Synchronous Scheduling Research Articles

Application of synchronous music reinforcement to increase walking speed: A novel approach for training intensity.

Walking is a common and preferred form of exercise. Although there are current recommendations for walking volume (e.g., steps per day), recent research has begun to distinguish volume from intensity (e.g., "brisk" walking) as an important dimension of exercise. Increasing intensity may confer health advantages beyond volume measures because it shifts cardiovascular performance to more vigorous training zones. Reinforcement-based approaches have been valuable in increasing volume measures of exercise, and the present study sought to develop a corresponding reinforcement approach to training walking intensity. For this study, we used a continuous reinforcement paradigm where music played only while walking met specified criteria; otherwise, music playback stopped. As a result, music was synchronized with walking performance. Seventeen participants walked on a nonmotorized treadmill at a self-selected pace. Across the session, different conditions arranged for music to play independent of walking speed or contingent on speed increases or decreases. An extinction component assessed performance when music was withdrawn completely. Walking speed was selectively increased and decreased by adjusting the contingencies that were arranged for music, and variability in speed increased during extinction, with both findings indicating that music was a reinforcer. Heart rate was also increased to moderate-vigorous intensities during reinforcement. The findings provide a compelling case that walking intensity can be modified by music reinforcement. We suggest that synchronous schedules may be an important foundation for future exercise technologies that are based on reinforcement.

Time optimal gathering of myopic robots on an infinite triangular grid

This work deals with the problem of gathering n oblivious mobile entities, called robots, at a point (not known beforehand) placed on an infinite triangular grid. The robots are considered to be myopic, i.e., robots have limited visibility. Earlier works of gathering mostly considered the robots either on a plane or on a circle or on a rectangular grid under both full and limited visibility. In the triangular grid, there are two works to the best of our knowledge. The first one is by Cicerone et al. on arbitrary pattern formation where full visibility is considered. The other one by Shibata et al. which considers seven robots with 2-hop visibility that form a hexagon with one robot in the center of the hexagon in a collision-less environment under a fully synchronous scheduler.In this work, we first show that gathering on a triangular grid with 1-hop vision of robots is not possible even under a fully synchronous scheduler if the robots do not agree on any axis. So one axis agreement has been considered in this work (i.e., the robots agree on a direction and its orientation). We have also shown that the lower bound for time is Ω(n) epochs when n number of robots are gathering on an infinite triangular grid. An algorithm is then presented where a swarm of n number of robots with 1-hop visibility can gather within O(n) epochs under a semi-synchronous scheduler. So the algorithm presented here is time optimal.

Design of an interdisciplinary training program for interprofessional collaboration in health and social services in patient partnership: contribution of an empowering approach reinforced by instructional design

Interprofessional education (IPE) has been a key area of research and teaching practice for the past twenty years in both university and practice settings in the health sciences and social psychology. IPE training opportunities arise when students from multiple health professions interactively learn together about interprofessional collaboration and how to improve care outcomes for the community at large. It has been proven that the design of care is of higher quality when healthcare professionals understand each other's respective roles, facilitating their communication and teamwork. However, this type of pedagogical approach to interdisciplinary training is fraught with problems, such as communication barriers, synchronization of schedules and logistics, as well as the compartmentalization of professions, which can lead to prejudice despite the educational efforts made. What's more, these courses are attended by large cohorts of initial university trainees, and their pedagogical design may lack authentic anchors, thus diminishing the ability of individuals to mobilize interprofessional collaboration in care partnerships. This article proposes a theoretical model based on an enhanced capability approach, including the use of pedagogical design for student success, to design this type of training by overcoming.

Thick-billed Murres in breeding pairs migrate and overwinter far apart but in similar photic environments

Scheduling between mates in species with long-term pair bonds can be essential for positive fitness. The annual cycle in photoperiod is the primary environmental cue used by many animals to synchronize behavior and physiology among members of a population, and animals that migrate must have similar annual schedules to ensure successful breeding. However, we know little about whether members of mated pairs in migratory species experience similar photic environments across the year, which could allow for synchronization in annual phenology. Here, we used light-based geolocation to estimate positions of mated pairs of Thick-billed Murres (Uria lomvia, a seabird a.k.a. Brünnich’s Guillemot) which bred above the northern polar circle in Greenland. We tested the hypothesis that individuals in mated pairs occur in more similar locations and photic environments than randomly matched females and males. We found no difference in the amount of spatial separation or in the photic environment between mates and randomized heterosexual pairings. In general, the distance between females and males ranged from 1,198.5 km during August to 737.4 km during January. The sexes remained in photic environments with highly correlated photoperiods and moderately correlated times of solar noon in UTC. The spatial separation of, but similar photic environments experienced by, female and male murres regardless of pair status is probably adaptive by facilitating the synchronization of annual schedules between sexes, while allowing individuals in mated pairs the freedom to pursue the best foraging opportunities during migration and overwintering independent of their mate.

Rancang Bangun Sistem Informasi Asistensi Berbasis Website Menggunakan Teknologi MERN Stack

The STMIK Amikom Surakarta Assistant Forum is a forum under the UPT STMIK Amikom Surakarta which aims to assist the system of teaching and learning activities in STMIK Amikom Surakarta lectures. In the process of assistance activities taking place, assistants have several problems such as filling out attendance papers that use paper as evidence for attendance that has carried out assistance tasks, then in the process of recapitulating the treasurer's attendance as financial administrators must collect proof papers on each assistant making less effective, and lastly during the scheduling process that uses Excel as a scheduler tool, and will later be shared through groups, this creates a lack of schedule synchronization if at any time there is an updated schedule. Because of this problem the author aims to solve these problems by creating an information system that can perform attendance, recapitulation, and scheduling without using paper and efficiently. The researcher in this research process uses the RAD (Rapid Application Development) method because this method is fast and efficient in the development process. In the manufacturing process, researchers use MERN Stack technology.

A framework of cloud-edge collaborated digital twin for flexible job shop scheduling with conflict-free routing

Synchronous scheduling of transportation resources such as automated guided vehicles (AGVs) and production resources can effectively improve the production efficiency of an automated flexible job shop, however limited transportation resources and persistent abnormal disturbances compromise the accuracy, reliability and practicability of such scheduling. In order to address the flexible job shop scheduling problem with limited transportation resources (FJSP-T) under abnormal disturbances, here we propose a cloud-edge combined digital twin (DT) flexible job shop scheduling (CE-DTFJSS) framework to realize real-time scheduling. Firstly, a time-space network based zero-one programming (TSN-ZOP) model is established to optimize makespan and energy consumption of flexible job shop scheduling with conflict-free routing. Subsequently, to achieve real-time interaction between scheduling system and physical workshop, a cloud-edge architecture is introduced to allocate computing resources for scheduling-supporting tasks such as simulation, state monitoring and distributed control in the DT system. Additionally, we design a cloud edge collaboration rescheduling strategy based on a rolling window, to update the parameters’ values in the improved time window Dijkstra nested multi-layer coding genetic algorithm we proposed, thus real-time scheduling can be achieved. The effectiveness of CE-DTFJSS are verified by a numeric simulation based on a real-world case of a digitalized automobile welding workshop. The experimental results indicate that compared with the scheduling scheme without considering AGVs routing problem, the CE-DTFJSS framework can reduce makespan and energy consumption by 8.30% and 3.73%, respectively, and real-time responses to abnormal disturbances can be rendered within 0.1 s.

Using synchronous reinforcement to increase mask wearing in young children: A replication and extension

AbstractIn the current study, experimenters implemented synchronous schedules of reinforcement to increase mask wearing for up to 30 min for six children under the age of 5 years. Additionally, for a subset of children, we evaluated whether mask wearing would continue under baseline conditions in their classroom with staff during 30 min sessions (treatment extension), and later throughout the day (all‐day probes). Results showed the intervention increased mask wearing for all children for up to 30 min. Additionally, treatment‐extension sessions and all‐day probes, conducted with some children, showed mask wearing maintained in their classroom with staff.

Increasing Socially Significant Behaviors for Children with Autism Using Synchronous Reinforcement

In some types of reinforcement schedules, a reinforcer is presented or given to the child and interacted with continuously while a target behavior is occurring. Previous researchers have used this type of reinforcement as an assessment tool and to study basic reinforcement processes. However, little research has explored how to effectively use these schedules to reinforce socially important responses in applied settings. The current study analyzed the implementation of synchronous reinforcement in a nonconcurrent multiple baseline across participants. Several interventionists implemented synchronous reinforcement with four children with autism across a variety of responses and reinforcers. The results indicated that delivering social, audio/visual, and tangible stimuli on a synchronous schedule resulted in increased durations of targeted (e.g., social skills and motor skills) and nontargeted (e.g., approach, social bids, and speed) measures across all children. Recommendations regarding reinforcer and response selection in implementing synchronous schedules in applied settings are provided.

A comparison of synchronous and noncontingent stimulus delivery on task engagement.

Synchronous schedules of reinforcement are those in which the onset and offset of a reinforcer are synchronized with the onset and offset of a target behavior. The current study replicated and extended Diaz de Villegas et al. (2020) by comparing synchronous reinforcement to noncontingent stimulus delivery while evaluating on-task behavior of school-age children. A concurrent-chains preference assessment was then used to determine the preferred schedule. Results indicated that the synchronous schedule was more effective than the continuous, noncontingent delivery of the stimulus at increasing on-task behavior but that the children preferred noncontingent delivery. Additionally, the use of synchronous and noncontingent delivery did not alter the children's preference for the task.

The Method of Synchronous Scheduling of Multi-Product Make-to-Order Production

Make-to-order production needs flexibility, quality and synchronicity of planning. Numerous types of products and complex control parameters lead to high requirements for safety, stability and continuity of the production process, as well as strict requirements for instant production management. The need for a high reaction rate to changes in the production system, adaptability and traceability, must be ensured by methods of accurate and reliable control and management of production. The most difficulty is the stage of making a schedule for make-to-order multi-nomenclature productions. Existing systems of scheduling are often not connected in real time with the current production process, all this leads to a high level of unfinished orders. It is necessary to take a new look at the existing planning systems and search for an approach with the possibility of analyzing and optimizing the operational and production plan, taking into account the actual implementation of the provided production process. The research is aimed at developing a synchronous scheduling method suitable for a multi-nomenclature make-to-order production with a variable number of products, and designed to reduce order fulfillment time, reduce inventory and improve work efficiency by adapting to fluctuations in production and product life cycle and implementing an optimal production plan.

Using synchronous reinforcement to increase mask wearing in adults with intellectual and developmental disabilities.

In 2020 the Centers for Disease Control provided the public with recommendations to slow the spread of COVID-19 by wearing a mask in the community. In the current study, experimenters coached group home staff via telehealth to implement synchronous schedules of reinforcement to increase mask wearing for 5 adults with intellectual and developmental disabilities. Results showed the intervention effectively increased mask wearing for all participants for up to 30 min. Additionally, some participants for whom we assessed generalization of mask wearing demonstrated generalization to various community environments. Furthermore, procedural integrity data suggested staff could be coached via telehealth to implement the intervention, and staff surveys suggested the procedures and coaching were socially valid.

Joint optimisation of uncertain distributed manufacturing and preventive maintenance for semiconductor wafers considering multi-energy complementary

Aiming at the joint optimisation problem of uncertain distributed manufacturing and preventive maintenance (PM) for semiconductor wafers considering multi-energy complementary (UDMPM-MEC), a bi-level integrated scheduling model is constructed with interval makespan, total interval carbon emissions and total interval cost as the optimisation objectives. The upper model is used to obtain the joint optimisation scheduling scheme of distributed manufacturing and PM, and the lower model determines the energy allocation scheme on this basis. Given the problem characteristics, we propose an improved multi-objective whale swarm algorithm (IMOWSA). By designing jobs-to-factories allocation strategy, synchronous scheduling maintenance strategy, multi-energy complementary energy allocation decoding strategy, individual distance calculation strategy, multi-neighbourhood search strategy and deduplication strategy, the local and global search are effectively balanced, and the convergence precision is improved. A large number of simulation experiments and comparative analyses show that the IMOWSA algorithm is feasible and effective to solve this problem.

Container Terminal Berth and Yard Collaborative Allocation for Import and Export Synchronous Operations by Computational Logistics

Container terminal operators have practical and clear requirements on improving operational efficiency and service level to address running challenges. The resource allocation and collaborative scheduling of quayside berth and storage yard are vital issues in the optimization of container terminal handling systems (CTHSs). The allocation of berth in quayside and blocks on storage yard directly affects the running efficiency of CTHS. Consequently, we focus on the berth and yard collaborative allocation for import and export synchronous operations (BYCA-IESOs) and propose the BYCA-IESO research model based on synchronous or asynchronous integrated scheduling strategy by computational logistics. The BYCA-IESO model is a mixed integer quadratic programming model to minimize multiple time consumption of calling liners and the total horizontal transferring distances of yard trailers at container terminals. Furthermore, we design other two allocation policies for comparison on the BYCA-IESO, which are both multistage scheduling strategy profiles. CPLEX 20.1.0 is applied to implement and solve the model and tactics of BYCA-IESO. Accordingly, the feasibility, validity, and relative merits of the models and strategies are obtained and verified by analyzing and comparing multiple numerical experimental results.

Path-oriented synchronized transit scheduling using time-dependent data

With the emergence of innovations associated with public transport (PT) services, such as Mobility-as-a-Service, demand responsive transit, and autonomous vehicles, the door-to-door PT journey is achievable via multiple transfers between and within different PT modes. As such, seamless transfers between different modes of public transportation become an increasingly important factor for the attractiveness of PT services. At the same time, recent developments in travel time prediction methodologies offer new, reliable data sources for the optimization of PT operations. This work, with the consideration of these two elements, develops a mixed integer linear programming model for the PT schedule synchronization problem. The novelty is threefold. First, a novel concept of path-oriented scheduling is proposed. The path transfer time is explicitly formulated and minimized to provide a seamless travel experience considering that the emerging multimodal mobility inevitably induces multiple transfers. Second, time-dependent travel time data is also utilized in the model, which allows us to harness new and more representative data sources for improving PT services. Third, in order to complement the increase in computational complexity as a result of the utilization of time-dependent travel time data, three novel valid inequalities (VIs) are derived. Numerical studies show that the use of time-dependent travel time data is beneficial in terms of reducing path transfer times, when compared to using the mean historical travel times. The numerical study also reveals a tradeoff between the maximum allowable path transfer time and trip time. Using simulation studies on three bus lines in Copenhagen, we demonstrate that the valid inequalities could reduce the computation time by 8.5% on average, where the maximum reduction of computation time could reach 54.0%. The proposed valid inequalities are benchmarked against two classes of valid inequalities in the literature. It is found that the proposed valid inequalities could outperform those in the literature. We also found that further improvement in computational performance can be attained by using a combination of the proposed valid inequalities.

Digitalization and Information Management Mechanism of Sports Events Based on Cooperative Sensing Model of Multisensor Nodes

This paper provides an in-depth study and analysis of the optimization of sports event management systems using wireless sensor networks. Aiming at the monitoring task of a directed wireless sensor network in a three-dimensional environment, the directed sensing nodes scattered inside the designated monitoring area in a random deployment manner usually have uneven distribution and other problems; we analyze the characteristics of the directed sensor nodes, probabilistic sensing model, and the cooperative sensing model of multiple sensor nodes for monitoring target points and propose a sensing optimization strategy in polar coordinates to guide the three-dimensional plane directed orientation adjustment and sensing optimization of sensor nodes, thus enhancing the sensing capability of network nodes. The experimental results confirm that the algorithm can improve the coverage of the area to be monitored and the quality of sensing service, and it reduces the overall energy consumption of the network by using the distributed node synchronization scheduling mechanism to extend the life cycle of the network to maintain good monitoring capability under the premise of the limited total usage of the directed nodes in wireless sensor networks. The application of wireless sensor network technology in sports competition management mainly includes the application of smart wearable devices in sports competition training, the application of goal-line technology in sports competition, and the application of eagle eye technology in sports events, all three technologies have certain advantages in the application of sports competition, and all of their help to promote the improvement of sports event management and the development of sports industry; the second aspect is wireless sensor. The second aspect is the application of wireless sensor network technology in sports event information management, which is mainly used to collect information related to sports events and fully utilize it to make sports event management more informative and digital, which is helpful to improve the level of sports event management; the third aspect is the application of wireless sensor network technology in sports event stadium management, which is mainly based on intelligent stadiums to create a more spectator-friendly and good experience for the audience, a more ornamental and good experience viewing place, to promote the development and growth of sports industry.

Improved Energy Based Multi-Sensor Object Detection in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can sense physical characteristics such as temperature, sound, pressure, energy, and so on. WSNs have secure link to physical environment and robustness. Data Aggregation (DA) plays a key role in WSN, and it helps to minimize the Energy Consumption (EC). In order to have trustworthy DA with a rate of high aggregation for WSNs, the existing research works have focused on Data Routing for In-Network Aggregation (DRINA). Yet, there is no accomplishment of an effective balance between overhead and routing. But EC required during DA remained unsolved. The detection of objects belonging to the same event into specific regions by the Bayes Node is distributed through the Sensor Nodes (SNs). Multi-Sensor Data Synchronization Scheduling (MSDSS) framework is proposed for efficient DA at the sink in a heterogeneous sensor network. Secure and Energy-Efficient based In-Network Aggregation Sensor Data Routing (SEE-INASDR) is developed based on the Dynamic Routing (DR) structure with reliable data transmission in WSNs. Theoretical analysis and experimental results showed that in WSN, the proposed Bayes Node Energy Polynomial Distribution (BNEPD) technique reduced Energy Drain Rate (EDR) by 39% and reduced 33% of Communication Overhead (CO) using poly distribution algorithm. Similarly, the proposed MSDSS framework increased the Network Lifetime (NL) by 15%. This framework also increased 10.5% of Data Aggregation Routing (DAR). Finally, the SEE-INASDR framework significantly reduced EC by 51% using a Secure and Energy-Efficient Routing Protocol (SEERP).

Virtual Interprofessional Education (VIPE): a Multi-institutional Innovation.

The virtual interprofessional (VIPE) site provides asynchronous content with both video and written case vignettes, pedagogic facilitator guides, and synchronous scheduling options for IPE trainings. VIPE offers an efficient opportunity for educators and students to learn from, with, and about each other in the virtual world.

Investigation synchronous planning methods efficiency in small-batch make-to-order production

Lack of effective planning methods is one of the reasons for uneven use of production capacity, the occurrence of unplanned downtime and various types of losses. Small-scale make-to-order productions are characterized by weak workplaces specialization, by the versatility of the equipment used with a wide range of used components. They differ in the presence of repeated processing of part at the same workplaces and in occurrence of “a return flow” in a production system. The article discusses the features of planning due to technological specifics in such enterprises and a significant number of applicable incoming nomenclature items. Existing systems of production planning such Manufacturing Execution System and Advanced Planning & Scheduling System are compared, variants of their algorithmic implementation are proposed. The authors investigated the effectiveness of the application of the developed algorithms for different planning levels - interdepartmental and shop, depending of the size of order book and number of technological operations. The analysis of the conducted research allows us to assert that to provide synchronous scheduling in make-to-order small-scale productions it is necessary to apply combined planning approach using APS-and MES-technologies together.

ZipLine: an optimized algorithm for the elastic bulk synchronous parallel model

The bulk synchronous parallel (BSP) is a celebrated synchronization model for general-purpose parallel computing that has successfully been employed for distributed training of deep learning models. A shortcoming of the BSP is that it requires workers to wait for the straggler at every iteration. Therefore, employing BSP increases the waiting time of the faster workers of a cluster and results in an overall prolonged training time. To ameliorate this shortcoming of BSP, we propose ElasticBSP, a model that aims to relax its strict synchronization requirement with an elastic synchronization by allowing delayed synchronization to minimize the waiting time. ElasticBSP offers more flexibility and adaptability during the training phase, without sacrificing the accuracy of the trained model. ElasticBSP is realized by the algorithm named ZipLine, which consists of two phases. First, it estimates for each worker the end time points of its future iterations at run time, and then a one-pass algorithm over the estimated time points of all workers is employed to fast compute an optimal future time point for synchronization. We provide theoretical results about the correctness and performance of the ZipLine algorithm. Furthermore, we propose algorithmic and implementation optimizations of ZipLine, namely ZipLineOpt and ZipLineOptBS, which reduce the time complexity of ZipLine to linearithmic time. A thorough experimental evaluation demonstrates that our proposed ElasticBSP model, materialized by the proposed optimized ZipLine variants, converges faster and to a higher accuracy than the predominant BSP. The focus of the paper is on optimizing the synchronization scheduling over a parameter server architecture. It is orthogonal to other types of optimizations, such as the learning rate optimization.

Collaborative optimization for logistics and processing services in cloud manufacturing

Efficient service scheduling is an important technique to support collaborative manufacturing platforms such as IoT-enable manufacturing systems and cloud manufacturing. In the past few years, optimization problems for processing services have attracted the most attention of researchers and practitioners in terms of task matching, service selection, and scheduling. Logistics services, as another important kind of services in the cloud manufacturing environment, need to be explored further, beyond parameters of costs and time, in order to obtain more efficient task execution and more timely product delivery. In this paper, we consider the problem of synchronous scheduling of logistics services and processing services in cloud manufacturing. Based on the mathematical description, we present a collaborative optimization algorithm for logistics and processing services which we call COOPS to generate scheduling solutions for both processing tasks and logistics tasks at the same time. Typical optimization algorithms such as pattern search, particle swarm optimization and simulated annealing are compared with the proposed algorithm to show their performance on the average completion time of all manufacturing tasks. Results show that the proposed method obtains a shorter average completion time for all tasks in different scenarios.