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International Conference on Advanced engineering Theory and Applications, AETA 2022

作者： Le, Si-Phu Van Nguyen, Minh-Sang Nguyen, Hong-Nhu Do, Dinh-Thuan Voznak, Miroslav Fazio, Peppino Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava 17. Listopadu 2172/15 Ostrava708 00 Czech Republic Faculty of Electronics Technology Industrial University of Ho Chi Minh City Ho Chi Minh City Viet Nam Faculty of Electronics and Telecommunications Saigon University Ho Chi Minh City Viet Nam Department of Electrical and Computer Engineering The University of Texas at Austin AustinTX78712 United States DSMN Ca’ Foscari University Via Torino 155 VE Mestre30172 Italy

ISBN: (纸本)9789819987023

In this paper, we investigate an application of the Intelligent Reflecting Surface (IRS). This technology has emerged as promising and low-cost technology for 6G networks improving wireless communications by collecting dispersed radio waves and redirecting them to the intended destination users. We characterize the achievable rate when multiple IRSs are utilized in the manner of Decode-and-Forward (DF) relaying. Our capacity performance analysis is based on the Rayleigh fading model with perfect Channel State Information (CSI) and we optimize the IRS configuration considering the ergodic capacity of the proposed scheme, derived by analyzing the statistics of CSI, which provides useful insights for practical design. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Rayleigh fading

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Flexible Consensus Mechanism for Current Allocation in DC Microgrid

Flexible Consensus Mechanism for Current Allocation in DC Mi...

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2023 International Symposium on Electrical and electronics engineering, ISEE 2023

作者： Tran, Khoa Dang Nguyen Ly, Trinh Thi Hoang, Khoa Truong Phuoc, Hoa Truong Le, Nhuan An Nguyen, Hung Duc Ho Chi Minh City University of Technology VNU-HCM Faculty of Electrical and Electronics Engineering Ho Chi Minh City Viet Nam University of Science Vietnam National University Faculty of Physics and Engineering Physics Department of Physics and Computer Science Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350315486

Renewable energy sources (RESs) have become the predominant trend in the development of energy systems in many countries. To coordinate RESs, microgrids have emerged as an efficient and optimal solution. However, the microgrid is facing the problem of inaccurate power sharing between the generators. To address the issue, this paper proposes a control technique that combines a dynamic consensus with droop control algorithms. The proposed method calculates current sharing error by utilizing current values and consensus algorithm. Then, an external current-sharing controller is adopted to regulate the droop parameter in an inner controller for improving the current sharing among RESs. By applying the proposed control method, the current sharing accuracy is achieved in the microgrid system under different load conditions. The proposed technique is analyzed and evaluated with the scale-down microgrid consisting of three distributed generators. The simulation results of the scale-down microgrid are obtained from the PLECS simulation platform. © 2023 IEEE.

关键词： Controllers

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An Improved Convolutional Neural Network for Medical Image Segmentation

An Improved Convolutional Neural Network for Medical Image S...

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2023 IEEE International Conference on Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario, ICPSITIAGS 2023

作者： Obaidi Al-Khafaji, Safaa Hakeem Palle, Kowstubha Thingbaijam, Lenin Prasad, P. Venkata Mallala, Balasubbareddy Pund, Sachin College of Dentistry University of Babylon University of Babylon Computer Science Babylon Iraq Chaitanya Bharathi Institute of Technology Department of Electrical and Electronics Engineering Hyderabad India Mlcu Faculty It India Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India

ISBN: (纸本)9798350329773

This paper provides a progressed convolutional neural community (CNN) version for medical picture segmentation. It specializes in improving the accuracy and speed of today's segmenting of scientific photos and improving modern semantic segmentation of first-rate present-day clinical photos. Modern accuracy is improved by introducing pre-processing layer, residual connection, attention module, and up sampling layer to the CNN. The stepped-forward overall performance state-of-the-art pace is achieved through dual-project cutting-edge, wherein the segmentation task is divided into two sequential sub-obligations, modern-day semantic segmentation and shape regression. The improved version is examined on publicly available scientific datasets, achieving 49a2d564f1275e1c4e633abc331547db segmentation performance. The results show that the proposed method is robust, green, and generalizable.. © 2023 IEEE.

关键词： Semantic Segmentation

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A Novel RIS-Empowered Base Station: A Practical Implementation and Experimental Validation

A Novel RIS-Empowered Base Station: A Practical Implementati...

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2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Park, Je Hyeon Kim, Suhyun Amri, Muhammad Miftahul Tran, Nguyen Minh In Kim, Dong Choi, Kae Won Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of Faculty of Electronics and Telecommunications Vnu - University of Engineering and Technology Hanoi Viet Nam

ISBN: (纸本)9798350368369

This article presents a novel reconfigurable intelligent surface (RIS)-integrated base station (BS) by deploying an RIS very close to the base station antennas (BAs), within its radiative near-field range. We propose a practical algorithm to maximize the performance of uplink communications with the proposed RIS-integrated BS while maintaining reasonable complexity. Furthermore, we have implemented a testbed to experiment with the proposed RIS-integrated BS-based uplink multiple-input-multiple-output (MIMO) system. The experimental data validates the performance of the proposed RIS-integrated BS-based uplink MIMO system. © 2025 IEEE.

关键词： multi-beam design reconfigurable intelligent surface (RIS) RIS-integrated base station

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Evaluating importance of AI in Robotics and Automation in Healthcare for Different age Groups 1

Evaluating importance of AI in Robotics and Automation in He...

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1st International Conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Abu Eid, Aws Ismail Pethkar, Rajendra Huda, Bintul Patil, Jaykar Bhaskar Gatla, Ranjith Kumar Kumbhar, Ramchandra Arab Open University Faculty of Computing Studies Amman Jordan Jaywant College of Engineering and Polytechnic Department of Mechanical Engineering Karad India Sharda University Department of Computer Science & Technology Srinagar India Jaywant Institute of Management Karad India Institute of Aeronautical Engineering Department of Electrical and Electronics Engineering Hyderabad India Department of Radio-Diagnosis Karad India

ISBN: (纸本)9798350360707

Nowadays robotics is mostly used in the world. There are many industries which used robots for reducing time and to have high precision of work. The use of artificial intelligence is now increasing which helps in automations and processing of machines. Thus, the focus of study is to find the different applications of automation of robotics (i.e. robotic process automation) in the field of healthcare and its impact on the employment of medical field. Four major categories can be used to group AI applications in healthcare: expressive, analytical, prognostic, and prescriptive. The only way to close the skills gap in the healthcare industry is to increase the application of artificial intelligence. Hospitals are developing mental commit robots to treat their patients. Through physical contact, these robots can have an impact on humans' psyche, physiology, and social interactions. Thus, in coming time most of the healthcare industry will be with the robots which will reduces the human interventions with the patients through one of the host servers. © 2024 IEEE.

关键词： Medical robotics

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Applying Data Science to Real-Time Data Analysis Problems 1

Applying Data Science to Real-Time Data Analysis Problems

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1st IEEE International Conference on Emerging Research in Computational Science, ICERCS 2023

作者： Jain, Narendra Kumar Kumar, P. Kishore Singh, Shweta Katyal, Ashu Srisainath, R. Karnik, Madhuri P. Vivekananda Global University Department of Civil Engineering Jaipur India Faculty of Engineering and Technology Department of Electrical and Electronics Engineering Karnataka Bangalore India Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350359756

Records technology uses facts, evaluation strategies, and equipment to derive insights and enable decision-making for enterprises, firms, and governments. The data technology aims to increase predictive fashions and gear, which may be applied to enhance the know-how of clients, markets, and products. information technological know-how may be applied to actual-time statistics evaluation to recognize and discover styles and trends and modify enterprise operations to act in reaction to the changing environment. Actual-time data analysis can offer an aggressive advantage over other evaluation methods, especially within consumer enjoy optimization. Facts scientists use predictive analytics, machine mastering, synthetic intelligence (AI), and natural language processing (NLP) to system and analyze vast statistics in real time. The technological know-how of records facilitates delivering all the facts and points together to tell selection-making and enhance methods. information technology can be utilized to benefit insights into purchaser behavior, marketplace dynamics, and how products perform in their respective marketplace segments. Information technology applications give enterprises a more profound knowledge of purchaser wishes, choices, and behaviors, which can be used to improve patron stories and optimize pricing, product bundles, or promotional offers. With the assistance of statistics technology in real-time, organizations can count on consumer behavior if they want to reply and act as a consequence. © 2023 IEEE.

关键词： Consumer behavior

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A Machine Learning based Facial Expression and Emotion Recognition for Human computer Interaction through Fuzzy Logic System 6

A Machine Learning based Facial Expression and Emotion Recog...

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6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Vinutha, K. Niranjan, Manoj Kumar Makhijani, Jagdish Natarajan, B. Nirmala, V. Vijaya Lakshmi, T.R. Department of Information Science and Engineering BMS Institute of Technology and Management Karnataka Bengaluru India Department of Computer Applications Rustamji Institute of Technology Madhya Pradesh Gwalior India Department of Computer Science and Engineering Rustamji Institute of Technology Madhya Pradesh Gwalior India Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Tamil Nadu Chennai India Department of Science and Humanities Faculty of Engineering Karpagam Academy of Higher Education Tamil Nadu Coimbatore India Department of Electronics and Communication Engineering Mahatma Gandhi Institute of Technology Telangana Hyderabad India

ISBN: (纸本)9798350398496

Facial recognition is in use for the past decade there are many applications that needs facial expression to learn the human behaviour and emotions for certain activities. Facial recognition is in a development phase where many service providers use this feature to find the expression of the people on using their BlogSpot or website or reading any news article. This recognition of facial expression is highly possible with the help of machine learning technology. This research study has developed a facial expression recognizing algorithm using Python programming language with the help of Keras software package. This algorithm is purely based on machine learning approach that enables the programmer to process the facial image and convert it into data that is helpful in prediction of facial expression using the fuzzy logic technique. The fuzzy logic technique is a prediction method that helps programmer to predict the intermediate data by providing the initial and ending conditions. For enabling the facial recognition to process any system or a mobile device the algorithm needs permission to access the camera, once the onto the access is permitted the algorithm retrieves the image from the Vision sensor and with the help of image processing technology of the machine learning algorithm the program the program converts the data from the vision sensor into required facial expression and emotional content. © 2023 IEEE.

关键词： Emotion Recognition

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A Review on the Advancement of Renewable Natural Fiber Hybrid Composites: Prospects, Challenges, and Industrial Applications

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Journal of Renewable Materials 2024年第7期12卷 1237-1290页

作者： Mohammed Mohammed Jawad K.Oleiwi Aeshah M.Mohammed Anwar Ja’afar Mohamad Jawad Azlin F.Osman Tijjani Adam Bashir O.Betar Subash C.B.Gopinath Center of Excellence Geopolymer&Green Technology(CEGeoGTech) Universiti Malaysia PerlisArau02600Malaysia Faculty of Chemical Engineering Technology Universiti Malaysia Perlis(UniMAP)Arau02600Malaysia Department of Materials Engineering University of TechnologyBaghdad10070Iraq Department of Chemical Materials University of Bagdad College of Education for Pure Science Ibn-AlhaithamBaghdad10001Iraq Department of Computer Techniques Engineering Al-Rafidain University CollegeBaghdad10001Iraq Faculty of Electronics Engineering Technology Universiti Malaysia PerlisKampus Uniciti Alam Sg.ChuchuhPerlis02100Malaysia Research Center(NANOCAT) University of MalayaKuala Lumpur50603Malaysia Institute of Nano Electronic Engineering Universiti Malaysia PerlisPerlis01000Malaysia Center for Global Health Research Saveetha Medical College&HospitalSaveetha Institute of Medical and Technical Sciences(SIMATS)Tamil Nadu602105India

Naturalﬁbre(NFR)reinforced functional polymer composites are quickly becoming an indispensable sustainable material in the transportation industry because of their lightweight,lower cost in manufacture,and adaptability to a wide variety of ***,the major difﬁculties of using theseﬁbres are their existing poor dimensional stability and the extreme *** assessing the mechanical properties(MP)of composites,the interfacial bonding(IB)happening between the NFR and the polymer matrix(PM)plays an incredibly signiﬁcant *** compared to NFR/syntheticﬁbre hybrid composites,hybrid composites(HC)made up of two separate NFR are less prevalent;yet,these hybrid composites also have the potential to be valuable materials in terms of environmental issues.A new dimension to theﬂexibility of composites reinforced with NFR is added by the cost-effective manufacture of hybrid composites utilising *** purpose of this study is to offer an over-view of the keyﬁndings that were presented on hybrid *** emphasis was focused on the factors that inﬂuence the performance of the naturalﬁber composites,diverse approaches to enhancing MP,physical,electri-cal,and thermal characteristics of the *** study in polymer science gains interest for applications in con-struction and automotive industries.

关键词： Renewable naturalﬁber hybrid composites sustainability nanomaterial greener material

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Efficient Segmentation Approach for Different Medical Image Modalities

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computers, Materials & Continua 2022年第11期73卷 3119-3135页

作者： Walid El-Shafai Amira A.Mahmoud El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

This paper presents a study of the segmentation of medical *** paper provides a solid introduction to image enhancement along with image segmentation *** the first step,the morphological operations are employed to ensure image detail protection and *** objective of using morphological operations is to remove the defects in the texture of the ***,the Fuzzy C-Means(FCM)clustering algorithm is used to modify membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster *** proposed technique is very simple to implement and significantly fast since it is not necessary to compute the distance between the neighboring pixels and the cluster *** is also efficient when dealing with noisy images because of its ability to efficiently improve the membership partition *** results are performed on different medical image ***(Us),X-ray(Mammogram),Computed Tomography(CT),Positron Emission Tomography(PET),and Magnetic Resonance(MR)images are the main medical image modalities used in this *** obtained results illustrate that the proposed technique can achieve good results with a short time and efficient image *** results on different image modalities show that the proposed technique can achieve segmentation accuracies of 98.83%,99.71%,99.83%,99.85%,and 99.74%for Us,Mammogram,CT,PET,and MRI images,respectively.

关键词： Image segmentation ultrasonic mammogram CT PET MRI morphological operations FCM active contours

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An Intelligent System for Furfural Estimation in the Power Transformers 2nd

An Intelligent System for Furfural Estimation in the Power T...

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2nd International Conference on Renewable Power, ICRP 2023

作者： Nezami, Md. Manzar Hashem, Hythem Equbal, Md. Danish Khan, Mohammad Junaid Ansari, Md. Fahim Mustafa, Elfatih Elmubarak Department of Electronics and Communication Engineering GLA University Mathura281406 India Department of Computer Science Faculty of Science and Arts at Belqarn University of Bisha Sabt-Al-Alaya61985 Saudi Arabia Department of Electrical Engineering Galgotias College of Engineering and Technology Greater Noida India Haryana Nuh India Department of Electrical Engineering Graphic Era University Dehradun India

ISBN: (纸本)9789819967483

Power transformers are supposed to be an expensive and critical component of a power system and so its schedule maintenance is an important aspect near the utilities. The cellulose paper used as the solid insulating material of the transformer deteriorates regularly due to progressive aging. As a result, it produces several degradation by-products of cellulose insulation into the transformer oil. Furfurals are among the major by-product of cellulose and are exploited to estimate the physical state of the transformer’s dielectric and the electrical insulation directly and noninvasively. In the present work, an intelligent system is proposed and developed that predicts the level of furfural in the transformer oil. The system makes predictions using easily quantifiable parameters, enabling utilities to avoid suffering financial losses. The proposed system employs the Adaptive Neuro Fuzzy Inference System (ANFIS) technique with temperature and moisture as the input and 2-Furfuraldehyde (2-FAL) as the output. An optimum arrangement of the developed model to find accurate outputs has been achieved by the suitable selection of number and types of the membership functions of the network. Also, an exhaustive study is made to optimize the training data points to achieve the accurate predictions at minimum iterations. The proposed system is validated with nine test conditions of temperature and moisture, and the output thus obtained is verified through existing life models in the literature. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Power transformers

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