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sustainable Computing and Data Communication systems (iCsCDs), international Conference on

作者： R. Jayanthi s. sundararajan tanweer Alam Neha Garg Rupesh Roshan singh M. Udhayamoorthi Department of Commerce Vidhya Sagar Women’s College University of Madras Chennai Tamilnadu SNS College of Technology Coimbatore-35 Tamilnadu Department of Computer Science Faculty of Computer and Information Systems Islamic University of Madinah Madinah Saudi Arabia Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Block-14 Mittal School of Business Lovely Professional University Jalandhar-Delhi G.T. Road Phagwara Punjab INDIA

For all parties involved in a logistics system, precise data and smart business operations are essential. However, a hurdle to implementation could be posed by a lack of shared trust. supply chains experience difficulties as a result of a lack of confidence in data sharing, according to several studies. the degree to which each stakeholder has faith in the data they acquire can have a significant impact on management choices. the processing of bitcoin transactions has made extensive use of blockchain technology. it has recently been shown to be successful in building confidence within the Network of *** building trust between entities who would otherwise have been distrustful of each other’s data, blockchain technology permits more seamless and secure data sharing. However, businesses may encounter severe delays and the requirement for significant processing resources if the network is not iot-optimized. Additionally, traditional consensus algorithms still have severe limitations on the nodes’ ability to agree. trust is one of the major concerns in blockchain technology and stands as a severe challenge presently. Confidentiality, privacy, data integrity, and scalability analysis can be identified as the main challenges presently.

关键词： Protocols scalability Buildings supply chains standards organizations Blockchains safety

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Deep Learning Model to Predict Pneumonia Disease based on Observed Patterns in Lung X-rays 4

Deep Learning Model to Predict Pneumonia Disease based on Ob...

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4th international Conference on Electronics, Communication and Aerospace technology, iCECA 2020

作者： singh, Utkarsh totla, Aditi Kumar, Dr. Prakash R. V. College of Engineering Dept. of Computer Science and Engineering Bengaluru Karnataka India B. I. T. Sindri Dhanbad Dept. of Production Engineering Jharkhand India

ISBN: (纸本)9781728163871

Due to the recent technological advancements, healthcare industry is also undergoing some major changes. the volume of medical data continues to increase at a staggering rate and artificial intelligence is poised to be the engine that drives improvements across the care continuum. Pneumonia is a serious disease, which can range from mild to life-threatening as it causes inflammation and fluid accumulation in the lungs and making it hard to breathe. it remains as the most serious for infants, children, and people older than 65 years. it is also considered to be a potential complication of the COViD-19 disease. Chest X-ray is an important pneumonia diagnosis worldwide. to help detect patients, who require intense medical care, artificial intelligence can be used to analyse lung imaging as a part of the clinical research study. the primary goal is to reduce the complex task of understanding scans through experts and provides easy prediction by developing a model that can predict the possibility of the disease in a patient through their lung X-ray images. © 2020 iEEE.

关键词： Convolutional neural networks

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Constructive Barrier Feedback for Collision Avoidance in Leader-Follower Formation Control

Constructive Barrier Feedback for Collision Avoidance in Lea...

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iEEE Conference on Decision and Control

作者： Zhiqi tang Rita Cunha tarek Hamel Carlos silvestre Institute for Systems and Robotics Instituto Superior Técnico Universidade de Lisboa Portugal I3S-CNRS Université Côte d'Azur and Institut Universitaire de France France Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macao China

this paper proposes a novel constructive barrier feedback for reactive collision avoidance between two agents. it incorporates this feature in a formation tracking control strategy for a group of 2nd-order dynamic robots defined in three-dimensional space. Using only relative measurements between neighboring agents, we propose an elegant decentralized controller as the sum of a nominal tracking controller and the constructive barrier feedback for leader-follower formations under a directed single-spanning tree graph topology. the key ingredient is the use of divergent flow as a dissipative term, which slows down the relative velocity in the direction of the neighboring robots without compromising the nominal controller's performance. Compared to traditional barrier function-based optimization controllers, the proposed constructive barrier feedback avoids feasibility issues and results in more computationally efficient control algorithms with systematic equilibrium analysis. simulations are provided to validate the effectiveness of the proposed control method.

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A systematic study on the role of sentiWordNet in opinion mining

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Frontiers of computer science 2021年第4期15卷 165-183页

作者： Mujtaba HUsNAiN Malik Muhammad saad MissEN Nadeem AKHtAR Mickael COUstAtY shahzad MUMtAZ V.B.surya PRAsAtH Department of IT Faculty of ComputingThe Islamia University of BahawalpurBahawalpur 63100Pakistan Laboratoire Informatique Image et Interaction(L3i)Facultés des Sciences et TechnologiesUniversity of La RochelleLa Rochelle 17000France Division of Biomedical Informatics Cincinnati Children’s Hospital Medical CenterCincinnati 45229USA Department of Pediatrics University of Cincinnati College of MedicineCincinnati 45229USA Department of Biomedical Informatics College of MedicineUniversity of CincinnatiCincinnati 45267USA Department of Electrical Engineering and Computer Science University of CincinnatiCincinnati 45221USA

sentiment lexicons(sL)(aka lexical resources)are the repositories of one or several dictionaries that consist of known and precompiled sentiment *** lexicons play an important role in performing several different opinion mining *** efficacy of the lexicon-based approaches in performing opinion mining(OM)tasks solely depends on selecting an appropriate opinion lexicon to analyze the ***,one has to explore the available sentiment lexicons and then select the most suitable *** available resources,sentiWordNet(sWN)is the most widely used lexicon to perform tasks related to opinion *** sWN,each synset of WordNet is being assigned the three sentiment numerical scores;positive,negative and objective that are calculated using by a set of *** this paper,a detailed and comprehensive review of the work related to opinion mining using senti-WordNet is provided in a very distinctive *** survey will be useful for the researchers contributing to the field of opinion *** features make our contribution worthwhile and unique among the reviews of similar kind:(i)our review classifies the existing literature with respect to opinion mining tasks and subtasks(ii)it covers a very different outlook of the opinion mining field by providing in-depth discussions of the existing works at different granularity levels(word,sentences,document,aspect,clause,and concept levels)(iii)this state-ofart review covers each article in the following dimensions:the designated task performed,granularity level of the task completed,results obtained,and feature dimensions,and(iv)lastly it concludes the summary of the related articles according to the granularity levels,publishing years,related tasks(or subtasks),and types of classifiers *** the end,major challenges and tasks related to lexicon-based approaches towards opinion mining are also discussed.

关键词： opinion mining lexical based resources senti-WordNet opinion strength

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View-based and visual-attention-based background modeling for detecting frequently and infrequently moving objects for video summarization 1

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international Conference on Communication systems and Networks, ComNet 2019

作者： Minola Davids, D. seldev Christopher, C. Department of Electronics and Communication Engineering C.S.I Institute of Technology Kanyakumari NagercoilTamilNadu India Department of Computer Science and Engineering St.Xavier’s Catholic College of Engineering Chunkankadai Kanyakumari NagercoilTamilNadu India

ISBN: (数字)9789811539923

ISBN: (纸本)9789811539916

the real-time face detection (FD) algorithm is proposed to find faces in the images as well as videos. Besides face regions, this algorithm also finds the exact localities of the face parts like lips and eyes. initially, skin pixels are extracted centered on the rules of simple quadratic polynomial model. By introducing small modifications, this polynomial model (PM) could be applied for extracting the lips. the merits of adopting these two identical PMs are two-fold. Firstly, computation time is saved. secondly, these extraction processes could be executed at the same time on one scan of the video or image frame. subsequent to skin and lips, the eyes are extorted. Later, the algorithm eliminates the falsely extorted parts by validating with rules taken as of the spatial and geometrical relationships (sGR) of face parts. At last, the exact face regions are ascertained accordingly. As per the experiential outcomes, the proposed algorithm evinces preeminent task in respect of accuracy and speed for FD with huge differences in color, size, shape, expressions, and angles. © springer Nature singapore Pte Ltd 2020.

关键词： Face recognition

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segmentation of Arecanut Bunches: A Comparative study of Different Color Models 1

Segmentation of Arecanut Bunches: A Comparative Study of Dif...

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1st iEEE Mysore sub section international Conference, MysuruCon 2021

作者： Dhanesha, R. Umesha, D.K. shrinivasa Naika, C.L. Girish, G.N. Davangere University Dept. of Studies in Computer Science Davanagere Karnataka India Government Women's Polytechnic Shiralakoppa Dept. of CS&E Shivamogga Karnataka India U. B. D. T. College of Engineering Dept. of Studies in CS&E Davanagere Karnataka India Indian Institute of Information Technology Computer Science and Engineering Group Sri City Chittoor India

ISBN: (纸本)9780738146621

Arecanut is one of the important commercial crop of Agriculture sector. Agriculture sector plays important role towards the economic development of india. the market price of arecanut is determined by it's maturity level of the ripeness. Farmers often incur loss in profit due to the lack of expertise in judging the ripeness maturity level of the arecanut bunches before the harvest. in the recent years, image processing and computer vision based precision agriculture techniques has helped the farmers in identifying the ripeness quality of the crops. so, accurate segmentation of the arecanut bunches plays vital role in the automated identification of the arecanut ripeness maturity level. in this proposed work YUV, YCbCr, YCgCr, YPbPr and HsV color models are used to segment arecanut bunches. Dataset with 1017 images of arecanut bunch are used to conduct experiment and segmentation result of the each color model is evaluated using different segmentation performance metrics. Results of experiment clarifies, segmentation of arecanut bunches were efficient using YCgCr and HsV color models. © 2021 iEEE.

关键词： computer vision

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CNNs in Crop Care: A Comparative Analysis of tomato Disease Detection Models

CNNs in Crop Care: A Comparative Analysis of Tomato Disease ...

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Cyber Resilience (iCCR), international Conference on

作者： Ali M Ali shadi Nashwan Ahmad Al-Qerem Amjad Aldweesh Mohammad Alauthman Zenab Elgamal Ammar Almomani Communications and Computer Engineering Department Faculty of Engineering AlAhliyya Amman University Amman Jordan Cybersecurity Department Faculty of Information Technology Middle East University (MEU) Amman Jordan Computer Science Department Faculty of Information Technology Zarqa University Zarqa Jordan College of Computing and IT Shaqra University Shaqra Saudi Arabia Department of Information Security Faculty of Information Technology University of Petra Amman Jordan School of Computing Skyline University College University City of Sharjah Sharjah United Arab Emirates School of Computing Skyline University College Sharjah UAE I.T. department AlHuson University College AlBalqa Applied University Irbid Jordan

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

timely and accurate detection of plant diseases is critical for sustainable crop production. this paper presents a comparative analysis of convolutional neural network (CNN) models for automated tomato leaf disease detection, including VGG16, VGG19, AlexNet and Google Net. A dataset of tomato leaf images with multiple disease types was utilized to train and test the performance of each CNN architecture. Our results demonstrate that the VGG16 model achieved the highest accuracy of 99.38% in classifying tomato leaf diseases. Compared to AlexNet and VGG19 models which obtained 98.67% and 99.29% accuracy respectively, the superior performance of VGG16 highlights its suitability for deploying robust tomato disease detection systems to enable prompt disease control interventions. Our work provides valuable insights on harnessing deep learning for agricultural disease surveillance, allowing farmers and agronomists to identify crop infections early and implement timely management practices to reduce yield losses.

关键词： Deep learning Plant diseases Analytical models Visualization surveillance Crops training data

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solar PV array powered on board electric vehicle charging with charging current protection scheme 9

Solar PV array powered on board electric vehicle charging wi...

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9th iEEE international Conference on Power Electronics, Drives and Energy systems, PEDEs 2020

作者： singh, Harshit Kumar Kumar, Nishant Dr. A.P.J Technical University Uttar Pradesh I. T. S Engineering College Department of Electrical and Electronics Engineering Greater Noida201308 India Department of Electrical and Computer Engineering Singapore117583 Singapore

ISBN: (纸本)9781728156729

in this paper, a three-sensors based Maximum Power Point tracking (MPPt) scheme with charging current protection facility has been proposed for solar PV powered ON board Electric Vehicles (EV) applications. therefore, this scheme is capable of charging the different types of EVs with current within the rated limit of the EV. solar PV array can be directly attached for charging the EV without any external required circuitry. therefore, any solar panel array can be attached to charge the EV safely. the Above strategy is simulated and tested in MAt LAB simulink under variable irradiance of solar energy, which optimal sOC, charging current, and voltage shows satisfactory performance. © 2020 iEEE.

关键词： Electric vehicles

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Only-Metal Ultra-small Circular slot Antenna for 3U Cubesats 13

Only-Metal Ultra-Small Circular Slot Antenna for 3U CubeSats

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13th international Conference on Computing Communication and Networking technologies, iCCCNt 2022

作者： Omari, Fouad Hussain, Niamat Benhmimou, Boutaina Gupta, Nancy Laamara, Rachid Ahl Rahim, Mohamad Kamal A Guerrero, Josep M. Kogut, Aleksandr Arpanaei, Farhad Kuzmichev, igor Annino, Giuseppe Arora, sandeep Kumar Alibakhshikenari, Mohammad Abdulkarim, Yadgar ibrahim El Bakkali, Mohamed Faculty of Sciences of Rabat Mohammed 5 University of Rabat Rabat Morocco Department of Smart Device Engineering Sejong University Seoul Korea Republic of ECE LKCE I.K.G. Punjab Technical University Jalandhar India Medical Physics Department College of Medicals & Applied Science Charmo University Sulaimania Chamchamal46023 Iraq 12 Ac. Proskura st. Kharkiv61085 Ukraine Department of Telematic Engineering Universidad Carlos III de Madrid Madrid Leganés28911 Spain Istituto per i Processi Chimico-Fisici IPCF-CNR via G. Moruzzi 1 Pisa56124 Italy Lovely Professional University Punjab Phagwara India Department of Signal Theory and Communications Universidad Carlos III de Madrid Madrid Leganés28911 Spain School of Computer Science and Engineering Central South University Changsha410075 China

ISBN: (数字)9781665452625

ISBN: (纸本)9781665452625

in this research work, an only metal small antenna is constructed for 3U Cubesats. the proposed antenna structure presents very small size and ultra-lightweight with high peak gain for Cubesat communications. the proposed small antenna is configured and optimized at Ku-Band using ANsYs HFss and Quasi Newtonian Method. in addition to that, this study introduces the use of a 3U Cubesat top face as reflector for increasing the antenna gain and so targeted satellite orbits using this antenna configuration. the achieved results show that this small size metallic antenna configuration presents good impedance matching, ultra-wide band of 2.78 GHz (-10 dB BW of almost 93%) and a peak gain of about 8.4 dBi at Ku-Band (13.4 GHz). these performances make proposed metallic slot antenna very suitable for uplink and downlink Cubesat transmissions at Ku-band. © 2022 iEEE.

关键词： Orbits

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Versatile tape-drive target for high-repetition-rate laser-driven proton acceleration

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High Power Laser science and engineering 2023年第4期11卷 59-69页

作者： N.Xu M.J.V.streeter O.C.Ettlinger H.Ahmed s.Astbury M.Borghesi N.Bourgeois C.B.Curry s.J.D.Dann N.P.Dover t.Dzelzainis V.istokskaia M.Gauthier L.Giuffrida G.D.Glenn s.H.Glenzer R.J.Gray J.s.Green G.s.Hicks C.Hyland M.King B.Loughran D.Margarone O.McCusker P.McKenna C.Parisuaña P.Parsons C.spindloe D.R.symes F.treffert C.A.J.Palmer Z.Najmudin John Adams Institute for Accelerator Science Blackett LaboratoryImperial College LondonLondonUK School of Maths and Physics Queen’s University BelfastBelfastUK Central Laser Facility STFC Rutherford Appleton LaboratoryDidcotUK SLAC National Accelerator Laboratory Menlo ParkUSA ELI Beamlines Centre Institute of PhysicsCASDolni BrezanyCzech Republic Faculty of Nuclear Sciences and Physical Engineering Czech Technical University in PraguePragueCzech Republic Department of Physics SUPAUniversity of StrathclydeGlasgowUK Department of Mechanical Engineering Stanford UniversityStanfordUSA Department of Applied Physics Stanford UniversityStanfordUSA Department of Electrical and Computer Engineering University of AlbertaEdmontonCanada Institut für Kernphysik Technische Universität DarmstadtDarmstadtGermany

We present the development and characterization of a high-stability,multi-material,multi-thickness tape-drive target for laser-driven acceleration at repetition rates of up to 100 *** tape surface position was measured to be stable on the sub-micrometre scale,compatible with the high-numerical aperture focusing geometries required to achieve relativistic intensity interactions with the pulse energy available in current multi-Hz and near-future higher repetition-rate lasers(>kHz).Long-term drift was characterized at 100 Hz demonstrating suitability for operation over extended *** target was continuously operated at up to 5 Hz in a recent experiment for 70,000 shots without intervention by the experimental team,with the exception of tape replacement,producing the largest data-set of relativistically intense laser–solid foil measurements to *** tape drive provides robust targetry for the generation and study of high-repetitionrate ion beams using next-generation high-power laser systems,also enabling wider applications of laser-driven proton sources.

关键词： high-repetition-rate laser target laser-plasma acceleration proton generation tape-drive target

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