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An efficient deep learning-assisted person re-identification solution for intelligent video surveillance in smart cities

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Frontiers of Computer Science 2023年第4期17卷 83-96页

作者： muazzam maqsood Sadaf YASMIN Saira GILLANI Maryam BUKHARI Seungmin RHO Sang-Soo YEO Department of Computer Science COMSATS University IslamabadAttock CampusAttock 43600Pakistan Department of Computer Science Bahria UniversityLahore 54600Pakistan Department of Industrial Security Chung-Ang UniversitySeoul 06974Republic of Korea Department of Computer Engineering Mokwon UniversityDaejeon 35349Republic of Korea

Innovations on the Internet of Everything(IoE)enabled systems are driving a change in the settings where we interact in smart units,recognized globally as smart city ***,intelligent video-surveillance systems are critical to increasing the security of these smart *** precisely,in today’s world of smart video surveillance,person re-identification(Re-ID)has gained increased consideration by *** researchers have designed deep learningbased algorithms for person Re-ID because they have achieved substantial breakthroughs in computer vision *** this line of research,we designed an adaptive feature refinementbased deep learning architecture to conduct person *** the proposed architecture,the inter-channel and inter-spatial relationship of features between the images of the same individual taken from nonidentical camera viewpoints are focused on learning spatial and channel *** addition,the spatial pyramid pooling layer is inserted to extract the multiscale and fixed-dimension feature vectors irrespective of the size of the feature ***,the model’s effectiveness is validated on the CUHK01 and CUHK02 *** compared with existing approaches,the approach presented in this paper achieves encouraging Rank 1 and 5 scores of 24.6% and 54.8%,respectively.

关键词： Internet of Everything(IoE) visual surveillance systems big data security systems person re-identification(Re-ID) deep learning

An Efficient False-Positive Reduction System for Cerebral Microbleeds Detection

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Computers, Materials & Continua 2021年第3期66卷 2301-2315页

作者： Sitara Afzal muazzam maqsood Irfan Mehmood Muhammad Tabish Niaz Sanghyun Seo Department of Computer Science COMSATS University IslamabadAttock CampusAttockPakistan Department of Media Design and Technology Faculty of Engineering&InformaticsUniversity of BradfordBradfordBD71AZUK Department of Smart Device Engineering School of Intelligent Mechatronics EngineeringSejong UniversitySeoulSouth Korea School of Computer Art College of Art&TechnologyChung-Ang UniversityAnseong17546South Korea

Cerebral Microbleeds(CMBs)are microhemorrhages caused by certain abnormalities of brain *** can be found in people with Traumatic Brain Injury(TBI),Alzheimer’s disease,and in old individuals having a brain *** research reveals that CMBs can be highly dangerous for individuals having dementia and *** CMBs seriously impact individuals’life which makes it crucial to recognize the CMBs in its initial phase to stop deterioration and to assist individuals to have a normal *** existing work report good results but often ignores false-positive’s perspective for this research *** this paper,an efficient approach is presented to detect CMBs from the Susceptibility Weighted Images(SWI).The proposed framework consists of four main phases(i)making clusters of brain Magnetic Resonance Imaging(MRI)using k-mean classifier(ii)reduce false positives for better classification results(iii)discriminative feature extraction specific to CMBs(iv)classification using a five layers convolutional neural network(CNN).The proposed method is evaluated on a public dataset available for 20 *** proposed system shows an accuracy of 98.9%and a 1.1%false-positive rate *** results show the superiority of the proposed work as compared to existing states of the art methods.

关键词： Microbleeds detection false-positive deep learning CNN

An Efficient Method for Underwater Video Summarization and Object Detection Using YoLoV3

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Intelligent Automation & Soft Computing 2023年第2期35卷 1295-1310页

作者： Mubashir Javaid muazzam maqsood Farhan Aadil Jibran Safdar Yongsung Kim Department of Computer Science UETTaxilaPakistan Department of Computer Science COMSATS University IslamabadAttock CampusAttockPakistan Department of Technology Education Chungnam National UniversityDaejeon34134Korea

Currently,worldwide industries and communities are concerned with building,expanding,and exploring the assets and resources found in the oceans and *** precisely,to analyze a stock,archaeology,and surveillance,sev-eral cameras are installed underseas to collect ***,on the other hand,these large size videos require a lot of time and memory for their processing to extract relevant ***,to automate this manual procedure of video assessment,an accurate and efﬁcient automated system is a greater *** this perspective,we intend to present a complete framework solution for the task of video summarization and object detection in underwater *** employed a perceived motion energy(PME)method toﬁrst extract the keyframes followed by an object detection model approach namely YoloV3 to perform object detection in underwater *** issues of blurriness and low contrast in underwater images are also taken into account in the presented approach by applying the image enhancement ***,the suggested framework of underwater video summarization and object detection has been evaluated on a publicly available brackish *** is observed that the proposed framework shows good performance and hence ultimately assists several marine researchers or scientists related to theﬁeld of underwater archaeology,stock assessment,and surveillance.

关键词： Computer vision deep learning digital image processing underwater video analysis video summarization object detection YOLOV3

An LSTM Based Forecasting for Major Stock Sectors Using COVID Sentiment

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Computers, Materials & Continua 2021年第4期67卷 1191-1206页

作者： Ayesha Jabeen Sitara Afzal muazzam maqsood Irfan Mehmood Sadaf Yasmin Muhammad Tabish Niaz Yunyoung Nam Department of Computer Science COMSATS University IslamabadAttock CampusPakistan Department of Media Design and Technology Faculty of Engineering&InformaticsUniversity of BradfordBradfordBD71AZUK Department of Smart Device Engineering School of Intelligent Mechatronics EngineeringSejong UniversitySeoulKorea Department of Computer Science&Engineering Soonchunhyang UniversityAsan36538Korea

Stock market forecasting is an important research area,especially for better business decision *** stock predictions continue to be significant for business *** short-term stock market forecasting is usually based on historical market data analysis such as stock prices,moving averages,or daily ***,major events’news also contains significant information regarding market *** effective stock market forecasting system helps investors and analysts to use supportive information regarding the future direction of the stock *** research proposes an efficient model for stock market *** current proposed study explores the positive and negative effects of coronavirus events on major stock sectors like the airline,pharmaceutical,e-commerce,technology,and *** use the Twitter dataset for calculating the coronavirus sentiment with a Long Short-Term Memory(LSTM)model to improve stock *** LSTM has the advantage of analyzing relationship between time-series data through memory *** performance of the system is evaluated by Mean Absolute Error(MAE),Mean Squared Error(MSE),and Root Mean Squared Error(RMSE).The results show that performance improves by using coronavirus event sentiments along with the LSTM prediction model.

关键词： Business intelligence decision making stock prediction long short-term memory COVID-19 event sentiment

An Immutable Framework for Smart Healthcare Using Blockchain Technology

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Computer Systems Science & Engineering 2023年第7期46卷 165-179页

作者： Faneela muazzam A.Khan Suliman A.Alsuhibany Walid El-Shafai Mujeeb Ur Rehman Jawad Ahmad Department of Computer Science Quaid-i-Azam UniversityIslamabad45320Pakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Computer Science Security Engineering LaboratoryPrince Sultan UniversityRiyadh11586Saudi Arabia James Watt School of Engineering University of GlasgowG128QQUK School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK

The advancements in sensing technologies,information processing,and communication schemes have revolutionized the healthcare *** Healthcare Records(EHR)facilitate the patients,doctors,hospitals,and other stakeholders to maintain valuable data and medical *** traditional EHRs are based on cloud-based architectures and are susceptible to multiple cyberattacks.A single attempt of a successful Denial of Service(DoS)attack can compromise the complete healthcare *** article introduces a secure and immutable blockchain-based framework for the Internet of Medical Things(IoMT)to address the stated *** proposed architecture is on the idea of a lightweight private blockchain-based network that facilitates the users and hospitals to perform multiple healthcare-related operations in a secure and trustworthy *** efficacy of the proposed framework is evaluated in the context of service execution time and *** experimental outcomes indicate that the proposed design attained lower service execution time and higher throughput under different control parameters.

关键词： Blockchain technology healthcare applications cybersecurity services IoMT DoS EHR

A Highly Secured Image Encryption Scheme using Quantum Walk and Chaos

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Computers, Materials & Continua 2022年第10期73卷 657-672页

作者： Muhammad Islam Kamran muazzam A.Khan Suliman A.Alsuhibany Yazeed Yasin Ghadi Arshad Jameel Arif Jawad Ahmad Department of Computer Science Quaid-i-Azam UniversityIslamabad45320Pakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science and Software Engineering Al Ain UniversityAbu Dhabi15551UAE Institute for Energy and Environment University of StrathclydeGlasgowG11XQUK School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK

The use of multimedia data sharing has drastically increased in the past few decades due to the revolutionary improvements in communication technologies such as the 4th generation(4G)and 5th generation(5G)*** have proposed many image encryption algorithms based on the classical random walk and chaos theory for sharing an image in a secure *** of the classical random walk,this paper proposes the quantum walk to achieve high image *** random walk exhibits randomness due to the stochastic transitions between states,on the other hand,the quantum walk is more random and achieve randomness due to the superposition,and the interference of the wave *** proposed image encryption scheme is evaluated using extensive security metrics such as correlation coefficient,entropy,histogram,time complexity,number of pixels change rate and unified average intensity *** experimental results validate the proposed scheme,and it is concluded that the proposed scheme is highly secured,lightweight and computationally *** the proposed scheme,the values of the correlation coefficient,entropy,mean square error(MSE),number of pixels change rate(NPCR),unified average change intensity(UACI)and contrast are 0.0069,7.9970,40.39,99.60%,33.47 and 10.4542 respectively.

关键词： Cryptography chaotic maps logistic map quantum walk security

Modeling the Process of Transportation of Seed Cotton through the Parameters of the Food Zone

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Engineering（科研） 2021年第9期13卷 493-501页

作者： Akmal Umarov Dilmurat Kurbanov muazzam Kenjayeva Botir Mardonov Namangan Institute of Engineering and Technology Namangan Uzbekistan Tashkent Institute of Textile and Light Industry Tashkent Uzbekistan

In the process of separating the fiber from the seed, the density of the seed roll in the roll box of the saw gin is constantly changing. With an increase in the density of the seed roll, the quality indicators of fiber and seed deteriorate, energy consumption increases, machine breakdowns increase, and with a decrease in density, the productivity of the machine decreases. For this reason, the regulation of the density of the seed roll is one of the important problems in the ginning process. For this, the speed of rotation of the feed rollers changes, which, with an increase in speed, the mass of cotton increases, and with a decrease, it decreases. Thus, the density of the seed roll is controlled. The article describes the problem of regulating the density of a seed roll in a saw gin of the DP series, an overview of the work on regulating the operation of the machine is given. In this work, the force of cotton pressure between two feed rollers is also theoretically investigated. Graphs of changes in the force of cotton pressure between two rollers are plotted depending on various initial pressure forces. The results of the study will be used in the further improvement of the cotton feeding regulation in order to maintain the optimum density of the seed roll, which will preserve the quality of the fiber and seeds while increasing the productivity of the machine.

关键词： Cotton Saw Gin Feed Rollers Roll Box Seed Roll Productivity Pressure Density Cotton Movement Speed Coefficient of Elasticity of Cotton Mass

The Saw Gin Stand with Adjustable Movement of the Roll Box

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Engineering（科研） 2018年第8期10卷 486-494页

作者： Umarov Akmal Akhmedkhodzhaev Khamit Sarimsakov Akramjon Kenjaeva muazzam Namangan Institute of Engineering and Technology Namangan Uzbekistan

The article contains information about saw gin used at cotton processing plants. The influence of the density of the seed roll, which is formed in the roll box of the saw gin, on the load of the saw cylinder drive and on the technological characteristics of the machine is considered. As a result of the research, in order to preserve the quality characteristics of fiber and seeds, the author proposes a gin stand with a system for regulating the position of the roll box.

关键词： Seed Cotton Ginning of Cotton Saw Gin Stand Roll Box Seed Roll Load Current Sensor Controller