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Gammatone Visualization based Cough Sound Classification: Performance Comparison with Delta and Delta-Delta Features 2

Gammatone Visualization based Cough Sound Classification: Pe...

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2nd International Conference on Smart Technologies and Systems for Next Generation Computing, ICSTSN 2023

作者： Priya, B.Lakshmi Jayalakshmy, S. Saraswath, D. Vellore Institute of Technology School of Computer Science and Engineering Chennai Campus Chennai India IFET College of Engineering Dept. of Electronics and Communication Engineering Villupuram India

ISBN: (纸本)9798350348002

Cough being a common symptom for most respiratory disease is considered as a predictor in the diagnosis of the diseases. In recent years, time frequency representations of signals are acclaimed for its efficacy in the classification of signals. This work explores the potential of time frequency representation derived from gammatone features in the classification of cough signals. Accordingly, visualization of gammatone cepstral coefficients (GTCC) and its delta and delta-delta variants are employed for classifying cough signals using GoogLeNet, a prominent pre-trained CNN architecture. The results of this study evinces that the delta-delta variant of GTCC with a classification accuracy of 98.02% has significantly outperformed GTCC and its delta variant which recorded accuracies of 97.22% and 94.44% respectively. © 2023 IEEE.

关键词： Visualization

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Experimental Approach to Internal Security Threats for 5G-Advanced Core Networks 35

Experimental Approach to Internal Security Threats for 5G-Ad...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Park, Jaehyoung Kim, Jihye Woo, Seungchan Park, Kyungmin Kim, Jonghyun Lee, Jong-Hyouk Sejong University Dept. of Computer and Information Security & Convergence Engineering for Intelligent Drone Seoul Korea Republic of Sejong University Dept. of Computer and Information Security Seoul Korea Republic of Sejong University Dept. of Computer and Information Security & Convergence Engineering for Metaverse Seoul Korea Republic of Electronics and Telecommunications Research Institute Daejeon Korea Republic of

ISBN: (纸本)9798350362244

As we embrace the dawn of the 5G era, the fusion of Software Defined Network (SDN) and Network Function Virtualization (NFV) technologies has heralded a new epoch in network architecture. This provides indispensable capabilities and virtualized infrastructure to meet the burgeoning demands of modern networks. Yet, with each stride forward in mobile communication technology, security threats loom larger, casting a shadow over the very fabric of our networks. In this context, identifying and addressing these threats is crucial as it plays a key role in enhancing the security of a 5G-Advanced and a next 6G mobile communication technologies. Therefore, this paper undertakes an investigative journey to explore security threats introduced by SDN/NFV technologies in the 5G-Advanced core networks. Through our simulations, we unveil a need for fortified security technologies within the 5G-Advanced core networks, illuminating a path towards the creation of bespoke datasets tailored for the trends of 5G-Advanced security research. © 2024 IEEE.

关键词： 5G mobile communication systems

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Security in remote access, based on Zero Trust Model concepts and SSH authentication with signed certificates 11

Security in remote access, based on Zero Trust Model concept...

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Advanced Topics in Optoelectronics, Microelectronics, and Nanotechnologies XI 2022

作者： Iță, Cristina-Raluca Constantinescu, Rodica-Claudia Vlădescu, Alexandru Alexandrescu, Bogdan Information and Computer Systems Engineering POLITEHNICA University of Bucharest Romania Applied Electronics and Information Engineering Dept. POLITEHNICA University of Bucharest Romania

ISBN: (纸本)9781510660939

This paper aims to resume the information on the various ways in which security can be achieved when it comes to accessing external resources from the outside through company devices or personal devices. When planning security policies, it is essential to start with the idea that anything outside is exposed to the risk of infection. We will analyze the Zero Trust model and other security concepts in order to use them for remote access. The model has been designed to adapt to the modern needs of the workforce and employers, including remote work in terms of maximum cyber security, minimizing the risk of resource exploitation (people, devices, applications or data). In order to make the transition to such a model, this paper will implement and test a solution for remote management of resources (applications, servers), which implements some of the principles of Zero Trust architectures, starting from the classic version SSH (Secure Shell) access. The solution involves accessing, securing and authorizing a secure virtual machine via SSH, and then securing access to production resources. The technical mechanism by which these operations are performed presupposes that after authentication on the buffer machine a user certificate is automatically requested which will be signed by a certification authority. This certificate contains the group to which the operator belongs so that, by presenting this certificate, it is allowed to authenticate, authorize and audit access to the resources that will be managed by the user in that session. © 2023 SPIE.

关键词： Authentication

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Efficient GPU-based Gridding and Segmentation of Microarray Images via K-Means and Fuzzy C-Means

Efficient GPU-based Gridding and Segmentation of Microarray ...

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2023 International Conference on Data Science, Agents and Artificial Intelligence, ICDSAAI 2023

作者： Eric Clapten, J. Sasimekala, M.M. Rajeswari, C. Sanjay Kumar, K. Communication Engineering Department of Electronics Chennai India Department of Biomedical Engineering Chennai India Chennai Institute of Technology Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350348910

The analysis of microarray image helps in identifying new genes that enables us to understand their functions and gene expression levels simultaneously at different conditions. This is also useful in diagnosing the various diseases and helps in develop the treatment for the required disease. In general it has 3 stages, the first one is gridding, and the second segmentation and the third one is intensity extraction. In this paper we are going to discuss various machine learning techniques in segmenting the microarray images. This proposed algorithm eliminates the noise and enhances the image quality by finding the nearest spots in segmentation and enhancing the spot using KNN algorithm. The performance can be improved further by the efficient utilization of a graphics processing unit (GPU). It is also shown that the method can be employed to produce a model on health based on a PET-MRI dataset which can be utilized to automatically detect pathology in the imaging. © 2023 IEEE.

关键词： Graphics processing unit

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PV Systems Generation Prediction Considering Cloud Cover Using Deep Learning Techniques

PV Systems Generation Prediction Considering Cloud Cover Usi...

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2024 IEEE Global Energy Conference, GEC 2024

作者： Wadi, Mohammed Salemdeeb, Mohammed Jouda, Mohammed Tur, Mehmet Rida Ayachi, Bilel Husain, Nour Electrical & Electronics Engineering Dept. Istanbul Sabahattin Zaim University Istanbul Turkey Electrical Engineering Dept. Istanbul Sabahattin Zaim University Istanbul Turkey Dept. of Electrical and Electronic Engineering Batman University Batman Turkey Electrical and Electronic Eng. University 20 August 1955 Skikda Algeria Computer Engineering Dept. Al-Azhar University Gaza Gaza Palestine

ISBN: (纸本)9798331532611

Numerous environmental elements, including sun irradiation, temperature, shade, wind speed, and others, can significantly influence the output of photovoltaic (PV) systems. Solar generation forecasts across various time ranges are required to meet demand and grid restrictions. Short-term predictions are essential for energy trading, real-time control, and grid balancing. This paper presents a concise overview of shading due to cloud cover on the generation of PV systems. Furthermore, the convolutional neural network (CNN) deep learning model predicts PV generation by considering cloud movement over a specific area. The results demonstrate that cloud cover significantly impacts the generation of PV systems. Consequently, PV power generation forecasting is essential for enhancing the stability, quality, and reliability of smart grids and modern power systems. The suggested deep learning model occupies 12% of the memory size of the state-of-the-art model. The suggested model surpasses these models in the MSE, RMSE, and MAE test set metrics, yielding values of 1 KW, 2.37 KW, and 1.35 KW, respectively. ©2024 IEEE.

关键词： Cloud Cover CNN Deep Learning Impact of Cloud Shade PV Generation

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An Efficient Approach of Drowsiness Detection Based on ResNet50 and Xception Architectures 3

An Efficient Approach of Drowsiness Detection Based on ResNe...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： El-Nabi, Samy Abd El-Rabaie, El-Sayed M. Emam, Ahmed Ramadan, Khalil F. Faculty of Computer Science and Engineering Dept. of Artificial Intelligence Engineering South Sinai46511 Egypt Menoufia University Faculty of Electronic Engineering Dept. of Electronics and Electrical Communications Menouf32952 Egypt Menoufia University Dept. of Computer Science and Math Faculty of Science Menoufia Egypt

ISBN: (纸本)9798350323511

This paper delves into a critical aspect of road safety by investigating a method to detect drowsiness in images. The accurate utilization of this technology by fatigued drivers holds the potential to prevent numerous fatal accidents, as the proposed models exhibit swift responsiveness in identifying instances of driver drowsiness. Within the realm of eye closure detection, two drowsiness models, namely ResNet50 and Xception, are employed to portray various eye state classifications. Nonetheless, the scarcity of readily available and reliable eye datasets poses a formidable challenge. Leveraging the power of ResNet50, deep facial features are extracted, resulting in an impressive accuracy of 98.06%. Similarly, the utilization of Xception yields a commendable accuracy of 95.69% when evaluated with the MRL dataset. These experimental outcomes firmly establish the higher accuracy and cost-effectiveness of eye closure estimation, thereby underscoring the efficacy of the proposed framework for drowsiness recognition. © 2023 IEEE.

关键词： Cost effectiveness

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Advanced Machine Learning Techniques for Enhancing Data Security in Cloud Computing Systems 5

Advanced Machine Learning Techniques for Enhancing Data Secu...

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5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Dhinakaran, M. Sundhari, M. Ambika, S. Balaji, V. Rajasekaran, R.Thalapathi Galgotias College of Engineering & Technology Department of Electronics and Communication Engineering Uttar Pradesh Greater Noida India Grt Institute of Engineering and Technology Dept. of Computer Science and Engineering Tamil Nadu Tiruttani India E. G. S. Pillay Engineering College Department of Information Technology Tamil Nadu Nagapattinam India Chennai India Saveetha School of Engineering Simats Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350383522

In the age of cloud computing, data stored and processed in the cloud must be secure. This study examines how powerful machine learning can secure cloud computing data. Three trials assessed different machine learning models in this setting. Experiment 1 used a Random Forest model and achieved 95% accuracy, 0.92 precision, 0.96 recall, and 0.94 F1 Score. This shows that the model can accurately categorize security threats with a good balance of true and false positives. A Deep Neural Network (DNN) improved accuracy to 97% in Experiment 2. Precision, recall, and F1 Score values of 0.94, 0.98, and 0.96 demonstrate the DNN's ability to discriminate threats from normal activity. The model captures complicated patterns well, making it a powerful cloud security tool. Security analysis using reinforcement learning, specifically Q-learning, was introduced in Experiment 3. The model's 88% detection rate showed its capacity to identify threats, but its 0.05 false positive rate created a tradeoff between true and false positives. With the 0.12 false negative rate, one can infer improvements in threat detection accuracy. These results indicate that state-of-the-art machine learning is capable of protecting cloud data. The Random Forest and Deep Neural Network models have very high accuracy balanced with reasonable precision-recall trade-offs, whereas reinforcement learning through Qlearning shows promise but needs modification to improve the model's performance in terms of both accuracy and false positive rates. While rising threats need constant adaptation and learning, the model should also fulfill security needs. This study helps formulate a secure cloud computing infrastructure that can stand threats of change. © 2024 IEEE.

关键词： Cloud Computing Data Security Machine learning Q-Learning

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Administrator Controlled Timetable Based Automatic Facial Recognition Attendance System

Administrator Controlled Timetable Based Automatic Facial Re...

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2023 International Conference in Advances in Power, Signal, and Information Technology, APSIT 2023

作者： Dash, Ankit Jena, Siba Prasad Gantayet, Amaresh Siksha O Anusandhan Deemed to Be University Dept. of Electrical and Electronics Engineering Bhubaneswar India Siksha O Anusandhan Deemed to Be University Dept. of Computer Science & Engineering Bhubaneswar India

ISBN: (纸本)9798350339369

A facial recognition attendance system is a technology-based solution for automating the process of taking attendance in schools, offices, or other organizations. The present work mainly focuses on image capturing, training and recognition in real-time using free source Python modules. The system uses computer vision algorithm such as the Open Source computer Vision (OpenCV) Library to recognize and identify individuals based on their facial features. Additionally, the Numerical Python (NumPy) library is used to store and manipulate arrays of facial recognition data, such as feature vectors or embeddings. The Tkinter GUI is employed as an interface for managing attendance and allows the administrator to access the system and view attendance records for individual students. The ESP32-CAM module and thin-film-transistor liquid-crystal (TFT) display has been used together to provide a live video stream, while the server processes the video and records attendance. This system would improve accuracy of attendance records because it will remove all the hassles of roll calling (in case of classroom attendance of students) and will save valuable time of the teachers as well as students. © 2023 IEEE.

关键词： Open systems

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Mitigation and Comparison of Chromatic Dispersion at Distinct Frequencies Using Hybrid Model at A Bit Rate of 100Gbps over 120Km Distance 6

Mitigation and Comparison of Chromatic Dispersion at Distinc...

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6th International Conference on Information Systems and computer Networks, ISCON 2023

作者： Verma, Amita Kumar, Sushil Singh, Inder Kumar, Ashwani Saini, Raj Kumar Moharana, Saubhagya Kumar Shoolini University School of Core Engineering Dept. Electronics and Communication Engineering Solan India Shoolini University School of Core Engineering Dept. Mechanical Engineering Solan India University of Petroleum and Energy Studies School of Computer Science Engineering Dehradun India

ISBN: (纸本)9798350346961

In this paper, a Hybrid model is proposed for compensation of chromatic dispersion which can ensure the high bit rate, a higher Q-factor and lower BER for long distance optical communication. It can be achieved by taking into consideration the major limiting factors like dispersion, attenuation, and other linear and non-linear effects of optical fiber. Chromatic dispersion is the principal deterrents in high velocity information transmission thus ought to be compensated by different methodologies all through the transmission system. This study presents the simulation results of a proposed hybrid model which is a combination of Uniform Fiber Bragg Grating (UFBG) and Electronic Dispersion Compensation (EDC) along with Erbium Doped Fiber Amplifier (EDFA). This model is designed to mitigate the effect of chromatic dispersion present in optical fiber communication system. Here, the analysis is carried out by varying the input carrier frequency range from 193.1 THz to 193.5 THz and then comparing their outcomes to get the satisfactory result. As a result, we find that the quality factor rises monotonically as the frequency is increased up to some level and then it undergoes an abrupt fall along with a rise in BER. The simulation is done with the help of Opti-System 7.0 simulator.. © 2023 IEEE.

关键词： Fiber Bragg gratings

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IoT based Cold Supply Chain for Food Processing 3

IoT based Cold Supply Chain for Food Processing

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3rd IEEE Asian Conference on Innovation in Technology, ASIANCON 2023

作者： Abishek, R. Harish Chensudar, K. Lokesh, R. Jacob Paul, P. Balamurugan, Kavitha Kcg College of Technology Dept. of Electronics and Communication Engineering Chennai India Kcg College of Technology Dept. of Computer Science and Engineering Chennai India Kcg College of Technology Dept. of Ece Chennai India

ISBN: (纸本)9798350302288

Food is one of the essential needs for human survival. In the present era, there is a rapid increase in the population and emerging growth of technology in the developing countries around the globe. Due to the population increase, there is a demand for an abundant food supply. Most of the food products have a shorter shelf life. It is necessary to maintain food products at a certain temperature so that they can be preserved for a longer duration. There arises a necessity to develop a device that can monitor and maintain the food products. This research seeks to design a cold storage device that can monitor essential food storage specifications such as temperature, humidity, pressure, light and gas compositions like ammonia, methane, carbon dioxide and so on. The cold storage also alerts the user when a parameter passes through the threshold value. The cold storage device can be instated in a moving truck carrying food products as well as in a storage warehouse. It also has a Global Positioning System (GPS) module for the purpose of tracking the real time location of the transporting truck and it also provides a theft alert in the warehouse. Further the user can control the exceeded threshold value from any remote location. © 2023 IEEE.

关键词： Supply chains

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