• Journal of the Korea Society of Computer and Information
• /
• v.24 no.6
• /
• pp.81-88
• /
• 2019

Based on the theory of planned behavior and the theory of legal deterrence, this study takes consumers' willingness to pay for digital music as the research object, investigates the consumers who have digital music consumption channels and behaviors, and discusses the willingness of consumers to pay for digital music and its influencing factors. The study attempts to achieve the following research purposes: First, explore the influencing factors of willingness to pay for digital music using domestic and foreign literature research and related content analysis. Second, we want to examine the effect of Attitude, Collective Specifications, Quality Sensitivity and Music affinity on willingness to pay. Third, Legal deterrence and resource availability tries to verify whether there is a moderating effect between Attitude, Collective Specifications, Quality Sensitivity and Music affinity and willingness to pay. The research data was collected in 2019 between April 6th to May 8th. Questionnaires were randomly distributed in fixed places, mainly in Hubei Province, China. A total of 393 questionnaires were selected for data analysis. Based on the previous theoretical review and empirical analysis, the study draws the following conclusions: Firstly, attitude, collective specifications, quality sensitivity and music affinity have an impact on the willingness to pay. Second, Legal deterrence has a regulatory effect on the relationship among quality sensitivity, musical affinity and the willingness to pay. Last the resource availability has a significant impact on the willingness to pay. It also has a regulatory effect on the relationship among quality sensitivity, music affinity and the willingness to pay.

• Journal of Internet Computing and Services
• /
• v.24 no.2
• /
• pp.1-10
• /
• 2023

The Multi-access Edge Computing (MEC) paradigm equips network edge telecommunication infrastructure with cloud computing resources. It seeks to transform the edge into an IT services platform for hosting resource-intensive and delay-stringent services for mobile users, thereby significantly enhancing perceived service quality of experience. However, erratic user mobility impedes seamless service continuity as well as satisfying delay-stringent service requirements, especially as users roam farther away from the serving MEC resource, which deteriorates quality of experience. This work proposes a deep reinforcement learning based service mobility management approach for ensuring seamless migration of service instances along user mobility. The proposed approach focuses on the problem of selecting the optimal MEC resource to host services for high mobility users, thereby reducing service migration rejection rate and enhancing service availability. Efficacy of the proposed approach is confirmed through simulation experiments, where results show that on average, the proposed scheme reduces service delay by 8%, task computing time by 36%, and migration rejection rate by more than 90%, when comparing to a baseline scheme.

• Industrial Engineering and Management Systems
• /
• v.9 no.2
• /
• pp.70-79
• /
• 2010

Makespan and cost minimization are two important factors in project investment. This paper considers a multi-mode resource-constrained project scheduling problem with the objective of minimizing costs, subject to a deadline constraint. A number of studies have focused on minimizing makespan or resource availability cost with a specified deadline. This problem assumes a fixed cost for the availability of each renewable resource per period, and the project cost to be minimized is the sum of the variable cost associated with the execution mode of each activity. The presented memetic algorithm (MA) consists of three features: (1) a truncated branch and bound heuristic that serves as effective preprocessing in forming the initial population; (2) a strategy that maintains two populations, which respectively store deadline-feasible and infeasible solutions, enabling the MA to explore quality solutions in a broader resource-feasible space; (3) a repair-and-improvement local search scheme that refines each offspring and updates the two populations. The MA is tested via ProGen generated instances with problem sizes of 18, 20, and 30. The experimental results indicate that the MA performs exceptionally well in both effectiveness and efficiency using the optimal solutions or the current best solutions for the comparison standard.

• Journal of Ecology and Environment
• /
• v.48 no.3
• /
• pp.374-381
• /
• 2024

Background: There is a wide range of phenotypic plasticity in plants that respond to tissue damage. Compensatory growth after physical damage may function as a part of tolerance to herbivory, which is affected by resource limitations and/or damage properties. Results: Under different light availability (unshaded and shaded) and damaged leaf ontogeny (control, young leaf- and mature leaf-damaged), compensatory growth was examined for the herbal vine Aristolochia contorta. Under the unshaded treatment, compensatory growth on leaf and branch emergence was strongly induced compared to the shaded treatment. Damage to young leaves induced leaf emergence more strongly than damage to old leaves. Conclusions: It appears that light availability acted as a limiting factor in the compensatory growth of A. contorta after the damage despite its vigorous growth under the shade treatment. Under the shade, leaf damage led to altered biomass allocation as indicated by a decrease in specific leaf area and an increase in root mass fraction. The present study contributes to the understanding of the phenotypic plasticity of vine species under different environmental conditions and damaged tissue, which may differ depending on the species' habitat range.

• KIPS Transactions on Computer and Communication Systems
• /
• v.4 no.9
• /
• pp.283-288
• /
• 2015

Scientists gain benefits from on-demand scalable resource provisioning, and various computing environments by using cloud computing resources for their applications. However, many cloud computing service providers offer their cloud resources according to their own policies. The descriptions of resource specification are diverse among vendors. Subsequently, it becomes difficult to find suitable cloud resources according to the characteristics of an application. Due to limited understanding of resource availability, scientists tend to choose resources used in previous experiments or over-performed resources without considering the characteristics of their applications. The need for standardized notations on diverse cloud resources without the constraints of complicated specification given by providers leads to active studies on intercloud to support interoperability in hybrid cloud environments. However, projects related to intercloud studies are limited as they are short of expertise in application characteristics. We define an intercloud resource classification and propose semantic resource recommendation based on statistical analysis to provide semantic cloud resource services for an application in hybrid cloud computing environments. The scheme proves benefits on resource availability and cost-efficiency with choosing semantically similar cloud resources using cluster analysis while considering application characteristics.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2004.10a
• /
• pp.527-530
• /
• 2004

This paper presents an optimization formulation for resource scheduling in Critical Resource Diagramming (CRD) of production scheduling networks. A CRD network schedules units of resources against points of needs in a production network rather than the conventional approach of scheduling tasks against resource availability. This resource scheduling approach provides more effective tracking of utilization of production resources as they are assigned or 'moved' from one point of need to another. Using CRD, criticality indices can be developed for resource types in a way similar to the criticality of activities in Critical Path Method (CPM). In our supply chain model, upstreams may choose either normal operation or expedited operation in resource scheduling. Their decisions affect downstream's resource scheduling. The suggested optimization formulation models resources as CRD elements in a production two-stage supply to minimize the total operation cost

• Journal of the Korea Society for Simulation
• /
• v.12 no.4
• /
• pp.51-59
• /
• 2003

Real-Time applications on Grid environment have several problems in terms of resource management addressed as follows; (1) dynamic resource allocation to provide QoS objectives, (2) heterogeneous resources that is different scale, or capacity in same unit, and (3) resource availability, and resource needs. This paper describes the techniques of resource manager (RM) handling above problems to support QoS of dynamic real-time applications on Grid. The contributions of this paper to solve problems are as follows: unification of dynamic resource requirements among heterogeneous hosts, control of resources in heterogeneous environments, and dynamic load balancing/sharing. Our heuristic allocation scheme works not only 257% better than random, 142% better than round robin, and 36.4% better than least load in QoS sensitivity, but also 38.6% better than random, 28.5% better than round robin, and 31.6% better than least load in QoS.

• International conference on construction engineering and project management
• /
• 2011.02a
• /
• pp.201-208
• /
• 2011

Today's highly competitive construction scenario forces all the major players in the field to take up multiple projects which have put an undue pressure on the resources available within the organization. Under such a situation, there are many instances where in the resource requirement exceeds its availability due to multiple activities (with same resource requirement) which are scheduled to start simultaneously and thus results in the constrained resource becoming a bottleneck of the project. As a consequence of sharing resources, this paper studies the impact on the completion date of two similar projects under two different conditions, the first one resulting in a postponed end date and the second without any postponement. The resource utilization, the possibility of substitution of a resource and its subsequent impact on the deadline of the project is analyzed under these two circumstances. The study is done on a Critical Chain Project Management (CCPM) platform instead of leaving the schedule with a traditional Critical Path Method (CPM) finish, which gives an added advantage of validating the robustness of the emerging CCPM trend in the field of resource management.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.60 no.4
• /
• pp.93-103
• /
• 2018

The aim of this study is to apply the Water-Energy-Food-Land Nexus approach which can analyze the trade-offs among resources, and assess the holistic impacts of food security. First, we applied rice as a study crop and analyzed the trend of consumption of rice and the area of paddy fields. Second, the portfolios of water, energy, and land for rice production were constructed using data of footprints and productivity. Finally, the self-sufficiency ratio (SSR) of rice in target year was set as food security scenario and assessed the impacts of food security on water, energy, and land availability. In 2030, the SSR of rice decreased to 87 %, and water use for producing rice decreased from 4,728 to $3,350million\;m^3$, and the water availability index increased from 0.33 to 0.53. However, food security is essential issue and we set the 50 % and 100 % SSR of rice as high and low food security scenarios. For 100% SSR in 2030, about $3,508million\;m^3$ water was required and water availability index reached to 0.5. In other words, there is the trade-off between food security and water-energy-lands availability. Therefore, it is difficult to make a decision whether a high level of SSR is better or worse. However, this study showed the both positive and negative impacts by change of food security and it can be useful for setting the policy decision considering both food security and sustainable resource management at the same time.

• Journal of Korea Society of Industrial Information Systems
• /
• v.17 no.5
• /
• pp.29-36
• /
• 2012

Cloud computing has gained great popularity because users don't need to install any softwares as well as maintain hardwares and service providers also can utilize its resources through virtualization of servers. As workflows feature variableness and servers are heterogenous, efficient scheduling of workflows in cloud computing is important factor in view of responsibility and resource utilization. In this paper, we propose a new workflow scheduling named 2-step scheduling which prioritizes each workflow through its significance degree and allocates resources to workflows through decision table. The goal of this 2-step scheduling is to improve responsibility as well as availability versus cost. Simulation results show that the proposed scheme in contrast of counterparts can improve the responsibility as well as availability of resource.