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A Dynamic Pricing Method with LoRa Technique in Smart Parking systems Along with the Edge-Cloud Based Computing 1

A Dynamic Pricing Method with LoRa Technique in Smart Parkin...

1st International Conference on Innovative Sustainable Technologies for Energy, Mechatronics and Smart systems, ISTEMS 2024

作者： Singh, Baldev Kumar, Ritesh Neetha, S.S. Vivekananda Global University Department of Computer Science and Engineering Jaipur India Maharishi School of Engineeing and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350384246

The increasing quantity of automobiles on the road these days has resulted in chronic traffic jams and difficulties with urban traffic control. Increased traffic bottlenecks are mostly caused by unlicensed and unregulated parking. The management of present parking spots is ineffective, and traffic-related problems are made worse by a lack adequate real-time advice and general ignorance. The constrained growth of highways and other transportation and related infrastructure highlights the urgent need for a clever, flexible, and effective parking solution. We suggest a complex multi-layer design for intelligent parking facilities to overcome these issues. This system uses cutting-edge extended, low-power wireless communications, powerful edge and cloud computing processing capacity, and sensor nodes with different parameters for parking spots. By dynamically managing large areas and providing drivers with real-time information on parking spaces and related services via continuous vehicle tracking, our proposed system seeks to transform parking management. We also provide a dynamic pricing strategy that aims to maximise parking authority income while guaranteeing drivers have the best possible availability of parking spaces. By addressing the problems caused by careless parking and improving general traffic control, this all-encompassing strategy aims to improve the effectiveness and smooth operation of the city's transport network. © 2024 IEEE.

关键词： Traffic congestion

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A Collaborative Approach for Secured Routing in Mobile Ad-Hoc Network

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Intelligent Automation & Soft Computing 2023年第2期35卷 1337-1351页

作者： W.Gracy Theresa A.Gayathri P.Rama Department of Computer Science and Engineering Panimalar Institute of TechnologyChennai600123Tamil NaduIndia Department of Information Technology Vellore Institute of TechnologyVellore632014Tamil NaduIndia Department of Computer Science and Engineering Loyola Institute of TechnologyChennai600123Tamil NaduIndia

Mobile computing is the most powerful application for network com-munication and connectivity,given recent breakthroughs in theﬁeld of wireless networks or Mobile Ad-hoc networks(MANETs).There are several obstacles that effective networks confront and the networks must be able to transport data from one system to another with adequate *** most applications,a frame-work must ensure that the retrieved data reﬂects the transmitted *** driv-ing to other nodes,if the frame between the two nodes is deformed in the data-link layer,it must be *** link-layer protocols immediately disregard the frame and enable the high-layer protocols to transmit it *** other words,because of asset information must be secured from threats,information is a valu-able *** MANETs,some applications necessitate the use of a network method for detecting and blocking these *** a secure intrusion detection system in the network,which provides security to the nodes and route paths in the network,is a major difﬁculty in *** on the network can jeopardize security issues discovered by the intrusion detection system engine,which are then blocked by the network’s intrusion prevention *** bringing the Secure Intrusion Detection system(S-IDS)into the network,a new technique for implementing security goals and preventing attacks will be *** Secure Energy Routing(SER)protocol for MANETs is introduced in this *** protocol addresses the issue of network security by detecting and preventing attacks in the *** data transmission in the MANET is forwarded using Elliptical Curve Cryptography(ECC)with an objective to improve the level of *** Simulator–2 is used to simulate the network and experiments are compared with existing methods.

关键词： Mobile ad-hoc network(MANET) intrusion detection system secure energy routing(SER) elliptical curve cryptography(ECC) security

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Spatiotemporal crowds features extraction of infrared images using neural network

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Journal of Ambient Intelligence and Humanized Computing 2024年第4期15卷 2543-2556页

作者： Al-Oraiqat, Anas M. Drieiev, Oleksandr Drieieva, Hanna Meleshko, Yelyzaveta AlRawashdeh, Hazim Al-Oraiqat, Karim A. Hasan, Yassin M. Y. Maricar, Noor Khan, Sheroz Department of Computer Science College of Engineering and Information Technology Onaizah Colleges Qassim Saudi Arabia Department of Cybersecurity and Software Central Ukrainian National Technical University Kropyvnytskyi Ukraine Department of Artificial Intelligence Faculty of Information Technology Zarqa University Zarqa Jordan Department of Electrical Engineering College of Engineering and Information Technology Onaizah Colleges Qassim Saudi Arabia

Crowds can lead up to severe disasterous consequences resulting in fatalities. Videos obtained through public cameras or captured by drones flying overhead can be processed with artificial intelligence-based crowd analysis systems. Being a hot area of research over the past few years, the goal is not only to identify the presence of crowds but also to predict the probability of crowd-formation in order to issue timely warnings and preventive measures. Such systems will significantly reduce the probablity of the potential disasters. Developing effective systems is a challenging task, especially due to factors such as naturally occuring diverse conditions, variations in people or background pixel areas, noise, behaviors of individuals, relative amounts/distributions/directions of crowd movements, and crowd building reasons. This paper proposes an infrared video processing system based on U-Net convolutional neural network for crowd monitoring in infrared video frames to help estimate the people crowd with normal or abnormal trends. The proposed U-Net architecture aims to efficiently extract crowd features, achieve sufficient people marking-up accuracy, competitively with optimal network configurations in terms of the depth and number of filters to consequently minimise the number of coefficients. For further faster processing, hardware resources/implementation area savings, and lower power, the optimized network coefficients measured are represented in Canonic-Signed Digit with minimal number of nonzero (± 1) digits, minimizing the number of underlying shift-add/subtract operations of all multipliers. The achieved significantly reduced computational cost makes the proposed U-Net effectively suitable for resource-constrained and low power applications. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Convolutional neural networks

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Plagiarism Detection and Similarity Checking Program using Machine Learning and String Matching Algorithm 9

Plagiarism Detection and Similarity Checking Program using M...

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9th International Conference on Communication and Electronics systems, ICCES 2024

作者： Bhavana, Munugapati Rao, Koppula Srinivas Koduru, Gagan Kumar Vatsal, K.Vijay Krupa Parvathi, S. Sravani, Mogiligidda Mlr Institute of Technology Affiliated to Jntu Dept. of Computer Science & Information Technology Hyderabad India Mlr Institute of Technology Affiliated to Jntu Department of Computer Science & Engineering Hyderabad India Mlr Institute of Technology Hyderabad India Malla Reddy University Department of Computer Science & Engineering Hyderabad India Mlr Institute of Technology Dept.of Computer Science & Information Technology Hyderabad India Mvsr Engineering College Department of Information Technology India

ISBN: (纸本)9798350377972

This research proposes a system for detecting plagiarism in academic submissions. The system utilizes advanced text comparison algorithms to identify instances of plagiarism, ensuring academic integrity and promoting a culture of originality among students. By providing educators with a tool to efficiently detect plagiarism, this system aims to streamline the evaluation process and enhance the overall learning experience for students. This system has the potential to significantly reduce plagiarism incidents and foster a more ethical and productive academic environment. © 2024 IEEE.

关键词： Contrastive Learning

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Analyzing the Role of Time Series Analysis in Early Detection of Merkel Cell Carcinoma

Analyzing the Role of Time Series Analysis in Early Detectio...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Singh, Akhilendra Pratap Seth, Jyoti Nachappa, M.N. Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

this paper investigates the potential of using time collection evaluation to detect Merkel cellular Carcinoma (MCC) early. MCC is a competitive shape of pores and skin. Early detection is critical to the growing survival rate. Time collection evaluation is an adequate records mining technique used to degree diffused styles in facts. This look aims to discover the usage of time series analysis to stumble on early signs and symptoms of MCC and evaluate the results to present strategies that include Random forest and decision Tree classifiers. First, fixed healthcare information collected from patients with MCC became amassed, and the related time series was created. Next, different versions of time collection models consisting of ARIMA (car-Regressive included transferring common) and SARIMA (Seasonal ARIMA) become used to measure the extent of temporal trends inside the records. Subsequently, the models were compared in opposition to the present system learning classifiers and assessed in phrases of accuracy, precision, take into account, and F1-score. © 2024 IEEE.

关键词： adjustments discovering Regressive sickness stumble

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The Smart Predictive Analysis of Stock Market Performance using Restricted Boltzmann Machines

The Smart Predictive Analysis of Stock Market Performance us...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Devrani, Rekha Mahajan, Prerna Kumar, Dinesh Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350383348

Restricted Boltzmann Machines (RBMs) are a system getting-to-know algorithm that may be used to predict the overall performance of inventory markets. This painting aims to analyze the overall performance of inventory markets via growing an RBM version. The RBM version will benefit from the temporal correlation of stock marketplace information and put it to use to make more correct predictions. The version is educated using historical facts, and the model parameters are adjusted to optimize the prediction accuracy. This painting demonstrates the use of an RBM model for predicting the returns of stocks and analyzing the stock marketplace's overall performance. The outcomes from these paintings show that the proposed RBM version effectively predicts the overall performance of inventory markets and provides an alternative version for forecasting stock markets. Confined Boltzmann Machines (RBMs) are a form of synthetic neural network which can be used for unsupervised studying tasks consisting of dimensionality discount, function mastering, and collaborative filtering. RBMs have been correctly used in numerous applications, including sentiment evaluation, natural language processing, and computer imagination and prescient. In current years, there was a surge of hobby in using RBMs to expect inventory market overall performance. On the way to expand a predictive model, RBMs extract separable functions from the uncooked market data, which can be pattern inputs. The extracted capabilities are used because of the input to a supervised mastering version to predict stock marketplace overall performance based on previous statistics. A vital advantage of using RBMs for feature extraction is that they can identify latent components of the facts, which would, in any other case, remain hidden from the consumer. By combining RBMs with supervised learning, it is viable to develop models which can be more powerful than those using either technique for my part. Because of this reality,

关键词： algorithms correlations historical inventory stock

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BHJO: A Novel Hybrid Metaheuristic Algorithm Combining the Beluga Whale, Honey Badger, and Jellyfish Search Optimizers for Solving Engineering Design Problems

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computer Modeling in Engineering & sciences 2024年第10期141卷 219-265页

作者： Farouq Zitouni Saad Harous Abdulaziz S.Almazyad Ali Wagdy Mohamed Guojiang Xiong Fatima Zohra Khechiba Khadidja Â Kherchouche Department of Computer Science and Information Technology Kasdi Merbah UniversityP.O.Box 30000OuarglaAlgeria Department of Computer Science College of Computing and InformaticsUniversity of SharjahP.O.Box 27272SharjahUnited Arab Emirates Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China

Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization *** approach aims to leverage the strengths of multiple algorithms,enhancing solution quality,convergence speed,and robustness,thereby offering a more versatile and efficient means of solving intricate real-world optimization *** this paper,we introduce a hybrid algorithm that amalgamates three distinct metaheuristics:the Beluga Whale Optimization(BWO),the Honey Badger Algorithm(HBA),and the Jellyfish Search(JS)*** proposed hybrid algorithm will be referred to as *** this fusion,the BHJO algorithm aims to leverage the strengths of each *** this hybridization,we thoroughly examined the exploration and exploitation capabilities of the BWO,HBA,and JS metaheuristics,as well as their ability to strike a balance between exploration and *** meticulous analysis allowed us to identify the pros and cons of each algorithm,enabling us to combine them in a novel hybrid approach that capitalizes on their respective strengths for enhanced optimization *** addition,the BHJO algorithm incorporates Opposition-Based Learning(OBL)to harness the advantages offered by this technique,leveraging its diverse exploration,accelerated convergence,and improved solution quality to enhance the overall performance and effectiveness of the hybrid ***,the performance of the BHJO algorithm was evaluated across a range of both unconstrained and constrained optimization problems,providing a comprehensive assessment of its efficacy and applicability in diverse problem ***,the BHJO algorithm was subjected to a comparative analysis with several renowned algorithms,where mean and standard deviation values were utilized as evaluation *** rigorous comparison aimed to assess the performance of the BHJOalgorithmabout its counterparts,shedd

关键词： Global optimization hybridization of metaheuristics beluga whale optimization honey badger algorithm jellyfish search optimizer chaotic maps opposition-based learning

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Maximizing the Accuracy of Time Series Analysis for the Early Detection of Rhabdomyosarcomas

Maximizing the Accuracy of Time Series Analysis for the Earl...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Shree, Ritu Prabhu, A. Gautam, Anupam Kumar Vivekananda Global University Department of Computer Science & Application Jaipur India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350383348

Rhabdomyosarcomas are a rare malignant tender tissue tumor that generally gives in younger children and teenagers. Early prognosis and remedy are essential for successful outcomes. Time collection evaluation is a valuable tool for recognizing styles and trends in medical facts, mainly for rare situations, which include Rhabdomyosarcomas. It has consequently been increasingly employed to detect early signs and symptoms of the ailment. On this look, we are conscious of investigating and optimizing techniques for time collection analysis. It is an excellent way to enhance its application and accuracy in identifying early symptoms and signs of rhabdomyosarcoma. We examine present strategies and suggest improvement techniques, along with function extraction and system mastering techniques. We further inspect the effectiveness of our strategies by conducting experiments on a dataset installed from scientific facts and literature of rhabdomyosarcoma instances. Those experiments show promising effects, indicating that our proposed strategies can considerably increase the accuracy and sensitivity of time series evaluation for the early detection of rhabdomyosarcoma and cause higher prognoses for affected sufferers. The focal point of this study is to maximize the accuracy of time series analysis for the early detection of rhabdomyosarcoma. Time collection analysis includes: • The gathering of temporal information from multiple sources. • The assessment of these records. • The interpretation of correlations between the facts points. This study aims to utilize these techniques to discover diffused adjustments in affected person information so that you can perceive the onset of the disorder in advance than would be possible with traditional techniques. The examination will expand algorithms to systematically and accurately procedure the temporal statistics and discover adjustments indicative of Rhabdomyosarcomas. In addition, the look will rent gadget learning to boost the dete

关键词： malignant recognizing Rhabdomyosarcomas strategies Time

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Performance Analysis of 3D Rendering Method on Web-Based Augmented Reality Application Using WebGL and OpenGL Shading Language 23

Performance Analysis of 3D Rendering Method on Web-Based Aug...

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8th International Conference on Sustainable information Engineering and technology, SIET 2023

作者： Hamzaturrazak, Multohadi Jonemaro, Eriq Muhammad Adams Pinandito, Aryo Informatics Engineering Department Universitas Brawijaya Faculty of Computer Science Indonesia Information System Department Universitas Brawijaya Faculty of Computer Science Indonesia

ISBN: (纸本)9798400708503

In recent years, web programming has increased to the extent where it is capable of rendering 3D objects on the web. Its rendering performance varied depending on where it ran and what library was used to render the objects. This study aims to investigate the rendering performance of several 3D renderer libraries that render 3D objects in an augmented reality application. WebGL is one of the APIs that uses the Javascript programming language to render 3D objects in web applications. To create augmented reality on the web, a JavaScript library called *** is needed, which allows developers to create augmented reality on the web without the need to use additional plugins. *** supports various types of augmented reality, i.e., bookmarks, images, and location-based types. It also allows developers to incorporate visual and audio effects into augmented reality. This study aims to investigate the rendering performance of WebGL raw shaders and GLSL shaders in an HTML-based augmented reality application. The results suggested that both WebGL and GLSL could render low-poly and medium-poly 3D objects well. However, according to the test, WebGL performance drops significantly when rendering high-polygon 3D objects. Nonetheless, the GLSL library could render the same high-poly 3D objects at a similar level with native library rendering performance. Thus, suggest GLSL shaders as the recommended library to render 3D objects on the web. © 2023 ACM.

关键词： Augmented reality

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Prototype Proposal of an 18 kW Non-Isolated Bidirectional Converter for Battery Energy Storage system 22

Prototype Proposal of an 18 kW Non-Isolated Bidirectional Co...

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22nd International Symposium on Power Electronics, Ee 2023

作者： Brandis, Andrej Knol, Kristian Pelin, Denis Topic, Danijel Computer Science and Information Technology Osijek Faculty of Electricity Engineering Department of Electromechanical Engineering Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Power Engineering Osijek Croatia

ISBN: (纸本)9798350343175

In this paper, a brief overview of converter topologies used in stationary battery energy storage systems is given. A simulation model of converter was developed in MATLAB Simulink. A simulation is conducted to provide a preliminary understanding of the converter's bidirectional nature. The results indicate that the state of charge (SOC) increases during battery charging and decreases during discharging. The topology of non-isolated two-stage bidirectional converter is presented for proposed real-world prototype, including the high-level electrical schematic and mechanical layout. An 18-kW prototype converter for stationary battery energy storage systems was developed and presented. The converter housing with all installed ancillary components for proper operation is also described. At the time of writing this paper, the actual converter is still in the development phase. © 2023 IEEE.

关键词： Charging (batteries)

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