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Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

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Computers, Materials & Continua 2024年第4期79卷 93-115页

作者： Shafi Ullah Sibghat Ullah Bazai Mohammad Imran Qazi mudassar Ilyas Abid Mehmood Muhammad Asim Saleem Muhmmad Aasim Rafique Arsalan Haider Ilyas Khan Sajid Iqbal Yonis Gulzar Kauser hameed Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Department of Information Technology Balochistan University of Information TechnologyEngineeringand Management SciencesQuetta87300Pakistan Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Software Engineering College of ComputingRiphah International UniversityFaisalabad44000Pakistan Department of Electrical Engineering Balochistan University of Information Technology Engineeringand Management SciencesQuetta87300Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

关键词： Authentication cyber security internet of things machine-type communication devices machine-to-machine communication

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Deep Convolutional Neural Networks for Accurate Classification of Gastrointestinal Tract Syndromes

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Computers, Materials & Continua 2024年第1期78卷 1207-1225页

作者： Zahid Farooq Khan Muhammad Ramzan mudassar Raza Muhammad Attique Khan Khalid Iqbal Taerang Kim Jae-Hyuk Cha Department of Computer Science COMSATS University IslamabadWah CampusWah47040Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science COMSATS University IslamabadAttock CampusAttock43600Pakistan Department of Computer Science Hanyang UniversitySeoul04763Korea

Accurate detection and classification of artifacts within the gastrointestinal(GI)tract frames remain a significant challenge in medical image processing.Medical science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous diseases.Key to this is the development of robust algorithms for image classification and detection,crucial in designing sophisticated systems for diagnosis and treatment.This study makes a small contribution to endoscopic image classification.The proposed approach involves multiple operations,including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and Xception.Additionally,feature optimization utilizes the binary dragonfly algorithm(BDA),with the fusion of the obtained feature vectors.The fused feature set is input into the ensemble subspace k nearest neighbors(ESKNN)classifier.The Kvasir-V2 benchmark dataset,and the COMSATS University Islamabad(CUI)Wah private dataset,featuring three classes of endoscopic stomach images were used.Performance assessments considered various feature selection techniques,including genetic algorithm(GA),particle swarm optimization(PSO),salp swarm algorithm(SSA),sine cosine algorithm(SCA),and grey wolf optimizer(GWO).The proposed model excels,achieving an overall classification accuracy of 98.25% on the Kvasir-V2 benchmark and 99.90% on the CUI Wah private dataset.This approach holds promise for developing an automated computer-aided system for classifying GI tract syndromes through endoscopy images.

关键词： Feature fusion Darknet-53 Xception binary dragonfly algorithm ensemble

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Bond-Slip Behavior of Steel Bar and Recycled Steel Fibre-Reinforced Concrete

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Journal of Renewable Materials 2024年第1期12卷 167-186页

作者： Ismail Shah Jing Li Nauman Khan Hamad R.Almujibah Muhammad mudassar Rehman Ali Raza Yun Peng School of Architecture and Civil Engineering Yunnan Agricultural UniversityKunming650000China Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu610041China Yunnan International Joint R&D Center of Smart Agriculture and Water Security Yunnan Agricultural UniversityKunming650201China School of Water Conservancy Yunnan Agricultural UniversityKunming650201China School of Civil Engineering Guizhou UniversityGuiyang550025China Department of Civil Engineering College of EngineeringTaif UniversityP.O.Box 11099Taif City21974Saudi Arabia School of Civil Engineering Zhengzhou UniversityZhengzhou450001China

Recycled steel fiber reinforced concrete is an innovative construction material that offers exceptional mechanical properties and durability.It is considered a sustainable material due to its low carbon footprint and environmental friendly characteristics.This study examines the key influencing factors that affect the behavior of this material,such as the steel fiber volume ratio,recycled aggregate replacement rate,concrete strength grade,anchorage length,and stirrup constraint.The study investigates the bond failure morphology,bond-slip,and bond strength constitutive relationship of steel fiber recycled concrete.The results show that the addition of steel fibers at 0.5%,1.0%,and 1.5%volume ratios can improve the ultimate bond strength of pull-out specimens by 9.05%,6.94%,and 5.52%,respectively.The replacement rate of recycled aggregate has minimal effect on the typical bond strength of pull-out specimens.However,the ultimate bond strengths of pull-out specimens with concrete strength grades C45 and C60 have improved compared to those with C30 grade.The specimens with longer anchorage lengths exhibit lower ultimate bond strength,with a reduction of 33.19%and 46.37%for anchorage lengths of 5D and 7D,respectively,compared to those without stirrups.Stirrup restraint of 1φ8 and 2φ8 improves the ultimate bond strength by 5.29%and 6.90%,respectively.Steel fibers have a significant effect on the behavior of concrete after it cracks,especially during the stable expansion stage,crack instability expansion stage,and failure stage.

关键词： Recycled coarse aggregates(RCA) steel fiber bonding performance bond-slip environmental challenges

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不同国家黄油和黄油乳脂理化性质的比较评价

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中国油脂 2024年第7期49卷 29-39页

作者：邹孝强蒋邦智郑磊胡纪洁潘月超王钦民 IMAD Khan mudassar Hussain 江南大学食品学院食品科学与资源挖掘国家重点实验室国家功能食品工程技术研究中心粮食发酵与食品生物制造国家工程研究中心江苏无锡214122 伽力森食品生物科技(江苏)有限公司江苏泰州225700

为帮助食品生产商和消费者选择适用于不同应用途径的黄油,并为生产更受消费者喜爱的黄油替代品提供理论支持,选取了11个国家的黄油并提取黄油乳脂,对黄油及黄油乳脂的理化性质进行了系统的比较评价。结果表明:11个国家黄油中的脂肪、水... 详细信息

为帮助食品生产商和消费者选择适用于不同应用途径的黄油,并为生产更受消费者喜爱的黄油替代品提供理论支持,选取了11个国家的黄油并提取黄油乳脂,对黄油及黄油乳脂的理化性质进行了系统的比较评价。结果表明:11个国家黄油中的脂肪、水分、蛋白质含量和滑动熔点分别为82.97%~86.40%、12.84%~16.14%、0.45%~0.78%、31.5~33.9℃,酸值(KOH)和过氧化值分别不超过0.32 mg/g、0.029 g/100 g。中国黄油的L值最高(86.87),而新西兰黄油的b值最高(35.28)。所有黄油共检出29种脂肪酸和42种甘油三酯,蛋白质主要由αs1-酪蛋白、β-酪蛋白、κ-酪蛋白、α-乳白蛋白和Adipophilin组成。爱尔兰黄油的不饱和脂肪酸含量最高(35.65%),固体脂肪含量(SFC)较低,而美国、荷兰和澳大利亚黄油的饱和脂肪酸和SFC含量较高。不同国家的黄油和黄油乳脂的晶体均为均匀精细的球晶,其中美国黄油和黄油乳脂的晶体均呈现部分聚集,且绝大多数晶体主要由β′型晶体组成。质地和流变学分析表明,爱尔兰黄油和黄油乳脂的硬度最低,所有黄油和黄油乳脂都表现出良好的黏弹性和剪切变稀性能。综上,不同国家黄油在基本理化性质、脂肪酸和甘油酯组成、SFC及硬度等方面存在差异,在食品工业中需要根据成品、加工工艺等有针对性地选择黄油,在新型人造奶油的构建中,也可依据各黄油特点进行定向研究。

关键词：黄油黄油乳脂理化性质晶体质构流变

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不同国家黄油和黄油乳脂的理化性质的比较评价

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中国油脂 2024年

作者：邹孝强蒋邦智郑磊胡纪洁潘月超王钦民 IMAD Khan mudassar Hussain 伽力森食品生物科技(江苏)有限公司食品科学与资源挖掘国家重点实验室国家功能食品工程技术研究中心粮食发酵与食品生物制造国家工程研究中心江南大学食品学院

不同国家的饲养方式及加工条件会在一定程度上影响黄油的理化性质，由此对其使用特性产生影响，但是目前极少有研究对此进行报道。本研究选取了11个国家的黄油并对其理化性质进行了系统的比较评价。黄油中的水分和蛋白质含量分别为12.84... 详细信息

不同国家的饲养方式及加工条件会在一定程度上影响黄油的理化性质，由此对其使用特性产生影响，但是目前极少有研究对此进行报道。本研究选取了11个国家的黄油并对其理化性质进行了系统的比较评价。黄油中的水分和蛋白质含量分别为12.84%-16.14%、0.45%-0.78%，且不同国家存在显著差异。中国黄油的颜色是最白的（L=86.87，b=14.19），而新西兰黄油的颜色则是最黄的（L=78.45，b=35.28）。爱尔兰黄油的不饱和脂肪酸含量最高（35.65%），固体脂肪含量（SFC）最低，而美国、荷兰和澳大利亚的黄油的饱和脂肪酸和SFC含量较高。不同国家的黄油晶体主要由β’晶体组成，中国、美国、法国和德国的黄油β’晶体含量相对较高。中国黄油的晶体最小，意大利黄油的晶体呈现部分聚集成，因而具有较大的晶体颗粒。质地和流变学分析表明，爱尔兰黄油的硬度最低（5 ℃，938.13 g；25 ℃，20.15 g），所有黄油都表现出良好的粘弹性和剪切变稀性能。本研究所得基础数据将有助于食品生产商和消费者选择适用于不同应用途径的黄油，并为生产更受消费者喜爱的黄油替代品提供支持。

关键词：黄油理化性质晶体质构流变

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On the gauge dependence of scalar induced secondary gravitational waves during radiation and matter domination eras

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中国科学:物理学、力学、天文学英文版 2023年第9期66卷 23-41页

作者： Arshad Ali Ya-Peng Hu mudassar Sabir Taotao Sui College of Physics Nanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Aerospace Information Materials and Physics(NUAA) MIITNanjing 211106China Center for Gravitation and Cosmology College of Physical Science and TechnologyYangzhou UniversityYangzhou 225009China School of Geophysics and Geomatics China University of GeosciencesWuhan 430074China

We revisit the vital issue of gauge dependence in the scalar-induced secondary gravitational waves(SIGWs), focusing on the radiation domination(RD) and matter domination(MD) eras. The energy density spectrum is the main physical observable in such induced gravitational waves. For various gauge choices, there has been a divergence in the energy density, ?GW, of SIGWs.We calculate SIGWs in diferent gauges to quantify this divergence to address the gauge-dependent problem. In our previous studies, we had found that the energy density diverges in the polynomial power of conformal time(e.g., η^(6) in uniform density gauge). We try to fix this discrepancy by adding a counter-term that removes the fictitious terms in secondary tensor perturbations. We graphically compare the calculations in various gauges and also comment on the physical origin of the observed gauge dependence.

关键词： scalar induced gravitational waves gauge transformation cosmology

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Post-hepatectomy liver failure:A timeline centered review

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Hepatobiliary & Pancreatic Diseases International 2023年第6期22卷 554-569页

作者： Mohamed Bekheit Lisa Grundy Ahmed KA Salih Petru Bucur Eric Vibert mudassar Ghazanfar Department of Surgery NHS GrampianForesterhill Health CampusAshgrove RoadAB252ZN AberdeenUK Institute of Medical Sciences Medical SchoolForesterhill Health CampusAshgrove RoadAB252ZN AberdeenUK Hépatica Integrated Center of HPB CareElite HospitalAgriculture RoadAlexandriaEgypt Department of Surgery University Hospital ToursVal de la Loire 37000France Centre Hépatobiliaire Paul Brousse Hospital12 Paul Valliant Couturier94804 VillejuifFrance

Background: Post-hepatectomy liver failure(PHLF) is a leading cause of postoperative mortality after liver surgery. Due to its significant impact, it is imperative to understand the risk stratification and preventative strategies for PHLF. The main objective of this review is to highlight the role of these strategies in a timeline centered way around curative resection. Data sources: This review includes studies on both humans and animals, where they addressed PHLF. A literature search was conducted across the Cochrane Library, Embase, MEDLINE/Pub Med, and Web of Knowledge electronic databases for English language studies published between July 1997 and June 2020. Studies presented in other languages were equally considered. The quality of included publications was assessed using Downs and Black’s checklist. The results were presented in qualitative summaries owing to the lack of studies qualifying for quantitative analysis. Results: This systematic review with 245 studies, provides insight into the current prediction, prevention, diagnosis, and management options for PHLF. This review highlighted that liver volume manipulation is the most frequently studied preventive measure against PHLF in clinical practice, with modest improvement in the treatment strategies over the past decade. Conclusions: Remnant liver volume manipulation is the most consistent preventive measure against PHLF.

关键词： Post-hepatectomy liver failure Liver neoplasms Prediction Prevention Management

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Parametic Model for Optimization of Battery Capacity and Power Transmitters of On-line Electric Vehicles in Closed/Open Environments

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CSEE Journal of Power and Energy Systems 2023年第1期9卷 185-196页

作者： Fatima Nisar Syed Haider Imtiaz Alam Asad Waqar Toqeer Ahmed mudassar Usman Department of Electrical Engineering School of Engineering&Applied Sciences(BSEAS)Bahria UniversityIslamabadPakistan Department of Centre for Advanced Electronics and Photovoltaic Engineering(CAEPE) International Islamic Universityand School of Interdisciplinary Engineering and Science(SINES)National University of Science and Technology(NUST)IslamabadPakistan

An on-line electric vehicle(OLEV)uses a wireless charging phenomenon,in which power transmitters are installed beneath the road and the OLEV’s battery is charged remotely.This paper deals with the optimization of two key economic and design parameters,i.e.,the size of the battery and the power transmitters allocation.A complete model configuration of the OLEV system,including the vehicle design and power transmitter,is implemented using MATLAB/Simulink.The battery’s state of charge(SOC)rises and drops according to the vehicle’s velocity and power collection and consumption.The mixed integer programming(MIP)model is used for cost calculation.Therefore,with the help of the SOC graph and MIP model,the battery size and the number of power transmitters,along with their placements,are optimized.The proposed model is applicable to both closed and open environments as it accepts both regulated and deregulated velocities.Two test cases are performed for this purpose.The first test case deals with regulated velocity for which we have applied the KAIST campus OLEV’s velocity along with its 13 kWh battery size and 4 power transmitters,and then applied the suggested solution with the same velocity and route i.e.,8 power transmitters with shorter lengths and reduced battery size(3.25 kWh;one-fourth of the first case).SOC is found within limits at the end of the route,saving$1600 and validating the proposed model in this paper.For the second test case,we use deregulated velocity and optimize both parameters,using the same approach.

关键词： Closed and open environments mixed integer programming on-line electrical vehicle power transmitters state of charge wireless charging

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Liquidity connectedness in cryptocurrency market

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Financial Innovation 2022年第1期8卷 81-105页

作者： mudassar Hasan Muhammad Abubakr Naeem Muhammad Arif Syed Jawad Hussain Shahzad Xuan Vinh Vo Lahore Business School The University of LahoreLahorePakistan Smurfit Graduate School of Business University Col-lege DublinDublinIreland Institute of Business Research University of Economics Ho Chi Minh CityHo Chi Minh CityVietnam Department of Business Administration Shaheed Benazir Bhutto UniversityShaheed BenazirabadPakistan Montpellier Business School MontpellierFrance South Ural State University ChelyabinskRussian Federation Institute of Business Research and CFVG University of Economics Ho Chi Minh CityHo Chi Minh CityVietnam

We examine the dynamics of liquidity connectedness in the cryptocurrency market.We use the connectedness models of Diebold and Yilmaz(Int J Forecast 28(1):57–66,2012)and Baruník and Křehlík(J Financ Econom 16(2):271–296,2018)on a sample of six major cryptocurrencies,namely,Bitcoin(BTC),Litecoin(LTC),Ethereum(ETH),Ripple(XRP),Monero(XMR),and Dash.Our static analysis reveals a moderate liquidity connectedness among our sample cryptocurrencies,whereas BTC and LTC play a significant role in connectedness magnitude.A distinct liquidity cluster is observed for BTC,LTC,and XRP,and ETH,XMR,and Dash also form another distinct liquidity cluster.The frequency domain analysis reveals that liquidity connectedness is more pronounced in the short-run time horizon than the medium-and long-run time horizons.In the short run,BTC,LTC,and XRP are the leading contributor to liquidity shocks,whereas,in the long run,ETH assumes this role.Compared with the medium term,a tight liquidity clustering is found in the short and long terms.The time-varying analysis indicates that liquidity connectedness in the cryptocurrency market increases over time,pointing to the possible effect of rising demand and higher acceptability for this unique asset.Furthermore,more pronounced liquidity connectedness patterns are observed over the short and long run,reinforcing that liquidity connectedness in the cryptocurrency market is a phenomenon dependent on the time–frequency connectedness.

关键词： Liquidity Time-frequency connectedness Cryptocurrencies

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Malaria Parasite Detection Using a Quantum-Convolutional Network

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Computers, Materials & Continua 2022年第3期70卷 6023-6039页

作者： Javaria Amin Muhammad Almas Anjum Abida Sharif mudassar Raza Seifedine Kadry Yunyoung Nam University of Wah Wah CanttPakistan National University of Technology(NUTECH) IslamabadPakistan COMSATS University Islamabad Vehari CampusVehariPakistan COMSATS University Islamabad Wah CampusPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea

Malaria is a severe illness triggered by parasites that spreads via mosquito bites.In underdeveloped nations,malaria is one of the top causes of mortality,and it is mainly diagnosed through microscopy.Computer-assisted malaria diagnosis is difficult owing to the fine-grained differences throughout the presentation of some uninfected and infected groups.Therefore,in this study,we present a new idea based on the ensemble quantum-classical framework for malaria classification.The methods comprise three core steps:localization,segmentation,and classification.In the first core step,an improved FRCNN model is proposed for the localization of the infected malaria cells.Then,the RGB localized images were converted into YCbCr channels to normalize the image intensity values.Subsequently,the actual lesion region was segmented using a histogram-based color thresholding approach.The segmented images were employed for classification in two different ways.In the first method,a CNN model is developed by the selection of optimum layers after extensive experimentation,and the final computed feature vector is passed to the softmax layer for classification of the infection/non-infection of themicroscopicmalaria images.Second,a quantum-convolutionalmodel is employed for informative feature extraction from microscopicmalaria images,and the extracted feature vectors are supplied to the softmax layer for classification.Finally,classification results were analyzed from two different models and concluded that the quantum-convolutional model achieved maximum accuracy as compared to CNN.The proposed models attain a precision rate greater than 90%,thereby proving that these models performed better than the existing models.

关键词： Quantum convolutional RGB YCbCr histogram Malaria

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