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Deep Learning Control for Autonomous Robot

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Computers, materials & Continua 2022年第8期72卷 2811-2824页

作者： Rihem Farkh Saad Alhuwaimel Sultan Alzahrani Khaled Al Jaloud m.ham.ad tabrez quasim College of Engineering Muzahimiyah BranchKing Saud UniversityRiyadh11451Saudi Arabia Laboratory for Analysis Conception and Control of SystemsLR-11-ES20Department of Electrical Engineering National Engineering School of TunisTunis El Manar University1002Tunisia King Abdulaziz City for Science and Technology Saudi Arabia College of Computing and Information Technology University of BishaBisha67714Saudi Arabia

Several applications of machine learning and artificial intelligence,have acquired importance and come to the fore as a result of recent advances and improvements in these *** cars are one such *** is expected to have a significant and revolutionary influence on *** with smart cities,new infrastructure and urban planning with sophisticated cyber-security are some of the current ramifications of self-driving *** autonomous automobile,often known as selfdriving systems or driverless vehicles,is a vehicle that can perceive its surroundings and navigate predetermined routes without human *** are on the verge of evolving into autonomous robots,thanks to significant breakthroughs in artificial intelligence and related technologies,and this will have a wide range of socio-economic ***,in order for these automobiles to become a reality,they must be endowed with the perception and cognition necessary to deal with high-pressure real-life events and make proper judgments and take appropriate *** majority of self-driving car technologies are based on computer systems that automate vehicle control *** forward-collision warning and antilock brakes to lane-keeping and adaptive drive control,to fully automated driving,these technological components have a wide range of capabilities.A self-driving car combines a wide range of sensors,actuators,and *** researches on computer vision and deep learning are used to control autonomous driving *** self-driving automobiles,lane-keeping is *** study presents a deep learning approach to obtain the proper steering angle to maintain the robot in the *** propose an advanced control for a selfdriving robot by using two controllers *** neural networks(CNNs)are employed,to predict the car’and a proportionalintegral-derivative(PID)controller is designed for speed and steering *** stu

关键词： Autonomous car cascade PID control deep learning convolutional neural network differential drive system raspberry PI road lane detector

Intelligent Autonomous-Robot Control for medical Applications

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Computers, materials & Continua 2021年第8期68卷 2189-2203页

作者： Rihem Farkh Haykel marouani Khaled Al Jaloud Saad Alhuwaimel m.ham.ad tabrez quasim Yasser Fouad College of Engineering Muzahimiyah BranchKing Saud UniversityRiyadh11451Saudi Arabia Laboratory for Analysis Conception and Control of SystemsDepartment of Electrical EngineeringNational Engineering School of TunisTunis El Manar University1002Tunisia King Abdulaziz City for Science and Technology Riyadh12354Saudi Arabia College of Computing and Information Technology University of BishaBisha67714Saudi Arabia

The COVID-19 pandemic has shown that there is a lack of healthcare facilities to cope with a *** has also underscored the immediate need to rapidly develop hospitals capable of dealing with infectious patients and to rapidly change in supply lines to manufacture the prescription goods(including medicines)that is needed to prevent infection and treatment for infected *** COVID-19 has shown the utility of intelligent autonomous robots that assist human efforts to combat a *** artificial intelligence based on neural networks and deep learning can help to fight COVID-19 in many ways,particularly in the control of autonomous medic *** officials aim to curb the spread of COVID-19 among medical,nursing staff and patients by using intelligent *** propose an advanced controller for a service robot to be used in *** type of robot is deployed to deliver food and dispense medications to individual *** autonomous line-follower robot that can sense and follow a line drawn on the floor and drive through the rooms of patients with control of its *** criteria were met by using two controllers simultaneously:a deep neural network controller to predict the trajectory of movement and a proportional-integral-derivative(PID)controller for automatic steering and speed control.

关键词： Autonomous medic robots PID control neural network control system real-time implementation navigation environment differential drive system

A Deep Learning model to Analyse Social-Cyber Psychological Problems in Youth

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Computer Systems Science & Engineering 2023年第7期46卷 551-562页

作者： Ali Alqazzaz m.ham.ad tabrez quasim mohammed mujib Alshahrani Ibrahim Alrashdi m.ham.ad Ayoub Khan College of Computing and Information Technology University of Bisha67714BishaSaudi Arabia Department of Computer Science College of Computer and Information SciencesJouf UniversitySakakaAljouf72388Saudi Arabia

Facebook,Twitter,Instagram,and other social media have emerged as excellent platforms for interacting with friends and expressing thoughts,posts,comments,images,and videos that express moods,sentiments,and *** this,it has become possible to examine user thoughts and feelings in social network data to better understand their perspectives and ***,the analysis of depression based on social media has gained widespread acceptance worldwide,other verticals still have yet to be *** depression analysis uses Twitter data from a publicly available web source in this *** assess the accuracy of depression detection,long-short-term memory(LSTm)and convolution neural network(CNN)techniques were *** method is both efficient and *** simulation results have shown an accuracy of 86.23%,which is reasonable compared to existing methods.

关键词： Emotions depression social media

An Improved machine Learning Technique with Effective Heart Disease Prediction System

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Computers, materials & Continua 2021年第12期69卷 4169-4181页

作者： m.ham.ad tabrez quasim Saad Alhuwaimel Asadullah Shaikh Yousef Asiri Khairan Rajab Rihem Farkh Khaled Al Jaloud College of Computing and Information Technology University of BishaBisha67714Saudi Arabia King Abdulaziz City for Science and Technology P.O.Box 6086Riyadh11442Saudi Arabia College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia College of Engineering Muzahimiyah BranchKing Saud UniversityRiyadh11451Saudi Arabia Department of Electrical Engineering Laboratory for AnalysisConception and Control of SystemsLR-11-ES20National Engineering School of TunisTunis El Manar University1002Tunisia

Heart disease is the leading cause of death *** heart disease is challenging because it requires substantial experience and *** research studies have found that the diagnostic accuracy of heart disease is *** coronary heart disorder determines the state that influences the heart valves,causing heart *** indications of coronary heart disorder are strep throat with a red persistent skin rash,and a sore throat covered by tonsils or strep *** work focuses on a hybrid machine learning algorithm that helps predict heart attacks and arterial *** first,we achieved the component perception measured by using a hybrid cuckoo search particle swarm optimization(CSPSO)*** this perception measure,characterization and accuracy were improved,while the execution time of the proposed model was *** CSPSO-deep recurrent neural network algorithm resolved issues that state-of-the-art methods *** proposed method offers an illustrative framework that helps predict heart attacks with high *** proposed technique demonstrates the model accuracy,which reached 0.97 with the applied dataset.

关键词： machine learning deep recurrent neural network effective heart disease prediction framework

ANN Based Novel Approach to Detect Node Failure in Wireless Sensor Network

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Computers, materials & Continua 2021年第11期69卷 1447-1462页

作者： Sundresan Perumal mujahid Tabassum Ganthan Narayana Suresh Ponnan Chinmay Chakraborty Saju mohanan Zeeshan Basit m.ham.ad tabrez quasim Faculty of Science and Technology Universiti Sains Islam MalaysiaNilai71800Malaysia advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi MalaysiaKuala Lumpur54100Malaysia Department of ECE Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology600062TamilnaduIndia Department Electronics&Communication Engineering Birla Institute of TechnologyMesraJharkhandIndia Faulty of Information Technology University of Technology and Applied SciencesMuscat133Oman College of Computing and Information Technology University of BishaBisha67714Saudi Arabia

A wireless sensor network(WSN)consists of several tiny sensor nodes to monitor,collect,and transmit the physical information from an environment through the wireless *** node failure is considered as one of the main issues in the WSN which creates higher packet drop,delay,and energy consumption during the *** the node failure occurred mostly due to persistent energy exhaustion during transmission of data *** this paper,Artificial Neural Network(ANN)based Node Failure Detection(NFD)is developed with cognitive radio for detecting the location of the node *** ad hoc on-demand distance vector(AODV)routing protocol is used for transmitting the data from the source node to the base ***,the mahalanobis distance is used for detecting an adjacent node to the node failure which is used to create the routing path without any node *** performance of the proposed ANN-NFD method is analysed in terms of throughput,delivery rate,number of nodes alive,drop rate,end to end delay,energy consumption,and overhead ***,the performance of the ANN-NFD method is evaluated with the header to base station and base station to header(H2B2H)*** packet delivery rate of the ANN-NFD method is 0.92 for 150 nodes that are high when compared to the H2B2H ***,the ANN-NFD method provides data consistency during data transmission under node and battery failure.

关键词： AODV artificial neural network artificial intelligence mahalanobis distance node failure throughput wireless sensor network

Petrographical and geochemical signatures of Jurassic rocks of Chari Formation, Western India： implications for provenance and tectonic setting

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Acta Geochimica 2016年第2期35卷 184-202页

作者： Shaista Khan A. H. m. Ahmad m. masroor Alam adnan quasim Department of Geology Aligarh Muslim University AligarhUP. India Geology Section Civil Engineering Z.H. College of Engineering and Technology Aligarh Muslim UniversityAligarh UP India

members The sandstones of the Ridge and Athleta of Chari Formation （Callovian-Oxfordian） exposed at Jara have been analyzed for their petrographical and geochemical studies. Texturally, these sandstones are medium to coarse grained, poorly to well sorted, sub-an- gular to sub-rounded, and show low to medium sphericity. These sandstones were derived from a mixed provenance including granites, granite-gneisses, low and high-grade metamorphic, and some basic rocks of Aravalli range and Nagarparkar massif. The petrofacies analysis reveals that these sandstones belong to the continental block and recycled orogen tectonic regime. The studied sandstones are modified by paleoclimate, distance of transport, and diagenesis. mineralogically and geochemically, sandstones are classified as quartzarenite, subarkose, arkose, sublithic arenite, and wacke, respectively. The A-CN-K ternary plot and CIA, CIW, PIA, and ICV values suggest that the similar source rocks suffered moderate to high chemical weathering under a hot-humid climate in an acidic envi- ronment with higher Pco2. Generally good to strong cor- relations between AI2O3 and other oxides in these sediments indicate clay mineral control. The K2O/Na2O versus SiO2 diagram indicates that the studied samples occupy passive margin fields but the SiO2/A12O3 versus K2O/Na20 plot suggests that the Athleta Sandstone and Ridge Sandstone fall within the passive margin field, while Ridge Shale falls within the active continental margin field.

关键词： Petrography Geochemistry Jurassic rocks Chari Formation Kachchh Gujarat

孟加拉国锡尔赫特都会市年龄12~16岁小学生中高血压的患病率及其危险因素

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中华高血压杂志 2020年第2期28卷 162-162页

作者：周卫(译) 叶鹏(摘、审校) Akther m tabrez mS Ali mm Dey PR Hoque m Alam ST 不详

血压是一种常见病,其死亡率和发病率都很高。高血压可能起源于儿童时期,除非经过特别的检查,否则难以被发现。全球化不但改变了生活方式,也让青少年暴露于更多的致病风险因素中(除了遗传因素),如缺乏体育锻炼、肥胖、非健康膳食、学业... 详细信息

血压是一种常见病,其死亡率和发病率都很高。高血压可能起源于儿童时期,除非经过特别的检查,否则难以被发现。全球化不但改变了生活方式,也让青少年暴露于更多的致病风险因素中(除了遗传因素),如缺乏体育锻炼、肥胖、非健康膳食、学业压力。早期诊断是控制、有效治疗高血压并预防并发症的重要手段。2014年1-6月,研究者进行了一项横断面描述性研究。根据纳入和排除标准,将锡尔赫特大都市的1000名12~16岁学龄儿童纳入研究。入选标准为锡尔赫特市所有12~16岁的学龄儿童,不包括12岁以下或16岁以上以及有任何系统性疾病的学龄儿童。研究表明,锡尔赫特市学龄儿童高血压患病率为0.70%,肥胖、高血压家族史、膳食习惯、缺乏体育锻炼与高血压显著相关。

关键词：系统性疾病高血压患病率高血压家族史膳食习惯危险因素早期诊断遗传因素学龄儿童