Average Delay Research Articles

Integrated operations strategies for shared and privately-owned autonomous vehicles: A deep reinforcement learning framework

The shared autonomous vehicle (SAV), combining shared mobility and vehicle automation, will play a pivotal role in urban transportation. Effectively matching SAVs to stochastic customer demand poses a significant challenge, particularly when addressing microscopic multi-AV coordination to prevent conflicts and congestion within a network. To tackle this issue, we propose a novel traffic control scheme called the Integrated Operation Framework for Order Matching and AV Coordination (I-OFOMAC). This scheme introduces a third-party coordinator responsible for integrating online order matching for the SAV platform and real-time AV coordination for the road manager. Our approach utilizes an offline deep reinforcement learning method to train a state value neural network, which facilitates strategic order matching. Additionally, a neural network approximating bisimulation metrics is trained to enhance exploration and accelerate learning. To achieve scalability in network-level AV coordination, we adopt a scheduled transportation scheme. The coordinator solves the I-OFOMAC during each decision epoch, optimizing order matching and AV coordination. The I-OFOMAC aims to balance the goals of minimizing AV travel delay and maximizing SAV service revenue. We conduct extensive simulation studies in the realistic Wangjing network to evaluate the proposed I-OFOMAC scheme. Compared to two-step benchmark frameworks that implement order matching and AV coordination sequentially, the I-OFOMAC achieves an average increase of 13.28% in platform revenue (ranging from 2% to 22.53%) and a 4.48% reduction in average PAV travel delay (ranging from −6.55% to 20.17%).

Application of Photovoltaic Panels as Producers of Electrical Energy With IoT Technology Based on Programmable Logic Controller

The process of converting solar cell electrical energy is a form of utilizing environmentally friendly alternative energy sources (renewable energy). The conversion system is in the form of PV panels that are installed in a location exposed to sunlight and unobstructed. Monitoring is carried out when the sun shines from morning to evening. The location of the panel is in the vehicle parking lot of the engineering faculty, while monitoring is carried out in the Control Laboratory of the Tanjungpura University Engineering Faculty, which is 300 meters away. Factors that determine the quality of PV panels are the system and dimensions. This shows that fluctuations in current (I), voltage (V) and power (P) need to be controlled so that load distribution and reserves can prevent reduced energy generation. Observation and control using Long Range Area (LoRa) radio transmission media connections, Internet of Things (IoT) and Programmable Logical Control (PLC) in real-time. Observation and test results show that energy generation has experienced an increase in temperature which has an impact on reducing power. Meanwhile, the effect of the distance between the installed panels produces an average delay of 7 milliseconds (midday conditions). Meanwhile, the Signal to Noise Ratio (SNR) value for data transmission is 30 dBm at the device frequency of 868.125 MHz. Baud rate 2400-9600 bps with a speed of 0.3 bps – 62.5 Kbps. The application of this system is a research novelty because it can determine and control the generation of electrical energy at minimum, maximum and optimum conditions with a certain distance between the observer and the installed panel.

Collaborative Optimization of Dynamic Lane Assignment and Signal Timing for Incident-Affected Intersections

Traffic accidents can lead to rapid changes in the traffic supply and demand at urban intersections, thus causing a severe traffic supply/demand imbalance during specific periods. Responding to accidents requires dynamic and accurate adjustments to optimize intersection resources collaboratively and enhance the real-time reliability and stability of traffic flows during such accidents. Currently, research on traffic incidents rarely considers real-time data-based collaborative optimization theories. Therefore, this study, supported by real-time incident detection technology and accident data, first considers the location and intensity of traffic incidents to update dynamically the changes in intersection traffic demand and supply. Subsequently, a dynamically collaborative optimization method is proposed based on lane assignment and signal timings to minimize the sum of variances of the degree of saturation of various approach lanes. Finally, various traffic demand scenarios are set, and the effectiveness of the proposed model is validated based on numerical and sensitivity analyses. The results demonstrate that compared with signal-only optimization and the highway capacity methods (HCM), the collaborative optimization method presented in this study reduces the average vehicular delay percentages by 8.54% and 16.47%, respectively. Sensitivity analysis indicates that, under various detour rates and detour modes, collaborative optimization methods have effectively mitigated the average vehicular delay at upstream intersections to varying degrees. In the context of real-time accident response, collaborative optimization methods demonstrate a capacity to promptly address the urgency of incidents occurring and maintain a sustained reduction in overall delay levels following detours.

A route network resource allocation method based on multi-objective optimization and improved genetic algorithm

In order to solve the problem of imbalance between traffic demand and airspace capacity of high-altitude air route network, reduce unnecessary delay costs, and improve air route operation efficiency, the resource allocation problem of multi-objective air route network for CTOP program is studied. Taking the affected flights in the congested area of air routes as the research object, taking into account the constraints of actual flight operation, FCA time slot resource availability limit, FCA capacity limit, etc., aiming at minimizing the total delay time of each flight and maximizing the fairness of airlines, a multi-objective optimization model for air route network resource allocation is established, and an improved NSGA-II algorithm is designed to solve the model. Based on the actual operation data of air routes in East China, the Pareto optimal solution set is obtained and compared with the traditional RBS algorithm, the average delay time is reduced by 5.49% and the average fair loss degree is reduced by 66.76%. The results show that the proposed multi-objective optimization model and the improved NSGA-II algorithm have better performance, which can take into account the fairness of each airline on the basis of reducing the total delay cost, realize the allocation of optimal flight trajectories and time slot resources, and provide a reference scheme for air traffic control resource scheduling.

A Longitudinal Multiinstitutional Study of Vulvar Lichen Sclerosus: From Childhood to Perimenopause.

The main outcome of this study was the evaluation of clinical characteristics, comorbidities, and therapeutic approaches in patients with vulvar lichen sclerosus (VLS) aged from childhood to perimenopause. Secondly, it was intended to compare these characteristics according to the menarchal status. Patients less than 45 years of age with a diagnosis of VLS from January 2002 to June 2022 in 10 referral centers were included in this retrospective longitudinal study. The univariate analysis compared the dependent variables according to menarchal status. One hundred eighty-six patients met the inclusion criteria. At diagnosis, between 25% and 40% of premenarchal patients reported signs related to subepithelial hemorrhage. A significantly greater presence of bleeding ( p < .005), easy bruising ( p = .028), fissures ( p = .008), petechiae/splinter hemorrhages ( p < .001), and bleeding/blistering or open sores ( p = .011) was observed in premenarchal patients with respect to the postmenarchal group. The perineum ( p = .013) and the perianal region ( p < .001) were significantly more involved in the premenarchal group. Topical calcineurin inhibitors were more used in the premenarchal population ( p = .004), whereas vitamin E oil and moisturizers were more used in the postmenarchal population ( p = .047). Vulvar lichen sclerosus is a chronic condition that can cause vulvar changes that result in severe morbidity and affects sexual function and quality of life, even before menopause. Vulvar lichen sclerosus continues to be misdiagnosed in this population. This may lead to an average delay from symptom onset to diagnosis. Evaluating clinical manifestations of VLS in premenarchal and postmenarchal age allowed us to find different clinical characteristics between the 2 periods suggestive of the diagnosis.

A NLP-based semi-automatic identification system for delays in follow-up examinations: an Italian case study on clinical referrals

BackgroundThis study aims to propose a semi-automatic method for monitoring the waiting times of follow-up examinations within the National Health System (NHS) in Italy, which is currently not possible to due the absence of the necessary structured information in the official databases.MethodsA Natural Language Processing (NLP) based pipeline has been developed to extract the waiting time information from the text of referrals for follow-up examinations in the Lombardy Region. A manually annotated dataset of 10 000 referrals has been used to develop the pipeline and another manually annotated dataset of 10 000 referrals has been used to test its performance. Subsequently, the pipeline has been used to analyze all 12 million referrals prescribed in 2021 and performed by May 2022 in the Lombardy Region.ResultsThe NLP-based pipeline exhibited high precision (0.999) and recall (0.973) in identifying waiting time information from referrals’ texts, with high accuracy in normalization (0.948-0.998). The overall reporting of timing indications in referrals’ texts for follow-up examinations was low (2%), showing notable variations across medical disciplines and types of prescribing physicians. Among the referrals reporting waiting times, 16% experienced delays (average delay = 19 days, standard deviation = 34 days), with significant differences observed across medical disciplines and geographical areas.ConclusionsThe use of NLP proved to be a valuable tool for assessing waiting times in follow-up examinations, which are particularly critical for the NHS due to the significant impact of chronic diseases, where follow-up exams are pivotal. Health authorities can exploit this tool to monitor the quality of NHS services and optimize resource allocation.

Registry of Members of the Association of Patients with Hereditary Angioedema of Perú

To report the registry of the HAE Peruvian patient's association. We used the questionnaire of the Latin American HAE committee. Consent was requested from the patient's association to report the data. We report data of 63 patients, 51 Female, 12 Male, range age between 6 to 74 years. Nine under 18 years old, 5/9 between 6 to 13 years. Forty-five HAE C1-INH type I, 12 HAE-FXII, 5 HAE UNK, 1 AAE. Symptoms onset average age in 56/62 HAE patients was 16.8. In a group of 50/62 adult HAE patients, the average diagnostic delay approximately was 19.3 years. Laboratory tests: we can perform C4 complement C1-inhibitor antigenic and functional tests. Treatments: The patients have access to tranexamic acid (TA) and attenuated androgens. We do not have registered specific long-term prophylaxis treatments. We used moderate/high doses of TA, in most patients up to 6 gr i.v./in 24 hours, we start with the treatment immediately the HAE acute crisis is beginning, it helps to the HAE attacks are less symptomatic, resolves in a few days and decrease the frequency. We present 63 members of the Association of Patients with Hereditary Angioedema of Perú. We have improved blood tests for HAE diagnosis. Moderate and high doses of Tranexamic Acid are used for prophylaxis and acute crisis respectively, with acceptable response. No deaths have been reported due to HAE crisis in the patient's association.

A cloud-edge collaborative computing framework using potential games for space-air-ground integrated IoT

As a critical component of space-air-ground integrated IoT, the aerial network provides highly reliable, low-latency and ubiquitous information services to ground users by virtue of their high mobility, easy deployment and low cost. However, the current computation and resource management model of air-ground integrated networks are insufficient to meet the latency demanding of emerging intelligent services such as autonomous systems, extended reality and haptic feedback. To tackle these challenges, we propose a computation offloading and optimization method based on potential game. First, we construct an cloud-edge collaborative computing model. Secondly, we construct Offloading Decision Objective Functions (ODOF) with the objective of minimum task processing latency and energy consumption. ODOF is proved to be a Mixed Inferior Nonlinear Programming (MINLP) problem, which is hard to solve. ODOF is converted to be a full potential game, and the Nash equilibrium solution exists. Then, a computational resource allocation algorithm based on Karush–Kuhn–Tucker (KKT) conditions is proposed to solve resource allocation problem. On this basis, a distributed game-based computational offloading algorithm is proposed to minimize the offloading cost. Extensive simulation results demonstrate that the convergence performance of the proposed algorithm is reduced by 50%, the convergence time is reduced by 13.3% and the average task processing delay is reduced by 10%.

Call to Action: Investigating Interaction Delay in Smartphone Notifications.

Notifications are an essential part of the user experience on smart mobile devices. While some apps have to notify users immediately after an event occurs, others can schedule notifications strategically to notify them only on opportune moments. This tailoring allows apps to shorten the users' interaction delay. In this paper, we present the results of a comprehensive study that identified the factors that influence users' interaction delay to their smartphone notifications. We analyzed almost 10 million notifications collected in-the-wild from 922 users and computed their response times with regard to their demographics, their Big Five personality trait scores and the device's charging state. Depending on the app category, the following tendencies can be identified over the course of the day: Most notifications were logged in late morning and late afternoon. This number decreases in the evening, between 8 p.m. and 11 p.m., and at the same time exhibits the lowest average interaction delays at daytime. We also found that the user's sex and age is significantly associated with the response time. Based on the results of our study, we encourage developers to incorporate more information on the user and the executing device in their notification strategy to notify users more effectively.

Burst traffic: Congestion management and performance optimization strategies in heterogeneous cognitive radio networks

AbstractIn order to solve the network congestion problem caused by burst service flows in heterogeneous cognitive radio networks (Het‐CRN), a two‐stage dual‐threshold random early detection (TD‐RED) control mechanism is proposed here. Meanwhile, a three‐state Markov modulated Poisson process (MMPP‐3) is used to model the burst service to analyze its arrival in depth. Moreover, a performance evaluation system (PES) is proposed to quantify the interference of burst services to different classes of services and their quality of service, which can comprehensively evaluate the performance enhancement of the TD‐RED control mechanism for each service. The system examines performance metrics such as packet loss rate, average delay, average captain etc. PES simulation results show that TD‐RED significantly reduces the packet rejection rate and transmission delay compared to the no congestion control (NCC) and random early detection (RED) methods, thus providing superior quality of service to all services. thereby providing a superior quality of service to cognitive users. Its lower average captain fully proves that TD‐RED can effectively alleviate congestion.

Guidelines for bus speed at intersections under travel time control

To improve the traffic efficiency of bus at a group of intersections and reduce their delay, this paper develops a speed guidance strategy for buses under travel time control at intersection groups. The approach considers the influence of bus departure time, bus station arrival rate, and bus station dwell time. Simulation experiments are carried out on three consecutive intersections along Jinshan Avenue in Fuzhou, China. Results show that the average travel time of buses, the average delay of buses, and the average delay per capita in the priority direction are reduced by 5.5%, 9.9%, and 9.4%, respectively. The optimal rate of the average number of bus stops reached 15.2%. The indicators of the non-priority direction of social vehicles are not significantly affected. It shows that the efficiency of buses has improved after implementing the speed guidance strategy at the intersection groups without affecting the social vehicles as far as possible.

Evaluation of the Limitation of Operational Parameters of the IEEE 802.11 ac Network in the 20MHz Channel

IEEE 802.11 wireless network technologies are widely used to create corporate and personal local networks for data exchange and access to Internet resources. The main principle of operation of IEEE 802.11 networks is the principle of competitive access, according to which all wireless network users have the same access rights to the information transmission environment. This method of access leads to the occurrence of collisions in networks with a large number of users, which complicates the process of network functioning and leads to the degradation of quality indicators. The purpose of the study is to estimate the limit values of the operational characteristics of the IEEE 802.11 ac wireless network in the mode with the highest transmission rate (MCS8) in a frequency channel of 20 MHz with one spatial stream, provided that the network has a significant number of active stations with a saturated load. An alternative model of processes in IEEE 802.11 networks based on the concept of a virtual competitive window is used for research. According to the concept of virtual contention window (VCW), the process of data transmission in a network with competitive access is considered as a quasi-stationary process. Numerical data were obtained and graphs of channel bandwidth, transmission delay, and delay non-uniformity were given in the presence of one to sixteen active stations with a saturated load in the network, in the case of transmission of frames with a data volume of 512 or 1500 bytes. The maximum possible bandwidth of the channel with a frequency band of 20 MHz (68.387 bit/s) was determined, in the case of using frames with the maximum load (11454 bytes) provided by the standard. Estimated data on the number of collisions occurring in a network with a saturated load and the number of frames transmitted at various stages of channel access are also provided. The frame transmission delay increases almost proportionally to the number of active stations and varies from 0.605 ms to 5.293 ms, in the case of loading all data frames of 512 bytes, and from 0.785 to 6.41 ms, in the case of a load of 1500 bytes, for changes in the number of active stations in the network from 2 to 16. The unevenness of the delay exceeds the average delay and grows non-linearly, in the case of an increase in the number of active stations from 1 to 6 (CWmin=15), and linearly — with a further increase in the number of stations (over 6). The obtained results are useful for reasonable planning of wireless networks and configuration of network equipment parameters.

Flexible optimal bus‐schedule bridging for metro operation‐interruption

AbstractUnder the sudden interruption of the metro, it is significant to dispatch emergency bridging buses to evacuate stranded passengers to improve linkage management and service reliability. Aiming at the problem of emergency bridging bus scheduling, considering the remaining capacity of conventional buses, passenger tolerance, and site convenience, a flexible combined emergency bridging bus scheduling model is constructed based on the constraints of vehicle capacity, dispatching capacity, and maximum evacuation times of emergency bridging bus, aiming at minimizing the maximum evacuation time and passenger delay. The improved Harris hawk algorithm is used to solve the model, and the evacuation plan of the demand‐responsive and station‐station bridging lines is obtained. The maximum evacuation time is 41 min, and the average delay of stranded passengers is 19 min. The results show that the maximum evacuation time is 10% and 27% less than the fixed combined and single scheduling. The average delay is 16% and 42% less than the fixed combination and traditional single scheduling. The sensitivity analysis of the influencing factors of emergency bridging bus scheduling is conducted. The results show that the flexible combined emergency bridging bus scheduling model constructed in this paper can improve evacuation efficiency and reduce passenger travel delays.

Clomiphene Citrate Administered in Periconception Phase Causes Fetal Loss and Developmental Impairment in Mice.

Clomiphene citrate is a common treatment for ovulation induction in subfertile women, but its use is associated with elevated risk of adverse perinatal outcomes and birth defects. To investigate the biological plausibility of a causal relationship, this study investigated the consequences in mice for fetal development and pregnancy outcome of periconception clomiphene citrate administration at doses approximating human exposures. A dose-dependent adverse effect of clomiphene citrate given twice in the 36 hours after mating was seen, with a moderate dose of 0.75 mg/kg sufficient to cause altered reproductive outcomes in 3 independent cohorts. Viable pregnancy was reduced by 30%, late gestation fetal weight was reduced by 16%, and ∼30% of fetuses exhibited delayed development and/or congenital abnormalities not seen in control dams, including defects of the lung, kidney, liver, eye, skin, limbs, and umbilicus. Clomiphene citrate also caused a 30-hour average delay in time of birth, and elevated rate of pup death in the early postnatal phase. In surviving offspring, growth trajectory tracking and body morphometry analysis at 20 weeks of age showed postweaning growth and development similar to controls. A dysregulated inflammatory response in the endometrium was observed and may contribute to the underlying pathophysiological mechanism. These results demonstrate that in utero exposure to clomiphene citrate during early pregnancy can compromise implantation and impact fetal growth and development, causing adverse perinatal outcomes. The findings raise the prospect of similar iatrogenic effects in women where clomiphene citrate may be present in the periconception phase unless its use is well-supervised.

ПРИМЕНЕНИЕ НЕЙРОСЕТЕВЫХ ТЕХНОЛОГИЙ В УПРАВЛЕНИИ СВЕТОФОРНЫМИ ОБЪЕКТАМИ

The paper describes the use of an artificial neural network to determine the optimal parameters of traffic light regulation based on the intensity of traffic flow. At regulated intersections, there is an imbalance in the intensity of traffic flow, due to which one operation mode of traffic lights at an intersection may be ineffective. The study objective is to develop software for predicting the operating modes of traffic lights, taking into account the spatial and temporal unevenness of transport demand. Based on the simulation of traffic flows at one regulated intersection, the values of the average delay time were determined for different traffic light operating modes and traffic flow intensities, including turning ones. The artificial neural network was trained on data from 16 thousand simulations and tested on four thousand simulations. Using an artificial neural network to calculate the optimal operating mode of traffic lights reduces the delay time by 20-50% for two rush hours. A pre-trained artificial neural network can calculate the optimal operating mode of traffic lights for a specific regulated intersection in one second. The developed software can be used to implement an intelligent transport system in an automated traffic control system.

TDITI: A time-delay information transfer index algorithm for corticomuscular coupling

Time delay (TD) across corticomuscular coupling (CMC) is a significant index to assess the information transmission between brain and muscle during movement execution. Larger methods have been widely used to calculate the time delay by estimating phase information, but fail to account for both linear and nonlinear characteristics in the bidirectional coupled systems. For this, this study proposed a novel time-delay estimation method, defined as time-delay information transfer index (TDITI), to explore the TD characteristics between two signal deriving from one system with time-delay coupling. To verify this, we introduced two models to generate a series of simulation signal with linearly unidirectional/ bidirectional coupling or nonlinearly unidirectional/ bidirectional coupling. Simulation results manifested that the TDITI method, compared with the information transfer index (ITI) and coherence methods, can not only describe the TD in the linearly or nonlinearly unidirectional systems, but was also suitable for the bidirectional coupled systems. We also found its robustness to data length, coupling strength and signal-noise ratio. After that, we applied it to explore the TD of CMC by synchronizing the electroencephalogram (EEG) and electromyogram (EMG) signal during steady-state task. Experimental results showed that the CMC between cortex and muscle were direction-dependent, and the average delay time from EEG to EMG (∼25 ms) was shorter than that in the opposition (∼30 ms). Both simulation and experimental data expound the effectiveness of the TDITI method to describe the time delay in the unidirectional or bidirectional coupled systems, and this study extends our perspective to the mechanism of motor control.

Evidence for weak azimuthal anisotropy beneath the Kumaon-Garhwal Himalaya

SUMMARY This study attempts to interrogate the upper mantle deformation pattern beneath the Kumaon-Garhwal region, located in the western Himalaya, using shear wave splitting (SWS) analysis of core-refracted (XK(K)S) phases recorded at 53 broad-band stations. The fast polarization azimuths (FPAs) revealed by 338 well constrained measurements are dominantly clustered around ENE–WSW, with a few along the NE and E–W directions. The delay times vary from 0.2 to 1.4 s, with an average of 0.6 s that is smaller than that for the Indian shield (∼0.8 s), central and eastern Himalayas. The northern part of the lesser Himalaya shows a slightly smaller delay time compared to the southern part, which is attributed to the weakening of azimuthal anisotropy caused by the dipping of the Indian lithosphere. In order to understand the crustal contribution, its anisotropy is measured by analysing the splitting of Ps conversions from the Moho (Pms), akin to that of the XK(K)S phases. However, reliable results for crustal anisotropy could be obtained only at 10 stations. The average delay time due to crustal anisotropy is 0.47 s, with a variation from 0.2 to 0.9 s. Although the dominant period of Pms is smaller than that of SK(K)S, crustal anisotropy contributing to splitting of the latter phases cannot be ruled out. The orientation of FPAs obtained from Pms phases is found to be parallel or sub-parallel to those from XK(K)S phases, suggesting a similar deformation mechanism in the mid- to lower-crust and upper mantle. On the basis of FPAs derived from XK(K)S measurements, the Kumaon-Garhwal Himalaya (KGH) region can be divided into four subregions. In the western and eastern parts, the FPAs are mostly aligned along NE and ENE–WSW, and NE, respectively. In the central and south-eastern parts, their orientation is along ENE–WSW and NW, respectively. The strong ENE–WSW orientation in the central part could result from a slightly variable anisotropy in the crust to the upper part of the lithosphere or basal topography causing deflection of mantle flow. Also, the NW orientation in the south-eastern part of KGH is associated with a shallow source within the lithosphere. Application of the spatial coherency technique to single-layered anisotropic parameters results in a depth of 220–240 km, implying that the dominant source of anisotropy could lie in the upper mantle.

Exponential stability of impulsive random delayed nonlinear systems with average-delay impulses

In this paper, we investigate the pth moment exponential stability of impulsive random delayed nonlinear systems (RDNS) with average-delay impulses. Utilizing the average impulsive interval, average impulsive delay, and the Lyapunov method, we present several criteria for pth exponential stability in these systems under a novel condition, diverging from previous literature. Additionally, we explore the effects of delayed impulses, analyzing both destabilizing and stabilizing impulses. Our findings reveal the dual effects of time delay in impulses, which can potentially destabilize a stable system or stabilize an unstable one.

Machine learning-Based Energy Efficient and Enhancing Communication Reliability for MANETs of Balanced Less Loss Routing Protocol

The aim of the presented research was the utilization of machine learning methods, for example, SOM, MARL, and DQN, to promote the increase of energy efficiency and communication reliability in MANET. For the purpose of the research conduction, 10 trials of the experiment were carried out with the view to establish the performance of the proposed approaches from various perspectives. DQN demonstrated superior performance throughout all experiment trials as compared to both SOM and MARL. The model recorded an average energy efficiency of 95%, indicating that it was highly successful in optimizing routing strategies and communication policies. Furthermore, the average packet delivery ratio was shown to be 96%, meaning that DQN provided guarantees of timely and reliable data exchange across the MANET infrastructure. Finally, the average delay was determined to be from 4 ms to 9 ms, evidencing the quick delivery of packets with little temporal latency. The results obtained demonstrate that DQN is able to alleviate the challenges associated with the energy efficiency and communication reliability of MANETs. Notably, deep reinforcement learning with DQN appears to offer viable solutions for more energy-efficient routing, minimized energy consumption in these networks, and improvement to their communication reliability. Thus, the study under consideration has contributed to the development of the existing knowledge as it has expanded the existing understanding of the fact that machine learning, in general, and DQN, in particular, can be utilized to optimize the operation of MANETs.

Remote practical instruction using web browsers

&lt;p&gt;This paper introduces a novel approach to remote coaching, specifically targeting the body movements of learners participating remotely. The proposed system employs a smartphone camera to capture the learner’s body and represent it as a 3D avatar. The instructor can then offer guidance and instruction by manipulating the 3D avatar’s shape, which is displayed on a web browser. The main challenge faced by the system is to enable the sharing and editing of 3D objects among users. Since the HTML5 drag-and-drop feature is inadequate for transforming virtual objects consisting of multiple interconnected rigid bodies, the system tracks the pivot point of the manipulated rigid body. It assigns attributes such as pivot points and action points to each object, extending beyond their 2D screen coordinates. To implement the system, an interactive web application framework following the model-view-view-model (MVVM) architecture is utilized, incorporating Vue.js, Three.js, and Google Firebase. The prototype system takes advantage of the data binding capability of the framework and successfully operates within the 3D space of a web browser. Experimental results demonstrate that it can effectively share transformation information with an average delay of 300 ms.&lt;/p&gt;