Search Results (44)

The emergence of Flexible Manufacturing Systems (FMS) presents new challenges in Industrial IoT (IIoT) environments. Unlike traditional real-time systems, FMS must accommodate task set variability driven by human–machine interaction. As such variations can lead to abrupt resource overload or idleness, a dynamic scheduling mechanism is required. Although prior studies have explored dynamic scheduling, they often relax deadlines for lower-criticality tasks, which is not well suited to IIoT systems with strict deadline constraints. In this paper, instead of treating dynamic scheduling as a prediction problem, we model it as deterministic planning in response to explicit, observable user input. To this end, we precompute feasible resource plans for anticipated task set variations through offline optimization and switch to the appropriate plan at runtime. During this process, our approach jointly optimizes processor speeds, memory allocations, and edge/cloud offloading decisions, which are mutually interdependent. Simulation results show that the proposed framework achieves up to 73.1% energy savings compared to a baseline system, 100% deadline compliance for real-time production tasks, and low-latency responsiveness for user-interaction tasks. We anticipate that the proposed framework will contribute to the design of efficient, adaptive, and sustainable manufacturing systems. Full article

In recent years, the healthcare market has grown very fast and is dealing with a huge increase in data. Healthcare applications are time-sensitive and need quick responses with fewer delays. Fog Computing (FC) was introduced to achieve this aim. It can be applied in various application areas like healthcare, smart and intelligent environments, etc. In healthcare applications, some tasks are considered critical and need to be processed first; other tasks are time-sensitive and need to be processed before their deadline. In this paper, we have proposed a Task Classification algorithm based on Deadline and Criticality (TCDC) for serving healthcare applications in a fog environment. It depends on classifying tasks based on the critical level to process critical tasks first and considers the deadline of the task, which is an essential parameter to consider in real-time applications. The performance of TCDC was compared with some of the literature. The simulation results showed that the proposed algorithm can improve the overall performance in terms of some QoS parameters like makespan with an improved ratio from 60% to 70%, resource utilization, etc. Full article

To address the insufficient bandwidth and message response delays in FlexRay dynamic segments within automotive communication networks, this study proposes an optimized message scheduling strategy based on the FlexRay dynamic segment (DSMSS). By holistically integrating multi-dimensional parameters—including message length, deadline, remaining processing time, and Automotive Safety Integrity Level (ASIL)—the strategy introduces a dynamic frame ID priority allocation mechanism. Leveraging dynamic programming, this approach systematically optimizes message transmission sequences. Furthermore, a new compensation scheduling method is proposed to prevent the continuous delay of low-priority messages and achieve priority transmission within the compensation period after high-priority tasks. Guided by ISO 26262 standards, electronic control units (ECUs) are classified, and an experimental platform simulating an automotive chassis control system is established using the FlexRay bus topology. The verification is performed using the CANoe.FlexRay simulation tool and the VN8970 hardware interface. The experimental results demonstrate that, compared to the conventional Earliest Deadline First (EDF) algorithm, the DSMSS strategy achieves a 28.1% improvement in bandwidth utilization and a 9.4% reduction in worst-case response time when transmitting 20 dynamic messages. This study addresses communication system asymmetry through balanced supply–demand scheduling, significantly enhancing real-time FlexRay performance and resource efficiency. The findings provide theoretical and technical foundations for designing efficient, robust communication architectures in intelligent connected vehicles, advancing practical solutions for bandwidth-constrained automotive networks. Full article

Background: Migrant construction workers involved in building infrastructure for mega-sporting events face elevated risks of illness and death. However, specific health outcomes for these workers have not been systematically reviewed, limiting opportunities to identify and address their challenges. Methods: This study systematically reviewed health outcomes among migrant construction workers involved in mega-sporting events. Results: 89 eligible studies involving 23,307 workers were identified. Of these, only 11 directly addressed specific health outcomes, including heat stress, occupational fatalities, and sexually transmitted infections. Notably, increased heat exposure during peak construction phases and the proximity of deadlines for mega-sporting events were correlated with elevated rates of occupational fatalities. Other key adverse factors impacting migrant construction workers’ health included an observed correlation between the timing of mega-sporting events and increased occupational fatalities, the involvement of labor recruiters, and shifting health and safety responsibilities among stakeholders (e.g., host states, event organizers, contractors, and recruitment agencies). Positive outcomes were observed when workers voluntarily engaged in non-mandatory safety activities, such as safety training programs and awareness meetings. Conclusions: There is a critical need for longitudinal and comparative studies to comprehensively examine the health of migrant workers throughout all stages of their journey, from pre-migration to return. This review underscores the urgency of prioritizing evidence-based policies that address unique health risks in this population, including mitigation of heat stress and enforcement of occupational safety standards, particularly amid construction spikes preceding mega-sporting events. Recommendations: Future research should prioritize understanding the unique health challenges faced by migrant workers to inform policy making, develop effective interventions, and implement best practices to improve their health and well-being. Full article

The aim of this work is to analyse the quality and transparency of data on the additional costs of public works. The problem identified is the lack of detailed and accessible information that allows for an adequate analysis of the performance and final state of public works, especially in relation to prices and deadlines. This is a case study carried out in Portugal, in which information from public works contracts with a closing date in 2022 was analysed. The data were extracted from the public access portal, responsible for making available and publishing information on the execution of public works contracts. The information was subjected to a statistical treatment process seeking to identify answers to transparency issues. The originality of this study lies in the quantitative and statistical approach applied to the evaluation of the transparency of the data made available on the portal, contributing to the debate on improving public management. The results indicate the need to expand the content available on the portal since the information provided does not allow for an analysis of the final state and performance of the works carried out, especially those relating to price and deadline, which in turn limits the construction of forecasting models and performance indicators. Corrective measures are proposed that include information that allows for answering questions about transparency and that allows for the construction and analysis of statistics and indicators, contributing to identifying the need for improvements in legislation, and the adoption of mechanisms that can improve, correct and or reinforce actions with an impact on the management of public resources. Full article

In the scheduling of hard real-time systems on multicore platforms, significant unpredictability arises from interference caused by shared hardware resources. The objective of this paper is to offer a schedulability analysis for such systems by assuming a general model that introduces interference as a time parameter for each task. The analysis assumes constrained deadlines and is provided for fixed priorities. It is based on worst-case response time analysis, which exists in the literature for monocore systems. We demonstrate that the worst-case response time is an upper bound, and we evaluate our proposal with synthetic loads and execution on a real platform. Full article

By pioneering a comprehensive analysis of lean integration within the construction sector, this research provides novel insights into optimizing project outcomes. The construction industry is generally known for its frequent deadline slip-ups, budget overruns, and issues with upholding proper quality. It is usual practice to integrate different management techniques which are successful in the production industry in order to avoid such issues. Several researchers adopted sustainable construction management, lean management and alliance contract practices individually on construction sites to improve the profit, productivity, quality and transparency of the project. In this study, the synergetic integration of sustainable construction management, lean management and alliance contract practices have been studied. A questionnaire survey was conducted among 345 practitioners, resulting in 309 responses after screening. These respondents, comprising various roles in the AEC sector, provided insights into their experience, project involvement, and business sectors. The study identified 23 factors associated with lean practices, sustainable construction, and alliance contracts, examining their relationships and benefits through Structural Equation Modeling (SEM). The results demonstrate significant effects of lean practice, sustainable construction, and alliance contract factors on the benefits derived from their integration. Measures of reliability and validity affirm the robustness of these relationships. The discussion underscores the benefits of integration, including enhanced efficiency, reduced environmental impact, improved collaboration, shared risk and reward, superior project outcomes, and competitive advantage. Overall, this research elucidates the potential advantages of integrating these methodologies within construction projects. Full article

RISC-V offers a modular technical approach combined with an open, royalty-free instruction set architecture (ISA). However, despite its advantages as a fundamental building block for many embedded systems, the escalating complexity and functional demands of real-time applications have made adhering to response time deadlines challenging. For real-time applications of RISC-V, real-time performance analysis is required for various ISAs. In this paper, we analyze the real-time performance of RISC-V through two real-time approaches based on processor architectures. For real-time operating system (RTOS) applications, we adopted FreeRTOS and evaluated its performance on HiFive1 Rev B (RISC-V) and STM3240G-EVAL (ARM M). For real-time Linux, we utilized Linux with the Preempt-RT patch and tested its performance on VisionFive 2 (RISC-V), MIO5272 (x86-64), and Raspberry Pi 4 B (ARM A). Through these experiments, we examined the response times on the real-time mechanisms of each operating system. Additionally, in the Preempt-RT experiments, scheduling latencies were evaluated by means of the cyclictest. These are very important parameters for implementing real-time applications comprised of multi-tasking. Finally, in order to show the real-time capabilities of RISC-V practically, we implemented motion control of a six-axis collaborative robot, which was performed on the VisionFive 2. This implementation provided a comparative result of RISC-V’s performance against the x86-64 architecture. Ultimately, the results indicated that the real-time performance of RISC-V for real-time applications was feasible. A noticeable achievement of this research is its first implementation of an EtherCAT master on RISC-V designed for real-time applications. The successful implementation of the EtherCAT master on RISC-V shows real-time capabilities for a wide range of real-time applications. Full article

The intelligent transportation system (ITS) relies heavily on the vehicular ad hoc network (VANET) and the internet of vehicles (IoVs), which combine cloud and fog to improve task processing capabilities. As a cloud extension, the fog processes’ infrastructure is close to VANET, fostering an environment favorable to smart cars with IT equipment and effective task management oversight. Vehicle processing power, bandwidth, time, and high-speed mobility are all limited in VANET. It is critical to satisfy the vehicles’ requirements for minimal latency and fast reaction times while offloading duties to the fog layer. We proposed a fuzzy logic-based task scheduling system in VANET to minimize latency and improve the enhanced response time when offloading tasks in the IoV. The proposed method effectively transfers workloads to the fog computing layer while considering the constrained resources of car nodes. After choosing a suitable processing unit, the algorithm sends the job and its associated resources to the fog layer. The dataset is related to crisp values for fog computing for system utilization, latency, and task deadline time for over 5000 values. The task execution, latency, deadline of task, storage, CPU, and bandwidth utilizations are used for fuzzy set values. We proved the effectiveness of our proposed task scheduling framework via simulation tests, outperforming current algorithms in terms of task ratio by 13%, decreasing average turnaround time by 9%, minimizing makespan time by 15%, and effectively overcoming average latency time within the network parameters. The proposed technique shows better results and responses than previous techniques by scheduling the tasks toward fog layers with less response time and minimizing the overall time from task submission to completion. Full article

For several decades, universities have sought to promote better mental health amongst students. For example, universities now have formal institutional arrangements to postpone deadlines for students where there are mitigating circumstances, such as ill health. Such provisions might be understood as praiseworthy cases of institutional compassion. But, empirical research is needed to investigate how these measures play out in practice. This paper draws on ethnographic research in several UK universities to explore the experiences of staff responsible for the enactment of mitigating circumstance provisions. We find staff members sympathetic to the aims of the measures but also sceptical, and in some cases angry, because they find that the provisions have unwanted and undesirable effects. This paper uses the wider social science literature on bureaucracy to consider why this might be the case and raises questions about the capacity of institutions to enact ethical ideals. Full article

Inland waterway transportation plays a pivotal role in advancing economic development and nurturing sustainable progress. It serves as a vital conduit linking communities, industries, and markets, thereby facilitating the seamless flow of essential commodities and fostering regional integration. However, in today’s era, marked by a resolute commitment to environmental responsibility and sustainability, inland shipping confronts formidable challenges, particularly pertaining to emission pollution and the escalating costs of fuel. These challenges represent significant impediments to the pursuit of environmentally conscious and sustainable growth by shipping companies. This research endeavor is geared towards the creation of a mathematical model that takes into account various factors, including the types of waterways, temporal constraints, and punctual arrival at the port of discharge. The primary objective is to empower shipping companies to make informed decisions about optimal sailing speeds and the most opportune time windows for entering one-way waterway segments. This, in turn, leads to reductions in fuel costs and waiting times for shipping companies, all while achieving cost minimization and mitigating emissions issues in inland waterway transportation. Ultimately, this research advances the cause of green and sustainable development in the inland waterway shipping sector. Specifically, this study focuses on routes that involve the dynamic transition between one-way and two-way segments. To accomplish this, an integer programming (IP) model is proposed to meticulously analyze the ideal sailing speed for each segment of the route and determine the optimal windows for accessing single-direction channels, thus representing a multistage decision-making process. Meanwhile, the model’s reliability is substantiated through a rigorous comparative assessment against three benchmark strategies (EAS, LAS, and MAS). In our experiments, the optimization model yielded a total cost for the entire inland waterway amounting to $80,626.20. This figure stands below the total costs of $87,118.14 under the EAS strategy and $83,494.70 under the MAS strategy (the LAS strategy failed to meet the port of discharge deadline), thereby conclusively validating its ability to guide vessels to their port of discharge within prescribed schedules, all while reducing overall operational costs and promoting sustainable and environmentally responsible practices. Full article

An IoT data system is a time constraint in which some data needs to be serviced on or before its deadline. Distributed processing is one of the most latent sources in such systems and is considered a vital design concern. Many sources of delay in the IoT can affect the availability of data from different resources, which may cause missing data deadlines, resulting in a catastrophic effect. In fact, such systems are inherently distributed in nature and use distributed processing. The distributed processing permits different nodes to obtain the information from remote sites, which may take a long time to access the required data. Therefore, it is considered one of the most latent sources in such systems, which is considered a vital design concern. The typical recommended solution for this problem is to commit distributed transactions locally. Therefore, replication techniques are used to enhance the availability of data and consequently avoid the resulting latency. However, the use of local processing raises inconsistent periods. Therefore, this study proposes a new synchronization framework to minimize periods of temporal inconsistency. It permits several connected nodes to synchronize the shared data on demand concurrently without any need to use distributed synchronization, which consumes the system resource and raises its delay cost. The proposed framework aims to enhance the timely response of IoT real-time systems by minimizing the temporal inconsistency periods. The results indicate that the synchronization framework can be completed within a reasonable time period. They also depict improved consistency by minimizing the temporal inconsistency duration and increasing the chance of meeting critical time requirements. Full article

Failure to meet the deadlines for the implementation of investment-construction projects is a problem in all countries of the world and leads to unstable activity of construction companies. This article studies the most important destabilizing factors affecting the main indicator of sustainable activity of construction companies, i.e., the duration of the implementation of an investment-construction projects. To determine and assess the impact of destabilizing factors on the duration of implementation of selected investment-construction projects, a survey was conducted in which a number of customers, consultants, and contractors involved in construction projects took part. Questionnaires developed on the basis of a cluster sample were sent to respondents, and 84 responses were received in response to the assessment of destabilizing factors. To analyze the received and grouped information, structural equation modeling using the Smart-PLS program was used. As a result of modeling, a number of results were obtained, the most important of which was the identification of the main reasons that lead to an average (20–50%) increase in the duration of projects in the construction sector. The most significant was the lack of an appropriate procurement program for materials; inefficient scheduling by contractors and instability of construction production, poor-quality processing of incoming information, and untimely decision-making due to changes in projects during their implementation. Destabilizing factors contribute to an increase in the duration of construction sector projects, which leads to time overruns, cost overruns, and an increase in the negative impact on the overall use of resources. As a result of the study, a set of recommendations was formed, the most important of which is the use of possible compensatory measures that can allow construction companies to eliminate the risks of disrupting construction deadlines for sustainable activities. These compensatory measures include: 1. recommendations to customers of the construction project, 2. recommendations to contractors, and 3. recommendations to the consultant. Moreover, the control of destabilizing factors that can cause delays, the improvement of contracts, and the precise and clearer definition of all elements of the project can help to reduce the duration of construction, and will allow companies to maintain sustainable activities in the construction industry. Full article

The latest wireless network technology, Fifth Generation (5G) new radio (NR), is considered to be an emerging wireless network solution for smart grid (SG) communications owing to its ultra-reliable low latency and larger bandwidth properties. Packet scheduling is one of the mechanisms that plays a vital function in the performance of smart grid communications since it is highly responsible for the bandwidth resource allocation processes. The union of a scheduling approach and a beamforming technique can, however, boost the performance of multi-users in the communication system. Since 5G communication is not intended for smart grid communications, the performance of a scheduling approach must be properly utilized and effectively optimized. This paper evaluates and examines the Deadline Scheduling with Commitment (DSC) scheduling approach and further demonstrates that the performance of the popular Earliest Deadline First (EDF) scheduling approach can be richly enhanced by our modification and improvement of the approach. A novel Optimal Usage and Dropping Scheduling (OUD) approach for proper utilization and assigning of Resource Blocks (RBs) is also proposed to meet the stringent requirements of smart grid communications. Several performance indexes are employed to ascertain the performance of these scheduling approaches, and the results indicate that our proposed OUD approach shows a superior scheduling performance. It is concluded that 5G communications can be effectively employed in smart grids while utilizing the proposed OUD scheduling approach. Full article

Augmented cognition, which refers to real-time modifications to a human–system interface to improve performance and includes dynamic task environments with automated adaptations, can serve to protect against performance impairment under challenging work conditions. However, the effectiveness of augmented cognition as a countermeasure for performance impairment due to sleep loss is unknown. Here, in a controlled laboratory study, an adaptive version of a Change Signal task was administered repeatedly to healthy adults randomized to 62 h of total sleep deprivation (TSD) or a rested control condition. In the computerized task, a left- or right-facing arrow was presented to start each trial. In a subset of trials, a second arrow facing the opposite direction was presented after a delay. Subjects were to respond within 1000 ms of the trial start by pressing the arrow key corresponding to the single arrow (Go trials) or to the second arrow when present (Change trials). The Change Signal Delay (CSD)—i.e., the delay between the appearance of the first and second arrows—was shortened following incorrect responses and lengthened following correct responses so that subsequent Change trials became easier or harder, respectively. The task featured two distinct CSD dynamics, which produced relatively stable low and high error rates when subjects were rested (Low and High Error Likelihood trials, respectively). During TSD, the High Error Likelihood trials produced the same, relatively high error rate, but the Low Error Likelihood trials produced a higher error rate than in the rested condition. Thus, sleep loss altered the effectiveness of the adaptive dynamics in the Change Signal task. A principal component analysis revealed that while subjects varied in their performance of the task along a single dominant dimension when rested, a second inter-individual differences dimension emerged during TSD. These findings suggest a need for further investigation of the interaction between augmented cognition approaches and sleep deprivation in order to determine whether and how augmented cognition can be relied upon as a countermeasure to performance impairment in operational settings with sleep loss. Full article