Hasil untuk "Transportation and communication"

Akanksha Sneh, Aakanksha Tewari, Shobha Sundar Ram et al.

Next-generation intelligent transportation systems require both sensing and communication between road users. However, deploying separate radars and communication devices involves the allocation of individual frequency bands and hardware platforms. Integrated sensing and communication (ISAC) offers a robust solution to the challenges of spectral congestion by utilizing a shared waveform, hardware, and spectrum for both localization of mobile users and communication. Various waveforms, including phase-modulated continuous waves (PMCW) and frequency-modulated continuous waves (FMCW), have been explored for target localization using traditional radar. On the other hand, new protocols such as the IEEE 802.11ad have been proposed to support wideband communication between vehicles. This paper compares both traditional radar and communication candidate waveforms for ISAC to detect single-point and extended targets. We show that the response of FMCW to mobile targets is poorer than that of PMCW. However, the IEEE 802.11ad radar outperforms PMCW radar and FMCW radar. Additionally, the radar signal processing algorithms are implemented on Zynq system-on-chip through hardware-software co-design and fixed-point analysis to evaluate their computational complexity in real-world implementations.

Christian Deppe, Eduard Jorswieck, Pin-Hsun Lin et al.

The Foundations of Future Communication Systems (FFCS) conference brought together leading researchers from information theory, quantum communication, molecular communication, semantic communication, and secure network design to explore the fundamental principles shaping next-generation communication systems. The event serves as a platform for interdisciplinary exchange, bridging classical Shannon theory, post-Shannon paradigms, quantum information science, and emerging physically grounded communication models. This report compiles the abstracts of all invited talks, contributed presentations, and poster contributions presented at FFCS. The collected works reflect the breadth of contemporary research directions, including identification-based communication, entanglement-assisted networks, semantic and goal-oriented communication, coding for molecular and nanoscale systems, secure authentication mechanisms, and information-theoretic limits of novel physical-layer architectures. A central theme of the conference was the re-examination of foundational limits under realistic physical, architectural, and security constraints. Many contributions move beyond traditional rate-centric perspectives and instead investigate reliability, identification, semantics, resource efficiency, and trust in complex and heterogeneous networks. The inclusion of poster abstracts further highlights emerging ideas, early-stage research results, and innovative cross-disciplinary approaches that contribute to shaping future communication paradigms. By documenting the intellectual landscape presented at FFCS, this report aims to provide a structured overview of current research frontiers and to stimulate continued collaboration across theoretical and experimental domains.

Wei Wang, Anqi Liu, Xiaoxiao Xu

Traditional villages are crucial for the sustainable development of both urban and rural areas, and identifying their spatial patterns is key to guiding village construction and promoting urban–rural integration. This research selected 274 traditional Huizhou villages located in the upper basin of the Xin’an River. It examined how the four main factors—construction period, geography, ecology, and social and economic development—shape and influence each other. By incorporating an optimal parameters-based geographical detector model, this study further explored the driving mechanisms behind spatial differentiation. The villages exhibit a “one belt, two cores, and multiple dispersion” pattern, with Shexian and Yixian counties as hot gathering areas of traditional villages. Population migration, internal growth, and external cultural and commercial exchanges drove village formation in three stages. Spatial distribution favors locations with gentle slopes, sunny aspects, proximity to water, suitable climates, convenient transportation, and distance from crowded areas. Topography, water systems, and external communication are key drivers, while the synergy between water systems and transportation is particularly significant. This study concludes that water systems have the greatest influence on village spatial patterns, recommending watersheds as regional boundaries and advocating a clustering development model for planning and protection efforts.

Toqa Amoush, Luay Jum’a

<i>Background</i>: The retail sector in Jordan is adopting Industry 4.0 (I4.0) technologies to enhance efficiency and sustainability. Nevertheless, there is a lack of empirical evidence to inform retail managers regarding the impact of I4.0 adoption on environmental, economic, and social sustainability, particularly in dynamic contexts. Therefore, this study aims to investigate the impact of Industry 4.0 on the three types of sustainable performance, with the moderating effect of environmental dynamism. <i>Methods</i>: This quantitative study collected data using a cross-sectional survey of 100 retail professionals from large companies that was analyzed using structural equation modeling (SEM) to test the hypotheses. <i>Results</i>: I4.0 practices improved retail environmental, economic, and social sustainability. Additionally, environmental dynamism moderated the relationship between I4.0 and environmental sustainability, suggesting that dynamic environments may reduce the effectiveness of I4.0 technologies in driving environmental performance. Economic and social sustainability had no significant moderating effects. <i>Conclusions</i>: This study examines the sustainability benefits of I4.0 adoption in an unexplored developing economy. It emphasizes the strategic importance of digital transformation for retail sustainability and provides practical recommendations for dynamic markets. The findings support I4.0 technologies role in sustainable growth and lay the groundwork for digital transformation research in emerging markets.

Osayuwamen Omoruyi, Albert Antwi, Alfred Mwanza et al.

<i>Introduction</i>: This study explores the impact of logistics information technology (LIT) on supply chain relationships and distribution performance in small and medium-sized enterprises (SMEs) using South Africa as a case study. Although digital supply chain solutions are increasingly important, there is limited evidence of SME efficiency in emerging markets using LIT. <i>Methods</i>: This study utilises a survey of 313 SMEs from four South African provinces. Bayesian structural equation modelling (Bayesian SEM) was then used to examine LIT’s effects on distribution performances in terms of timeliness, product availability, and condition. <i>Results</i>: The results show that the adoption of LIT strengthens buyer–seller networks (β = 0.524, CI = [0.434, 0.613]) and improves distribution by enhancing both timeliness performance (β = 0.237, CI = [0.098, 0.372]) and product condition performance (β = 0.175, CI = [0.042, 0.259], β = 0.222, <i>p</i> < 0.001). However, it does not directly enhance product availability performance (β = 0.085, CI = [−0.030, 0.199]), signifying that LIT adoption by itself fails to improve product availability. The results also demonstrate that SME network relationships mediate the connection between LIT adoption and distribution performance metrics. <i>Discussion</i>: This study’s findings contribute to the literature and offer valuable information and guidance to policymakers as they underscore the importance for SMEs to invest in LIT integration and compatibility, as well as inventory optimisation and improved supplier communication to minimise transit time variation. Policymakers should support SMEs’ digital transformation through interventions including funding and training for LIT adoption. This study confirms the essential role of LIT in SME supply chains and illustrates that technology-facilitated relationships enhance distribution performance, which enhances SME competitiveness.

Salah eddine Boukredine, Elhadi Mehallel, Ahcene Boualleg et al.

This paper presents the design and analysis of a high-performance 4×1 linear microstrip-fed antenna array optimized for wireless communication systems operating at 2.45 GHz. A novel concave-shaped modification is introduced on both the horizontal and vertical edges of the rectangular patch elements, significantly enhancing key performance metrics such as gain, impedance matching, and radiation efficiency. In addition, cut-corner techniques are applied to each patch element to minimize return loss and improve bandwidth, effectively addressing common limitations of traditional rectangular patch antennas, such as low gain and narrow bandwidth. Through rigorous simulations and physical prototyping, the proposed antenna array demonstrates a peak gain of 18 dB and a return loss of -33.82 dB at the target frequency. This makes it highly suitable for high-performance wireless applications, including WLAN, mobile communications, and smart transportation systems. The design not only improves antenna efficiency but is also cost-effective and simple to fabricate, making it ideal for mass production in modern communication systems.

Okafor UB, Obasanjo I, Goon DT

Uchenna Benedine Okafor,1 Iyabo Obasanjo,2 Daniel Ter Goon3 1Department of Nursing Science, Faculty of Medicine and Health Sciences, Walter Sisulu University, Mthatha, 5117, South Africa; 2Faculty of Health Sciences, University of Maryland, Baltimore, MD, USA; 3Faculty of Health Sciences, University of Limpopo, Polokwane, 0727, South AfricaCorrespondence: Uchenna Benedine Okafor, Department of Nursing Science, Faculty of Medicine and Health Sciences, Walter Sisulu University, Nelson Mandela Drive Campus, Mthatha, 5117, South Africa, Email ucheysonic@gmail.comIntroduction: One of the challenges CHWs face in their profession is their underrepresentation in program advancement. Despite the importance of community health workers as an adjunct health workforce providing crucial healthcare services to the rural, marginalized, and underserved populations, their opinions on strengthening the CHW program remain understudied in certain geographical contexts. Consequently, this study explores the opinions of community health workers regarding the support systems desirable for their effective delivery of healthcare support services in the Buffalo Municipality City, Eastern Cape Province of South Africa.Methods: In-depth individual, semi-structured interviews (n=10) as well as focus groups interviews (n=13) were conducted with 23 community health workers, using an audio recorder with their permission to record the interviews. Content and thematic data analysis was applied.Results: The CHWs made several suggestions to assist them serve the community better and improve the community health program. These include provision of transportation, constant training workshops to enhance and maintain their skills and knowledge, support to improve communication with clients, provision of work identifiers to earn community’s recognition, respect, and trust, and improvement in human and material resources to mitigate the overwhelming workload. In addition, they emphasised the need to address job insecurity by offering them with permanent, salaried positions, as well as the safety concerns posed by violent crimes in the communities they served.Conclusion: The findings of this study have implications for improving the practise of CHW programs, policies, and future research recommendations, emphasising the need to take into considerations, the suggestions of the CHWs in improving the CHW program to enable them to provide effective and optimal healthcare support services to clients and the community. We advocated for the integration of community health workers into the larger healthcare system.Keywords: community health workers, challenges, strategies, strengthening, South Africa

Hassam Ahmed Tahir, Walaa Alayed, Waqar Ul Hassan

Intelligent Transportation Systems (ITS) demand robust privacy-preserving frameworks that maintain efficiency and adaptability in dynamic Vehicle-to-Vehicle (V2V) networks. Conventional federated learning (FL) approaches falter under non-IID data distributions, adversarial threats, and rapidly changing traffic conditions. This paper introduces FLAA-V2V, a novel FL framework that addresses these challenges through three key innovations: (1) A reinforcement learning-based adaptive aggregation engine dynamically weights vehicle contributions using context-aware metrics (data quality, network stability), reducing communication overhead by 23% versus FedAvg; (2) A hierarchical privacy mechanism combining Local Differential Privacy (LDP) and Lightweight Homomorphic Encryption (LHE) secures V2V exchanges while achieving 92.3% collision-avoidance F1-score under attacks; and (3) A meta-learning drift detector with Kolmogorov-Smirnov validation and gradient compensation reduces accuracy degradation by 18.7% in non-stationary environments. Evaluated on 200+ autonomous vehicles, FLAA-V2V sustains sub-300ms latency at 95% density and demonstrates 16.1% higher adversarial resilience than state-of-the-art FL baselines. This framework establishes a new paradigm for secure, adaptive federated learning in mission-critical ITS applications.

Abdullah Alsaleh

The rapid advancement of automotive technologies has spurred the development of innovative applications within intelligent transportation systems (ITS), aimed at enhancing safety, efficiency and sustainability. These applications, such as advanced driver assistance systems (ADAS), vehicle-to-everything (V2X) communication and autonomous driving, are transforming transportation by enabling adaptive cruise control, lane-keeping assistance, real-time traffic management and predictive maintenance. By leveraging cloud computing and vehicular networks, intelligent transportation solutions optimize traffic flow, improve emergency response systems, and forecast potential collisions, contributing to safer and more efficient roads. This study proposes a Vehicular Cloud-based Intelligent Transportation System (VCITS) model, integrating vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication through roadside units (RSUs) and cloudlets to provide real-time access to cloud resources. A novel search and management protocol, supported by a tailored algorithm, was developed to enhance resource allocation success rates for vehicles within a defined area of interest. The study also identifies critical security vulnerabilities in smart vehicle networks, emphasizing the need for robust solutions to protect data integrity and privacy. The simulation experiments evaluated the VCITS model under various traffic densities and resource request scenarios. Results demonstrated that the proposed model effectively maintained service availability rates exceeding 85 % even under high demand. Furthermore, the system exhibited scalability and stability, with minimal service loss and efficient handling of control messages. These findings highlight the potential of the VCITS model to advance smart traffic management while addressing computational efficiency and security challenges. Future research directions include integrating cybersecurity measures and leveraging emerging technologies like 5G and 6G to further enhance system performance and safety.

Yiwei Liao, Shurui Tu, Yujie Zhou et al.

Semantic communication is a novel communication paradigm that focuses on the transportation and delivery of the \emph{meaning} of messages. Recent results have verified that a graphical structure provides the most expressive and structurally faithful formalism for representing the relational semantics in most information sources. However, most existing works represent the semantics based on pairwise relation-based graphs, which cannot capture the higher-order interactions that are essential for some semantic sources. This paper proposes a novel Bayesian hypergraph inference-based semantic communication framework that can directly recover implicit semantic information involving high-order hyperedges at the receiver based on the pairwise relation-based explicit semantics sent by the transmitter. Experimental results based on real-world datasets demonstrated that the proposed SBRF achieves up to 90\% recovery accuracy of the high-order hyperedges based on the pairwise relation-based explicit semantics.

Xuyang Chen, Chong Huang, Gaojie Chen et al.

Semantic communications have emerged as a crucial research direction for future wireless communication networks. However, as wireless systems become increasingly complex, the demands for computation and communication resources in semantic communications continue to grow rapidly. This paper investigates the trade-off between computation and communication in wireless semantic communications, taking into consideration transmission task delay and performance constraints within the semantic communication framework. We propose a novel tradeoff metric to analyze the balance between computation and communication in semantic transmissions and employ the deep reinforcement learning (DRL) algorithm to minimize this metric, thereby reducing the cost associated with balancing computation and communication. Through simulations, we analyze the tradeoff between computation and communication and demonstrate the effectiveness of optimizing this trade-off metric.

Thomas K. Dasaklis, Evangelia Kopanaki, Panos T. Chountalas et al.

<i>Background</i>: The electronic Freight Transport Information (eFTI) regulation is critical in modernizing freight transport (FT) within the European Union by establishing a framework for the electronic exchange of information. Despite its importance, there is a notable gap in the literature regarding the practical implementation challenges, especially from an empirical perspective. <i>Methods</i>: To address this gap, our study utilized a grounded theory approach, conducting interviews with a diverse group of logistics experts from Greece. The selection of experts was strategic to ensure a comprehensive range of knowledge and expertise, including insights at the policy level as well as practical experiences. <i>Results</i>: Our findings highlight several significant challenges in the implementation of eFTI, including the digital skill gap among the workforce, issues with system interoperability, and diverse capacities and resources of companies of different sizes. Economic factors, regulatory frameworks and the necessity for targeted training and leadership support were also identified as crucial for the digital transition. <i>Conclusions</i>: The study shows that uniform eFTI implementation may not work for all organizations, highlighting the necessity for customized strategies that address specific challenges in the FT chain. Our research deepens the understanding of these issues, providing actionable insights for successful eFTI adoption.

Falk Dettinger, Matthias Weiß, Daniel Dittler et al.

Wireless communication between road users is essential for environmental perception, reasoning, and mission planning to enable fully autonomous vehicles, and thus improve road safety and transport efficiency. To enable collaborative driving, the concept of vehicle-to-Everything (V2X) has long been introduced to the industry. Within the last two decades, several communication standards have been developed based on IEEE 802.11p and cellular standards, namely Dedicated Short-Range Communication (DSRC), Intelligent Transportation System G5 (ITS-G5), and Cellular- and New Radio- Vehicle-to-Everything (C-V2X and NR-V2X). However, while there exists a high quantity of available publications concerning V2X and the analysis of the different standards, only few surveys exist that summarize these results. Furthermore, to our knowledge, no survey that provides an analysis about possible future trends and challenges for the global implementation of V2Xexists. Thus, this contribution provides a detailed survey on Vehicle-to-Everything communication standards, their performance, current and future applications, and associated challenges. Based on our research, we have identified several research gaps and provide a picture about the possible future of the Vehicle-to-Everything communication domain.

S. Danish, Kaiwen Zhang, H. Jacobsen et al.

The Intelligent Transportation System (ITS) has become essential for the economical and technological development of a country. The maturity of communication technologies (Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V)) and the amalgamation of smart grids, electric vehicles (EVs) and energy trading resulted in a storm of research opportunities for green ITS. In addition, the combination of vehicular communication technologies and ITS enable efficient selection of EV charging stations (CS) and scheduling EVs charging requirements in real-time. However, the untrusted centralized nature of energy markets and EV charging infrastructures result in several privacy and security threats to EV user’s private information. These security and privacy threats include targeted advertisements, privacy leakage, selling data to third party, etc. In this work, we propose BlockEV, a blockchain-based efficient CS selection protocol for EVs to ensure the security and privacy of the EV users, availability of the reserved time slots at CSs, high Quality of Service (QoS) and enhanced EV user comfort. First, a blockchain-based framework is introduced to implement secure charging services and trusted reservation for EVs with the execution of smart contract. Second, we focus on the efficient CS selection and propose a mechanism for EVs to select the CS locally without sharing private information to CS, while fulfilling their service requirements. Evaluations show that the proposed BlockEV is scalable with significantly low blockchain transaction and storage overhead.

Manoj Sindhwani, Shippu Sachdeva, Akhil Gupta et al.

The Vehicular Ad-hoc Network (VANET) is an innovative technology that allows vehicles to connect with neighboring roadside structures to deliver intelligent transportation applications. To deliver safe communication among vehicles, a reliable routing approach is required. Due to the excessive mobility and frequent variation in network topology, establishing a reliable routing for VANETs takes a lot of work. In VANETs, transmission links are extremely susceptible to interruption; as a result, the routing efficiency of these constantly evolving networks requires special attention. To promote reliable routing in VANETs, we propose a novel context-aware reliable routing protocol that integrates k-means clustering and support vector machine (SVM) in this paper. The k-means clustering divides the routes into two clusters named GOOD and BAD. The cluster with high mean square error (MSE) is labelled as BAD, and the cluster with low MSE is labelled as GOOD. After training the routing data with SVM, the performance of each route from source to target is improved in terms of Packet Delivery Ratio (PDR), throughput, and End to End Delay (E2E). The proposed protocol will achieve improved routing efficiency with these changes.

Anil Sigdel, Anu Bista, Hardik Sapkota et al.

<h4>Background</h4>The COVID-19 virus is still with us, and in resource-limited countries, like Nepal, resurgence of a new variant is still a threat. In this pandemic, low-income countries struggle to provide essential public health services, including family planning. This study was conducted to explore what sorts of barriers are faced by women needing family planning services in Nepal during the pandemic.<h4>Methods</h4>This qualitative study was conducted in five districts of Nepal. Telephonic in-depth interviews were conducted with 18 women of reproductive age (18-49 years) who were the regular clients of family planning services. Data were coded deductively using the preexisting themes based on a socio-ecological model (e.g., individual, family, community, and health-facility levels).<h4>Results</h4>Individual level barriers included low self-confidence, inadequate knowledge on COVID-19, myths and misconception related to COVID-19, limited access to FP services low priority to SRH services, low autonomy in family and limited financial ability. Family level barriers comprised of partner's support, social stigma, increased time at home with husbands or parents, un-acceptance of family planning services as essential health services, financial hardship due to loss of jobs, and communication with in-laws. Movement restrictions and transportation hindering access, unsecured feeling, violation of privacy, and obstacles from security personnel were the community level barriers and unavailability of preferred choice of contraception, increased waiting time, limited outreach services by community health workers, limited physical infrastructures, the behavior of health workers, stock out of commodities, and absence of health workers were health facility level barriers.<h4>Conclusion</h4>This study highlighted key barriers faced by women in seeking family planning services during the COVID-19 lockdown in Nepal. Policymakers and program managers should consider strategies to ensure continued availability of the full method mix during emergency, particularly since disruptions may go unnoticed and strengthen the provision of services through alternative service delivery channels to ensure sustained uptake of such services in this sort of pandemic.

Salma El Bourkadi

This article focuses on the role that algorithms play as a communicative infrastructure that contributes to poorer occupational health in the gig economy by interviewing 50 Uber drivers based on the life-story methodological approach. Specifically, the paper draws attention to Uber structure's managerial algorithmic communication and its effects on drivers' occupational health by engaging with Giddens's theoretical framework of structure-agency and Weick's theory of sensemaking. Furthermore, the study also explores the different factors contributing to the construction of individual and collective resistance of drivers to Uber's monopoly. The findings reveal that Uber's structure imprisons the users' freedom of negotiation and action, which creates a stressful work environment as managerial algorithmic communication only functions effectively in ideal working conditions, while abnormality is very frequent in a profession like transportation. Driver agency consists of organizing individual and collective resistance to change Uber's work decisions and weaken them. On an outside platform, resistance strategies are deployed by drivers to pressure Uber, with the goal of protecting their occupational health.

Xiaoyuan Zhang, Yunfei Ma, Zongkai Zhu et al.

At present, tuff aggregates as asphalt pavement mixtures have insufficient water damage resistance; hence, modifying and evaluating the related properties of tuff asphalt mixtures are necessary. In this study, cement and a liquid antistripping agent were selected as admixtures, and tuff and limestone mixtures without admixtures were selected as control. The surface energy for the SBS-modified asphalt polymers and aggregates in the mixtures was evaluated by using surface energy theory. The adhesion work and the spalling work of the polymer–aggregate interface was calculated, and a factor <i>k</i> was proposed to predict the water damage resistance of the tuff mixture with admixtures. The prediction values were compared with those of the macroscopic water stability test for the mixture. The results of this research showed that the factor <i>k</i> after adding admixtures was improved, and the increase range was from 7.14% to 47.62%. The admixture scheme with the best improvement was that with 2% cement content, in which the <i>k</i> value increased by 21.57% and 47.62% compared with that of the limestone and tuff mixtures without admixtures, respectively. The tested water stability indexes and the predicted factor <i>k</i> under different admixture schemes exhibited a good positive correlation, and the correlation equations were obtained by linear fitting. Thus, it was feasible to use the factor <i>k</i> characterizing the water damage resistance of tuff mixtures using surface energy theory.

Ricardo Muñoz-Cancino, Sebastián A. Ríos, Manuel Graña

The impact of micro-level people’s activities on urban macro-level indicators is a complex question that has been the subject of much interest among researchers and policymakers. Transportation preferences, consumption habits, communication patterns and other individual-level activities can significantly impact large-scale urban characteristics, such as the potential for innovation generation of the city. Conversely, large-scale urban characteristics can also constrain and determine the activities of their inhabitants. Therefore, understanding the interdependence and mutual reinforcement between micro- and macro-level factors is critical to defining effective public policies. The increasing availability of digital data sources, such as social media and mobile phones, has opened up new opportunities for the quantitative study of this interdependency. This paper aims to detect meaningful city clusters on the basis of a detailed analysis of the spatiotemporal activity patterns for each city. The study is carried out on a worldwide city dataset of spatiotemporal activity patterns obtained from geotagged social media data. Clustering features are obtained from unsupervised topic analyses of activity patterns. Our study compares state-of-the-art clustering models, selecting the model achieving a 2.7% greater Silhouette Score than the next-best model. Three well-separated city clusters are identified. Additionally, the study of the distribution of the City Innovation Index over these three city clusters shows discrimination of low performing from high performing cities relative to innovation. Low performing cities are identified in one well-separated cluster. Therefore, it is possible to correlate micro-scale individual-level activities to large-scale urban characteristics.

Mohd Hamza Naim Shaikh, Khaled Rabie, Xingwang Li et al.

Vehicle-to-everything (V2X) connectivity in 5G-and-beyond communication networks supports the futuristic intelligent transportation system (ITS) by allowing vehicles to intelligently connect with everything. The advent of reconfigurable intelligent surfaces (RISs) has led to realizing the true potential of V2X communication. In this work, we propose a dual RIS-based vehicle-to-infrastructure (V2I) communication scheme. Following that, the performance of the proposed communication scheme is evaluated in terms of deriving the closed-form expressions for outage probability, spectral efficiency and energy efficiency. Finally, the analytical findings are corroborated with simulations which illustrate the superiority of the RIS-assisted vehicular networks.