Search Results (60)

5G private mobile networks are becoming a platform for ‘wire-free’ networking for professional applications in smart industry sectors, such as automated warehousing, logistics, autonomous vehicle deployments in campus environments, mining, material processing, and more. It is expected that most of these Machine-to-Machine (M2M) and Industrial Internet of Things (IIoT) communication paths will be realized wirelessly, as the advantages of providing flexibility are obvious compared to hard-wired network installations. Unfortunately, the deployment of private 5G networks in smart industries has faced delays due to a combination of high costs, technical challenges, and uncertain returns on investment, which is reflected in troublesome access to fully operational private networks. To obtain insight into occupational exposure to radiofrequency electromagnetic fields (RF EMF) emitted by 5G private mobile networks, an analysis of RF EMF due to different types of 5G equipment was carried out on a real case scenario in the production and logistic (warehouse) industrial sector. A private standalone (SA) 5G network operating at 3.7 GHz in a real industrial environment was numerically modeled and compared with in situ RF EMF measurements. The results show that RF EMF exposure of the workers was far below the existing exposure limits due to the relatively low power (1 W) of indoor 5G base stations in private networks, and thus similar exposure scenarios could also be expected in other deployed 5G networks. In the analyzed RF EMF exposure scenarios, the radio transmitter—so-called ‘radio head’—installation heights were relatively low, and thus the obtained results represent the worst-case scenarios of the workers’ exposure that are to be expected due to private 5G networks in smart industries. Full article

Operating room (OR) scheduling problems are often addressed using deterministic models that assume surgery durations are known in advance. However, such assumptions fail to reflect the uncertainty that often occurs in real surgical environments, especially during the surgery and recovery stages. This study focuses on a robust scheduling problem involving a three-stage surgical process that includes pre-surgery, surgery, and post-surgery stages. The scheduling needs to coordinate multiple resources—pre-operative holding unit (PHU) beds, ORs, and post-anesthesia care unit (PACU) beds—while following a strict no-wait rule to keep patient flow continuous without delays between stages. The main goal is to minimize the makespan and improve schedule robustness when surgery and post-surgery durations are uncertain. To solve this problem, we propose a Genetic Algorithm for Robust Scheduling (GARS), which evaluates solutions using a scenario-based robustness criterion derived from multiple sampled instances. GARS is compared with four other algorithms: a deterministic GA (GAD), a random search (BRS), a greedy randomized insertion and swap heuristic (GRIS), and an improved version of GARS with simulated annealing (GARS_SA). The results from different problem sizes and uncertainty levels show that GARS and GARS_SA consistently perform better than the other algorithms. In large-scale tests with moderate uncertainty (30 surgeries, α = 0.5), GARS achieves an average makespan of 633.85, a standard deviation of 40.81, and a worst-case performance ratio (WPR) of 1.00, while GAD reaches 673.75, 54.21, and 1.11, respectively. GARS can achieve robust performance without using any extra techniques to strengthen the search process. Its structure remains simple and easy to use, making it a practical and effective approach for creating reliable and efficient surgical schedules under uncertainty. Full article

The goal of this article is to reduce the vibration of a hybrid oscillator with a cubic–quintic nonlinear term under internal and external forces in the worst resonance case. To eliminate the harmful vibration in the system, the following strategies are suggested: nonlinear derivative feedback control (NDF), linear negative velocity feedback control (LNVC), nonlinear integral positive position feedback (NIPPF), integral resonant control (IRC), negative velocity with time delay (TD), and positive position feedback (PPF). It is discovered that the PPF control suppresses vibration more effectively than typical controllers, which reduces the vibration to 0.0001 with an effectiveness of 99.92%. Moreover, the main advantages of the PPF controller are its low cost and the fast response. The multiple time scale perturbation technique (MSPT) is used to apply the theoretical methodology and obtain a perturbed response. In order to close the concurrent primary and internal resonance case, frequency response (FR) equations are also used to study and analyze the system’s stability. The MATLAB software is used to complete and clarify all numerical topics. The FR curves are examined to determine the amplitude’s subsequent impact from variations in the parameters’ values. Lastly, a comparison of the numerical and analytical solutions is performed utilizing time history. Along with comparing the impact of our PPF damper on the hybrid oscillator, earlier research is also provided. 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

This work investigates a new erase scheme in NAND flash memory to improve the lifetime and performance of modern solid-state drives (SSDs). In NAND flash memory, an erase operation applies a high voltage (e.g., >20 V) to flash cells for a long time (e.g., >3.5 ms), which degrades cell endurance and potentially delays user I/O requests. While a large body of prior work has proposed various techniques to mitigate the negative impact of erase operations, no work has yet investigated how erase latency and voltage should be set to fully exploit the potential of NAND flash memory; most existing techniques use a fixed latency and voltage for every erase operation, which is set to cover the worst-case operating conditions. To address this, we propose Revisiting Erase Operation, (REO) a new erase scheme that dynamically adjusts erase latency and voltage depending on the cells’ current erase characteristics. We design REO by two key apporaches. First, REO accurately predicts such near-optimal erase latency based on the number of fail bits during an erase operation. To maximize its benefits, REO aggressively yet safely reduces erase latency by leveraging a large reliability margin present in modern SSDs. Second, REO applies near-optimal erase voltage to each WL based on its unique erase characteristics. We demonstrate the feasibility and reliability of REO using 160 real 3D NAND flash chips, showing that it enhances SSD lifetime over the conventional erase scheme by 43% without change to existing NAND flash chips. Our system-level evaluation using eleven real-world workloads shows that an REO-enabled SSD reduces average I/O performance and read tail latency by 12% and 38%, respectivley, on average over a state-of-the-art technique. Full article

In a kind of system, where strong time constraints exist, very often, worst-case design is applied. It could drive to the suboptimal usage of resources. In previous work, the mechanism of self-adaptive software that is able to reduce this was presented. This paper introduces a novel extension of the method for self-adaptive software synthesis applicable for real-time multicore embedded systems with dynamic voltage and frequency scaling (DVFS). It is based on a multi-criteria approach to task scheduling, optimizing both energy consumption and proof against time delays. The method can be applied to a wide range of embedded systems, such as multimedia systems or Industrial Internet of Things (IIoT). The main aim of this research is to find the method of automatic construction of the task scheduler that is able to minimize energy consumption during the varying execution times of each task. Full article

Wearable motion capture gloves enable the precise analysis of hand and finger movements for a variety of uses, including robotic surgery, rehabilitation, and most commonly, virtual augmentation. However, many motion capture gloves restrict natural hand movement with a closed-palm design, including fabric over the palm and fingers. In order to alleviate slippage, improve comfort, reduce sizing issues, and eliminate movement restrictions, this paper presents a new low-cost data glove with an innovative open-palm and finger-free design. The new design improves usability and overall functionality by addressing the limitations of traditional closed-palm designs. It is especially beneficial in capturing movements in fields such as physical therapy and robotic surgery. The new glove incorporates resistive flex sensors (RFSs) at each finger and an inertial measurement unit (IMU) at the wrist joint to measure wrist flexion, extension, ulnar and radial deviation, and rotation. Initially the sensors were tested individually for drift, synchronisation delays, and linearity. The results show a drift of 6.60°/h in the IMU and no drift in the RFSs. There was a 0.06 s delay in the data captured by the IMU compared to the RFSs. The glove’s performance was tested with a collaborate robot testing setup. In static conditions, it was found that the IMU had a worst case error across three trials of 7.01° and a mean absolute error (MAE) averaged over three trials of 4.85°, while RFSs had a worst case error of 3.77° and a MAE of 1.25° averaged over all five RFSs used. There was no clear correlation between measurement error and speed. Overall, the new glove design proved to accurately measure joint angles. Full article

Signal retiming is the most cost-efficient measure to reduce vehicle delay and alleviate congestion on urban roads. Previous studies have explored the potential of using connected vehicle data for signal retiming specifically under the current low-penetration environment, which will significantly reduce the cost and increase the productivity of signal retiming. However, the existing methods are mostly deterministic and do not well consider the uncertainty in both traffic demand and capacity. This compromises their robustness in a real application. In this study, a novel traffic state measure—queue service time (QST)—is introduced and used as the only input to generate a robust signal plan at isolated intersections for a time-of-day period. First, a Bayesian-based model is proposed to estimate the QST distribution by collectively using the lower and upper boundary observations reported by connected vehicles. Then, a goal programming-based signal optimization model is formulated using quantiles of QST as input, which accounts for the combined uncertainty in both traffic demand and capacity. Simulation experiments validate the effectiveness and robustness of the proposed method. It is shown that the proposed QST estimation model is reliable to use under a penetration rate as low as 0.05 and can effectively estimate the actual distribution in both under- and oversaturation conditions. Compared with a demand-based method that only accounts for uncertainty in traffic demand, the proposed QST-based signal timing optimization method shows its superiority in reducing the occurrence of oversaturation or phase failure, as well as enhancing performance against the worst cases. Full article

A hybrid ship uses integrated generators, an energy storage system (ESS), and photovoltaics (PV) to match its propulsion and service loads, and together with optimal power and voyage scheduling, this can lead to a substantial improvement in ship operation cost, ensuring compliance with the environmental constraints and enhancing ship sustainability. During the operation, significant uncertainties such as waves, wind, and PV result in considerable speed loss, which may lead to voyage delays and operation cost increases. To address this issue, a distributionally robust optimization (DRO) model is proposed to schedule power generation and voyage. The problem is decoupled into a bi-level optimization model, the slave level can be solved directly by commercial solvers, the master level is further formulated as a two-stage DRO model, and linear decision rules and column and constraint generation algorithms are adopted to solve the model. The algorithm aims at minimizing the operation cost, limiting greenhouse gas (GHG) emissions, and satisfying the technical and operational constraints considering the uncertainty. Extensive simulations demonstrate that the expected total cost under the worst-case distribution is minimized, and compared with the conventional robust optimization methods, some distribution information can be incorporated into the ambiguity sets to generate fewer conservative results. This method can fully ensure the on-time arrival of hybrid ships in various uncertain scenarios while achieving expected operation cost minimization and limiting greenhouse gas (GHG) emissions. Full article

Ultra-low-voltage design brings considerable outcomes in power reduction and energy efficiency improvement at the cost of performance degradation and uncertainty. Conventional standard cell design methodology cannot guarantee optimal performance for subthreshold operations due to the lack of consideration of process variation. In this paper, an effective subthreshold cell sizing method is proposed to minimize the worst-case propagation delay by deriving the optimal pMOS-to-nMOS width ratio (β) analytically, which reveals the relation between the minimal worst-case delay and the process parameters and provides distinct guidance for standard cell library design. The proposed method demonstrated good agreement with the Monte Carlo SPICE simulation results and was validated at the cell level and the circuit level. At the cell level, the logic cells designed with the proposed method show at least 8.6% and 7.4% improvement, on average, for worst-case delay and energy-delay product (EDP), respectively, with an additional 3.2% energy overhead compared to the prior approaches. At the circuit level, the proposed method improves the worst-case performance and worst-case EDP of the ring oscillator by at least 15.5% and 15.0%, respectively, with a 0.9% energy penalty. Moreover, the ISCAS’89 and OpenCores circuits synthesized with the optimized cells achieve at least 6.6% worst-case performance enhancement, 6.9% power reduction, and 9.4% area saving. Full article

The rising complexity of construction projects and the industry’s commitment to sustainable practices have driven the extensive adoption of Building Information Modeling (BIM) technology. A core function of BIM is the early identification and resolution of clashes during the design phase, which serves to mitigate costly rework and delays in the construction process. This study presents an advanced method for classifying and prioritizing hard clashes between structural components and mechanical, electrical, and plumbing (MEP) systems. Employing the Best-Worst Method (BWM), this research assigned specific weights to structural and MEP elements based on expert evaluations. Six parameters were incorporated into this prioritization framework: the weights determined by the BWM, outputs from Navisworks software (v2021), the ratio of MEP volume to floor volume, the functional purpose of each floor, and the number of adjacent elements. A custom-developed plugin for Autodesk Navisworks integrated these parameters, enabling real-time automated clash prioritization. Clashes were ranked by criticality through a calculation involving the six parameters, which enhanced the efficiency of clash detection by optimizing time and cost considerations during the design phase. Case study results indicate that beams and columns represent the most critical structural elements, while ducts are identified as the most significant MEP elements. The proposed method substantially improves clash detection and prioritization efficiency and accuracy, yielding considerable benefits in project management and resource allocation. Full article

This paper considers a nominal undelayed and time-varying second-order Sturm–Liouville differential equation on a finite time interval which is a nominal version of another perturbed differential equation subject to a delay in its dynamics. The nominal delay-free differential equation is a Sturm–Liouville system in the sense that it is subject to prescribed two-point boundary conditions. However, the perturbed differential system is not a Sturm–Liouville system, in general, due to the presence of delayed dynamics. The main objective of the paper is to investigate the loss of the boundary values of the Sturm–Liouville nominal undelayed system in the presence of the delayed dynamics. Such a delayed dynamics is considered a perturbation of the nominal dynamics related to the Sturm–Liouville system with given two-point boundary values. In particular, this loss of the Sturm–Liouville exact tracking of the prescribed two-point boundary values might happen because the nominal boundary values may become lost by the state trajectory solution in the presence of delays, related to the undelayed case, due to the presence of the delayed dynamics. The worst-case error description of the deviation of the two-point boundary values of the current perturbed differential with respect to those of the nominal Sturm–Liouville system is characterized in terms of error norms related to the nominal system. Under sufficiently small deviations of the parameterization of the perturbed system with respect to the nominal one, such a worst-error characterization makes the current perturbed system an approximate Sturm–Liouville system of the nominal undelayed one. Full article

Software-Defined Networking (SDN) revolutionizes network management by decoupling control plane functionality from data plane devices, enabling the centralized control and programmability of network behavior. This paper uses the ternary system to improve the Central Processing Unit (CPU) inside the SDN controller to enhance network management. The Multiple-Valued Logic (MVL) circuit shows remarkable improvement compared to the binary circuit regarding the chip area, propagation delay, and energy consumption. Moreover, the Carbon Nanotube Field-Effect Transistor (CNTFET) shows improvement compared to other transistor technologies regarding energy efficiency and circuit speed. To the best of our knowledge, this is the first time that a ternary design has been applied inside the CPU of an SDN controller. Earlier studies focused on Ternary Content-Addressable Memory (TCAM) in SDN. This paper proposes a new 1-trit Ternary Full Adder (TFA) to decrease the propagation delay and the Power–Delay Product (PDP). The proposed design is compared to the latest 17 designs, including 15 designs that are 1-trit TFA CNTFET-based, 2-bit binary FA FinFET-based, and 2-bit binary FA CMOS-based, using the HSPICE simulator, to optimize the CPU utilization in SDN environments, thereby enhancing programmability. The results show the success of the proposed design in reducing the propagation delays by over 99% compared to the 2-bit binary FA CMOS-based design, over 78% compared to the 2-bit binary FA FinFET-based design, over 91% compared to the worst-case TFA, and over 49% compared to the best-case TFAs. Full article

Data centers consume significant amounts of energy, contributing indirectly to environmental pollution through greenhouse gas emissions during electricity generation. According to the Natural Resources Defense Council, information and communication technologies and networks account for roughly 10% of global energy consumption. Reducing power consumption in Data Center Networks (DCNs) is crucial, especially given that many data center components operate at full capacity even under low traffic conditions, resulting in high costs for both service providers and consumers. Current solutions often prioritize power optimization without considering Quality of Service (QoS). Services such as video streaming and Voice over IP (VoIP) are particularly sensitive to loss or delay and require QoS to be maintained below certain thresholds. This paper introduces a novel framework called QoS-Aware Power-Optimized Path Selection (Q-PoPS) for software-defined DCNs. The objective of Q-PoPS is to minimize DCN power consumption while ensuring that an acceptable QoS is provided, meeting the requirements of DCN services. This paper describes the implementation of a prototype for the Q-PoPS framework that leverages the POX Software-Defined Networking (SDN) controller. The performance of the prototype is evaluated using the Mininet emulator. Our findings demonstrate the performance of the proposed Q-PoPS algorithm in three scenarios. Best-case: Enhancing real-time traffic protocol quality without increasing power consumption. midrange-case: Replacing bottleneck links while preserving real-time traffic quality. Worst-case: Identifying new paths that may increase power consumption but maintain real-time traffic quality. This paper underscores the need for a holistic approach to DCN management, optimizing both power consumption and QoS for critical real-time applications. We present the Q-PoPS framework as evidence that such an approach is achievable. Full article

With escalating global regulatory pressure for countries to adhere to emission laws, repurposing existing natural gas pipelines for hydrogen-based commodities stands to be an economical solution. However, the effects of hydrogen embrittlement must be thoroughly considered for this application to avoid the unexpected catastrophic failure of these pipelines. The literature proposes several physicochemical embrittlement models. This paper reports one aspect of hydrogen embrittlement that remains to be quantified: the recovery of ductility (embrittlement) of mild steel specimens subjected to artificially accelerated hydrogen absorption via electrochemical charging as a function of time. The effects of charging duration and particularly the delay period between charging and mechanical tensile testing were investigated. Unsurprisingly, longer charging time shows a greater loss of elongation; however, a more extensive recovery of ductility correlated with longer charging time in the first few days after charging. The data also show that while the uncharged mild steel met all minimum required values for strength and elongation for the specified grade, there was a substantial variability in the elongation to failure. The same trends in variability of elongation translated to the hydrogen-charged specimens. Due to this extensive variability, failure to meet the elongation specification of the grade is reported based on the worst-case scenario obtained for a given set of samples for each exposure condition. These results have practical implications for the monitoring and testing of infrastructure exposed to hydrogen, particularly as this relates to industry planned operational shutdown schedules. Full article