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7th IEEE International Conference on Electronic Information and Communication technology, ICEICT 2024

作者： Rao, Liwei Feng, Botao Ding, Xiao Gu, Wenzhe Deng, Li Zeng, Qingsheng Shenzhen University College of Electronics and Information Engineering Shenzhen518060 China Macau University of Science and Technology Faculty of Humanities and Arts Macau999078 China Huizhou University School of Computer Science and Engineering Huizhou China Beijing University of Posts and Telecommunications College of Information and Communication Engineering Beijing China Nanjing University of Aeronautics and Astronautics College of Astronautics Nanjing210016 China

ISBN: (纸本)9798350384437

An "I"-shaped polarization conversion unit was developed in this study, capable of functioning at a frequency of 12 GHz. The design involved rotating metal patches on the unit by 90 degrees, resulting in an alternative unit with the same reflection coefficient and a phase difference of 180°. The final step involved incorporating choke rings around the "I"-shape to provide filtering functionality. Based on this, a high-gain filtering reflective array consisting of 20×20 proposed antenna unit was constructed. At 12 GHz, the attained gain was 24.7 dBi, and the radiation patterns for both H-plane and V-plane are demonstrated to be stable enough. © 2024 IEEE.

关键词： Polarization

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Optimal Energy Management based on Dynamic Programming

Optimal Energy Management based on Dynamic Programming

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Haripriya, D. Dahiwade, Mandakini Kotiyal, Arnav Al-Farouni, Mohammed Yadav, Kanchan Francis Raj, J. Relin Department of CSE Veltech Ranagarajan Dr.Saguntala R&D Institute of Science and Technology Avadi Tamilnadu Chennai India Department of Basic Engineering Indira College of Engineering and Management Pune India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of computers Techniques engineering College of technical engineering The Islamic university Najaf Iraq Department of Electrical Engineering GLA University Mathura India Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

ISBN: (纸本)9798350355338

The strategy based on reinforced learning will be able to present a solution that is close to the optimal solution achieved by using Dynamic Programming (DP), and the power distribution for hybrid vehicles also seems promising with DP. It addresses nonlinear dynamical systems' optimal control issues. However, DP cannot be applied to the majority of problems of practical interest due to its high complexity in terms of computation and dimensionality. In various energy policies, variability has not been addressed, and it is based on fixed driving profiles, which affect vehicle operation. The proposed study's goal is to create an optimal hybrid energy management system that generates more power at the lowest possible cost. The control strategy has been formed based on DP through the rule extraction process, and the fuel consumption must be minimized for the drive cycles. It has simple mathematical foundations, ensures the optimal solution for a given tolerance, and can be easily implemented in a short computer program. The strategy is evaluated in terms of real and predicted values, which makes the performance indices, and this comparison is done on different levels of time. © 2024 IEEE.

关键词： Hybrid power

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Secure Authentication and Session Key Management Scheme for Distributed Sensor Networks 5

Secure Authentication and Session Key Management Scheme for ...

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5th International Conference on Computing, Electronics and Communications engineering. iCCECE 2022

作者： El Zouka, Hesham A. Hosni, Mustafa M. Arab Academy for Science Technology and Maritime Transport Computer Eng. Dept College of Engineering and Technology Alexandria Egypt Managing Director of Omikron Technologies Electrical Engineering Dept Faculty of Engineering Alexandria Egypt

ISBN: (数字)9781665489805

ISBN: (纸本)9781665489805

Wireless sensor networks are liable to attacks because of the complicated operations they perform especially the node deployment one. Security and energy consumption represent two big flaws in Wireless sensor networks and this paper is discussing how those networks can be secured against network violations and attacks while preserving the energy consumption in the network. Therefore, handling this problem using security schemes should ensure a moderate consumption of energy and for this target a secure hybrid session key management scheme is proposed where most of the operations taking place depend on cryptography and the heart of cryptography is the keys which are used to ensure that the energy consumption will remain limited and the security issue will be guaranteed. Benchmark schemes have been of great help in analyzing the proposed scheme to come out with the targeted conclusion ensuring its efficiency in comparison with other benchmark schemes and its ability to limit energy consumption and to present quite an effective tool in network environment that is able to secure management and key agreements. © 2022 IEEE.

关键词： Energy utilization

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Correction to: Automated approach to predict cerebral stroke based on fuzzy inference and convolutional neural network (Multimedia Tools and Applications, (2024), 10.1007/s11042-024-19254-0)

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Multimedia Tools and Applications 2024年 1-2页

作者： Alrowais, Fadwa Jamjoom, Arwa A. Karamti, Hanen Umer, Muhammad Alsubai, Shtwai Abate, Andrea F. Ashraf, Imran Department of Computer Sciences College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia Department of Computer Science The Islamia University of Bahawalpur Bahawalpur Pakistan Department of Computer Science College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University P.O. Box 151 Al-Kharj11942 Saudi Arabia Department of Computer Science University of Salerno Fisciano84084 Italy Department of Information and Communication Engineering Yeungnam University Gyeongsan38541 Korea Republic of

The original publication of this article contains an error in the affiliation of authors Fadwa Alrowais and Hanen Karamti. Incorrect: Department of Information Systems, College of computer and Information sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia Correct: Department of computer sciences, College of computer and Information sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia The original article has been corrected. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

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Improving the learning performance by exploiting multimedia in eXtreme apprenticeship

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Multimedia Tools and Applications 2024年 1-25页

作者： Persia, Fabio D’Auria, Daniela Ge, Mouzhi Pilato, Giovanni Department of Information Engineering Computer Science and Mathematics University of L’Aquila Via Vetoio L’Aquila67100 Italy Faculty of Computer Science Free University of Bozen-Bolzano Piazza Domenicani 3 Bozen-Bolzano39100 Italy Faculty of European Campus Rottal-Inn Deggendorf Institute of Technology Dieter-Görlitz-Platz 1 Deggendorf94469 Germany Institute for High Performance Computing and Networking National Research Council of Italy Via Ugo La Malfa 153 Palermo90146 Italy

From prior studies on eXtreme Apprenticeship (XA), it can be seen that XA has emerged as an innovative and effective educational approach. The technology in computer science evolves rapidly and XA tackles the gap between University education and industry development. Additionally, distance learning by multimedia is more and more important, sometimes even becoming necessary. As a result, this paper intends to study how to integrate XA and multimedia to improve the learning performance in computer science, with particular reference to the programming courses. Since computer science is mostly driven by the new applications, XA and multimedia are considered to be effective and efficient to reduce the cognitive efforts by practical demonstration. The experimental results, based on the case study of the operating systems course at the Bachelor’s level, show that exploiting multimedia in XA can significantly improve the learning performance in terms of grade distributions, reliability, knowledge transfer and student satisfaction with respect to more traditional approaches based on frontal lectures. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Distance education

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A Study and Recognition of Alzheimer's Disease Using Machine Learning 8

A Study and Recognition of Alzheimer's Disease Using Machine...

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8th IEEE International Conference for Convergence in technology, I2CT 2023

作者： Basha, S.K. Masthan Ashalatha, G. Vara Prasad, Srisailapu D Al-Hameed, Mazin R. Zearah, Sajad Ali Saikumar, K. Vignan's Institute of Management and Technology for Women ECE Department Hyderabad India VNR Vignana Jyothi Institute of Engineering and Technology Department of Computer Science-CS-DS&AI&DS Telangana Hyderabad India GITAM Deemed to Be University Computer Science and Engineering School of Technology Telangana Hyderabad India National University of Science and Technology College of Engineering Technology Department of Medical Device Industry Engineering Dhi Qar Iraq Al-Ayen University Scientific Research Center Thi-Qar Iraq Koneru Lakshmaiah Education Foundation Andhra Pradesh India

ISBN: (纸本)9798350334012

Nowadays, Alzheimer's disease is one of the most severe threats to people of all ages and socioeconomic backgrounds. Their everyday activities may measure this disorder, and how they speak about it shows how concerned they are about it. The way we live today is different from how it was in the past because of our working environment and the lack of opportunities to interact with people. WHO estimates that about 10 billion individuals perish each year due to Alzheimer's disease since not been appropriately diagnosed and treated. An advanced Machine Learning-based recognition system design performs in this research work. The proposed model has been designed based on the human being EEG dataset(testing) and the Kaggle Alzheimer dataset (training). The developed intelligent system will be updated with data collection and pre-processing through the Random Forest machine model to locate our health condition and recognize daily routine changes. Only by developing a machine-based approach will we be able to discover Alzheimer's patients who previously had no idea that they had the illness and are now unable to reverse the progression of their condition. The designed application has attained a sensitivity of 93.01%, an accuracy of 91.32%, a recall of 97.28%, and a detection rate of 98.91%. The implemented application is beneficial to investigators and surgeons for easy treatment. The proposed RFO Machine learning design competes with present technology and outperforms methodology. © 2023 IEEE.

关键词： Intelligent systems

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Adaptive Thermal Clothing with IoT and Random Forest Regression for Dynamic Outdoor Comfort

Adaptive Thermal Clothing with IoT and Random Forest Regress...

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2024 International Conference on Advances in Modern Age Technologies for Health and engineering science, AMATHE 2024

作者： Srinivasan, S. Sridevi, V. Saravanan, K. Murugan, S. Srinivasan, C. Muthulekshmi, M. Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Saveetha University Department Of Biomedical Engineering Tamil Nadu Chennai India Academy Of Maritime Education And Training Deemed To Be University Department Of Electrical And Electronics Engineering Tamil Nadu Chennai India R.M.D. Engineering College Department Of Information Technology Tamil Nadu Chennai India Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Saveetha University Department Of Computer Science And Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350371567

This research presents a novel method for improving outdoor comfort by combining adaptive thermal apparel with Internet of Things (IoT) and Random Forest Regression. Wearing inflexible traditional outdoor gear may be a real pain for those living in different parts of the world. As a solution, we present an intelligent garment system that can adapt its thermal insulation in real-time using data gathered from IoT sensors. A Random Forest Regression model is used to ascertain the most appropriate thermal settings for the garments based on the gathered data, which encompasses environmental factors such as humidity, temperature, and wind speed. By taking each user's tastes and physiological needs into account, the adaptive system strives to provide individualized comfort. The suggested technique successfully maintains the target comfort levels throughout varied outside situations, according to the experimental findings. In an age of rising climatic fluctuation, our study offers a potential answer for dynamic outdoor comfort to the expanding area of smart fabrics and wearable technologies. © 2024 IEEE.

关键词： Energy efficiency

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Exploration and Analysis of Seizure Spikes Through Spectral Domain Transformation

Exploration and Analysis of Seizure Spikes Through Spectral ...

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International Conference on Business Intelligence and Information technology, BIIT 2023

作者： Najmusseher Nizar Banu, P.K. Azar, Ahmad Taher Kamal, Nashwa Ahmad Alzahrani, Abdulkareem Central Campus Karnataka Bangalore India College of Computer and Information Sciences Prince Sultan University Riyadh11586 Saudi Arabia Faculty of Computers and Artificial Intelligence Benha University Benha13518 Egypt Faculty of Engineering Cairo University Giza Egypt Department of Computer Engineering and Science Faculty of Computer Science and Information Technology Al-Baha University Al-Baha Saudi Arabia Prince Sultan University Riyadh Saudi Arabia

ISBN: (纸本)9789819739790

Seizure detection is the most crucial area of investigation when it comes to understanding brain disorders. This proposed research study embarked on an automated model for epileptic seizure diagnosis by means of different kinds of Spectral transformation using EEG inputs from seizure sufferers and healthy subjects. This automated model accommodates non-invasive brain electrical activity monitoring. This method aims to facilitate the analysis and identification of epileptic seizure states since, monitoring and diagnosing such brain electrical activity is a complex task due to its numerous divisions and underlying features. The primary objective of this research study is to distinguish between EEG-based seizures and healthy individuals. To achieve this goal, a combination of spectral transformation and EEG analysis techniques is utilized. These techniques include examining the frequency spectrum, magnitude spectrum, correlation, and T-Distributed Stochastic Neighboring Embedding (T-SNE) analysis. This analysis yields valuable insights from EEG data, refining the input data and making it more suitable for prediction and identification. The model’s performance is evaluated using two distinct datasets: real-time EEG data from individuals experiencing epileptic seizures and EEG data from healthy subjects. These datasets are sourced from the Bangalore EEG Epilepsy Dataset (BEED), India and the BONN epilepsy dataset from the UCI repository. In a comparative study of spectral transformation methods, including Complex Fast Fourier Transform (CFFT) and Real-Valued Fast Fourier Transform (RFFT), it is discovered that reducing the data dimension by using feature extraction is not the optimal approach. This simplification leads to the loss of valuable information. Therefore, preserving the full spectrum of EEG characteristics is crucial for gaining valuable insights into brain neuronal functions, ultimately enabling more accurate seizure prediction. © The Author(s), under exclusi

关键词： Fast Fourier transforms

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Using Natural Language Processing for Biometric Identification Optimizatoin 3

Using Natural Language Processing for Biometric Identificati...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Kumar, Bhupendra Nagpal, Amandeep Bisht, Yashwant Sreenivasgoud, Pulluri Qureshi, Kashif Lourens, Melanie Mangalmay Institute of Engineering Technology Computer Science Engineering Greater Noida India Lovely Professional University Phagwara India Uttaranchal University Uttaranchal Institute of Technology India SR University School of Sciences Warangal India Lingaya's Vidyapeeth Department of Computer Science Information Technology Haryana Faridabad India Durban University of Technology Deputy Dean Faculty of Management Sciences South Africa

ISBN: (纸本)9798350399264

The use of natural language processing (NLP) methods for assessing employee performance is examined in this research article. The paper suggests a technique for extracting pertinent information on work performance from employee-generated text data, such as emails, chats, and feedback surveys. The suggested approach makes use of NLP methods including topic modelling, sentiment analysis, and text classification to extract characteristics that may be utilized as performance indicators for employees. The study's findings imply that the suggested approach, when compared to more conventional assessment techniques, may provide a more comprehensive perspective of employee performance, and assist managers in reaching more informed conclusions about that performance. © 2023 IEEE.

关键词： Classification (of information)

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Self-Propelled Capsule Endoscope and Tracking Control of Its Wireless Power Supply Coil 1

Self-Propelled Capsule Endoscope and Tracking Control of Its...

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1st International Conference on Robotics, engineering, science, and technology, RESTCON 2024

作者： Ito, Takahiro Fujita, Kohei Miyauchi, Kenji Murakami, Sunao Ohtake, Hiroshi Katsuta, Chihiro Karasawa, Kaoru Tanaka, Akane Matsuda, Hiroshi Kimura, Toshihiro Kutsumi, Hiromu Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan Tokyo University of Agriculture and Technology Division of Animal Life Science Fuchu-shi Japan Savior Inc Yokohama Japan Center for Clinical Research and Advanced Medicine Establishment Shiga University of Medical Science Otsu-Shi Japan

ISBN: (纸本)9798350348842

We have developed the self-propelled capsule endoscope. Although it is the same size as a conventional capsule endoscope, with a diameter of 11 mm and a length of 31 mm, it can travel inside the gastrointestinal tract. A running mechanism that uses vibrations allows it to run without any protrusions on the outer shell. Therefore, there is no risk of harming the inside of the body. This is a noteworthy feature of this capsule. Experiments have confirmed that this capsule can travel in the intestines of living dogs. Because the power supply to this capsule needs to continue stably for over an hour, we developed a wireless power supply method to the internal capsule. Conventional wireless power supply with a fixed power transmission coil had the problem that power supply would be interrupted if the capsule moved. Therefore, we investigated stabilizing the power supply by moving the power transmission coil in X-Y to follow the capsule in response to increases and decreases in the power supply. We were able to confirm the feasibility through experiments. This technology can be expected to perform endoscopic examinations with less burden on both patients and doctors, and can also be applied to power supply to medical devices inside the body. © 2024 IEEE.

关键词： Endoscopy

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