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Standardization Review on Non-Terrestrial Networks 39

Standardization Review on Non-Terrestrial Networks

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39th International Conference on Information Networking, ICOIN 2025

作者： Kyung, Yeunwoong Lee, Jaewook Ko, Haneul Oh, Seungmin Lee, Jaehwan Kim, Youngjun Kongju National University Div. of Info. & Comm. Eng Cheonan South Korea Pukyong National University Dep. of Info. and Comm. Engineering Busan South Korea Kyung Hee University Dep. of Electronic Eng Yongin-si South Korea Kongju National University Dep. of Computer Science and Eng Cheonan South Korea Kyungnam University School of Computer Science and Eng Changwon South Korea

ISBN: (纸本)9798331506940

As the demand for global connectivity increases, non-terrestrial networks (NTNs), particularly satellite-based systems, have gained significant attention in communication network standardization. The 3rd Generation Partnership Project (3GPP) has been at the forefront of developing standards that incorporate satellite communications into the broader terrestrial network framework. This paper reviews the progression of NTN standardization, focusing on three key stages: (1) the use of satellites as relays or the next generation NodeBs (gNBs), (2) the integration of user plane functions (UPF) within satellites, and (3) the inclusion of control plane network functions (NFs) within satellites. These developments in standardizations reflect a shift from basic relay functions to fully integrated satellite networks. © 2025 IEEE.

关键词： 3GPP Standards Control Plane Network Functions Non-Terrestrial Networks

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Blockchain-based Device Identity Management with Consensus Authentication for IoT Devices 19

Blockchain-based Device Identity Management with Consensus A...

引用

19th IEEE Annual Consumer Communications and Networking Conference, CCNC 2022

作者： Mukhandi, Munkenyi Damiao, Francisco Granjal, Jorge Vilela, Joao P. University of Coimbra Cisuc Dep. of Informatics Engineering Coimbra Portugal Pdmfc Lisbon Portugal University of Porto Faculty of Sciences Cracs Inesctec Cisuc Dep. of Computer Science Porto Portugal

ISBN: (纸本)9781665431620

To decrease the IoT attack surface and provide protection against security threats such as introduction of fake IoT nodes and identity theft, IoT requires scalable device identity and authentication management. This work proposes a blockchain-based identity management approach with consensus authentication as a scalable solution for IoT device authentication management. The proposed approach relies on having a blockchain secure tamper proof ledger and a novel lightweight consensus-based identity authentication. The results show that the proposed decentralised authentication system is scalable as we increase number of nodes. © 2022 IEEE.

关键词： Authentication

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Design of Technology for Secure File Storage Based on Hybrid Cryptography Methods: Short Overview

Design of Technology for Secure File Storage Based on Hybrid...

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Smart Information Systems and Technologies (SIST), IEEE International Conference on

作者： Gulnara A. Abitova Abu Said Manap Korlan Kulniyaziva Vladimir Nikulin Dep. of Electrical Engineering and Computer Science State University of New York Binghamton NY USA Dep. of Computer Engineering Astana IT University Astana Kazakhstan Master’s Degree Astana IT University Astana Kazakhstan Dep. of System Analysis and Management L.N. Gumilyov Eurasian National University Astana Kazakhstan Dep. of Electrical Engineering and Computer Science Binghamton University Binghamton NY USA

ISBN: (数字)9798350374865

ISBN: (纸本)9798350374872

In the era of pervasive digital data, ensuring secure file storage has become a paramount concern. This paper explores the significance of hybrid cryptography for design of an advanced tools and techniques for secure file storage. Hybrid cryptography, combining symmetric and asymmetric encryption, offers robust protection against unauthorized access, tampering, and data loss. The article reviews recent cryptography literature, highlighting the importance of secure file storage in today's interconnected world and examining the benefits of hybrid cryptography. The analysis of articles on cryptography reveals emerging trends and challenges. Post-quantum cryptography addresses concerns about quantum threats, while blockchain-based cryptography enhances security in IoT data sharing. Homomorphic encryption enables computations on encrypted data, and cryptographic protocols that protect privacy enable safe multi-party computation. Machine learning's intersection with cryptanalysis introduces efficiency but raises ethical considerations. The paper further discusses advancements and trends in cryptography techniques, including post-quantum cryptography, homomorphic encryption, zero-knowledge proofs, post-quantum key exchange, secure multi-party computation, and post-quantum signature schemes. These developments aim to ensure long-term security against quantum attacks, enable privacy-preserving computations, and enhance the confidentiality, integrity, and authentication of digital communication and data storage. In conclusion, the paper advocates for the adoption of hybrid cryptography in secure file storage systems. Its combination of symmetric and asymmetric encryption, along with its adaptability to evolving security landscapes, positions hybrid cryptography as a formidable approach to data protection. By embracing hybrid cryptography and staying informed about the latest advancements, organizations can navigate the digital age with confidence, ensuring the confidentiality

关键词： Navigation Reviews Organizations Machine learning Market research Multi-party computation Complexity theory

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Performance assessment of low-cost sensors under representative indoor air conditions 17

Performance assessment of low-cost sensors under representat...

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17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022

作者： Alonso, Maria Justo Jørgensen, Rikke Bramming Madsen, Henrik Mathisen, Hans Martin NTNU Dep. Energy and Process Engineering Trondheim Norway NTNU Dep. Industrial Economics and Technology Management Trondheim Norway DTU Applied Mathematics and Computer Science Kgs. Lyngby Denmark

Recently many indoor air quality (IAQ) low-cost sensors (LCS) have arrived in the market. Being cost-effective encourages sensor installation in many different situations for IAQ-monitoring and sometimes for control of HVAC systems. However, very often these sensors are delivered with incomplete information and there are many doubts about their performance, reliability, and response to aging or drift. In this article, an evaluation of the performance of eight equal in-house mounted IAQ stations is presented. Pre-calibrated LCS measuring CO2, temperature, RH, and particulate matter were connected to a RaspberryPi. Some tests were repeated with 6 months of difference and some with one year. In general, all stations responded similarly to the events to which they were exposed, the inter-sensor correlations values were higher than 0.95. LCS reacted similarly to the sources (trends) but with quantitative disparities. Sensor calibration is needed but when included, the tested LCS seem fit for IAQ measurements. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

关键词： Carbon dioxide

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Pollutant correlation analysis in measurements at four classrooms in four Norwegian schools 17

Pollutant correlation analysis in measurements at four class...

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17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022

作者： Alonso, Maria Justo Jørgensen, Rikke Bramming Madsen, Henrik Mathisen, Hans Martin Dep. Energy and Process Engineering Trondheim Norway Dep. Industrial Economics and Technology Management Trondheim Norway Technical University of Denmark Applied Mathematics and Computer Science Kgs. Lyngby Denmark

Demand-controlled ventilation (DCV) is often used in school buildings to save energy by modulating the airflow rates based on the demand. However, other pollutants and indoor air parameters may affect health and are not necessarily correlated to CO2. In this study investigation of correlations between PM2.5, formaldehyde, absolute humidity, CO2 and temperature are performed. Measurements of these parameters were performed between two months and one year, positioned in the supply air in four CO2-based DCV classrooms at four different schools. The time series of measurements were de-trended to avoid overestimating cross-correlation functions. From the measurements we have concluded the need to measure: 1) pollutants related to human activities (CO2) 2) pollutants that infiltrate from processes like combustion or traffic outdoors (PM2.5), and 3) parameters related to other "non-combustion-related activities" indoors, heat sources and moisture loads (temperature). Formaldehyde from building materials seems to be mostly degassed in these older than one-year buildings, but this study should be repeated on newer buildings. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

关键词： Formaldehyde

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Intelligent Recognition of Immune Cells: Analysis and Research 19

Intelligent Recognition of Immune Cells: Analysis and Resear...

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19th IEEE International Conference on e-Business engineering, ICEBE 2023

作者： Li, Chih-En Liu, Wei-Lun Lai, Kun-Yi Chiang, Yu-Hsiang Yan, Xiaowei Chen, Hao-Xiang Li, Hsu-Ching Cheng, Wan-Shu National Kaohsiung University of Science and Technology Department of Electrical Engineering Kaohsiung Taiwan Institute for Systems Biology Seattle Washington United States Providence University Dep. of Computer Science and Information Management Taichung Taiwan

ISBN: (纸本)9798350325553

Immunotherapy utilizes the potential of the patient's immune system to fight disease. T-lymphocytes have become the central focus of the immune system in the fight against cancer. One of the fundamental studies in immunotherapy is how to accurately identify various types of immune cells. Therefore, the study of immune-related cells will be an important reference for the treatment of COVID19 or other related diseases. In this paper, a series of experiments were conducted with COVID-19 patients as the starting point to design a strategy to identify the important subtypes of CD$4^{+}$T cells. In this paper, an intelligent machine learning algorithm is proposed according to the results of different experiments of linear and nonlinear dimension reduction algorithms, integrating the important characteristics of these two algorithms and improving the performance. Our experimental results show that the algorithm designed based on the front-end experiments can effectively distinguish the important lymphocytes. The proposed algorithm not only improves the performance, but also the dimension reduction procedure keeps the important features of both global and regional data. The experimental results of this paper will be beneficial for the subsequent analysis of the clustering in identifying important subtypes of CD$4^{+}$T cells. Most importantly, this wm significantly improve the procedure of manually integrating and labeling the recorded data after several tedious and monotonous analyses with external software. © 2023 IEEE.

关键词： COVID-19

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Prediction of Electrical Characteristics of a-IGZO TFT Based on Transfer Learning-Based Variational Autoencoder

Prediction of Electrical Characteristics of a-IGZO TFT Based...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Bea, Khean-Thye Wei-Hsuan Lin, Shih-Shin Hu Lin, Da-Zheng Hu, Hsin-Hui Chen, Xiu-Zhi Lin, Ting-Ru Chen, Yen-Lin Chen, Kun-Ming Cheng, Wai Khuen National Taipei University of Technology Dep. of Electronic Engineering Taipei106 Taiwan National Taipei University of Technology Dep. of Computer Science and Information Engineering Taipei106 Taiwan Taiwan Semiconductor Research Institute Hsinchu30078 Taiwan Universiti Tunku Abdul Rahman Faculty of Information and Communication Technology Kampar31900 Malaysia

ISBN: (纸本)9798350337020

In this study, we proposed a transfer-learning based variational autoencoder model for predicting the electrical characteristics in the parameter tuning process of a-IGZO TFT structure design. The result achieve a high R2 score of 0.9704 with a low-computing-power hardware-friendly method that reduced time consumption significantly compared to prior approaches. The findings have practical implications for mitigating the time-consuming nature of TCAD simulations, and the method can expand to various types of input data while ensuring high performance and generalization. We demonstrated significant improvement in generalization and accuracy through a k-fold validation. © 2023 IEEE.

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A Review of Grid-Connected Inverters and Control Methods Under Unbalanced Grid Conditions

A Review of Grid-Connected Inverters and Control Methods Und...

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Power Electronic and Drive Systems and Technologies Conference (PEDSTC)

作者： Milad Ghavipanjeh Marangalu Fazal Ur Rehman Naser Vosoughi Kurkdjian Dep. Of Electrical and Computer Engineering Computer Queen’s University Kingston Ontario Canada Dep. Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Faculty of Electrical and Computer Engineering San Diego State University San Diego CA USA

ISBN: (数字)9798331533946

ISBN: (纸本)9798331533953

Grid-connected inverters play a pivotal role in integrating renewable energy sources into modern power systems. However, the presence of unbalanced grid conditions poses significant challenges to the stable operation of these inverters. This review paper provides a comprehensive overview of grid-connected inverters and control methods tailored to address unbalanced grid conditions. Beginning with an introduction to the fundamentals of grid-connected inverters, the paper elucidates the impact of unbalanced grid voltages on their performance. Various control strategies, including voltage and current control methods, are examined in detail, highlighting their strengths and limitations in mitigating the effects of grid imbalance. Lastly, the review identifies emerging trends and future research directions in the field, emphasizing the need for innovative solutions to address the evolving challenges posed by unbalanced grid conditions in the context of renewable energy integration.

关键词： Current control Photovoltaic systems Renewable energy sources Technological innovation Reviews Pressing Market research Inverters Power systems Voltage control

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Detecting 5G Signal Jammers with Autoencoders Based on Loose Observations

Detecting 5G Signal Jammers with Autoencoders Based on Loose...

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IEEE Globecom Workshops

作者： Matteo Varotto Stefan Valentin Stefano Tomasin Dep. of Information Engineering University of Padova Padova Italy Dep. of Computer Science Darmstadt University of Applied Sciences Darmstadt Germany Dep. of Information Engineering Dep. of Mathematics University of Padova Padova Italy

Fifth-generation (5G) networks are prone to jamming attacks, which are particularly dangerous in mission-critical applications such as factory automation. In this paper, we present a simple method to detect jamming attacks with machine learning techniques operating on in-phase and quadrature (IQ) modulated signals. In particular, a convolutional autoencoder (CAE) learns the structure of the clean signal to distinguish it from jammed signals in real time. This approach requires only a loose synchronization to the OFDM symbol, while equalization and decoding are not necessary. Despite its simplicity, our technique has shown high detection rates in experiments on a 5G testbed.

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COVID-19 detection from Xray and CT scans using transfer learning

COVID-19 detection from Xray and CT scans using transfer lea...

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2021 International Conference of Women in Data science at Taif University, WiDSTaif 2021

作者： Berrimi, Mohamed Hamdi, Skander Yahia Cherif, Raoudha Moussaoui, Abdelouahab Oussalah, Mourad Chabane, Mafaza Dep. of Computer Science University of Ferhat Abbes Setif I Setif Algeria Dep. of Computer Science and Engineering University of Oulu Oulu Finland

ISBN: (纸本)9781665449489

Since the novel coronavirus SARS-CoV-2 outbreak, intensive research has been conducted to find suitable tools for diagnosis and identifying infected people in order to take appropriate action. Chest imaging plays a significant role in this phase where CT and Xrays scans have proven to be effective in detecting COVID-19 within the lungs. In this research, we propose deep learning models using Transfer learning to detect COVID-19. Both X-ray and CT scans were considered to evaluate the proposed methods. © 2021 IEEE.

关键词： Medical imaging

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