Scheduling Period Research Articles

Edge Computing Task Offloading for Environmental Perception of Autonomous Vehicles in 6G Networks

The most basic requirement for autonomous vehicles is accurate environmental perception. However, the lack of onboard computing resources makes it difficult for such a vehicle to process all environmental information. Through the edge computing technology and 6G networks, vehicles can offload computing tasks to edge servers for execution, which alleviates the problem of insufficient onboard resources. The environmental perception task offloading problem for autonomous vehicles is studied. The purpose is to improve the environmental perception quality through reasonable task offloading. After assigning dynamic priorities to tasks generated by autonomous vehicles, the multi-vehicle and multi-server task offloading process is abstracted as a Markov decision process, and an offloading decision algorithm based on deep reinforcement learning is designed to select edge nodes for task execution to obtain better long-term benefits. The earliest deadline first algorithm is improved to consider the deadline and priority of each task, allowing the edge node to complete more high-priority tasks within the specified time. Experimental results show that the proposed method can guarantee the basic environmental perception requirements of every vehicle, and performs better than existing methods in terms of the total priority of the discarded tasks in each scheduling period and the completion rate of key tasks.

基于 Hdyrus-2D 和 Stewart 模型的半干旱区灌溉制度优化及其应用

Water scarcity has been a critical constraint to economic development in semi-arid areas of China, so optimizing irrigation scheduling has become essential. This study obtained quantitative relationships between crop yield, crop water consumption, and irrigation quantity based on the Hydrus-2D and Stewart models. Different irrigation scheduling scenarios were evaluated to obtain the best irrigation scheduling based on the principle of simultaneous water conservation and crop productivity improvement with the evaluation indicators of crop yield, water use efficiency (WUE), irrigation water use efficiency (IWUE), and Critic-Topsis method. Taking drip irrigation under mulch as an example, the problem of optimizing the irrigation scheduling for different typical years was calculated. The optimization results showed that in the wet, normal, dry, and very dry years the annual irrigation quantity should be 49.68 mm, 49.68 mm, 85.38 mm, and 123.72 mm, when the WUE as well as IWUE, increases significantly, which had less impact on the crop yield and can save irrigation quantity by 30.00%, 30.00%, 35.00%, 27.00%. This study used Hydrus-2D to make a new attempt in irrigation scheduling optimization, giving full play to the model's high accuracy in soil water transport simulation and flexibility in boundary condition simulation. The optimization results can provide a reference for achieving accurate control of irrigation quantity during the crop growth period and reasonable irrigation scheduling formulation for regional crops.

Methodological Approaches to Assessing the Economic Damage Associated with the Incidence of Hemorrhagic Fever with Renal Syndrome in the Russian Federation

The aim of the study was to develop methodological approaches to assessing the economic damage associated with the incidence of hemorrhagic fever with renal syndrome (HFRS) and to calculate the economic damage by the example of an outbreak of HFRS in the Saratov region in 2019. Materials and methods. The paper analyzes the economic indicators of the Federal State Statistics Service; data on the incidence of HFRS in the Russian Federation for the period of 2019–2022. To calculate the cost of outpatient and inpatient medical care, as well as the costs associated with the medical follow-up of convalescents, the indicators of the Program of state guarantees of free provision of medical care to citizens for 2022 and for the scheduled period of 2023 and 2024 were used. The calculation of economic losses associated with the payment of temporary disability benefits was carried out according to the equation provided in the Federal Law No. 255-FZ dated December 29, 2006 (as amended on October 07, 2022). Economic losses associated with premature death at an economically active age were calculated based on the value of unproduced GDP due to lost years of life in the corresponding age group. Results and discussion. The costs of treatment, rehabilitation and payment of temporary disability benefits for 1 case of HFRS at the age of 0 to 56.5 years for the female population and from 0 to 61.5 years for the male population amount to 140 495 rubles; over the age of 56.5 years for the female population and 61.5 years for the male population – 95 412 rubles, respectively. Each fatal case of HFRS aged 0 to 16 years among the male population costs the state 38 976 231 rubles; among the female population – 34 708 331 rubles; in active working age – the value of economic damage varies depending on the age of the person who died of HFRS. The economic damage of the outbreak of HFRS in the Saratov Region (2019), taking into account the direct expenditures of the healthcare system and indirect losses of the country’s economy amounted to 441 453 432 rubles. It is of note that the structure of the main damage is dominated by indirect losses in the economy caused by the premature death of people in economically active age.

STYLE (NCT03449173): A Phase 2 Trial of Sunitinib in Patients With Type B3 Thymoma or Thymic Carcinoma in Second and Further Lines

IntroductionThymic malignancies are rare tumors with few therapeutic options. The STYLE trial was aimed to evaluate activity and safety of sunitinib in advanced or recurrent type B3 thymoma (T) and thymic carcinoma (TC). MethodsIn this multicenter, Simon 2 stages, phase 2 trial, patients with pretreated T or TC were enrolled in two cohorts and assessed separately. Sunitinib was administered 50 mg daily for 4 weeks, followed by a 2-week rest period (schedule 4/2), until disease progression or unacceptable toxicity. The primary endpoint was objective response rate (ORR). Progression-free survival, overall survival, disease control rate and safety were secondary endpoints. ResultsFrom March 2017 to January 2022, 12 patients with T and 32 patients with TC were enrolled. At stage 1, ORR was 0% (90% confidence interval [CI]: 0.0–22.1) in T and 16.7% (90% CI: 3.1–43.8) in TC, so the T cohort was closed. At stage 2, the primary endpoint was met for TC with ORR of 21.7% (90% CI: 9.0%–40.4%). In the intention-to-treat analysis, disease control rate was 91.7% (95% CI: 61.5%–99.8%) in Ts and 89.3% (95% CI: 71.8%–97.7%) in TCs. Median progression-free survival was 7.7 months (95% CI: 2.4–45.5) in Ts and 8.8 months (95% CI: 5.3–11.1) in TCs; median overall survival was 47.9 months (95% CI: 4.5–not reached) in Ts and 27.8 months (95% CI: 13.2–53.2) in TCs. Adverse events occurred in 91.7% Ts and 93.5% TCs. Grade 3 or greater treatment-related adverse events were reported in 25.0% Ts and 51.6% TCs. ConclusionsThis trial confirms the activity of sunitinib in patients with TC, supporting its use as a second-line treatment, albeit with potential toxicity that requires dose adjustment.

An Iterative Re-Optimization Framework for the Dynamic Scheduling of Crossover Yard Cranes with Uncertain Delivery Sequences

In yard-crane scheduling problems, as loading operations take priority over unloading, the delivery sequence of unloading from the quaysides to the yard is uncertain. The delivery sequence changes may make crane scheduling more difficult. As a result, the crane operations schedules developed statically become suboptimal or even infeasible. In this paper, we propose a dynamic scheduling problem considering uncertain delivery sequences. A mixed-integer linear program is developed to assign tasks to cranes and minimize the makespan of crane operations. We propose an iterative solution framework in which the schedules are re-optimized whenever the delivery sequence change is revealed. A genetic algorithm is proposed to solve the problem, and a greedy algorithm is designed to re-optimize and update the solution. To make the updated solution take effect as soon as possible, regarding batch-based task assignment, the tasks in the scheduling period are divided into several batches. In this case, the instant requests arising from the delivery sequence change are added to corresponding batch tasks and re-optimized together with the tasks of this batch. In addition, a relaxation model is formulated to derive a lower bound for demonstrating the performance of the proposed algorithm. Experimental results show that the average gap between the algorithm and the lower bound does not exceed 5%. The greedy insertion algorithm can re-optimize the instant requests in time. Therefore, the proposed iterative re-optimization framework is feasible and has the advantages (necessity) of batch-based task assignment.

A Multistep Iterative Ranking Learning Method for Optimal Project Portfolio Planning of Smart Grid

Optimal project portfolio planning is a typical nonconvex, multiobjective, highly constrained, multitemporal coupling, and combinatorial optimization problem. This paper proposes a novel multistep iterative ranking learning method (MIRL) to solve this complex combinatorial optimization problem from massive infrastructure projects of smart grid. The optimal project portfolio planning problem of power grid is formulated as the optimization process of massive project priority sorting with an improved knapsack model. The proposed method dynamically optimizes the best infrastructure project combination for each round to maximize the economic, social, and security benefits without exceeding the annual investment limit. A pairwise-based ranking learning algorithm is used to mine the priority sorting law from massive historical combination data of power grid to initialize candidate project portfolio. In order to approach the optimal portfolio planning solution with the constraint satisfactions of project construction duration and electric load supplies, a heuristic greedy strategy is designed to search the solution dynamically for selecting the project having highest construction benefits iteratively. The effectiveness of the proposed method is proved by experiments with real-world project data of Hunan power grid in China, and experimental results show that the proposed MIRL can outperform other methods on investment efficiency, calculation time, and rationality of project construction period schedule.

Storage allocation rules to meet shared water demands for optimal operation of reservoir water supply

AbstractThe priority principle of storage allocation rules of serial cascade reservoirs within an interbasin water supply can reduce water loss and reduce water supply times. Reasonable balancing curves for reservoirs in parallel are proposed, and the proportional distribution of water is determined to illustrate the optimal allocation rule for different reservoir scheduling periods. The mutation point and slope are used to describe the segmentation of reservoirs in parallel. Finally, the relative optimal water supply rule is obtained. Taking the reservoir groups in the lower reaches of the Luanhe River basin as the research object, the results show that the water supply obtained by the balancing curve is increased by approximately 4% compared with the compensation regulation, and wasted water is reduced by 10%. The results are close to the largest water supply, the annual average wasted water and the guarantee rate obtained by dynamic programming. The suggested method can achieve the operation goal effectively and improve the operation performance of the shared water demands for the reservoir water supply. This article highlights the superior results obtained compared with the current storage allocation rules to meet shared water demands.

Research on Day-Ahead Optimal Scheduling Considering Carbon Emission Allowance and Carbon Trading

In the context of the marketization of carbon trading in the power system, it is of great theoretical and practical significance to study a scientific and effective carbon emission quota allocation strategy. To solve this problem, under the current situation of large-scale access to new energy, considering the limitations of the carbon emissions from different emission subjects plus the construction of a carbon trading model among the emission subjects, a day-ahead optimal scheduling method that takes carbon emission quotas and carbon trading into account is proposed. Firstly, carbon transaction cost models of thermal power and wind power are constructed, respectively, and a carbon emission quota allocation strategy based on the entropy method is proposed to redistribute the weights of baseline emission factors for the regional power grid. Then, considering the additional carbon emissions of conventional thermal power units caused by wind power access, the carbon trading costs of different types of generation units are calculated on the basis of carbon trading price prediction. Thereafter, a day-ahead optimal scheduling model considering carbon emissions trading is constructed with the objective of minimizing the total cost of the system in the scheduling period. The model is solved as an MINLP problem based on MATLAB 2016a software utilizing CPLEX 12.4. Simulation results verify the correctness and effectiveness of the proposed method.

A novel economic scheduling of multi-product deterministic demand for co-production air separation system with liquid air energy storage

Air separation units (ASUs) integrated with liquid air energy storage (LAES) have the potential to balance grid demand and improve production profits. This study aims to enhance the demand response of a novel co-production air separation system (NCASS) by maximizing the energy arbitrage of a LAES system. We developed a mixed-integer nonlinear programming model to minimize operating costs by using a proxy model to represent the ASU production space and a black box model to represent the material and energy flow balance of LAES. The model is based on rigorous mathematical programming and, considers material and energy flow balance, analyzes the production and delivery processes and constraints for each product, and matches equipment start-up and shutdown time constraints. The case study shows that the model achieves a high level of matter and energy matching between the distillation process and the LAES process, maximizing the LAES peak-shaving capacity and improving system economics. During the 24 h schedule period, the total electricity consumption of NCASS increases by 18.94% during the valley electricity period and decreases by 20.59% during the flat and peak electricity period. The economic benefits increase by 9.51 k$, accounting for 14.29% of the total costs. This study contributes to the wider application of NCAS with LAES technology for sustainable energy management.

A data-driven bi-objective matheuristic for energy-optimising timetables in a passenger railway network

Energy-efficient train timetabling (EETT) is essential to achieve the full potential of energy-efficient train control, which can reduce operating costs and contribute to a reduction in CO2 emissions. This article proposes a bi-objective matheuristic to address the EETT problem for a railway network. To our knowledge, this article is the first to suggest using historical data from train operation to model the actual energy consumption, reflecting the different driving behaviours. The matheuristic employs a genetic algorithm (GA) based on NSGA-II. The GA uses a warm-start method to generate the initial population based on a mixed-integer program. A greedy first-come-first-served fail-fast repair heuristic is used to ensure feasibility throughout the evolution of the population. The objectives taken into account are energy consumption and passenger travel time. The matheuristic was applied to a real-world case from a large North European train operating company. The considered network consists of 107 stations and junctions, and 18 periodic timetables for 9 train lines. Our results show that for an entire network, a reduction up to 3.3% in energy consumption and 4.64% in passenger travel time can be achieved. The results are computed in less than a minute, making the approach suitable for integration with a decision support tool.

Gastrointestinal stromal tumors of the small intestine: the challenge of diagnosis and the outcome of management

PurposesGastrointestinal stromal tumor (GIST) is a rare small intestinal tumor. Most patients usually report long-period complaints due to difficult diagnoses. A high grade of suspicion is required for early diagnosis and initiation of the proper management.MethodsA retrospective study of all patients with small intestinal GIST who were operated in the period between January 2008 and May 2021 at Mansoura University Gastrointestinal Surgical Center (GIST).ResultsThirty-four patients were included in the study with a mean age of 58.15 years (± 12.65) with a male to female ratio of 1.3:1. The mean duration between onset of symptoms and diagnosis was 4.62 years (± 2.34). Diagnosis of a small intestinal lesion was accomplished through abdominal computed tomography (CT) in 19 patients (55.9%). The mean size of the tumor was 8.76 cm (± 7.76) ranging from 1.5 to 35 cm. The lesion was of ileal origin in 20 cases (58.8%) and jejunal in 14 cases (41.2%). During the scheduled follow-up period, tumor recurrence occurred in one patient (2.9%). No mortality was encountered.ConclusionDiagnosis of a small bowel GISTs requires a high grade of suspicion. Implementing new diagnostic techniques like angiography, capsule endoscopy, and enteroscopy should be encouraged when suspecting these lesions. Surgical resection is always associated with an excellent postoperative recovery profile and very low recurrence rates.

Enhancing Resilience in Mobile Edge Computing Under Processing Uncertainty

Task offloading is a powerful tool in Mobile Edge Computing (MEC). However, in many practical scenarios, the number of required processing cycles of a task is unknown beforehand and only known until its completion. This poses a serious challenge in making offloading decisions as the number of processing cycles is a key parameter to determine whether a task’s deadline can be met. To cope with such processing uncertainty, we formulate a Chance-Constrained Program (CCP) that offers probabilistic guarantees to task deadlines. The goal is to minimize energy consumption for the users while meeting the probabilistic task deadlines. We assume that only the means and variances of the random processing cycles are available, without any knowledge of distribution functions. We employ a powerful tool called Exact Conic Reformulation (ECR) that reformulates probabilistic deadline constraints into deterministic ones. Subsequently, we design an online solution called EPD (Energy-minimized solution with Probabilistic Deadline guarantee) for periodic scheduling and schedule updates during run-time. We show that EPD can address the processing uncertainty with probabilistic deadline guarantees while minimizing the users’ energy consumption.

Mars: Near-Optimal Throughput with Shallow Buffers in Reconfigurable Datacenter Networks

The performance of large-scale computing systems often critically depends on high-performance communication networks. Dynamically reconfigurable topologies, e.g., based on optical circuit switches, are emerging as an innovative new technology to deal with the explosive growth of datacenter traffic. Specifically, periodic reconfigurable datacenter networks (RDCNs) such as RotorNet (SIGCOMM 2017), Opera (NSDI 2020) and Sirius (SIGCOMM 2020) have been shown to provide high throughput, by emulating a complete graph through fast periodic circuit switch scheduling. However, to achieve such a high throughput, existing reconfigurable network designs pay a high price: in terms of potentially high delays, but also, as we show as a first contribution in this paper, in terms of the high buffer requirements. In particular, we show that under buffer constraints, emulating the high-throughput complete graph is infeasible at scale, and we uncover a spectrum of unvisited and attractive alternative RDCNs, which emulate regular graphs, but with lower node degree than the complete graph. We present Mars, a periodic reconfigurable topology which emulates ad-regular graph with near-optimal throughput. In particular, we systematically analyze how the degree d can be optimized for throughput given the available buffer and delay tolerance of the datacenter. We further show empirically that Mars achieves higher throughput compared to existing systems when buffer sizes are bounded.

Evaluasi Kondisi Kerja Pada UMKM Pempek Menggunakan Work Improvement In Small Enterprises (Wise)

Pempek Ita is a MSMEs that produces several types of processed pempek products, based on the results of initial observations there are several problems in their working conditions and the absence of K3 implementation in the workplace. This study aims to improve the work system by evaluating the condition of Pempek Ita using the WISE checklist, then using the Borda method for decision making. The evaluation results from the WISE checklist contained 19 elements that required corrective action. By using the Borda method, it is obtained that decision making for the priority of improving the work system is the work organization because it has the highest weight, which is 23%. Then a proposal for improvement of the work system is made based on the criteria of the work organization, namely implementing a periodic rest schedule in accordance with Article 79 paragraph (2) letter a of Law no. 13/2003 stipulates that companies must provide rest periods between working hours, at least half an hour after workers have worked continuously for 4 hours and that rest time does not include working hours. And conduct training programs for employees regarding OHS. General OHS expert training (Indonesian Ministry of Manpower Certification) is a program of the Ministry of Manpower (KEMNAKER) to prepare OHS experts in companies who can help develop OHS in companies.

Management of Railway Power System Peaks with Demand-Side Resources: An Application to Periodic Timetables

The objective of this paper involves the analysis of opportunities for the management of Railway Systems’ demand using Physical-Based models and aggregation tools well-known in “conventional” Power Systems to develop and enlarge the portfolio of Distributed Energy Resources. This proposed framework would also enable the use of railway flexible resources to their use in Power Systems. The work considers trends for the development of railway transportation units through the adoption of technologies that increase the flexibility of railway units. For instance, we mean a set of resources such as onboard generation in dual units, energy storage and generation in last-mile units, and auxiliary loads. Their inherent flexibility can contribute to increasing the management possibilities of the overall net demand. The proposed scenario under study faces some of the energy concerns of periodic timetables: fast and high-power peaks in demand unknown in conventional Power Systems. The simulation results present the achieved flexibility and its potential: a decrease in peak demand by around 20% and an increase in energy recovery by 10%, lagging new investments in infrastructure. These results improve the social and economic benefits of railway transportation on the overall energy and environmental objectives while reducing energy concerns due to the increasing use of railways and boosting the sustainability of the transportation system in the coming decades.

4-E (Energy-Emission-Environment-Economic) Dispatch Problem in Solar PV Energy Using Hybrid PSOTLBO Search Algorithm

Renewable energy sources have evolved into a technologically and economically feasible choice for use by electrical utilities. Furthermore, the widespread usage of renewable energy sources is driving policymakers and utilities to increase green energy’s role to ensure long-term economic growth. The most influential non-conventional energy source for generating power is solar energy. Electric power systems must be designed, built, and run in such a way that the majority of energy demand for loads is supplied reliably, cost-effectively, and in an environmentally responsible manner. In 4-E dispatch, the term “energy” refers to generated power in the scheduled period, the term “emission” refers to the amount of emission released in the scheduled period, and the term “environment” refers to health and environmental damage costs in the scheduled period and the term “economic” refers to power generating cost in the scheduled period. In this paper a hybrid of particle swarm optimization (PSO) and teaching learning-based optimization (TLBO), named as PSOTLBO is proposed, developed, and effectively applied to attain the best or optimum solutions for the 4-E (Energy-Emission-Environment-Economic) dispatch problem for scenarios involving ten thermal power plants and thirteen solar photovoltaic (PV) plants.

Newfangled Design Thinking-Based Application for Blood Donation and Assistance

All lives are in the digital era, where everything is available online and mostly application. To enrich its strength, an application for blood donation has been developed in the name of “Blood World”. This application helps to overcome the knowledgelessness over blood donation and services by providing accurate information about the availability of blood and ways to donate blood.There are more centers to provide the information on blood donation camps, but in this era the human beings are busy with their periodic schedule. so make it available in the form of a mobile application. Requests can also be given which will be processed earlier than the available ones. The application also includes information about the cause and preventive measures about blood related problems and also includes options for making appointments with the doctors. The complete design is made up of XML and the powerful language JAVA is used in the construction of application. The app thus developed is highly reliable and is more user-friendly.

Newfangled Design Thinking-Based Application for Blood Donation and Assistance

All lives are in the digital era, where everything is available online and mostly application. To enrich its strength, an application for blood donation has been developed in the name of “Blood World”. This application helps to overcome the knowledgelessness over blood donation and services by providing accurate information about the availability of blood and ways to donate blood.There are more centers to provide the information on blood donation camps, but in this era the human beings are busy with their periodic schedule. so make it available in the form of a mobile application. Requests can also be given which will be processed earlier than the available ones. The application also includes information about the cause and preventive measures about blood related problems and also includes options for making appointments with the doctors. The complete design is made up of XML and the powerful language JAVA is used in the construction of application. The app thus developed is highly reliable and is more user-friendly.

Metabolic correction of sports horses, their adaptation to active muscular and nervous activity in the prize period

In modern conditions, sports horses are constantly exposed to stressful factors, in which significant clinical and biochemical changes occur in organs and systems, which leads to metabolic diseases, low athletic results andsignificant economic damage. Intensive training has a significant impact on the biochemical parameters of blood, clinical and physiological condition and muscular activity of sports horses. The busy schedule of the competitive period is accompanied by excessive stress of metabolic processes, which leads to rapidfatigue, decreased agility and sports horses lose their athletic form for a long time. Hematological, biochemical and physico-chemical parameters of the blood of sports horses are subject to changes under the influence of muscle work, metabolic processes and the stressful situation of the competitive period. The adaptation of the body to intense muscular activity consists in the peculiarities of training sportshorses. The level of adaptation of the body is characterized by an indicator of the functional state of the cardiovascular system - a change in the pulse rate, which reflects the activity of the heart and has a smaller number of heartbeats at rest. The degree of decrease in the pulse rate, which is the result of functional and morphological changes in the body, depends on the intensity of muscle loads, the type of equestrian sport and the duration of sports operation of the horse. Higher muscle activity is provided by the cardiovascular system, increasing the necessary blood flow and increasing energy metabolism, thus carrying out the transfer of oxygen to the tissues of the body. The role of blood circulation in the body is determined by the ability to keep the amount of oxygen delivered per unit of time by arterial blood to tissues at a level adequate to oxygen consumption in a given period. The amount of oxygen consumption characterizes the level ofredox processes in the body, and the measure of the participation of the processes of anaerobic energy formation in muscle activity is oxygen debt. The sum of these values, that is, oxygen consumption during work and oxygen debt, is the level of oxygen demand and is an indicator of the energy consumption of the body. All processes occurring in the body of sports horses and the connection with the external environment are regulated by the nervous system.

Factors influencing seniors' willingness to pay intention for exercise in the civil sports and recreation centers.

The increasing trend for an older population is a phenomenon that is well recognized around the world. The percentage of senior citizens participating in sports, recreation, and leisure activities is also increasing in order to sustain a healthier society. As long as seniors recognize the importance and benefits of keeping healthy, they would prefer to be active in various sports and fitness activities. The seniors could engage in making decisions about their own health by exercising regularly and by encouraging their similar-age peers. The civil sports and recreation centers (CSRCs) in Taiwan have adopted operating transfer (OT) and are located mainly in metropolitan areas, with programs consisting of indoor sports offering people daily exercise. The major aims of the CSRC are to keep the citizens in good health and not to be the city government's financial burden. The extant literature examines the determinants of general consumer behavior, neglecting studies on older adults. This study aims to explore the factors influencing seniors' willingness to pay (WTP) more for exercise in CSRCs outside of free hours. This mixed-method study consists of quantitative and qualitative analyses. For the quantitative component, we invited five experts in the sports industry from the industry and academia to evaluate the validity of the questionnaire. A questionnaire consisting of motivation, exercise involvement, and constraint constructs in the quantitative method was administered to 193 older adults in CSRCs. The collected data were analyzed through descriptive statistics, t-test, one-way analysis of variance (ANOVA), and structural equation model (SEM). Empirical results indicate that WTP in groups of people aged 75-79, 70-74, and 65-69 years is higher than in the group of people aged 85 years and above. Exercise involvement and motivation had more of a positive impact on seniors' WTP. Developing a regular exercise habits and having social interaction in exercise courses drive female seniors to pay more for body health. The results of this study provide managers of CSRCs with decision-making recommendations: (1) initiate entry-level sports courses, such as quick chair exercise, to cultivate among seniors the habit of exercise; (2) motivate seniors to participate in sports with other seniors in order to enhance their social activity and raise their WTP more for sports consumption outside of free scheduled periods; and (3) recruit seniors as exercise coaches or personal trainers to pass their experiences with other people of their age. In addition to expanding seniors' social connections, it encourages peers to exercise. Managerial implications and future research are also discussed. This study contributes to exploring the determinants of seniors' WTP intention. Motivation and exercise involvement had a significantly positive impact on seniors' WTP intention.