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Dataset of Large Gathering Images for Person Identification and Tracking

Computers, Materials & Continua 2023年第3期74卷 6065-6080页

作者： adnan nadeem Amir Mehmood Kashif Rizwan Muhammad Ashraf Nauman Qadeer Ali Alzahrani Qammer H.Abbasi Fazal Noor Majed Alhaisoni nadeem Mahmood Faculty of Computer and Information System Islamic University of MadinahMadinah42351Saudi Arabia Department of Computer Science and Information Technology Sir Syed University of Engineering and TechnologyKarachi75300Pakistan Department of Computer Science Federal Urdu University of ArtsScience&TechnologyIslamabad45570Pakistan Department of Physics Federal Urdu University of ArtsScience&TechnologyKarachi75300Pakistan James Watt School of Engineering University of GlasgowGlasgowG128QQUK Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science University of KarachiKarachi75270Pakistan

This paper presents a large gathering dataset of images extracted from publicly filmed videos by 24 cameras installed on the premises of Masjid Al-Nabvi,Madinah,Saudi *** dataset consists of raw and processed images reflecting a highly challenging and unconstraint *** methodology for building the dataset consists of four core phases;that include acquisition of videos,extraction of frames,localization of face regions,and cropping and resizing of detected face *** raw images in the dataset consist of a total of 4613 frames obtained fromvideo *** processed images in the dataset consist of the face regions of 250 persons extracted from raw data images to ensure the authenticity of the presented *** dataset further consists of 8 images corresponding to each of the 250 subjects(persons)for a total of 2000 *** portrays a highly unconstrained and challenging environment with human faces of varying sizes and pixel quality(resolution).Since the face regions in video sequences are severely degraded due to various unavoidable factors,it can be used as a benchmark to test and evaluate face detection and recognition algorithms for research *** have also gathered and displayed records of the presence of subjects who appear in presented frames;in a temporal *** can also be used as a temporal benchmark for tracking,finding persons,activity monitoring,and crowd counting in large crowd scenarios.

关键词： Large crowd gatherings a dataset of large crowd images highly uncontrolled environment tracking missing persons face recognition activity monitoring

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Fusion-Based Machine Learning Architecture for Heart Disease Prediction

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Computers, Materials & Continua 2021年第5期67卷 2481-2496页

作者： Muhammad Waqas nadeem Hock Guan Goh Muhammad adnan Khan Muzammil Hussain Muhammad Faheem Mushtaq Vasaki a/p Ponnusamy Faculty of Information and Communication Technology(FICT) Universiti Tunku Abdul Rahman(UTAR)KamparPerak31900Malaysia Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan Department of Information Technology Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan

The contemporary evolution in healthcare technologies plays a considerable and signicant role to improve medical services and save human *** disease or cardiovascular disease is the most fatal and complex disease which it is hardly to be detected through our naked eyes,as numerous people have been suffering from this disease *** attacks occur when the ranges of vital signs such as blood pressure,pulse rate,and body temperature exceed their normal *** efcient diagnosis of heart diseases could play a substantial role in the eld of cardiology,while diagnostic time could be *** has been a key challenge for researchers and medical experts to diagnose heart diseases accurately and ***,machine learning-based techniques are used for the diagnosis with higher accuracy,using datasets compiled from former medical patients’*** recent years,numerous studies have been presented in the literature propose machine learning techniques for diagnosing heart ***,the existing techniques have some limitations in terms of their *** this paper,a novel Support Vector Machine(SVM)based architecture for heart disease prediction,empowered with a fuzzy based decision level fusion,is *** SVMbased architecture has improved the accuracy signicantly as compared to existing solutions,where 96.23%accuracy has been achieved.

关键词： Heart disease machine learning support vector machine fuzzy logic fusion cardiovascular

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Enabling Smart Cities with Cognition Based Intelligent Route Decision in Vehicles Empowered with Deep Extreme Learning Machine

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Computers, Materials & Continua 2021年第1期66卷 141-156页

作者： Dildar Hussain Muhammad adnan Khan Sagheer Abbas Rizwan Ali Naqvi Muhammad Faheem Mushtaq Abdur Rehman Afrozah nadeem School of Computational Sciences Korea Institute for Advanced StudySeoul02455Korea Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Unmanned Vehicle Engineering Sejong UniversitySeoul05006Korea Department of Information Technology Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan

The fast-paced growth of artificial intelligence provides unparalleled opportunities to improve the efficiency of various industries,including the transportation *** worldwide transport departments face many obstacles following the implementation and integration of different vehicle *** of these tasks is to ensure that vehicles are autonomous,intelligent and able to grow their repository of *** learning has recently been implemented in wireless networks,as a major artificial intelligence branch,to solve historically challenging problems through a data-driven *** this article,we discuss recent progress of applying machine learning into vehicle networks for intelligent route decision and try to focus on this emerging *** Extreme Learning Machine(DELM)framework is introduced in this article to be incorporated in vehicles so they can take human-like *** present GPS compatibility issues make it difficult for vehicles to take real-time decisions under certain *** leads to the concept of vehicle controller making *** proposed DELM based system for self-intelligent vehicle decision makes use of the cognitive memory to store route *** overcomes inadequacy of the current in-vehicle route-finding technology and its *** the relevant route-related information for the ride will be provided to the user based on its *** the DELM method,a high degree of precision in smart decision taking with a minimal error rate is *** investigation,it has been observed that proposed framework has the highest accuracy rate with 70%of training(1435 samples)and 30%of validation(612 samples).Simulation results validate the intelligent prediction of the proposed method with 98.88%,98.2%accuracy during training and validation respectively.

关键词： DELM ANN IoT feedforward route decision prediction smart city

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Factors influencing hybrid maize farmers' risk attitudes and their perceptions in Punjab Province,Pakistan

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Journal of Integrative Agriculture 2018年第6期17卷 1454-1462页

作者： Shoaib Akhtar LI Gu-cheng Raza Ullah adnan Nazir Muhammad Amjed Iqbal Muhammad Haseeb Raza nadeem Iqbal Muhammad Faisal College of Economics & Management Huazhong Agricultural University Institute of Agricultural and Resource Economics University of Agriculture Faisalabad The Management School Lancaster University

Hybrid maize farmers have to face diverse kinds of climate, biological, price and financial risks. Farmers＇ risk perceptions and risk attitudes are essential elements influencing farm operations and management decisions. However, this important issue has been overlooked in the contemporary studies and therefore there is a dearth of literature on this important issue. The present research is therefore, an attempt to fill this gap. This study aims to quantify hybrid maize farmers＇ perceptions of disastrous risks, their attitudes towards risk and to explore the impacts of various farm and farm household factors on farmers＇ risk attitudes and risk perceptions. The present study is conducted in four hybrid maize growing districts of Punjab Province, Pakistan, using cross-sectional data of 400 hybrid maize farmers. Risk matrix and equally likely certainty equivalent （ELCE） method are used to rank farmers＇ perceptions of four catastrophic risk sources including climate, biological, price and financial risks and to investigate farmers＇ risk aversion attitudes, respectively. Furthermore, probit regression is used to analyze the determinants affecting farmers＇ risk attitudes and risk perceptions. The results of the study showed that majority of farmers are risk averse in nature and perceive price, biological and climate to be potential sources of risks to their farm enterprise. In addition, analysis divulges that distance from farm to main market, off-farm income, location dummies for Sahiwal and Okara, age, maize farming experience, access to extension agent, significantly （either negatively or positively） influence farmers＇ risk attitudes and risk perceptions. The study delivers valuable insights for farmers, agricultural insurance sector, extension services researchers and agricultural policy makers about the local understanding of risks to hybrid maize crop in developing countries, like Pakistan, and have implications for research on farmers＇ adaptation to exposed risks.

关键词： risk perceptions risk attitude hybrid maize determinants Punjab Pakistan

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Comprehensive genetic screening reveals wide spectrum of genetic variants in monogenic forms of diabetes among Pakistani population

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World Journal of Diabetes 2021年第11期12卷 1957-1966页

作者： Ibrar Rafique Asif Mir Shajee Siddiqui Muhammad Arif nadeem Saqib Asher Fawwad Luc Marchand Muhammad adnan Muhammad Naeem Abdul Basit Constantin Polychronakos Department of Biological Sciences International Islamic UniversityIslamabad 44000Pakistan Departments of Pediatrics and Human Genetics McGill University Health Centre Research InstituteMontreal H4A 3J1Canada Research Development and Coordination Pakistan Health Research CouncilIslamabad 44000Pakistan Department of Medicine Pakistan Institute of Medical SciencesIslamabad 44000PakistanPakistan Department of Medical Laboratory Technology National Skills UniversityIslamabad44000Pakistan Department of Biochemistry Baqai Institute of Diabetology and EndocrinologyBaqai Medical UniversityKarachi 74600SindhPakistan PHRC Research Centre FJMUPakistan Health Research CouncilLahore 54000Pakistan Department of Biotechnology Quaid-I-Azam UniversityIslamabad 44000Pakistan Department of Medicine Baqai Institute of Diabetology and EndocrinologyBaqai Medical UniversityKarachi 74600SindhPakistan

BACKGROUND Monogenic forms of diabetes(MFD)are single gene *** diagnosis is challenging,and symptoms overlap with type 1 and type 2 *** To identify the genetic variants responsible for MFD in the Pakistani population and their *** A total of 184 patients suspected of having MFD were *** inclusion criterion was diabetes with onset below 25 years of *** demographic and clinical information were taken from the *** maturity-onset diabetes of the young(MODY)probability score was calculated,and glutamate decarboxylase ELISA was *** negative patients and features resembling MODY were selected(n=28)for exome sequencing to identify the pathogenic *** A total of eight missense novel or very low-frequency variants were identified in 7 *** variants were found in genes for MODY,***1A(c.169C>A,***57Met),KLF11(c.401G>C,***134Ala),and HNF1B(c.1058C>T,***353Leu).Five variants were found in genes other than the 14 known MODY genes,***6(c.919G>A,***307Lys),WFS1(c.478G>A,***160Lys)and WFS1(c.517G>A,***173Lys),RFX6(c.1212T>A,***404Gln)and ZBTB20(c.1049G>A,***350His).CONCLUSION The study showed wide spectrum of genetic variants potentially causing MFD in the Pakistani *** MODY genes prevalent in European population(GCK,HNF1A,and HNF4a)were not found to be common in our *** of novel variants will further help to understand the role of different genes causing the pathogenicity in MODY patient and their proper management and diagnosis.

关键词： MODY Diabetes Genetics Monogenic diabetes Monogenic forms of diabetes

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