohamed I.Eldesouki Abu sarwar Zamani Mohammed Rizwanullah Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The skeletal bone age assessment(BAA)was extremely implemented in development prediction and auxiliary analysis of medicinal issues.X-ray images of hands were detected from the estimation of bone age,whereas the ossification centers of epiphysis and carpal bones are important *** typical skeletal BAA approaches remove these regions for predicting the bone age,however,few of them attain suitable efficacy or *** BAA techniques with deep learning(DL)methods are reached the leading efficiency on manual and typical ***,this study introduces an intellectual skeletal bone age assessment and classification with the use of metaheuristic with deep learning(ISBAAC-MDL)*** presented ISBAAC-MDL technique majorly focuses on the identification of bone age prediction and classification *** attain this,the presented ISBAAC-MDL model derives a mask Region-related Convolutional Neural Network(Mask-RCNN)with MobileNet as baseline model to extract *** by,the whale optimization algorithm(WOA)is implemented for hyperparameter tuning of the MobileNet *** last,Deep Feed-Forward Module(DFFM)based age prediction and Radial Basis Function Neural Network(RBFNN)based stage classification approach is *** experimental evaluation of the ISBAAC-MDL model is tested using benchmark dataset and the outcomes are assessed over distinct *** experimental outcomes reported the better performances of the ISBAACMDL model over recent approaches with maximum accuracy of 0.9920.

关键词： Biomedical images bone age assessment age prediction computer vision deep learning image classification

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Mineralogy and element geochemistry of the Sohnari rocks of Early Eocene Laki Formation in the Southern Indus Basin,Pakistan:Implications for paleoclimate,paleoweathering and paleoredox conditions

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Energy Geoscience 2023年第1期4卷 143-157页

作者： Asghar A.A.D.Hakro Sajjad Ali Abdul Shakoor Mastoi Riaz Hussain Rajper Rizwan sarwar Awan Muhammad Soomar Samtio Hong Xiao Xiaolin Lu Centre for Pure&Applied Geology University of SindhJamshoro76080Pakistan Xinjiang Centre for Mineral Resources Xinjiang Institute of Ecology and GeographyUrumqiXinjiang830011China College of Geosciences China University of PetroleumBeijing102249China State Key Laboratory of Petroleum Resources and Prospecting China University of PetroleumBeijing102249China School of Resources and Environmental Engineering Hefei University of TechnologyHefei Anhui230009China

The Sohnari Member of the Early Eocene Laki Formation is massively deposited in the Southern Indus Basin of Pakistan and is considered a potential source rock to generate ***,the detailed paleoclimatic,paleoweathering,and depositional conditions of the Sohnari Member have not been studied *** research mainly discusses the detailed mineralogical(bulk and clay)and elemental geochemistry of the Laki Formation from two outcrop sections(Jhimpir and Lakhra)in the Southern Indus Basin,*** bulk minerals,including quartz(low),hematite,calcite,halite,gypsum,and clay minerals such as kaolinite,chlorite,smectite and illite have been discussed *** results demonstrate the paleo-environment of studied area was arid with enhanced saline and weak to strong oxidizing depositional *** chemical index of alteration(CIA)values in Jhimpir and Lakhra sections are in the ranges of 41.30-97.93 and 22.30-96.19,respectively,indicating that the Sohnari sediments experienced weak to intense chemical weathering in the source *** interpretation of the A-CN-K ternary diagram is consistent with the clay mineral contents in the studied sediments,which is characterized by the predominance of kaolinite,gibbsite and chlorite,demonstrating the weak to strong weathering state under warm and humid climatic *** chemical indices such as Sr/Ba,δU,V/Cr,Ni/Co,and Cu/Zn,U/Th and Ba/Ga show that Sohnari rocks of Early Eocene Laki Formation underwent strong evaporation,oxic water column with warm to humid and minor contact of cold climatic *** on our present data,it can be concluded that the sediments of Sohnari Member of Laki Formation from Jhimpir and Lakhra areas of Southern Indus Basin in Pakistan are related to Indio-Eurasian collision and came from the Indian shield rocks that were deposited in a brackish water body with a minor contact of the freshwater oxidizing paleo-environment depositional conditions.

关键词： Mineralogy Geochemistry Paleoclimate Sohnari Southern indus basin Lakhra

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冠状面下肢力线的评估及其对膝关节单髁置换术后功能的影响 ——回顾性研究

冠状面下肢力线的评估及其对膝关节单髁置换术后功能的影响 ——...

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作者： SHAKEEL sarwar（沙克尔）东南大学

学位级别：硕士

背景和目的:单髁置换术(UKA)是治疗膝关节内侧间室骨关节炎的常用技术。与全膝关节置换术相比,它具有费用低、并发症少、容易翻修、术后康复快等优势,且保留了交叉韧带可使膝关节获得更为接近正常的运动功能。本研究的目的是通过站立位... 详细信息

背景和目的:单髁置换术(UKA)是治疗膝关节内侧间室骨关节炎的常用技术。与全膝关节置换术相比,它具有费用低、并发症少、容易翻修、术后康复快等优势,且保留了交叉韧带可使膝关节获得更为接近正常的运动功能。本研究的目的是通过站立位下肢全长片对接受UKA患者的术前术后下肢力线进行评估,确定患者下肢冠状面力线畸形的病理来源(关节内或关节外),并观察下肢力线对接受UKA患者术后膝关节短期功能的影响。方法:回顾性分析2015年10月-2018年08月在东南大学附属中大医院接受膝关节内侧间室UKA患者的临床资料。纳入标准:1.明确诊断为膝关节内侧间室骨关节炎的患者。2.患者在术前和术后均接受了下肢全长x线摄片。3.完成了美国特殊外科医院膝关节评分(HSS)、西大略湖麦克马斯特大学关节炎指数(WOMAC)问卷的患者。排除标准:1.无术前或术后下肢全长x线摄片,2.同时存在髋关节骨关节炎的患者,3.同侧肢体外伤,4.关节假体周围感染的患者,5.失访的患者。对纳入患者术前术后患肢全长正位X线摄片片进行影像学测量,测量指标包括:MAA,LDFA,mPTA和JLCA。根据术后股骨和胫骨解剖轴成角度数分为中立位对线组(≤3°)和内翻对线组(>3°),采用HSS评分和WOMAC指数对患者术前及末次随访膝关节功能进行评价。使用SPSS 15.0软件进行统计学分析,比较中立位对线组和内翻对线组膝关节功能之间的差异,P<0.05为差异有统计学意义。结果:共收集99例(114膝)接受膝关节内侧间室UKA的患者,根据纳入及排除标准,最终筛选出53例(62膝)患者。其中女性患者38例(43膝,69.35%),男性患者15例(19膝,30.65%)。平均年龄为67.87±7.738(52-88岁)。随访的平均值为22.5±24.75(5-40月)。根据术前影像学测量,中立位对线组17例,内翻对线组45例,其中关节外畸形14例,关节内畸形31例。术后影像学测量,中立位对线组45例,内翻对线组17例,其中关节外畸形13例,关节内畸形4例。术后畸形矫正率为62.22%(28/45)。所有患者术前及术后HSS评分由52.89±15.73提高至92.79±9.518(P<0.001)。WOMAC指数也从14.5±3.297降至1.477±1.753(P<0.001),其中关节僵硬指数从3.316±2.548降至0.509±0.953(P<0.001),躯体功能指数从43.03±9.972降至5.897±7.149(P<0.001),上述两者评分越低提示膝关节功能越好。根据术后下肢冠状面全长力线分组,中立位对线组和内翻对线组HSS评分分别为93.11±8.52和91.94±12.02(p=0.6696),两组间比较无统计学差异,中立位对线组和内翻对线组WOMAC指数分别为2.566±5.123和2.792±4.16(p=0.7782),两组间比较无统计学差异,提示术后临床疗效相近。结论:UKA治疗膝关节内侧间室骨关节炎可显著缓解疼痛、改善患者的膝关节功能。胫骨近端关节外内翻畸形可能是导致膝关节内侧间室骨关节炎的重要原因,包括其他关节外的因素,如躯体姿势、遗传因素、软组织不平衡等。同样,若术中膝关节矫正不佳,也会加重内翻畸形。由于UKA只能纠正关节内畸形,因此这部分患者术后容易遗留下肢内翻畸形,但术后下肢力线内翻并不影响患者膝关节短期内的功能恢复。我们的研究表明,接受了UKA的患者术后膝关节功能评分较术前均有显着的改善,且HSS评分和WOMAC指数结果提示,中立位对线组(0-3°)和内翻对线组(3-7°)在术后临床疗效上无统计学差异,故术后内翻畸形在0-7°间是可以接受的。

关键词：单髁置换全膝关节置换术内翻对线中立位对线

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Improved Ant Lion Optimizer with Deep Learning Driven Arabic Hate Speech Detection

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Computer Systems Science & Engineering 2023年第9期46卷 3321-3338页

作者： Abdelwahed Motwakel Badriyya B.Al-onazi Jaber S.Alzahrani Sana Alazwari Mahmoud Othman Abu sarwar Zamani Ishfaq Yaseen Amgad Atta Abdelmageed Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaifP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Arabic is the world’s first language,categorized by its rich and complicated grammatical ***,the Arabic morphology can be perplexing because nearly 10,000 roots and 900 patterns were the basis for verbs and *** Arabic language consists of distinct variations utilized in a community and particular *** media sites are a medium for expressing opinions and social phenomena like racism,hatred,offensive language,and all kinds of verbal *** conduct does not impact particular nations,communities,or groups only,extending beyond such areas into people’s everyday *** study introduces an Improved Ant Lion Optimizer with Deep Learning Dirven Offensive and Hate Speech Detection(IALODL-OHSD)on Arabic *** presented IALODL-OHSD model mainly aims to detect and classify offensive/hate speech expressed on social *** the IALODL-OHSD model,a threestage process is performed,namely pre-processing,word embedding,and ***,data pre-processing is performed to transform the Arabic social media text into a useful *** addition,the word2vec word embedding process is utilized to produce word *** attentionbased cascaded long short-term memory(ACLSTM)model is utilized for the classification ***,the IALO algorithm is exploited as a hyperparameter optimizer to boost classifier *** illustrate a brief result analysis of the IALODL-OHSD model,a detailed set of simulations were *** extensive comparison study portrayed the enhanced performance of the IALODL-OHSD model over other approaches.

关键词： Hate speech offensive speech Arabic corpora natural language processing social networks

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Manta Ray Foraging Optimization with Machine Learning Based Biomedical Data Classification

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Computers, Materials & Continua 2022年第11期73卷 3275-3290页

作者： Amal Al-Rasheed Jaber S.Alzahrani Majdy M.Eltahir Abdullah Mohamed Anwer Mustafa Hilal Abdelwahed Motwakel Abu sarwar Zamani Mohamed I.Eldesouki Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The biomedical data classification process has received significant attention in recent times due to a massive increase in the generation of healthcare data from various *** developments of artificial intelligence(AI)and machine learning(ML)models assist in the effectual design of medical data classification ***,this article concentrates on the development of optimal Stacked Long Short Term Memory Sequence-toSequence Autoencoder(OSAE-LSTM)model for biomedical data *** presented OSAE-LSTM model intends to classify the biomedical data for the existence of ***,the OSAE-LSTM model involves min-max normalization based pre-processing to scale the data into uniform *** by,the SAE-LSTM model is utilized for the detection and classification of diseases in biomedical *** last,manta ray foraging optimization(MRFO)algorithm has been employed for hyperparameter optimization *** utilization of MRFO algorithm assists in optimal selection of hypermeters involved in the SAE-LSTM *** simulation analysis of the OSAE-LSTM model has been tested using a set of benchmark medical datasets and the results reported the improvements of the OSAELSTM model over the other approaches under several dimensions.

关键词： Biomedical data classification deep learning manta ray foraging optimization healthcare machine learning artificial intelligence

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Chapman-Kolmogorov equations for global PPIs with Discriminant-EM

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International Journal of Biomathematics 2014年第5期7卷 95-101页

作者： Md. sarwar Kamal Mohammad Ibrahim Khan Department of Computer Science and EngineeringChittagong University of Engineering and Technology Chittagong ~3~9 Bangladesh

Ongoing improvements in Computational Biology research have generated massive amounts of Protein-Protein Interactions （PPIs） dataset. In this regard, the availability of PPI data for several organisms provoke the discovery of computational methods for measurements, analysis, modeling, comparisons, clustering and alignments of biological data networks. Nevertheless, fixed network comparison is computationally stubborn and as a result several methods have been used instead. We illustrate a prohabilistic approach among proteins nodes that are part of various networks by using Chapman-Kolmogorov （CK） formula. We have compared CK formula with semi-Markov random method, SMETANA. We significantly noticed that CK outperforms the SMETANA in all respects such as efficiency, speed, space and complexity. We have modified the SMETANA source codes available in MATLAB in the light of CK formula. Discriminant-Expectation Maximization （D-EM） accesses the parameters of a protein network datasets and determines a linear transformation to simplify the assumption of probabilistic format of data distributions and find good features dynamically. Our implementation finds that D-EM has a satisfactory performance in protein network alignment applications.

关键词： SMETANA semi-Markov method Chapman-Kolmogorov formula D-EM.

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Utility of liver biopsy in predicting clinical outcomes after percutaneous angioplasty for hepatic venous obstruction in liver transplant patients

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World Journal of Hepatology 2015年第14期7卷 1884-1893页

作者： Ammar sarwar Edward Ahn Ian Brennan Olga R Brook Salomao Faintuch Raza Malik Khalid Khwaja Muneeb Ahmed Divison of Vascular and Interventional Radiology Beth Israel Deaconess Medical Center/Harvard Medical School Division of Gastroenterology and Hepatology Beth Israel Deaconess Medical Center/Harvard Medical School Division of Transplant Surgery Beth Israel Deaconess Medical Center/Harvard Medical School

AIM: To determine utility of transplant liver biopsy in evaluating efficacy of percutaneous transluminal angioplasty(PTA) for hepatic venous obstruction(HVOO). METHODS: Adult liver transplant patients treated with PTA for HVOO(2003-2013) at a single institution were reviewed for pre/post-PTA imaging findings, manometry(gradient with right atrium), presence of HVOO on prePTA and post-PTA early and late biopsy(EB and LB, 60 d after PTA), and clinical outcome, defined as good(no clinical issues, non-HVOO-related death) or poor(surgical correction, recurrent HVOO, or HVOOrelated death). RESULTS: Fifteen patients meeting inclusion criteria underwent 21 PTA, 658 ± 1293 d after *** procedures with pre-PTA biopsy(n = 19), no difference was seen between pre-PTA gradient in 13/19 procedures with HVOO on biopsy and 6/19 procedures without HVOO(8 ± 2.4 mm Hg vs 6.8 ± 4.3 mm Hg; P = 0.35). Post-PTA, 10/21 livers had EB(29 ± 21 d) and 9/21 livers had LB(153 ± 81 d). On clinical follow-up(392 ± 773 d), HVOO on LB resulted in poor outcomes and absence of HVOO on LB resulted good outcomes. Patients with HVOO on EB(3/7 good, 4/7 poor) and no HVOO on EB(2/3 good, 1/3 poor) had mixed outcomes. CONCLUSION: Negative liver biopsy greater than 60 d after PTA accurately identifies patients with good clinical outcomes.

关键词： Hepatic venous outflow obstruction Livertransplantation Post-transplant biopsy Angioplasty

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图像分类与融合研究基于机器学习技术

图像分类与融合研究基于机器学习技术

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作者： sarwar Shah Khan 北京化工大学

学位级别：硕士

视觉对人类具有至关重要的意义,图像在人类生活中广泛分布。因此,图像处理被广泛应用于遥感,军事,医疗等领域。如今,人们很容易通过数字技术获取大量图像。图像处理需要能够解决更复杂的问题,适应人类视觉。机器学习技术是图像处理开发... 详细信息

视觉对人类具有至关重要的意义,图像在人类生活中广泛分布。因此,图像处理被广泛应用于遥感,军事,医疗等领域。如今,人们很容易通过数字技术获取大量图像。图像处理需要能够解决更复杂的问题,适应人类视觉。机器学习技术是图像处理开发的重要部分。因为数据集的发展,图像处理和机器学习引起了巨大的关注。基于机器学习的图像处理有很多优势,能够更好地理解复杂的图像。本文研究了三个方面问题:多光谱和全色图像的锐化、多焦点图像融合和高光谱图像分类。首先,图像锐化前进行图像增强,它是一个预处理的过程。图像增强包括同域增强和交叉域增强。同域增强方法（如拉普拉斯、边缘锐化）是在空间域增强多光谱和全色图像。交叉域增强方法是混合了拉普拉斯滤波器和离散傅里叶变换锐化。其次,使用抠图模型（MM）融合增强后的图像,获得高分辨率合成图像。定性和定量的实验结果表明本文方法在两个数据集上优于现有方法。多焦点图像是当视场超过成像系统景深时,导致图像模糊”。彩色多焦点图像融合是合并多张多焦点图像,获得清晰的合成图像。该方法分为两步。首先,通过具有离散傅立叶变换（DFT）和拉普拉斯滤波器（LF）技术增强了多焦点图像。其次,通过静止小波变换（SWT）对增强图像进行进一步处理,获得更多信息的融合图像。定性和定量方法实验结果表明,该方法的结果犹豫传统的SWT方法。。本文提出了基于最近正则化子空间（NRS）的高光谱图像（HSI）分类。因为NRS利用距离加权的Tikhonov正则化来确保类内相似样本的适当表示,NRS优于协同表示分类和基于稀疏表示的技术。然而,典型的NRS仅考虑欧几里德距离,这对于解决频谱绝对幅度中的灵敏度问题不是最佳的。提出了一种基于NRS-曼哈顿距离（MD）策略的HSI分类。MD控制了幅度变化并强化了频谱的形状。此外,MD度量使用HSI像素全维度的光谱带的全部信息,这使NRS-MD成为更有效的像素分类器。通过印度松树,博茨瓦纳,萨利纳斯和休斯敦高光谱数据的实验结果表明,NRS-MD优于现有方法。

关键词：机器学习全色锐化多光谱图像全色图像多焦点图像融合高光谱图像分

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Metaheuristics Enabled Clustering with Routing Scheme for Wireless Sensor Networks

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Computers, Materials & Continua 2022年第12期73卷 5491-5507页

作者： Mashael M.Asiri Saud S.Alotaibi Dalia H.Elkamchouchi Amira Sayed A.Aziz Manar Ahmed Hamza Abdelwahed Motwakel Abu sarwar Zamani Ishfaq Yaseen Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Wireless Sensor Network(WSN)is a vital element in Internet of Things(IoT)as the former enables the collection of huge quantities of data in energy-constrained *** offers independent access to the target region and performs data collection in an effective *** energy constraints remain a challenging issue in WSN since it operates on in-built *** studies conducted earlier recommended that the energy spent on communication processmust be considerably reduced to improve the efficiency of *** organization and optimal selection of the routes are considered as NP hard optimization problems which can be resolved with the help of metaheuristic *** and routing are considered as effective approaches in enhancing the energy effectiveness and lifespan of *** this background,the current study develops an Improved Duck and Traveller Optimization(IDTO)-enabled cluster-based Multi-Hop Routing(IDTOMHR)technique for ***,IDTO algorithm is exploited for the selection of Cluster Head(CH)and construction of ***,Artificial Gorilla Troops Optimization(ATGO)technique is also used to derive an optimal set of routes to the *** clustering and routing approaches derive a fitness function with the inclusion of multiple input *** proposed IDTOMHR model was experimentally validated for its performance under different *** extensive experimental results confirmed the better performance of IDTOMHR model over other recent approaches.

关键词： Wireless sensor network clustering routing metaheuristics energy efficiency lifetime

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