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IFIP Networking Conference

作者： Róża Goścień Department of Systems and Computer Networks Faculty of Information and Communication Technology Wroclaw University of Science and Technology Wroclaw Poland

ISBN: (数字)9783903176638

ISBN: (纸本)9798350390605

The recent research reveals a high potential and efficiency of machine learning (ML) algorithms applied to aid the optimization of telecommunication networks. Moreover, thanks to the tools of explainable artificial intelligence (XAI), it is possible to better understand and interpret the decisions of ML models, identify the features influencing them the most, and use that knowledge for further targeted optimization improvements. In this paper, we use these approaches to aid the optimization of the well-known and essential problem of dynamic routing in software-defined elastic optical networks (EONS). We use the XAI to verify which transmission and network state parameters influence the performance the most (expressed as a bandwidth blocking probability (BBP)) of a dynamic EON. The analysis reveals that two of the most relevant features are related to characteristics of the incoming traffic requests - the source node and the traffic prediction for the demand's source-destination nodes. Next, we use that data to propose six traffic prediction-and XAI-based demands ordering policies, which are used to improve a benchmark allocation algorithm. Then, we perform simulations to evaluate the policies' efficiency and compare them with reference methods. The results show that our targeted proposal is exceptionally efficient - the best policy allowed to reduce the BBP up to about 6.1%, representing 4203 Gbps of more served traffic compared to the best reference policy.

关键词： Machine learning algorithms Explainable AI Optical design Optical fiber networks Routing Prediction algorithms Resource management

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A Review of Satellite Image Analysis Tools 4th

A Review of Satellite Image Analysis Tools

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4th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2023

作者： Pawar, Bhushan Prakash, Vijay Garg, Lalit Galdies, Charles Buttigieg, Sandra Calleja, Neville Department of Computer Information Systems Faculty of Information and Communication Technology University of Malta MSD Msida2080 Malta Department of Computer Science and Engineering Graphics Era Hill University Dehradun India Environmental Management and Plan Division Institute of Earth Systems University of Malta Msida Malta Faculty of Health Sciences University of Malta Msida Malta Faculty of Medicine and Surgery University of Malta Msida Malta

ISBN: (纸本)9789819994410

The rapid growth of urban areas, population, and pollution presents a significant environmental challenge. Addressing these challenges requires innovative analytical approaches and data sources. This study focuses on the three-scale phenomena of the environmental system, physical environment, and regional surroundings, considering their implications on a global network scale. Remote sensing data, with its easy accessibility, offers new toolkits and methods to improve the global environment. It provides self-consistent measurements of vital physical attributes and surpasses traditional data sources regarding accuracy, efficiency, and coverage of larger geographical areas. This study aims to identify and analyze appropriate satellite image analysis tools for healthcare. The study objectives include studying available tools, analyzing their features, categorizing tools into open-source and commercial categories, and providing recommendations. This study emphasizes feature extraction and image enhancement parameters, which are crucial for image analysis. Further, this study provides a functional overview of various commercial and open-source satellite image analysis tools and suggests suitable tools for healthcare applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Geographic information systems

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PERFORMANCE ANALYSIS OF VLC-BASED LI-FI NLOS UNDERWATER CHANNEL USING ASK MODULATION SCHEME OVER WDM UNDER THE INFLUENCE OF AMBIENT LIGHT

PERFORMANCE ANALYSIS OF VLC-BASED LI-FI NLOS UNDERWATER CHAN...

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2025 International Conference on Energy, Power, Environment, Control and Computing, ICEPECC 2025

作者： Umer, Rao Behram Mushtaq, Farhan Khan, Faisal Hammad Nouman, Muhammad Hassan, Usman Amanullah Adnan, Muhammad Photonics And Communication Lab Department of Electrical Engineering University of Engineering & Technology Taxila Pakistan Electronics and Communication Systems Lab Department of Telecommunication Engineering University of Engineering & Technology Taxila Pakistan School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad Pakistan

ISBN: (纸本)9781837243235

Li-Fi is another term for Visible light communication (VLC) which operates by transmitting data through free space by using either Light Emitting Diodes (LEDs) or Laser Diodes (LDs). The technique finds substantial applications in scientific research as well as military applications when used underwater. VLC technology helps eliminate radio interference alongside providing replacement solutions for traditional underwater communication systems. The research develops and models a visible light wireless communication system through ambient light testing with two 550 nm and 450 nm LD light sources and Pin photodetector over 10 meters using Opti System software. The system uses Non-Return-to-Zero On-Off Keying (NRZ OOK) also known as Amplitude Shift Keying (ASK) modulation through Mach-Zehnder Modulator with WDM technology in NLOS environment. A 10 Gbps data transmission occurs through the clear ocean environment along a 10-meter channel with 0.0405 1/m absorption and 0.0025 1/m scattering. The 550 nm transmitted source emits its maximum Quality factor as 8.35 when BER analyzers operate under ambient light conditions and produce its minimum BER as 4.89e-11 under the same conditions. Examining similar ambient light influences reveals the BER analyzers demonstrate a maximum Quality factor of 8.62 and minimum BER of 18.11e-12 when operating under 450 nm transmitted light. © The Institution of Engineering & Technology 2025.

关键词： BIT ERROR RATE LASER DIODE LI-FI QUALITY FACTOR UNDERWATER WIRELESS communication

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BER Improvement of Cooperative Spectrum Sharing of NOMA in 5G Network 3

BER Improvement of Cooperative Spectrum Sharing of NOMA in 5...

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3rd IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer Engineering, MI-STA 2023

作者： Hassan, Mohamed Saeed, Rashid A. Mokhtar, Rania A. Hamid, Khalid Ali, Elmustafa Sayed Odeh, Nidhal Singh, Manwinder Khalifa, Othman O. Islam, Shayla Lovely Professional University Department of Wireless Communication Punjab Phagwara144001 India Taif University Department of Computer Engineering College of Computers and Information Technology Taif21944 Saudi Arabia University of Science & Technology Department of Communication Systems Engineering Omdurman Sudan Department of Electronics Engineering Khartoum Sudan University of Wollongong School of Electrical Computer and Telecommunications Engineering Australia International Islamic University Malaysia Department of Electrical and Computer Engineering Gombak Malaysia Libyan Center for Engineering Resarch and Information Technology Bani Waleed Libya Institute of Computer Science and Digital Innovation Ucsi University Malaysia Department of Computer Science Kuala Lumpur56000 Malaysia

ISBN: (纸本)9798350319897

Non-orthogonal multiple access is one of the best methods for addressing the needs of 5G wireless services (NOMA). The proliferation of mobile devices in recent years has increased the importance of cooperative spectrum sharing and utilization in wireless communication due to increases in the bit error rate (BER) brought on by collisions and interference. In this study, MIMO and Massive MIMO (M-MIMO) in the downlink (DL) NOMA power domain (PD) in conjunction with the Cooperative Cognitive Radio Network are proposed as two new ways for improving and evaluating BER in the 5G network (CCRN). Customers of NOMA compete for available channels on the CCRN in this first strategy. The second approach creates a dedicated channel for NOMA users. Three scenarios with varying distances, power location coefficients, and transmission power are used to evaluate the proposed methods in the MATLAB software program. It is assumed that four users will share a 90 MHz BW using QPSK modulation in all three scenarios. When evaluating the performance of the suggested system under the presumption of frequency-selective Rayleigh fading, concurrent interference cancellation (SIC) and unstable channel conditions are also considered. © 2023 IEEE.

关键词： 5G mobile communication systems

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Evaluating Generative Adversarial Networks for Virtual Contrast-Enhanced Kidney Segmentation using Res-UNet in Non-Contrast CT Images

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Multimedia Tools and Applications 2025年第18期84卷 20121-20144页

作者： Syamala, Maganti Chandrasekaran, Raja Balamurali, R. Rani, R. Hashmi, Arshad Kiran, Ajmeera Rajaram, A. Assistant Professor Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Guntur District Andhra Pradesh Vaddeswaram522502 India Department of ECE Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Tamil Nadu Chennai India Centre for non linear systems Chennai institute of technology Chennai India Department of ECE Vemu Institute of Technology Tirupathi-chittoor Highway P. Kothakota Chittoor District AP Pakala India King Abdulaziz University P.O. Box 344 Rabigh21911 Saudi Arabia Department of Computer Science and Engineering MLR Institute of Technology Dundigal Telangana Hyderabad500043 India Department of Electronics and Communication Engineering EGS Pillay Engineering College Nagapattinam611002 India

This study addresses the challenges of accurately segmenting kidneys in non-contrast CT images;where Convolutional neural networks (CNNs) perform best. The main goal is to investigate how well a Generative Adversarial Network (GAN) performs in producing virtual contrast-enhanced (vCECT) images from non-contrast sources. A GAN model is trained to generate simulated contrast-enhanced images that preserve pertinent information throughout translation by utilizing a dataset of 286 paired non-contrast and contrast-enhanced images. Following, 20 pairs of non-contrast and vCECT pictures are used to assess the performance of a unique segmentation model named Res-U-Net. The Res-U-Net architecture, which combines a U-Net design with residual connections, is optimized to efficiently extract detailed information from original and vCECT images. Image preprocessing methods like Hounsfield windowing with histogram equalization are used to improve the quality of the data before it is fed into the deep neural network. Dice similarity coefficient (DSC) is used to measure Res-U-Net's performance and acts as a benchmark against the most advanced kidney segmentation techniques. ResU-Net's performance is evaluated using the DSC. When compared to state-of-the-art methods for kidney segmentation recognition, the ResU-Net systems with intact connections achieved a DSC value of 0.97 percent for organs recognition and 0.83 percent for segmentation approaches. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Generative adversarial networks

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An energy-aware routing scheme based on a virtual relay tunnel in flying ad hoc networks

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Alexandria Engineering Journal 2024年 91卷 249-260页

作者： Hosseinzadeh, Mehdi Ali, Saqib Mohammed, Adil Hussein Lansky, Jan Mildeova, Stanislava Yousefpoor, Mohammad Sadegh Yousefpoor, Efat Hassan Ahmed, Omed Rahmani, Amir Masoud Mehmood, Asif Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Department of Information Systems College of Economics and Political Science Sultan Qaboos University Al Khoudh Muscat Oman Department of Communication and Computer Engineering Faculty of Engineering Cihan University-Erbil Kurdistan Region Iraq Department of Computer Science and Mathematics Faculty of Economic Studies University of Finance and Administration Prague Czech Republic Department of Computer Engineering Dezful Branch Islamic Azad University Dezful Iran Department of Information Technology University of Human Development Sulaymaniyah Iraq Future Technology Research Center National Yunlin University of Science and Technology Yunlin Taiwan Department of Biomedical Engineering Gachon University Gyeonggi-do Seongnam-si13120 Korea Republic of

Flying ad hoc networks (FANETs) tackle diverse challenges, for example, dynamic topological structure, high mobility of nodes, low density, and energy restrictions. These challenges make problems in designing reliable and stable routing in FANETs. Hence, the design of a routing algorithm is essential for transferring data between drones. In this paper, an energy-aware routing scheme based on a virtual relay tunnel (EARVRT) is proposed in flying ad hoc networks. EARVRT includes a virtual relay tunnel (VRT) that manages relay nodes in the route discovery process and lowers network overhead. Moreover, three metrics, namely route energy, hop counts, and a new metric called path correlation are regarded in the path selection operation. Note that correlation is defined with regard to two scales, including the cosine similarity of two nodes and their distance. EARVRT is evaluated according to delay, network longevity, consumed energy, and packet delivery rate. Then, our scheme is compared with three methods, namely LoCaL, O-LAR, and PSO-GLFR. These results show the superiority and success of EARVRT in comparison with other algorithms. © 2024 The Author(s)

关键词： Drones

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Advancements in Lung Cancer Diagnosis: A Comprehensive Study on the Role of PCA, LDA, and t-SNE in Deep Learning Frameworks 1

Advancements in Lung Cancer Diagnosis: A Comprehensive Study...

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1st Asian Conference on communication and Networks, ASIANComNet 2024

作者： Vikas, B. Makkapati, Satya Sukumar Bogireddy, Srinivasa Rao Balamurugan, K.S. Deepa, M. Koneru Lakshmaiah Education Foundation Bowrampet Department of Computer Science and Engineering Telangana Hyderabad500043 India Acharya Nagarjuna University Department of Computer Science and Engineering A.P Guntur District India Horizon Systems Inc PhoenixAZ United States Karpaga Vinayaga College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Chengalpattu India Sri Shakthi Institute of Engineering and Technology Department of IT Coimbatore India

ISBN: (纸本)9798350367003

In the ever-evolving domain of medical imaging, the integration of deep learning techniques holds the promise of transformative advancements. This research delved into the potential of employing data transfer within deep learning architectures for the automated detection of three distinct lung cancer types. Leveraging sophisticated methodologies like linear discriminant analysis (LDA), t-SNE, and PCA, the study aimed to enhance accuracy and efficiency in detecting malignancies from lung CT scan images. On rigorous evaluation, the models demonstrated compelling accuracy rates: salivary gland-type lung tumors at 9 0. 5%, pleomorphic (spindle/giant cell) carcinoma at 88.2%, and primary pulmonary sarcomas at 91.3%. Additionally, ROC curve analysis further highlighted the robust discriminative capability of the models across varied decision thresholds. The promising results accentuate the potential of integrating data transfer techniques with deep learning in a clinical setting. This research not only exhibits a significant stride in lung cancer detection but also paves the path for further innovations in automated medical image analysis. © 2024 IEEE.

关键词： Lung cancer

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Towards Blockchain-based Decentralized Employee Transfer System 6

Towards Blockchain-based Decentralized Employee Transfer Sys...

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6th International Conference on Blockchain Computing and Applications, BCCA 2024

作者： Zaib, Alam Mustafa, Ehzaz Khan, Ahsan Khattak, Hasan Ali Ibrahim, Isa Ali Namoun, Abdallah Shuja, Junaid Ahmad, Raja Wasim Department of Computer Science Comsats University Islamabad Abbottabad Campus Pakistan Faculty of Computing & Information Technology Sohar University Sohar Oman School of Information and Communication Technology Federal University of Technology Imo Owerri1526 Nigeria AI Centre Faculty of Computer and Information Systems Islamic University of Madinah Madinah42351 Saudi Arabia Department of Computer Science Southeast Missouri State University Cape GirardeauMO United States Department of Computer & Information Sciences Ajman University Ajman United Arab Emirates

ISBN: (纸本)9798350351538

Employees are the main driving force in organizations that undergo recruitment, promotion, and transfer. There are many employee management systems, but most of them are centralized. Centralization leads to problems such as lack of transparency, auditability issues, vulnerability, and a single point of failure. Blockchain technology addresses these concerns. Despite some blockchain-based HRM and employee management systems, none of the existing blockchain-based systems have addressed the problems of employee transfers. We propose a secure and transparent blockchain-based employee transfer (E-transfer) system to address this. The proposed system uses smart contracts for transfer management, recording outcomes on an unchangeable ledger. We conducted tests on Hyperledger Fabric for our proposed system. Our study aims to introduce an automated, auditable, and efficient transfer process. The findings of the study validate the effectiveness of the blockchain-based E-transfer system. © 2024 IEEE.

关键词： Smart contract

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So Timely, Yet So Stale: The Impact of Clock Drift in Real-Time systems

arXiv

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arXiv 2024年

作者： Salimnejad, Mehrdad Pappas, Nikolaos Kountouris, Marios The Department of Computer and Information Science Linköping University Sweden The Communication Systems Dept. EURECOM France The Department of Computer Science and Artificial Intelligence University of Granada Spain

In this paper, we address the problem of timely delivery of status update packets in a real-time communication system, where a transmitter sends status updates generated by a source to a receiver over an unreliable channel. The timestamps of transmitted and received packets are measured using separate clocks located at the transmitter and receiver, respectively. To account for possible clock drift between these two clocks, we consider both deterministic and probabilistic drift scenarios. We analyze the system's performance regarding the Age of Information (AoI) and derive closed-form expressions for the distribution and the average AoI under both clock drift models. Additionally, we explore the impact of key system parameters on the average AoI through analytical and numerical results. Copyright © 2024, The Authors. All rights reserved.

关键词： Transmitters

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Evaluation of Bfloat16, Posit, and Takum Arithmetics in Sparse Linear Solvers

arXiv

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arXiv 2024年

作者： Hunhold, Laslo Quinlan, James Parallel and Distributed Systems Group University of Cologne Cologne Germany Department of Computer Science University of Southern Maine Portland ME United States

Solving sparse linear systems lies at the core of numerous computational applications. Consequently, understanding the performance of recently proposed alternatives to the established IEEE 754 floating-point numbers, such as bfloat16 and the tapered-precision posit and takum machine number formats, is of significant interest. This paper examines these formats in the context of widely used solvers, namely LU, QR, and GMRES, with incomplete LU preconditioning and mixed precision iterative refinement (MPIR). This contrasts with the prevailing emphasis on designing specialized algorithms tailored to new arithmetic formats. This paper presents an extensive and unprecedented evaluation based on the SuiteSparse Matrix Collection—a dataset of real-world matrices with diverse sizes and condition numbers. A key contribution is the faithful reproduction of SuiteSparse’s UMFPACK multifrontal LU factorization and SPQR multifrontal QR factorization for machine number formats beyond single and double-precision IEEE 754. Tapered-precision posit and takum formats show better accuracy in direct solvers and reduced iteration counts in indirect solvers. Takum arithmetic, in particular, exhibits exceptional stability, even at low precision. © 2024, CC BY.

关键词： Iterative methods

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