Response Time Delay Research Articles

Fine Motor Assessment in Upper Extremity Using Custom-Made Electronic Pegboard Test.

A fine motor test involves the manipulation of smaller objects with fingers, hands, and wrists. This test is an integral part of the evaluation of an upper extremity function. Nine Hole Peg Test (NHPT) is one among such tests which assess the ability to manipulate pegs with the thumb and finger. There is a need to develop a fine motor assessment tool which is reproducible and mimics closely the natural movement of hands. The aim of this work is to develop an electronic pegboard which is easy to administer and efficient in terms of time. Pegboard device is modified and standardized by (1) Adding electronic circuits to custom-made pegboard and programmed using a microcontroller (ATmega2560), (2) Following a specific sequence in placing and picking the pegs from the board, and (3) Using Infrared sensor and robust algorithm to ensure one peg movement at a time. The setup is administered on 15 healthy participants (nine females, six males aged between 21 and 80) and the outcome is compared with the results of traditional NHPT. Predefined sequence in moving the pegs and electronic timer features provide reliable results for repeated measurements and facilitate storing test score in a digital repository. This data could be used as reference data during the follow-up visits. The maximum difference between the measured timing between the present setup and traditional NHPT is about 6.7%. It is important to note that, due to inherent delay (response time) in the traditional NHPT, when compared to present setup the measured timing is always on the higher side. Nondependency on the manual stopwatch to record the time and hands-free of any wearable device are the advantages of the present setup.

ComFlex: Composable and Flexible Resource Management for the IoT

The Internet of Things (IoT) enables new services, such as smart home and smart healthcare integrating various resources of networked devices. However, managing IoT resources is very challenging because a device may have multiple different resources and the service accesses subsets of the resources in multiple devices. To simplify the resource management, the existing IoT frameworks provide resource models and protocols for manufacturers and programmers, but their access granularity is too coarse grained causing overprivilege problems, or too fine grained causing management overheads. To avoid the overprivilege problems without the management overheads, this work proposes a new composable and flexible resource management scheme and implements its prototype compiler-runtime framework called ComFlex. The ComFlex compiler allows manufacturers to register their devices as composition of fine-grained resources by inheriting the existing interfaces of the resources, and programmers to define their own access granularity as a virtual resource that consists of the fine-grained resources of multiple devices. The ComFlex runtime supports fine-grained access control without additional overheads by mapping the fine-grained resources of the virtual resource into physical resources of different devices. To evaluate the ComFlex framework, this work implements 52 resources on 14 devices and six IoT services with ComFlex and an existing fine-grained resource management scheme. Compared to the existing scheme, the ComFlex framework supports the IoT services with 40.2% fewer lines of code and 80.9% less discovery time, without any overprivilege problem and response time delay.

Research on Mobile English Learning System Based on iOS

In order to improve the use experience of mobile learning and reduce the response delay caused by the slow positioning of system resources, research on mobile English learning systems based on iOS is proposed. Firstly, the value of realizing mobile learning is objectively analyzed, and the practical significance of the research is clarified from the perspectives of social development and learning conditions. On this basis, taking the intelligent client equipped with an iOS operating system as the hardware condition of the system, the system architecture, including data access layer, business logic layer, and presentation layer, is constructed by MVC. In the model module, it is divided into ten difficulty levels by using the frequency of vocabulary, the length of words, and the number of syllables of a single word. The learning resources of the reading class are uniformly represented by the vector space model, and the improved TF-IDF is used to calculate the weight of eigenvalues in the resources. According to the calculation results, the resources are also divided into ten difficulty levels, and the divided resources correspond to their respective databases and use regular expressions to find the learning resources that match the access request. Finally, with the support of the iOS protocol, the feedback mechanism between each module is constructed by Express.js. By analyzing the access requests sent and received by the view, the timely call to the target database resources is realized to improve the response rate of the system. The test results show that the function of the designed system can be realized stably, and the module response delay time is stable within 1s; under the ideal network environment, the buffer delay is in the range of 0.4–0.6 s, and the loading delay is no more than 1.8 s when the network speed is 3 Mpbs, which has a good user experience.

Moderating effects of out-of-hospital cardiac arrest characteristics on the association between EMS response time and survival

BackgroundAlthough several Utstein variables are known to independently improve survival, how they moderate the effect of emergency medical service (EMS) response times on survival is unknown. ObjectivesTo quantify how public location, witnessed status, bystander CPR, and bystander AED shock individually and jointly moderate the effect of EMS response time delays on OHCA survival. MethodsThis retrospective cohort study was a secondary analysis of the Resuscitation Outcomes Consortium Epistry-Cardiac Arrest database (December 2005 to June 2015). We included all adult, non-traumatic, non-EMS witnessed, and EMS-treated OHCAs from eleven sites across the US and Canada. We trained a logistic regression model with standard Utstein control variables and interaction terms between EMS response time and the four aforementioned OHCA characteristics. Results102,216 patients were included. Three of the four characteristics – witnessed OHCAs (OR = 0.962), bystander CPR (OR = 0.968) and public location (OR = 0.980) – increased the negative effect of a one-minute delay on the odds of survival. In contrast, a bystander AED shock decreased the negative effect of a one-minute response time delay on the odds of survival (OR = 1.064). The magnitude of the effect of a one-minute delay in EMS response time on the odds of survival ranged from 1.3% to 9.8% (average: 5.3%), depending on the underlying OHCA characteristics. ConclusionsDelays in EMS response time had the largest reduction in survival odds for OHCAs that did not receive a bystander AED shock but were witnessed, occurred in public, and/or received bystander CPR. A bystander AED shock appears to be protective against a delay in EMS response time.

THE STABILITY OF THE CRITICAL POINTS OF THE GENERALIZED GAUSE TYPE PREDATOR-PREY FISHERY MODELS WITH PROPORTIONAL HARVESTING AND TIME DELAY

In the marine ecosystem, the time delay or lag may occur in the predator response function, which measures the rate of capture of prey by a predator. This is because, when the growth of the prey population is null at the time delay period, the predator’s growth is affected by its population and prey population densities only after the time delay period. Therefore, the generalized Gause type predator-prey fishery models with a selective proportional harvesting rate of fish and time lag in the Holling type II predator response function are proposed to simulate and solve the population dynamical problem. From the mathematical analysis of the models, a certain dimension of time delays in the predator response or reaction function can change originally stable non-trivial critical points to unstable ones. This is due to the existence of the Hopf bifurcation that measures the critical values of the time lag, which will affect the stabilities of the non-trivial critical points of the models. Therefore, the effects of increasing and decreasing the values of selective proportional harvesting rate terms of prey and predator on the stabilities of the non-trivial critical points of the fishery models were analysed. Results have shown that, by increasing the values of the total proportion of prey and predator harvesting denoted by qx Ex and qy Ey respectively, within the range 0.3102 ≤ qx Ex ≤ 0.9984 and 0.5049 ≤ qy Ey ≤ 0.5363, the originally unstable non-trivial critical points of the fishery models can be stable.

FACTORS CONTRIBUTING TO DELAYED AMBULANCE RESPONSE TIME USING AMBULANCE VEHICLE LOCATOR AND GLOBAL INTEGRATING SYSTEM (AVL- GIS) AT HOSPITAL UNIVERSITI SAINS MALAYSIA


 
 
 This study aims to determine ambulance response time in KubangKerian district, Kelantan, Malaysia using Ambulance Vehicle Locator and Global Integrating System (AVL-GIS) device and the factors associated with delayed response time. This was a 6-months prospective, cross-sectional study conducted at Emergency and Trauma Department, Hospital Universiti Sains Malaysia (HUSM) in Kubang Kerian, Kelantan, Malaysia. The possible factors identified to have caused delayed ambulance response time from previous literature were included in this study. All prehospital cases from September 2017 until February 2018 attended to by AVL- GIS installed ambulances were included in this study. Data were obtained from the standardized prehospital Proforma forms and extracted from AVL-GIS using iGPS software. Simple and multiple logistic regression tests were used to determine the factors associated to delayed response time. From 505 cases, 75% found to be delayed case meanwhile 25% is non delayed case as defined in study protocol. Further analysis on delayed cases show that call duration, caller type, traffic condition, travelling time and team allocation time were associated with delayed ambulance response time. Evaluation of each component contributing to delayed ambulance response time is needed for intervention to improve prehospital care in the future.
 
 

A Federated Learning Approach to Anomaly Detection in Smart Buildings

Internet of Things (IoT) sensors in smart buildings are becoming increasingly ubiquitous, making buildings more livable, energy efficient, and sustainable. These devices sense the environment and generate multivariate temporal data of paramount importance for detecting anomalies and improving the prediction of energy usage in smart buildings. However, detecting these anomalies in centralized systems is often plagued by a huge delay in response time. To overcome this issue, we formulate the anomaly detection problem in a federated learning setting by leveraging the multi-task learning paradigm, which aims at solving multiple tasks simultaneously while taking advantage of the similarities and differences across tasks. We propose a novel privacy-by-design federated learning model using a stacked long short-time memory (LSTM) model, and we demonstrate that it is more than twice as fast during training convergence compared to the centralized LSTM. The effectiveness of our federated learning approach is demonstrated on three real-world datasets generated by the IoT production system at General Electric Current smart building, achieving state-of-the-art performance compared to baseline methods in both classification and regression tasks. Our experimental results demonstrate the effectiveness of the proposed framework in reducing the overall training cost without compromising the prediction performance.

Site Selection of Fire Stations in Large Cities Based on Actual Spatiotemporal Demands: A Case Study of Nanjing City

The rapid expansion of cities brings in new challenges for the urban firefighting security, while the increasing fire frequency poses serious threats to the life, property, and safety of individuals living in cities. Firefighting in cities is a challenging task, and the optimal spatial arrangement of fire stations is critical to firefighting security. However, existing researches lack any consideration of the negative effects of the spatial randomness of fire outbreaks and delayed response time due to traffic jams upon the site selection. Based on the set cover location model integrated with the spatiotemporal big data, this paper combines the fire outbreak point with the traffic situation. The presented site selection strategy manages to ensure the arrival of the firefighting task force at random simulated fire outbreak points within the required time, under the constraints of the actual city planning and traffic situation. Taking Nanjing city as an example, this paper collects multi-source big data for the comprehensive analysis, including the full data of the fire outbreak history from June 2014 to June 2018, the traffic jam data based on the Amap, and the investigation data of the firefighting facilities in Nanjing. The regularity behind fire outbreaks is analyzed, the factors related to fire risks are identified, and the risk score is calculated. The previous fire outbreak points are put through the clustering analysis, the spatial distribution probability at points in each cluster is calculated according to the clustering score, and the random fire outbreak points are generated via the Monte Carlo simulation. Meanwhile, the objective emergency response time is set as five minutes. The average vehicle speed for each road in the urban area is calculated, and the actual traffic network model is built to compute the travel time from massive randomly-distributed simulated fire points. The problem is solved by making the travel time for all simulated demand points below five minutes. At last, the site selection result based on our model is adjusted and validated, according to the planned land use. The presented method incorporates the view of the spatiotemporal big data and provides a new idea and technical method for the modification and efficiency improvement of the fire station site selection model, contributing to a service cover ratio increase from 58% to 90%.

On the Improvement of ROS-Based Control for Teleoperated Yaskawa Robots

This paper deals with Yaskawa robots controlling the Robot Operating System (ROS) for teleoperation tasks. The integration of an open-source ROS interface based on standard Motoman packages into control loop leads to large trajectory tracking errors and latency, which are unsuitable for robotic teleoperation. An improved version of the standard ROS-based control is proposed by adding a new velocity control mode into the standard Motoman ROS driver. These two approaches are compared in terms of response time and tracking delay. Investigations applied on the Yaskawa GP8 robot while using the proposed improved ROS-based control confirmed trajectory tracking and latency improvements, which can achieve 43% with respect to standard control.

Performance on a modified signal detection task of attention is impaired in male and female rats following developmental exposure to the synthetic progestin, 17α-hydroxyprogesterone caproate

Based on evidence that the developing mesocortical dopamine pathway is sensitive to progestins, in the present study we tested the hypothesis that attention, a fundamental component of successful cognitive behavior, is disrupted by developmental exposure to the synthetic progestin, 17-α-hydroxyprogesterone caproate (17-OHPC). To assess attentional impairments, a modified signal detection task was utilized with three stimulus modalities: compound (light and tone), light alone, and tone alone, for four stimulus durations (2, 0.5, 0.25, 0.125 s). Adult rats were trained to push one lever if they detected the stimulus, and another lever if the stimulus was not presented. 17-OHPC animals were able to attend to the task, as evidenced by similar correct responses as controls. However, as the task became increasingly difficult at shorter durations, 17-OHPC animals made significantly more omissions compared to controls, suggesting that 17-OHPC treatment may disrupt attentional processes and/or delay response time. These findings add to the current body of literature demonstrating that exposure to 17-OHPC during development produces deficits in cognitive behavior in adulthood. These results may inform potential risks associated with 17-OHPC treatment in pregnant women with a history of preterm delivery who are commonly recipients of such treatment.

Response Time Analysis for Nonperiodic CAN Message Based on GI/G/1 Queue Model

Controller area network (CAN) has wide applications in modern industrial control systems. Automobile manufacturers use this communication protocol for vehicle control, which is subject to real-time and high-reliability performance. However, with the increasing actuators gathered in the vehicle, time delay will lead to a serious problem for the vehicle safety and performance control. Thus, the information transmission stability of the CAN message needs to be investigated. In order to find out the delay response time of nonperiodic CAN message in the vehicle bus area, the response of the message transmitted in the CAN bus is modeled based on the GI/G/1 queue theory. The test platform is developed to verify the methodology. In the experimental test, some conditions with different IDs, load ratios, and priorities are investigated. Experimental results are compared with the theoretical results, and the simulation results show that the method is valid and verify the real response delay time of nonperiodic CAN message.

COVID-19 mitigation by digital contact tracing and contact prevention (app-based social exposure warnings)

A plethora of measures are being combined in the attempt to reduce SARS-CoV-2 spread. Due to its sustainability, contact tracing is one of the most frequently applied interventions worldwide, albeit with mixed results. We evaluate the performance of digital contact tracing for different infection detection rates and response time delays. We also introduce and analyze a novel strategy we call contact prevention, which emits high exposure warnings to smartphone users according to Bluetooth-based contact counting. We model the effect of both strategies on transmission dynamics in SERIA, an agent-based simulation platform that implements population-dependent statistical distributions. Results show that contact prevention remains effective in scenarios with high diagnostic/response time delays and low infection detection rates, which greatly impair the effect of traditional contact tracing strategies. Contact prevention could play a significant role in pandemic mitigation, especially in developing countries where diagnostic and tracing capabilities are inadequate. Contact prevention could thus sustainably reduce the propagation of respiratory viruses while relying on available technology, respecting data privacy, and most importantly, promoting community-based awareness and social responsibility. Depending on infection detection and app adoption rates, applying a combination of digital contact tracing and contact prevention could reduce pandemic-related mortality by 20–56%.

A New Estimation Method of the PID Controller In Automatic Train Operation Systems

PID controller plays an important role in Automatic Train Operation systems. Many researches have been done on the PID parameters estimation. However, the traditional models simplified the characteristics of the trains in different speeds and operation modes. It was difficult to overcome the problems with different kinds of algorithms based on the traditional models, especially the accuracy requirement of the stopping distance. In this paper, a new model of the PID controller was proposed based on the practical train operation stages. And the different response time delay was considered besides of the transmission time delay. With this new model, an Improved Fruit Fly Optimization Algorithm was applied. The tracking performance were greatly improved both on running distance and real time. The simulation results showed a better performance than the traditional methods.

Mathematical modeling of tumor surface growth with necrotic kernels

A two‐dimensional tumor‐immune model with the time delay of the adaptive immune response is considered in this paper. The model is designed to account for the interaction between cytotoxic T lymphocytes (CTLs) and cancer cells on the surface of a solid tumor. The model considers the surface growth as a major growth pattern of solid tumors in order to describe the existence of necrotic kernels. The qualitative analysis shows that the immune‐free equilibrium is unstable, and the behavior of positive equilibrium is closely related to the ratio of the immune killing rate to tumor volume growth rate. The positive equilibrium is locally asymptotically stable when the ratio is smaller than a critical value. Otherwise, the occurrence of the delay‐driven Hopf bifurcation at the positive equilibrium is proved. Applying the center manifold reduction and normal form method, we obtain explicit formulas to determine the properties of the Hopf bifurcation. The global continuation of a local Hopf bifurcation is investigated based on the coincidence degree theory. The results reveal that the time of the adaptive immune system taken to response to tumors can lead to oscillation dynamics. We also carry out detailed numerical analysis for parameters and numerical simulations to illustrate our qualitative analysis. Numerically, we find that shorter immune response time can lead to longer patient survival time, and the period and amplitude of a stable periodic solution increase with the increasing immune response time. When CTLs recruitment rate and death rate vary, we show how the ratio of the immune killing rate to tumor volume growth rate and the first bifurcation value change numerically, which yields further insights to the tumor‐immune dynamics.

Dynamic operational characteristics and preliminary control of a packed liquid desiccant dehumidifier

Liquid desiccant dehumidifiers (LDDs) has attracted much attention due to its advantages of energy-saving and environmental protection. However, dynamic characteristics of LDDs, which are essential to develop appropriate control methods, are still not clear at present. In this paper, the performance of a packed LDD was investigated under changes of desiccant inlet temperature and flow rate as well as air inlet humidity ratio, temperature and flow rate. Due to the random packings and interaction between air and desiccant, the air is normally distributed randomly during a dynamic process of LDDs and air outlet humidity ratio at the sampling point is serrated with time going. It was found that exponent function could be utilized to smooth the experimental result of air outlet humidity ratio, providing a simple way to determine the evaluation indexes like the response delay and response time as well as response rate, which could facilitate to evaluate dynamic characteristics of the dehumidifier. And through comparing those evaluation indexes corresponding to changes of different inlet parameters, it was revealed that air outlet humidity ratio was more sensitive to the change of desiccant or air flow rate, but not desiccant inlet temperature as indicated in a previous research getting from quasi-steady state experiments. Therefore, it would be more reasonable to select the desiccant or air flow rate as control variables instead of desiccant inlet temperature. Furthermore, preliminary control experiments were conducted to compare the performance of control algorithms developed based on the steady state characteristics and expert experience of dynamic characteristics. Results show that the control algorithm developed based on the expert experience of dynamic characteristics performs much better, which indicates that the obtained steady state characteristics in existing researches are unsuitable for developing control algorithms for a packed LDD. The dynamic characteristics revealed in current research paves the way for the future development of appropriate control algorithms.

FACTORS RELATED TO THE RESPONSE TIME OF NURSING IN EMERGENCY PATIENTS MANAGEMENT

Background:One indicator of the successful prevention of medical emergency patients is the response time of health workers. Response time A fast will reduce the incidence of death by about 30%, on the other hand, if the delayed response time is will have an adverse impact, resulting in permanent disability and death.Objective:This study aims to determine the factors related to the response time of nurses in handling emergencies in the Emergency Room(IGD), Operating Room (OK), and Intensive Care Unit (ICU) at Ilagaligo East Luwu Hospital 2020. Method: Thestudy is a cross-sectional study. The population in this study were all nurses in the IGD, OK, and ICU Lagaligo I Hospital, East Luwu. The sampling technique was total sampling with a total of60 nurses.Result:The results showed that there was a relationship (p-value <0.034) between education (p = 0.05), years of service (p = 0.016), and training (p = 0.034) with the response time of nurses at Lagaligo I Hospital in 2020. It is hoped that the hospital will continue to encourage staff/employees, in this case, nurses, to continue their education and continuous training to support the professionalism of all nurses. Conclusion:The incidence of the response time of slownurses in patients is due to the absence of good cooperation with the patient's family.It is hoped that the hospital will provide support and motivation to nurses to improve their education by existing standards.

Time-delay characteristics of air-conditioning system for subway trains

The time-delay characteristic of the air-conditioning system is the basis of predictive control of the air-conditioning system. The time-delay of the subway train's air-conditioning system can be divided into system response delay and carriage temperature change delay. Among them, the system response delay can be divided into two stages. The first stage is when the cooling load enters the carriage to the air-conditioning system starts to adjust; the second stage is when the air-conditioning system starts to adjust to the carriage temperature starts to decrease. In this study, the time-delay characteristics of the subway train's air-conditioning system are studied by numerical simulation and mathematical derivation. The accuracy of the calculation model was verified by comparing it with the field measurements data. Then, the influence of various factors on the time-delay characteristics of the air-conditioning system are analyzed. The results indicated that the system response delay time of the subway train's air-conditioning system increases exponentially with the instantaneous cooling load change and decreases linearly with the carriage design temperature. Moreover, the carriage temperature change delay of the air-conditioning system is related to the train carriage volume and temperature, the supply air volume and temperature, and the instantaneous cooling load change. However, the influence of the carriage and the supply air temperature on the carriage temperature change delay is minimal. Especially in the constant air volume air-conditioning system, the carriage temperature change delay is mainly affected by the instantaneous cooling load change.

Fully Integrated Data Communication Framework by Using Visualization Augmented Reality for Internet of Things Networks.

The new and integrated area called Internet of Things (IoT) has gained popularity due to its smart, objects, services and affordability. These networks are based on data communication, augmented reality (AR), and wired and wireless infrastructures. The basic objective of these network is data communication, environment monitoring, tracking, and sensing by using smart devices and sensor nodes. The dAR is one of the attractive and advanced areas that is integrated in IoT networks in smart homes and smart industries to convert the objects into 3D to visualize information and provide interactive reality-based control. With attraction, this idea has suffered with complex and heavy processes, computation complexities, network communication degradation, and network delay. This article presents a detailed overview of these technologies and proposes a more convenient and fast data communication model by using edge computing and Fifth-Generation platforms. The article also introduces a Visualization Augmented Reality framework for IoT (VAR-IoT) networks fully integrated by communication, sensing, and actuating features with a better interface to control the objects. The proposed network model is evaluated in simulation in terms of applications response time and network delay and it observes the better performance of the proposed framework.

Effects of exercise anticipation on cardiorespiratory responses before and after start of dynamic exercise at various intensities

The purpose of this study was to examine the effects of exercise anticipation on time-dependent cardiorespiratory response preceding and after onset of dynamic exercise at various intensities. Experiments were conducted by two different groups of subjects; one group (N=11) for the experiment to test preparatory cardiorespiratory responses to exercise intensity (Exp.1), and the other group (N=15) for the experiment to test the effect of unexpected timing of high intensity exercise on the cardiorespiratory function (Exp.2). In Exp.1, the quantitative and temporal changes in cardiorespiratory and metabolic responses during pre-exercise resting periods changed over time, depending on the subsequent exercise intensity. In Exp.2, The initial increases in cardiorespiratory and metabolic responses after the onset of exercise under anticipation condition were significantly different from those under non-anticipation condition, and the difference in heart rate (HR) responses between the 2 conditions varied in a time-dependent manner. The time to exhaustion and initial HR increase after the start of high-intensity exercise under anticipation condition were higher than those under non-anticipation condition. A significant correlation was observed between percent change in time to exhaustion and percent change in HR in the anticipation condition versus the non-anticipation condition in each time before and after the start of exercise. Anticipatory control mechanisms of the cardiorespiratory system via the higher brain preceding exercise initiation may plays an important role in minimizing the time delay of circulatory response and metabolic cost after the onset of dynamic exercise, thereby enhancing physiological efficiency and maximal exercise performance during high-intensity exercise.

A Generic Methodology for Calculating Rescheduling Time for Multiple Unexpected Events in the Era of Zero Defect Manufacturing

Nowadays, the manufacturing industry is constantly changing. Production systems must operate in a highly dynamic environment where unexpected events could occur and create disruption, making rescheduling inevitable for manufacturing companies. Rescheduling models are fundamental to the robustness of production processes. This paper proposes a model to address rescheduling caused by unexpected events, aiming to achieve the zero-defect manufacturing (ZDM) concept. The goal of the model is to incorporate traditional and ZDM–oriented events into one methodology to calculate when the next rescheduling will be performed to effectively react to unexpected events. The methodology relies on the definition of two key time parameters for each event type: event response time (RT) and event delay response time (DRT). Based on these parameters, an event management algorithm is designed to identify the optimal rescheduling solution. The DRT parameter is calculated based on a multi-parametric dynamic formula to capture the dynamics of production. Moreover, ANOM, and ANOVA methods are used to analyse the behaviour of the developed method and to assess the level of robustness of the proposed approach. Finally, a case study based on real production scenarios is conducted, a series of simulation experiments are performed, and comparisons with other rescheduling policies are presented. The results demonstrate the effectiveness of the proposed event management algorithm for managing rescheduling.