System Response Time Research Articles

How latency, action modality and display modality influence the sense of agency: a virtual reality study

The objective of this study was to investigate the influences of latency (i.e., technical system response time), action modality (button press, voice command) and display modality (head-mounted display, monitor) on the sense of agency (SOA). SOA is the experience of controlling one’s own actions and their corresponding effects in the environment. The N = 31 (48% female, with a mean age of 24) participants had to interact repeatedly with three different objects (lamp, tablet and computer) in a virtual environment (presented on a monitor or via a head-mounted display) by using a voice command or pressing a button to turn the objects on. The objects reacted after a specific technical system response delay (150, 450 and 750 ms). Results showed that the SOA was weaker for actions employing voice commands opposed to button presses, except for the explicit SOA in the monitor condition. Higher latencies diminished the explicit, but not the implicit SOA. Neither the explicit nor the implicit SOA was significantly affected by the display modality. The findings in part support the weighting process of different agency cues of the underlying framework, and we propose to extend this model by a sense of presence. Users seem to react as if they have the impression that they are not able to control the technical system properly if they interact through a voice command. Therefore, human–computer interface designers could take account of our findings regarding the modality of an action by providing additional feedback cues to increase the SOA for interactions with voice interfaces.

Kinetic processes of copper and lead remobilization during sediment resuspension of marine polluted sediments

Contaminated sediments could act as a source of contamination to the surrounding environments by several processes (e.g., diffusive flux, sediment resuspension). This study aimed at highlighting the mechanisms of copper and lead mobilization from resuspended particles to the aqueous phase using laboratory experiments and a kinetic model. Three sediments, differed by their compositions and metal partition from Toulon Bay (SE France) were used. In addition, three solid/liquid ratios (0.1, 1 and 10 g L−1) allowed simulating at best natural and anthropogenic scenarios (e.g., storm, nautical traffic, dredging). We monitored metal concentrations, physicochemical parameters (pH, Eh, [O2]) and organic matter concentration along with their optical properties. Experimental results showed successive reactions over short and long terms (hour and day scale, respectively) that controlled Cu and Pb exchanges between particles and the aqueous phase over 4 weeks. The quick Cu removal was attributed to the implications of newly formed oxides while the long-term Cu release in the dissolved fraction from the more refractory solid pool is more likely related to organic complexation. In fact, we observed a transformation of the dissolved organic matter: an increase in molecular weight and in humic fluorescence properties. However, the Pb removal toward the end of the experiment could be explained by a migration toward the exchangeable sites of higher energy, which could correspond to the particulate organic matter or a combination with organic-coating carrier phases. Both kinetic rate and system response times (τi) were coherent despite the variability of parameters intrinsic to sediments (e.g., sediment composition and initial metal repartition) but also extrinsic parameters (solid/liquid ratios). Such a coherence would imply the universality of the obtained constants to be used in a more predictive approach to assess the potential of metal mobility using metal repartition in contaminated sediments when combined with hydrological and sedimentological models.

Nonlinear methods for evaluating and online predicting the lifetime of fuel cells

Lifetime evaluation and prediction is a key topic for proton exchange membrane (PEM) fuel cells, which can contribute to prolong the durability and accelerate the commercialization of fuel cells. In this paper, a linear formula to evaluate the maximum service lifetime of fuel cells for vehicle applications and several nonlinear formulas to predict the lifetime of fuel cells are presented. The terminal voltage of fuel cells at the rated condition is defined as the average cell voltage decreasing by ca. 10% from the start rated voltage at the rated condition. A nonlinear formula based on the variation of the hydrogen crossover is derived, which reveals that the variation of the hydrogen crossover is the main factor for the nonlinear lifetime degradation of fuel cells. The nonlinear formula based on the time response of first-order control systems (FOCS) for the overall process is proposed, and the segment point between linear and nonlinear degradation is also defined by this formula. Then a more accurate segmented formula with linear lifetime formula and nonlinear lifetime formula based on the time response of FOCSs for the local process is derived. Finally, the segmented formula is verified by experiment results of the single cell and fuel cell stacks and practical operating results of fuel cell vehicles. Moreover, methods for lifetime evaluation in the laboratory and online prediction in the vehicle are proposed.

Importance of clinical decision support system response time monitoring: a case report.

Clinical decision support (CDS) systems are prevalent in electronic health records and drive many safety advantages. However, CDS systems can also cause unintended consequences. Monitoring programs focused on alert firing rates are important to detect anomalies and ensure systems are working as intended. Monitoring efforts do not generally include system load and time to generate decision support, which is becoming increasingly important as more CDS systems rely on external, web-based content and algorithms. We report a case in which a web-based service caused significant increase in the time to generate decision support, in turn leading to marked delays in electronic health record system responsiveness, which could have led to patient safety events. Given this, it is critical to consider adding decision support-time generation to ongoing CDS system monitoring programs.

Spatial and Temporal Resolution Optimization on Raman Distributed Temperature Sensor System for Quench Detection in a No-Insulated Coil

Quench detection and protection technologies are extremely important for high-temperature superconducting (HTS) magnet applications. In a previous work, we have verified the feasibility of using a Raman-based distributed temperature sensor (RmDTS) system to measure a no insulation (NI) HTS coil temperature changes in an overcurrent induced quench event. However, rough and slow temperature measurement is unsuitable for actual application on quench detection and protection. Therefore, we designed a new RmDTS system consisting of an RmDTS device whose temporal resolution is 15 ms and a thinner polyimide-coated optical fiber with a diameter of 150 μ m. Then, the optimized RmDTS system and an original one were, respectively, applied to detect the NI coil temperature during quenches. The comparative results show that the highest heat was generated on the 22nd turn of the NI coil, and the temperature response time of the original DTS system is 2 s slower than that of the optimized one. By using an optimization method, the spatial and temporal resolutions of the RmDTS system have been enhanced triple and 66 times than before.

The evaluation of performance cost for network based moving target defense

Network based moving target defense prevents attackers from reliably contacting a system by re-configuring network factors. Although limited researching has demonstrated it to be practical and feasible, little studies have been conducted to evaluate the performance cost appended to the original system. Without quantitative results, it is challenging to implement moving target techniques to typical information system broadly. This paper introduces a Queueing Petri Net model that can provide insight into the performance of network re-configurations. This model quantifies the system throughput, queue utilization and response time of requests regarding configurations of the information system, type of strategies for mutation and the frequency of networking transformation. Through logical deductions and simulations using Queueing Petri net Modelling Environment, results show that the network shifting method is an affordable defense technology compared to the performance loss in the processing of servers. Moreover, event-based strategies can get the trade-off between security and performance. These results guide the research deep into developing a more optimized method in moving target defense.

A New Multi-objective Artificial Bee Colony Algorithm for Optimal Adaptive Robust Controller Design

Artificial bee colony algorithm as a recent meta-heuristic algorithm, inspired from the foraging behavior of honey bees, can be considered as a proper technique to handle optimization problems. In this paper, a multi-objective artificial bee colony algorithm is introduced in which an archive is defined to store non-dominated solutions. Furthermore, to reduce computations and to have evenly distributed solutions, the archive is pruned using a technique based on neighborhood radius concepts. A group of bees that is responsible for improvement of the solutions chooses and exploits one solution of the archive. Because of the definition of neighborhood radius and retaining adjacent solutions, the remaining solutions have an equal chance to be selected by onlooker bees. In order to examine the proposed algorithm, some benchmark functions are used and the results are compared with true Pareto fronts. Moreover, the algorithm is utilized to optimize the coefficients of a new combined controller applied to a ball-beam system. In fact, the proposed controller is a combination of robust decoupled sliding mode and adaption laws based on the gradient decent method. The objective functions are considered as the integral time of absolute of errors of the ball position and the beam angle that should be minimized with a constraint on the control effort. To evaluate and validate the suggested approach, the obtained time responses of the ball-beam system are compared with those of other recently reported controllers.

FC: Built-in flash cache with fast cleaning for SMR storage systems

Shingled Magnetic Recording (SMR) disks are adopted as a high-density, non-volatile storage media which significantly precedes conventional disks in both the storing volume and cost. However, time-consuming Read–Modify–Writes (RMWs) significantly degrade the system performance of SMR disks. Current designs devote a portion of disk spaces as a cache to alleviate the negative effect brought by RMWs; however, when the cache is full, the cleaning process becomes the performance bottleneck of the system. This paper presents a hybrid architecture called FC (Flash Cache) to manage the SMR disks by replacing the cache with a built-in NAND flash. The performance without triggering a cleaning process of FC can be comparable to that of the NAND flash rather than Hard Disk Drives (HDDs). Furthermore, FC is capable of shortening the large-scale cleaning process and performing much faster cleaning. Our experimental results show that FC can improve both system response time and cleaning efficiency.

Texture Entropy-Based Classification for Iris Recognition Systems

In recent years, iris recognition is one of the most widely used techniques for person identification. Automatic iris identification implies a comparison of query iris image with iris entries in a large database to determine the identity of the person. In this paper, we propose a straightforward and effective algorithm for the classification of irises into several categories according to the iris texture characteristics. The goal of the classification is to identify and retrieve a smaller subset of the large database and to narrow down the search space. In this way, the response time of the iris recognition system could be significantly improved. We analyzed several cases for dividing the whole database (we used UPOL, CASIA, and UBIRIS databases) into up to eight subsets and calculated the time savings. The simulation results illustrate the potential of the proposed classification method for large-scale iris databases.

Deadline-Constrained Connection Request Scheduling in Mobile Relay-Assisted LTE Networks

Connection and service request scheduling affects the performance of a mobile relay node (MRN) in a relay-assisted long-term evolution network in terms of crucial quality-of-service (QoS) metrics such as the blocking probability and the system's response time. In this paper, a novel Deadline-constrained Connection and service Request Scheduling (DCRS) scheme is proposed with the objective of improving an MRN's performance in terms of the above-mentioned metrics. In this paper, a stochastic queueing model is formulated for the purpose of capturing the MRN's behavioral dynamics and evaluating its performance as it operates under DCRS. Simulations are conducted in order to verify the model's results’ validity and accuracy. Moreover, the MRN performance achieved under DCRS is compared to that achieved under the typically adopted first-come-first-service (FCFS) scheme. Results indicate that DCRS remarkably outperforms FCFS.

INDUCTIVE LINEAR DISPLACEMENT SENSOR IN ACTIVE MAGNETIC BEARING

Active magnetic bearings are increasingly used in various fields of industry. The absence of mechanical contact makes it possible to use them in ultra-high-speed electric drives. The main trend of active magnetic bearings development is the improvement of the control system. The main problem of the control system is the displacement sensor (most of them has low accuracy and large interference). The sensor must have the following properties: simple in realization, high linearity of the characteristic, high sensitivity and noise immunity, high reliability. At the present time there is no sensor that satisfies all these conditions. Most manufacturers use various kinds of filters to get an accurate position signal. This increases the response time of the control system. Thus, problem of designing and modeling the position sensor, considered in the article is topical.

Load Balancing Guardrails

Load balancing systems, comprising a central dispatcher and a scheduling policy at each server, are widely used in practice, and their response time has been extensively studied in the theoretical literature. While much is known about the scenario where the scheduling at the servers is First-Come-First-Served (FCFS), to minimize mean response time we must use Shortest-Remaining-Processing-Time (SRPT) scheduling at the servers. Much less is known about dispatching polices when SRPT scheduling is used. Unfortunately, traditional dispatching policies that are used in practice in systems with FCFS servers often have poor performance in systems with SRPT servers. In this paper, we devise a simple fix that can be applied to any dispatching policy. This fix, called guardrails, ensures that the dispatching policy yields optimal mean response time under heavy traffic when used in a system with SRPT servers. Any dispatching policy, when augmented with guardrails, becomes heavy-traffic optimal. Our results yield the first analytical bounds on mean response time for load balancing systems with SRPT scheduling at the servers.

Knocking down free-flight adult mosquitoes via dynamic tracking

Elimination of virus-carrying insects, such as mosquitoes, by an efficient method is of primary importance to preventing the dissemination of infectious diseases and consequentially reducing the health and financial burden on human society. Research herein entails the design, characterization, and implementation of a structurally simple and cost-effective electro-optical system for mosquito-hunting, which is optimized with a system response time under 1.25 ms considering the average mosquito flight speed of 0.2777 m/s, capable of locating the free-flight adult mosquito and knocking it down, synchronously, without any post data-processing. Empirically, the visible-near-infrared absorption spectra of three mosquito species, namely, Culex piplens molestus, Aedes albopictus, and Armigeres subalbatus, were acquired to examine the disparity in photo-absorption property among different mosquito species and help determine an optimal wavelength for injuring the insects. Armigeres subalbatus, a natural transmission vector of filariasis to humans, was employed for the evaluation of the system's efficacy. By introducing a free-flight mosquito about 20 cm in front of an dichroic mirror that combines two optical beams for detection and eradication, a dynamically tracking photonic antenna with a maximal area of 45 mm by 39 mm can continuously track the insect and then knock it down by an instant exposure of a lethal beam with average energy ranging from 75 mJ to 155 mJ. Moreover, the dependence of the fate of the insects on the lethal beam energy dosage is statistically assessed. Overall, this research has successfully demonstrated the concept of the synchronizing scheme of identification and eradication with over 60% of mortality rate once the energy dosage is increased above 75mJ, and may be applicable to the control of other insects or avian animals.

Efficiency of vibration signal feature extraction for surface finish monitoring in CNC machining

On-line monitoring technologies in CNC machining operations eliminate post-process quality control, and are crucial for improving productivity and reliability, reducing production times and costs, and enhancing automation of the process. The appropriate selection of sensors, signal feature extraction methods, and parametric characterization techniques are critical aspects influencing the quality of predictions and system response times. This paper examined four signal feature extraction methods to optimize surface finish monitoring by focusing on the analysis of vibration signals in order to correlate signal statistical measurements and frequency bands with surface roughness. Thus, a single low cost sensor (accelerometer) easily implemented in CNC turning machine was used to make in-process decisions on product surface finish. Two non-advanced signal feature extraction methods (time direct analysis TDA, and power spectral density PSD), and two advanced methods (singular spectrum analysis SSA, and wavelet packet transform WPT) were assessed. The results show that the advanced methods (SSA and WPT) permitted optimum vibration signal feature extraction, but the SSA method exhibited a high computational cost. The WPT provided the excitation ranges that correlate the vibration parametric features with surface finish. The vibration signal and WPT method can be used effectively for real-time surface finish monitoring with high accuracy, reliability, and a low analytical-computational cost in CNC machining. This work is innovative in revealing that not all vibration feature extraction methods are appropriate for the real-time monitoring of surface finish, and that on-line surface quality control is possible with a low cost sensor easily implemented in CNC machine tools.

AAIoT: Accelerating Artificial Intelligence in IoT Systems

Existing deep learning systems in the Internet of Things (IoT) environments lack the ability of assigning compute tasks reasonably which leads to resources wasting. In this letter, we propose an AAIoT, a method to allocate the inference computation of each network layer to each device in multi-layer IoT system. To our best knowledge, this is the first attempt to solve this problem. We design a dynamic programming algorithm to minimize the response time when weighing the cost of computation and transmission. Simulation results show that our approach makes significant improvements in system response time.

Improved wind system using non-linear power control

<p>This article, present a new contribution to the control of wind energy systems, a robust nonlinear control of active and reactive power with the use of the Backstepping and Sliding Mode Control approach based on a doubly fed Induction Generator power (DFIG-Generator) in order to reduce the response time of the wind system. In the first step, a control strategy of the MPPT for the extraction of the maximum power of the turbine generator is presented. Subsequently, the Backstepping control technique followed by the sliding mode applied to the wind systems will be presented. These two types of control system rely on the stability of the system using the LYAPUNOV technique. Simulation results show performance in terms of set point tracking, stability and robustness versus wind speed variation. </p>

Edge Computing: A Promising Framework for Real-Time Fault Diagnosis and Dynamic Control of Rotating Machines Using Multi-Sensor Data

Edge computing is an emerging computing paradigm where computation is executed on the edge of networks rather than on cloud servers, thereby reducing the system response time, transmission bandwidth occupation, and storage and computation resources on the cloud. In this paper, an edge computing-based method for real-time fault diagnosis and dynamic control of rotating machines is proposed, and an edge computing node (ECN) is designed. A vibration signal and three motor-phase current signals are acquired synchronously by the ECN. Subsequently, 40 features are extracted from the signals and fused into an indicator that can effectively distinguish multiple motor conditions. The experimental results show that the designed ECN can diagnose electrical and mechanical faults with 100% accuracy and take control of the motor when an emergency fault is detected. The algorithm procedures, including signal acquisition, feature extraction and fusion, and fault identification, can be accomplished within 0.25 s on the ECN. The proposed edge computing framework processes sensor data in real time and thus shows potential applications in the rotating machines where fault diagnosis and dynamic control are highly time sensitive.

Performance Analysis and Optimization Techniques for Oracle Relational Databases

Abstract Databases provide an efficient way to store, retrieve and analyze data. Oracle relational database is one of the most popular database management systems that is widely used in a different variety of industries and businesses. Therefore, it is important to guarantee that the database access and data manipulation is optimized for reducing database system response time. This paper intends to analyze the performance and the main optimization techniques (Forall, Returning, and Bulk Collect) that can be adopted for Oracle Relational Databases. The results have shown that the adoption of Forall and Bulk Collect approaches bring significant benefits in terms of execution time. Furthermore, the growth rate of the average execution time is lower for Bulk Collect than Forall. However, adoption of Returning approach doesn’t bring significant statistical benefits.

Intracellular Noise Level Determines Ratio Control Strategy Confined by Speed-Accuracy Trade-off.

Robust and precise ratio control of heterogeneous phenotypes within an isogenic population is an essential task, especially in the development and differentiation of a large number of cells such as bacteria, sensory receptors, and blood cells. However, the mechanisms of such ratio control are poorly understood. Here, we employ experimental and mathematical techniques to understand the combined effects of signal induction and gene expression stochasticity on phenotypic multimodality. We identify two strategies to control phenotypic ratios from an initially homogeneous population, suitable roughly to high-noise and low-noise intracellular environments, and we show that both can be used to generate precise fractional differentiation. In noisy gene expression contexts, such as those found in bacteria, induction within the circuit's bistable region is enough to cause noise-induced bimodality within a feasible time frame. However, in less noisy contexts, such as tightly controlled eukaryotic systems, spontaneous state transitions are rare and hence bimodality needs to be induced with a controlled pulse of induction that falls outside the bistable region. Finally, we show that noise levels, system response time, and ratio tuning accuracy impose trade-offs and limitations on both ratio control strategies, which guide the selection of strategy alternatives.

Simultaneous Quantification of Soil Phosphorus Labile Pool and Desorption Kinetics Using DGTs and 3D-DIFS.

The buffering of phosphorus concentrations in soil solution by the soil-solid phase is an important process for providing plant root access to nutrients. Accordingly, the size of labile solid phase-bound phosphorus pool and the rate at which it can resupply phosphorous into the dissolved phase can be important variables in determining when the plant availability of the nutrient may be limited. The phosphorus labile pool (Plabile) and its desorption kinetics were simultaneously evaluated in 10 agricultural UK soils using the diffusive gradients in thin-films (DGT) technique. The DGT-induced fluxes in the soil and sediments model (DIFS) was fitted to the time series of DGT deployments (1-240 h), which allowed the estimation of Plabile, and the system response time ( Tc). The Plabile concentration was then compared to that obtained by several soil P extracts including Olsen P, FeO-P, and water extractable P, in order to assess if the data from these analytical procedures can be used to represent the labile P across different soils. The Olsen P concentration, commonly used as a representation of the soil labile P pool, overestimated the desorbable P concentration by 6-fold. The use of this approach for the quantification of soil P desorption kinetic parameters found a wide range of equally valid solutions for Tc. Additionally, the performance of different DIFS model versions working in different dimensions (1D, 2D, and 3D) was compared. Although all models could provide a good fit to the experimental DGT time series data, the fitted parameters showed a poor agreement between different model versions. The limitations of the DIFS model family are associated with the assumptions taken in the modeling approach and the three-dimensional (3D) version is here considered to be the most precise among them.