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IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)

作者： Priya Govindarajan Aswin Surendran P Sanjeev Kumar S Abebe Tesfahun Department of Computer Science Amrita School of Computing Amrita Vishwa Vidyapeetham School of Electrical & Computer Engineering Ethiopia Debre Markos Institute of Technology Debre Markos University Ethiopia

ISBN: (数字)9798350360059

ISBN: (纸本)9798350360066

The rampant spread of deepfake videos, a significant threat to media integrity, occurs widely on social media and news platforms. Detecting Deepfakes is a formidable challenge. The proposed study involves a novel algorithm to detect the deepfake. The model comprises of various pre-existing classifiers and a novel algorithm named ForenShield – which detects the deepfakes with an accuracy of 97%. The proposed novel technique works on voting strategy and it outperforms all the pre-existing classifiers, exhibiting the models excellence through the same.

关键词： Deepfakes Cloud computing Accuracy Social networking (online) Forensics Computational modeling Media Classification algorithms

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Hybrid Blockchain and IoT Driven Framework for Supply Chain Optimization by Enhancing Transparency, Efficiency and Cost Reduction

Hybrid Blockchain and IoT Driven Framework for Supply Chain ...

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Electronics and Renewable Systems (ICEARS), International Conference on

作者： Pradeep Kumar S CH Hussaian Basha C. Arun Prasath G. Amirthayogam Syed Ismail Abdul Lathif R. Leelavathi Computer Science Design Department Rajalakshmi Engineering College Thandalam Chennai Department of Electrical and Electronics Engineering SR University Warangal Department of ECE Mahendra Engineering College Namakkal Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Department of Data Science and Business Systems SRM Institute of Science and Technology Chennai Department of Biomedical Engineering Velalar College of Engineering and Technology Erode

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

Blockchain technology represents a modern supply chain management revolution which fixes operational challenges while providing enhanced transparency at reduced costs. The research develops HB-SCOF (Hybrid Blockchain-Enabled Supply Chain Optimization Framework) which combines blockchain self-verification databases with automatic smart contracts to maintain continuous supply chain observation and evaluate data credibility. The framework integrates tamper-proof transaction tracking mechanisms with unified supply chain network connectivity for securing data transmission as a trust delivery method through unbreakable shared databases. The retail-industry case study demonstrated a 25% decrease in expenses stemming from agency elimination alongside enhanced flow management and better stock distribution. The system demonstrates its effectiveness through assessments of key performance indicators including transaction speed and data accuracy together with business cost efficiency. This part looks at implementation methods through training stakeholders in addition to transforming organizational policies which produce successful outcomes. Blockchain technology labs verify its capability to enhance supply chain management efficiency while showing realistic deployment methods.

关键词： Training Costs Supply chain management Supply chains Smart contracts Key performance indicator Blockchains Stakeholders Internet of Things Optimization

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A 2D Transmitarray-Augmented Luneburg Lens Antenna for Millimeter-Wave Applications

A 2D Transmitarray-Augmented Luneburg Lens Antenna for Milli...

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Antennas and Propagation & USNC/URSI National Radio science Meeting

作者： Bader Alali Dmitry Zelenchuk Muhammad Ali Babar Abbasi Centre for Wireless Innovation (CWI) School of Electronics Electrical Engineering and Computer Science (EEECS) Queens University Belfast Belfast UK Electrical Engineering Department College of Engineering Jouf University Sakaka Saudi Arabia

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

This paper demonstrates a circular transmitarray- augmented Luneburg lens antenna for beam-forming at a millimeter-wave (mmWave) regime. The proposed structure is comprised of an augmentation of 80 dielectric cubes phase correction layer and two semi-circular 10-layer Luneburg lenses. The circular transmitarray-augmented Luneburg lens antenna is fed by a 9 dBi horn antenna at normal incidence and an oblique incidence of −150. The beam is successfully transmitted with an angle up to +45°. When the feed is oriented in normal incidence, a pencil beam is transmitted at 166°and 151°with a realized gain of 20.3 dBi, and sidelobe level (SSL) below −10.0 dB, at 28 GHz.

关键词： Horn antennas Two-dimensional displays Conferences Transmitting antennas Antenna feeds Dielectrics Millimeter wave communication

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Optimal Deep Learning Enabled Statistical Analysis Model for Traffic Prediction

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computers, Materials & Continua 2022年第9期72卷 5563-5576页

作者： Ashit Kumar Dutta S.Srinivasan S.N.Kumar T.S.Balaji Won Il Lee Gyanendra Prasad Joshi Sung Won Kim Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Institute of Biomedical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversitySaveetha NagarThandalamChennai602105India Department of Electrical&Electronics Engineering Amal Jyothi College of EngineeringKanjirappallyKerala686518India Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha UniversitySaveetha NagarThandalamChennai602105India Department of Electronics and Communication Engineering College of Engineering and TechnologySRM Institute of Science and TechnologyVadapalani CampusChennai600026India Department of Business Administration Hanbat National National UniversityDaejeon34158Korea Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siGyeongbuk-do38541Korea

Due to the advances of intelligent transportation system(ITSs),traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control,navigation,route mapping,*** traffic prediction model aims to predict the traffic conditions based on the past traffic *** more accurate traffic prediction,this study proposes an optimal deep learning-enabled statistical analysis *** study offers the design of optimal convolutional neural network with attention long short term memory(OCNN-ALSTM)model for traffic *** proposed OCNN-ALSTM technique primarily preprocesses the traffic data by the use of min-max normalization ***,OCNN-ALSTM technique was executed for classifying and predicting the traffic data in real time *** enhancing the predictive outcomes of the OCNN-ALSTM technique,the bird swarm algorithm(BSA)is employed to it and thereby overall efficacy of the network gets *** design of BSA for optimal hyperparameter tuning of the CNN-ALSTM model shows the novelty of the *** experimental validation of the OCNNALSTM technique is performed using benchmark datasets and the results are examined under several *** simulation results reported the enhanced outcomes of the OCNN-ALSTM model over the recent methods under several dimensions.

关键词： Statistical analysis predictive models deep learning traffic prediction bird swarm algorithm

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Optical spatiotemporal vortices

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eLight 2023年第1期3卷 156-168页

作者： Chenhao Wan Andy Chong Qiwen Zhan School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Optical and Electronic Information and Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074HubeiChina Department of Physics Pusan National UniversityGeumjeong-GuBusan 46241South Korea Zhangjiang Laboratory 100 Haike RoadShanghai 201204China Shanghai Key Lab of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China

Spatiotemporal vortices of light,featuring transverse orbital angular momentum(OAM)and energy circulation in the spatiotemporal domain,have received increasing attention *** experimental realization of the controllable generation of spatiotemporal vortices triggers a series of research in this *** review article covers the latest developments of spatiotemporal vortices of light ranging from theoretical physics,experimental generation schemes,and characterization methods,to applications and future *** new degree of freedom in photonic OAM endowed by spatiotemporal vortices paves the way to the discovery of novel physical mechanisms and photonic applications in light science.

关键词： Spatiotemporal optical vortex Orbital angular momentum Spin-orbit interaction Linear momentum density Toroidal vortex Topological charge

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A Service-Enhanced Task Offloading Method in MEC-Enabled IoV Networks 19

A Service-Enhanced Task Offloading Method in MEC-Enabled IoV...

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2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and Computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable Computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy Computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Zhao, Bohai Peng, Kai Leung, Victor C.M. Xia, Yunni Huaqiao University College of Engineering Quanzhou China Nanjing University State Key Lab. for Novel Software Technology Nanjing China Shenzhen University School of Computer Science and Software Engineering Shenzhen China The University of British Columbia Department of Electrical and Computer Engineering Vancouver Canada Chongqing University School of Computers Chongqing China

ISBN: (纸本)9798350346558

To facilitate the evolution from independent transportation means to vehicle-to-infrastructure communications, traditional vehicle-to-vehicle (V2V) technologies are growing to a more advanced and generalized paradigm, i.e., the Internet of Vehicles (IoV). This paradigm has stimulated ever-increasing calling for more capabilities and intelligence for vehicles to foster the potential of supporting a plethora of emerging applications and ubiquitous automotive network access. Combining caching-aided communication and edge computing has been expected to be an advantageous framework to cope with the surging requirements for timely data processing and storage from intelligent IoV applications. In light of the delay restriction and the heterogeneity of edge service nodes (ESNs), we study the service-enhanced problem in edge-enabled IoV networks by configuring proactive service caching. Specifically, based on task scale and relational restrictions, we design an adaptive non-linear caching probability mapping function and further propose a proactive service-enhanced task offloading method in edge-enabled IoV networks named SEOEV. Performance evaluation demonstrates that SEOEV efficiently reduces task processing overhead in comparison to other comparative computing migration approaches. © 2022 IEEE.

关键词： Multiobjective optimization

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Soft Gripping: Specifying for Trustworthiness

Soft Gripping: Specifying for Trustworthiness

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Dhaminda B. Abeywickrama Nguyen Hao Le Greg Chance Peter D. Winter Arianna Manzini Alix J. Partridge Jonathan Ives John Downer Graham Deacon Jonathan Rossiter Kerstin Eder Shane Windsor School of Computer Science University of Bristol UK Department of Computer Science The University of Manchester UK School of Engineering Mathematics and Technology University of Bristol UK School of Sociology Politics and International Studies University of Bristol UK Bristol Medical School (PHS). University of Bristol UK School of Electrical Electronic and Mechanical Engineering University of Bristol UK Robotics Research Team Ocado Technology UK School of Civil Aerospace and Design Engineering University of Bristol UK

Soft robotics is an emerging technology in which engineers create flexible devices for use in a variety of applications. In order to advance the wide adoption of soft robots, ensuring their trustworthiness is essential; if soft robots are not trusted, they will not be used to their full potential. In order to demonstrate trustworthiness, a specification needs to be formulated to define what is trustworthy. However, even for soft robotic grippers, which is one of the most mature areas in soft robotics, the soft robotics community has so far given very little attention to formulating specifications. In this work, we discuss the importance of developing specifications during development of soft robotic systems, and present an extensive example specification for a soft gripper for pick-and-place tasks for grocery items. The proposed specification covers both functional and non-functional requirements, such as reliability, safety, adaptability, predictability, ethics, and regulations. We also highlight the need to promote verifiability as a first-class objective in the design of a soft gripper.

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Intervention of AI and Social engineering in the Education Sector of Ethiopia 2

Intervention of AI and Social Engineering in the Education S...

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： Bishnoi, Malini Mittal Ramakrishnan, Swamynathan Joghee, Shanmugan Kumar, Anand Thilagavathi, N. School Of Haas Amity University Dubai Dubai United Arab Emirates Amity Business School Amity University Dubai Dubai United Arab Emirates School Of Business Skyline University College Sharjah Sharjah United Arab Emirates Amity University Dubai Deparmetnt Of Electrical And Electronics Engineering Dubai United Arab Emirates Government Arts And Science College Department Of Computer Science Tamilnadu Mettupalayam India

ISBN: (纸本)9798350394962

AI has the potential to convert both the educating and learning processes;its application within the zone of instruction has gathered critical consideration over the globe for social engineering. AI's infusion in Ethiopia's instructive framework is the central contention of this research work. Ethiopia's instructive setting gives an interesting set of challenges and possibilities to study AI and its integration in education. The reason of this enquiry is to study and analyze the potential benefits, downsides, and strategies for utilizing AI in Ethiopian instructive settings. This research work commences with a thorough literature survey of the applications of AI within the instruction segments around the world and in Ethiopia. A mixed methodology research approach was delpoyed to collect data through in-depth interviews, case studies, and field observations. Policymakers, instructors, educationalists and parents are few of the stakeholders who would be able to gain valuable insights from recommendations of this research and utilize to set-up an educational framework in Africa. © 2024 IEEE.

关键词： engineering research

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Yoga in Digital Age: A Hybrid Approach Using ML and computer Vision

Yoga in Digital Age: A Hybrid Approach Using ML and Computer...

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IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)

作者： Priya Govindarajan Achaiah K K Arjun S Pramod Abebe Tesfahun Department of Computer Science Amrita School Of Computing Amrita Vishwa Vidyapeetham School of Electrical & Computer Engineering Ethiopia Debre Markos Institute of Technology Debre Markos University Ethiopia

ISBN: (数字)9798350360059

ISBN: (纸本)9798350360066

In today's fast-paced world, stress and pressure affect people of all ages, both physically and mentally. Yoga has emerged as a highly sought-after solution due to its numerous benefits. In the present technology-dependent era of digital age, it's only natural that we turn to technology for assistance in their yoga journey. This is where the proposed article comes into play, serving as one's digital Yoga Guru. In this paper, seven classifiers, out of which six are Machine Learning classifiers namely Support Vector Machine, Naïve Bayes, Random Forest, K-Nearest Neighbor, Logistic Regression, and Ensembler are employed to classify the dataset. These classifiers exhibit a promising average accuracy exceeding 90%. Additionally, the proposed method incorporates a Deep Learning model, specifically the Multi-Perceptron Neural Network, which has been trained to predict outputs with an impressive accuracy of 92%. This Paper utilizes the power of MediaPipe, a cutting-edge technology that plays a pivotal role in this innovative approach to yoga. MediaPipe is capable of identifying individuals on the screen and provides 33 key-points, including critical markers like facial key-points, and main key-points of the body such as shoulders, elbows, knees, feet, wrists, and etc. These key points are essential for pose recognition, and assessing the correctness of yoga postures. What sets the proposed method apart is its real-time, live tracing feature, boasting an impressive accuracy rate of 99%. As one engages in yoga practice, this technology tracks their movements, and compares them to the ideal yoga postures. This immediate feedback ensures that one performs each pose correctly, promoting better results and minimizing the risk of injury. In essence, the proposed method bridges the gap between ancient yoga wisdom and modern technology, offering a digital Yoga Guru that guides one to achieve physical and mental well-being with precision and confidence.

关键词： Wrist Support vector machines Accuracy Tracking Neural networks Predictive models Nearest neighbor methods Real-time systems Stress Random forests

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A Multi-Stage Security Solution for Medical Color Images in Healthcare Applications

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computer Systems science & engineering 2023年第9期46卷 3599-3618页

作者： Walid El-Shafai Fatma Khallaf El-Sayed M.El-Rabaie Fathi E.Abd El-Samie Iman Almomani Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Engineering Faculty of EngineeringAhram Canadian UniversityGizaEgypt Computer Science Department King Abdullah II School of Information TechnologyThe University of JordanJordan11942Jordan

This paper presents a robust multi-stage security solution based on fusion,encryption,and watermarking processes to transmit color healthcare images,*** presented solution depends on the features of discrete cosine transform(DCT),lifting wavelet transform(LWT),and singular value decomposition(SVD).The primary objective of this proposed solution is to ensure robustness for the color medical watermarked images against transmission *** watermark embedding,the host color medical image is transformed into four sub-bands by employing three stages of *** resulting low-frequency sub-band is then transformed by employing three stages of DCT followed by SVD ***,a fusion process is used for combining different watermarks into a single watermark *** single fused image is then ciphered using Deoxyribose Nucleic Acid(DNA)encryption to strengthen the ***,the DNA-ciphered fused watermark is embedded in the host medical image by applying the suggested watermarking technique to obtain the watermarked *** main contribution of this work is embedding multiple watermarks to prevent identity *** the presence of different multimedia attacks,several simulation tests on different colormedical images have been *** results prove that the proposed security solution achieves a decent imperceptibility quality with high Peak Signal-to-Noise Ratio(PSNR)values and high correlation between the extracted and original watermark ***,the watermark image extraction process succeeds in achieving high efficiency in the presence of attacks compared with related works.

关键词： Medical images DNA encryption digital image watermarking fusion healthcare applications

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