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Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

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Computers, Materials & Continua 2021年第2期66卷 1595-1612页

作者： Kashif Iqbal Sagheer Abbas muhammad adnan Khan Atifa Ather muhammad Saleem Khan Areej Fatima Gulzar Ahmad School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Sciences GC UniversityLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Comsats University IslamabadLahore CampusLahore54000Pakistan

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of ***-based target detection and object classification have been improved due to the development of deep learning *** fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise,well-engineered,and complete detection of objects,scene or *** target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion *** this study we examined to solve these problems described by(1)extracting region-of-interest in the images(2)vehicle detection based on instance segmentation,and(3)building deep learning model based on the key features obtained from input parking *** build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking *** augmentation techniques were performed using edge detection,cropping,refined by rotating,thresholding,resizing,or color augment to predict the region of bounding boxes.A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling,training,validating and testing on parking video frames through *** results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6%than previous reported ***,this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space *** results are verified using Python,TensorFlow,OpenCV computer simulation frameworks.

关键词： Smart parking-lot detection deep convolutional neural network data augmentation region-of-interest object detection

Factors Affecting Time Overrun in Green-Line BRT Project-A Case of Pakistan

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Factors Affecting Time Overrun in Green-Line BRT Project-A C...

作者： muhammad adnan KHUHSHEED 山东大学

学位级别：硕士

发展中国家的交通系统存在拥堵、设施不足和高事出率等问题,包括噪音和空气污染。人口的快速增长和城市地区的扩张导致了对城市交通和其他服务或设施的需求。BRT是一种高质量、高容量的快速交通系统,在很多方面都是传统轨道交通系统的... 详细信息

发展中国家的交通系统存在拥堵、设施不足和高事出率等问题,包括噪音和空气污染。人口的快速增长和城市地区的扩张导致了对城市交通和其他服务或设施的需求。BRT是一种高质量、高容量的快速交通系统,在很多方面都是传统轨道交通系统的改进版本。本文的研究区域是位于巴基斯坦卡拉奇的快速公交绿线（BRT）项目。这个快速公交建设项目被认为是道路基础设施项目,是卡拉奇最大的快速公交项目。建筑业是我国重要的工业部门,是推动经济发展的重要力量。它在时间、成本和质量产出方面存在许多缺陷。以确定影响绿线快速公交建设项目时间超限的因素为目标。本研究主要侧重于识别当前的时间规划实践和巴基斯坦快速公交道路建设项目成功完成过程中时间超期因素的影响。通过从参与项目的116名受访者（112名定量分析,04名定性分析）中收集数据进行的调查。结果采用相对重要性指数（RII）进行分析。采用问卷调查的方法,根据显著性和频度对考虑变量进行评分。数值结果表明,影响巴基斯坦绿线BRT道路建设项目超限时间的最大障碍是:设计变更、利益相关者沟通、业主延迟提供资金、合同困难和项目规划不当。

关键词：时间超支因素项目时间计划 BRT项目

Structural Improvements in Consensus Based Cooperative Control of DC Microgrids

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Structural Improvements in Consensus Based Cooperative Contr...

作者： muhammad adnan Mumtaz 上海交通大学

学位级别：硕士

电力能源危机是大多数发展中国家最基本、最具挑战性的问题之一。这是因为,大多数传统发电厂以燃料或天然气资源为基础,成本昂贵,并且会对环境产生不利影响。现代电力系统因其具备环保性、无限可用性,并且可以用作不可再生能源的短期补...

电力能源危机是大多数发展中国家最基本、最具挑战性的问题之一。这是因为,大多数传统发电厂以燃料或天然气资源为基础,成本昂贵,并且会对环境产生不利影响。现代电力系统因其具备环保性、无限可用性,并且可以用作不可再生能源的短期补充,为可再生能源的使用提供了更多可能。近年来,由于可再生能源需求不断增加,以及能源整合对促进郊区电气化具有重要意义,微电网的理念受到了广泛关注。微电网是一个能够同时与电力存储系统、分布式世代和多个用户互联的小型配电系统,它在整合可再生能源的过程中发挥着至关重要的作用。微电网同时依赖分布式能源、先进的电力电子转换器、通信结构和储能电池等多种技术,可分为交流和直流微电网。近年来,直流微电网以其系统稳定性好、效率高、电能质量好、AC/DC转换级数量少和灵活性好等优点而受到广泛关注。在直流微电网中,能源资源、电池和负载通过并行连接的DC-DC降压转换器连接到公共总线,如何控制DC-DC降压转换器是直流微电网的关键操作。直流微电网控制中最基本的、具有挑战性的问题之一是保证电流共享比例的公平性,从而在实现电压调节的同时,实现分布式世代向分布式负载的公平调度,使得所需的直流母线电压在并行连接的分布式电源中保持稳定。下垂控制方法通常用于实现并行转换器之间的比例负载共享,但传统下垂控制方法的局限性限制了其可靠性。为了提高系统的稳定性和控制性能,本文提出了如下的结构改进方案。在变频器内电流控制回路中,外部电压控制回路采用简单的比例控制器作为有限增益控制器;由于有限增益控制器的下垂,本文方法无需下垂系数就可以实现功率共享。为了进一步提高功率共享精度和直流电压调节,本文采用了一种基于共识的合作控制方法来估计平均电流和平均电压差。此外,平均电压和电流差控制器可以降低通信延迟效应。本文还利用小信号分析对局部控制器的稳定性和控制性能进行了分析,并在实验过程中采用了不同的通信延迟和电流扰动。最后,在MATLAB/Simulink环境中开发了一个基于四节点的直流微电网设置,并对本文技术和现有技术的仿真结果进行了研究。仿真结果验证了本文提出的控制技术的有效性。

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Intelligent Cloud Based Load Balancing System Empowered with Fuzzy Logic

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Computers, Materials & Continua 2021年第4期67卷 519-528页

作者： Atif Ishaq Khan Syed Asad Raza Kazmi Ayesha Atta muhammad Faheem Mushtaq muhammad Idrees Ilyas Fakir muhammad Safyan muhammad adnan Khan Awais Qasim Department of Computer Science Government College UniversityLahore54000Pakistan Department of Information Technology Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Department of Computer Science and Engineering University of Engineering and Technology LahoreNarowal Campus51600Pakistan Department of Computer Science Riphah International University Lahore CampusLahore54000Pakistan

Cloud computing is seeking attention as a new computing paradigm to handle operations more efficiently and *** computing uses dynamic resource provisioning and de-provisioning in a virtualized *** load on the cloud data centers is growing day by day due to the rapid growth in cloud computing *** in cloud computing is one of the fundamental properties,and elastic load balancing automatically distributes incoming load to multiple virtual *** work is aimed to introduce efficient resource provisioning and de-provisioning for better load *** this article,a model is proposed in which the fuzzy logic approach is used for load balancing to avoid underload and overload of resources.A Simulator in Matlab is used to test the effectiveness and correctness of the proposed *** simulation results have shown that our proposed intelligent cloud-based load balancing system empowered with fuzzy logic is better than previously published approaches.

关键词： Cloud computing fuzzy logic load balancing

Simulation of snowmelt-runoff under climate change scenarios in a data-scarce mountain environment

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International Journal of Digital Earth 2019年第8期12卷 910-930页

作者： adnan Ahmad Tahir Samreen Abdul Hakeem Tiesong Hu Huma Hayat muhammad Yasir Department of Environmental Sciences COMSATS Institute of Information TechnologyAbbottabadPakistan State Key Laboratory of Water Resources and Hydropower Engineering Sciences Wuhan UniversityWuhanPeople’s Republic of China

Pakistan is an agriculture-based economy and major proportion of irrigation water for its cultivated lands is abstracted from the Upper Indus Basin(UIB).UIB water supplies are mostly contributed from the high-altitude snow and glacier fields situated in the Hindukush–Karakoram–Himalayan *** change in the flows of these river catchments due to climate variability may result in the form of catastrophic events like floods and droughts and hence will adversely affect the economy of *** study aims to simulate snowmelt runoff in a mountainous sub-catchment(Shyok River basin)of the UIB under climate change *** Runoff Model(SRM)coupled with remotely sensed snow cover product(MOD10A2)is used to simulate the snowmelt runoff under current and future climate scenarios in the study *** results indicate that(a)SRM has efficiently simulated the flow in Shyok River with average Nash–Sutcliff coefficient value(R2)of 0.8(0.63–0.93)for all six years(2000–2006)of basin-wide and zone-wise simulations,(b)an increase of 10%(by 2050)and 20%(by 2075)in SCA will result in a flow rise of∼11%and∼20%,respectively,and(c)an increase of 1℃(by 2025),2℃(by 2050),3℃(by 2075)and 4℃(by 2100)in mean temperature will result in a flow rise of∼26%,∼54%,∼81%and∼118%,*** study suggests that SRM equipped with remotely sensed snow cover data is an effective tool to estimate snowmelt runoff in high mountain data-scarce environments.

关键词： Upper Indus Basin(UIB) Shyok River basin MOD10A2 Snowmelt Runoff Model(SRM) climate change

Emotion Based Signal Enhancement Through Multisensory Integration Using Machine Learning

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Computers, Materials & Continua 2022年第6期71卷 5911-5931页

作者： muhammad adnan Khan Sagheer Abbas Ali Raza Faheem Khan T.Whangbo Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Riphah School of Computing&Innovation Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Engineering Gachon UniversitySeongnam13557Korea

Progress in understanding multisensory integration in human have suggested researchers that the integration may result into the enhancement or depression of incoming *** is evident based on different psychological and behavioral experiments that stimuli coming from different perceptual modalities at the same time or from the same place,the signal having more strength under the influence of emotions effects the response *** research inmultisensory integration has not studied the effect of emotions despite its significance and natural influence in multisensory enhancement or ***,there is a need to integrate the emotional state of the agent with incoming stimuli for signal enhancement or *** this study,two different neural network-based learning algorithms have been employed to learn the impact of emotions on signal enhancement or *** was observed that the performance of a proposed system for multisensory integration increases when emotion features were present during enhancement or depression of multisensory signals.

关键词： Multisensory integration sensory enhancement depression emotions

Maize production under risk:The simultaneous adoption of off-farm income diversification and agricultural credit to manage risk

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Journal of Integrative Agriculture 2019年第2期18卷 460-470页

作者： Shoaib Akhtar LI Gu-cheng adnan Nazir Amar Razzaq Raza Ullah muhammad Faisal muhammad Asad Ur Rehman Naseer muhammad Haseeb Raza College of Economics&Management Huazhong Agricultural UniversityWuhan 430070P.R.China Institute of Agricultural and Resource Economics University of Agriculture FaisalabadFaisalabad 38000Pakistan

Farmers in Pakistan continue to produce maize under various types of risks and adopt several strategies to manage those risks. This study is the first attempt to investigate the factors affecting the concurrent adoption of off-farm income diversification and agricultural credit which the farmers use to manage the risk to maize production. We apply bivariate and multinomial probit approaches to the primary data collected from four districts of Punjab Province in Pakistan. The results show that strong correlations exist between the off-farm diversification and agricultural credit which indicates that the use of one risk management strategy leads to another. The findings demonstrate that education, livestock number, maize farming experience, perceptions of biological risks and risk-averse nature of the growers significantly encourage the adoption of diversification as a risk management tool while farm size inversely affects the adoption of diversification. Similarly, in the adoption equation of credit, maize farming experience, farm size, perceptions of price and biological risks and risk attitude of farmers significantly enhance the chances of adopting agricultural credit to manage farm risks. These findings are important for the relevant stakeholders who seek to offer carefully designed risk minimizing options to the maize farmers.

关键词： maize off-farm diversification credit multinomial probit Pakistan

Estimating the basic reproductive ratio for the Ebola outbreak in Liberia and Sierra Leone

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Infectious Diseases of Poverty 2015年第1期4卷 114-121页

作者： adnan Khan Mahim Naveed muhammad Dur-e-Ahmad Mudassar Imran Department of Mathematics Lahore University of Management SciencesLahorePakistan Department of Mathematics State University of New York at PlattsburghPlattsburghNYUSA Department of Mathematics Waterloo UniversityWaterlooONCanada Department of Mathematics and Natural Sciences GULF University for Science and TechnologyMubarak Al-AbdullahWest MishrefKuwait

Background:Ebola virus disease has reemerged as a major public health crisis in Africa,with isolated cases also observed globally,during the current ***:To estimate the basic reproductive ratio R0,which is a measure of the severity of the outbreak,we developed a SEIR(susceptible-exposed-infected-recovered)type deterministic model,and used data from the Centers for Disease Control and Prevention(CDC),for the Ebola outbreak in Liberia and Sierra *** different data sets are available:one with raw reported data and one with corrected data(as the CDC suspects under-reporting).Results:Using a deterministic ordinary differential equation transmission model for Ebola epidemic,the basic reproductive ratio R0 for Liberia resulted to be 1.757 and 1.9 for corrected and uncorrected case data,*** Sierra Leone,R0 resulted to be 1.492 and 1.362 for corrected and uncorrected case data,*** each of the two cases we considered,the estimate for the basic reproductive ratio was initially greater than unity leading to an epidemic ***:We obtained robust estimates for the value of R0 associated with the 2014 Ebola outbreak,and showed that there is close agreement between our estimates of *** of our model also showed that effective isolation is required,with the contact rate in isolation less than one quarter of that for the infected non-isolated population,and that the fraction of high-risk individuals must be brought to less than 10%of the overall susceptible population,in order to bring the value of R0 to less than 1,and hence control the outbreak.

关键词： Epidemiology Ebola virus disease Transmission model Basic reproductive ratio

Personality Detection Using Context Based Emotions in Cognitive Agents

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Computers, Materials & Continua 2022年第3期70卷 4947-4964页

作者： Nouh Sabri Elmitwally Asma Kanwal Sagheer Abbas muhammad A.Khan muhammad adnan Khan Munir Ahmad Saad Alanazi College of Computer and Information Sciences Jouf UniversitySakaka72341Saudi Arabia Department of Computer Science Faculty of Computers and Artificial IntelligenceCairo University12613Egyp t 3School of Computer Science National College of Business administration and EconomicsLahore54000Pakistan Department of Computer Science GC UniversityLahorePakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13120Korea

Detection of personality using emotions is a research domain in artificial *** present,some agents can keep the human’s profile for interaction and adapts themselves according to their ***,the effective method for interaction is to detect the person’s personality by understanding the emotions and context of the *** idea behind adding personality in cognitive agents begins an attempt to maximize adaptability on the basis of *** our daily life,humans socially interact with each other by analyzing the emotions and context of interaction from audio or visual *** paper presents a conceptual personality model in cognitive agents that can determine personality and behavior based on some text input,using the context subjectivity of the given data and emotions obtained from a particular situation/*** proposed work consists of Jumbo Chatbot,which can chat with *** this social interaction,the chatbot predicts human personality by understanding the emotions and context of interactive ***,the Jumbo chatbot is using the BFI technique to interact with a *** accuracy of proposed work varies and improve through getting more experiences of interaction.

关键词： Emotions fuzzy personality detection contextual analysis semantic analysis