Hasil untuk "Transportation and communication"

Abdolhamid Tajvar, Shokrollah Mohseni, Marzieh Kazempour

ABSTRACT Background and Aim With the development of trade between countries, the transportation of goods has increased, and ports struggle to accommodate the demands of unloading and loading operations. Seaport workers may experience work‐related musculoskeletal disorders (WMSDs), which in many cases result in disabilities. Few studies have investigated the prevalence of work‐related musculoskeletal disorders (WMSDs) and associated psychological factors among dock workers in Iran. Existing findings indicate a high prevalence of WMSDs in these settings, primarily attributed to adverse working conditions such as repetitive movements, awkward postures, heavy lifting, and excessive physical strain. Moreover, there is a scarcity of research examining the impact of psychological factors on musculoskeletal disorders within this occupational group. This study investigated the relationship between work‐related psychological factors and job characteristics and WMSDs at the Port of Shahid Rajaee in Bandar Abbas, Iran, from December 2023 to April 2024. Methods In this cross‐sectional study, all 351 dock workers were enrolled as research subjects. Dock workers in our study encompassed four distinct occupational roles with different physical and postural demands, including Trans Trainer Operators, Gantry Crane Operators, Tractor Drivers, and warehouse workers. To collect data, the Job Content Questionnaire (JCQ) and the Nordic Musculoskeletal Questionnaire (NMQ) were used. The sampling method used in this study was a census approach, encompassing all eligible workers at Sina port and Marine Service Development Company. Statistical analyses included descriptive statistics, independent t‐tests, Pearson's correlation coefficients, and one‐way analysis of variance (ANOVA). Results The NMQ scores across the four groups were highest for the neck, shoulder, and upper back regions, with a mean score of 38.02, and lowest for the upper limb region, with a mean score of 10.40. Trans trainer and gantry crane operators and warehouse workers had significantly higher WMSDs in neck, shoulder, and upper back than tractor drivers (p < 0.001). Additionally, NMQ scores for the lower back were significantly correlated with the job type (p < 0.001), with warehouse workers having the highest MSD scores (22.85). Higher psychological job demands and psychosocial and physical stress were associated with more severe WMSDs for the workers. In addition, type of the job, age, work experience, marital status, and high job insecurity were significant factors influencing WMSDs. Conclusion Work‐related psychosocial factors play an important role in the development of work‐related musculoskeletal disorders (WMSDs) among port workers. To mitigate these risks, it is essential to address psychological stress and job demands. Additionally, improving communication between port workers and management may contribute to a healthier and more supportive work environment.

Preeti Kumari, Sergiy A. Vorobyov, Robert W. Heath

Anis ur Rehman, Ishaq G. Muhammad Alblushi, Muhammad Fahad Zia et al.

In the absence of portable charging devices, sectors such as transportation, communication, and emergency services deal with various challenges towards electric power needs while compromising on (1) operational efficiency, (2) insufficient portable charging solutions, and (3) limited versatility. This highlights the critical need for reliable and multi-functional power solutions. To provide a portable charging solution across diverse sectors, this paper proposes an innovative development of a solar-powered multi-functional portable charging device (SPMFPCD) with internet- of-thing (IoT)-based monitoring capabilities. The proposed scheme introduces a comprehensive model integrating advanced technologies which include a highly efficient solar panel, charge controller, sensors, and IoT module. The proposed system facilitates versatile charging solutions for a wide range of power requirements with real-time monitoring and data analysis through the IoT platform. Moreover, the proposed work explores the applications of the SPMFPCD in (1) emergency medical scenarios, (2) outdoor adventures, (3) disaster management, and 4) public spaces. Performance evaluation was made by proposing case studies to validate the (1) economic viability, (2) power management, and (3) environmental impact of widespread deployment of SPMPFCD in public spaces. Furthermore, detailed analysis of battery energy storage system (BESS) and photovoltaic (PV) integration for load management, seasonal dynamics, and renewable energy integration (REI) contribute to a comprehensive understanding of the proposed solution.

Mirabela Melinda Medvei, Alin-Viorel Bordei, Ștefania Loredana Niță et al.

Urban traffic congestion remains a major contributor to vehicle emissions and travel inefficiency, prompting the need for adaptive and intelligent traffic management systems. In response, we introduce DeepSIGNAL-ITS (Deep Learning Signal Intelligence for Adaptive Lights in Intelligent Transportation Systems), a unified framework that leverages real-time traffic perception and learning-based control to optimize signal timing and reduce congestion. The system integrates vehicle detection via the YOLOv8 architecture at roadside units (RSUs) and manages signal control using Proximal Policy Optimization (PPO), guided by global traffic indicators such as accumulated vehicle waiting time. Secure communication between RSUs and cloud infrastructure is ensured through Transport Layer Security (TLS)-encrypted data exchange. We validate the framework through extensive simulations in SUMO across diverse urban settings. Simulation results show an average 30.20% reduction in vehicle waiting time at signalized intersections compared to baseline fixed-time configurations derived from OpenStreetMap (OSM). Furthermore, emissions assessed via the HBEFA-based model in SUMO reveal measurable reductions across pollutant categories, underscoring the framework’s dual potential to improve both traffic efficiency and environmental sustainability in simulated urban environments.

Benedikte Borgström, Luis Araujo, Susanne Hertz

<i>Background</i>: Customer orders are key in developing logistics processes and in strategic developments of customer orientation. This paper investigates the notion of customer orientation. In the literature, the concept of customer is underdeveloped in that it is seen as a single object rather than how it is enacted in multiple ways. The study examines a customer-oriented production process managed in the supply chain of an automotive manufacturer. <i>Methods</i>: Based on a longitudinal study we explain what constitutes customer knowledge and what processes are involved in constructing this knowledge. <i>Results</i>: The study shows that in a supply chain, multiple versions of customers coexist and overlap that have implications on how multiple-customer orientation is performed and aligned in the supply chain. <i>Conclusions</i>: We find that customer representations proliferate as a result of multiple objectives; we demonstrate what objects and assemblages bring particular customer representation to life and show that these are used to shape customer orientation.

Samia Haman, Anass Ben Abdelouahab, Younes El Bouzekri El Idrissi et al.

<i>Background:</i> The rapid digital transformation driven by Industry 4.0 technologies is reshaping manufacturing supply chains, yet comprehensive insights into how these technologies are integrated remain limited. <i>Methods:</i> This study addresses this research gap by conducting a systematic bibliometric analysis and literature review of integrating Industry 4.0 technologies in the manufacturing supply chain. We used different scientific databases, Scopus and Web of Science, to elaborate this study. <i>Results</i>: Using advanced bibliometric methods, this study examines the evolution of academic discourse, identifies key themes, and maps the intellectual structure of this transformative research field. By leveraging bibliometric tools, the study names the most prolific authors, countries, and journals contributing to this domain. The findings of the first phase reveal the growing focus on topics like supply chain resilience and real-time decision-making, while also finding gaps in the literature related to technology integration. In the second phase, the literature review identified the most used adoption models in empirical studies such as resource-based view, dynamic capabilities view, and technology acceptance model, we also categorized the adoption drivers into technological, organizational, and environmental. <i>Conclusions:</i> This review emphasizes that although research on Industry 4.0 has expanded significantly, the majority of studies predominantly concentrate on technology adoption and quantitative analysis, with little examination of integration, contextual factors, and longitudinal effects.

David R. Gruber

Strategic Communication Protocols provide a structured approach for first contact with interstellar objects that demonstrate technological characteristics and high levels of threat. The protocols find their starting point in an ISO Information-Communication Paradox, namely, as our knowledge of an ISO's threatening capabilities increases, the probability of successful communication decreases while the urgency of communication attempts simultaneously intensifies. From this paradox, a Threat-Communication Viability Index is created to describe when the value of communication attempts outweighs strategic silence. The index scores the situation and operates as a decision-making tool for stakeholders tracking an ISO. The communication protocols subsequently outline several diplomatic strategies in cases where the index recommends communication.

Megh Bahadur KC, Ziqi Song, Keunhyun Park et al.

Despite the growing recognition of the importance of inclusive transportation policies nationwide, there is still a gap, as the existing transportation models often fail to capture the unique travel behavior of people with disabilities. This research study focuses on understanding the mode choice behavior of individuals with travel-limited disabilities and comparing the group with no such disability. The study identified key factors influencing mode preferences for both groups by utilizing Utah's household travel survey, simulation algorithm and Multinomial Logit model. Explanatory variables include household and socio-demographic attributes, personal, trip characteristics, and built environment variables. The analysis revealed intriguing trends, including a shift towards carpooling among disabled individuals. People with disabilities placed less emphasis on travel time saving. A lower value of travel time for people with disabilities is potentially due to factors like part-time work, reduced transit fare, and no or shared cost for carpooling. Despite a 50% fare reduction for the disabled group, transit accessibility remains a significant barrier in their choice of Transit mode. In downtown areas, people with no disability were found to choose transit compared to driving, whereas disabled people preferred carpooling. Travelers with no driving licenses and disabled people who use transit daily showed complex travel patterns among multiple modes. The study emphasizes the need for accessible and inclusive transportation options, such as improved public transit services, shorter first and last miles in transit, and better connectivity for non-motorized modes, to cater to the unique needs of disabled travelers. The findings of this study have significant policy implications such as an inclusive mode choice modeling framework for creating a more sustainable and inclusive transportation system.

Jinjing Wu, Xiaobo Lin, Chengkai Yang et al.

Wearable sensors are important components, converting mechanical vibration energy into electrical signals or other forms of output, which are widely used in healthcare, disaster warning, and transportation. However, the reliance on batteries limits the portability of wearable sensors and hinders their application in the field of Internet of Things. To solve this problem, we designed a miniaturized high-performance hybrid nanogenerator (MHP-HNG), which combined the functions of triboelectric sensing and electromagnetic power generation as well as the advantages of miniaturization. By optimizing the design of TENG and EMG, the wearable sensor achieved a voltage output of 14.14 V and a power output of 49 mW. Based on the wireless optical communication and wireless communication technologies, the wearable sensor achieved the integration of sensing, communication, and self-powered function, which is expected to realize health monitoring, emergency warning, and rehabilitation assistance, and further extend the potential application value in the medical field.

Pei Yu, Yubao Han, Lulu Meng et al.

Osteosarcoma, a prevalent primary malignant bone tumor, often presents with lung metastases, severely impacting patient survival rates. Extracellular vesicles, particularly exosomes, play a pivotal role in the formation and progression of osteosarcoma-related pulmonary lesions. However, the communication between primary osteosarcoma and exosome-mediated pulmonary lesions remains obscure, with the potential impact of pulmonary metastatic foci on osteosarcoma progression largely unknown. This study unveils an innovative mechanism by which exosomes originating from osteosarcoma pulmonary metastatic sites transport the miR-194/215 cluster to the primary tumor site. This transportation enhances lung metastatic capability by downregulating myristoylated alanine-rich C-kinase substrate (MARCKS) expression. Addressing this phenomenon, in this study we employ cationic bovine serum albumin (CBSA) to form nanoparticles (CBSA-anta-194/215) via electrostatic interaction with antagomir-miR-194/215. These nanoparticles are loaded into nucleic acid-depleted exosomal membrane vesicles (anta-194/215@Exo) targeting osteosarcoma lung metastatic sites. Intervention with bioengineered exosome mimetics (anta-194/215@Exo) not only impedes osteosarcoma progression but also significantly prolongs the lifespan of tumor-bearing mice. These findings suggest that pulmonary metastatic foci-derived exosomes initiate primary osteosarcoma lung metastasis by transferring the miR-194/215 cluster targeting MARCKS, making the miR-194/215 cluster a promising therapeutic target for inhibiting the progression of patients with osteosarcoma lung metastases.

Joaquin Gonzalez, Liliana Avelar Sosa, Gabriel Bravo et al.

<i>Background</i>: Efficient inventory management is critical for sustainability in supply chains. However, maintaining adequate inventory levels becomes challenging in the face of unpredictable demand patterns. Furthermore, the need to disseminate demand-related information throughout a company often relies on cloud services. However, this method sometimes encounters issues such as limited bandwidth and increased latency. <i>Methods</i>: To address these challenges, our study introduces a system that incorporates a machine learning algorithm to address inventory-related uncertainties arising from demand fluctuations. Our approach involves the use of an attention mechanism for accurate demand prediction. We combine it with the Newsvendor model to determine optimal inventory levels. The system is integrated with fog computing to facilitate the rapid dissemination of information throughout the company. <i>Results</i>: In experiments, we compare the proposed system with the conventional demand estimation approach based on historical data and observe that the proposed system consistently outperformed the conventional approach. <i>Conclusions</i>: This research introduces an inventory management system based on a novel deep learning architecture that integrates the attention mechanism with cloud computing to address the Newsvendor problem. Experiments demonstrate the better accuracy of this system in comparison to existing methods. More studies should be conducted to explore its applicability to other demand modeling scenarios.

Seid Koudia, Leonardo Oleynik, Mert Bayraktar et al.

Quantum communication systems support unique applications in the form of distributed quantum computing, distributed quantum sensing, and several cryptographic protocols. The main enabler in these communication systems is an efficient infrastructure that is capable to transport unknown quantum states with high rate and fidelity. This feat requires a new approach to communication system design which efficiently exploits the available physical layer resources, while respecting the limitations and principles of quantum information. Despite the fundamental differences between the classic and quantum worlds, there exist universal communication concepts that may proven beneficial in quantum communication systems as well. In this survey, the distinctive aspects of physical layer quantum communications are highlighted in a attempt to draw commonalities and divergences between classic and quantum communications. More specifically, we begin by overviewing the quantum channels and use cases over diverse optical propagation media, shedding light on the concepts of crosstalk and interference. Subsequently, we survey quantum sources, detectors, channels and modulation techniques. More importantly, we discuss and analyze spatial multiplexing techniques, such as coherent control, multiplexing, diversity and MIMO. Finally, we identify synergies between the two communication technologies and grand open challenges that can be pivotal in the development of next-generation quantum communication systems.

Xinran Liu, Rocío Díaz Martín, Yikun Bai et al.

The optimal transport (OT) problem has gained significant traction in modern machine learning for its ability to: (1) provide versatile metrics, such as Wasserstein distances and their variants, and (2) determine optimal couplings between probability measures. To reduce the computational complexity of OT solvers, methods like entropic regularization and sliced optimal transport have been proposed. The sliced OT framework improves efficiency by comparing one-dimensional projections (slices) of high-dimensional distributions. However, despite their computational efficiency, sliced-Wasserstein approaches lack a transportation plan between the input measures, limiting their use in scenarios requiring explicit coupling. In this paper, we address two key questions: Can a transportation plan be constructed between two probability measures using the sliced transport framework? If so, can this plan be used to define a metric between the measures? We propose a "lifting" operation to extend one-dimensional optimal transport plans back to the original space of the measures. By computing the expectation of these lifted plans, we derive a new transportation plan, termed expected sliced transport (EST) plans. We prove that using the EST plan to weight the sum of the individual Euclidean costs for moving from one point to another results in a valid metric between the input discrete probability measures. We demonstrate the connection between our approach and the recently proposed min-SWGG, along with illustrative numerical examples that support our theoretical findings.

Martin Huesmann, Michael Goldman, Dario Trevisan

We establish the validity of asymptotic limits for the general transportation problem between random i.i.d. points and their common distribution, with respect to the squared Euclidean distance cost, in any dimension larger than three. Previous results were essentially limited to the two (or one) dimensional case, or to distributions whose absolutely continuous part is uniform. The proof relies upon recent advances in the stability theory of optimal transportation, combined with functional analytic techniques and some ideas from quantitative stochastic homogenization. The key tool we develop is a quantitative upper bound for the usual quadratic optimal transportation problem in terms of its boundary variant, where points can be freely transported along the boundary. The methods we use are applicable to more general random measures, including occupation measure of Brownian paths, and may open the door to further progress on challenging problems at the interface of analysis, probability, and discrete mathematics.

Şemsettin Çiğdem, Ieva Meidute-Kavaliauskiene, Bülent Yıldız

<i>Background:</i> Human–robot collaboration is essential for efficient manufacturing and logistics as robots are increasingly used. Using industrial robots as part of an automation system results in many competitive benefits, including improved quality, efficiency, productivity, and reduced waste and errors. When robots are used in production, human coworkers’ psychological factors can disrupt operations. This study aims to examine the effect of employees’ negative attitudes toward robots on their acceptance of robot technology in manufacturing workplaces. <i>Methods:</i> A survey was conducted with employees in manufacturing companies to collect data on their attitudes towards robots and their willingness to work with them. Data was collected from 499 factory workers in Istanbul using a convenience sampling method, which allowed for the measurement of variables and the analysis of their effects on each other. To analyze the data, structural equation modeling was used. <i>Results:</i> The results indicate that negative attitudes towards robots have a significant negative effect on the acceptance of robot technology in manufacturing workplaces. However, trust in robots was found to be a positive predictor of acceptance. <i>Conclusions:</i> These findings have important implications for manufacturing companies seeking to integrate robot technology into their operations. Addressing employees’ negative attitudes towards robots and building trust in robot technology can increase the acceptance of robots in manufacturing workplaces, leading to improved efficiency and productivity.

Veronica De Micco, Chiara Amitrano, Felice Mastroleo et al.

Abstract Long-term human space exploration missions require environmental control and closed Life Support Systems (LSS) capable of producing and recycling resources, thus fulfilling all the essential metabolic needs for human survival in harsh space environments, both during travel and on orbital/planetary stations. This will become increasingly necessary as missions reach farther away from Earth, thereby limiting the technical and economic feasibility of resupplying resources from Earth. Further incorporation of biological elements into state-of-the-art (mostly abiotic) LSS, leading to bioregenerative LSS (BLSS), is needed for additional resource recovery, food production, and waste treatment solutions, and to enable more self-sustainable missions to the Moon and Mars. There is a whole suite of functions crucial to sustain human presence in Low Earth Orbit (LEO) and successful settlement on Moon or Mars such as environmental control, air regeneration, waste management, water supply, food production, cabin/habitat pressurization, radiation protection, energy supply, and means for transportation, communication, and recreation. In this paper, we focus on air, water and food production, and waste management, and address some aspects of radiation protection and recreation. We briefly discuss existing knowledge, highlight open gaps, and propose possible future experiments in the short-, medium-, and long-term to achieve the targets of crewed space exploration also leading to possible benefits on Earth.

Suying Jiang, Wei Wang, Ibrahim Rashdan et al.

Vehicular ad hoc network (VANET) brings an excellent solution to ensure road safety and transportation efficiency in critical environment like tunnel. Particularly, radio link connectivity of vehicle-to-vehicle (V2V) significantly influences the performance of VANETs. The communication range of the radio systems is a random variable in reality due to the channel fading effect. Therefore, the connectivity model between vehicles in realistic environment is a key for accurate evaluation of system performances. In this paper, we study the V2V connectivity performance in the presence of channel randomness for tunnel environment. Firstly, based on channel measurement campaign, empirical path loss (PL) and small-scale fading channel models are established. Secondly, we study the influence of large-scale fading parameters on V2V connectivity. Thirdly, based on real small-scale fading characteristics, we derive the V2V connectivity probability between any two vehicles under Nakagami fading channel for one-dimensional VANET, and give the closed-form of V2V connectivity probability. Finally, we study the influences of various parameters (i.e., Nakagami fading factor, vehicle density, and neighbor order) on V2V connectivity performance. Results show that with the Nakagami fading shape factor increases, the connectivity probability increases. The shadowing fading can improve connectivity in the VANET; the path loss exponent, transmission distance, and signal-to-noise ratio (SNR) threshold have a negative impact on connectivity probability. The transmit power, vehicle density, and path loss threshold value have a positive impact on connectivity.

Xiuxian Yang, Wanxiang Feng, Xiao-Ping Li et al.

Recently, Heusler ferromagnets have been found to exhibit unconventional anomalous electric, thermal, and thermoelectric transport properties. In this study, we employed first-principles density functional theory calculations to systematically investigate both intrinsic and extrinsic contributions to the anomalous Hall effect (AHE), anomalous Nernst effect (ANE), and anomalous thermal Hall effect (ATHE) in two Heusler ferromagnets: Fe$_2$CoAl and Fe$_2$NiAl. Our analysis reveals that the extrinsic mechanism originating from disorder dominates the AHE and ATHE in Fe$_2$CoAl , primarily due to the steep band dispersions across the Fermi energy and corresponding high longitudinal electronic conductivity. Conversely, the intrinsic Berry phase mechanism, physically linked to nearly flat bands around the Fermi energy and gapped by spin-orbit interaction band crossings, governs the AHE and ATHE in Fe$_2$NiAl. With respect to ANE, both intrinsic and extrinsic mechanisms are competing in Fe$_2$CoAl as well as in Fe$_2$NiAl. Furthermore, Fe$_2$CoAl and Fe$_2$NiAl exhibit tunable and remarkably pronounced anomalous transport properties. For instance, the anomalous Nernst and anomalous thermal Hall conductivities in Fe$_2$NiAl attain giant values of 8.29 A/Km and 1.19 W/Km, respectively, at room temperature. To provide a useful comparison, we also thoroughly investigated the anomalous transport properties of Co$_2$MnGa. Our findings suggest that Heusler ferromagnets Fe$_2$CoAl and Fe$_2$NiAl are promising candidates for spintronics and spin-caloritronics applications.

Dakshita Reebadiya, Tejal Rathod, Rajesh K. Gupta et al.

Mariya Ouaissa, Mariyam Ouaissa, Meriem Houmer et al.