Vincent van Vliet, Menno van den Hout, Eduward Tangdiongga
et al.
Free-space optical communication links can enable high-capacity wireless connectivity in urban areas. We discuss the feasibility, challenges, and recent developments for high-capacity urban free-space optical links at kilometer scale.
<i>Background:</i> As a labor-, capital-, and technology-intensive sector, shipbuilding supports water transportation, international trade, and marine development, driving economic growth and employment. Yet rising raw material/labor costs now bottleneck enterprise performance, making cost reduction and efficiency improvement urgent for shipbuilding and repair firms. It is an effective way to improve logistics transportation efficiency for reducing the cost of shipbuilding and repair firms. However, there are still few methods specifically designed for logistics transportation scheduling in shipbuilding and repair firms. <i>Methods:</i> In this paper, a “dual-cycle” strategy is proposed to optimize material transportation and cut logistics vehicles’ empty-load rate in the shipbuilding and repair process. A mixed-integer programming model is built to minimize total empty travel time, considering task priorities and time windows. A genetic algorithm-based scheduling method is proposed to solve this complex scheduling model. <i>Results</i>: Simulation with real shipyard logistics data shows the proposed model and algorithm can effectively address the shipbuilding logistics vehicle scheduling problem. In addition, the proposed algorithm performs better than two other compared algorithms in handling the studied problem. <i>Conclusions:</i> This study aids shipbuilding and repair logistics managers in making scheduling plans and determining optimal vehicle numbers, supporting cost-efficiency improvement.
Transportation and communication, Management. Industrial management
Sukanta Ghadei, Amaresh Chandra Panada, Surapati Pramanik
et al.
This research paper presents an innovative approach for determining the minimum spanning tree (MST) in an undirected neutrosophic graph using Prim's Algorithm, which is extensively used in addressing network optimization problems. We analyze the effectiveness of Prim's method for constructing the minimum spanning trees in undirected neutrosophic networks, where edge weights are denoted by neutrosophic numbers. Neutrosophic numbers with components reflecting truth, uncertainty, and Neutrosophic Sets and Systems, Vol. 85, 2025 362 Sukanta Ghadei, Amaresh Chandra Panada,Surapati,Pramanik, Nihar Ranjan Panda, Prasanta Kumar Raut, Evaluating the Minimum Spanning Trees Using Prim's Algorithm with Undirected Neutrosophic Graphs falsehood provide a more sophisticated method of expressing uncertainty in network modeling. Here, we use a score function to contrast different NMSTs based on weights calculated by adding neutrosophic numbers. This method is particularly beneficial for use in transportation, communication networks, and logistics, where uncertain properties frequently define network configurations. Numerical illustrations prove the effectiveness of the proposed method, showing its efficiency in handling neutrosophic graphs and keeping it computationally feasible. The results indicated that the suggested Prim's algorithm efficiently produces the minimum spanning trees in uncertain environments and is advantageous for network design and optimization in these scenarios.
This study aims to investigate the effectiveness of carbon nanotubes (CNTs) and styrene-butadiene-styrene (SBS) on the fatigue performance of two types of base asphalt binders (70# and 90#). Frequency sweep and linear amplitude sweep (LAS) tests were carried out on CNT- and CNT/SBS-modified asphalt binders using a dynamic shear rheometer. The fatigue damage characteristics and fatigue failure behavior of the modified binders were analyzed using the simplified viscoelastic continuous damage theoretical model. The dynamic modulus master curve outcomes indicated that incorporating CNT and SBS enhanced the stiffness and elastic recovery of the base asphalt binder, thereby enhancing its resistance to permanent deformation. The results of the LAS tests showed that incorporating CNT nanoparticles can significantly improve the fatigue life of 70# and 90# base asphalt binders. The fatigue damage resistance of both the CNT-modified and the CNT/SBS-modified asphalt binders was also significantly improved. The fatigue life of the 90#/CNT-modified asphalt binder was greater than that of the 70#/CNT-modified asphalt binder under an unaged condition. After the short-term aging process, the fatigue life of the modified asphalt binder decreases, and the fatigue life of the modified asphalt binder after ultraviolet aging indicates an additional reduction in overall fatigue life.
Vehicular Ad-hoc Networks (VANETs) are critical to Intelligent Transportation Systems (ITS), enabling vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication to improve road safety and traffic flow. However, VANETs face significant security threats, particularly position falsification attacks, where malicious nodes disseminate false Basic Safety Messages (BSMs). This study proposes an ensemble learning framework to detect such attacks, leveraging Decision Tree (CART), Random Forest, K-Nearest Neighbors (KNN), and Multilayer Perceptron (MLP) classifiers enhanced with bagging. Using the VeReMi dataset, our RSU-level detection system analyzes sequential BSMs to detect malicious behavior. Results demonstrate that KNN with bagging achieves perfect precision, recall, accuracy, and F1 score (100%) for Attack 1, while maintaining near-perfect performance for complex attacks like Attack 2 (99.87% accuracy) and Attack 16 (97.85% accuracy). Decision Tree with bagging also performs well for simpler attacks but experiences a slight decline for highly complex scenarios. Random Forest with bagging excels in simpler attacks but struggles with complex patterns. MLP with bagging shows strong results for simpler attacks but underperforms in complex scenarios. The proposed framework highlights the effectiveness of ensemble techniques, particularly KNN with bagging, in safeguarding VANET communication systems, offering a scalable, efficient, and robust solution for VANET security.
The ever-growing learning model size nowadays challenges the communication efficiency and privacy preservation of the traditional federated learning (FL). In this paper, we propose a novel differentially private (DP) over-the-air federated distillation (FD) framework, where wireless devices (WDs) periodically share noise-perturbed model outputs with the parameter server by harnessing the superposition property of multi-access channels. Accordingly, over-the-air FD enables the shared responsibility of the DP preservation on the low-dimensional disclosed signals among WDs. We study the communication-learning co-design problem in differentially private over-the-air FD, aiming to maximize the learning convergence rate while meeting the transmit power and DP requirements of WDs. The main challenge is rooted in the intractable learning and privacy analysis in over-the-air FD, together with the strong coupling among the decision variables spanning two timescales. To tackle this problem, we first derive the analytical learning convergence rate and privacy losses of WDs, based on which the optimal transceiver design per FD round and long-term training rounds decision are obtained in the closed forms. Numerical results demonstrate that the proposed differentially private over-the-air FD approach achieves a better learning-privacy trade-off with largely-reduced communication overhead than the conventional FL benchmarks.
Computer vision has become a popular tool in intelligent transportation systems (ITS), enabling various applications through roadside traffic cameras that capture video and transmit it in real time to computing devices within the same network. The efficiency of this video transmission largely depends on the available bandwidth of the communication system. However, limited bandwidth can lead to communication bottlenecks, hindering the real-time performance of ITS applications. To mitigate this issue, lossy video compression techniques can be used to reduce bandwidth requirements, at the cost of degrading video quality. This degradation can negatively impact the accuracy of applications that rely on real-time vehicle detection. Additionally, vehicle detection accuracy is influenced by environmental factors such as weather and lighting conditions, suggesting that compression levels should be dynamically adjusted in response to these variations. In this work, we utilize a framework called Precision-Aware Video Compression (PAVC), where a roadside video camera captures footage of vehicles on roadways, compresses videos, and then transmits them to a processing unit, running a vehicle detection algorithm for safety-critical applications, such as real-time collision risk assessment. The system dynamically adjusts the video compression level based on current weather and lighting conditions to maintain vehicle detection accuracy while minimizing bandwidth usage. Our results demonstrate that PAVC improves vehicle detection accuracy by up to 13% and reduces communication bandwidth requirements by up to 8.23x in areas with moderate bandwidth availability. Moreover, in locations with severely limited bandwidth, PAVC reduces bandwidth requirements by up to 72x while preserving vehicle detection performance.
Shubha Bakkappa Davalagi, Eshwar S. Kasturi, P Vaman Nayak
et al.
Introduction:
The major advantages of telemedicine can be saving time, cost, and effort, especially for rural patients, during challenging times such as COVID for obtaining consultation and treatment. Telemedicine, if properly implemented, can reduce gaps and strengthen the health-care delivery system in India.
Objective:
The objective of the study was to assess the perception and practice of health-care providers toward telemedicine.
Methodology:
We conducted a cross-sectional study among 141 health-care providers who ever practiced telemedicine consultation. Utilizing online Google Forms, we used snowball sampling. Four sections made up the pretested study questionnaire: demographic information, perceptions, and practices. Statistical Package for the Social Sciences (SPSS) version 21 was used for data analysis.
Results:
Among them, majority were aged between 35 and 44 years (49.6%), males (56%), had M.D./M.S. degree (57.4%), postgraduates (33.3%), worked in private sector (56.7%), and were from clinical specialty (80.8%) We had majority health-care workers who used telemedicine application for the first time after COVID (80.1%), used only mobile (82.2%), used only one application (83.6%), and gave 5–10 consultations per day (57.4%). Most of our study participants feel teleconsultation takes less time (61.7%), reduces waiting list at medical center (92.9%), has better communication (83.6%), gives better aid during emergency (53.9%), and saves money on transportation (97.1%).
Conclusion:
In this study, we could conclude that most participants started practicing telemedicine post-COVID. Health-care professionals still feel challenging to provide effective patient counseling through telemedicine; moreover, they are benefitted from telemedicine practice.
Although the development of electric vehicle (EV) technology offers opportunities for reducing CO2 emissions through the electrification of transportation, the integration of EVs into distribution systems poses a significant challenge to the reliable operation of existing protection systems. As the penetration level of EVs continues to rise, the fault current characteristic of the distribution system changes, resulting in load de-energization, equipment damage, and reduced reliability. This paper develops a protection scheme for preserving coordination between main and backup overcurrent relays considering various penetration levels and locations of integrated EVs. By modifying the EV charger control system, the proposed scheme limits the fault current contribution of adopted EV charge stations into the fault point. The developed scheme does not alter the structure of the available protection system of the distribution network and is compatible with both old and nonprogrammable relays. Furthermore, it does not require communication links. The effectiveness of the proposed scheme is validated through several case studies on the Isfahan distribution network. The findings indicate that the operating time of the backup relay in the conventional protection system exceeds the thermal limit at 100% penetration level of EVs installed upstream of this relay as it reaches 1810 ms, while by using the proposed strategy, this time reduces to 776 ms, preserving protection coordination between the main and backup relays.
Abstract The urban rail transit (URT) system in China has undergone development spanning over 50 years. In the period from 2008 to 2015, numerous URT lines were under construction. After 2015, an increasing number of cities have transitioned to multi-line network operations, with greater emphasis on system efficiency and passenger service. This transition has been accompanied by numerous successful innovations and applications aimed at enhancing system intelligence and automation. This paper provides a review of operational statistics based on annual reports, successful operational practices, and industry development characteristics over the past decade in mainland China. Additionally, suggestions and trends for the further development of URT in China are proposed.
Transportation engineering, Transportation and communications
Browser fingerprinting is the identification of a browser through the network traffic captured during communication between the browser and server. This can be done using the HTTP protocol, browser extensions, and other methods. This paper discusses browser fingerprinting using the HTTPS over TLS 1.3 protocol. The study observed that different browsers use a different number of messages to communicate with the server, and the length of messages also varies. To conduct the study, a network was set up using a UTM hypervisor with one virtual machine as the server and another as a VM with a different browser. The communication was captured, and it was found that there was a 30\%-35\% dissimilarity in the behavior of different browsers.
Optimal transport has numerous applications, particularly in machine learning tasks involving generative models. In practice, the transportation process often encounters an information bottleneck, typically arising from the conversion of a communication channel into a rate-limited bit pipeline using error correction codes. While this conversion enables a channel-oblivious approach to optimal transport, it fails to fully exploit the available degrees of freedom. Motivated by the emerging paradigm of generative communication, this paper examines the problem of channel-aware optimal transport, where a block of i.i.d. random variables is transmitted through a memoryless channel to generate another block of i.i.d. random variables with a prescribed marginal distribution such that the end-to-end distortion is minimized. With unlimited common randomness available to the encoder and decoder, the source-channel separation architecture is shown to be asymptotically optimal as the blocklength approaches infinity. On the other hand, in the absence of common randomness, the source-channel separation architecture is generally suboptimal. For this scenario, a hybrid coding scheme is proposed, which partially retains the generative capabilities of the given channel while enabling reliable transmission of digital information. It is demonstrated that the proposed hybrid coding scheme can outperform both separation-based and uncoded schemes.
Reconfigurable intelligent surface (RIS) provides a promising way to proactively augment propagation environments for better transmission performance in wireless communications. Existing multi-RIS works mainly focus on link-level optimization with predetermined transmission paths, which cannot be directly extended to system-level management, since they neither consider the interference caused by undesired scattering of RISs, nor the performance balancing between different transmission paths. To address this, we study an innovative multi-hop multi-RIS communication system, where a base station (BS) transmits information to a set of distributed users over multi-RIS configuration space in a multi-hop manner. The signals for each user are subsequently reflected by the selected RISs via multi-reflection line-of-sight (LoS) links. To ensure that all users have fair access to the system to avoid excessive number of RISs serving one user, we aim to find the optimal beam reflecting path for each user, while judiciously determining the path scheduling strategies with the corresponding beamforming design to ensure the fairness. Due to the presence of interference caused by undesired scattering of RISs, it is highly challenging to solve the formulated multi-RIS multi-path beamforming optimization problem. To solve it, we first derive the optimal RISs' phase shifts and the corresponding reflecting path selection for each user based on its practical deployment location. With the optimized multi-reflection paths, we obtain a feasible user grouping pattern for effective interference mitigation by constructing the maximum independent sets (MISs). Finally, we propose a joint heuristic algorithm to iteratively update the beamforming vectors and the group scheduling policies to maximize the minimum equivalent data rate of all users.
Recent developments of information and communication technologies (ICT) have enabled vehicles to timely communicate with each other through wireless technologies, which will form future (intelligent) traffic systems (ITS) consisting of so-called connected vehicles. Cooperative driving with the connected vehicles is regarded as a promising driving pattern to significantly improve transportation efficiency and traffic safety. Nevertheless, unreliable vehicular communications also introduce packet loss and transmission delay when vehicular kinetic information or control commands are disseminated among vehicles, which brings more challenges in the system modeling and optimization. Currently, no data has been yet available for the calibration and validation of a model for ITS, and most research has been only conducted for a theoretical point of view. Along this line, this paper focuses on the (theoretical) development of a more general (microscopic) traffic model which enables the cooperative driving behavior via a so-called inter-vehicle communication (IVC). To this end, the authors design a consensus-based controller for the cooperative driving system (CDS) considering (intelligent) traffic flow that consists of many platoons moving together. More specifically, the IEEE 802.11p, the de facto vehicular networking standard required to support ITS applications, is selected as the IVC protocols of the CDS, in order to investigate how the vehicular communications affect the features of intelligent traffic flow. This study essentially explores the relationship between IVC and cooperative driving, which can be exploited as the reference for the CDS optimization and design.
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'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'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]
Therapeutics. Pharmacology, Pharmacy and materia medica
The transit service in a city should be the most efficient, least polluting, most accessible, and sustainable means of transportation for its citizens. However, serious shortcomings have been detected, mainly in medium-sized cities in developing countries. These shortcomings are related to a lack of user information, insecurity, low service availability, and repeated stops in inappropriate and/or unauthorized places. Some of these shortcomings contribute to high accident rates and traffic congestion. The development of tools to improve the characteristics and conditions of transit service in cities has become an imperative need to improve the quality of life of citizens and city sustainability. Transit service tracking is relevant in aspects such as online location information to travelers and control by transport companies for compliance with speed limits, schedules, routes, and stops. This research proposes a transit vehicle tracking system based on the Internet of Vehicles (IoV) in Vehicle-to-Roadside (V2R) classification. The proposed system is ideal for the use of electric vehicles due to the low power consumption of the tracking device. This system uses Intelligent Transportation Systems (ITS) tracking service architecture, Long Range (LoRa) communication technology, and its LoRa Wide Area Network (LoRaWAN) protocol. Additionally, the system offers real-time location prediction in the absence of position data. The IoV tracking device integrates a GPS-LoRa module card with an Inertial Measurement Unit (IMU). A location prediction algorithm was implemented to train and store a prediction model with previously collected data from tracking devices. To evaluate the developed model, a case study in the city of Popayán (Colombia) was implemented, using three routes for testing. The results of the system implementation were satisfactory, obtaining an average coverage of 60.4% of the routes in the final field tests through LoRa communication. For the remaining 39.6% of the routes, location data prediction was used, with an average accuracy of 177 m with respect to the real location. Considering the obtained results, a tracking system such as the one proposed in this article can be used in the transit systems of medium-sized cities in developing countries to improve service quality and fleet control.
<i>Background:</i> The Middle Corridor, a transport route from Asia to Europe that also facilitates major energy projects through the Caspian Sea and its surrounding countries, has gained even more attention after the intensification of the conflict in Ukraine in 2022. <i>Methods:</i> On the basis of major scientific papers on the topic, foreign policy addresses from <i>The Diplomat</i> and studies by the <i>United Nations and Asian Development Bank Institute</i>, a framework with five aspects was created. In addition, two interviews with sector stakeholders were conducted to apply the framework and determine the relevance of the route to Finnish and Estonian economies. <i>Results:</i> A multifaceted overview of the current economic, political, and infrastructural state of the Trans-Caspian trade route is given. The practical value of the article lies in creating a framework for evaluating the route for related economies and testing this out for the Finnish and Estonian economies. <i>Conclusions:</i> Despite the challenges, there are enormous opportunities in this logistics route, especially with the restrictions facing Russia due to western bloc sanctions. Finland and Estonia, however, are suffering under the effects of war in Ukraine and the related sanctions, which has hindered the capacity to further enhance development projects.
Transportation and communication, Management. Industrial management