Hasil untuk "Transportation and communication"

T. Laer, K. Ruyter, L. M. Visconti et al.

Emily Johnson, Sarah Tucker Marrison, Mattie Banks et al.

Unhoused individuals experience numerous barriers to healthcare access and higher morbidity and mortality rates than housed individuals. In collaboration with community-based organizations (CBOs) and healthcare profession learners we developed a program involving in-person and telehealth visits at a CBO clinic and via street medicine outreach to address healthcare needs of the unhoused in a small Southeastern city. In its fifth year of operation, from January through April 2024, we evaluated the program using key stakeholder interviews (patients, CBO staff learners) guided by the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework. A template analysis approach was utilized to evaluate barriers and facilitators to implementation outcomes. Results demonstrated consistent themes across stakeholders. Factors central to reach included advertisement by word-of-mouth, location convenience, and perceived service benefits. For learners, barriers to reach included clinic hours conflicting with academic schedules and apprehension of providing medical care in this setting. Regarding effectiveness, facilitating themes included opportunities for autonomy and enhanced understanding of treatment of underserved populations (learners) and improvement in health (patients, CBO staff). There were no consistently identified unintended negative consequences of the program. For adoption, all stakeholders described strong perceptions of trust in providers and the importance of team communication and coordination of care, in addition to the need to add disciplines included in the multidisciplinary care team. Facilitating implementation themes included comprehensive access for existing patients, while barriers identified were adequacy of access to social resources (housing, food, transportation) and continued increase in numbers of unhoused individuals outpacing available services. Themes facilitating maintenance included continued outreach efforts and integration into existing healthcare and community-based systems. The addition of additional services and specialties was consistently identified as essential to health status of the patients and an opportunity for growth of the program. This implementation evaluation involving key stakeholders of a community engaged telehealth-based intervention for the unhoused provides thematic considerations to guide program implementation and sustainability to improve health equity for vulnerable populations.

Emmanuel Ahatsi, Oludolapo Akanni Olanrewaju

<i>Background:</i> This study examines the application of Artificial Intelligence (AI) and Big Data Analytics (BDA) in enhancing humanitarian supply chain resilience, focusing on Ghana and South Africa. Despite their potential, AI-BDA applications are underexplored in disaster response, particularly in developing economies. <i>Methods:</i> An explanatory research design using a quantitative approach was employed, analyzing data from 200 supply chain professionals in both nations. Structured questionnaires assessed the implementation of four key AI-BDA techniques: Time-Series Forecasting (TSF), Early Warning Systems (EWS), Logistics Optimization (LO), and Real-time Monitoring (RTM). Exploratory factor analysis and regression analysis were conducted to evaluate the relationship between these techniques and supply chain resilience, controlling for organizational size and technological readiness. <i>Results:</i> The findings indicate that AI-BDA techniques significantly improve humanitarian supply chain resilience, with TSF and LO demonstrating the highest predictive power. Additionally, technological readiness facilitates the adoption of these techniques. <i>Conclusions:</i> While AI-BDA offers substantial benefits, opportunities for greater adoption remain, particularly in real-time monitoring and predictive analytics. Humanitarian organizations should invest in capacity-building initiatives, enhance data quality, and foster multi-stakeholder partnerships to maximize the impact of AI-BDA.

Md Bokhtiar Al Zami, Shaba Shaon, Vu Khanh Quy et al.

Industrial networks are undergoing rapid transformation driven by the convergence of emerging technologies that are revolutionizing conventional workflows, enhancing operational efficiency, and fundamentally redefining the industrial landscape across diverse sectors. Amidst this revolution, Digital Twin (DT) emerges as a transformative innovation that seamlessly integrates real-world systems with their virtual counterparts, bridging the physical and digital realms. In this article, we present a comprehensive survey of the emerging DT-enabled services and applications across industries, beginning with an overview of DT fundamentals and its components to a discussion of key enabling technologies for DT. Different from literature works, we investigate and analyze the capabilities of DT across a wide range of industrial services, including data sharing, data offloading, integrated sensing and communication, content caching, resource allocation, wireless networking, and metaverse. In particular, we present an in-depth technical discussion of the roles of DT in industrial applications across various domains, including manufacturing, healthcare, transportation, energy, agriculture, space, oil and gas, as well as robotics. Throughout the technical analysis, we delve into real-time data communications between physical and virtual platforms to enable industrial DT networking. Subsequently, we extensively explore and analyze a wide range of major privacy and security issues in DT-based industry. Taxonomy tables and the key research findings from the survey are also given, emphasizing important insights into the significance of DT in industries. Finally, we point out future research directions to spur further research in this promising area.

Zhenkun Liu, Yun Ou, Zhuo Yang et al.

Wireless sensor networks (WSNs) are fundamental to applications in the Internet of Things, smart cities, and environmental monitoring, where coverage optimization is critical for maximizing monitoring efficacy under constrained resources. Conventional approaches often suffer from low global coverage efficiency, high computational overhead, and a tendency to converge to local optima. To address these challenges, this study proposes the fusion multi-strategy gray wolf optimizer (FMGWO), an advanced variant of the Gray Wolf Optimizer (GWO). FMGWO integrates various strategies: electrostatic field initialization for uniform population distribution, dynamic parameter adjustment with nonlinear convergence and differential evolution scaling, an elder council mechanism to preserve historical elite solutions, alpha wolf tenure inspection and rotation to maintain population vitality, and a hybrid mutation strategy combining differential evolution and Cauchy perturbations to enhance diversity and global search capability. Ablation studies validate the efficacy of each strategy, while simulation experiments demonstrate FMGWO’s superior performance in WSN coverage optimization. Compared to established algorithms such as PSO, GWO, CSA, DE, GA, FA, OGWO, DGWO1, and DGWO2, FMGWO achieves higher coverage rates with fewer nodes—up to 98.63% with 30 nodes—alongside improved convergence speed and stability. These results underscore FMGWO’s potential as an effective solution for efficient WSN deployment, offering significant implications for resource-constrained optimization in IoT and edge computing systems.

Ilias Alexandros Parmaksizoglou, Alessandro Bombelli, Alexei Sharpanskykh

<i>Background:</i> The rapid growth of international maritime trade has intensified operational challenges at marine terminals due to increased interaction between vessels, trucks, and trains. Key issues include berth congestion, inefficient truck arrivals, and underutilization of terminal resources. Ensuring coordinated planning among transport modes and fostering collaboration between stakeholders such as vessel operators, logistics providers, and terminal managers is critical to mitigating these inefficiencies. <i>Methods:</i> This study proposes a multi-agent, multi-objective coordination model that synchronizes vessel berth allocation with truck appointment scheduling. A solution method combining prioritized planning with a neighborhood search heuristic is introduced to explore Pareto-optimal trade-offs. The performance of this approach is benchmarked against well-established multi-objective evolutionary algorithms (MOEAs), including NSGA-II and SPEA2. <i>Results:</i> Numerical experiments demonstrate that the proposed method generates a greater number of Pareto-optimal solutions and achieves higher hypervolume indicators compared to MOEAs. These results show improved balance among objectives such as minimizing vessel waiting times, reducing truck congestion, and optimizing terminal resource usage. <i>Conclusions:</i> By integrating berth allocation and truck scheduling through a transparent, multi-agent approach, this work provides decision-makers with better tools to evaluate trade-offs in port terminal operations. The proposed strategy supports more efficient, fair, and informed coordination in complex multimodal environments.

Muhammad Ali Jamshed, Muhammad Ahmed Mohsin, Hongliang Zhang et al.

To overcome the challenges of ultra-low latency, ubiquitous coverage, and soaring data rates, this article presents a combined use of Near Field Communication (NFC) and Reconfigurable Holographic Surfaces (RHS) for Non-Terrestrial Networks (NTN). A system architecture has been presented, which shows that the integration of RHS with NTN platforms such as satellites, High Altitute Platform Stations (HAPS), and Uncrewed Aerial Vehicles (UAV) can achieve precise beamforming and intelligent wavefront control in near-field regions, enhancing Energy Efficiency (EE), spectral utilization, and spatial resolution. Moreover, key applications, challenges, and future directions have been identified to fully adopt this integration. In addition, a use case analysis has been presented to improve the EE of the system in a public safety use case scenario, further strengthening the UAV-RHS fusion.

Mitra Rezaei, Michael Chappell, Adam Noel

Spherical multi-layered structures are prevalent in numerous biological systems and engineered applications, including tumor spheroids, layered tissues, and multi-shell nanoparticles for targeted drug delivery. Despite their widespread occurrence, there remains a gap in modeling particle propagation through these complex structures from a molecular communication (MC) perspective. This paper introduces a generalized analytical framework for modeling diffusion-based molecular communication in multi-layered spherical environments. The framework is capable of supporting an arbitrary number of layers and flexible transmitter-receiver positioning. As an example, the detailed formulation is presented for the three-layer sphere, which is particularly relevant for different biological models such as tumor spheroids. The analytical results are validated using particle-based simulation (PBS) in scenarios that have short inter-layer distances. The findings reveal that the characteristics of each layer significantly impact molecule propagation throughout the entire structure, making their consideration crucial for designing targeted therapies and optimizing drug delivery systems.

YU Kan, LI Dong, ZHANG Qixun et al.

Communication and sensing in the millimeter-wave (mmWave) frequency band face two major challenges. Interference between sensing and communication limits their respective performances, and the coupling mechanisms and decoupling methods are still underdeveloped. The strong directionality of mmWave leads to potential security risks in information transmission. To address the physical layer security in the ISAC network of intelligent transportation systems, the concepts of ubiquitous sensing, potential communication, integrated computing, and inherent security, and characterizes the coupling relationships among them were defined. The current research and limitations of sensing, communication, computation, and security were reviewed, and feasible approaches for resource optimization, cognitive modeling of sensing-communication coupling interference, and the mechanisms constraining the performance of sensing-communication enabled security were presented.

Ana Isabel Bento, Carla Cruz, Gabriela Fernandes et al.

<i>Background</i>: Supply chains, characterized by complexity and sensitivity, require continuous mapping to address challenges, particularly disruptions like the COVID-19 pandemic. In this context, Social Network Analysis (SNA) has proven valuable in analyzing how actors in a network connect and create interdependencies. However, some studies suggest that the SNA literature needs to embrace new fields of application and develop innovative metrics. <i>Methods</i>: The aim of this study is to clarify the role and contribution of SNA when characterizing and understanding the challenges of contemporary supply chains. A literature review was conducted to achieve this. <i>Results</i>: The results reveal that SNA has been applied in a wide variety of areas (e.g., manufacturing and construction sectors), with an emerging application in the tertiary sector. Furthermore, the findings demonstrate that metrics related to the network and to nodes have been used repeatedly, highlighting the need for new supply-chain-related metrics, such as the novel concept of semi-directedness. <i>Conclusions</i>: Despite the versatility of SNA, some aspects may limit its application to supply chain management, including shortcomings in data acquisition and the fact that SNA only allows for the visualization of network configurations, thus preventing the capture of nuances that characterize the relationships between the actors involved.

Shuaifeng Jiang, Ahmed Alkhateeb

This paper explores a novel research direction where a digital twin is leveraged to assist the beamforming design for an integrated sensing and communication (ISAC) system. In this setup, a base station designs joint communication and sensing beamforming to serve the communication user and detect the sensing target concurrently. Utilizing the electromagnetic (EM) 3D model of the environment and ray tracing, the digital twin can provide various information, e.g., propagation path parameters and wireless channels, to aid communication and sensing systems. More specifically, our digital twin-based beamforming design first leverages the environment EM 3D model and ray tracing to (i) predict the directions of the line-of-sight (LoS) and non-line-of-sight (NLoS) sensing channel paths and (ii) identify the dominant one among these sensing channel paths. Then, to optimize the joint sensing and communication beam, we maximize the sensing signal-to-noise ratio (SNR) on the dominant sensing channel component while satisfying a minimum communication signal-to-interference-plus-noise ratio (SINR) requirement. Simulation results show that the proposed digital twin-assisted beamforming design achieves near-optimal target sensing SNR in both LoS and NLoS dominant areas, while ensuring the required SINR for the communication user. This highlights the potential of leveraging digital twins to assist ISAC systems.

Sana Hafeez, Mahmoud A. Shawky, Mohammad Al-Quraan et al.

Unmanned aerial vehicles (UAV), an emerging architecture that embodies flying ad-hoc networks, face critical privacy and security challenges, mainly when engaged in data-sensitive missions. Therefore, message authentication is a crucial security feature in drone communications. This paper presents a Blockchain-based Efficient, and Trusted Authentication scheme for UAV communication, BETA-UAV, which exploits the inherent properties of blockchain technology concerning memorability and is immutable to record communication sessions via transactions using a smart contract. The smart contract in BETA-UAV allows participants to publish and call transactions from the blockchain network. Furthermore, transaction addresses are proof of freshness and trustworthiness for subsequent transmissions. Furthermore, we investigated their ability to resist active attacks, such as impersonation, replaying, and modification. In addition, we evaluate the gas costs associated with the functions of the smart contract by implementing a BETA-UAV on the Ethereum public blockchain. A comparison of the computation and communication overheads shows that the proposed approach can save significant costs over traditional techniques.

Danrui Li, Mathew Schwartz, Samuel S. Sohn et al.

For transportation hubs, leveraging pedestrian flows for commercial activities presents an effective strategy for funding maintenance and infrastructure improvements. However, this introduces new challenges, as consumer behaviors can disrupt pedestrian flow and efficiency. To optimize both retail potential and pedestrian efficiency, careful strategic planning in store layout and facility dimensions was done by expert judgement due to the complexity in pedestrian dynamics in the retail areas of transportation hubs. This paper introduces an attention-based movement model to simulate these dynamics. By simulating retail potential of an area through the duration of visual attention it receives, and pedestrian efficiency via speed loss in pedestrian walking behaviors, the study further explores how design features can influence the retail potential and pedestrian efficiency in a bi-directional corridor inside a transportation hub. Project webpage: https://danruili.github.io/AttentionMove

Corinna Oschatz, Caroline Marker

This meta-analysis builds on the broad and diverse research on the persuasive effects of narrative communication. Researchers have found that narratives are a particularly effective type of message that often has greater persuasive effects than non-narratives immediately after exposure. The present study meta-analyzes whether this greater persuasive power persists over time. Results are based on k1 = 14 studies with k2 = 51 effect sizes for immediate measurement (N = 2,834) and k2 = 66 effect sizes for delayed measurement (N = 2,459). They show that a single narrative message has a stronger persuasive impact than a non-narrative message on attitudes and intentions at immediate as well as on attitudes, intentions, and behaviors at delayed measurement. Both message types did not differently affect the participants’ beliefs. Meta-analytic structural equation modeling confirms transportation as a mediator of immediate persuasive effects.

Chunlei SUN, Linpei LI, Haijun ZHANG

The vehicle-to-everything (V2X) network has the potential to revolutionize the way we interact with vehicles and the surrounding. By utilizing innovative information and communication technologies, V2X networks can connect human beings, vehicles, roadside units, and even the cloud. In the near future, beyond 5G (B5G) and 6G technologies will enable the next-generation V2X networks to achieve superior communication and sensing capabilities, which is expected to offer advanced technologies such as intelligent driving and transportation. However, the strong Doppler effects arising from the high mobility of vehicles may lead to significant inter-carrier interference and pilot overheads in the existing orthogonal frequency division multiplexing (OFDM) systems, particularly as the millimeter wave and terahertz technologies dominate the B5G/6G era. In recent years, orthogonal time frequency space (OTFS) techniques have attracted attention owing to their ability to resist doubly-selective fading. In addition, the integrated sensing and communication (ISAC) based on OTFS (OTFS-ISAC) has emerged as a promising approach for V2X networks. In this context, our objective is to investigate the system structure, application and challenges of OTFS-ISAC in V2X networks, along with the related key techniques such as frame structure, pilot design and signal processing. First, we will explore the structures and fundamental theories of OTFS-ISAC systems, followed by the evaluation of communication and sensing performance. In particular, we will investigate the system architecture of OTFS-ISAC in monostatic and bistatic radar modes, respectively. Secondly, we will provide an overview of the state-of-the-art of OTFS techniques and further discuss the challenges and key techniques of OTFS-ISAC concerning the frame structure in the physical layer, pilot mechanism design, communication and radar signal analyses, etc. Finally, we will examine the case studies of OTFS-ISAC utilization in V2X networks to address corresponding major issues such as the inadequacy of Doppler resolution, low overhead beam scanning and target detection, and cooperative resource management. The ISAC system is in developmental stages, and this is the first comprehensive review that investigates the OTFS-ISAC system in detail. Although OTFS-ISAC offers significant advantages over OFDM-enabled ISAC in V2X characterized by high mobility, it faces numerous challenges in practical applications, including the well-known fractional Doppler effect and high peak-to-average ratio. However, with continuous development and technological advancements, it is anticipated that the OTFS-ISAC system will gain wide acceptance.

Amit M Shah

Telemedicine aims to provide increased access to high-quality healthcare that is efficient and cost-effective. It involves real-time interactive communication between patients and physicians at distant sites. It has the potential to revolutionize health-care delivery in India. Telemedicine in India offers several benefits, particularly in addressing healthcare challenges. It also bridges health-care disparities based on location, ethnicity, and social status. It reduces long waitlists, inflexible appointments, transportation difficulties, and frequent follow-ups. It enables doctors to remotely monitor patients, leading to more efficient health-care delivery and cost savings. Telemedicine facilitates collaboration among health-care providers, enabling them to share knowledge, seek second opinions, or consult specialists without physical limitations. Effective implementation of telemedicine improves India&apos;s primary health-care system by enhancing palliative care, early identification of diseases, prevention strategies, and rehabilitation. The Indian government has recognized the potential of telemedicine and has taken steps to promote its adoption through initiatives such as the National Telemedicine Portal and Collaboration with the Indian Space Research Organization. Despite challenges such as infrastructure limitations, proper regulation, and data security, the widespread accessibility of mobile devices and the Internet in India makes telemedicine a promising avenue for doctors to reach a larger population while improving patient care. Therefore, telemedicine in India offers doctors and health-care providers expanded access to patients, improved patient care through enhanced communication, increased efficiency in health-care delivery, opportunities for collaboration and knowledge sharing among health-care providers, and the strengthening of primary health-care systems. The Indian government&apos;s support further highlights the potential of telemedicine to transform health-care delivery in the country while addressing existing challenges. [Natl J Physiol Pharm Pharmacol 2023; 13(8.000): 1597-1603]

Fan Zeng, Jingxuan Yu, Jiamin Li et al.

In this paper, we combine the network-assisted full-duplex (NAFD) technology and distributed radar sensing to implement integrated sensing and communication (ISAC). The ISAC system features both uplink and downlink remote radio units (RRUs) equipped with communication and sensing capabilities. We evaluate the communication and sensing performance of the system using the sum communication rates and the Cramer-Rao lower bound (CRLB), respectively. We compare the performance of the proposed scheme with other ISAC schemes, the result shows that the proposed scheme can provide more stable sensing and better communication performance. Furthermore, we propose two power allocation algorithms to optimize the communication and sensing performance jointly. One algorithm is based on the deep Q-network (DQN) and the other one is based on the non-dominated sorting genetic algorithm II (NSGA-II). The proposed algorithms provide more feasible solutions and achieve better system performance than the equal power allocation algorithm.

Florian Muhr, Lorenzo Zaniboni, Saeid K. Dehkordi et al.

In a typical communication system, in order to maintain a desired SNR level, initial beam alignment (BA) must be established prior to data transmission. In a setup where a Base Station (BS) Tx sends data via a digitally modulated waveform, we propose a User Equipment (UE) enhanced with a Hybrid Intelligent Reflecting Surface (HIRS) to aid beam alignment. A novel multi-slot estimation scheme is developed that alleviates the restrictions imposed by the Hybrid Digital-Analog (HDA) architecture of the HIRS and the BS. To demonstrate the effectiveness of the proposed BA scheme, we derive the CRLB of the parameter estimation scheme and provide numerical results.

Keqiang Li, Yougang Bian, S. Li et al.

Abstract Vehicle-to-vehicle (V2V) communication-enabled cooperation of multiple connected vehicles improves the safety and efficiency of our transportation systems. However, the joining and leaving of vehicles and unreliability of wireless communication channels will cause the switching of communication topology among vehicles, thus affecting the performance of multi-vehicle systems. To address this issue, a distributed model predictive control (DMPC) method is proposed for multi-vehicle system control under switching communication topologies. First, an open-loop optimization problem is formulated, within which neighbor-deviation and self-deviation penalties and constraints are incorporated to ensure stability. Then, a DMPC algorithm is designed for multi-vehicle systems subject to switching communication topologies. For the closed-loop system, the convergence of predicted terminal states is proved based on the neighbor-deviation constraint. After that, closed-loop system stability is analysed based on a common Lyapunov function (CLF) defined using a joint neighbor set. It is proved that asymptotic stability of the closed-loop system can be achieved through a sufficient condition on the weight matrices of the open-loop optimization problem. Numerical simulations are conducted to demonstrate the effectiveness of the proposed DMPC controller.

Rajat Chaudhary, G. Aujla, S. Garg et al.

Industrial Internet of things (IIoT) is an emerging technology with a large number of smart connected devices having sensing, storage, and computing capabilities. IIoT is used in a wide range of applications such as transportation, healthcare, manufacturing, and energy management in smart grids. Most of the solutions reported in the literature for secure communications are not suitable for the aforementioned applications due to the usage of traditional TCP/IP-based network infrastructure. So, to handle this challenge, in this paper, a software-defined network (SDN) enabled multi-attribute secure communication model for an IIoT environment is designed. The proposed scheme works in three phases: 1) an SDN-IIoT communication model is designed using a cuckoo-filter-based fast-forwarding scheme, 2) an attribute-based encryption scheme is presented for secure data communication, and 3) a peer entity authentication scheme using a third party authenticator, Kerberos , is also presented. The proposed scheme has been evaluated using different parameters where the results obtained prove its effectiveness in comparison to the existing solutions.