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Implementation of Dynamic Spectrum Access Techniques in Cognitive Radio Networks under Generalized Fading Conditions 2

Implementation of Dynamic Spectrum Access Techniques in Cogn...

引用

2nd International Conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Garg, Shobhit Sharma, Amulya Devgan, Divyansh 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 Graphic Era Deemed to be University Dept. of Management Studies Dehradun India

ISBN: (纸本)9798331519056

This paper is organized as follows: Section II provides a background on our research work based on DSA in CRNs using CR under different fading conditions. c) Performance: We also study how effective adaptive algorithms along with the machine learning can prove in achieving higher spectrum sensing accuracy and decision making on run time. By conducting simulations and extensive performance evaluation, we show that the traditional solutions fall short when compared to our AI-based methodology in terms of accuracy especially under harsh fading conditions. Finally, sensitivity analysis highlights the control parameters that need to be submitted to further optimization for better system performance. With all above analysis, our results indicate that DSA can alleviate spectrum underutilization problem and enhance communication reliability in CRNs. Thus, with proper adaptation strategies and machine learning algorithms, the DSA systems provide an appealing opportunity to meet the continuously increasing requirements of bandwidth-consuming applications in current days wireless networks. The results of this research are helpful in providing effective value input to Advances in the understanding and design of robust, efficient spectrum management approaches for dynamic and diverse wireless settings. © 2024 IEEE.

关键词： Sensitivity analysis

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Study of Fiber Optic Sensor for Various Biomedical Applications

Study of Fiber Optic Sensor for Various Biomedical Applicati...

引用

2023 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2023

作者： D'Sa, Joyline Germine Ullal, Poojith Kumar Srajana, Srajana Maroli, Sushanth Shetty, Nikhil Sahyadri College of Engineering & Management Dept. of Computer Science and Engineering Adyar Mangalore India Sahyadri College of Engineering & Management Dept. of Electronics and Communication Engineering Adyar Mangalore India

ISBN: (纸本)9798350340129

Fiber optic sensors have been widely used in various biomedical applications due to their high sensitivity, reliability, and non-invasiveness. In this paper, we propose a novel approach to designing an optical sensor for detecting impurities in a mixture. The proposed sensor utilizes a flexible polymer layer and an optical fiber cable to detect variations in the power of the adulterated mixture. The polymer layer is made of PDMS, which swells or shrinks in response to the level of adulteration present in the mixture. As a result, the intensity of the output spectra changes, which can be used to detect impurities. The sensor's results will be compared with those obtained from the pure mixture to evaluate its accuracy. In conclusion, the proposed sensor has several advantages, such as low cost, easy to handle, ease of fabrication, and high sensitivity, making it a promising candidate for detecting impurities in various mixtures. © 2023 IEEE.

关键词： Medical applications

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Art of Rare Pattern Discovery Techniques in Data Mining

Art of Rare Pattern Discovery Techniques in Data Mining

引用

2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Mahendra, M. Adarsha, S.P. Saraswat, Anant Nagaraju, D. Sanskrithi School of Engineering Dept. of Computer Science and Engineering Andhra Pradesh Puttaparthi India Sanskrithi School of Engineering Dept. of Electronics and Communication Engineering Andhra Pradesh Puttaparthi India

ISBN: (纸本)9798350308167

In the current era, data analysis has become an integral part of decision-making processes. Data is collected from various sources, such as cloud warehouses, for decision-making and subjected to different classifications and data mining algorithms. One of the most crucial tasks in data mining is rare item set mining, which employs different association-based techniques and threshold values to uncover hidden data in the form of patterns. The research paper provides a comprehensive overview of the latest rare pattern mining techniques and their applications, which can be highly beneficial in achieving efficient and effective decision-making processes. © 2023 IEEE.

关键词： Association Rules Data Mining Frequent Item-sets Rare Item-sets Rare pattern Threshold

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BanijyaPrayukti: E-Commerce Recommendation Engine for Sustainable Products 7

BanijyaPrayukti: E-Commerce Recommendation Engine for Sustai...

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7th IET Smart Cities Symposium, SCS 2023

作者： Pradhan, Aditya Ghosh, Amartya Mondal, Rintu Saxena, Kumar Abhi Dutta, P.K. Mitra, Anirban Dept. of Computer Science and Engineering Amity School of Engineering and Technology Kolkata Kolkata India Dept. of Electronics and Communication Engineering Amity School of Engineering and Technology Kolkata Kolkata India

ISBN: (纸本)9781839539831

The rapid growth of e-commerce has revolutionized the way businesses operate and interact with customers. E- commerce has revolutionized the way businesses operate, making it easier than ever to reach customers and sell products. However, with this convenience comes a challenge: how can we promote sustainable products and encourage consumers to make eco- friendly choices? The primary objective of this project is to pro- mote sustainability by utilizing artificial intelligence techniques in recommending eco-friendly alternatives. Our goal is to provide users with recommendations on sustainable products based on their shopping history, behavior patterns, and demographic information. The system continuously learns from user interactions, enabling it to provide increasingly accurate and personalized recommendations over time. © The Institution of engineering & Technology 2023.

关键词： Electronic commerce

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Machine Learning Approaches to Predict Post Covid-19 Severity: A Detail Case Study

Machine Learning Approaches to Predict Post Covid-19 Severit...

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2024 International Conference on Big Data Analytics in Bioinformatics, DABCon 2024

作者： Mathur, Richa Dutta, Ritam Bansal, Payal Kumar, Rajeev Poornima University Dept. of Computer Scinece & Engineering Rajasthan Jaipur303905 India Rajasthan Jaipur302022 India Poornima Institute of Engineering & Technology Dept. of Electronics & Comm. Engineering Rajasthan Jaipur302022 India Moradabad Institute of Technology Dept. of Computer Science & Engineering Uttar Pradesh Moradabad244001 India

ISBN: (纸本)9798350378047

The entire world has witnessed a horrific pandemic in last three years, whose long term and short-term impact to human body has been observed in large scale in these post covid-19 years. Machine learning (ML) techniques have been successfully implemented in medical field since last one decade. The emergence of post covid-19 pandemic symptoms are compelling researchers to re-search for minute detection and predict patient's probable infection rate. Long lasting chest pain, breathing issues, liver and kidney dialysis issues have been apparently visible as post covid-19 symptoms. In this paper, the journals regarding the prediction of covid-19 severity based on symptoms have been discussed. Several researchers have established deep learning-based models for the prediction. They have used the test data from the hospitals for their research process. The KNN models, ANN models, and SVM models have been discussed. The limitations of the past research process have been evaluated to be the biased test data set and missing values. The methodology that was used for the research process has been described. Mixed method of data collection was used for the research processes. The secondary data was collected from reliable sources for this research process. Considerable amount of test data has been retrieved from Kaggle database regarding post covid-19 patient's symptoms. The data analysis is performed on the Weka tool using various machine learning models. © 2024 IEEE.

关键词： COVID-19

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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...

引用

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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Detection of Multi-Class Multi-Label Ophthalmological Diseases in Retinal Fundus Images Using Machine Learning

Detection of Multi-Class Multi-Label Ophthalmological Diseas...

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2024 International Conference on Innovations and Challenges in Emerging Technologies, ICICET 2024

作者： Karule, P.T. Bhele, Sujata B. Palsodkar, Prasanna Agarkar, Poonam T. Hajare, Hirendra R. Patil, Prashant R. Yeshwantrao Chavan College of Engineering Dept. of Electronics Engineering M.S Nagpur India Government College of Engineering Dept. of Electronics & Telecommunication Engineering M.S Nagpur India Ballarpur Institute of Technology Dept. of Computer Science and Engineering M.S Chandrapur India Smt. Radhikatai Pandav College of Engineering Dept. of Management Studies M. S Nagpur India

ISBN: (纸本)9798350319019

Multi-disease diagnosis of fundus image is a great challenge even though sophisticated computer-aided tools are available and ophthalmologist experience is to par. Clinical tests capture abnormalities and anatomical structures for various diagnoses of the retinal image. The proposed work uses RFMiD (Retinal Fundus Multi-Disease Image Dataset) to classify ocular diseases using an efficient feature extraction framework and machine learning. The framework considers 8-12 diverse ophthalmological diseases from 3200 dataset images labeled with the help of two senior medical (retinal) experts. Experimental evaluation of the dataset using Random forest classified up to 10 diseases with an accuracy of 100% while 96.75% was obtained when 12 diseases were considered without augmenting the dataset images. The evaluation successfully determined the retinal infection due to fine-grained variability, appearance, and closeness in the presence of several lesions. © 2024 IEEE.

关键词： Classification (of information)

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Design of Low Drop Out Regulator with High Robustness ESD Protection Circuit Using Current Buffer Structure

Design of Low Drop Out Regulator with High Robustness ESD Pr...

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2023 International Conference on electronics, Information, and Communication, ICEIC 2023

作者： Kwon, Sang Wook Jeong, Seung Gu Lee, Kwang Yeob Koo, Yong Seo Dankook University Dept. Engineering of Electronics and Electrical Seoul Korea Republic of Seokyeong University Dept. Engineering of Computer Seoul Korea Republic of

ISBN: (纸本)9798350320213

This paper proposes an LDO regulator that uses a current buffer for the peak voltage exposed to the load current. In the case of conventional LDO regulators, a method of adjusting the size of the external capacitor has been used to alleviate overshoot and undershoot phenomena. When the size of the external capacitor increases, the overshoot and undershoot voltages are reduced, but the chip size increases. Therefore, the proposed LDO regulator is designed to have improved overshoot and undershoot voltages using the current buffer structure instead of the method of resizing the external capacitor. The current buffer structure was designed so that it could detect the overshoot and undershoot voltages generated from the feedback voltage, and charge and discharge the current. As a result, it was verified that the LDO regulator with the current buffer structure could improve the overshoot and undershoot voltages according to the load current. The LDO regulator having the current buffer structure has a load current of up to 250 mA at the output voltage. According to the measurement results, when the load current is 250 mA, the power voltage according to the undershoot is 38 mV, and the power voltage according to the overshoot is 29 mV. Additionally, the LDO regulator with a current buffer structure has an ESD protection circuit built in to ensure reliability in ESD situations. © 2023 IEEE.

关键词： ESD protection circuit ESD surge LDO regulator LDO regulator with ESD protection circuit overshoot undershoot

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Large Language Models versus Natural Language Understanding and Generation 27

Large Language Models versus Natural Language Understanding ...

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27th Pan-Hellenic Conference on Progress in Computing and informatics with International Participation, PCI 2023

作者： Karanikolas, Nikitas Manga, Eirini Samaridi, Nikoletta Tousidou, Eleni Vassilakopoulos, Michael Dept. of Informatics and Computer Engineering University of West Attica Athens Greece Dept. of Electrical and Computer Eng. University of Thessaly Volos Greece

ISBN: (纸本)9798400716263

In recent years, the process humans adopt to learn a foreign language has moved from the strict "Grammar -Translation"method, which is based mainly on grammar and syntax rules, to more innovative processes, resulting to the more modern "Communicative approach". As its name states, this approach focuses on the coherent communication with native speakers and the cultivation of oral skills, without taking into consideration, at least at the first stages, the rules that govern the language. The same trend seems to have been applied to the way machinery can be "educated"to comprehend and reproduce the unfamiliar, human language. The "rule based"Natural Language Generation (NLG) and Natural Language Understanding (NLU) algorithms, on one hand, and the "text based"Large Language Models (LLMs), on the other, are two, analogous to the two human foreign language learning processes, subareas of Natural Language Processing (NLP). This paper presents these two alternative approaches, LLMs (a technology having surfaced as an influential catalyst of NLP, during last years) on the one hand and NLG/NLU on the other, highlighting their applications, their technologies, their capabilities, their differences, their strengths and weaknesses and the challenges they present, contributing to a deeper comprehension of the evolving landscape of Artificial Intelligence and human-computer communication. © 2023 Owner/Author.

关键词： Natural language processing systems

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Protocol Stack-Aware Comparison of Centroid Localization Algorithms Based on Anchor Density Using Cooja

Protocol Stack-Aware Comparison of Centroid Localization Alg...

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2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023

作者： Turan, Ismail Hakki Yildiz, Dogan Demirci, Sercan Ondokuz Mayis University Dept. of Computer Engineering Samsun Turkey Ondokuz Mayis University Dept. of Electrical & Electronics Engineering Samsun Turkey

ISBN: (纸本)9798350302523

Location reconnaissance of sensor nodes is crucial for many outdoor applications. In fact, some outdoor wireless sensor networks are deployed solely for location information. However, adding a GPS module to each node can increase the cost of the wireless sensor network. Therefore, software-based location estimation using radio signals becomes necessary. Hardware without a GPS module requires nodes with known locations in the network. To keep the cost of the network economically reasonable, the density of anchor nodes in the network with expensive nodes that have GPS modules should be investigated. In this study, an alternative method has been developed for transmitting localization packets in Contiki-NG firmware Wireless Sensor Networks (WSNs), as point-to-point communication is not suitable for the nature of WSNs. Using the method, the minimum anchor node density and transmission range required for localization in mesh topologies, was investigated according to negligible location estimation errors with Cooja network simulation environment. Three centroid-based algorithms have been compared based on localization error and localization ratio. At the end of the study, the minimum transmission range and anchor density ratio required for localization algorithms were determined. It was shown how effective the MAC policy was up to which transmission range. It was demonstrated how incorrect conclusions could be reached when network protocol stack requirements were not considered. © 2023 IEEE.

关键词： Firmware

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