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1st IEEE International Conference on Automation, Computing and Renewable Systems, ICACRS 2022

作者： Hanumanthakari, Sudheer Kumar Pullela, S.V.V.S.R. Bhukya, Shankar Nayak Vijayalakshmi, K. Rehan Ahmad, S. Kumar, Narendra Department of Electronics and Communication Engineering Faculty of Science and Technology IFHE Telangana Hyderabad501203 India Department of Computer Science and Engineering Aditya College of Engineering Andhra Pradesh Surampalem533437 India CMR Technical Campus Telangana Hyderabad501401 India Department of Computer Science and Engineering Sri Sai Ram Institute of Technology Tamil Nadu Chennai600044 India Department of Zoology Hiralal Mazumdar Memorial College for Women West Bengal Kolkata700035 India Department of Electronics and Communication Engineering RNS Institute of Technology Karnataka Bengaluru560098 India

ISBN: (纸本)9781665460842

The medical field requires constant updating and the usage of advanced technology. This is due to the fact that different kinds of diseases as increased as the population of world has increased. S cientists and doctors try to come up with different types of preliminary tests and other diagnostic technologies to detect the presence of a disease in its early stages. Though the preliminary test for different health issues is different it all consists of the measurement of basic vital parameters like temperature and the d pressure etc. To ease this process this study aims the development a circuit which is capable of constantly monitoring the vitals of a patient and displaying the result to an attendant. The principal flow of the circuit is initiated by the sensors that are instantly fastened to the patient. The sensors continuously gather and transmit the patient's vital indicators to the node MCU model. The AWS cloud then receives data from the model. The platform compares the collected data to the specified value. If no anomalies are found, the cloud simply records the data before stopping. However, if there are any anomalies, the cloud orders the node MCU model to activate the emergency output gadgets, such as the buzzer and the LED, to immediately alert the attendant or the nurses. A website is also created, and it is utilised to display the patient's information as well as vital records. Along with the patient's vital signs, it also shows an emergency condition when one of the patients has certain irregularities in one or more of the parameters. The physicians and other staff can keep an eye on all the patients at once without having to frequently visit a specific room thanks to this display of emergency information. This system is anticipated to be enhanced in the future with additional capabilities including automated parameter control without human intervention. In other words, the temperature is regulated when the ambient humidity or the body's temperature is

关键词： Internet of things

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High Gain, E-Shaped Microstrip Antenna with Two Identical Slits for 5G Applications in the 60 GHz Band

High Gain, E-Shaped Microstrip Antenna with Two Identical Sl...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Ala'a N. S. Ali AbdulGuddoos S. A. Gaid Mamoon M. Saeed Rashid A. Saeed Burkan Hawash Dept. of Communications & Computer Faculty of Engineering & Information Technology Taiz University Taiz Yemen Dept. Communications & Electronics Engineering Faculty of Engineering University of Modern Sciences (UMS) Sana'a Yemen Dept. of Computer Engineering College of Computers & Information Technology Taif University Taif Saudi Arabia Faculty of Information Science & Technology Universiti Kebangsaan Malaysia (UKM) Selangor Malaysia

This article presents a simple, high-gain, E-shaped antenna suitable for 5G applications in the unlicensed 60 GHz band, characterized by high absorption and path losses. In order to optimize the reflection coefficient performance, enhance the gain, and adjust the resonance frequency of the proposed antenna, two identical slits are incorporated into the front edge of the radiating patch. The proposed structure is built on a Rogers RT/Duroid 5880 dielectric substrate, characterized by a thickness of 0.118 mm, a dielectric constant of 2.2, and a tangent loss of 0.0009. The optimized design with a compact size of 3.8 x 6 x 0.118 mm 3 achieves an impedance bandwidth (< -10 dB) of 2.135 GHz, extending from 58.876 GHz to 61.011 GHz. As for gain, it changes slightly from 9.17dB at the lower frequency to 9.66dB at the higher frequency and 9.5dB at the center frequency of the operating band. In addition, the antenna achieves nearly consistent radiation efficiency over its operational band, ranging from 87.9% at the highest frequency to 89.2% at the lowest frequency and 88.6% at the center frequency. The design exhibits a good impedance matching between the radiating patch and the feed line, as indicated by the low (VSWR) of 1.01919 and a high return loss of 40.438 dB at the resonance frequency. Although the proposed design has good radiation characteristics, the operating impedance bandwidth covers only a part of the 60 GHz band (57 GHz to 64 GHz), a shortcoming to be overcome in future work. Moreover, design, simulation, and optimization processes are carried out using the CST simulator to ensure that design objectives are met. On the other hand, the HFSS simulator is employed to validate CST simulation results, thus providing a robust validation framework for the antenna design.

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Speech Detection and Comparison using Different Feature Extraction Method for Correct Verification

Speech Detection and Comparison using Different Feature Extr...

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Communication, Control and Intelligent Systems (CCIS)

作者： Shrikant Upadhyay Binod Kumar Rajan Singh Md. Irfan Alam Barkha Kumari Binita Roshima Hinz Department of Electronics and Communication Engineeing MLR Insitute of Technology Hyderabad India Facultyt of CSE & IT Jharkhand Rai University Ranchi India Department of Electronics and Communication Engineering MLR Institute of Technology Hyderabad India Faculty of CSE & IT Jharkhand Rai University Ranchi India Department of Computer Science and Engineering (AI & AIML) GH Raisoni College of Engineering and Management Pune Department of Computer Science and Engineering-Cyber Security RTC Institute of Technology Ranchi India

ISBN: (数字)9798331528201

ISBN: (纸本)9798331528218

Mental status through physical appearance identification is not possible as it does not give complete status of any human. Using voice and considering quality extraction of talked it is quite easy to predict the mental behavior and internal variation that will help the doctor related with medical treatment that support them to give proper treatment to person. Hindi is the natural language of India and large community of population talk and speaks this language to exchange and communicate. Various inputs like specific feature, images and vital report of serious person and it is one of the important facts sources for deep training or gaining systems. In this research paper we try to identify the speech signal under different scenario like gun noise, car noise etc. following different feature extraction approaches and compare it for its proper verification. This verification may help to enhance the quality of speech in different adverse scenario and make the speech detection easy. Here, the comparison has been done with various feature extraction method and the results reflects that MFCC has good efficiency of 95% and with a low error rate of 2% compared to other approach. For analysis Hindi voice sample were used for the experimental analysis for 50 samples.

关键词： Voice activity detection Training Error analysis Simulation Noise Natural languages Speech enhancement Feature extraction Object recognition Mel frequency cepstral coefficient

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An Ensemble MLP-RF Model for the Prediction of DG-MOSFETs: Addressing Fabrication Process Variations

An Ensemble MLP-RF Model for the Prediction of DG-MOSFETs: A...

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International Conference on VLSI Design

作者： Vaikunth Muthuraman Khushwant Sehra Vandana Kumari Manoj Saxena Department of Computer Science and Engineering College of Engineering Guindy Anna University Chennai India Department of Electronics and Communication Engineering Faculty of Technology University of Delhi New Delhi India Department of Electronics Maharaja Agrasen College University of Delhi New Delhi India Department of Electronics Deen Dayal Upadhyaya College University of Delhi New Delhi India

ISBN: (数字)9798331522445

ISBN: (纸本)9798331522452

To improve the efficacy of semiconductor device characteristics prediction, this work proposes a machine learning (ML) model that can predict drain current, gate-source capacitance, and drain-gate capacitance. The model displays outstanding accuracy, thus, allowing for the prognosis of device characteristics with reliability. Compared to the simulations in technology computer-Aided Design (TCAD), this ML approach can be considered a speedy alternative. To the best of the authors' knowledge, this manuscript specifically proposes a novel approach to utilize the MLP-RF (ensemble of multilayer perceptron (MLP) regressor and random forest (RF) regressor) model for Double-Gate MOSFET. The accuracy of the ensemble model is verified by calculating the mean squared error, root mean squared error, and mean coefficients of determination values. In addition, an MLP-RF classification model was implemented that would take, as input, characteristics of devices whose channel lengths are unknown and classify them into the most probable devices from a set of devices whose channel lengths are known thereby modeling the process variations during the fabrication process. The results thus encourage further interdisciplinary endeavors to benefit the semiconductor industry.

关键词： Semiconductor device modeling Fabrication Accuracy Computational modeling Predictive models Logic gates Very large scale integration Capacitance Scattering parameters Testing

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Chimp Optimization Algorithm Based Feature Selection with Machine Learning for Medical Data Classification

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computer Systems Science & engineering 2023年第12期47卷 2791-2814页

作者： Firas Abedi Hayder M.A.Ghanimi Abeer D.Algarni Naglaa F.Soliman Walid El-Shafai Ali Hashim Abbas Zahraa H.Kareem Hussein Muhi Hariz Ahmed Alkhayyat Department of Mathematics College of EducationAl-Zahraa University for WomenKarbalaIraq Biomedical Engineering Department College of EngineeringUniversity ofWarith Al-AnbiyaaKarbalaIraq Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science Department Security Engineering LabPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt College of Information Technology Imam Jaafar Al-Sadiq UniversityAl-Muthanna66002Iraq Department of Medical Instrumentation Techniques Engineering Al-Mustaqbal University CollegeHillah51001Iraq Computer Engineering Department Mazaya University CollegeDhi QarIraq College of Technical Engineering the Islamic UniversityNajafIraq

Datamining plays a crucial role in extractingmeaningful knowledge fromlarge-scale data repositories,such as data warehouses and *** rule mining,a fundamental process in data mining,involves discovering correlations,patterns,and causal structures within *** the healthcare domain,association rules offer valuable opportunities for building knowledge bases,enabling intelligent diagnoses,and extracting invaluable information *** paper presents a novel approach called the Machine Learning based Association Rule Mining and Classification for Healthcare Data Management System(MLARMC-HDMS).The MLARMC-HDMS technique integrates classification and association rule mining(ARM)***,the chimp optimization algorithm-based feature selection(COAFS)technique is employed within MLARMC-HDMS to select relevant *** by the foraging behavior of chimpanzees,the COA algorithm mimics their search strategy for ***,the classification process utilizes stochastic gradient descent with a multilayer perceptron(SGD-MLP)model,while the Apriori algorithm determines attribute *** propose a COA-based feature selection approach for medical data classification using machine learning *** approach involves selecting pertinent features from medical datasets through COA and training machine learning models using the reduced feature *** evaluate the performance of our approach on various medical datasets employing diverse machine learning *** results demonstrate that our proposed approach surpasses alternative feature selection methods,achieving higher accuracy and precision rates in medical data classification *** study showcases the effectiveness and efficiency of the COA-based feature selection approach in identifying relevant features,thereby enhancing the diagnosis and treatment of various *** provide further validation,we conduct detailed experiments on a benchmark

关键词： Association rule mining data classification healthcare data machine learning parameter tuning data mining feature selection MLARMC-HDMS COA stochastic gradient descent Apriori algorithm

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Validating IP Reputation in Cloud Firewall Systems Using Machine Learning Driven Signature Generation and Detection Techniques

Validating IP Reputation in Cloud Firewall Systems Using Mac...

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IEEE Industrial electronics and Applications Conference (IEACon)

作者： NW Chanka Lasantha Valmik Tilwari MWP Maduranga Ruvan Abeysekara Nilotpal Chakraborty Debashree Sharma Faculty of Graduate Studies IIC University of Technology Phnom Penh Cambodia Department of Electronics & Communication Engineering Indian Institute of Information Technology Guwahati India Department of Software Engineering Sri Lanka Technology Campus Padukka Sri Lanka Department of Computer Science Engineering Indian Institute of Information Technology Guwahati India

ISBN: (数字)9798350382976

ISBN: (纸本)9798350382983

This paper offers a new approach to validation for IP address reputation (IPR) using dynamic signatures achieved through the application of machine learning (ML) to conduct an accurate detection of malicious IPs. The proposed solution connects to the Amazon Web Services (AWS) Web Application Firewall (WAF) to improve security by deploying artificial intelligence (AI) models and natural language (NL) processing for automation of information extraction from IP-related information saved in the AWS object storages. All these lead to minimization of the number of false positives, real-time feedback, and optimization of IP reputation checking. The experimental outcome proves the capability of the proposed system to mitigate the IP address of the attacker and improve the protection of web applications against cybercrimes. This new approach is much advanced and a major leap ahead of other conventional IP reputation techniques, which offer a good protection shield against spam, DDoS, and other such evils.

关键词： Radio frequency Accuracy Firewalls (computing) Web services Natural languages Real-time systems IP networks Protection computer crime Optimization

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Studying Physical Properties of Gas-To-Liquid Compared with Mineral Oil under Accelerated Thermal Aging

Studying Physical Properties of Gas-To-Liquid Compared with ...

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International Middle-East Power System Conference, MEPCON

作者： Mohamed Badawi Shimaa A. Ibrahim Diaa-Eldin A. Mansour Adel El-Faraskoury Sayed A. Ward Department of Electrical Engineering Faculty of Engineering at Shoubra Benha University Egypt Electrical Power Engineering Department School of Electronics Communications and Computer Engineering Egypt-Japan University of Science and Technology Alexandria Egypt Electrical Power and Machines Engineering Department Faculty of Engineering Tanta University Tanta Egypt Extra High Voltage Research Centre Egyptian Electricity Holding Company Department of Electrical Engineering Faculty of Engineering Delta University for Science and Technology Egypt

ISBN: (数字)9798350379648

ISBN: (纸本)9798350379655

Mineral oil (MO) has long been utilized in high-voltage power transformers, as a cooling and dielectric medium; because of it is availability as it is extracted from fossil oil. Recently, Gas-To-Liquid (GTL) has a significant increase in use due to its superior performance, its purity and chemical consistency over conventional mineral oils. This paper presents examination of the temperature effects on mineral (Diala S2) and gas to liquid (Diala S4) oil physical properties. Fresh oil and aged oil samples, of the two oil types, have been tested in this paper. Accelerated thermal aging test have been conducted in laboratory to simulate the heat stress experienced by transformers during operation. Three aged oil samples, of the two types of oil, have been prepared in laboratory (3, 6, and 10 days). Density and viscosity measurements were performed on these fresh and aged oil samples. The results concluded that during the initial years, chemical changes cause a minor drop in the density of the mineral oil. Conversely, GTL oil has superior qualities since it stays more stable over time. Over time, the density of both oils exhibits comparable stability, however GTL oil is favored over mineral oil due to its consistency and stability. Diala S4 and Diala S 2 oils have higher viscosity, suggesting superior cooling performance before aging. However, Diala S 2 dropped to 10.649 mm 2 /s after three years, indicating its long-term consequences. Diala S4 oil had higher flow efficiency, enhancing transformer cooling and insulating performance within thermal aging. This is due to GTL oil, derived from natural gas, has higher resistance to chemical deterioration, allowing it to sustain its viscosity stability over extended periods. These results emphasize the importance of choosing oils, especially GTL oil type based on their apparent and physical stability over time.

关键词： Viscosity Cooling Oils Power system stability Oil insulation Stability analysis Minerals Thermal stability Chemicals Power transformer insulation

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Hybrid Machine Learning Approach for Enhanced Vulnerability Detection in Cloud Environments Using NIST and MITRE Frameworks 5

Hybrid Machine Learning Approach for Enhanced Vulnerability ...

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5th International Conference on Advanced Research in Computing, ICARC 2025

作者： Lasantha, N W Chanaka Maduranga, M.W.P. Abeysekara, Ruvan Tilwari, Valmik Chakraborty, Nilotpal Sharma, Debashree Iic University of Technology Faculty of Graduate Studies Phnom Penh Cambodia University of Sri Jayewardenepura Department of Electrical and Electronic Engineering Nugegoda Sri Lanka Bcas Campus Faculty of Computing Colombo Sri Lanka Indian Institute of Information Technology Department of Computer Science Engineering Guwahati India Indian Institute of Information Technology Department of Electronics & Communication Engineering Guwahati India

ISBN: (纸本)9798331530983

Cloud security is challenged by constant adaptive cyber threats and traditional detection methods lack real time adaptability. In this paper, we propose a new hybrid ML approach stitching data from National Institute of Standards and technology (NIST) and MITRE Adversarial Tactics, Techniques and Common Knowledge (ATT&CK) databases together. In contrast to existing methods, this framework combines, in unique and unprecedented fashion, ensemble ML models and Realtime data processing for increased detection accuracy and reduced false positives. This approach addresses specific challenges in the cloud environments and by leveraging standardised frameworks, it offers actionable audiences for efficient and effective vulnerability management process. The framework is validated by the experimental results which prove its robustness to evolution of the cybersecurity demands. © 2025 IEEE.

关键词： Cyber attacks

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Secrecy Performance and Power Allocation for Cooperative Vehicular Relaying Networks in the Presence of Interference

Secrecy Performance and Power Allocation for Cooperative Veh...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Mohamed G. Abd El Ghafour Ahmed H. Abd El-Malek Mohammed Abo-Zahhad Department of Engineering Mathematics and Physics Faculty of Engineering Alexandria University Alexandria Egypt School of Electronics Communications & Computer Engineering Egypt-Japan University of Science & Technology Alexandria Egypt Electrical Engineering Department Faculty of Engineering Assiut University Assiut Egypt

This paper investigates the secrecy performance of cooperative vehicular relaying networks in the presence of a source of interference. The network consists of a fixed source node, a fixed destination, a fixed source of interference, a mobile relay, and a mobile passive eavesdropper. Except for the channel from the relay to the eavesdropper, all of the channel coefficients between the nodes are represented as Nakagami-m fading channels. We construct closed-form formulas for the secrecy outage probability (SOP), the asymptotic SOP (ASOP), and the probability of non-zero secrecy capacity (PNZSC). Furthermore, a proposed power allocation model is presented to reduce the SOP about the source and relay transmission powers. The impact of the channel condition, the secrecy data rate threshold, and the strength of interference on the secrecy performance are presented and demonstrated. In addition, the proposed power allocation model enhances the system secrecy performance compared to the equal power distribution model.

关键词： Fading channels Closed-form solutions Computational modeling Power distribution Interference Probability Power system reliability

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ROF systems performance efficiency based on continuous phase frequency shift keying phase modulation scheme

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Journal of Optical Communications 2024年第0期45卷 s417-s429页

作者： Eid, Mahmoud M. A. Sorathiya, Vishal Lavadiya, Sunil Abd El-Aziz, Ismail A. Asaduzzaman, Sayed Rehana, Hasin Ali Mohammed Ibrahim, Abd El-Naser Rashed, Ahmed Nabih Zaki Department of Electrical Engineering College of Engineering Taif University Taif Saudi Arabia Department of Information and Communication Technology Marwadi University Rajkot India Benha Faculty of Engineering Benha University Benha Egypt Department of Computer Science and Engineering Rangamati Science and Technology University Rangamati Bangladesh Department of Computer Science and Engineering University of Dhaka Dhaka Bangladesh Higher Institute of Electronic Engineering Belbeis Ministry of Higher Education 10th of Raman Belbeis Egypt Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf32951 Egypt

Radio over fiber (ROF) technique has been presented with hybrid ordinary modulation technology to achieve improvement in optical communication network performance. Fiber Bragg grating (FBG) is employed in single mode (SM) optical channel in order to enhance the transmission environment with dispersion compensation. The continuous phase frequency shift keying phase modulation (CPFSKPM) technique is included in this study. Both previous and proposed models have been inspected and investigated. Min. bit error rate (BER), max. Q factor, signal/noise ratio (SNR), received power (RP), and noise figure (NF) are the most essential parameters able to explain the behavior performance of optical communication network model. © 2021 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Fiber Bragg gratings

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