Hasil untuk "Transportation and communication"

Lu Yu, Zheng Chang, Ying-Chang Liang

Vehicular edge intelligence (VEI) is vital for future intelligent transportation systems. However, traditional centralized learning in dynamic vehicular networks faces significant communication overhead and privacy risks. Split federated learning (SFL) offers a distributed solution but is often hindered by substantial communication bottlenecks from transmitting high-dimensional intermediate features and can present label privacy concerns. Semantic communication offers a transformative approach to alleviate these communication challenges in SFL by focusing on transmitting only task-relevant information. This paper leverages the advantages of semantic communication in the design of SFL, and presents a case study the semantic communication-enhanced U-Shaped split federated learning (SC-USFL) framework that inherently enhances label privacy by localizing sensitive computations with reduced overhead. It features a dedicated semantic communication module (SCM), with pre-trained and parameter-frozen encoding/decoding units, to efficiently compress and transmit only the task-relevant semantic information over the critical uplink path from vehicular users to the edge server (ES). Furthermore, a network status monitor (NSM) module enables adaptive adjustment of the semantic compression rate in real-time response to fluctuating wireless channel conditions. The SC-USFL framework demonstrates a promising approach for efficiently balancing communication load, preserving privacy, and maintaining learning performance in resource-constrained vehicular environments. Finally, this paper highlights key open research directions to further advance the synergy between semantic communication and SFL in the vehicular network.

Haythem Hayouni, Leila Nasraoui

Internet of Things (IoT) has brought unprecedented opportunities across various sectors, including healthcare, transportation, industrial automation, and smart cities. However, this expansion has also introduced significant security vulnerabilities due to the heterogeneous nature, limited computational capabilities, and large-scale deployment of IoT devices. Detecting anomalies, which often signify security breaches or system malfunctions, is crucial to maintaining the integrity and reliability of IoT systems. Traditional anomaly detection methods, typically rule based or signature driven, struggle to adapt to evolving threats and diverse data patterns in IoT networks. This paper proposes a novel architecture named NAIIDS4IoT (Novel Artificial Intelligence-based Intrusion Detection System architecture for IoT), designed to provide efficient, accurate, and scalable anomaly detection using Artificial Intelligence. The core of NAIIDS4IoT lies in the integration of federated learning with deep autoencoders, enabling decentralized model training across edge devices without sharing raw data, thereby preserving user privacy and reducing communication overhead. Each edge node independently learns patterns of normal behavior and identifies anomalies based on reconstruction errors. A global model is continuously refined through collaborative learning across nodes. Furthermore, NAIIDS4IoT incorporates lightweight encryption and blockchain based model integrity verification to enhance security and trust in the detection process. Experimental validation using real-world IoT datasets demonstrates that NAIIDS4IoT achieves high detection accuracy, low false positive rates, and strong adaptability to dynamic environments, significantly outperforming conventional centralized and shallow learning based solutions. This architecture represents a significant step toward intelligent, autonomous, and privacy-preserving anomaly detection in next generation IoT ecosystems.

Samnang Um, Channnarong Phan, Daraden Vang et al.

Breast cancer incidence is increasing globally, and it is the third leading cause of morbidity and mortality among women in Cambodia. This study explores how access to digital tools, media exposure, transportation, travel time to health facilities, and autonomy in health decisions relate to breast cancer screening among Cambodian women aged 15-49. The study used nationally representative, cross-sectional data from the Cambodia Demographic and Health Survey (CDHS) 2021-2022. After excluding 204 women who were unaware of breast or cervical cancer screening, the final weighted sample comprised 19,292 participants. The outcome was whether a woman had ever received a breast examination from a healthcare provider, encompassing clinical breast examinations (CBEs) and imaging techniques, such as mammograms. Multivariable logistic regression, adjusted for demographic and socioeconomic characteristics, was used. Only 10.9% (95% CI: 9.7%-11.6%) of women had undergone a breast exam. Exposure to multiple forms of media was associated with a higher odds of screening (AOR = 1.47; 95% CI: 1.13-1.91). Phone ownership-both non-smartphone (AOR = 1.35; 95% CI: 1.03-1.78) or smartphone (AOR = 1.37; 95% CI: 1.03-1.82)-was also positively associated. In contrast, longer travel times of over 30 minutes (AOR = 0.55; 95% CI: 0.39-0.78) and a lack of autonomy in healthcare decisions (AOR = 0.70; 95% CI: 0.52-0.94) were associated with reduced screening. Wealthier women had greater odds of being screened (AOR = 1.86; 95% CI: 1.40-2.48). These findings highlight the need for health initiatives that use digital communication to reach and emphasize the importance of improving transportation, and support women's decision-making to increase screening rates in Cambodia.

Juan Gabriel França Canon, Robério José Rogério dos Santos, Victor Diogho Heuer de Carvalho et al.

<i>Background</i>: Logistics and supply chain management are crucial in modern commerce, impacting global competition, and both can directly benefit by using enterprise resource planning (ERP) systems. This case study examines key success factors behind a significant operational transformation in a company in the countryside of Alagoas, Brazil. From this context, two research questions emerge: (a) What are the main success factors that drove a significant operational transformation in logistics and supply chain management, and how did these factors impact the company’s growth? (b) How does digital transformation and adopting an ERP impact the company’s logistics activities? <i>Methods</i>: Data were collected through on-site observations, interviews with supervisors and a manager, and analysis of company-provided documentation. <i>Results</i>: The study identified key processes, stakeholders, and practices, focusing on critical success factors, mission-critical processes, and the integration of core and support functions. Notable changes were observed through key logistics performance indicators, tracking the evolution from pre-implementation to post-implementation and revealing their impact on the company’s growth. <i>Conclusions</i>: Improved decision making between departments significantly enhanced performance and growth. The analyzed company’s success can be attributed to a process-oriented approach, digital transformation in logistics, and investment in information technology.

Aparna G. Kachoria, Hiba Fatima, Alexandra F. Lightfoot et al.

Abstract Background Pregnancy related hypertension is a leading cause of preventable maternal morbidity and mortality in the US, with consistently higher rates affecting racial minorities. Many complications are preventable with timely treatment, in alignment with the Alliance for Innovation on Maternal Health’s Patient Safety Bundle (“Bundle”). The Bundle has been implemented successfully in inpatient settings, but 30% of preeclampsia-related morbidity occurs in outpatient settings in North Carolina. To address this, we have integrated community engagement and implementation science approaches to identify facilitators and barriers to Bundle implementation, which supports its adaptation for outpatient settings and identifies implementation strategies to be tested in a subsequent study. Methods Eleven key informant interviews were conducted across three clinics to assess the implementation needs for effectively utilizing the Bundle. The interview guide was created using the Consolidated Framework for Implementation Research domains to identify facilitators and barriers to implementation. Additionally, three focus group discussions with patient participants were conducted to understand lived experiences and perceptions of respectful care. A coalition of community partners, patients, providers, those with lived experience, and the research team reviewed materials from the formative study design to dissemination and planning for future study. Results Barriers included inadequate provider-patient interaction time, patients’ lack of transportation to access care, limited protocols to inform/assess/treat/escalate patients, and workforce capacity (staff training and turnover). Facilitators included staff recognition of the importance of treating preeclampsia, champion buy-in of the Bundle’s ability to improve outcomes, co-location of pharmacies for immediate treatment, and staff capacity. Respectful care principles were repeatedly identified as a facilitator for Bundle implementation, specifically for patient awareness of preeclampsia complications and treatment adherence. Conclusions Findings highlight the importance of community-engaged approaches. Further, clinic staff regarded Bundle implementation as crucial for the outpatient setting. Identified barriers suggest that strategies should address systemic social supports (i.e., transportation, childcare) and improve access to and use of home blood pressure monitoring. Identified facilitators support improving communication, increasing clinic champion engagement, enabling systems for identifying at-risk patients, and training staff on accurate blood pressure measurement. Successful Bundle implementation requires addressing systemic barriers to delivering respectful care, such as limited time with patients.

Faisal Alshammari, Abdullah Alsaleh

Abstract The Internet of Vehicles (IoV) has emerged as a transformative technology for intelligent transportation systems, enabling real-time communication between vehicles, infrastructure and external networks. However, this connectivity also introduces significant cybersecurity risks, such as spoofing, injection and denial of service (DoS) attacks, which threaten operational safety and system reliability. To address these challenges, this study proposes the adaptive CNN-based intrusion detection system (ACIDS), a robust and scalable framework designed to enhance intrusion detection in IoV environments. ACIDS integrates convolutional neural networks (CNN) for hierarchical feature extraction, the synthetic minority over-sampling technique (SMOTE) to address class imbalance and an open-set classification framework to detect novel attack patterns. The model was evaluated on the AWID dataset, achieving an accuracy of 94%, a perfect detection rate of 100% and a low false alarm rate of 3%. Additional validation on the NSL-KDD dataset confirmed its generalizability, with an accuracy of 91.7% and a detection rate of 98.3%. These results significantly outperform baseline models, including support vector machines (SVM) and random forests (RF), as well as recent methods such as transformer-based and hybrid RNN-CNN approaches. Key parameters used for benchmarking include accuracy, detection rate, false alarm rate, precision, F1-Score and AUC-ROC, demonstrating the model’s balanced performance and computational efficiency. By addressing critical issues such as class imbalance, adaptability to novel threats and real-time scalability, ACIDS offers a practical solution for securing IoV systems. Its low computational overhead and ability to operate on resource-constrained edge devices further emphasize its suitability for real-world deployments.

Zhiying Song, Tenghui Xie, Fuxi Wen et al.

Cooperative perception extends the perception capabilities of autonomous vehicles by enabling multi-agent information sharing via Vehicle-to-Everything (V2X) communication. Unlike traditional onboard sensors, V2X acts as a dynamic "information sensor" characterized by limited communication, heterogeneity, mobility, and scalability. This survey provides a comprehensive review of recent advancements from the perspective of information-centric cooperative perception, focusing on three key dimensions: information representation, information fusion, and large-scale deployment. We categorize information representation into data-level, feature-level, and object-level schemes, and highlight emerging methods for reducing data volume and compressing messages under communication constraints. In information fusion, we explore techniques under both ideal and non-ideal conditions, including those addressing heterogeneity, localization errors, latency, and packet loss. Finally, we summarize system-level approaches to support scalability in dense traffic scenarios. Compared with existing surveys, this paper introduces a new perspective by treating V2X communication as an information sensor and emphasizing the challenges of deploying cooperative perception in real-world intelligent transportation systems.

Hai Dinh-Tuan, Sandro Rodriguez Garzon, Jianeng Fu

In the evolving landscape of future mobile networks, there is a critical need for secure and trustful communication modalities to support dynamic interactions among core network components of different network domains. This paper proposes the application of W3C-endorsed Decentralized Identifiers (DIDs) to establish secure and trustful communication channels among network functions in 5G and subsequent generations. A new communication agent is introduced that integrates seamlessly with 5G-standardized network functions and utilizes a DID-based application layer transport protocol to ensure confidentiality, integrity, and authenticity for cross-domain interactions. A comparative analysis of the two different versions of the DID-based communication protocol for inter network function communication reveals compatibility advantages of the latest protocol iteration. Furthermore, a comprehensive evaluation of the communication overhead caused by both protocol iterations compared to traditional TCP/TLS shows the benefits of using DIDs to improve communication security, albeit with performance loses compared to TCP/TLS. These results uncover the potential of DID-based communication for future mobile networks but also point out areas for optimization.

Ventseslav Yordanov, Simon Schäfer, Alexander Mann et al.

While current onboard state estimation methods are adequate for most driving and safety-related applications, they do not provide insights into the interaction between tires and road surfaces. This paper explores a novel communication concept for efficiently transmitting integrated wheel sensor data from an ESP32 microcontroller. Our proposed approach utilizes a publish-subscribe system, surpassing comparable solutions in the literature regarding data transmission volume. We tested this approach on a drum tire test rig with our prototype sensors system utilizing a diverse selection of sample frequencies between 1 Hz and 32 000 Hz to demonstrate the efficacy of our communication concept. The implemented prototype sensor showcases minimal data loss, approximately 0.1 % of the sampled data, validating the reliability of our developed communication system. This work contributes to advancing real-time data acquisition, providing insights into optimizing integrated wheel sensor communication.

Eduardo Fernandes Montesuma, Adel El Habazi, Fred Ngole Mboula

Detecting anomalies in datasets is a longstanding problem in machine learning. In this context, anomalies are defined as a sample that significantly deviates from the remaining data. Meanwhile, optimal transport (OT) is a field of mathematics concerned with the transportation, between two probability measures, at least effort. In classical OT, the optimal transportation strategy of a measure to itself is the identity. In this paper, we tackle anomaly detection by forcing samples to displace its mass, while keeping the least effort objective. We call this new transportation problem Mass Repulsing Optimal Transport (MROT). Naturally, samples lying in low density regions of space will be forced to displace mass very far, incurring a higher transportation cost. We use these concepts to design a new anomaly score. Through a series of experiments in existing benchmarks, and fault detection problems, we show that our algorithm improves over existing methods.

Jiakun Yan, Marc Snir

The evolution of architectures, programming models, and algorithms is driving communication towards greater asynchrony and concurrency, usually in multithreaded environments. We present LCI, a communication library designed for efficient asynchronous multithreaded communication. LCI provides a concise interface that supports common point-to-point primitives and diverse completion mechanisms, along with flexible controls for incrementally fine-tuning communication resources and runtime behavior. It features a threading-efficient runtime built on atomic data structures, fine-grained non-blocking locks, and low-level network insights. We evaluate LCI on both Infiniband and Slingshot-11 clusters with microbenchmarks and two application-level benchmarks. Experimental results show that LCI significantly outperforms existing communication libraries in various multithreaded scenarios, achieving performance that exceeds the traditional multi-process execution mode and unlocking new possibilities for emerging programming models and applications. LCI is open-source and available at https://github.com/uiuc-hpc/lci.

Georg Finger, Gunnar Prause

Maria Mercedes Rossi, Heidi L. Radunovich, Michelle A. Parisi

Abstract Background Access to mental and physical healthcare in rural areas is challenging for Veterans and their families but essential for good health. Even though recent research has revealed some of the challenges rural Veterans face accessing healthcare, a complete understanding of the gap in access is still unclear. Methods This qualitative study aimed to explore participants’ perceptions of healthcare access. Structured interviews were conducted with 124 Veterans and spouses of Veterans from rural qualifying counties in South Carolina and Florida. Results The study’s results revealed five main dimensions of access: geographic proximity, transportation, communication, cultural competence, and resources. Distance to service needed can negatively impact access for Veterans and their families in general, especially for those whose health is declining or who cannot drive because of their age. Lack of transportation, problems with transportation services, and lack of public transportation can lead to delays in care. Additionally, the lack of communication with the Veterans Affairs (VA) Health System and with the healthcare team, as well as inefficient communication among the healthcare team, lack of coordination of care between the VA health system and community providers, and the lack of cultural competence of healthcare providers and contracted personnel made access to services even more challenging. Conclusions Improving communication can help to develop a sense of trust between Veterans and the VA, and between Veterans and spouses with the healthcare team. It can also lead to increased patient satisfaction. Ensuring healthcare providers and contracted personnel are culturally competent to talk and treat Veterans can improve patient trust and adherence to treatment. Lastly, resource-related challenges included financial problems, lack of prompt access to appointments, lack of providers, limited access to local clinics and hospitals, limited local programs available, and reimbursement issues.

Marlene Mellum, Raika Saei, Guttorm Brattebø et al.

Abstract Background Recent research has indicated that sex is an important determinant of emergency medical response in patients with possible serious injuries. Men were found to receive more advanced prehospital treatment and more helicopter transportation and trauma centre destinations and were more often received by an activated trauma team, even when adjusted for injury mechanism. Emergency medical dispatchers choose initial resources when serious injury is suspected after a call to the emergency medical communication centre. This study aimed to assess how dispatchers evaluate primary responses in trauma victims, with a special focus on the sex of the victim. Methods Emergency medical dispatchers were interviewed using focus groups and a semistructured interview guide developed specifically for this study. Two vignettes describing typical and realistic injury scenarios were discussed. Verbatim transcripts of the conversations were analysed via systematic text condensation. The findings were reported in accordance with the Consolidated Criteria for Reporting Qualitative Studies (COREQ) checklist. Results The analysis resulted in the main category “Tailoring the right response to the patient”, supported by three categories “Get an overview of location and scene safety”, “Patient condition” and “Injury mechanism and special concerns”. The informants consistently maintained that sex was not a relevant variable when deciding emergency medical response during dispatch and claimed that they rarely knew the sex of the patient before a response was implemented. Some of the participants also raised the question of whether the Norwegian trauma criteria reliably detect serious injury in women. Conclusions The results indicate that the emergency medical response is largely based on the national trauma criteria and that sex is of little or no importance during dispatch. The observed sex differences in the emergency medical response seems to be caused by other factors during the emergency medical response phase.

Tilahun M. Getu, Georges Kaddoum, Mehdi Bennis

Although many proposals have been developed for the sixth-generation (6G) technology, realizing 6G is fraught with numerous fundamental interdisciplinary, multidisciplinary, and transdisciplinary challenges. To mitigate some of these challenges, goal-oriented semantic communication (SemCom) has emerged as a promising 6G technology enabler. This enabler employs only semantically-relevant information for successful task execution while minimizing power usage, bandwidth consumption, and transmission delay. On the other hand, 6G is essential for realizing major goal-oriented SemCom use cases such as autonomous transportation. These paradigms of 6G for goal-oriented SemCom and goal-oriented SemCom for 6G call for a tighter integration of 6G and goal-oriented SemCom. To facilitate this purpose, this survey paper exposes the fundamental challenges of 6G; details the notion of goal-oriented SemCom and its state-of-the-art research landscape; presents state-of-the-art trends, use cases, and frameworks of goal-oriented SemCom; exposes the fundamental and major challenges of goal-oriented SemCom; and offers promising future research directions for goal-oriented SemCom. Consequently, this survey article stimulates numerous lines of research on goal-oriented SemCom theories, algorithms, and realization.

Feilong Wang, Xuegang Ban, Peng Chen et al.

Big mobility datasets (BMD) have shown many advantages in studying human mobility and evaluating the performance of transportation systems. However, the quality of BMD remains poorly understood. This study evaluates biases in BMD and develops mitigation methods. Using Google and Apple mobility data as examples, this study compares them with benchmark data from governmental agencies. Spatio-temporal discrepancies between BMD and benchmark are observed and their impacts on transportation applications are investigated, emphasizing the urgent need to address these biases to prevent misguided policymaking. This study further proposes and tests a bias mitigation method. It is shown that the mitigated BMD could generate valuable insights into large-scale public transit systems across 100+ US counties, revealing regional disparities of the recovery of transit systems from the COVID-19. This study underscores the importance of caution when using BMD in transportation research and presents effective mitigation strategies that would benefit practitioners.

Rajat Verma, Mithun Debnath, Shagun Mittal et al.

Locational measures of accessibility are widely used in urban and transportation planning to understand the impact of the transportation system on influencing people's access to places. However, there is a considerable lack of measurement standards and publicly available data. We propose a generalized measure of locational accessibility that has a comprehensible form for transportation planning analysis. This metric combines the cumulative opportunities approach with gravity-based measures and is capable of catering to multiple trip purposes, travel modes, cost thresholds, and scales of analysis. Using data from multiple publicly available datasets, this metric is computed by trip purpose and travel time threshold for all block groups in the United States, and the data is made publicly accessible. Further, case studies of three large metropolitan areas reveal substantial inefficiencies in transportation infrastructure, with the most inefficiency observed in sprawling and non-core urban areas, especially for bicycling. Subsequently, it is shown that targeted investment in facilities can contribute to a more equitable distribution of accessibility to essential shopping and service facilities. By assigning greater weights to socioeconomically disadvantaged neighborhoods, the proposed metric formally incorporates equity considerations into transportation planning, contributing to a more equitable distribution of accessibility to essential services and facilities.

Elmenshawy Adham Ahmed Awad Elsayed, Alomar Iyad, Arshad Ali

The aim of this paper is to optimize turbine blade cooling channels by applying jet impingement Method. The selection of experiment data for NASA 3CX turbine blade, and 3D model using solidworks software and create computational fluid dynamics (CFD) simulations used to model the coolant flow and temperature distribution in the vane, while experimental testing can validate the CFD results and provide additional insights into the cooling system's performance., ANSYS FLUENT code was used as a CFD solver, and ANSYS ICEM-CFD was used for mesh generation. MATLAB code is used for calculation using experiment data and this was helpful for simulations. Heat transfer conjugation analysis bases SST shear stress analyses K-ω turbulent model. The results conclude that providing additional information about the cooling channels and how they differ in the studies being compared. The results demonstrate that the cooling channels' hydraulic diameter decreases by a significant percentage (up to 49.70%–69.55%) as they are drawn to the trailing edge of the blade. This can have a significant impact on the heat transfer coefficients and the performance of the cooling system. The pressure side of the turbine blade is observed to follow the Hylton Model, while the current study predicts a large over-anticipated heat transfer coefficient around the Turbine blade head and on the bulk of the suction side. In terms of average heat transfer coefficient, the two models differ by 23.36%. The authors found that the cooling effectiveness for the Optimized jet impingement model is 0.4892 for whole blade and compared it with the cooling effectiveness for the optimized jet impingement model, which is 0.6936, The results of the comparison between the base model and the optimized jet impingement model suggest that the optimized model has a significantly higher cooling effectiveness. The increase in cooling effectiveness of 29.46% for the whole blade and 28.823% for the trailing edge indicates that the optimized jet impingement design provides improved cooling performance. These results highlight the importance of considering optimized cooling designs for turbine blades to maintain efficient and safe operation.

T. Kim, O. Kryvtsov

The global air transportation market has tremendously changed over the past three years. Worldwide quarantine restrictions complicated the process of aeronautical communication both at the domestic and international levels. Lockdown resulted in a sharp decrease in the volume of world passenger traffic - a vital source of airport revenues. This article studied global airport revenues and classified airport services by type and revenues according to the sources of their receipt. The structure of aeronautical and non-aeronautical revenues was given, and the most common airport charges were characterized. The state and forecasts of world passenger air transportation volume during 2015-2025 and the impact of the COVID-19 pandemic on them were studied in this article. In particular, the way it redistributed shares of non-aeronautical revenues with an increase in the share of rental revenues. Attention to the impact of a full-scale Russian invasion of Ukraine on the global aviation industry was paid. The current forecasts for the recovery of the global air transportation market were studied. Analysis of the current state of aeronautical and non-aeronautical airport revenues allowed to identify possible strategies for increasing their volume under post-pandemic aeronautical market recovery conditions. Among the possible measures for airports, the following were highlighted: implementation of dynamic pricing based on demand and airport workload, using the diversification strategy for organizing income sources with a focus on non-aeronautical services and air cargo transportation. The importance of greening economic activity in the long term was noted to ensure the investment attraction of airports.

Ricardo Moreira da Silva, Guilherme Francisco Frederico, Jose Arturo Garza-Reyes

<i>Background:</i> Industry 4.0 is one of the topics related to manufacturing, supply chain and logistics that has received great interest from the academic community, organizations and governments in the last decade. <i>Problem statement:</i> Several published articles discuss and seek to conceptualize what the fourth industrial revolution is, but no research relates Industry 4.0 in the context of logistics service providers (LSPs) in a clear and structured way. <i>Objectives:</i> This study aims to fill this research gap, proposing a conceptual framework and addressing the challenges, barriers and organizational dimensions that need adaptation to insert LSPs in the new Industry 4.0 environment. <i>Methods:</i> This theoretical and conceptual study uses the Systematic Literature Review (SLR) as a research method to understand the Industry 4.0 phenomenon in the context of LSPs. <i>Contributions:</i> The relevant constructs identified in this research will help professionals and organizations that provide logistics services to develop strategies and encourage new research in the field of Industry 4.0 from the perspective of LSPs. <i>Results:</i> In addition, this research identified and generally consolidated six dimensions, as a result of this innovative study a conceptual framework is presented.