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Design of Array Microstrip Antenna with Circular Polarization for WBAN/WIMAX 26

Design of Array Microstrip Antenna with Circular Polarizatio...

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2024 IEEE International Conference on Automation/26th Congress of the Chilean Association of Automatic Control, ICA-ACCA 2024

作者： Ahumada, Cristian Kaschel, Hector Osorio-Comparan, Roman Cordero, Sergio Universidad Técnica Federico Santa María Dept. Electrotechnics and Computer Valparaiso Chile Dept. of Electrical Engieneering Santiago Chile Dept. of Computer Systems Engineering Ciudad de México Mexico

ISBN: (纸本)9798350378115

This article presents the design of a array microstrip antenna with circular polarization for the evaluation of the specific absorption rate (SAR) in human tissues. The analysis focuses on a single element and a two element microstrip patch, each designed at 2.5 GHz. Both antennas were crafted on a microstrip substrate, sporting a thickness of 1.6 mm and a dielectric constant of 4.3. An evaluation was conducted that contrasted the efficiency of the engineered antenna array with that of the standalone antenna, with particular emphasis on VSWR (Voltage Standing Wave Radio), gain, and directionality, was designed, simulated, and optimized using CST Microwave Studio (MWS) software. Furthermore, the SAR level was scrutinized under flat conditions within the human tissue representation. © 2024 IEEE.

关键词： Circular polarization

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Alpha-x Framework for Assessing Network Robustness in Nakagami-m Fading and Co-Channel Interference Environments 3

Alpha-x Framework for Assessing Network Robustness in Nakaga...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Upadhyay, Deepak Siwach, Karan Dhondiyal, Shiv Ashish Upadhyay, Abhay Gupta, Mridul Sharma, Kunj Bihari Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India G.L. Bajaj Institute of Technology and Management Dept. of Computer Science and Engineering Greater Noida India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India

ISBN: (纸本)9798331518592

This article explores how the Alpha-x framework can improve network robustness under Nakagami-m fading and co-channel interference (CI), The study evaluates network performance using key metrics such as outage probability, spectral efficiency, and capacity degradation. The simulations show a 50% reduction in outage probability, a 20% boost in spectral efficiency, and a 33.3% lower capacity degradation compared to traditional models. These results demonstrate how the Alpha-x framework enhances network performance by adapting to various fading conditions and interference levels in wireless communication systems. The framework not only improves reliability and efficiency but also shows practical relevance in network planning and management. This can potentially lead to better user experiences and increased operational resilience. Future research could focus on optimizing the underlying algorithms and testing their performance on a larger scale in real-world environments. As telecommunications systems evolve, frameworks like Alpha-x could play a crucial role in ensuring reliable and efficient wireless networks. © 2024 IEEE.

关键词： Cochannel interference

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Slang Word Detection in the Context of User Profiling in the Social Media Platformes 4

Slang Word Detection in the Context of User Profiling in the...

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4th International Conference on Advances in electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Samanta, Bikram Shil, Ritika Pal, Alok Ranjan Pal, Antara College of Engg. and Management Dept. of Computer Science and Engg. Kolaghat India Atharva College of Engineering Dept. of Computer Science Engg. Mumbai India

ISBN: (纸本)9798350343670

On social media platforms, people express their views in various ways, sometimes using formal words and sometimes in informal form. The informal conversations may contain jargon words i.e. slang words which might be improper for all kinds of audience. In this work, an attempt has been made to identify slang words in a text, posted on the social media platform. The overall experiment has been carried out in 4 modules. In module-1, the suspicious words from the posted text have been identified using minimum edit distance. This experiment has been implemented by the help of a dataset of printable slang words collected from Kaggle. In module-2, the topic of discussion has been analyzed by using a knowledge based approach. This part of the experiment has been carried out by creating a newspaper archive from the online repository of the "Times of India"newspaper. But, this knowledge based strategy could not produce an appreciable accuracy at its baseline. Therefore, as a modification of this technique, in module-3, the context analysis task has been implemented combining knowledge based approach and machine learning based approach. In module-4, the module-1 and module-3 are merged to tag a suspicious word with its level of abusiveness. © 2024 IEEE.

关键词： Context Analysis Slang Word Social Media Transformer User Profiling

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Carotid plaque stroke risk assessment using multiscale AM-FM analysis based on DoG filterbanks 24

Carotid plaque stroke risk assessment using multiscale AM-FM...

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24th International Conference on Digital Signal Processing, DSP 2023

作者： Constantinou, Kyriacos P. Constantinou, Ioannis P. Pattichis, Marios S. Kyriacou, Efthyvoulos Pattichis, Constantinos S. University of Cyprus Dept. of Computer Science Nicosia Cyprus Istognosis Ltd Nicosia Cyprus University of New Mexico Dept. of Electrical and Computer Engineering AlbuquerqueNM United States Cyprus University of Technology Dept. of Electrical Engineering Computer Engineering and Informatics Limassol Cyprus

ISBN: (纸本)9798350339598

The objective of this work was the investigation of multiscale Amplitude Modulation - Frequency Modulation (AM-FM) analysis based on Difference of Gaussians (DoG) filterbanks representations in order to predict the risk of stroke by analysing carotid plaques ultrasound images of individuals with asymptomatic carotid stenosis. We computed the instantaneous amplitude, instantaneous phase and the magnitude of instantaneous frequency to extract histogram features on each plaque region. The Support Vectors Machine classifier was implemented to classify asymptomatic versus symptomatic plaques. A dataset of 100 carotid plaque images (50 asymptomatic and 50 symptomatic) were tested, and showed that the AM-FM features based on DoG filterbanks and simple histograms performed better than the traditional AM-FM features. Best results were obtained when an eight scale filterbank with a combination of scales was used reaching the accuracy of 75%. © 2023 IEEE.

关键词： Frequency modulation

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A Medium Voltage Bidirectional Modular LLC Converter With An Extendable Stacked-Switches Leg

A Medium Voltage Bidirectional Modular LLC Converter With An...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Beshara, Maria Cheema, Muhammad Ali Masood Lam, John York University Dept. of Electrical Engineering and Computer Science Toronto Canada Northern Transformer Corporation Toronto Canada

ISBN: (纸本)9798350376067

This paper proposes a new stacked-switches/full-bridge (FB) structured DC/DC bidirectional LLC resonant converter for medium voltage DC grids in energy storage application. With the proposed converter configuration, the extendable stacked-switch leg that interfaces with the MV side results in low voltage stress across the switch. In addition, this leg also facilitates rectification in the reverse power flow direction. The proposed converter utilizes variable frequency control to adjust the battery voltage, with FB synchronous rectification to facilitate efficient power flow for both charging and discharging of batteries. The circuit analysis, design considerations, and the operational framework are provided. Results on a 200kW, 100kHz, 10kV/600V design are provided to demonstrate the merits of this work. © 2024 IEEE.

关键词： energy storage medium voltage Resonant converters soft-switching

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Involutional Neural Network Based Approach for the Detection of Melanoma Cancer

Involutional Neural Network Based Approach for the Detection...

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2024 International Conference on computer, Electronics, electrical engineering and their Applications, IC2E3 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India

ISBN: (纸本)9798350388534

This paper presents an extraordinary method to detected melanoma, the most lethal form of skin cancer, using Involutional Neural Networks (INNs). Melanoma's early detection is crucial for effecacius treatment, yet existing diagnostic methods often lack the requiring precision and scalability. INNs offer a solve through their advanced capability to adaptively process spatial information in images, a huge different from traditional convolutional techniques. Our reaserch applies INNs to melanoma detectionair, focusing on their unique involution operations that significant enhance image analysis for accurately classification. The performance of our model, assessed across different metrics including accurate, precision, recall, and F1-scores, demonstrates its superior diagnostic capability. This investigation not only underscores the potency of INNs in medical imagining but also opens up new avenues for their application across diverse analytical needs in healthcare. By advancing melanoma detection methods, we contribute to the broader goal of improving early cancer diagnose and treatment outcomes! © 2024 IEEE.

关键词： Lung cancer

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Lightweight SNN-based White Space Detector for Cognitive Vehicular Networking

Lightweight SNN-based White Space Detector for Cognitive Veh...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Galib, Md Mehedi Hassan Younis, Mohamed University of Maryland Baltimore County Dept. of Computer Science and Electrical and Engineering BaltimoreMD21250 United States

ISBN: (纸本)9798350351255

The Dedicated Short-Range Communication (DSRC) protocol has become the de facto means for supporting vehicle ad hoc networking (VANET). Yet, the current allocated spectrum for DSRC is insufficient for handling large volumes of data, particularly during accidents or high traffic congestion, where most spectral resources are dedicated to control and emergency awareness, degrading infotainment and multimedia application services. Such a challenge motivates the pursuance of cognitive radio (CR), also known as CR-VANET, where vehicles opportunistically tap to utilize resources within the licensed spectrum as secondary users (SUs). To avoid interference with primary users (PUs), a vehicle needs to accurately sense the medium and detect white space. Given the dynamic nature of the VANET topology and varying volume of message traffic, machine-learning (ML) techniques, particularly those pursuing deep learning models, proved to be a viable option for spectrum sensing. However, the computational complexity of these techniques becomes an obstacle for vehicles. This paper opts to fill the technical gap by proposing a novel lightweight spectrum detector that employs spiking neural networks (SNN). The validation results using a field collected LTE-dataset clearly show that our proposed SNN model enables fast inference time, which ultimately expedites the spectrum sensing process and provides additional spectral resources for vehicular communication. © 2024 IEEE.

关键词： Traffic congestion

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A computer science Perspective on Digital Sustainability: A Thematic Literature Review 22

A Computer Science Perspective on Digital Sustainability: A ...

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22nd IEEE Consumer Communications and Networking Conference, CCNC 2025

作者： Delnevo, Giovanni Olaiya, Kelvin Salomoni, Paola University of Bologna Dept. of Computer Science and Engineering Bologna Italy

ISBN: (纸本)9798331508050

This paper explores the evolving concept of digital sustainability, emphasizing its growing importance as digital technologies become essential to addressing global sustainability challenges. Through a thematic literature review focused on computer science, we analyze papers from Scopus-indexed journals to identify key themes in the discourse on digital sustainability. Additionally, we map the identified topics to the traditional three-pillar model of sustainable development, noting areas of alignment and divergence. The study offers insights into how digital sustainability is framed within the computer science literature and its implications for future research. © 2025 IEEE.

关键词： Green development

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Application of Recommended Systems for E-commerce 14

Application of Recommended Systems for E-commerce

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14th International Conference on Emerging Ubiquitous Systems and Pervasive Networks / 13th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, EUSPN/ICTH 2023

作者： Gulnara, Bektemyssova Guldana, Shyntore Yerassyl, Akhmer Dept. of Computer engineering IITU Almaty Kazakhstan

A filtering method is indispensable in a data-flooded environment. Recommended systems have made a massive step towards this aim, speeding up internet-based customer experience. Most of today's examples of artificial marketing intelligence are known as supervised learning, which varies from offering personalized specific products identifying the most valuable marketing strategies, to forecasting customer churn rate or customer life value, and building up a positive client base. Generally, different types of stored information are used to customize various dimensions or search results, demonstrate the most targeted advertising on the homepage, etc. n our research we have also incorporated the benefits and drawbacks of every approach. Finally, this paper also presents numerous difficulties and problems confronting recommenders in their application systems algorithms. In this paper, we initially present multiple best-known types of recommended systems and concentrate on one part of the e- commerce recommendation and afterwards make their quantitative comparison. Recommender systems have taken a huge step towards this goal, greatly improving the user experience in the online environment. © 2024 Elsevier B.V.. All rights reserved.

关键词： Recommender systems

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A Novel Hybrid Deep Neural Network for Early Detection and Classification of Chicken Diseases 5

A Novel Hybrid Deep Neural Network for Early Detection and C...

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5th International Conference on Sustainable Technologies for Industry 5.0, STI 2023

作者： Uddin, Md Shihab Islam, Md Fakrul Rahman, Sharukh Foysal, Nasir Uddin Islam, Muhammad Nazrul Razzaque, Md. Abdur Al Faisal, Faiz Green University of Bangladesh Dept. of Computer Science and Engineering Dhaka Bangladesh Military Institute of Science and Technology Dept. of Computer Science and Engineering Dhaka1216 Bangladesh University of Dhaka Dept. of Computer Science and Engineering Dhaka1000 Bangladesh

ISBN: (纸本)9798350394290

Detection and classification of chicken diseases has been a longstanding concern for farmers. Relying solely on expert opinions could be a costly option. Moreover, there are certain chicken diseases that spread quickly, and necessary procedures are immediately needed to carryon. On the other hand, the lack of research activity or low availability of data on this topic leads to many misunderstandings and challenges so as to correctly detect a certain type of chicken disease. The existing techniques show low accuracy on disease classification, which leads to a complex engineering problem and critical analysis is required for sustainable development. In this paper, we develop a novel hybrid deep neural network, namely ChickenNet21, which combines a Convolutional Neural Network (CNN) and a fine-tuned Visual Geometry Group (VGG) model to address this challenge. Using a large dataset of 6,812 farm-labeled fecal images, we assess the effectiveness of ChickenNet21 and it achieves 98.83% accuracy in identifying chicken diseases. © 2023 IEEE.

关键词： Convolutional neural networks

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