{"title":"Sky visibility analysis under urban networks: A stochastic geometry approach","authors":"Heejung Yu , Sooyeob Jung , Joon Gyu Ryu , Junse Lee","doi":"10.1016/j.icte.2024.12.002","DOIUrl":"10.1016/j.icte.2024.12.002","url":null,"abstract":"<div><div>We propose a novel framework to analyze a ground user’s sky visibility in an urban outdoor network. In order to measure the user’s sky visibility, the point process theory is used to represent buildings of urban outdoor networks. We characterize the line-of-sight (LoS) probability between the ground user and a non-terrestrial network node such as a low-Earth-orbit (LEO) satellite. Then, we quantify how many satellites are observable by the user. This provides intuition for cell planning by answering how many satellites are needed for a ground user without discontinuity of network services. Our analysis is cross-validated by numerical experiments.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 157-160"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ICT ExpressPub Date : 2025-02-01DOI: 10.1016/j.icte.2024.09.006
Jiajian Li , Yanjun Shi , Yu Yang
{"title":"Two-stage optimization of computation offloading for ICN-assisted mobile edge computing in 6G network","authors":"Jiajian Li , Yanjun Shi , Yu Yang","doi":"10.1016/j.icte.2024.09.006","DOIUrl":"10.1016/j.icte.2024.09.006","url":null,"abstract":"<div><div>This paper investigates QoS-aware computation offloading issues for mobile edge computing in the 6G network. To minimize the end-to-end delay, we harness the Information-Centric Network (ICN) to ensure resource-constrained mobile user offloading computation-sensitive tasks in a distributed manner. Then, a two-stage approach based on a Multi-Agent Reinforcement Learning (MARL) algorithm entwined with optimization-embedding offloading ratio is proposed to enhance server selection for load balancing. Numeral results demonstrate that, with reference to a workshop-scale scenario, the proposed method can achieve outperformed performance in reducing delay and balancing loads on edge servers than the other four baseline schemes.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 26-33"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ICT ExpressPub Date : 2025-02-01DOI: 10.1016/j.icte.2024.09.005
Israel Araújo , Luis Guilherme Silva , Carlos Brito , Dugki Min , Jae-Woo Lee , Tuan Anh Nguyen , Erico Leão , Francisco A. Silva
{"title":"DDS-P: Stochastic models based performance of IoT disaster detection systems across multiple geographic areas","authors":"Israel Araújo , Luis Guilherme Silva , Carlos Brito , Dugki Min , Jae-Woo Lee , Tuan Anh Nguyen , Erico Leão , Francisco A. Silva","doi":"10.1016/j.icte.2024.09.005","DOIUrl":"10.1016/j.icte.2024.09.005","url":null,"abstract":"<div><div>Effective management of catastrophic events in high-risk zones necessitates a holistic technological approach to protect ecosystems, biodiversity, and native populations. Limitations in sensor range and connectivity hamper real-time data gathering in secluded areas, while financial and technical hurdles hinder the creation of cost-effective, automated systems. This study presents stochastic models, the LoRaW protocol, and cloud technology to enhance sensor deployment simulations. Wireless Sensor Networks and LoRa technology are crucial for extensive monitoring and communication infrastructures. Stochastic Petri Net models optimize system components by assessing crucial performance indicators, such as average response time and system utilization, thus improving disaster response and supporting research hypotheses.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 34-40"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ICT ExpressPub Date : 2025-02-01DOI: 10.1016/j.icte.2024.09.017
Bo Yang , Siyuan Xu , Lirong Yin , Chao Liu , Wenfeng Zheng
{"title":"Disparity estimation of stereo-endoscopic images using deep generative network","authors":"Bo Yang , Siyuan Xu , Lirong Yin , Chao Liu , Wenfeng Zheng","doi":"10.1016/j.icte.2024.09.017","DOIUrl":"10.1016/j.icte.2024.09.017","url":null,"abstract":"<div><div>A novel disparity estimation pipeline is proposed for 3D reconstruction of dynamic soft tissues in minimally invasive surgery (MIS), which uses a deep generative network to learn manifold distributions of reasonable disparity maps from past stereo images in the training phase, and transforms stereo matching into an optimization problem with respect to the low-dimensional latent vector of the learned generator in the application phase. The proposed pipeline is particularly suitable for dynamic MIS scenarios with insufficient training data, as the photometric loss is explicitly used in the application phase and the scenario priors are introduced via a deep generative network.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 74-79"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ICT ExpressPub Date : 2025-02-01DOI: 10.1016/j.icte.2024.09.010
Hyeyeon Na , Hosung Park , Hee-Youl Kwak , Seok-Ki Ahn
{"title":"Learning strategies for neural min-sum decoding of LDPC codes","authors":"Hyeyeon Na , Hosung Park , Hee-Youl Kwak , Seok-Ki Ahn","doi":"10.1016/j.icte.2024.09.010","DOIUrl":"10.1016/j.icte.2024.09.010","url":null,"abstract":"<div><div>The min-sum (MS) decoding for low-density parity-check codes, though less complex than the sum–product algorithm, suffers from worse error-correcting performance. For enhancement, neural MS decoders leveraging deep learning have recently been introduced, but how to train them has not been sufficiently discussed. In this paper, we propose a novel dataset construction method and also propose systematic learning strategies by finding a good combination of dataset composition, loss functions, weight sharing, weight assignment, and weight update method. Simulations demonstrate that the proposed method achieves better error-correcting performance than other works, especially in the error floor region, within a limited number of iterations.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 161-166"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ICT ExpressPub Date : 2025-02-01DOI: 10.1016/j.icte.2024.08.009
Yue Han , Rui-Feng Yu , Jie Wang , Shuai Yan , Shi-Wei Huo , Fu-Quan Li
{"title":"Evidential reasoning rule with dynamic reliability for performance assessment of wireless sensor network","authors":"Yue Han , Rui-Feng Yu , Jie Wang , Shuai Yan , Shi-Wei Huo , Fu-Quan Li","doi":"10.1016/j.icte.2024.08.009","DOIUrl":"10.1016/j.icte.2024.08.009","url":null,"abstract":"<div><div>The performance of wireless sensor network (WSN) continues to change over time, and it is required to track the WSN performance accurately. In this paper, a new assessment model known as the evidential reasoning rule with dynamic reliability (ERr-DR) is proposed. In the ERr-DR, the evidence reliability evolves from the traditional static value to a dynamic value, which can reveal the impact of external noise on network performance reasonably. As an effective extension of traditional ER rule, the ERr-DR has excellent modeling ability. Furthermore, by analyzing the physical meanings of model parameters in detail, an optimization objective with targeted constraints is established. Compared with the existing optimization strategies, this not only improves the output accuracy of ERr-DR, but also maintains the interpretability of assessment results. Finally, A case study of a simulated WSN scenario validates the effectiveness of the proposed model.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 19-25"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cross-domain autonomous driving visual segmentation based on enhanced target data learning","authors":"Chaoyu Rao , Xiaoyong Fang , Yunzhe Zhang , Wanshu Fan , Dongsheng Zhou","doi":"10.1016/j.icte.2024.09.020","DOIUrl":"10.1016/j.icte.2024.09.020","url":null,"abstract":"<div><div>Within the broader context of Information and Communications Technology (ICT), the quest for reliable and scalable visual segmentation methods poses significant challenges, particularly in autonomous driving, where real-world scene complexity requires advanced solutions. To address data scarcity and improve segmentation performance, we propose a novel unsupervised domain adaptation (UDA) approach that enhances target domain learning. Our method introduces multiple perturbations consistency, leveraging spatial context within the target domain to improve recognition. By applying perturbations at input and feature levels and using a consistency loss, we enhance contextual learning. Additionally, a weight mapping technique reduces the impact of detrimental source domain information. Experimental results demonstrate that our approach outperforms baseline methods on the GTAV<span><math><mo>→</mo></math></span>Cityscapes and SYNTHIA<span><math><mo>→</mo></math></span>Cityscapes datasets.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 53-58"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ICT ExpressPub Date : 2025-02-01DOI: 10.1016/j.icte.2024.10.009
Carlos Melo , Glauber Gonçalves , Francisco Airton Silva , Iure Fé , Ericksulino Moura , André Soares , Eunmi Choi , Dugki Min , Jae-Woo Lee , Tuan Anh Nguyen
{"title":"Transactional dynamics in hyperledger fabric: A stochastic modeling and performance evaluation of permissioned blockchains","authors":"Carlos Melo , Glauber Gonçalves , Francisco Airton Silva , Iure Fé , Ericksulino Moura , André Soares , Eunmi Choi , Dugki Min , Jae-Woo Lee , Tuan Anh Nguyen","doi":"10.1016/j.icte.2024.10.009","DOIUrl":"10.1016/j.icte.2024.10.009","url":null,"abstract":"<div><div>Blockchain, often integrated with distributed systems and security enhancements, has significant potential in various industries. However, environmental concerns and the efficiency of consortia-controlled permissioned networks remain critical issues. We use a Stochastic Petri Net model to analyze transaction flows in Hyperledger Fabric networks, achieving a 95% confidence interval for response times. This model enables administrators to assess the impact of system changes on resource utilization. Sensitivity analysis reveals major factors influencing response times and throughput. Our case studies demonstrate that block size can alter throughput and response times by up to 200%, underscoring the need for performance optimization with resource efficiency.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 87-92"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ICT ExpressPub Date : 2025-02-01DOI: 10.1016/j.icte.2024.10.004
Jong-Ho Lee, Jiho Song
{"title":"RIS reflection pattern design for vehicular platoon communications in mmWave channels","authors":"Jong-Ho Lee, Jiho Song","doi":"10.1016/j.icte.2024.10.004","DOIUrl":"10.1016/j.icte.2024.10.004","url":null,"abstract":"<div><div>In this paper, we propose a reflection pattern design scheme for reconfigurable intelligent surface (RIS) assisted vehicular platoon communications in millimeter wave (mmWave) channels. We focus on optimizing the reflection pattern of a RIS that is installed in a roadside unit to maximize the broadcast information rate from the lead vehicle in a platoon to each following member vehicle. We show that this problem can be effectively solved using semidefinite programming. Next, we propose a reflection pattern design scheme for the RIS that maximizes its reflection gain by exploiting the angle of departure, angle of arrival, and path loss information between each vehicle and the RIS in mmWave channels. Finally, we present numerical results that demonstrate the effectiveness of our proposed reflection pattern design scheme.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 105-109"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ICT ExpressPub Date : 2025-02-01DOI: 10.1016/j.icte.2024.11.003
Samuel Kakuba , Dong Seog Han
{"title":"Addressing data scarcity in speech emotion recognition: A comprehensive review","authors":"Samuel Kakuba , Dong Seog Han","doi":"10.1016/j.icte.2024.11.003","DOIUrl":"10.1016/j.icte.2024.11.003","url":null,"abstract":"<div><div>Speech emotion recognition (SER) is a critical field within affective computing, aiming to detect and classify emotional states from speech signals, which vary dynamically over time. These signals encode complex relationships between features at multiple time scales, effectively reflecting a speaker’s emotional state. Despite significant progress, SER faces the persistent challenge of labeled data scarcity, a major obstacle given the data-intensive requirements of deep learning models. This scarcity often results in small, imbalanced datasets that hinder model generalization. Various strategies, including feature selection, data augmentation, domain adaptation, and fusion techniques, have been employed to mitigate these issues. However, comprehensive reviews that critically analyze these methods remain limited. In this paper, we provide an extensive review of these data scarcity strategies in SER, assessing their merits and limitations in terms of efficiency and robustness. Special attention is given to how these strategies enhance the performance of both acoustic and multimodal SER systems when operating on limited datasets. Additionally, we highlight the potential of fusion strategies combined with attention mechanisms as promising solutions to improve convergence and reduce model complexity.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 110-123"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}