System Response Time Research Articles

Design and optimization of the Teaching evaluation system based on artificial intelligence

Abstract In today’s highly developed information society, the construction work of educational informatization has become the focus of the future development of major universities. This paper combines artificial neural networks and UML software modeling technologies to design a teaching evaluation system using artificial neural network technology. The system requirements are analyzed from three aspects: system feasibility, functional requirements, and neural network evaluation function. The proposed system performance requirements are based on these three aspects. The neural network approximation problem can be solved using the gradient descent method based on the BP neural network model. After a series of operations, such as data preprocessing, the Design of the teaching evaluation system is completed, realizing the joint role of teaching and neural network evaluation module, and at the same time, proposing a system optimization decision for the teaching quality aspect. The teaching evaluation system designed in this study passed the test as the average response time of the whole system was 94.366 seconds when the number of users was 100, and there was no phenomenon such as transaction unresponsiveness. After the use of the teaching system, the feedback from the students’ use shows that the number of computer science students who mastered more than 80% of the system concepts is 42, and the rest of the knowledge is concentrated in the number of people who mastered 40% to 80%.

A prostate seed implantation robot system based on human-computer interactions: Augmented reality and voice control.

The technology of robot-assisted prostate seed implantation has developed rapidly. However, during the process, there are some problems to be solved, such as non-intuitive visualization effects and complicated robot control. To improve the intelligence and visualization of the operation process, a voice control technology of prostate seed implantation robot in augmented reality environment was proposed. Initially, the MRI image of the prostate was denoised and segmented. The three-dimensional model of prostate and its surrounding tissues was reconstructed by surface rendering technology. Combined with holographic application program, the augmented reality system of prostate seed implantation was built. An improved singular value decomposition three-dimensional registration algorithm based on iterative closest point was proposed, and the results of three-dimensional registration experiments verified that the algorithm could effectively improve the three-dimensional registration accuracy. A fusion algorithm based on spectral subtraction and BP neural network was proposed. The experimental results showed that the average delay of the fusion algorithm was 1.314 s, and the overall response time of the integrated system was 1.5 s. The fusion algorithm could effectively improve the reliability of the voice control system, and the integrated system could meet the responsiveness requirements of prostate seed implantation.

An Assessment of Counter-Terrorism Options: A State Dependent Terror Queuing Model Perspective

The study is an application of a state-dependent queuing theory to evaluate the performance of counterterrorism (CT) options. The CT options examined include the Stick (use of force), the Carrot (non-coercive approaches), their combined variant, and covert agents. The model incorporates state transitions to capture the dynamic nature of terrorist recruitment processes in a CT environment. Performance measures are adapted from conventional queue frameworks to assess the effectiveness of these CT options in mitigating terrorist threats. The study analyses the CT options under an arithmetic progression pattern of terrorist recruitment and state transitions. The results demonstrate the importance of maximizing interdiction rate, discrimination rate, system efficiency, and intelligence integration while minimizing system unfairness factors, response time, and queue length for optimal CT operations. The results of the analysis also highlight a positive correlation between the Stick and the Carrot options, as well as between their intelligence-driven variants, emphasizing the need for a balanced and coordinated intelligence-driven CT approach. The study argues that relying solely on brute force or aggressive law enforcement measures without credible intelligence would be insufficient and counterproductive. It suggests leveraging syndromnized intelligence optimizing pseudo-terrorists (SIOP) agents for enhanced credibility, sufficient intelligence gathering, and covert supervision of terrorists’ compliance to Carrot instruments in the CT environment. The findings contribute to the existing literature on CT research and provide insights for informed decision-making in optimizing CT strategies. The study aims to support the development of more efficient and adaptive approaches to combat terrorism.

Effect of System Response Time on Brain Activity and Sense of Agency

Effect of System Response Time on Brain Activity and Sense of Agency

Construction of Cloud Computing Resource Allocation and Ideological and Political Education Platform Based on the Theme of Party History and Party Building

Abstract Party history and party-building education is an important carrier of party-building work in colleges and universities, and it is also an important content of cultivating and promoting socialist core values while party-building work is an effective way and the main hand of ideological and political work of students in colleges and universities. This paper takes the large amount of data generated in the process of ideological and political education resource allocation on the theme of party history and party building as the research object and builds a mapping relationship between tasks and ideological and political education resources according to certain strategies based on cloud computing resource allocation. A platform for allocating resources for ideological and political education has been designed and developed, which is based on a time series clustering algorithm and constructs resource overviews, sequence collections, and clustering modules. The functions of student behavior data collection and overview, feature calculation and selection, behavior time series clustering, and group feature analysis are realized, which enhances the efficiency of the ideological and political education resource platform. Functional and performance tests of the platform were completed, and the average system response times of the three modules were 75.05, 80.39, and 69.95ms, which were able to meet the actual application standards. With the help of the platform, the behavioral record data of 6,927 platform users were evaluated and practiced, and the user group classification and group characterization were carried out according to the output of the platform, which provided scientific suggestions for the distribution of ideological and political teaching resource services.

BERT4Cache: a bidirectional encoder representations for data prefetching in cache.

Cache plays a crucial role in improving system response time, alleviating server pressure, and achieving load balancing in various aspects of modern information systems. The data prefetch and cache replacement algorithms are significant factors influencing caching performance. Due to the inability to learn user interests and preferences accurately, existing rule-based and data mining caching algorithms fail to capture the unique features of the user access behavior sequence, resulting in low cache hit rates. In this article, we introduce BERT4Cache, an end-to-end bidirectional Transformer model with attention for data prefetch in cache. BERT4Cache enhances cache hit rates and ultimately improves cache performance by predicting the user's imminent future requested objects and prefetching them into the cache. In our thorough experiments, we show that BERT4Cache achieves superior results in hit rates and other metrics compared to generic reactive and advanced proactive caching strategies.

Design of Medical Equipment Management System Based on PCA-GRA-BK Algorithm

In recent years, medical technology has developed very well, and efficient management of medical equipment has become one of the key factors in improving hospital operational efficiency. This article proposes a design scheme for a medical equipment management system based on Principal Component Analysis (PCA), Grey Relational Analysis (GRA), and BK (Baker-King) algorithms. This research plan integrates these three algorithms to optimize the decision-making process of equipment procurement, maintenance, and replacement, in order to improve the decision-making efficiency and precision of the system. This study first analyzed the shortcomings of existing medical equipment management, and then compared the effectiveness of traditional management methods and this scheme by designing and implementing the integrated algorithm, verifying its effectiveness. In the decision precision testing experiment, it was shown that the PCA-GRA-BK algorithm based system achieved a precision of 82% and a recall rate of 75% in device classification tasks. In the experiment of resource utilization analysis, the PCA-GRA-BK algorithm significantly improved the efficiency of device utilization and reduced resource waste. In the system response time measurement experiment, the response time of the system based on PCA-GRA-BK algorithm increased to a maximum of 11.72 seconds. In the final user satisfaction survey evaluation, it was found that users felt good about the operation of the system. From the above results, it can be seen that these experimental results not only confirm the effectiveness of the system design based on PCA-GRA-BK algorithm, but also provide specific data support for further optimizing system performance.

Smart Agriculture system based on IoT reference architecture and service choreography

This paper presents a monitoring, control, and management system that allows the interoperability of multiple smart gateways in a greenhouse to bolster automatic decision making on water supplied to the crops in real-time. The system consists of several sensor nodes interconnected by Zigbee to measure ambient and soil parameters to control the greenhouse irrigation process. In addition, a web service is included to help the system manager to visualize and operate the greenhouse on a web platform. The system also supports human decision making to cope with undesirable and unexpected environmental events. Smart gateways enable data reading, storage and edge computing using automatic rules to manage actions in the greenhouse, as well as data transmission for centralized processing in cloud services. The service communication system layer is supported by choreography middleware for messaging distribution, which enables agile scalability. This research proposes a hybrid scheme and compares to a centralized scheme. The latency times in the choreography system were analyzed to find a suitable solution adapted to infrastructure deployment features. Numerical results shows that such an adaptive deployment of the irrigation services among edge and fog layers can reduce the computational load on the gateways, improve system response times, and enhance device performance.

A coordinated modelling and control of modified pumped storage governor with unified power flow controller to damp low frequency oscillations in power system for stochastic renewable penetrations

A modern power system network is more susceptible to oscillatory instability problem due to power oscillations caused by uncertain penetration of renewable sources. Also, pumped storage hydro power generation (PSHPG) is going to take important role for energy storage and management with varying renewable penetrations, but their governors need to be utilized efficiently for power oscillation damping. In this work a coordinated modified pumped storage governor with fractional parallel unified power flow controller (FPUPFC) has been modelled and controlled to damp angular frequency variations in power system. The prime objective of this work is to enhance efficacy of pumped storage hydro turbine governors integrated into an expert system with UPFC to take part in electromechanical oscillation damping. Here the governor is modified by fractional order PID action with additional phase compensation and in FPUPFC both series and shunt converters are controlled simultaneously by parallel fractional lead-lag based control action. The power system considered here consists of hydro generators of 100 MVA with 90.94 MW rated turbine output power with different operating conditions for two area 4 generators and 39 bus 10 generators multimachine renewable integrated system. It has been observed that efficacy of pumped storage hydro turbine governor action has been much improved when coordinated with FPUFC control action. A new hybridized modified differential evolution with fractional particle swarm optimization (MDEFPSO) is proposed to tune the parameters of proposed controller, with a multi-objective function considering variation in speed and real power deviations, settling time, overshoot and undershoot of system response.

Dynamic Characteristics and Optimization of Segmented Fork Arm Seat System

To improve the low-frequency vibration isolation performance and driving comfort of the engineering seat system, a segmented fork arm seat system is proposed. Firstly, the equivalent model of the n-level segmented seat system is established, the amplitude-frequency response function and phase-frequency response function of the segmented seat system are solved and analyzed. The theoretical study shows that, with the increase of segment levels, the response time of the seat system is shortened, and the attenuation rate of response amplitude is accelerated; with the increase of segment levels, the resonance peak value of the seat system tends to shift continuously, and the low-frequency vibration isolation range expands. Secondly, according to the actual application condition of a loader, the engineering structure of the 3-level segmented fork arm seat system was built, and the structure-stiffness parameters of the segmented fork arm seat system were optimized by multi-objective genetic algorithm. The optimization results show that the 3-level segmented fork arm seat system has obvious vibration reduction effect on the sensitive frequency band of the human body. The vibration reduction effect on road excitation increases by 63.2% on average under driving conditions, 75.8% on uneven road surface, and 65.2% under operating conditions, and the subjective comfort evaluation index of human body increases by two levels.

Iot and AI-Based MPPT Techniques for Hybrid Solar and Fuel Cell

Rising electricity demands necessitate advancements in energy generation efficiency and reliability, prompting increased interest in hybrid systems integrating solar and fuel cell renewable sources. This study proposes the MPPTs (maximum power point tracking) approach utilizing Internet of Things (IoT) for actual-time data collections from diverse sensors in a hybrid system. Sensors measuring solar irradiance, temperature, fuel cell performance, and energy storage levels feed data into AI algorithms, dynamically optimizing operational settings for enhanced energy extraction. The AI algorithms adapt to environmental changes, component deterioration, and energy consumption fluctuations, resulting in a continuous efficiency improvement. The proposed technique demonstrates superior tracking accuracy, boosting energy conversion efficiency from 88% to 94%, with a reduced system response time from 4.5 to 2.25 min. Performance metrics validate the effectiveness, suggesting potential for advanced control strategies in future renewable energy systems. Further research avenues include scalability, robustness, and cost-effectiveness for broader real-world applications.

Performance analysis of proportional feedback control and integral control in DC motors and speed control

Control systems play a crucial role in modern engineering and technology, and their stability and performance are vital for the success of various applications. This paper aims to explore the application and performance analysis of proportional feedback control (P control) in DC motors and integral control (PI control) in speed control. The following section provides an exposition of the fundamental principles underpinning P control and PI control, alongside an exhaustive account of their practical implementations within the Tinkercad and Octave software environments. The simulations carried out in Tinkercad serve as the basis for evaluating step responses associated with varying values, leveraging a 1Hz function generator. Subsequent analysis pertains to proportional-integral control through the utilization of Octave's PZmap and root locus methodologies, with specific regard to their implications for system stability and control performance in the context of speed control. The experimental outcomes reveal the aptitude of P control in scenarios demanding rapid responses, while establishing the superiority of PI control in the context of steady-state error mitigation. In the experimental analysis conducted, an evident trend emerged as Kp values were systematically increased within the framework of proportional feedback control. The primary observation related to the reduction in system response times, along with the concurrent rise in overshooting tendencies.

Towards an optimal frequency and time response of singe-tube pressure measurement systems under continuum-flow conditions

The pressure transmission tube, as part of a pressure measurement system, generally has a considerable influence on its dynamic characteristics. The paper deals with the mathematical modelling of the dynamic behaviour of pressure transmission tubes with the aim of providing guidelines for the optimal design of such systems in the frequency and time domains. The mathematical models used are based on linear wave theory and continuum flow mechanics with no-slip and isothermal boundary conditions. The frequency responses were evaluated in terms of frequency bandwidth and the transient step responses in terms of settling and rise times. Following a systematic analysis of these characteristic parameters, we derived an analytically formulated optimisation objective function defining the transition between the low-wavenumber and high-wavenumber pressure waves in the pressure transmission tubes. The demanded dynamic behaviour in the frequency and time domains can be achieved through an appropriate ratio between the actual tube radius and the so-called transition tube radius, which was derived as a function of the tube length, end volume and fluid properties.

Hollow waveguide CO2 laser sensing system for rapid detection of trace sulfur hexafluoride (SF6) gas

Sulfur hexafluoride (SF6) has been widely applied in electrical facilities due to its excellent electrical insulation and high-voltage arc extinguishing properties, although it is a potent greenhouse gas. Rapid detection of trace SF6 gas is significant for monitoring the operation safety of high-voltage power grid facilities and greenhouse gas emissions. In this work, a SF6 gas sensing system was proposed and built using a CO2 laser as the light source and a 700 μm bore Ag/AgI hollow glass waveguide (HGW) as the gas chamber and laser transmission channel. Sensing performances of the SF6 gas HGW sensors with different lengths were investigated. The gas sensing sensitivity and standard deviation (SD) of blank increase as the waveguide length increases. The limit of detection (LOD) decreases with waveguide length increase but the decline becomes less pronounced after the length exceeds 120 cm. The HGW length exhibits minor effect on the response and recovery time of the sensor system. The sensor sensitivity undergoes a slight reduction as the HGW is bent. Optimization of the sensing performance was achieved based on the straight 120 cm-length HGW SF6 gas sensor system. Its sensitivity reaches 0.384 dB/ppm and the LOD is 148 ppb with good cyclic response characteristics (response and recovery time 2–3 s). The present work provides a feasible idea for building up a trace SF6 gas sensing system with simple structure, easy operation and high performances.

Research on Tourism English Translation System Based on Fuzzy Clustering Algorithm

The emergence of economic globalization and the Internet have precipitated extensive and profound international exchanges and collaborations. Language barriers have surfaced as the primary impediment to effective international communication and cooperation. This study is dedicated to the development of a tourism English translation system utilizing the fuzzy clustering algorithm. The system's functionalities undergo testing and validation through black box testing. Key performance indicators like response time and throughput are scrutinized to evaluate the system's effectiveness. The performance evaluation involves monitoring specific checkpoints in test cases to ascertain whether the system aligns with the essential performance criteria. The system's response time and throughput take the forefront in this educational system assessment. Use-cases are categorized based on the number of online users, with the client's response time being assessed in each scenario. Successful completion of the criteria deems a use case qualified; conversely, failure designates it as unqualified, with any system deficiencies recorded within the testing framework. Data analysis reveals that the integration of the enhanced PCM algorithm elevates C-FCA's clustering data accuracy to 95%. Consequently, the findings signify that the fuzzy clustering algorithm significantly amplifies the precision of the tourism English translation system.

Optimization and testing of a Mass Spectrometer Leak Detection (MSLD) system

A rapid helium mass spectrometry leak detection method is established to respond to problems of low sensitivity and efficiency in detecting leaks in large vessels. The optimized multistage tandem leak detection system improves leak detection sensitivity by increasing the amount of gas entering the analysis chamber. By involving the main pumping system in the detection process, the effective pumping speed is increased, resulting in a significant reduction in system response time. Additionally, the optimal leak detection vacuum required for maximizing the leak velocity indicating gas movement is determined, thereby further decreasing the system’s response time. Our application demonstrates that the optimized leak detection system increases sensitivity by one to two orders of magnitude, reduces system response time by over 90%, and shortens evacuation time by 7 h. Ultimately, the optimized design of the vacuum system developed for large vessels demonstrates greatly improved leak detection efficiency and overall capability.

Electronics-Free Soft Robotic Knee Brace for Dynamic Unloading During Gait for Knee Osteoarthritis: A Proof-of-Concept Study

Abstract We present a novel electronics-free soft robotic knee brace which employs a closed-loop fluidic regenerative (CLFR) system for dynamic unloading in unicompartmental tibiofemoral osteoarthritis (OA). The existing dynamic unloaders are bulky, large, and heavy, and have low compliance likely due to the use of an electrical control box, which is eliminated in the CLFR system. The system consists of a commercial unloading knee brace, a spring-loaded bellow inserted under the heel inside a shoe, a soft-fluidic actuator (bladder), and tubing for fluid transfer. The novelty lies in the fact that the user's body weight (self-powered) compresses the bellow to provide energy to inflate the air bladder placed at the knee. As a result, the yielded pressure unloads the undesirable forces due to knee OA during the stance phase of gait while strategically applying no forces during the swing phase. The knee bladder contact pressure/force, the system response time, and the durability were evaluated via contact pressure measurements for six systems with varying bellow volumes and either pneumatic or hydraulic configurations. All systems produced safe pressure outputs for human skin within a tested bodyweight range of 60–90 kg. Pneumatic and hydraulic systems achieved 250 ms and 400 ms pressurization response times, respectively. During cyclic loading, pneumatic and hydraulic systems demonstrated less than 1% and ∼10% pressure loss, respectively. Overall, the CLFR system created a promising electronics-free solution for dynamically unloading the knee during gait, indicating a potential new paradigm for knee braces.

Response Time of Cloud-Based Facial Recognition System Utilizing Homomorphic Encryption

Response Time of Cloud-Based Facial Recognition System Utilizing Homomorphic Encryption

Reshaping the yeast galactose regulon via GPCR signaling cascade

Dynamically regulated systems are preferable to control metabolic pathways for an improved strain performance with better productivity. Here, we harnessed to the G protein-coupled receptor (GPCR) signaling pathway to reshape the yeast galactose regulon. The galactose-regulated (GAL) system was coupled with the GPCR signaling pathway for mating pheromone via a synthetic transcription factor. In this study, we refabricated the dynamic range, sensitivity, and response time of the GAL system to α factor by modulating the key components of the GPCR signaling cascade. A series of engineered yeasts with self-secretion of α factor were constructed to achieve quorum-sensing behaviors. In addition, we also repurposed the GAL system to make it responsive to heat shock. Taken together, our work showcases the great potential of synthetic biology in creating user-defined metabolic controls. We envision that the plasticity of our genetic design would be of significant interest for the future fabrication of novel gene expression systems.

The impact and value of information system audit enterprises risk management influencing quality assurance and system optimization—a touch from supply chain domains

The industries significantly rely on information technology for effective operations; however, there are hazards like data breaches and system breakdowns. Information system audits are essential to reducing these risks, ensuring quality control, and optimizing the system. These audits evaluate gaps in controls, non-compliance concerns, and vulnerabilities, allowing for the installation of efficient risk mitigation measures. Information system audits are essential for locating and reducing hazards related to an organization's information systems.Vulnerabilities, threats, and control flaws can be found through routine audits, which then allows for the deployment of the necessary controls and risk-reduction measures. Additionally, audits support quality assurance by assessing data reliability, accuracy, and completeness, as well as system performance, regulatory compliance, and industry best practices.The deployment of remedial steps to improve data integrity and system reliability is made possible by their assistance in assisting organizations in identifying gaps and flaws. Information system audits also aid system optimization by revealing details about the functionality and performance of the system.  An extensive evaluation of the literature and case study analysis was used to perform the research.For the analysis of this research, a sequential mixed technique (qualitative and quantitative) study was conducted. Delphi questionnaires were used twice to conduct the study. It encompasses organizations and entities involved in various aspects including but not limited to logistics companies, freight carriers, shipping and distribution firms, public transportation agencies, and supply chain service providers. Data from the semi-structured interviews for the qualitative study were collected via a Delphi survey, and 14 nodes and six themes were then generated.Audits assist organizations in identifying areas for improvement and informing decisions about system upgrades or alterations by analyzing system utilization, response times, resource allocation, and scalability. The results of this study highlight the importance of information system audits in assuring the prosperity, effectiveness, and resilience of businesses engaged in supply chain operations. Organizations can attain a greater level of enterprise risk management, quality assurance, and system optimization, which will improve supply chain operations in general, by managing risks, improving data quality, and optimizing system performance.