Calculation Of Response Time Research Articles

Hierarchical Ensemble Reduction and Learning for Resource-constrained Computing

Generic tree ensembles (such as Random Forest, RF) rely on a substantial amount of individual models to attain desirable performance. The cost of maintaining a large ensemble could become prohibitive in applications where computing resources are stringent. In this work, a hierarchical ensemble reduction and learning framework is proposed. Experiments show our method consistently outperforms RF in terms of both accuracy and retained ensemble size. In other words, ensemble reduction is achieved with enhancement in accuracy rather than degradation. The method can be executed efficiently, up to >590× time reduction than a recent ensemble reduction work. We also developed Boolean logic encoding techniques to directly tackle multiclass problems. Moreover, our framework bridges the gap between software-based ensemble methods and hardware computing in the IoT era. We developed a novel conversion paradigm that supports the automatic deployment of >500 trees on a chip. Our proposed method reduces power consumption and overall area utilization by >21.5% and >62%, respectively, comparing with RF. The hierarchical approach provides rich opportunities to balance between the computation (training and response time), the hardware resource (memory and energy), and accuracy.

Radiation View Factor for Building Applications: Comparison of Computation Environments

Computation of view factors is required in several building engineering applications where radiative exchange takes place between surfaces such as ground and vertical walls or ground and sloping thermal or photovoltaics collectors. In this paper, view factor computations are performed for bifacial solar photovoltaic (PV) collectors based on the finite element method (FEM) using two programming languages known as Microsoft Excel-Visual Basic for Applications (VBA) and Python. The aim is to determine the computer response time as well as the performance of the two languages in terms of accuracy and convergence of the numerical solution. To run the simulations in Python, an open source just-in-time (JIT) compiler called Numba was used and the same program was also run as a macro in VBA. It was observed that the simulation response time significantly decreased in Python when compared to VBA. This decrease in time was due to the increase in the total number of iterations from 400 million to 250 billion for a given case. Results demonstrated that Python was 71–180 times faster than VBA and, therefore, offers a better programming platform for the view factor analysis and modelling of bifacial solar PV where computation time is a significant modelling challenge.

A Splitting Frequencies-Based Wireless Power and Information Simultaneous Transfer Method

A splitting frequencies-based wireless power and information simultaneous transfer (SF-WPIT) method is proposed, and its power and information transfer performances are investigated theoretically and experimentally. First, the power and information transfer characteristics, including transmitting power, power efficiency, frequency bandwidth, and effective operating range, are investigated theoretically on the splitting frequencies of strongly coupled region in symmetric series-series resonant inductive link. The investigation result shows that the splitting frequencies have a good potential of realizing a high-performance power and information transfer. Second, the SF-WPIT system is configured and the factors that influence on the performance of this system are investigated theoretically. A method of tracing two splitting frequencies is presented. A response time calculation method of splitting frequencies is presented, and the influence of response times on the performance of the SF-WPIT system is clarified. Finally, an experimental prototype is constructed with a pair of planar coils of 75-mm mean radius, and the proposed theory and system performance are verified by experimental results. This prototype exhibits a 15 kb/s of data rate and a stable power transfer irrespective of distance change in its operating range of 0-120 mm.

Joint optimization of data placement and scheduling for improving user experience in edge computing

In recent years, edge computing becomes an increasingly popular alternative. Edge computing allows the computation is implemented in the edge of network, in which the data are stored in the edge of network, to improve the efficiency of data process. However, some resource management techniques in cloud or distributed system cannot better suit for edge computing. Therefore, there exist some challenges on the performance improvement of edge computing. In this paper, the main purpose is to combine the optimal placement of data blocks and the optimal scheduling of tasks to reduce the computation delay and response time for the submitted tasks and improve user experience in edge computing. In optimal placement of data blocks, the value of the data blocks considers not only the popularity of the data blocks, but the data storage capacity and replacement ratios of an edge server that will store those data blocks. Furthermore, the replacement cost for placed data blocks is regarded as an important component of data block placement. This optimal placement scheme can avoid replacing the placed data blocks repeatedly so that the bandwidth overhead is reduced. In optimal scheduling of tasks, the containers are taken as the lightweight resource unit for the services for user requests to make full use of data storage in edge servers and improve the services performance of edge servers. Finally, extensive experiments are conducted to value the performance of task scheduling strategy. The results show that the performance of the proposed task scheduling algorithm is better than that of the compared algorithms.

A Unified Framework for Period and Priority Optimization in Distributed Hard Real-Time Systems

Modern embedded systems, such as automotive, are physically distributed with an increasing number of microcontrollers and buses. They support complex functions such as active safety and autonomous driving features with a high degree of data dependencies. The most common configuration uses periodic activation of tasks and messages coupled with priority-based scheduling. Selecting task and message parameters so that end-to-end deadlines are met can be very challenging, since such deadlines are enforced across a set of microcontrollers and buses. In this paper, we address the problem of optimal selection of task and message activation periods and priorities. Existing approaches cannot scale to large designs and have to settle to optimize period or priority separately, largely due to the complexity of response time analysis techniques. Instead, we present a new, unified framework that simultaneously optimizes period and priority assignment. It avoids the pitfalls of existing approaches by abstracting the response time calculation with the new concept of maximal unschedulable period and deadline assignment. We demonstrate with two industrial case studies that our approach runs magnitudes faster than existing approach on period optimization, while providing substantially better solutions.

Optimal priority and threshold assignment for fixed-priority preemption threshold scheduling

Fixed-priority preemption-threshold scheduling (FPTS) is a generalization of fixed-priority preemptive scheduling (FPPS) and fixed-priority non-preemptive scheduling (FPNS). Since FPPS and FPNS are incomparable in terms of potential schedulability, FPTS has the advantage that it can schedule any task set schedulable by FPPS or FPNS and some that are not schedulable by either. FPTS is based on the idea that each task is assigned a priority and a preemption threshold. While tasks are admitted into the system according to their priorities, they can only be preempted by tasks that have priority higher than the preemption threshold. This paper presents a new optimal priority and preemption threshold assignment (OPTA) algorithm for FPTS which in general outperforms the existing algorithms in terms of the size of the explored state-space and the total number of worst case response time calculations performed. The algorithm is based on back-tracking, i.e. it traverses the space of potential priorities and preemption thresholds, while pruning infeasible paths, and returns the first assignment deemed schedulable. We present the evaluation results where we compare the complexity of the new algorithm with the existing one. We show that the new algorithm significantly reduces the time needed to find a solution. Through a comparative evaluation, we show the improvements that can be achieved in terms of schedulability ratio by our OPTA compared to a deadline monotonic priority assignment.

Computer aided calculation and experimental verification of response time of pneumatic brake system for 4x4 heavy duty vehicles

Computer aided calculation and experimental verification of response time of pneumatic brake system for 4x4 heavy duty vehicles

Accurate and efficient calculation of response times for groundwater flow

We study measures of the amount of time required for transient flow in heterogeneous porous media to effectively reach steady state, also known as the response time. Here, we develop a new approach that extends the concept of mean action time. Previous applications of the theory of mean action time to estimate the response time use the first two central moments of the probability density function associated with the transition from the initial condition, at t = 0, to the steady state condition that arises in the long time limit, as t→∞. This previous approach leads to a computationally convenient estimation of the response time, but the accuracy can be poor. Here, we outline a powerful extension using the first k raw moments, showing how to produce an extremely accurate estimate by making use of asymptotic properties of the cumulative distribution function. Results are validated using an existing laboratory-scale data set describing flow in a homogeneous porous medium. In addition, we demonstrate how the results also apply to flow in heterogeneous porous media. Overall, the new method is: (i) extremely accurate; and (ii) computationally inexpensive. In fact, the computational cost of the new method is orders of magnitude less than the computational effort required to study the response time by solving the transient flow equation. Furthermore, the approach provides a rigorous mathematical connection with the heuristic argument that the response time for flow in a homogeneous porous medium is proportional to L2/D, where L is a relevant length scale, and D is the aquifer diffusivity. Here, we extend such heuristic arguments by providing a clear mathematical definition of the proportionality constant.

Effects of Surface Roughness and Non-Newtonian Micropolar Fluid Squeeze Film between Conical Bearings

Abstract Based on the micropolar fluid models of Eringen and Christensen’s stochastic theories, the analysis of the effects of surface roughness and the squeeze film lubrication problems between conical bearings are presented. The concerned nondimensional Reynolds equation is solved with appropriate boundary conditions in dimensionless form to find the pressure distribution, which is then used to obtain the expression for load-carrying capacity, paving the way for the calculation of response time. Computed values of pressure, load capacity, and response time are displayed in graphical form. This investigation reveals that the bearing system admits an improved performance as compared with that of a bearing system working with a conventional lubricant. According to the results, the effects of transverse roughness provide an increase in the bearing characteristics as compared with the smooth bearing lubricated with micropolar fluid whereas the influences of longitudinal roughness yield a reversed trend. The quantifiable effects of rough surfaces and non-Newtonian fluids on bearing performances are more pronounced for the roughness and micropolar parameters.

Efficient exact Boolean schedulability tests for fixed priority preemption threshold scheduling

Abstract Fixed priority preemption threshold scheduling (PTS) is effective in scalable real-time system design, which requires system tuning processes, where the performance of schedulability tests for PTS matters much. This paper proposes five methods for efficient exact Boolean schedulability tests for PTS, which returns the Boolean result that tells whether the given task is schedulable or not. We regard the sufficient test for fully preemptive fixed priority scheduling (FPS) and the early exit in the response time calculations as the conventional approach. We propose (1) a new sufficient test, (2) new initial values for the start/finish times, (3) pre-calculation of the interference time within the start time, (4) incremental start/finish time calculation, and (5) early exits in start/finish time calculations. These are based on some previous work for FPS. The new initial start time, pre-calculation, and the incremental calculations also can be used for the exact response time analysis for PTS. Our empirical results show that the overall proposed methods reduce the iteration count/run time of the conventional test by about 60%/40%, regardless of the number of tasks and the total utilization.

An evolutionary single Gabor kernel based filter approach to face recognition

For the past few decades, Gabor filter banks have been used for extracting features in face recognition. The state-of-the-art approach for the design and selection of Gabor filter banks is based on a trial and error. This results in more computational complexity and higher response time. To overcome this problem, an attempt is made to design a single optimized Gabor filter instead of a filter bank for feature extraction. This approach improves the filter performance by significantly reducing the computational complexity and response time. The hybrid particle swarm optimization-gravitational search algorithm (PSO-GSA) is used for optimizing the parameters of the single Gabor filter. In this context, an evolutionary single Gabor kernel (ESGK) based filter approach is proposed for face recognition. The proposed method is used to extract Gabor energy feature vectors from face images. We also propose a new eigenvalue based classification approach for face recognition. This approach is derived from sparse based representation methods. The novelty in our paper is measurement of sparsity of the weighting coefficients of each training sample. The main contribution of the paper is two-fold. Firstly, investigation of ESGK approach, which is not found in the literature. Secondly, introducing a new eigen value based classifier. FERET, ORL, UMIST, GT and LFW databases are used to measure the efficiency of our proposed method. The results are compared with a holistic Gabor filter bank based recognition methods. It is witnessed that our proposed method outperforms the state-of-the-art methods.

An efficient schedulability analysis for optimizing systems with adaptive mixed-criticality scheduling

In the design optimization of real-time systems, the schedulability analysis is used to define the feasibility region within which tasks meet their deadlines, so that optimization algorithms can find the best solution within the region. However, the current analysis techniques for systems with adaptive mixed-criticality (AMC) scheduling are based on response time calculation, which are too complex for optimization purposes. In this paper, we provide a simpler schedulability test based on request bound functions, which allows an efficient definition of the feasibility region for AMC. We prove that the new analysis is safe with bounded pessimism. Experimental results show that our analysis provides much better scalability for optimization procedures, with only small loss of performance (less than 7% in weighted schedulability, and no more than 4% in optimization objectives).

To What Extent Can Motor Imagery Replace Motor Execution While Learning a Fine Motor Skill?

Motor imagery is generally thought to share common mechanisms with motor execution. In the present study, we examined to what extent learning a fine motor skill by motor imagery may substitute physical practice. Learning effects were assessed by manipulating the proportion of motor execution and motor imagery trials. Additionally, learning effects were compared between participants with an explicit motor imagery instruction and a control group. A Go/NoGo discrete sequence production (DSP) task was employed, wherein a five-stimulus sequence presented on each trial indicated the required sequence of finger movements after a Go signal. In the case of a NoGo signal, participants either had to imagine carrying out the response sequence (the motor imagery group), or the response sequence had to be withheld (the control group). Two practice days were followed by a final test day on which all sequences had to be executed. Learning effects were assessed by computing response times (RTs) and the percentages of correct responses (PCs). The electroencephalogram (EEG ) was additionally measured on this test day to examine whether motor preparation and the involvement of visual short term memory (VST M) depended on the amount of physical/mental practice. Accuracy data indicated strong learning effects. However, a substantial amount of physical practice was required to reach an optimal speed. EEG results suggest the involvement of VST M for sequences that had less or no physical practice in both groups. The absence of differences between the motor imagery and the control group underlines the possibility that motor preparation may actually resemble motor imagery.

Calculation of Water Injection Response Time in a Low-Permeability Anisotropic Reservoir

We propose a model for predicting the response time of a production well responding to a change in pressure in the injection well while developing a low-permeability oil reservoir. The governing equation is derived based on a nonlinear seepage law and the method of successive substitution of steady states, and takes into account the anisotropy of the oil formation. We show that this model permits more accurate calculation than the conventional model.

IR Sensor-Based Gesture Control Wheelchair for Stroke and SCI Patients

This paper presents a novel and simple hand gesture recognition method to be used in rehabilitation of people who have mobility issues particularly stroke patients and patients with spinal cord injury (SCI). Keeping in mind the reach of such a system for a wider community of people with mobility issues, the proposed low-cost control device called gpaD—gesture pad provides an alternative solution to the joystick-based powered wheelchair control through hand gestures. In this method, IR sensors are used for identifying the simple gestures to control the powered wheelchair to move in any direction. In the proposed prototype system HanGes, a gesture pad that includes IR sensors, MCU and power management circuit is designed for gesture recognition and identification and a controller for driving motors is implemented. HanGes’s design, implementation, the response time calculations of the system, testing, performance evaluation with stroke and SCI patients are discussed in detail. With the average success rate of gesture recognition above 99.25% and response time as comparable with that of commercially available joystick controlled wheelchair, HanGes could be a possible alternative to the existing ones. With extensive experiments that demonstrate the accuracy of the system, the user experience, testing with patients, and the implementation cost indicate the superiority of our system.

성능위주설계자들의 화재실 범위 설정 방식에 따른 소요피난안전시간(RSET) 비교 및 오차산정에 관한 연구

'화재예방, 소방시설 설치유지 및 안전관리에 관한 법률'에 의하면 지하층 포함 30층 이상 고층 건축물에 대해 화재발생에 따른 위험성을 사전에 과학적으로 평가하여 재난발생 시 인명피해 및 재산피해를 최소화시킬 수 있도록 성능위주 설계를 실시해야 한다. 이에 따라 설계자는 컴퓨터 시뮬레이션 모델링 등 과학적인 분석 기법을 활용하여 거주자의 화재 및 피난 안전성을 평가하고 있다. 이 때, 인명안전성 평가를 위해 가용피난안전시간(ASET)과 소요피난안전시간(RSET) 을 산정하게 되는데 RSET 중에서도 가장 중요한 '반응시간(Response Time)'을 산정함에 있어 우리나라 사람들에 대한 실측 데이터에 기반한 명확한 법적 기준이 제시되지 못하고 있는 것이 현실이다. 이에 '소방시설 등의 성능위주설계 방 법 및 기준, 별표1'을 토대로 설계자별로 각각 상이한 값을 선택, 입력하거나 일본건축센터의 '건축방재계획지침'에 따라 계산하고 있는 경향을 보이고 있다. 따라서 본 연구에서는 최근 5년간 부산지역에서 성능위주 설계대상으로 지정된 고층 특정소방대상물을 대상으로 총 6명의 설계자가 실시한 성능위주 설계안 13건을 중심으로 RSET의 계산방법에 대해 비교 분석하였고, 특히 RSET 계산 시 결과값에 가장 큰 영향을 미치는 반응시간의 계산방법에 대한 결과를 비교하여 오차값을 산정하였다. The Installation, Maintence, and Safety Control of Fire-fighting Systems Act of South Korea regulates that over 30-storey high-rise buildings including underground spaces should vitally perform the Performance-based Design to minimize property damage and personal injury as a fire risk assessment in advance. Therefore a PBD designer such as a fire safety professional engineer evaluate occupant's life safety by a scientific methodology. In order to evaluate the life safety, fire safety designers calculate the Required Safety Egress Time (RSET) which does not have the legal criteria regarding the standard method of calculation yet. So this way has been showing different results depending upon the designer's choice, knowledges and experiences. In this study, RSET calculation methods by six designers respectively were analysed from the thirteen reports of real performance based design projects conducted in Busan for a last five years. In particular, the Response Time calculation methods which have the most powerful effect for figuring the RSET are compared with the other designer's to deduce an error value.

Large Forest Fire Spread Prediction: Data and Computational Science

The accurate prediction of forest fire propagation is a crucial issue to minimize its effects. So, several models have been developed to determine the forest fire propagation beforehand. Such models require several input parameters that, in some cases, cannot be known precisely in a real emergency. So, a Two-Stage methodology was developed to calibrate the input parameters to improve the quality of the prediction. This methodology was based on Genetic Algorithms which require the execution of many simulations. Moreover, when the fire is large some input parameters cannot be considered uniform among the whole fire and extra models must be introduced. One of these non-uniform parameters is wind. So, in this work a wind field model is introduced. This model implies more computation time and response time is the main constraint. The prediction must be provided as fast as possible to be useful, thus it is necessary to exploit all available computing resources. So a Hybrid MPI-OpenMP application has been developed to reach a response in the shortest possible time. This work focuses on reducing the execution time of a worker in a MPI Master/Worker structure analyzing the simulation software parts which compose the Fire Simulator System.

Increased alpha band activity indexes inhibitory competition across a border during figure assignment

Figure–ground assignment is thought to entail inhibitory competition between potential objects on opposite sides of a shared border; the winner is perceived as the figure, and the loser as the shapeless ground. Computational models and response time measures support this understanding but to date no online measure of inhibitory competition during figure–ground assignment has been reported. The current study assays electroencephalogram (EEG) alpha power as a measure of inhibitory competition during figure–ground assignment. Activity in the EEG alpha band has been linked to functional inhibition in the brain, and it has been proposed that increased alpha power reflects increased inhibition. In 2 experiments participants viewed silhouettes designed so that the insides would be perceived as figures. Real-world silhouettes depicted namable objects. Novel silhouettes depicted novel objects on the insides of their borders, but varied in the amount of hypothesized cross-border competition for figural status: In “Low-Competition” silhouettes, the borders suggested novel objects on the outside as well as on the inside. In “High-Competition” silhouettes the borders suggested portions of real-world objects on the outside; these compete with the figural properties favoring the inside as figure. Participants accurately categorized both types of novel silhouettes as “novel” objects and were unaware of the real world objects suggested on the outside of the High-Competition silhouettes. In both experiments, we observed more alpha power while participants viewed High- rather than Low-Competition novel silhouettes. These are the first results to show via an online index of neural activity that figure assignment entails inhibitory competition.

An <sc>fptas</sc> for Response Time Analysis of Fixed Priority Real-Time Tasks with Resource Augmentation

Response time analysis is required both for on-line admission of applications in dynamic systems and as an integral part of design tools for complex distributed real-time systems. We consider sporadic tasks with fixed-priorities and arbitrary deadlines to be executed upon a uniprocessor platform. Pseudo-polynomial time algorithms are known for computing exact worst-case response times for this task model. Nevertheless, the problem is known NP-hard and there cannot exist a constant approximation algorithm for response time computation, unless P=NP. We propose a fully polynomial time approximation scheme (FPTAS) for computing response time upper bounds under resource augmentation. The resource augmentation is defined as the processor speedup factor bounded by (1 + 1/k), where k <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">def</sup> [1 = ε]-1 for any constant ε ∈ (0;1), the FPTAS accuracy parameter. This algorithm is best possible in the sense that resource augmentation is indeed necessary for an efficient response time calculation.

Period Optimization Scheduling Algorithm Research of CAN Bus in Electric Vehicle

Improving the real-time performance of CAN bus is the focus problem of in-vehicle network design. It can improve the efficiency of message transmission to meet the needs of system control requirement. This paper firstly put forward the message response time calculation method of CAN bus considering a periodic correction coefficient. Secondly, based on the message response time calculation method using periodic correction coefficient, the periodic scheduling algorithm was designed and researched, using nonlinear programming method. The efficiency of periodic scheduling algorithm was validated by an optimization example of hybrid electric vehicle message set. It can be used in the CAN bus optimization design stage, and as a guidance for the CAN bus system design.