Access Scheduling Research Articles

Socioeconomic and demographic factors predictive of same day access utilization in outpatient radiation oncology.

Access to medical care extends to not only the timely and appropriate receipt of services but also addresses inclusivity and underlying determinants of health. Given that patients from disadvantaged backgrounds have been shown to be more likely to experience delays in care, a same day access scheduling initiative was proposed to address this equity issue. Therefore, this study aims to evaluate our experience, focusing on identifying socioeconomic and demographic patterns of same day access utilization. From March 2021 to January 2023, all patients referred for new consultation to a tertiary care-based radiation oncology department were offered same day appointments as part of a prospective pilot initiative. Descriptive statistics were used to identify factors predictive of utilization. On multivariate analysis, patient characteristics independently associated with higher odds of same day access utilization included low-income status ([OR]=3.70, 95% CI (1.47-6.14)) and Black or Latino race ([OR]=4.05, 95% CI: 1.72-9.11). While we were unable to acquire data on actual clinical outcomes for patients opting for same day appointments, the enthusiasm for this program was obvious. Patients from disadvantaged backgrounds and vulnerable segments of the population were more likely to elect for same day appointments. Implications on health equity are discussed. Patient-centered approaches to overcome barriers of access can potentially help ensure that care is equitable. Our findings, representing the first published data analyzing a longitudinal experience with same day appointments in oncology, strongly suggest that certain disadvantaged populations may benefit more from access initiatives.

Unveiling Patients’ Perspectives: Impact of Varying Durations of Advanced Access Scheduling System Implementation on Access to Care in Academic Family Medicine Clinics

Unveiling Patients’ Perspectives: Impact of Varying Durations of Advanced Access Scheduling System Implementation on Access to Care in Academic Family Medicine Clinics

Joint optimization for energy efficient full-duplex UAV relaying with multiple user pairs

This paper investigates an unmanned aerial vehicle (UAV) assisted amplify-and-forward relaying, where a full-duplex (FD) fixed-wing UAV employs a time-division multiple access scheduling protocol to provide relay services for multiple source–destination user pairs. With the aim of maximizing energy efficiency (EE) of the system, a joint optimization problem is studied so as to jointly fulfill the communication scheduling of multiple user pairs, the transmit power control and the trajectory design of the UAV. Since the optimization variables of the problem are coupled, it is non-convex and hence hard to solve directly. To this end, the initial problem is decomposed into three subproblems corresponding to the optimization of communication scheduling, and transmit power and trajectory of the UAV, respectively. The three subproblems are solved by utilizing the linear programming, the successive convex approximation (SCA), and the Dinkelbach’s algorithm. Then an iterative algorithm based on the block coordinate descent technique is proposed to tackle the joint optimization problem by optimizing the three blocks of variables alternately. Simulation results demonstrate that the proposed algorithm converges efficiently, and the EE of the joint optimization scheme can be significantly improved compared to the benchmark schemes.

Evaluation of no-show rate in outpatient clinics with open access scheduling system: A systematic review.

Patients' missed appointments can cause interference in the functions of the clinics and the visit of other patients. One of the most effective strategies to solve the problem of no-show rate is the use of an open access scheduling system (OA). This systematic review was conducted with the aim of investigating the impact of OA on the rate of no-show of patients in outpatient clinics. Relevant articles in English were investigated based on the keywords in title and abstract using PubMed, Scopus, and Web of Science databases and Google Scholar search engine (July 23, 2023). The articles using OA and reporting the no-show rate were included. Exclusion criteria were as follows: (1) review articles, opinion, and letters, (2) inpatient scheduling system articles, and (3) modeling or simulating OA articles. Data were extracted from the selected articles about such issues as study design, outcome measures, interventions, results, and quality score. From a total of 23,403 studies, 16 articles were selected. The specialized fields included family medicine (62.5%, 10), pediatrics (25%, four), ophthalmology, podiatric, geriatrics, internal medicine, and primary care (6.25%, one). Of 16 articles, 10 papers (62.5%) showed a significant decrease in the no-show rate. In four articles (25%), the no-show rate was not significantly reduced. In two papers (12.5%), there were no significant changes. According to this studyresults, it seems that in most outpatient clinics, the use of OA by considering some conditions such as conducting needs assessment and system design based on the patients' and providers' actual needs, and cooperating of all system stakeholders through consistent training caused a significant decrease in the no-show rate.

Parvalbumin interneuron mGlu5 receptors govern sex differences in prefrontal cortex physiology and binge drinking.

Despite established sex differences in the prevalence and presentation of psychiatric disorders, little is known about the cellular and synaptic mechanisms that guide these differences under basal conditions. The proper function of the prefrontal cortex (PFC) is essential for the top-down regulation of motivated behaviors. The activity of the PFC is tightly controlled by parvalbumin-expressing interneurons (PV-INs), a key subpopulation of fast-spiking GABAergic cells that regulate cortical excitability through direct innervations onto the perisomatic regions of nearby pyramidal cells. Recent rodent studies have identified notable sex differences in PV-IN activity and adaptations to experiences such as binge drinking. Here, we investigated the cellular and molecular mechanisms that underlie sex-specific regulation of PFC PV-IN function. Using whole-cell patch-clamp electrophysiology and selective pharmacology, we report that PV-INs from female mice are more excitable than those from males. Moreover, we find that mGlu1 and mGlu5 metabotropic glutamate receptors regulate cell excitability, excitatory drive, and endocannabinoid signaling at PFC PV-INs in a sex-dependent manner. Genetic deletion of mGlu5 receptors from PV-expressing cells abrogates all sex differences observed in PV-IN membrane and synaptic physiology. Lastly, we report that female, but not male, PV-mGlu5-/- mice exhibit decreased voluntary drinking on an intermittent access schedule, which could be related to changes in ethanol's stimulant properties. Importantly, these studies identify mGlu1 and mGlu5 receptors as candidate signaling molecules involved in sex differences in PV-IN activity and behaviors relevant to alcohol use.

Age-of-Information based Multi-UAV Trajectories Using Deep Reinforcement Learning

The use of unmanned aerial vehicles (UAVs) as a unified platform for sensing and communication is especially relevant in environments with inadequate infrastructure. In this paper, a multi-UAV system is constructed for dynamic data collection in a resource-constrained environment. The devised approach involves the implementation of an access platform referred to as the Access UAV (A_UAV). This A_UAV orchestrates the data collection process from Inspection-UAVs (I_UAVs), each equipped with a visual sensor, facilitating the relay of collected data to the cloud. Our approach jointly considers the trajectory scheduling of A_UAV and I_UAV to collect data from specific points in a decentralized manner. Specifically, a Deep Reinforcement Learning framework utilizing an actor-critic network is formulated for A_UAV, aiming to generate an equitable access schedule for I_UAVs. Moreover, trajectory scheduling of A_UAV ensures dynamic data collection while minimizing total system energy and the Age of Information (AoI) of data arriving from I_UAVs. The simulation results validate the performance of our proposed approach against several baselines under different parameter settings.

L-NORM: Learning and Network Orchestration at the Edge for Robot Connectivity and Mobility in Factory Floor Environments

Robotic factory floors will revolutionize the future of manufacturing and the service industry by automating tasks. However, to fully supplement human effort, these robots will need low-latency, reliable connectivity throughout the work zone through links established by wireless access points (APs). This will allow the robot to assuredly respond to programming directives that rely on the real-time relaying of robot-generated sensor data to the Mobile Edge Computing (MEC) server. In this paper, we propose L-NORM, a multi-AP and multi-robot coordination framework, as a multi-tiered solution for such autonomous edge networks. First, multi-robot motion planning through reinforcement learning occurs at the MEC, using as input multi-modal robot sensor data. Second, multi-AP resource orchestration is performed using another reinforcement learning-based method that maps a subset of available APs to each robot toward meeting their sensor data delivery requirements. Furthermore, we suggest diversity combination of uplink channels with the 802.11ax scheduled access mode that will (i) support high reliability of multi-robot uplink sensor packets and (ii) enable multi-AP coordination, for optimized resource utilization. Through extensive simulation studies, we show that the probability of robot deviation to remain within 0.5 m from its optimal path, is 19% more in L-NORM compared to classical 802.11ax based edge network solution, considering <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula> 1 MB of sensor data per robot.

Sustainable optimizing WMN performance through meta-heuristic TDMA link scheduling and routing

Wireless mesh networks (WMNs) have become a popular solution for expanding internet service and communication in both urban and rural areas. However, the performance of WMNs depends on generating optimized time-division multiple access (TDMA) schedules, which distribute time into a list of slots called superframes. This study proposes novel meta-heuristic algorithms to generate TDMA link schedules in WMNs using two different interference/constraint models: multi-transmit-receive (MTR) and full-duplex (FD). The objectives of this study are to optimize the TDMA frame for packet transmission, satisfy the constraints, and minimize the end-to-end delay. The significant contributions of this study are: (1) proposing effective and efficient heuristic solutions to solve the NP-complete problem of generating optimal TDMA link schedules in WMNs; (2) investigating the new FD interference model to improve the network capacity above the physical layer. To achieve these objectives and contributions, the study uses two popular meta-heuristics, the artificial bee colony (ABC) and/or genetic algorithm (GA), to solve the known NP-complete problems of joint scheduling, power control, and rate control. The results of this study show that the proposed algorithms can generate optimized TDMA link schedules for both MTR and FD models. The joint routing and scheduling approach further minimizes end-to-end delay while maintaining the schedule's minimum length and/or maximum capacity. The proposed solution outperforms the existing solutions in terms of the number of active links, end-to-end delay, and network capacity. The research aims to improve the efficiency and effectiveness of WMNs in most applications that require high throughput and fast response time.

Rapid Access Scheduler: A Web-Based System for Direct Provider Scheduling to Pediatric Neurology.

Access to pediatric neurology care is limited, and outpatient waits can exceed 6 months. The referral process is often complex and burdensome. Our objective was to trial a program for scheduling access to pediatric neurology, to be controlled and accessed directly by outside providers. We developed a web-based automated system, "Rapid Access Scheduler" (RASr), for direct scheduling by outside providers. RASr is built around a calendar view that allows the provider to see and reserve an available slot at the time of care. Once a slot is reserved, the scheduling team contacts the family to finalize scheduling. The RASr system is a novel approach for facilitating pediatric neurology patient access through direct scheduling by outside providers using a web-based portal. Advantages of this include control and responsibility by outside providers, easy visibility of availability, and opportunity to inform patients and families at their point-of-care.

A Graph-Based Neural Approach to Linear Sum Assignment Problems.

Linear assignment problems are well-known combinatorial optimization problems involving domains such as logistics, robotics and telecommunications. In general, obtaining an optimal solution to such problems is computationally infeasible even in small settings, so heuristic algorithms are often used to find near-optimal solutions. In order to attain the right assignment permutation, this study investigates a general-purpose learning strategy that uses a bipartite graph to describe the problem structure and a message passing Graph Neural Network (GNN) model to learn the correct mapping. Comparing the proposed structure with two existing DNN solutions, simulation results show that the proposed approach significantly improves classification accuracy, proving to be very efficient in terms of processing time and memory requirements, due to its inherent parameter sharing capability. Among the many practical uses that require solving allocation problems in everyday scenarios, we decided to apply the proposed approach to address the scheduling of electric smart meters access within an electricity distribution smart grid infrastructure, since near-real-time energy monitoring is a key element of the green transition that has become increasingly important in recent times. The results obtained show that the proposed graph-based solver, although sub-optimal, exhibits the highest scalability, compared with other state-of-the-art heuristic approaches. To foster the reproducibility of the results, we made the code available at https://github.com/aircarlo/GNN_LSAP.

Innovative tools and methods for digitizing both visible and non-visible attributes of cultural heritage items. Part II: a multiscale approach

The process of object digitization marks the initial step toward digital transformation, focusing on discretizing specific geometric entities according to predefined level of detail. The degree of detail, depending on the scale of representation and visualization, is important for two critical steps: segmentation and classification. These stages aim to partition the object into regions with homogeneous properties and assigning labels to each region based on its characteristics. The geometrical model implementation follows, serving different objectives including the structural analyses of the digitized object. Within this framework three mechanical methods will be presented: the lattice-based model dating back to Hrennikoff (1943), the Discrete Element Method (Cundal, 1971) and the microplane method (Bažant and Oh, 1985). These methods will be discussed alongside applications concerning brick walls, concrete element and Fiber Reinforced Polymer (FRP) materials utilized for reinforcement of existing concrete elements as well as new FRP element. Depending on the chosen scale, the numerical model can be implemented based on Voronoi Diagram (1908) and Delaunay triangulation (1934). These techniques find applications in various fields, including cluster analysis, record access scheduling, and collision detection.

Multi-parametric magnetic resonance imaging of the prostate in Victoria, Australia; unintended consequences of changing Medicare Benefits Schedule access.

ObjectiveTo assess whether prostate biopsy rates have altered with the July 2018 change in Australian Medicare Benefits Schedule (MBS) rebates supporting multiparametric magnetic resonance imaging (mpMRI) for diagnosing prostate cancer.MethodsBiopsy data (both trans-rectal and trans-perineal) were obtained from the Victorian Agency for Health Information from July 2016 to June 2022. The data were stratified by financial year, age group and hospital type (public vs private). Comparison was made between rates pre and post the mpMRI MBS code change.ResultsThere was an 11.9% increase in the number of biopsies performed per year compared to the pre-MBS change period. There is a significant decreasing trend (P<0.001-4) in number of biopsies in the 40-49, 50-59 and 60-69-year-old age groups with a significant increasing trend (P<0.001) in the 70-79 and 80-89-year-old age groups. There was a 32.9% reduction in the mean number of biopsies performed per year in public hospitals, compared with an 18.3% increase in private.ConclusionContrary to expectations, and proposed funding, there has been an increase in the number of prostate biopsies since MRI became more easily available. This change will put increased pressure on the health budget and the large increase in biopsies in elderly patients was not anticipated when the changes were proposed. A review of the criteria is suggested.

Deep reinforcement learning based efficient access scheduling algorithm with an adaptive number of devices for federated learning IoT systems

With the widespread application of Internet of Things (IoT), its energy consumption is becoming a major concern. Federated Learning (FL) allows multiple low-power devices to collaboratively learn a shared model, which reduces the energy consumption of IoT systems. However, FL involves highly varied data structures and require large amounts of communication. The communication efficiency greatly affects the system performance. In this paper, we optimize communication efficiency in the device access layer. Considering the instability of IoT device network connections, we propose a Deep Reinforcement Learning (DRL) based Efficient Access Scheduling Algorithm (DRL-EASA). It can adapt to changes in IoT device numbers and densities and thus applicable to instantaneous dynamic FL IoT systems. In scale-changed scenarios, DRL-EASA constructs geospatial-oriented state spaces and utilizes learning algorithm to train access scheduling strategies, effectively decoupling device numbers from the algorithm’s network structure. Firstly, the geographic region is divided into grids and the User State Information (USI) is mapped into fixed-dimensional Geographic State Information Vectors (GSIV). Secondly, a Convolutional Neural Network (CNN) is used as an agent to extract interference feature information from GSIV, and the Proximal Policy Optimization (PPO) algorithm is utilized to train the agent. Finally, a random algorithm is employed to assist DRL in generating scheduling decisions, enhancing the algorithm’s generalization performance in high device density scenarios. Numerical results show that our approach optimizes access scheduling strategies for both uplink and downlink and demonstrates effective adaptability to dynamically changing device numbers and exhibits strong generalization performance across various device densities.

Estimation of the Term of Pre-Trial Investigation when Studying Its Materials: Theory and Practice

The analysis of court judgements established that the courts of first instance and the courts of appeal interpret and apply the provisions of Clause 10, Part 1 of Article 284, Part 5 of Article 219 of the Criminal Procedure Code of Ukraine differently. There are court rulings concerning the inclusion of the time when the defendant party did not yet have actual possession of the pre-trial investigation materials, based on the procedure described in Article 290 of the Criminal Code of Practice of Ukraine, into the timeframe of the pretrial investigation. This means including the time when the actual access to the materials was limited, impossible, or obstructed in some way, even though formal access could be granted and the formal requirements of the procedural law were satisfied by the investigator or prosecutor. In other words there are some situations where the prosecution failed to provide the defense with proper opportunities and conditions for unobstructed study of the pre-trial investigation materials. This appears to be the reason why the prevailing opinion is that this period is not a part of the term allocated for studying the materials of the pre-trial investigation and cannot be deducted from the total term of the pre-trial investigation. There is also an opinion that this approach contradicts the provisions of Part 5, Article 219 of the Criminal Code of Practice of Ukraine, because from the moment of sending out the notification of completion of the pre-trial investigation to the defense, the time limit for the pre-trial investigation is put on hold to provide the defense with an opportunity to study the materials.For this reason, the author attempted to demonstrate that when calculating the term of the pre-trial investigation, it is important to consider not only the day of notification indicating the completion of the pretrial investigation (which is included in the duration of the term of the pre-trial investigation), but also the actual provision of access to the pre-trial investigation materials for studying. Sending a notification that includes the date, time, and location for such study is not a sufficient proof of providing an actual access. It would be more appropriate to consider sending such a notification as one of the items in the list of the procedural and organizational measures aimed at facilitating further scheduled access to the materials. In its turn, access and subsequent study encompass the opportunity to copy and/or examine documents or their copies, physical evidence or relevant portions, etc. And it is the real opportunity provided for taking such actions, mentioning the names of the materials concerning which the party is granted such an opportunity (because the parties, having a real opportunity for such actions, have a right to refuse to take the mentioned actions at the pre-trial investigation) that one party of the criminal proceeding is obliged to confirm to the other, and the injured party, a representative of a legal entity, in relation to whom or which the proceeding is conducted, is to confirm it for the prosecutor (Part 9, Article 290 of the Criminal Procedure Code of Ukraine).

Effect of a same day appointment initiative on racial disparities in access for radiation oncology

PurposeWe present our single-institution experience with the development of a same day access scheduling initiative for an outpatient radiation oncology unit, focusing on its potential influence on ameliorating racial disparities. Methods and materialsFrom March 2021 to August 2022, a pilot initiative was conducted such that all new patients referred to a tertiary care-based radiation oncology department were offered the ability to be seen as a same day consultation. The timespan of this analysis was categorized into 2 distinct successive periods over 36 months—a 18-month pre-initiative period (September 2019 to February 2021) and another subsequent one (March 2021 to August 2022). Descriptive statistics were used to study the impact of this initiative on access-related benchmarks. ResultsA total of 2897 patients were referred. Among the 2107 patients scheduled, three hundred and sixteen (15 %) opted for same day appointments. Black, Latino, and Asian patients were significantly more likely to use the same day access initiative versus Caucasian patients (p = 0.01). The same day access initiative increased the proportion of patients seen within 5 days from referral from 8 % to 34 % for Blacks, 12–57 % for Latinos, and 18–67 % for Asians, compared to 39–55 % for Caucasians (p < 0.001). The no-show rate was reduced from 20 % to 7 % and 14–5 %, for Black and Latino patients, respectively (p < 0.001). ConclusionsThe implementation of a same day access initiative narrowed disparities with respect to access-related benchmarks.

Voltage-gated potassium channels control extended access cocaine seeking: a role for nucleus accumbens astrocytes.

Dopaminergic signaling in the nucleus accumbens shell (NAc) regulates neuronal activity relevant to reward-related learning, including cocaine-associated behaviors. Although astrocytes respond to dopamine and cocaine with structural changes, the impact of dopamine and cocaine on astrocyte functional plasticity has not been widely studied. Specifically, behavioral implications of voltage-gated channel activity in the canonically non-excitable astrocytes are not known. We characterized potassium channel function in NAc astrocytes following exposure to exogenous dopamine or cocaine self-administration training under short (2 h/day) and extended (6 h/day) access schedules. Electrophysiological, Ca2+ imaging, mRNA, and mass spectrometry tools were used for molecular characterization. Behavioral effects were examined after NAc-targeted microinjections of channel antagonists and astroglial toxins. Exogenous dopamine increased activity of currents mediated by voltage-gated (Kv7) channels in NAc astrocytes. This was associated with a ~5-fold increase in expression of Kcnq2 transcript level in homogenized NAc micropunches. Matrix-assisted laser desorption/ionization mass spectrometry revealed increased NAc dopamine levels in extended access, relative to short access, rats. Kv7 inhibition selectively increased frequency and amplitude of astrocyte intracellular Ca2+ transients in NAc of extended access rats. Inhibition of Kv7 channels in the NAc attenuated cocaine-seeking in extended access rats only, an effect that was occluded by microinjection of the astrocyte metabolic poison, fluorocitrate. These results suggest that voltage-gated K+ channel signaling in NAc astrocytes is behaviorally relevant, support Kv7-mediated regulation of astrocyte Ca2+ signals, and propose novel mechanisms of neuroglial interactions relevant to drug use.

Examination of onset trajectories and persistence of binge-like eating behavior in mice after intermittent palatable food exposure.

Binge eating is a persistent behavior associated with a chronic course of illness and poor treatment outcomes. While clinical research is unable to capture the full course of binge eating, preclinical approaches offer the opportunity to examine binge-like eating from onset through chronic durations, allowing identification of factors contributing to binge eating persistence. The present study quantified the trajectories of binge-like eating onset and modeled cycles of abstinence/relapse to develop a translational model for binge eating persistence. Adult male and female C57Bl6/J mice were randomized to a binge-like palatable food access schedule (daily 2-hr, 3×/week) or continuous, nonbinge like palatable food access for 12 days (Experiment 1). Persistence of palatable food consumption in both binge-like palatable food access groups was then examined across three cycles of forced abstinence and reexposure to palatable food (incubation) to model the persistence of binge eating in clinical populations. Mice with daily 2-hr palatable food access escalated their intake more than mice in the 3×/week or continuous groups (Experiment 1). This pattern was more pronounced in females. In addition, this pattern of palatable food intake reemerged across multiple cycles of behavioral incubation (Experiment 2). These findings provide a model of binge-like eating in mice that can be used in future studies examining both environmental factors and neural mechanisms contributing to binge eating persistence. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Same day access: a viable alternative for outpatient clinical care

To present our experience with a novel, same-day access (SDA) scheduling model for outpatient clinical care in oral and maxillofacial surgery (OMS). The primary outcome variable was OMS patient scheduling in a hospital-based outpatient clinic. Patients were given a specific appointment time to be seen the same day they contacted the clinic. This SDA clinic was compared to previous patient scheduling models for patient satisfaction, appointment wait times, annual clinic volume, no-show rates, and access to care. Patient satisfaction increased to 80% with SDA scheduling compared with 20% to 40% with prior models. The average wait time for patients improved to 19 minutes compared with 330 minutes with the walk-in model. Forty patients were scheduled on the same day, and 96% of all patients who called the clinic were seen within 14 days with the SDA approach. Same-day access was the only model that met its volume and budgetary goals. The incorporation of SDA scheduling improves patient satisfaction and is a viable alternative to more traditional scheduling protocols for clinics suffering from volume, revenue, and access to care issues.

Concurrent experimentation in NCSLab: A scalable approach for online laboratories

The scheduling of user access to test rigs is vital for online laboratories, as a good access scheduling scheme can reduce waiting time and improve the utilization of experimentation systems. To enhance the benefits of online laboratories and also improve user experience, a novel system that is constructed based on front-end and back-end separation has been explored in this paper, which is scalable with a complex four-tier architecture supporting both remote and virtual experiments. A concurrent scheme that allows many users to conduct real-time interactive experiments with a single test rig has been implemented. The new system enables massive access for virtual experimentation and saves users from booking sessions in advance or queuing. To verify the effectiveness of the system, a renewable energy system has been developed, thus, users can concurrently conduct experiments with different control algorithms and monitoring interfaces for research and education purposes. A scalability test was conducted, the results of which showed that 94.67% of 300 users can concurrently access the same virtual laboratory, proving the scalability and concurrency features of the proposed system. The system demonstrated a throughput of 499.4 requests per second without errors during a 30-second performance test with 1600 concurrent users, where each user established 10 connections.

Dynamic average consensus control based on event-triggered cloud access

A dynamic average consensus (DAC) control scheme is proposed in the presence of constrained communication, where event-triggered cloud access is presented with a cloud repository for agents. With this framework, agents upload and download information from the cloud repository, in which they exchange information with neighbors indirectly. We first propose a triggered condition with a deviation of control signals for reduction of the frequency of communication with the cloud repository. Due to the fact that the neighbors’ information in the condition can’t be obtained in the cloud framework, cloud access scheduling rules, with an adaptive threshold for control signal updating, are then introduced via available information at current instants, and agents access the cloud repository in an asynchronous manner to avoid congestion. Available information from the cloud is employed, as well as their own, into the triggered condition for prediction of next access instants, and the triggered consequence is generated. Stability analysis presents that the control scheme in this paper steers the MAS to achieve DAC with an ultimately bounded tracking error and rules out Zeno behaviors. The effectiveness of the control scheme is verified via an example.