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Titania coating formation on hydrostatically extruded pure titanium by micro-arc oxidation method

Journal of Materials Science & Technology 2022年第16期111卷 224-235页

作者： Ł.Maj D.Wojtas A.Jarz˛ebska M.Bieda K.Trembecka-Wójciga R.Chulist W.Kozioł A.Góral A.Trelka K.Janus J.Kawałko M.Kulczyk F.Muhaffel H.Çimeno˘glu K.Sztwiertnia Institute of Metallurgy and Materials Science Polish Academy of SciencesReymonta 25Krakow 30-059Poland Faculty of Physics and Applied Computer Science AGH University of Science and TechnologyKrakowPoland Academic Centre of Materials and Nanotechnology AGH University of Science and TechnologyKrakowPoland Institute of High Pressure Physics Polish Academy of SciencesWarsawPoland Department of Metallurgical and Materials Engineering Istanbul Technical UniversityIstanbulTurkey

In this work,the microstructure of titania coating fabricated on the surface of hydrostatically extruded titanium grade 4 with the use of the micro-arc oxidation method was *** surface topography and microstructure investigations performed with atomic force microscopy and scanning and transmission electron microscopy revealed that,by using an Na_(2)HPO_(4)electrolyte,a well-adherent porous coating is produced on the top surface and side walls of the extruded *** distribution of chemical elements was analyzed by using energy dispersive X-ray *** chemical elements dissolved in the electrolyte(Na,P and O)incorporated into the *** locates preferentially in the outer part of the coating,while phosphorus and oxygen are distributed throughout the whole *** most relevant finding shows that a grain refinement caused by a hydrostatic extrusion provoked an increase in density of high-angle grain boundaries(HAGB),which in turn secured the formation of a continuous amorphous layer close to the *** presence of this layer compensates for the effect of anisotropic substrate,producing a comparable and homogenous microstructure with a large number of micropores.

关键词： Micro-arc oxidation Titanium of commercial purity Hydrostatic extrusion Surface topography Microstructure

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A Hybrid Framework of Meta-Learning and Generative Adversarial Networks for Few-Shot Malware Detection

A Hybrid Framework of Meta-Learning and Generative Adversari...

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International Bhurban Conference on applied sciences & Technology, IBCAST

作者： Faiza Babar Khan Muhammad Hanif Durad Asifullah Khan Mureed Hussain Dept. of Computer & Information Sciences CIPMA Lab Pakistan Institute of Engineering and Applied Sciences (PIEAS) Islamabad Pakistan Dept. of Computer & Information Sciences PR Lab Pakistan Institute of Engineering and Applied Sciences (PIEAS) Islamabad Pakistan CESAT The National Centre for Physics Islamabad Pakistan

ISBN: (数字)9798350308259

ISBN: (纸本)9798350308266

Malware detection poses a significant challenge due to the constant evolution and proliferation of malicious software. Traditional approaches often struggle to keep up with the ever-growing variety of malware samples. In this paper, we offer a hybrid framework (MetaGANet) that combines the power of meta-learning and generative adversarial networks (GANs) to address the problem of few-shot malware detection. By leveraging the capabilities of meta-learning, our framework can rapidly acclimatize to new malware samples with limited training data, thereby enhancing detection performance. The GAN component of our framework generates synthetic malware samples, allowing for robust training and augmenting the available data. We conduct extensive experiments using benchmark dataset miniImagenet and malware dataset Figshare and demonstrate the effectiveness of our hybrid approach. Our results show significant improvements in few-shot malware detection accuracy, surpassing traditional methods. The proposed framework offers a promising solution to the ongoing challenge of efficiently detecting and combating emerging malware threats.

关键词： Metalearning Training Accuracy Training data Benchmark testing Generative adversarial networks Malware Hybrid power systems

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Real Transportation Data Benchmark: Advancing Efficiency through ML-Based Waiting Time Prediction

Real Transportation Data Benchmark: Advancing Efficiency thr...

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International Conference on Intelligent Transportation

作者： Julian Klinger Mohammad Reza Mohebbi Mario Döller University of Applied Sciences Kufstein Tirol Kufstein Austria Department of Computer Science University of Passau Passau Germany Josef Ressel Center Vision2Move University of Applied Science s Kufstein Tirol Kufstein Austria

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

In transport and supply chain management (SCM), accurate prediction of waiting times is pivotal for optimizing resource allocation, minimizing costs, and operational efficiency. However, this task is filled with challenges due to numerous unknown variables, including congestion, weather conditions, and varying operational requirements. This paper addresses these challenges by predicting the waiting times of transporters in transport management and SCM. By analyzing key performance indicators in the planning process of production measures and delivery cycles, we have identified an important research direction for improving the accuracy of forecasting waiting times. Therefore, we introduce a novel dataset based on real data, focusing on delivery cycles, by analyzing GPS-Trajectories and planning data of 165 transporters on 550 production measures in a span of one year and condensing them into a total of 6144 delivery records. To set a performance baseline, we analyze this dataset and apply several Machine Learning models, such as AdaBoost, SVR and MLP, for waiting time prediction by providing different metrics such as MAE, MSE and the R2-Score. We conclude that, with our approach, it is possible to successfully predict waiting time in the form of trends already in the planning phase of transport management. The dataset is available on GitHub: ***/KlingerjU/Real-Transportation-Data-Benchmark

关键词： Accuracy Supply chain management Supply chains Transportation Production Machine learning Predictive models Time measurement Planning Trajectory

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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

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computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

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Colouring of COVID-19 Affected Region Based on Fuzzy Directed Graphs

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computers, Materials & Continua 2021年第7期68卷 1219-1233页

作者： Rupkumar Mahapatra Sovan Samanta Madhumangal Pal Jeong-Gon Lee Shah Khalid Khan Usman Naseem Robin Singh Bhadoria Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar UniversityMidnapore721102India Department of Mathematics Tamralipta MahavidyalayaTamluk721636India Division of Applied Mathematics Wonkwang UniversityIksan-SiJeonbuk54538Korea School of Engineering RMIT UniversityMelbourne3001Australia School of Computer Science University of Sydney Sydney2006Australia Department of Computer Science&Engineering Birla Institute of Applied Sciences(BIAS)BhimtalUttarakhand263136India

Graph colouring is the system of assigning a colour to each vertex of a *** is done in such a way that adjacent vertices do not have equal *** is fundamental in graph *** is often used to solve real-world problems like traffic light signalling,map colouring,scheduling,***,social networks are prevalent systems in our ***,the users are considered as vertices,and their connections/interactions are taken as *** users follow other popular users’profiles in these networks,and some don’t,but those non-followers are connected directly to the popular *** means,along with traditional relationship(information flowing),there is another relation among *** depends on the domination of the relationship between the *** type of situation can be modelled as a directed fuzzy *** the colouring of fuzzy graph theory,edge membership plays a vital *** membership is a representation of flowing information between end nodes of the *** from the communication relationship,there may be some other factors like domination in *** influence of power is captured *** this article,the colouring of directed fuzzy graphs is defined based on the influence of *** with this,the chromatic number and strong chromatic number are provided,and related properties are *** application regarding COVID-19 infection is presented using the colouring of directed fuzzy graphs.

关键词： Graph colouring chromatic index directed fuzzy graphs

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Inf-TESLA++: A Blockchain-assisted Continuous Authentication Protocol for Broadcast Communication in Resource-Constrained Devices

Inf-TESLA++: A Blockchain-assisted Continuous Authentication...

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International Symposium on Advanced Networks and Telecommunication Systems (ANTS)

作者： Mallikarjun Reddy Dorsala Charugundla Lakshmi Nishitha Pendem Sathwik Gattu Srilekha Mahesh Kumar Morampudi Department of Computer Science and Engineering Indian Institute of Information Technology Sri City Chittoor India Department of Computer Science and Engineering School of Engineering and Applied Sciences (SEAS) SRM University AP India

ISBN: (数字)9798350391725

ISBN: (纸本)9798350391732

Many applications widely use broadcast communications (BC) due to their efficiency in simultaneously distributing data to many receivers. More specifically, BC is essential in resource-constrained devices (RCDs) for conserving energy and bandwidth, which are vital for increasing the longevity and performance of RCDs. The three major challenges in BC are source authentication, data integrity and continuous authentication (CA). The first two challenges are effectively addressed in TESLA and its variants. However, achieving CA without incurring overheads on the sender and receiver sides remains an unresolved challenge. In this paper, we propose Infinite (Inf) TESLA++, assisted by Blockchain and smart contracts, to address the CA challenge with minimal overhead at sender and receiver. Our theoretical and simulation analysis demonstrates that Inf-TESLA++ incurs minimal overhead compared to existing protocols while eliminating the need for direct communication between the sender and receiver for synchronization.

关键词： Performance evaluation Smart contracts Authentication Receivers Bandwidth Blockchains Telecommunications Security Synchronization Testing

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Resource Allocation in Cloud Computing Using Quasi-Opposition Learning Based Aquila Optimizer

Resource Allocation in Cloud Computing Using Quasi-Oppositio...

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International Conference on 6G Communications Networking and Signal Processing, SGCNSP 2023

作者： Kumari, K. Aruna Muvva, Vijaya Bhaskar Reddy Kumar, K. Sudheer Rai, B. Karunakara Shakir, Aboothar Mahmood Department of CSE SRKR Engineering College Bhimavaram Chinaamiram India Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences -Shinas Shinas Oman School of Computer Science and Artificial Intelligence SR University Warangal India Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India The Islamic University Najaf Iraq

ISBN: (纸本)9789819778751

The resource allocation is focus on enhancing the service provider proceedings and obtaining customer satisfaction by Service Level Agreements (SLA). Cloud technology has significantly transformed the organizations to manage and allocate their resources. The cloud users are choosing sources of application distribution exclusive of cooperating Quality of Service (QoS) necessities. To overcome this issue, this paper proposed a Quasi-Opposition Learning based Aquila Optimizer (QOL-AO) for resource allocation in cloud. The virtualization supports to implement task using resource availability and reduces the response time. The QOL-AO employs the hunting approach for obtain the effective and efficient resource allocation in cloud. The Performance of QOL-AO is estimate through execution time, response time and energy consumption for various number of Virtual Machines (VMs). The QOL-AO attained less execution time of 18.568 ms and response time of 0.095 s than existing algorithms like Emperor Penguin Optimization (EPO) and Particle Swarm Optimization (PSO). © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cloud platforms

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Insight into the liver dysfunction in COVID-19 patients: Molecular mechanisms and possible therapeutic strategies

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World Journal of Gastroenterology 2023年第14期29卷 2064-2077页

作者： Naina Khullar Jasvinder Singh Bhatti Satwinder Singh Bhawana Thukral P Hemachandra Reddy Gurjit Kaur Bhatti Department of Zoology Mata Gujri CollegeFatehgarh Sahib 140407PunjabIndia Laboratory of Translational Medicine and Nanotherapeutics Department of Human Genetics and Molecular MedicineSchool of Health SciencesCentral University of PunjabBathinda 151401PunjabIndia Department of Computer Science and Technology Central University of PunjabBathinda 151401PunjabIndia Department of Nutrition and Dietetics University Institute of Applied Health SciencesChandigarh UniversityMohali 140413PunjabIndia Department of Internal Medicine Texas Tech University Health Sciences CenterLubbockTX 79430United States Department of Medical Lab Technology University Institute of Applied Health SciencesChandigarh UniversityMohali 140413PunjabIndia

As of June 2022,more than 530 million people worldwide have become ill with coronavirus disease 2019(COVID-19).Although COVID-19 is most commonly associated with respiratory distress(severe acute respiratory syndrome),metaanalysis have indicated that liver dysfunction also occurs in patients with severe *** studies revealed distinctive patterning in the receptors on the hepatic cells that helps in viral invasion through the expression of angiotensinconverting enzyme *** has also been reported that in some patients with COVID-19,therapeutic strategies,including repurposed drugs(mitifovir,lopinavir/ritonavir,tocilizumab,etc.)triggered liver injury and cholestatic *** proven indicators support cytokine storm-induced hepatic *** there are 1.5 billion patients with chronic liver disease worldwide,it becomes imperative to critically evaluate the molecular mechanisms concerning hepatotropism of COVID-19 and identify new potential *** review also designated a comprehensive outlook of comorbidities and the impact of lifestyle and genetics in managing patients with COVID-19.

关键词： COVID-19 Liver damage Pharmacotherapy Cytokine storm Molecular mechanisms

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Impact and Research Challenges of Penetrating Testing and Vulnerability Assessment on Network Threat 2

Impact and Research Challenges of Penetrating Testing and Vu...

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Fatima, Areej Khan, Tahir Abbas Abdellatif, Tamer Mohamed Zulfiqar, Sidra Asif, Muhammad Safi, Waseem Hamadi, Hussam Al Al-Kassem, Amer Hani NCBA&E Department of Computer Science Lahore Pakistan NCBA&E School of Computer Science Lahore Pakistan Canadian University Dubai Faculty of Engineering Applied Science and Technology Dubai United Arab Emirates Applied Science Private University Applied Science Research Center Amman11937 Jordan Higher Institute for Applied Sciences and Technology- HIAST Damascus Syria University of Dubai College of Engineering and IT PO Box 14143 United Arab Emirates College of Business Management Sharjah United Arab Emirates

ISBN: (纸本)9798350335644

The primary goal of this research article is to identify prevalent network dangers and provide countermeasures to these threats. In this modern era, everyone has access to the internet. SECURITY is a serious issue that everyone faces. Every day, experienced hackers breach security and exploit weaknesses to gain access to top secret and confidential data. To avoid these risks, we proposed vulnerability assessment and penetration testing (VAPT). This technique addresses the CIA's principles of confidentiality, integrity, and availability. All three goals refer to keeping your data safe and out of the hands of intruders. We uncover weak places in the system during vulnerability assessment, and we provide strategies to keep the system secure from hackers and prevent possible attacks via penetration testing. This paper presented the most in-depth description of VAPT, discussing the many processes and methodologies of Vulnerability Assessment and Penetration Testing. © 2023 IEEE.

关键词： Personal computing

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Leaf Disease Detection of Multiple Plants Using Deep Learning

Leaf Disease Detection of Multiple Plants Using Deep Learnin...

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2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022

作者： Pawar, Shital Shedge, Sakshi Panigrahi, Nibedita Jyoti, A.P. Thorave, Pradnya Sayyad, Samina Bharati Vidyapeeth's College of Engineering for Women Computer Engineering Department Pune India RV Institute of Technology and Management Information Science and Engineering Department Bengaluru India Ramaiah University of Applied Sciences Computer Science and Engineering Department Bengaluru India

ISBN: (数字)9781665496025

ISBN: (纸本)9781665496025

The great advancement in deep learning has increased the interest in technologies of image recognition. Different deep learning techniques help big data analysis with large potential and finding the disease of plant in agriculture sector. The deep learning model extract the features from an input and uses its features for classification. In consideration of climate change, plants are affected, which impacts agricultural yield. When the condition worsens, the plants become more susceptible to many diseases caused by fungi, bacteria, viruses, etc. Diseases can affect the plant growth. In the proposed system, CNN algorithm is used to detect the disease from leaf images and pesticides are suggested based on the disease found. The proposed method uses 15-layer CNN. The proposed system will provide pesticide supplier name according to area as well as it provides additional information about the leaf disease of the affected plant in the area, disease name, complete accuracy, time, and weather forecasting information also. The dataset contains 10 plants - apple, potato, corn, tomato, grape, rice, sugarcane, cucumber, pepper, soyabean. © 2022 IEEE.

关键词： Pesticides

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