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5th IEEE International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2024

作者： Kaifas, Theodoros N. F. Democritus University of Thrace Dept. of Electrical and Computer Engineering Xanthi Greece

ISBN: (纸本)9798350352863

The work at hand provides a comprehensive study of Electromagnetic Power Harvesting via Metamaterial type antennas on the context of the Characteristic Mode Theory. Super-directive, parasitic arrays of electrically small but resonant element radiators - particles are studied, designed and evaluated. The presented designs provide more antenna-gain than conventional ones by invoicing and practically matching the theoretical maximum bounds of super-directivity boosting the rectenna system to its absolute limits, as far as the antenna part is concerned. Furthermore, those arrays apart from their own merit they exhibit the characteristic that can be arranged in large host surfaces to scale for even more increased performance. In the current work we will show that the analysis of harvesting particles via Characteristic Mode Theory can provide in-dept. understanding of the physics involved and assist on performance improvement strategies during relative design circles. © 2024 IEEE.

关键词： characteristic mode theory electromagnetic power harvesting super-directivity

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TurfIt: An Instant Turf Booking Application

TurfIt: An Instant Turf Booking Application

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2025 IEEE International Conference on Computational, Communication and Information technology, ICCCIT 2025

作者： Rajeswari, A.M. Tamilselvan, V. Abishek, M.R.P. Dept. of Computer Science and Engineering Velammal College of Engineering and Technology Madurai India

ISBN: (纸本)9798331512965

As sports grow in popularity need for effective online turf booking applications has also increased. Although some existing applications are faced with numerous challenges such as;restrictions on access, ineffectiveness in scheduling, and over-bookings, leading to frustrations and operational problems. This paper focuses on those problems by the presentation of an online turf booking application to streamline the booking process. The solution offers real-time updates, automatic payment, and safe transactions based on QR code. The more user-friendly the application is, the more efficient it will be. Firebase would be used for real-time data synchronization and the responsiveness of React interface ensures the smooth and conflict-free bookings. This solution would lead to increasing customer satisfaction as well as increasing the booking rates and effective utilization of sports facilities. © 2025 IEEE.

关键词： Customer satisfaction

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Disease Detection And Severity Prediction Of Pomegranate Fruit 15

Disease Detection And Severity Prediction Of Pomegranate Fru...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Paul, Poulin Manishankar, S. Satheesh Kumar, R. Sahrdaya College of Engineering and Technology Dept. of Computer Science and Engineering Kerala Thrissur India Jawaharlal College of Engineering and Technology Dept. of Computer Science and Engineering Kerala Palakkad India

ISBN: (纸本)9798350370249

This paper presents an integrated framework for the comprehensive analysis of diseases affecting pomegranate fruit. The suggested system, which makes use of deep learning techniques, includes semantic segmentation for diseased region localization, multiclass illness classification, and image processing-based severity assessment. Initially, four common diseases - Alternaria, Anthracnose, Bacterial Blight, and Cer-cospora - are successfully identified through the use of a Convolutional Neural Network (CNN) for multiclass classification. Then, annotated photos are used as training data for Semantic Segmentation, which uses the UNet architecture to identify the unhealthy spots within the fruit. The area and percentage of the segmented region are determined, and thresholds for high, medium, and low severity levels are then defined. The segmentation results are then used as inputs for severity estimate. Early identification and intervention tactics are made easier by the severity level prediction, which is based on the proportion of the segmented region. In order to improve pomegranate fruit management methods, the suggested framework provides a thorough method of disease analysis by combining categorization, semantic segmentation, and severity prediction. © 2024 IEEE.

关键词： Annotation Convolutional Neural Networks Deep learning Semantic segmentation Unet

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Scraping Data from Google Maps: Comparisons and Experimentations 15th

Scraping Data from Google Maps: Comparisons and Experimentat...

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15th International Conference on Intelligent Computing and Networking, IC-ICN 2024

作者： Thakur, Shivam Jha, Rajan Dalawat, Monika Jha, Prashant Khandare, Anand Dept. of Computer Engineering Thakur College of Engineering and Technology Autonomus Mumbai India

ISBN: (纸本)9789819786305

Web scraping, an automated process that extracts data from websites, is a powerful tool that faces several challenges. Existing scrapers often entail drawbacks, such as subscription fees and limited accessibility for small businesses. Concerns regarding the reliability and accuracy of data arise, especially with respect to real-time content. This study scrutinizes web scraping tools, delving into operational principles, advantages, and limitations, addressing applications in data mining, research, and social media marketing. Two scraping approaches, manual extraction, and automated methods, such as HTML parsing, were explored. Popular tools such as ParseHub, WebHarvy, and Octoparse have been discussed, but concerns about accessibility and accuracy persist. Libraries such as BeautifulSoup, Selenium, and Scrapy offer alternatives to those with programming skills. Although web scraping accelerates data collection, its limitations and potential drawbacks must be carefully considered. This paper focuses on web scraping, a potent tool for extracting data from websites. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data accuracy

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eXtended Reality Services for Outdoor Cultural Spaces: System Design and Evaluation Framework Using Unbiased Biometric Data 15

eXtended Reality Services for Outdoor Cultural Spaces: Syste...

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15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Koukopoulos, Zois Koukopoulos, Dimitrios Fidas, Christos University of Patras Interactive Technologies Lab Dept. of Electrical & Computer Engineering Patras Greece University of Patras Dept. of History-Archaeology Patras Greece University of Patras Dept. of Electrical & Computer Engineering Patras Greece

ISBN: (纸本)9798350368833

The concept of enriching the visible reality with more information has led to the development of the eXtended Reality technology, where digital elements like text, images, 3D representations and virtual scenarios, are embedded to the real world and become visible to humans via mobile devices. Cultural Heritage is embracing eXtended Reality and tries to find new ways to harvest its merits in an endless struggle to disseminate cultural information to the public and the next generations. In this paper, we are presenting an innovative intelligent Environment, operating in outdoor cultural spaces and offering personalized eXtended Reality cultural experiences to visitors. The Environment aims to support the financial sustainability of cultural heritage institutes by attracting visitors and especially younger ones, as well as create new sources of revenue for cultural heritage professionals by allowing them to create XR experiences, without the help of IT professionals and exploiting them in an online market of XR cultural experiences. We propose a novel framework to evaluate the user experience by collecting biometric data (brain activity and eye behavior) from the visitors of outdoor cultural spaces and exploring their cognition and emotions while using the new Environment. © 2024 IEEE.

关键词： Biometric Data eXtended Reality Outdoor Cultural Spaces Sustainability

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Performance Analysis of Reconfigurable Intelligent Surface in Enhancing Security of Wireless Networks 3

Performance Analysis of Reconfigurable Intelligent Surface i...

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3rd International Conference on Advancement in electrical and Electronic engineering, ICAEEE 2024

作者： Mamun, M.A.A. Sarkar, M.Z.I. Alam, A. Ruku, M.R.A. Rajshahi University of Engineering & Technology Dept. of Electrical and Electronic Engineering Rajshahi6204 Bangladesh Bangladesh Army University of Engineering & Technology Dept. of Electrical and Electronic Engineering Natore6431 Bangladesh

ISBN: (纸本)9798350388282

This paper delves into the security analysis of wireless communication networks incorporating reconfigurable intelligent surfaces (RIS) in the context of mathematical model of ergodic secrecy capacity. The investigation specifically focuses on scenarios with a single receiver and a single eavesdropper, operating over a Rayleigh fading channel. This study delves into the impact of parameters, including the average signal-to-noise ratio (SNR) of channels and the number of reflecting elements within the RIS. Analytical expressions for the ergodic secrecy capacity (ESC) are derived, providing insights into the system's security performance. The analysis is further extended to include a comparative study between scenarios with and without the integration of RIS. In addition to the analytical framework, the paper conducts Monte-Carlo simulations to validate the accuracy of the derived results. The obtained outcomes affirm the positive effect of employing RIS enhancing the ergodic secrecy capacity in wireless systems, particularly offering a foundation for further exploration and practical implementation in real-world scenarios. © 2024 IEEE.

关键词： Signal to noise ratio

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Adaptive Fuzzy Predictor based Fast Terminal Sliding Mode Controller Design for Two-link Robot Manipulator 10

Adaptive Fuzzy Predictor based Fast Terminal Sliding Mode Co...

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10th Indian Control Conference, ICC 2024

作者： Kumar, Shreyas Dash, Bishesha Maiti, Roshni Guha, Dipayan Dept. of Mechanical Engineering Indian Institute of Engineering Science and Technology Shibpur India Dept. of Electrical Engineering Indian Institute of Engineering Science and Technology Shibpur India Dept. of Electrical Engineering Motilal Nehru National Institute of Technology Allahabad Prayagraj India

ISBN: (纸本)9798331517212

This paper proposes an Adaptive Fuzzy Predictor based Fast Terminal Sliding Mode Control (AFP-FTSMC) for a two-link robotic manipulator (TLRM). The unknown disturbances, changing with time, present in the TLRM system are estimated using the fuzzy predictor model and the accurate control action is formulated using the FTSM controller to tackle the nonlinearities in the system. The disturbance, varying with time, is estimated using adaptive fuzzy predictor, and the fuzzy adaptive rule is developed from the Lyapunov stability criteria. The chattering phenomenon and singularity problem is efficiently addressed by utilizing the fast terminal sliding mode control law. The overall controller is capable of producing fast-tracking performance by rejecting the disturbance and chattering adequately. The stable performance of the TLRM system with the proposed controller is guaranteed by utilizing Lyapunov stability criteria. The experimental results demonstrate that the proposed controller achieves superior tracking performance and robustness for nonlinear TLRM system compared to the existing terminal sliding mode control method, even in the presence of significant uncertainties and time-varying external disturbances. © 2024 IEEE.

关键词： Sliding mode control

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Performance Analysis of RIS-aided Wireless Networks amidst Multiple Eavesdropping 6

Performance Analysis of RIS-aided Wireless Networks amidst M...

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6th International Conference on electrical engineering and Information and Communication technology, ICEEICT 2024

作者： Mamun, M.A.A. Sarkar, M.Z.I. Alam, A. Ruku, M.R.A. Rajshahi University of Engineering & Technology Dept. of Electrical & Electronic Engineering Rajshahi6204 Bangladesh Bangladesh Army University of Engineering and Technology Dept. of Electrical and Electronic Engineering Natore6431 Bangladesh

ISBN: (纸本)9798350385779

This research explores the mathematical model of ergodic secrecy capacity in the context of security analysis of wireless communication networks with reconfigurable intelligent surfaces (RISs). Particularly, the study concentrates on situations involving a multiple eavesdroppers and a single receiver using a Rayleigh fading channel. This paper explores the effects of several parameters, such as the number of reflecting elements in the RIS and the average signal-to-noise ratio (SNR) of the channel. For the ergodic secrecy capacity (ESC), the analytical formulas that provide important insights into the system's security performance was derived. A comparative analysis of those two scenarios with and without the incorporation of RIS is included to the analysis. The paper performs Monte-Carlo simulations in addition to the analytical framework to verify the veracity of the given conclusions. The results obtained validate the beneficial impact of using RIS to improve the ergodic secrecy capacity in wireless systems, especially providing a basis for additional research and useful application in real-world situations. © 2024 IEEE.

关键词： Signal to noise ratio

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Battery Degradation Heuristics for Predictive Energy Management in Shipboard Power Systems 50

Battery Degradation Heuristics for Predictive Energy Managem...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Vedula, Satish Olajube, Ayobami Omiloli, Koto Anubi, Olugbenga Moses Dept. of Electrical and Computer Engineering FAMU-FSU College of Engineering Tallahassee United States

ISBN: (纸本)9781665464543

The presence of Pulse Power Loads (PPLs) in the Notional Shipboard Power System (SPS) presents a challenge in the form of meeting their high ramp rate requirements. Considering the ramp rate limitations on the generators, this might hinder the power flow in the grid. Failure to meet the ramp rate requirements might cause instability. Aggregating generators with energy storage elements usually addresses the ramp requirements while ensuring the power demand is achieved. This paper proposes an energy management strategy that adaptively splits the power demand between the generators and the batteries while simultaneously considering the battery degradation and the generator’s efficient operation. Since it is challenging to incorporate the battery degradation model directly into the optimization problem due to its complex structure and the degradation time scale which is not practical for real-time implementation, two reasonable heuristics in terms of minimizing the absolute battery power and minimizing the battery state of charge are proposed and compared to manage the battery degradation. A model predictive energy management strategy is then developed to coordinate the power split considering the generator efficiency and minimizing the battery degradation based on the two heuristic approaches. The designed strategy is tested via a simulation of a lumped notional shipboard power system. The results show the impact of the battery degradation heuristics for energy management strategy in mitigating battery degradation and its health management. © 2024 IEEE.

关键词： Battery management systems

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ADRGS: an automatic diabetic retinopathy grading system through machine learning

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Multimedia Tools and Applications 2024年 1-25页

作者： Devi, Y. Aruna Suhasini Chari, K. Manjunatha Dept. of Electronics and Communication Engineering CMR College of Engineering & ampTechnology Telangana Hyderabad India Dept. of Electrical Electronics and Communication Engineering GITAM University Telangana Hyderabad India

In recent years, Diabetic Retinopathy (DR) has emerged as a significant chronic ailment affecting roughly one-third of diabetic patients globally. DR is the leading cause of vision impairment and detecting DR in its early stages can be a challenging task, but if neglected, it can lead to severe DR and, ultimately, permanent vision loss. Therefore, the development of an automated DR detection system, based on retinal fundus images is of paramount importance. This paper develops an automatic Diabetic Retinopathy (DR) screening system that analyzes the fundus retinal images and produces a grade to determine the severity of DR by using computer vision and machine learning algorithms. The complete system is four-fold;pre-processing, segmentation of the vessels and optic disc (OD), lesions classification and grading the severity of DR. The initial pre-processing phase enhances the quality of retinal image based on the spatial collaboration between pixels. The second phase segments the retinal vessels and Optic Disc through mathematical morphology and composite filtering strategy. The third phase performs classification of the entire image into four types of lesions namely Hard Exudates (EX), Hemorrhages (HM) and Microaneurysms (MA) and Cotton Wool Spots (CWS). At this phase, each pixel is represented with a set of 30 features including 14 structural features and 16 appearance based features. A two-step hierarchical classification method is employed to classify the image into lesions and sub lesions. Finally, the classification results are formulated as a function to determine the severity of DR. For validation purposes, DIARETDB1 database is used, and the performance is measured through the parameters: Specificity, Sensitivity, Area under Curve (AUC) and Accuracy. For feasibility checking, three machine learning algorithms are employed namely Gaussian Mixture Model, K-Nearest Neighbor and Support Vector Machine. © The Author(s), under exclusive licence to Springer Science

关键词： Nearest neighbor search

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