International Journal of Crowd Science最新文献

{"title":"CGLS Method for Efficient Equalization of OFDM Systems Under Doubly Dispersive Fading Channels with an Application Into 6G Communications in Smart Overcrowded","authors":"Issa Haitham M. Ata","doi":"10.26599/IJCS.2023.9100015","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100015","url":null,"abstract":"Because of its superior multipath channel performance and spectrum efficiency, orthogonal frequency-division multiplexing (OFDM) is one of the most suitable candidates for the 6G physical layer in contemporary applications like smart cities and crowded environments in a social Internet of Things (S-IoT) ecosystem. The terahertz (THz) band, 1Tbit/s data rate, low latency, spectrum efficacy, and mobility of 1000 km/h are just a few of the requirements that 6G must meet. Using single-tap equalization, OFDM may reduce the multipath channel impact optimally. However, when the channel has doubly dispersive fading, inter-carrier interference starts to create errors. The worst doubly dispersive fading channel will be produced when THz and high-speed mobility are combined with OFDM as the physical layer for 6G. OFDM requires a complicated equalizer when using channels with doubly dispersive fading. On the basis of band factorization, time domain least squares QR (LSQR) iterative computing, and banded minimum mean squared error (BMMSE), a number of low-complexity equalizers for OFDM have been proposed. Conjugate gradient least squares (CGLS), a revolutionary iterative computation algorithm, is proposed in this study; the proposed equalization technique obtains the trade-off between computations and performance. Simulation results show that the proposed equalizer outperforms the existing BMMSE and LSQR algorithms over doubly dispersive fading channels.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"9 1","pages":"3-12"},"PeriodicalIF":0.0,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10857982","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial of Cyber-Physical Social Systems and Smart Environments","authors":"Mohamadreza Khosravi;Lianyong Qi","doi":"10.26599/IJCS.2024.9100045","DOIUrl":"https://doi.org/10.26599/IJCS.2024.9100045","url":null,"abstract":"Smart environments are now an undeniable part of our life. A day-by-day increase in the use of new technologies based on Artificial Intelligence (AI), Internet of Things (IoT), communication and information systems, human-machine interactions, multimedia sensors, and bio-sensing devices is happening. The good research practice in these areas is absolutely the main factor of advancing our knowledge in this regard. Smart environments contain a variety of applications in different industries including entertainment industry, manufactures, healthcare systems, and Information Technology (IT). From the viewpoint of social systems, the main large-scale applications (not personal) of Cyber-Physical Systems (CPS) to make a smart environment are mainly smart homes and cities, health systems, intelligent transportation systems, green energy systems, and environmental protection and monitoring systems (including remote sensing). The personal use of such technologies is mostly around entertainment including IPTVs, virtual reality, games, other multimedia services, as well as personal healthcare services.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"9 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10858032","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Organizational Performance: Synergy of Cyber-Physical Systems, Cloud Services, and Crowdsensing","authors":"Ahmad Al-Qerem;Ali Mohd Ali;Ahmad Nabot;Issam Jebreen;Mohammad Alauthman;Someah Alangari;Faisal Aburub;Amjad Aldweesh","doi":"10.26599/IJCS.2023.9100033","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100033","url":null,"abstract":"In the contemporary business landscape, software has evolved into a strategic asset crucial for organizations seeking sustainable competitive advantage. The imperative of ensuring software quality becomes evident as low-quality software systems pose formidable challenges to organizational performance. This study delves into the profound impact of three key dimensions of information system quality on organizational performance—information quality (IQ), quality of service (QoS), and software quality (SQ). Anchored in the DeLone and McLean information system (IS) success model, a quantitative questionnaire was administered to 360 industry experts and academics. Rigorous data analysis, employing exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM), revealed significant positive effects of all three quality dimensions on organizational performance. Among these dimensions, software quality emerged as the most influential, showcasing substantial total effects, closely followed by information and service qualities. The study underscores the tangible value derived from strategic investments in enhancing software, information, and service quality. Elevating these facets manifests as a catalyst for improved organizational performance, empowering decision-makers with accurate and timely information while enhancing user satisfaction with the system. This research contributes significantly to the IS success literature by empirically validating the synergistic relationship between information quality, service quality, software quality, and organizational outcomes. The systematic analysis offered in this study goes beyond theoretical validation, providing actionable insights for managers. The findings guide the prioritization of quality initiatives and resource allocation, enabling organizations to maximize competitive advantage. As a future research direction, investigating moderator influences and exploring alternate quality constructs relevant to contemporary technologies, including cyber-physical systems, cloud services, and crowdsensing, holds promise for further enriching our understanding of the evolving digital landscape.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"9 1","pages":"44-55"},"PeriodicalIF":0.0,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10858030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Competition of Real Estate Agents and Housing Prices in Urban China","authors":"Leiju Qiu;Dongmei Guo","doi":"10.26599/IJCS.2024.9100019","DOIUrl":"https://doi.org/10.26599/IJCS.2024.9100019","url":null,"abstract":"Housing market can be viewed as a big intelligent system which gathers various intelligent agents including the demand side, the supply side, as well as the brokerage. Real estate agents are a large group that can lubricate housing transactions, but due to the principal-agent problem, this housing-transaction intelligent system shows low service efficiency. This paper claims that the non-price competition among real estate agents could possibly reconcile the principal-agent problem. With a merged dataset of housing listings and transaction records in Beijing, we find that the competition in the brokerage market raises housing prices significantly. This provides the first empirical evidence that the non-price competition of real estate agents could reconcile the principal-agent problem. Furthermore, we find that exclusive listing and the agent's effort positively relate to higher housing prices. The impact is even stronger in a hotter market. This paper explores the role of competition in the performance of the housing-transaction intelligent system, and therefore has important theoretical and practical significance for the system.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 4","pages":"205-211"},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681265","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Graph Convolutional Neural Network Based Emotion Recognition with Brain Functional Connectivity Network","authors":"Pengzhi Gao;Xiangwei Zheng;Tao Wang;Yuang Zhang","doi":"10.26599/IJCS.2024.9100022","DOIUrl":"https://doi.org/10.26599/IJCS.2024.9100022","url":null,"abstract":"Emotion recognition plays an important role in Human Computer Interaction (HCI) and the evaluation of human behavior based on emotional state is an important research topic. The purpose of emotion recognition is to automatically identify human's emotional states by analyzing physiological or non-physiological signals. The conventional emotion classification methods cannot comprehensively leverage global and local features which are extracted from Electroencephalogram (EEG) signal generated after being stimulated. Therefore, we propose the graph convolutional neural network based emotion recognition with brain functional connectivity network (GERBN). Firstly, raw EEG data of the public DEAP and SEED datasets is preprocessed and adopted in this study. Secondly, emotion-related brain functional connection pattern is constructed using Phase-Locking Value (PLV) adjacency matrix to measure connectivity between the signals of different EEG channels according to phase synchronization. A novel graph structure is constructed where the EEG electrode channels are defined as the vertex, and the edge is strong connection of the binary brain network. Thirdly, the GERBN model that includes six layers is designed to classify and recognize emotional states on the two-dimensional emotional models of valence and arousal. Finally, extensive experiments are conducted on DEAP and SEED datasets. Experimental results demonstrate that the proposed method can improve classification accuracies, in which average accuracies of 80.43% and 88.47% on DEAP are attained on valence and arousal dimensions, respectively. On the SEED dataset, the accuracy reaches 92.37% higher than some of the other methods.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 4","pages":"195-204"},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681263","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Selves Based Intelligent Construction Framework","authors":"Xiaomeng Liu;Hongbo Sun;Jiarui Lin","doi":"10.26599/IJCS.2023.9100036","DOIUrl":"https://doi.org/10.26599/IJCS.2023.9100036","url":null,"abstract":"Construction is the pillar industry of Chinese national economy, but the profit rate has continued to decline in recent years. The conventional job-centric construction information system cannot meet the requirements for safety, quality, and efficiency. In order to solve the above problems, a digital selves based intelligent construction framework has been proposed which is centred on workers, equipment, and sites. It changes the conventional job-centered construction information system and realizes efficient coordination of information among various departments and stages. Applying the digital selves based intelligent construction framework to the case has been proved to be a good solution to the problem of information sharing. Meanwhile, the authenticity and reliability of the information have been ensured. The system has improved management efficiency and information systematization for all participants. It has enabled companies and workers to have a more comprehensive understanding of themselves and to make timely and effective strategies against hazards. In addition, the system has effectively raised the level of digitalization, automation, and intelligence of construction, making governance more accurate and more effective.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 4","pages":"184-194"},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681261","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Total Contents","authors":"","doi":"","DOIUrl":"https://doi.org/","url":null,"abstract":"","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 4","pages":"I-II"},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681239","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of Service Utility in 5G Heterogeneous Networks Using Dynamic Game","authors":"Linhao Zhang;Xudong Lu;Lizhen Cui;Deyu Zhou;Wei Guo","doi":"10.26599/IJCS.2024.9100023","DOIUrl":"https://doi.org/10.26599/IJCS.2024.9100023","url":null,"abstract":"In response to the rapid growth of future business and data traffic, the widespread deployment of small base stations (BSs) in 5G networks has emerged as a promising solution, albeit intensifying the network's energy consumption. Additionally, traditional BSs lack adaptive adjustment of parameter information, posing challenges in delivering satisfactory quality of service (QoS), particularly in the context of highly uneven business distribution. Reducing energy consumption while ensuring that QoS represents a critical challenge. To address this issue, this paper first comprehensively considers the interests of both supply and demand, proposing a service utility measurement method in communication networks to achieve a balance between energy consumption and QoS. Furthermore, this paper integrates cell zooming and sleeping strategies for small BSs, designing a dynamic game algorithm aimed at optimizing service utility in a two-tier heterogeneous network. Through ten distinct scenario simulations, our proposed algorithm demonstrates significant enhancements in service utility while achieving near-optimal optimization results more expeditiously compared to the genetic algorithm (GA).","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 4","pages":"159-167"},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681260","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Index Prediction Model Based on LASSO-PCA and Deep Learning","authors":"Bo Xu;Xinpu Su;Yijun He","doi":"10.26599/IJCS.2024.9100013","DOIUrl":"https://doi.org/10.26599/IJCS.2024.9100013","url":null,"abstract":"Predicting financial market trends poses significant challenges due to the complex, dynamic, and often chaotic nature of the market, especially when dealing with data featuring a multitude of characteristics. In this research, we propose an effective data mining approach that combines Least Absolute Shrinkage and Selection Operator (LASSO) and Principal Component Analysis (PCA) for two-stage feature dimensionality reduction, resulting in a refined dataset. To enhance the model's capacity to capture medium- and long-term index trends, we implement a sliding time window approach, utilizing data from the preceding 60 trading days. Long-Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) models are employed to predict the return rate of Securities Bank of China (399986) over a 30-day trading period. We conducted a comprehensive comparative analysis involving our proposed model and established methods, namely, LASSO, PCA, and Hybrid Recurrent Neural Networks (RNN). Our empirical findings unequivocally demonstrate the superior performance of our model in terms of both prediction accuracy and stability. Specifically, our model exhibits significantly higher predictive accuracy when forecasting the return rate of Securities Bank of China (399986) over a 30-day trading period, all while maintaining enhanced stability. These results underscore the exceptional efficacy of our approach within the realm of financial market time series forecasting, thus providing robust support for further research and practical applications within this domain.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 4","pages":"176-183"},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681264","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Service Efficacy in 5G HetNets: An Adaptive Acceleration PSO Approach","authors":"Guowen Li;Wenbo Hu;Yang Zhao;Xudong Lu","doi":"10.26599/IJCS.2024.9100024","DOIUrl":"https://doi.org/10.26599/IJCS.2024.9100024","url":null,"abstract":"The dense deployment of Femto Base Stations (FBS) assisting Macro Base Stations (MBS) in a Heterogeneous Network (HetNet) resolves the coverage issue of 5G signal transmission. However, the imprudent layout of FBSs results in extensive energy consumption and increased signal interference among base stations. Regulating the transmission power of each base station in the HetNets through the main controller or MBS is essential to maximize the power efficiency of the entire HetNets while adhering to the constraints of basic signal throughput and fairness. To address this challenge, this paper proposes an Adaptive Acceleration Particle Swarm Optimization (AA-PSO) algorithm. This algorithm dynamically determines the inertia weight based on each particle's optimal position and the global optimal position, and introduces the concept of time-varying parameters to control the learning rate, thus managing the search range and convergence speed of the particle swarm. The results demonstrate that the AA-PSO algorithm can efficiently determine the optimal transmission power of each base station in the HetNets, reduce interference between MBS and FBSs, as well as among FBSs, and ultimately improve the service efficacy of the entire network.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 4","pages":"168-175"},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681262","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}