Search Results (101)

As electric multiple unit (EMU) operations and maintenance demands have expanded, spare parts supply chain management has become increasingly crucial. This study emphasizes the supply challenges of EMU spare parts, including inadequate minimum inventory levels and prolonged response times. Redesigning the OEM–railway bureau vendor-managed inventory (VMI) model contract incentive and penalty system is the key goal. Connecting the spare parts supply system with its characteristics yields a game theory model. This study analyzes and compares the equilibrium strategies and profits of supply chain members under different mechanisms for managing critical spare parts. The findings demonstrate that mechanism contracts can enhance supply chain performance in a Pareto-improving manner. An in-depth analysis of downtime loss costs, procurement challenges, and order losses reveals their effects on supply chain coordination and profit allocation, providing railway bureaus and OEMs with a theoretical framework for supply chain decision-making. This study offers theoretical justification and a framework for decision-making on cooperation between OEMs and railroad bureaus in the management of spare parts supply chains, particularly for extensive EMU operations. Full article

Modern industrial ecosystems, particularly those embracing Industry 4.0, increasingly depend on coherent optical networks operating at 400 Gbps and beyond. These high-capacity infrastructures, coupled with advanced digital signal processing and phase-sensitive detection, enable real-time data exchange for automated manufacturing, robotics, and interconnected factory systems. However, they introduce multilayer security challenges—ranging from hardware synchronization gaps to protocol overhead manipulation. Moreover, the rise of large-scale quantum computing intensifies these threats by potentially breaking classical key exchange protocols and enabling the future decryption of stored ciphertext. In this paper, we present a systematic vulnerability analysis of coherent optical networks that use OTU4 framing, Media Access Control Security (MACsec), and 400G ZR+ transceivers. Guided by established risk assessment methodologies, we uncover critical weaknesses affecting management plane interfaces (e.g., MDIO and I²C) and overhead fields (e.g., Trail Trace Identifier, Bit Interleaved Parity). To mitigate these risks while preserving the robust data throughput and low-latency demands of industrial automation, we propose a post-quantum security framework that merges spectral phase masking with multi-homodyne coherent detection, strengthened by quantum key distribution for key management. This layered approach maintains backward compatibility with existing infrastructure and ensures forward secrecy against quantum-enabled adversaries. The evaluation results show a substantial reduction in exposure to timing-based exploits, overhead field abuses, and cryptographic compromise. By integrating quantum-safe measures at the optical layer, our solution provides a future-proof roadmap for network operators, hardware vendors, and Industry 4.0 stakeholders tasked with safeguarding next-generation manufacturing and engineering processes. Full article

While digital transformation in e-commerce receives the most publicity, applications in energy and water utilities have been ongoing for decades. Using a methodology based on a systematic review, the paper offers a model of how it occurs in water utilities, reviews experiences from the field, and derives lessons learned to create a road map for future research and implementation. Innovation in water utilities occurs more in the field than through organized research, and utilities share their experiences globally through networks such as water associations, focus groups, and media outlets. Their digital transformation journeys are evident in business practices, operations, and asset management, including methods like decision support systems, SCADA systems, digital twins, and process optimization. Meanwhile, they operate traditional regulated services while being challenged by issues like aging infrastructure and workforce capacity. They operate complex and expensive distribution systems that require grafting of new controls onto older systems with vulnerable components. Digital transformation in utilities is driven by return on investment and regulatory and workforce constraints and leads to cautious adoption of innovative methods unless required by external pressures. Utility adoption occurs gradually as digital tools help utilities to leverage system data for maintenance management, system renewal, and water loss control. Digital twins offer the advantages of enterprise data, decision support, and simulation models and can support distribution system optimization by integrating advanced metering infrastructure devices and water loss control through more granular pressure control. Models to anticipate water main breaks can also be included. With such advances, concerns about cyber security will grow. The lessons learned from the review indicate that research and development for new digital tools will continue, but utility adoption will continue to evolve slowly, even as many utilities globally are too stressed with difficult issues to adopt them. Rather than rely on government and academics for research support, utilities will need help from their support community of regulators, consultants, vendors, and all researchers to navigate the pathways that lie ahead. Full article

In this article, we explored how open-source software serves as a strategic enabler for safety and security in the digital transformation of logistics systems. Open source is examined across multiple dimensions, including transparency, community collaboration, digital sovereignty, and long-term infrastructure resilience. The analysis focuses on the logistics domain, where interoperability, critical infrastructure protection, and supply chain continuity are essential. Key elements of open-source development—such as modular architectures, legal and licensing frameworks, and peer-reviewed codebases—support rapid vulnerability management, increased transparency, and the creation of sustainable digital ecosystems. Emphasis is placed on the role of open-source models in strengthening institutional trust, reducing dependency on proprietary vendors, and enhancing responsiveness to cyber threats. Our findings indicate that open source is not merely a technical alternative, but a strategic decision with legal, economic, and political implications, shaping secure, sovereign, and adaptive digital environments—particularly in mission-critical sectors. Full article

This study identifies key drivers for ERP implementation in small- and medium-sized enterprises (SMEs) in Austro–Ecuador and examines their impact on operational efficiency, strategic adaptability, and digital transformation. Motivated by the limited empirical evidence on ERP adoption in Latin American SMEs, this research aims to provide Austro–Ecuadorian insights that contribute to innovation management practices in emerging economies. To identify the critical success factors (CSFs) influencing ERP implementation, a four-phase methodology was employed, encompassing a CSF literature review, data collection and case analysis from 55 SMEs, multiple correspondence analysis (MCA), and descriptive ERP analysis. Statistical analysis of the surveyed SMEs, primarily from manufacturing sectors, revealed that while a significant portion (37%) lacked ERP experience, 22.9% were in the process of implementing or actively using systems such as Oracle’s J.D. Edwards Enterprise One and SAP. The MCA highlighted ERP system configuration, vendor relationships, and user training as significant factors for successful ERP implementation, reported by 54.5% of the companies. Quadrant analysis further emphasized the influence of IT structure and legacy systems on implementation characteristics, with cluster analysis identifying three distinct groups of companies based on their ERP strategies. The findings underscore the importance of top management support, business process re-engineering, and external consultants for successful ERP adoption in SMEs, providing practical insights for optimizing innovation management in the digital era. Future research should investigate the long-term impacts of ERP systems on organizational performance and innovation sustainability. Full article

Cloud computing has the potential to accelerate the digital journey of railways. Railway systems are big and complex, involving a lot of parts, like trains, tracks, signaling systems, and control systems, among others. The application of cloud computing technologies in the railway industry has the potential to enhance operational efficiency, data management, and overall system performance. Cloud management is essential for complex systems, and the automation of management services can speed up the provisioning, deployment, and maintenance of cloud infrastructure and applications by enabling visibility across the environment. It can provide consistent and unified management over resource allocation, streamline security processes, and automate the monitoring of key performance indicators. Key railway cloud management challenges include the lack of open interfaces and standardization, which are related to the vendor lock-in problem. In this paper, we propose an approach to design the railway cloud resource management as a service. Based on typical use cases, the requirements to fault and performance management of the railway cloud resources are identified. The main functionality is designed as RESTful services. The approach feasibility is proved by formal verification of the cloud resource management models supported by cloud management application and services. The proposed approach is open, in contrast to any proprietary solutions and feature scalability and interoperability. Full article

The flash translation layer (FTL) in SSDs introduces logical-to-physical address mapping, but this mapping alters data layout, leading to performance degradation. This issue is particularly evident in the Linux swap subsystem. While SSDs offer higher performance than HDDs, traditional FTL-based SSDs fail to meet swap performance expectations due to scattered page placement. The introduction of zoned namespace (ZNS) SSDs aims to address this problem by enforcing sequential writes within predefined zones, allowing hosts to directly manage physical data layout and garbage collection. Prior work leveraged this capability to enhance swap performance but introduced severe hardware dependencies, requiring specific logical block addressing (LBA) formats and vendor-specific firmware modifications. To overcome these limitations, we propose ZNSage, a hardware-agnostic swap subsystem for ZNS SSDs. Unlike prior work, ZNSage eliminates hardware dependencies by storing logical-to-physical mapping information in system memory, enabling compatibility with any ZNS SSD. ZNSage not only improves swap performance but also optimizes garbage collection by minimizing page faults during swap zone reclamation. Ultimately, ZNSage provides a generalized and efficient swap solution for next-generation storage architectures. Full article

Open Radio Access Networks (ORANs) are transforming the traditional telecommunications landscape by offering more flexible, vendor-independent solutions. Unlike previous systems, which relied on rigid, vertical configurations, ORAN introduces network programmability that is AI-driven and horizontally scalable. This shift is facilitated by modern container orchestrators, such as Kubernetes and Red Hat OpenShift, which simplify the development and deployment of components such as gNB, CU/DU, and RAN Intelligent Controllers (RICs). While these advancements help reduce costs by enabling shared infrastructure, they also create new challenges in meeting ORAN’s stringent latency requirements, especially when managing large-scale xApp deployments. Near-RTRICs are responsible for controlling xApps that must adhere to tight latency constraints, often less than one second. Current orchestration methods fail to meet these demands, as they lack the required scalability and long latencies. Additionally, non-API-based E2AP (over SCTP) further complicates the scaling process. To address these challenges, we introduce ORAN-HAutoscaling, a framework designed to enable horizontal scaling through Kubernetes. This framework ensures that latency constraints are met while supporting large-scale xApp deployments with optimal resource utilization. ORAN-HAutoscaling dynamically allocates and distributes xApps into scalable pods, ensuring that central processing unit (CPU) utilization remains efficient and latency is minimized, thus improving overall performance. Full article

The satisfaction of users is important for the success of government information systems. According to a satisfaction survey of X city’s Road Excavation Management Information System with 221 valid questionnaires in 2023 in Taiwan, however, the rate of those who were dissatisfied and felt a lack of systematical enhancement reached 20.81%. In this case, the reason for user dissatisfaction and the related aspects of user dissatisfaction must be discussed. Quality played an important role in influencing user satisfaction. Information, system, and service qualities have been ignored in the past. Yet, few studies have explored the application of these qualities to evaluate the context of government information systems. Government information systems in Taiwan have multiple stakeholders: the authorities concerned (i.e., government agencies), outsourcing contractors (i.e., IT vendors), and users (i.e., public infrastructure pipeline units). In this study, an e-service quality conceptual model and an information system success model were constructed to explore the differences in the quality of government information systems. We identified reasons for dissatisfaction. Using the Analytic Hierarchy Process, we analyzed the data of expert questionnaire surveys. The results showed that the authorities prioritized information quality, the outsourcing contractors prioritized system quality, and the public prioritized service quality. Full article

Internet of Things (IoT) devices are ubiquitous in various applications, such as smart homes, asset and people tracking, and city management systems. However, their deployment in adverse conditions, including unstable internet connectivity and power sources, present new cybersecurity challenges through new attack vectors. The LoRaWAN protocol, with its open and distributed network architecture, has gained prominence as a leading LPWAN solution, presenting novel security challenges. This paper proposes the implementation of machine learning algorithms, specifically the K-Nearest Neighbours (KNN) algorithm, within an Intrusion Detection System (IDS) for LoRaWAN networks. Through behavioural analysis based on previously observed packet patterns, the system can detect potential intrusions that may disrupt critical tracking services. Initial simulated packet classification attained over 90% accuracy. By integrating the Suricata IDS and extending it through a custom toolset, sophisticated rule sets are incorporated to generate confidence metrics to classify packets as either presenting an abnormal or normal behaviour. The current work uses third-party multi-vendor sensor data obtained in the city of Lisbon for training and validating the models. The results show the efficacy of the proposed technique in evaluating received packets, logging relevant parameters in the database, and accurately identifying intrusions or expected device behaviours. We considered two use cases for evaluating our work: one with a more traditional approach where the devices and network are static, and another where we assume that both the devices and the network are mobile; for example, when we need to report data back from sensors on a rail infrastructure to a mobile LoRaWAN gateway onboard a train. Full article

An advanced IoT-based Liquefied Petroleum Gas (LPG) cylinder monitoring and safety system is presented in this work. The proposed technique provides continuous monitoring of residential gas usage and detects any potential leakage. It utilizes an MQ135 gas sensor for gas leakage detection, a load cell to monitor the weight of the cylinder, and a DHT22 sensor for temperature sensing. The sensors are mounted on a customized trolley for domestic LPG cylinders. All the sensors are connected to a NodeMCU microcontroller, which exchanges sensor data with a cloud platform using HTTP GET and POST methods to transmit the data to a cloud-based MySQL database. Unlike other existing methods, the proposed approach does not necessitate any modifications to the existing setup, which includes the gas cylinder, regulating valve, and distribution pipe. Furthermore, a mobile application that emphasizes the needs of the user is developed to enable a wider range of functionalities using cloud data collected from the sensors. The software facilitates the real-time monitoring of gas levels, provides comprehensive usage records for daily, weekly, and monthly intervals, issues immediate alarms in the event of gas leakage and low gas levels, and detects any unauthorized movement of the LPG cylinder, such as theft. The proposed technique not only improves user safety but also streamlines gas cylinder management with predictive analytics based on gas consumption trends and projected days of usage. Moreover, the application includes functionality that automatically orders a new cylinder with the vendor when the gas level drops below a predetermined threshold, therefore ensuring continuous availability of gas supply. Full article

The motivation for this work arose when noticing that definitions of honeypots’ interaction level are mainly based on the information technology environment and do not reflect operational technology even if several honeypot projects approach this field. Within operational technology, programmable logic controllers (PLCs) have a main role, resulting in several honeypot researchers choosing to mimic this device at a certain interaction level. However, searching for an interaction level definition that approaches PLCs results in few studies. In this context, this work aims to explore how to adapt the information technology definition of the interaction level in order to encompass PLCs and their specific features. The method chosen to obtain inputs was a literature review where, in attempting to keep the connection with information technology, the features were based in terms of honey system, honey service, and honey token. The findings of this review provide a means to translate these terms when developing a PLC honeypot for a desired interaction level, resulting in a metrics proposal for low and high interaction. Summarizing the proposed metrics, the system of a PLC can be considered as the vendor specific firmware, its unique device banner, and a realistic network topology. For services, a PLC honeypot reflects the tasks performed by the real device, thus resulting in industrial communication protocols, network management protocols, appropriate response times, code-related interactions, dynamic input and output data processing, physical process simulation, and web interface. Lastly, a PLC honey token can be approached with the PLC program file, MIB file, and software license, among other elements. Based on these metrics, researchers can better evaluate how to design a programmable logic controller honeypot or select tools that match their target interaction level. Full article

Background: Traditional procurement and price negotiation methods in public hospitals in Thailand involve group purchasing agreements and bulk orders, posing challenges to improving inventory management efficiency. The vendor-managed inventory (VMI) model is a promising alternative for enhancing hospital performance, especially during crises. This study aimed to assess the potential cost savings in implementing VMI in a large general hospital in Thailand. Methods: A simulation modeling approach was used to compare the current inventory system with three VMI models: VMI1, focused on improving inventory turnover rate (ITR); VMI2, emphasized frequent replenishment with a 1-month supply; and VMI3, eliminated safety stock. Results: The results demonstrated significant cost savings, with potential reductions in total inventory management expenses. Specifically, VMI1 improved ITR from 6.31 to 7.76, reducing average inventory by 36% and cutting management costs by 40%. VMI2, with an ITR of 12.80, reduced inventory by 44% and saved 47% in management costs, while VMI3 achieved a 70% reduction in inventory and a 69% saving in management costs. Conclusions: This study highlights the VMI’s transformative potential in hospital inventory management, demonstrating significant cost savings. However, in the public sector, the feasibility of procurement regulations requires further exploration. Full article

Background/Objectives: Radiography is an essential and low-cost diagnostic method in pulmonary medicine that is used for the early detection and monitoring of lung diseases. An adequate and consistent image quality (IQ) is crucial to ensure accurate diagnosis and effective patient management. This pilot study evaluates the feasibility and effectiveness of the International Atomic Energy Agency (IAEA)’s remote and automated quality control (QC) methodology, which has been tested in multiple imaging centers. Methods: The data, collected between April and December 2022, included 47 longitudinal data sets from 22 digital radiographic units. Participants submitted metadata on the radiography setup, exposure parameters, and imaging modes. The database comprised 968 exposures, each representing multiple image quality parameters and metadata of image acquisition parameters. Python scripts were developed to collate, analyze, and visualize image quality data. Results: The pilot survey identified several critical issues affecting the future implementation of the IAEA method, as follows: (1) difficulty in accessing raw images due to manufacturer restrictions, (2) variability in IQ parameters even among identical X-ray systems and image acquisitions, (3) inconsistencies in phantom construction affecting IQ values, (4) vendor-dependent DICOM tag reporting, and (5) large variability in SNR values compared to other IQ metrics, making SNR less reliable for image quality assessment. Conclusions: Cross-comparisons among radiography systems must be taken with cautious because of the dependence on phantom construction and acquisition mode variations. Awareness of these factors will generate reliable and standardized quality control programs, which are crucial for accurate and fair evaluations, especially in high-frequency chest imaging. Full article

There are calls in the extant literature for further exploration into the factors influencing customer satisfaction in industrial vending solutions (IVS), a distinct vendor-managed inventory method. This study delves into these factors, identifying primary drivers of satisfaction, perceptions of service quality, and indicators of trust and commitment in B2B IVS. It examines how IVS execution impacts perceived service quality through in-depth semi-structured interviews with B2B customers, focusing on efficiency, user-friendliness, and timeliness as key satisfaction drivers. Trust in the customer–supplier relationship positively affects commitment to the supplier. Successful IVS implementation enhances inventory control, customer service, and cost management. Supply chain managers can use these insights to evaluate vending solutions. Future research could explore supplier perceptions of vendor-managed inventory (VMI) success and conduct larger quantitative studies. This study distinguishes itself by focusing on the primary drivers of customer satisfaction and the perception of service quality in B2B IVS environments. It offers a conceptual framework for managing customer satisfaction, product development, and marketing strategies in IVS, addressing a gap in the literature on IVS within VMI contexts. Full article