System Response Time Research Articles

Science and policy delay leading to loss of natural capital: case study of Te Waihora/Lake Ellesmere

ABSTRACT The paper analyses sources of delay in developing environmental interventions to address overallocation of groundwater and water quality degradation for Te Waihora/Lake Ellesmere, a coastal lake in the Canterbury Region of New Zealand. The analysis highlighted the length of time required to collect the science to understand an issue and to formulate and implement policy responses. It also identified delays due to scientific uncertainty, scientific controversies, disregarding science, decision processes, and the response time of the natural system. The absence of clear policy approaches and environmental outcomes in order to implement environmental legislation was a significant source of delay. Delays in implementing environmental interventions led to loss of natural capital with groundwater overallocation reducing flows in groundwater-fed streams and freshwater inflows to the lake, and land use intensification degrading groundwater, groundwater-fed streams, and lake water quality. The extent of development beyond sustainable limits during these delays may have permanently compromised the ability to implement comprehensive environmental interventions.

A construction and inspection technology of power emergency communication system based on Beidou

In order to improve the real-time performance of information transmission of power emergency communication system, the construction and inspection technology of power emergency communication system based on Beidou is proposed in this paper. Firstly, the differences between heterogeneous networks are described based on Beidou short message. Then, the fusion probability of heterogeneous network is calculated, and the optimal communication channel is obtained. Next, communication channel link is established, and the maximum transmission range is described. In addition, the network capacity is calculated, the congestion avoidance model is established, the bandwidth is obtained by defining the interference index of the information transmission channel, the total load during the construction and inspection process is calculated, and the construction and inspection of the power emergency communication system are realized.. Experimental results show that the proposed technology has better performance in information utilization, network throughput and system response time.

Influence of brake chamber pressure and effective cross-sectional area on time delay of pneumatic braking system

To face the problem of freight safety and reduce the traffic accidents, the influence of the response time of the pneumatic braking system on the braking performance should be investigated, which can improve the safety level of vehicle. The mathematical model of the pneumatic braking response time was established in this paper. The parameters of the pneumatic braking time and the time delay characteristics of the pneumatic braking system was discussed. The results show that the pressure and effective cross-sectional area of the brake chamber are the main factors affecting the time delay of the pneumatic braking system. When the effective cross-sectional area of the brake chamber is certain, the push rod stroke of the brake chamber increases significantly with the increase of air pressure; when the brake chamber pressure is constant, the larger the effective cross-sectional area of the brake chamber, the greater the output thrust of the brake chamber push rod.

Potential analysis of current battery storage systems for providing fast grid services like synthetic inertia – Case study on a 6 MW system

Large-scale battery energy storage systems (BESS) already play a major role in ancillary service markets worldwide. Batteries are especially suitable for fast response times and thus focus on applications with relatively short reaction times. While existing markets mostly require reaction times of a couple of seconds, this will most likely change in the future. During the energy transition, many conventional power plants will fade out of the energy system. Thereby, the amount of rotating masses connected to the power grid will decrease, which means removing a component with quasi-instantaneous power supply to balance out frequency deviations the millisecond they occur. In general, batteries are capable of providing power just as fast but the real-world overall system response time of current BESS for future grid services has only little been studied so far. Thus, the response time of individual components such as the inverter and the interaction of the inverter and control components in the context of a BESS are not yet known. We address this issue by measurements of a 6 MW BESS's inverters for mode changes, inverter power gradients and measurements of the runtime of signals of the control system. The measurements have shown that in the analyzed BESS response times of 175 ms to 325 ms without the measurement feedback loop and 450 ms to 715 ms for the round trip with feedback measurements are possible with hardware that is about five years old. The results prove that even this older components can exceed the requirements from current standards. For even faster future grid services like synthetic inertia, hardware upgrades at the measurement device and the inverters may be necessary.

Estimation of Water Vapor Density in Adiabatic Mixing of Cryogenic Gas and Moist Air

Concentration distribution is essential for the emergency disposal of cryogenic fuel leakage. In the dispersion process of cryogenic gas, its concentration is greatly influenced by the atmospheric water vapor. The authors have presented an adiabatic mixing model to derive the concentration of the cryogenic gas, in which the value of water vapor density is obtained by referring to the NIST database continuously. However, it is difficult to achieve fast system response times for real-time monitoring systems when calling NIST. Thus, a simple algebraic model of water vapor density with high calculation efficiency is necessary. Based on the detection of temperature and the solution of water vapor partial pressure, a calculation model was developed. For a given initial ambient temperature and relative humidity, the dew point could be solved by Qian’s correlation. By temperature comparisons of the mixture cloud, dew point, and triple point, the water vapor partial pressure can be calculated by the Goff–Gratch formulation. Then, the water vapor density during the temperature declining process can be derived via EOS. The results show that the model has high estimation accuracy, and has a close mean deviationof 0.08%to the IAPWS 95 of 0.03%. The increase in the computation efficiency was confirmed as +67% under nine testing points. The model facilitates the engineering utilization of the adiabatic mixing model for cryogenic fuel leakage monitoring.

Mixed-model assembly line balancing problem considering learning effect and uncertain demand

An assembly line system is a manufacturing process in which parts are added in sequence from workstation to workstation until the final assembly is produced. In a mixed-model assembly line balancing problem, tasks belonging to different product models, are allocated to workstations according to their processing times and precedence relationships amongst tasks. The research parlayed two features, learning effect and uncertain demand, into the conventional mixed-model assembly line balancing model, which is the main contribution of our paper. Both features can affect the new decision appeared in the stated problem — the level of production. The problem setup as well as the new decisions considered in the problem are novel. The proposed model optimized two objectives, total expected cost and average cycle time. To solve the model, a mixed integer-based heuristic and a customized variable neighborhood search method is proposed. The algorithms are examined for two different system response time requirements. Computational results showed that the mixed integer-based heuristic is more efficient if there is enough response time for the decision making process. On the contrary, the customized variable neighborhood search method can deliver promising results under real-time conditions. The Pareto-optimal set can be generated, which provides the managers with multiple choices for different cost and cycle time combinations.

Performance enhancement of phase change materials in triplex-tube latent heat energy storage system using novel fin configurations

Phase change material (PCM) has promising applications as an energy storage material in thermal energy storage (TES) systems. However, the low thermal conductivity of PCM limits its applications. To reduce the response time of TES systems, various configurations of fins are used to improve the heat transfer performance of PCM. The Y-structured fins utilize the Y-structure, a common structure in nature, and this study investigates the different structures of Y-shaped fins and the effect of HTF on melting time. A numerical research method based on the enthalpy-porosity method is adopted used for the study. The numerical model of the study is validated using previous experimental data. The simulation results have been obtained, including solid–liquid interface contours, isotherm contours, and evolution of the PCM liquid fraction. The results show that the melting process of the PCM is divided into three main stages and integrated solid fins within the PCM effectively reduce the melting time. Under certain operating conditions, reducing the fin thickness, increasing the fin angle, and increasing the HTF temperature can effectively reduce the PCM melting time. Transient heat transfer rates and dimensionless quantities are analyzed based on numerical results. This study provides potential applications of novel fin structures for new industrial products related to thermal energy storage and management.

Settling Time Optimization of a Critically Damped System with Input Shaping for Vibration Suppression Control

The input shaping technique is widely used as feedforward control for vibration suppression of flexible dynamic systems. The main disadvantage of the input shaping technique is the increasing system time response since the input shaper contains time delay parts. However, with the same reference input, the actuator effort in the case of using an input shaper is smaller than the one in the case without an input shaper. Thus, it is possible to decrease the system response time by designing the feedback controller to maximize the actuator effort. This paper proposes a design approach to design the Proportional-Derivative (PD) controller for position control of the actuator so that the settling time of the flexible system with input shaper is minimized. The actuator system with a PD controller is equivalent to a critically damped system, and the condition for the controller gains is established. In addition, the settling time and actuator effort with shaped step input are calculated. The controller gains can be determined by solving the settling time optimization problem with the actuator effort constraint. The effectiveness of the proposed approach is verified via experiments with an overhead crane model.

Comparing the Observable Response Times of ACC and CACC Systems

This paper analyzes trajectory observations from vehicles driving in platoon formation and they are equipped with Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) systems; aiming to quantify response delays. When a preceding vehicle induces a perturbation, the delay until the reaction of the following vehicle, often quoted as observable response time, can have negative implication to the traffic flow and other factors such as energy consumption, stability and safety. Quantifying such delays can help towards more realistic traffic simulation modeling. The analysis is performed based on empirical observations from three well-known experimental campaigns in the literature with data from ACC-driven and CACC-driven vehicle platoons. Three state-of-the-art techniques were implemented to provide quantitative results for the observed response times. The benefits and downsides of each technique are discussed as well. The results show that ACC systems do not exhibit a significant improvement compared to human drivers, yet, it can be concluded that the additional vehicle-to-vehicle communication incorporated in the CACC systems allows for a substantially higher traffic flow and possibly other benefits.

Towards a cooperative hierarchical healthcare architecture using the HMAN offloading scenarios and SRT calculation algorithm

The Internet of medical things (IoMT) is one of the most promising fields that is expected to rapidly expand in the near future. Consequently, vast amounts of data will be generated, necessitating faster and more intensive processing capabilities. Several healthcare architectures based on Edge/Fog technologies have been created to lower healthcare expenses and provide better and more reliable services. Scalability, availability, capacity, latency, and privacy are some of the most pressing issues to consider when designing such architectures due to the critical and sensitive nature of healthcare data. To contribute to the reliability and robustness of electronic health services, this work proposes Healthcare Metropolitan Area Network (HMAN), a cooperative hierarchical Edge/Fog computing-based architecture for the urban healthcare systems. The presented architecture suggests HMAN offloading scenarios and system response time calculation (HOSSC) algorithm which is specially designed to provide an abundance of offloading and processing scenarios within the network. The architecture also connects patients to the healthcare system by utilising the existing infrastructure in cities (e.g. medical centres and hospitals). Simulation results revealed that the designed architecture produced a ubiquitous and scalable healthcare system with promising and competitive performance, such as the computing capacity and service availability, by adopting multiple cooperative hierarchical offloading scenarios across the framework units. Moreover, the HMAN system was evaluated for latency and found to be very robust, with a short response time ranging between 6.043 and 31.45 ms in responding to 1 to 300 patients simultaneously sending. In addition to these appealing features, the proposed architecture ensures patients' privacy because the data are locally stored and processed in the most anticipated scenarios. The proposed architecture is a viable solution to providing healthcare services to a large number of patients.

IoT-fog-based healthcare 4.0 system using blockchain technology.

Real-time tracking and surveillance of patients' health has become ubiquitous in the healthcare sector as a result of the development of fog, cloud computing, and Internet of Things (IoT) technologies. Medical IoT (MIoT) equipment often transfers health data to a pharmaceutical data center, where it is saved, evaluated, and made available to relevant stakeholders or users. Fog layers have been utilized to increase the scalability and flexibility of IoT-based healthcare services, by providing quick response times and low latency. Our proposed solution focuses on an electronic healthcare system that manages both critical and non-critical patients simultaneously. Fog layer is distributed into two halves: critical fog cluster and non-critical fog cluster. Critical patients are handled at critical fog clusters for quick response, while non-critical patients are handled using blockchain technology at non-critical fog cluster, which protects the privacy of patient health records. The suggested solution requires little modification to the current IoT ecosystem while decrease the response time for critical messages and offloading the cloud infrastructure. Reduced storage requirements for cloud data centers benefit users in addition to saving money on construction and operating expenses. In addition, we examined the proposed work for recall, accuracy, precision, and F-score. The results show that the suggested approach is successful in protecting privacy while retaining standard network settings. Moreover, suggested system and benchmark are evaluated in terms of system response time, drop rate, throughput, fog, and cloud utilization. Evaluated results clearly indicate the performance of proposed system is better than benchmark.

Digital Transformation of Tourism Industry and Smart Tourism Recommendation Algorithm Based on 5G Background

As a hot issue of current research, tourism information service has higher and higher requirements for intelligent construction. Tourism service recommendation is the embodiment of smart tourism. However, there are still obvious deficiencies in solving the problem of Internet information load and improving user experience. Through functional analysis, architecture design, selection of relevant development frameworks, and improvement of collaborative filtering algorithms, a stable, reliable, high-performance, multi-functional intelligent travel recommendation system can be developed that can complete personalized recommendations. It can achieve the purpose of improving the efficiency and accuracy of recommendation and recommending tourism-related information to users in a targeted manner. Analyze the test plan and test the recommended algorithm module. In the case of different concurrency and database levels, the system response time is 0.9 s and 1 s, respectively. And in the case of high throughput, the system response time is 1.5 s, indicating that the system is running stably. It not only tested the storage and calculation of big data but also improved the usability of the travel information service recommendation system and the user experience of the system.

Intelligent Vehicle Engine Dynamic Test System Based on Internet of Things

In the context of technological modernization in the field of automotive engine testing, the development of an intelligent automotive engine testing system based on IQ has become an important trend in the future. This paper mainly studies the development of engine test software platform, the technical control of test process conditions, and the intelligent conversion of important components such as temporary fuel flow meters. By comparing the traditional bench test system and the dynamic test system based on the Internet of Things, the efficiency of data information transmission, information security, perception ability, and response speed between them are compared, and the intelligent dynamic engine detection based on the Internet of Things is found. The system is more secure and more efficient in information transmission, with a 12% increase in perception performance and a 48% increase in system response time. This also fully shows that the intelligent dynamic engine detection system based on the Internet of Things will be more suitable for current equipment and can also be detected more accurately, which can realize effective supervision of the running status of the test prototype and remote online feedback of the analysis results, and solve the engine test process. It solves the problem of efficient, reliable, and safe transmission and transmission of data and information between all levels and layers, and improves the ability of rapid perception and response in the process of engine testing.

Estimating the response time of a data-intensive computing environment

Introduction: The amount of digital data is constantly growing as well as the need for its storage and processing for various purposes. To conduct data analysis, high-performance computing environments associated with parallelization methods, and, accordingly, data-intensive applications are used. The lack of quality tools for evaluating the effectiveness of the process of parallel data processing or tasks leads to excessive allocation of resources. Purpose: To develop mathematical models of data-intensive computing environments and methods for their performance analysis, i.e., for estimating the average system response time based on the data on system performance at the level of subtask solving. Results: We present a mathematical model of a parallel computing system in the form of a queueing system with parallel query processing on various architectures, including non-Poisson input flow and non-exponential service times. As a method for analyzing the average response time, we use a combination of simulation modeling with one of the machine learning methods (artificial neural networks). The effectiveness of the method is confirmed by numerical experiments and depends neither on the type of input flow, nor on the type of distribution of query service times, nor on the number of servers in the nodes of the system. The approximation error of the average response time does not exceed 10%, which makes it possible to optimize the generally accepted resource allocation, significantly reducing the amount of the resources. Practical relevance: The presented models and the method of their analysis can be used for efficient planning and allocation of resources for data-intensive systems.

Mid‐infrared dissolved CO2 measurement system using the ultra‐compact multipass cell

AbstractTo measure natural gas hydrate, a mid‐infrared dissolved CO2 measurement system is designed using the tunable diode laser spectroscopy with ultra‐compact multipass cell. The QCL laser of 4319 nm has a scanning range from 2315.05 to 2315.40 cm−1, which contains 12CO2 and 13CO2 for isotope measurement and wide range of concentration detection. The optimized 3f + 1f wavelength modulation method reduces the limit of detection to 7.1 ppbv. An ultra‐compact multi‐pass cell with effective optical path length of 6.3 m and small volume of 15 ml is designed to achieve the system response time of 40 s. The dissolved CO2 sensing system has been used in deep sea natural gas hydrate detection.

Performance Assessment of a Sensor-Based Variable-Rate Real-Time Fertilizer Applicator for Rice Crop

Variable-rate technology (VRT) may reduce input costs, increase crop productivity and quality, and help to protect the environment. The present study was conducted to evaluate the performance of a variable-rate fertilizer applicator for rice (Oryza sativa L.). Three replications were conducted, each of which was divided into four plots. Field performance of the system was assessed at different nitrogen levels (N1 to N4, i.e., 75, 125, 175, 225 kg ha−1), growth stages (tillering, panicle initiation, heading), and heights (40, 60, 80, 100 cm) of the sensor from the crop canopy. Fertilizer rate was at minimum 12.59 kg ha−1 at 10 rpm of drive-shaft rotational speed and at maximum 50.41 kg ha−1 at 40 rpm. The system response time was within the range of 3.53 to 4.93 s, with overall error ranging between 0.83% to 4.92%. Across different growth stages, when fertilizer rate was increased from N1 to N4, NDVI increased from 0.49 to 0.69. Hence, drive-shaft rotational speed is decreased from 25 to 7 rpm to shift the application rate from 30.83 to 9.15 kg ha−1. There was a 45% reduction in total fertilizer rate applied by the system, with respect to the recommended rate.

Exploration of micro-video teaching mode of college students using deep learning and human-computer interaction.

In order to improve the efficiency of teaching and learning in Colleges and Universities (CAUs), this work combines the Browser/Server (B/S) framework with Model View Presenter (MVP) technology to build a college student–oriented micro-video teaching system based on Deep Learning (DL) and Human–Computer Interaction (HCI) technology. Firstly, it makes an in-depth analysis of the problems in the classroom teaching of Chinese CAUs. Three functional modules are designed for the micro-video online teaching platform: video management, user learning, and system management. Then, it uses MVP technology to analyze the use-cases of these three functional modules in detail. Based on this, the micro-video online teaching platform is designed using the B/S framework. The teaching platform interface layer realizes the HCI between the platform and users. The business logic layer responds to the user requests submitted and returns the processing results to the interface layer. Finally, the function test and stress test of each module of the micro-video online teaching platform is carried out. The test results show that the response time of the proposed micro-video teaching platform increases with the number of users. Under the peak concurrent users, the system response time is 6 s, without abnormalities. Meanwhile, the proposed teaching platform has improved students' satisfaction with classroom teaching by nearly 15% and improved the compactness of the college classroom by nearly 12%. When the number of virtual users increases and the number of services increases linearly, the Random Access Memory and Central Processing Unit growth rate is significantly lower than that of the number of services. These outcomes indicate that many system resources are reused, and the system has good scalability, which can meet users' needs for the network video teaching system. The proposed teaching platform provides a new idea for applying DL and HCI technology in researching college students' micro-video teaching mode.

玉米播种位置动态补偿系统设计与台架试验分析

Aiming at the problem that the existing planters cannot accurately maintain the seeding spacing and row spacing in the field, the high-speed photography technology is used to analyze the seeding trajectory, so as to determine the key factors affecting the seeding position. First, a dynamic compensation system for maize seeding position based on fuzzy PID control was designed. In the dynamic compensation system, the biaxial angle sensor was used to detect the angle of seeding monomer, and the space rotation theory was used to calculate the offset of the seeding position. Then, the dynamic compensation of seeding position was completed by the fuzzy PID control servo electric push rod, and the response time of fuzzy PID control system was 0.035 s. When the seed spacing of maize was 30 cm, the conveyor speed was 1.67 m/s and the seed tray speed was 30 r/min. Finally, the bench test was carried out under the conditions of random disturbance signal, sinusoidal wave disturbance signal and random disturbance signal plus sinusoidal wave disturbance signal. The results showed that compared without dynamic compensation, the variation coefficient of the longitudinal grain spacing and the transverse grain spacing decreased by an average of 6.94 % and 9.16 %, respectively. In this way, this study can provide a reference for improving the stability of seeding row spacing and plant spacing.

Artificial Intelligence-Based Online Education System for University Music

Aiming at the problems that students in the traditional music teaching system seldom participate in the system interaction and the relatively few types of system transportable files, this research designs and researches the music teaching system in school through artificial intelligence technology, streaming media technology, and webcast technology. The system mainly designs specific online classroom teaching modules according to the main characteristics of college music teaching. The system mainly adopts the b/s framework. Through the system performance test, the system response time is less than 2.5 when 200 people visit. Even when 500 people visit, the response time exceeds 3S, but it also maintains a certain performance level.

Resource Cache Sharing System of Education Information Center Network Based on Internet of Things

The development of the internet of things has spawned new information concepts such as educational information sharing. Due to the openness of the internet of things, all kinds of mobile terminal devices can rely on the internet of things for data communication, information interaction, and resource sharing. Although the development of the internet of things has brought convenience to people’s lives, the internet of things is facing severe challenges in the fields of internal data sharing and cache sharing of educational information. The existing resource sharing systems do not fully consider the problems of privacy, shared data security, and data access control. This paper mainly studies the network integrated resource cache sharing system of the education information center based on internet of things. The data management system of the network education information center is developed on the basis of the school teaching management system and lifelong education public service platform, combined with the actual situation of student information. This paper combines the enrollment and information workflow of the student information management website, analyzes the problems existing in the current workflow, and then uses computer technology to standardize and transform the workflow, realize the information of the built-in resources in the data management, and solve the problems of data cache sharing and data statistics in the management of the education information center. The simulation results show that with the increase in the number of concurrent threads, the average response time of the edge cloud system deployed with two servers is smaller than that of the edge cloud system deployed with a single server, and the cloud system has good scalability.