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New Trends in Signal Processing (NTSP)

作者： Zdenek Vylezich Martin Kyselak Karel Slavicek David Grenar Zuzana Chalk Department of Electrical Engineerings Faculty of Military Technlogy Brno Czech Republic Institute of Computer Science Data and Technical Networks Brno Czech Republic Department of Telecommunication Faculty of Electrical Engineering and Communication Brno Czech Republic Department of Communication Technology Electronic Warfare and Radiolocation Faculty of Military Technology Brno Czech Republic

ISBN: (数字)9788080406370

ISBN: (纸本)9798350362688

The article analyses enhancing the sensitivity of fiber-optic polarization sensors to temperature changes via additional longitudinal strain. This multifunctional sensor is suitable for application as a sensing element for security purposes and has many possible biomedical applications. The testing method consists of stretching the fiber on a proof tester where it is possible to get an exact setting of the operating force, and then applying a container of water at a different temperature. Changes were captured by a laser power meter and plotted into graphs describing several sets of measurements to keep independence on manufacturing. The sensor sensitivity was increased and the proposed solution appeared to be suitable for in-position sensors with minimum additional outlays.

关键词： Temperature sensors Temperature measurement Optical fiber polarization Mechanical sensors Optical fiber sensors Sensitivity Force Sensor phenomena and characterization Optical fiber testing Stress

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Evaluation and Measures for Improving the Energy Efficiency of Medium-Sized Enterprises

Evaluation and Measures for Improving the Energy Efficiency ...

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Junior Conference on Lighting (Lighting)

作者： Plamen Stanchev Gergana Vacheva Nikolay Hinov Departement of Information Technology in industry Faculty of Computer Systems and Technologies Technical University of Sofia Sofia Bulgaria Departement of Power Electronics Faculty of Electronic Engineering and Technologies Technical University of Sofia Sofia Bulgaria

In the presented article, an assessment and measurements were realized to determine the energy efficiency of a medium-sized industrial enterprise. Real data from a three-shift plant was used. An assessment of the current electricity consumption was made and an energy audit was carried out to reduce electricity costs. The main goal of the current research is to ensure the basic functionality of the buildings, as well as the production-technological process, ensuring minimum electricity costs and maximum efficiency.

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Review of Energy Management Systems for Small and Medium Enterprises

Review of Energy Management Systems for Small and Medium Ent...

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Junior Conference on Lighting (Lighting)

作者： Gergana Vacheva Plamen Stanchev Nikolay Hinov Departement of Power Electronics Faculty of Electronic Engineering and Technologies Technical University of Sofia Sofia Bulgaria Departement of Information Technology in Industry Faculty of Computer Systems and Technologies Technical University of Sofia Sofia Bulgaria

This article provides an overview of systems and methodologies used for energy management in small and medium-sized industrial enterprises. The main goal of the presented development is to examine basic principles in the management of energy flows in industrial enterprises powered by various renewable energy sources and energy storage elements. With the addition of additional energy sources, energy efficiency would significantly increase, which would also lead to a reduction in electricity costs.

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Intelligent Tunicate Swarm-Optimization-Algorithm-Based Lightweight Security Mechanism in Internet of Health Things

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computers, Materials & Continua 2021年第1期66卷 551-562页

作者： Gia Nhu Nguyen Nin Ho Le Viet Gyanendra Prasad Joshi Bhanu Shrestha Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam Graduate School Duy Tan UniversityDa Nang550000Vietnam Department of Computer Science and Engineering Sejong UniversitySeoul05006South Korea Department of Electronic Engineering Kwangwoon UniversitySeoul01897South Korea

Fog computing in the Internet of Health Things(IoHT)is promising owing to the increasing need for energy-and latency-optimized health sector ***,clinical data(particularly,medical image data)are a delicate,highly protected resource that should be utilized in an effective and responsible manner to fulfil consumer ***,we propose an energy-efficient fog-based IoHT with a tunicate swarm-optimization-(TSO)-based lightweight Simon cipher to enhance the energy efficiency at the fog layer and the security of data stored at the cloud *** proposed Simon cipher uses the TSO algorithm to select the optimal keys that will minimize the deterioration of quality between the original and reconstructed(decrypted)*** this study,the decrypted image quality is preserved by the peak signal-to-noise ratio(PSNR)such that consumers can generate precise medical reports from IoHT devices at the application ***,a lightweight encryption step is implemented in the fog to improve energy efficiency and reduce additional computations at the cloud *** results indicate that the TSO-Simon model achieved a high PSNR of 61.37 dB and a pixel change rate of 95.31.

关键词： Internet of Health Things healthcare Simon cipher tunicate swarm optimization

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Joint Optimization of Sensing and Communication for Digital Twin Edge Networks

Joint Optimization of Sensing and Communication for Digital ...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Yi Chen Zheng Chang Timo Hämäläinen Geyong Min School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Information Technology University of Jyväskylä Jyväskylä Finland Department of Computer Science University of Exeter Exeter U.K.

Digital twin (DT) technology enables the replica of physical objects and environmental statuses of a physical system, which can be used for further simulation, analysis, and prediction. By combining DT with mobile edge computing (MEC), a new paradigm called digital twin edge networks (DITEN) is able to fill the gap between physical edge networks and digital systems and provide novel services to physical devices. Due to possible failure in data sensing, balancing sensing time and successful sensing rate needs to be considered to ensure the freshness of collected data in DITEN. Additionally, an optimal data scheduling policy is necessary to ensure efficient communication between physical devices and the edge server while maintaining the accuracy of DT. Therefore, this paper proposes a joint optimization problem for the sensing and communication for DITEN. Due to the nonconvex nature of the formulated problem, we decompose the original problem into three subproblems, and an iterative optimization algorithm is proposed to minimize the system overhead of DNT realization. The effectiveness of the proposed method is evaluated through extensive simulations.

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A coherent approach-based fine-tuning of segment anything model plus watershed algorithm for instance segmentation of mitochondria in electron microscopy images

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IEEE Access 2025年 13卷 98088-98105页

作者： Faska, Zahra Khrissi, Lahbib Mountasser, Imadeddine Haddouch, Khalid Akkad, Nabil El Alshathri, Samah El-Shafai, Walid Sidi Mohamed Ben Abdellah University Laboratory of Engineering Systems and Applications ENSA Fez Morocco Princess Nourah Bint Abdulrahman University College of Computer and Information Sciences Department of Information Technology P.O. Box 84428 Riyadh11671 Saudi Arabia Computer Science Department Riyadh11586 Saudi Arabia Menoufia University Faculty of Electronic Engineering Department of Electronics and Electrical Communications Engineering Menouf32952 Egypt

Increasingly available ultrastructural data from a continuously growing diversity of experimental conditions are driving new opportunities for fruitful neuroscientific hypotheses tested in intracellular compartments such as the nanoscale roles of, e.g., the mitochondria. Reliable morphological statistics are based on achieving highly accurate semantic segmentations of EM images. The state-of-the-art deep CNNs can be somewhat brittle;they tend to provide coarse and high-frequency-oscillatory solutions with discontinuities and false positives even for simple mitochondria segmentation. Historically, the current state-of-the-art in medical image segmentation would involve some variant of the encoder-decoder architecture, such as the U-Net architecture. The SAM does not perform as well, since it has not been explicitly trained for the task and does not demonstrate user-interactive, over one billion annotations mostly for natural images. However, the SAM may be applied to segment anything, including medical image segmentation challenging new datasets. This work is aimed at the difficult task of implementing domain adaptation in mitochondria segmentation within EM images obtained from various tissues and species, using deep learning. We do a systematic study to assess SAM's ability to perform segmentation in medical images, measure its performance on volumetric EM datasets, and show that it is powerful at segmenting instances even under challenging imaging conditions. We provide a fine-tuning SAM which can be naturally trained by SAM at an exemplary scale, benefiting from a diverse and large dataset over one million image masks in 11 modalities. This model would be able to perform precise segmentation for a wide range of targets under various imaging conditions, at the level of performance of specialized U-Net models, or even better. A visual comparison is shown between our fine-tuning SAM model and U-Net, along with an examination of different watershed post-processing st

关键词： Semantic Segmentation

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IEEE CAS Society Turns 75—Commemorative Events and Celebrations [Special Section on the 75th Anniversary of the IEEE Circuits and Systems Society]

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IEEE Circuits and Systems Magazine 2024年第4期24卷 17-21页

作者： Yongfu Li Fakhrul Zaman Rokhani Hanho Lee Kea-Tiong Tang Jie Chen Mohd Hafiz Ismail Yoko Uwate Molly Brackin Amara Amara Myung Hoon Sunwoo Department of Micro and Nano Engineering Shanghai Jiao Tong University Shanghai China Department of Computer and Communication Systems Engineering Universiti Putra Malaysia Serdang Malaysia Department of Electrical and Computer Engineering Inha University Incheon South Korea Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan Institute of Biomedical Engineering and Technology Fudan University Shanghai China Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Arau Malaysia Department of Electrical and Electronic Engineering Tokushima University Tokushima Japan Conference Catalysts LLC Gainesville FL USA Hangzhou International Innovation Institute Beihang University Beijing China Department of Electrical and Computer Engineering Ajou University Suwon South Korea

The IEEE Circuits and Systems (CAS) Society celebrates its 75th anniversary in 2024, showcasing its evolution from a Circuit Theory Group to a leading global technological force. This year, the Society introduces a commemorative logo that encapsulates its innovative spirit and a Promotion Toolkit to amplify the celebratory atmosphere across all chapters. The 75th CAS Society’s Global Celebration is set to engage members worldwide, with a virtual event on May 21st, 2024, featuring photo and video contests highlighting member creativity and experiences. The pinnacle of the celebration was at IEEE ISCAS 2024, where the 2nd Edition of “A Short History of Circuits and Systems” was launched, and contributions were recognized during the IEEE CAS Society Award ceremony. The Society, with 15,236 members and a strong global presence, continues to foster innovation and collaboration through its conferences, publications, and community programs, reflecting its commitment to advancing technology for the betterment of humanity.

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Void Handling by Utilizing Location-Based Assistance Through Trajectory Mapping

Void Handling by Utilizing Location-Based Assistance Through...

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International Conference on engineering, Applied Sciences, and technology (ICEAST)

作者： Phonepadith Phoummavong Vimontha Khieovongphachanh Khanthanou Luangxaysana Phouthong Southisombath Sathaporn Promwong Dept. Computer Engineering and IT Faculty of Engineering National University of Laos Vientiane Lao Dept. Electronic and Telecommunications Engineering Faculty of Engineering National University of Laos Vientiane Lao Department of Telecommunications Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

The Ad hoc Networks (MANETs) rely heavily on location-aided routing protocols due to their energy-saving capabilities and ability to extend the network lifetime, especially in emergency situations where private IP addresses are unavailable. However, the route discovery process of the location-aided routing (LAR) is ineffective in void zone environments where data packets cannot reach their intended destination. To address this issue, this paper presents a new approach called Location-aided base on trajectory that eliminates the void zone. The results demonstrate that the proposed method outperforms existing approaches in terms of reachability, making it a more robust alternative to the default location-aided routing protocol.

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Machine Learning based Comparative Analysis of Cervical Cancer Risk Classifications Algorithms

Machine Learning based Comparative Analysis of Cervical Canc...

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Advances in Computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： Tania Ganguly Peeta Basa Pati K. Deepa Tripty Singh Tolga Özer Department of Computer Science and Engineering Amrita School of Computing Bengaluru India Department of Electrical and Electronics Engineering Amrita School of Engineering Bengaluru India Technology Faculty Electric Electronic Engineering Afyon Kocatepe University Afyonkarahisar Turkey

Cervical cancer is a major health concern for women worldwide, and early detection is essential for successful treatment. Since symptoms often do not appear until later stages, early screening is necessary. Machine learning can help classify cervical cancer risk by analyzing patient datasets and identifying the important factors that predict the likelihood of emerging cervical cancer. This paper evaluates six different machine-learning approaches for analyzing risk factors associated with cervical cancer using a dataset of 838 instances with 36 features. Results show that the SVM classifier performs the best, with an accuracy of 99.60% which emphasize the possibility of utilizing machine learning to enhance the precision of cervical cancer risk assessment. This can result in the development of better screening and prevention techniques for cervical cancer, which can be more effective in identifying and managing this disease.

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Virtual Laboratory Learning Experience in engineering: An Extended technology Acceptance Model (TAM)

Virtual Laboratory Learning Experience in Engineering: An Ex...

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Sciences and Techniques of Automatic Control and computer engineering MI-STA, IEEE International Maghreb Meeting of the Conference on

作者： Ahmed Jamah Ahmed Alnagrat Khamiss M. S. Ahmed Muhannad Ismail Alkhallas Osama Abulaqasim Ibrahim Almakhzoom Syed Zulkarnain Syed Idrus Rizalafande Che Ismail Department of Computer Science and Information Technology Higher Institute of Science and Technology Wadi al-Shati Wadi al-Shati Fezzan Libya Department of Computer Science Faculty of Information Technology Sebha University Sebha Libya Department of Software Engineering Faculty of Engineering Technology in Zuwarah Zuwarah Libya Department of Communication Faculty of Business & Communication (FPK) Universiti Malaysia Perlis(UniMAP) Kangar Perlis Malaysia Faculty of Electronic Engineering Technology (FTKEN) Universiti Malaysia Perlis (UniMAP) Arau Malaysia

This research presents an enhanced version of the technology Acceptance Model (TAM), which integrates usability and learning objectives to evaluate the effect of adopting virtual laboratories on student performance. Data from 97 participants, gathered via a survey, was used to examine the correlation between perceived usefulness (PU), perceived ease of use (PEOU), and intention to use (IU) concerning their experiences and outcomes with a simulation-based virtual laboratory. A custom questionnaire was designed to assess TAM components, namely PU, PEOU, and IU, specifically in the context of virtual laboratory learning environments. Findings indicate that the integration of specific laboratory learning objectives fosters the creation of a more credible and authentic simulation tool. This, in turn, optimizes the learning process and enhances students' learning outcomes. The refined TAM model provides valuable insights into the determinants of user acceptance of virtual laboratories and offers practical guidance for educators and instructional designers to construct more effective and efficient virtual laboratory environments in educational contexts.

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