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International Conference on Microelectronics, MIEL

作者： M. Milovanović J. Pejić P. Pejić Department of Electronics Faculty of Electronic Engineering University of Niš Niš Serbia Department of Computer Science Faculty of Sciences and Mathematics University of Niš Niš Serbia Faculty of Information Technology Belgrade Metropolitan University

Honeybees are essential for pollination in agriculture. This paper presents a smart beehive frame for multi-parameter monitoring. The system is based on opto elements that emit IR light to the honeycomb and measure the reflection. The results showed that this kind of system can be used in practice to decrease the number of the visual on-site observations of the bee colonies.

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Structural, Morphological, and Chemical Composition of Ternary Zrhfn Thin Films Deposited by Reactive Co-Magnetron Sputtering

SSRN

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SSRN 2024年

作者： Gitgeatpong, Ganatee Prathumsit, Jedsada Phae-Ngam, Wuttichai Horprathum, Mati Triamnak, Narit Nakajima, Hideki Faculty of Science and Technology Phranakhon Rajabhat University Bangkhen Bangkok10220 Thailand National Electronics and Computer Technology Center Pathumthani 12120 Thailand Department of Materials Science and Engineering Faculty of Engineering and Industrial Technology Silpakorn University Nakhon Pathom73000 Thailand Synchrotron Light Research Institute Muang Nakhon Ratchasima30000 Thailand

This study focuses on a deposited ternary zirconium hafnium nitride (ZrHfN) thin film prepared using the reactive co-magnetron sputtering technique. The effect of the nitrogen (N2) flow rate on the films' structural, morphological, and chemical composition was investigated. The gracing-incidence X-ray diffraction (GIXRD) showed that all ZrHfN thin films exhibited a crystalline face-centered cubic structure with a strong (111) orientation. With increasing the N2 flow rate, the film's crystallography changed based on thermodynamic theory. The films demonstrated uniformity and homogeneity in their ternary nitride composition, as confirmed by TEM-EDS mapping and EPMA. Chemical state analysis using XPS indicated the presence of both nitride and oxynitride species in all samples. Notably, the atomic concentration of the main elements (Zr, Hf, and N) remained relatively stable over the controlled N2 flow rate range. However, the N2 flow rate played a crucial role in forming hafnium nitride and oxynitride chemical states, whereas it did not significantly influence the Zr phases, dominated by Zr oxides. Additionally, the hardness of the ternary ZrHfN thin films exhibited enhancement comparable to typical ternary nitrides. © 2024, The Authors. All rights reserved.

关键词： Hardness

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COVID-X: Novel Health-Fog Framework Based on Neutrosophic Classifier for Confrontation Covid-19

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Neutrosophic Sets and Systems 2020年 35卷 1-21页

作者： Yasser, Ibrahim Twakol, Abeer El-Khalek, A.A. Abd Samrah, Ahmed Salama, A.A. Communications and Electronics Engineering Department Nile Higher Institute for Engineering and Technology Mansoura Egypt Department of Computer Engineering Faculty of Engineering Benha University Egypt Electronics and Communications Engineering Department Faculty of Engineering Mansoura University Egypt Department of Mathematics and Computer Science Faculty of Sciences Port Said University Egypt

The newly identified Coronavirus pneumonia, subsequently termed COVID-19, is highly transmittable and pathogenic with no clinically approved antiviral drug or vaccine available for treatment. Technological developments like edge computing, fog computing, Internet of Things (IoT), and Big Data have gained importance due to their robustness and ability to provide diverse response characteristics based on target application. In this paper, we present a novel Health-Fog framework universal system to automatically assist the early diagnosis, treatment, and preventive of people with COVID-19 in an efficient manner. Achieving an empirical of the proposed framework which mix between deep learning and Neutrosophic classifiers in the task of classifying COVID-19. There are some proposed applications based on the proposed COVID-X framework such as smart mask, smart medical suit, safe spacer, and Medical Mobile Learning (MML) will be presented. computer-aided diagnosis systems could assist in the early detection of COVID-19 abnormalities and help to monitor the progression of the disease, potentially reduce mortality rates. © 2020, Neutrosophic Sets and Systems. All Rights Reserved.

关键词： Coronavirus

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Ultra-Low-Power Graphene-Nanoribbon-Based Current-Starved Ring Oscillator

Ultra-Low-Power Graphene-Nanoribbon-Based Current-Starved Ri...

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International Conference on Semiconductor

作者： F.-S. Dumitru M. Enachescu A. Antonescu N. Cucu-Laurenciu S. Cotofana Devices Circuits and Architectures Department Faculty of Electronics Telecommunications and Information Technology University Politehnica of Bucharest Bucharest Romania High Energy Physics Department IMAP Radboud University The Netherlands Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology The Netherlands

ISBN: (数字)9798350352078

ISBN: (纸本)9798350352085

Identifying methods to further push the boundaries of existing low-power designs has gained new traction, driven by the wide-scale use of large language models. Graphene is well-suited for ultra-low-power nano-electronics due to its exceptional characteristics like ballistic transport, flexibility, and bio-compatibility. In this paper we investigate the feasibility of using ultra-low-voltage GNR structures, in conjunction with power reduction techniques to implement a GNR-based current-starved ring oscillator. By exploiting their low operating voltage and attofarad range intrinsic capacitances we achieve a 1.89 x higher output frequency while simultaneously reducing the power consumption by 553.8 x and achieving a 812 x higher power efficiency.

关键词： Ring oscillators Electric potential Power demand Large language models Graphene Voltage Logic gates FinFETs Capacitance Topology

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CRISP - DM Process in Smart Building Management

CRISP - DM Process in Smart Building Management

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International Conf on Electrical and Electronic engineering (ICEEE)

作者： Mahir Dursun Moldir Sabyrzhan Dept. of Electrical and Electronics Engineering Faculty of Technology Gazi University Ankara Türkiye Department of Computer Science Graduate School of Informatics Gazi University Ankara Türkiye

ISBN: (数字)9798350362541

ISBN: (纸本)9798350362558

Smart Buildings are buildings that integrate and combine intelligence, management, control, materials, and construction as a single system to meet all the needs of the building, such as comfort, energy efficiency, and durability. In universities, laboratories are used less frequently than other facilities and classrooms. Courses and students may change in the same classroom, and the period of use of such classrooms is much more extended than in laboratories. However, classrooms may only be used for classes during long breaks or for short periods of non-use between exams. In addition, there is no provision for when the heating system will start to heat up before classes or when it will be turned off after classes. By planning heating and lightning, energy and costs will be saved. This paper presents data acquisition methods for preparing a dataset to create a machine learning (ML) model to save energy loss in university laboratories. The developed model will predict energy consumption in classrooms and laboratories based on weather conditions. The study is being conducted in two stages. The first stage describes how to collect data using electronic devices such as Internet of Things (IoT) controllers of Smart Building Management Systems. The second stage gave possibilities for data analysis and preparation using the phases of the Cross-Industry Standard Process for Data Mining (CRISP-DM).

关键词： Heating systems Smart buildings Laboratories Energy conservation Decision making Process control Data models Planning Internet of Things Data mining

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IoT Enabled Bee Hive Monitoring System

IoT Enabled Bee Hive Monitoring System

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International Conference on Microelectronics, MIEL

Beehive monitoring can provide useful information for people associated with beekeeping to help to manage their honey bee (Apis mellifera) colonie. This paper presents the development and experimental results of a IoT...

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Slots Effect on CPW Pentagonal Patch Antenna for 3.5 GHz 5G and 5.9 GHz DSRC Applications

Slots Effect on CPW Pentagonal Patch Antenna for 3.5 GHz 5G ...

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International Symposium on Antennas and Propagation (ISAP)

作者： Amier Hafizun Ab Rashid Badrul Hisham Ahmad Nornikman Hassan Saidatul Norlyna Azemi Centre of Telecommunication Research and Innovation Faculty of Electronics and Computer Technology and Engineering Universiti Teknikal Malaysia Melaka (UTeM) Durian Tunggal Melaka Malaysia Kolej Komuniti Segamat Johor Segamat Johor Malaysia Advanced Communication Engineering Center of Excellence Faculty of Electronic Engineering & Technology Universiti Malaysia Perlis Arau Perlis Malaysia

ISBN: (数字)9798350364774

ISBN: (纸本)9798350364781

This research investigates the effects of two different slots on the CPW pentagonal patch antenna for 5G and Dedicated short-range communications (DSRC). Initially, first antenna design, Antenna A is pentagonal patch antenna with pentagonal slots while the second antenna design B is constructed by a pentagonal patch antenna with mini multiple slots structure. This Antenna A performs best at 3.32 GHz and 5.77 GHz with - 20.83 dB and - 49.56 dB, respectively. Besised that, the Antenna B perfoms at 3.50 GHz and 5.92 GHz with - 46.13 dB and - 20.09 dB, respectively.

关键词： Slot antennas 5G mobile communication Patch antennas Design methodology Coplanar waveguides Dedicated short range communication Gain Antenna radiation patterns

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Multi-factor based face validation attendance system with contactless design in training event 18

Multi-factor based face validation attendance system with co...

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18th International Conference on Electrical engineering/electronics, computer, Telecommunications and Information technology, ECTI-CON 2021

作者： Pichetjamroen, Sasakorn Rattanalerdnusorn, Ekkachan Vorakulpipat, Chalee Pichetjamroen, Achara National Electronics and Computer Technology Center Information Security Research Team Pathumthani Thailand Kasetsart University Faculty of Engineering Department of Electrical Engineering Bangkok Thailand

ISBN: (纸本)9780738111278

Various methods for face validation-based authentication systems have been applied in a number of access control applications. However, using only one biometric factor such as facial data may limit accuracy and use, and is not practical in a real environment. This paper presents the implementation of a face time attendance system with an additional factor, a QR code to improve accuracy. This two- factor authentication system was developed in the form of a kiosk with a contactless process, which emerged due to the COVID-19 pandemic. The experiment was conducted at a well- known training event in Thailand. The proposed two-factor system was evaluated in terms of accuracy and satisfaction. Additionally, it was compared to a traditional single-factor system using only face recognition. The results confirm that the proposed two-factor scheme is more effective and did not incorrectly identify any users. © 2021 IEEE.

关键词： Face recognition

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Towards backward compatibility of ADRC: revisiting classical state-feedback control with integral compensator

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Bulletin of the Polish Academy of Sciences: Technical Sciences 2025年第2期73卷

作者： Mrotek, Mikolaj Michalski, Jacek Madonski, Rafal Pazderski, Dariusz Retinger, Marek Faculty of Control Robotics and Electrical Engineering Institute of Robotics and Machine Intelligence Poznan University of Technology Piotrowo 3a Poznan60-965 Poland Faculty of Automatic Control Electronics and Computer Science Department of Automatic Control and Robotics Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Faculty of Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Poznan University of Technology Piotrowo 3a Poznan60-965 Poland

In this paper, the problem of backward compatibility of active disturbance rejection control (ADRC) is investigated. The goal is to contextualize ADRC to deliver its interpretations from the established field of linear control systems. For this study, a control algorithm, denoted here as integral disturbance rejection control (IDRC), is considered that combines classical state-feedback control with an integral compensator. At first, an interpretation of ADRC is involved in terms of existing state-space control approaches. Next, a transition to the frequency domain is performed, which is justified as a significant part of practical control engineering is conducted in that domain. For assumed specific plant structures, both ADRC and IDRC are then holistically compared in terms of transfer function representation and frequency characteristics, as well as steady-state convergence conditions. Such a juxtaposition helps to highlight the similarities and differences of both approaches, whereas the utilized bandwidth parameterization is shown to bring the control system to the same form, thus indicating some interesting practical aspects. Finally, the theoretical results concerning both considered control structures are validated in a set of numerical simulations and experiments conducted on a laboratory hardware testbed. © 2025 The Author(s).

关键词： Disturbance rejection

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Robotics Architectures Based Machine Learning and Deep Learning Approaches 8

Robotics Architectures Based Machine Learning and Deep Learn...

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8th International Conference on Mechatronics engineering, ICOM 2022

作者： Alatabani, Lina E. Ali, E.S. Mokhtar, R.A. Khalifa, Othman O. Saeed, Rashid A. Department of Data Communications & Network Engineering Faculty of Telecommunications The Future University Khartoum Sudan port Sudan Sudan Khartoum Sudan Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Department of Electrical and Electronics Engineering Faculty of Engineering International Islamic University Malaysia Malaysia The Libyan Center for Engineering Research and Information Technology Bani Walid Libya

ISBN: (数字)9781839538063

ISBN: (纸本)9781839538063

Robotics has been playing a vital role in our daily lives with a wide range of applications to improve the quality of life. With a variety of usable applications in the medical, manufacturing, and transportation industries, there is a continuous need for improving the performance of robotics for the importance of precision in executing commands and tasks. The implementation of precise commands has led to intense research on approaches to improve the performance of robotics. Machine Learning (ML) and Deep Learning (DL) have been drawing attention to applying architectures and algorithms to robotics which imposed a positive impact on the field of robotics. ML and DL applications in robotics include areas of computer vision, imitation learning, self-supervised learning, assistive and medical technologies, multi-agent learning, and manufacturing. This paper provides a comprehensive review of autonomous vs automatic robotics, robotic applications, extreme learning machine methods, and ML for soft robotics applications, in addition, to discussing the challenges, and future trends for AI applications in robotics applications. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Robotics

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