• KIPS Transactions on Computer and Communication Systems
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• v.10 no.12
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• pp.311-318
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• 2021

With the rapid development of the Internet of Things(IoT) technology recently, multi-access edge computing(MEC) is emerged as a next-generation technology for real-time and high-performance services. High mobility of users between MECs with limited service areas is considered one of the issues in the MEC environment. In this paper, we consider a vehicle edge computing(VEC) environment which has a high mobility, and propose a task migration algorithm to decide whether or not to migrate and where to migrate using DQN, as a reinforcement learning method. The objective of the proposed algorithm is to improve the system throughput while satisfying QoS(Quality of Service) requirements by minimizing the difference between queueing delays in vehicle edge computing servers(VECSs). The results show that compared to other algorithms, the proposed algorithm achieves approximately 14-49% better QoS satisfaction and approximately 14-38% lower service blocking rate.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.71-79
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• 2021

In the manufacturing industry, there is a transition to multi-item production for reinforcement of competitiveness. Therefore, the hybrid manufacturing technology is increasing. Especially, many efforts in production quality improvement are made through the adoption of the manufacturing execution system and ERP, so it is necessary to operate MES for prompt and effective management. MES should improve ineffective parts in production activities while managing all stages related to production of products. If there is change in the process, the changed items should be reflected to the system. However, most manufacturing execution systems are operated passively and repetitively by system administrators. This study presents a model that system administrators can comprehensively apply reference information about production related requirements on specific line's equipment to the same equipment of other lines. The flexible response for application to production lines is possible thanks to the division of blanket application and selective application of reference information through proposed model.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.305-312
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• 2021

Background: Butterflies make an important part for plant-pollinator guild. These are nectar feeder or occasionally pollen feeder and thus proboscis of the butterfly species are considered as one of the most important variable in relation to the collection of food from plants. In butterfly-plant association, nectar source is principally determined by quality of nectar, corolla length, and nectar quantity. For the butterfly, nectar uptake is determined by proboscis length because flowers with long corolla restrict butterfly species containing shorter proboscis. Empirical studies proved that butterfly species with high wing loading visit clustered flowers and species with low wing loading confined their visit to solitary or less nectar rich flowers. The present study tries to investigate the flower preference of butterfly species from Lycaenidae family having very short proboscis, lower body length, lower body weight and wing span than the most species belonging from Nymphalidae, Pieridae, Papilionidae, and Hesperiidae. Results: Butterflies with shorter proboscis cannot access nectar from deeper flower. Although they mainly visit on less deeper flower to sucking nectar, butterflies with high wing loading visits clustered flowers to fulfill their energy requirements. In this study, we demonstrated flower choice of seven butterfly species belonging to Lycanidiae family. The proboscis length maintains a positive relationship with body length and body weight. Body length maintains a positive relationship with body weight and wing span. Wing span indicate a strong positive relationship with body weight. This study proved that these seven butterfly species namely Castalius rosimon (CRN), Taracus nara (TNA), Zizinia otis (ZOT), Zizula hylax (ZHY), Jamides celeno (JCE), Chilades laius (CLA), and Psuedozizeeria maha (PMA) visit frequently in Tridax procumbens (TPR), Ocimum americanum (OAM) and Syndrella nodiflora (SNO). The species do not visit Lantana camara (LCA) and Catharanthus roseus (CRO) plants. Conclusion: The present study proved that butterfly species visits frequently in Tridax procumbens (TPR), Ocimum americanum (OAM) but less frequently in Syndrella nodiflora (SNO). So, that study determined the butterfly species helps in pollination of these herbs that in turn helps the conservation of these butterfly species.

• Journal of Software Engineering Society
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• v.24 no.3
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• pp.77-89
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• 2011

Software product line engineering is a software reuse paradigm that helps organizations improve software productivity and quality by developing software products from reusable core assets. For the satisfaction of common and variable requirements among products in the product line, the core assets must be configurable according to the selection of variable features. Therefore, unlike software architecture model of a single product, product line architecture model must embed and express variabilities among the products. Many researches have proposed methods of embedding and expressing variabilities in the product line architecture models, but there are few comparative studies on the proposed methods. In this paper we discuss strong points and weak points of the proposed methods and compare expressiveness of the methods, which helps select a proper method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3199-3218
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• 2019

Location-based services (LBSs) have become popular in recent years due to the ever-increasing usage of smart mobile devices and mobile applications through networks. Although LBS application provides great benefits to mobile users, it also raises a sever privacy concern of users due to the untrusted service providers. In the lack of privacy enhancing mechanisms, most applications of the LBS may discourage the user's acceptance of location services in general, and endanger the user's privacy in particular. Therefore, it is a great interest to discuss on the recent privacy-preserving mechanisms in LBSs. Many existing location-privacy protection-mechanisms (LPPMs) make great efforts to increase the attacker's uncertainty on the user's actual whereabouts by generating a multiple of fake-locations together with user's actual positions. In this survey, we present a study and analysis of existing LPPMs and the state-of-art privacy measures in service quality aware LBS applications. We first study the general architecture of privacy qualification system for LBSs by surveying the existing framework and outlining its main feature components. We then give an overview of the basic privacy requirements to be considered in the design and evaluation of LPPMs. Furthermore, we discuss the classification and countermeasure solutions of existing LPPMs for mitigating the current LBS privacy protection challenges. These classifications include anonymization, obfuscation, and an encryption-based technique, as well as the combination of them is called a hybrid mechanism. Finally, we discuss several open issues and research challenges based on the latest progresses for on-going LBS and location privacy research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3917-3941
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• 2019

The recent interest in artificial intelligence and machine learning has partly contributed to an interest in the use of such approaches for hyperspectral remote sensing (HRS) imagery classification, as evidenced by the increasing number of deep framework with deep convolutional neural networks (CNN) structures proposed in the literature. In these approaches, the assumption of obtaining high quality deep features by using CNN is not always easy and efficient because of the complex data distribution and the limited sample size. In this paper, conventional handcrafted learning-based multi features based on expert knowledge are introduced as the input of a special designed CNN to improve the pixel description and classification performance of HRS imagery. The introduction of these handcrafted features can reduce the complexity of the original HRS data and reduce the sample requirements by eliminating redundant information and improving the starting point of deep feature training. It also provides some concise and effective features that are not readily available from direct training with CNN. Evaluations using three public HRS datasets demonstrate the utility of our proposed method in HRS classification.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.99-111
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• 2019

With the low birth rate and the inner city decline, the number of small schools is expected to increase. In this trend, the Ministry of Education has consistently used the number of students as a standard for the merger and abolition of schools since 1982, but it seems that has generated a vicious circle of education in rural areas and also it did not reflect realistic requirements and changes in the times although it is efficiency of local education finances. With the number of students constantly decreasing, it has a high probability to make villages without schools in urban areas if decisions are made by the number of students. In this sense, it is suggested that regional contexts and socioeconomic environment should be taken into account rather than to conduct the merger and abolition of small schools with economic logic. It is necessary to change the direction of improving the quality of education through the operation of small schools for coexistence of schools and villages and a cultivating the manpower needed in the 21st century knowledge information society and the 4th industrial revolution era. Therefore, we tried to find tasks for expanding small schools of the local community and developing small schools suitable for future social change.

• Journal of The Korean Society of Integrative Medicine
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• v.6 no.4
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• pp.149-169
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• 2018

Purpose : This study was to develop a strategy for modeling future workforce projections to serve as a basis for analyzing annual supply of and demand for physical therapists across the South Korea into 2030. Methods : In-and-out movement model was used to project the supply of physical therapists. The demand was projected according to the demand-based method which consists of four-stages such as estimation of the utilization rate of the base year, forecasting of health care utilization of the target years, forecasting of the requirements of clinical physical therapists and non-clinical physical therapists based on the projected physical therapists. Results : Based on the current productivity standards, there will be oversupply of 39,007 to 40,875 physical therapists under the demand scenario of average rate in 2030, undersupply of 44,663 to 49,885 under the demand scenario of logistic model, oversupply of 16,378 to 19,100 under the demand scenario of logarithm, and oversupply of 18,185 to 20,839 under the demand scenario of auto-regressive moving average (ARIMA) model in 2030. Conclusion : The result of this projection suggests that the direction and degree of supply of and demand for physical therapists varied depending on physical therapists productivity and utilization growth scenarios. However, the need for introduction of a professional physical therapist system and the need to provide long-term care rehabilitation services are actively being discussed in entering the aging society. If community rehabilitation programs for rehabilitation of disabled people and the elderly are activated, the demand of physical therapists will increase, especially for elderly people. Therefore, healthcare policy should focus on establishing rehabilitation service infrastructure suitable for an aging society, providing high-quality physical therapy services, and effective utilization of physical therapists.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.813-823
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• 2018

UHD content is characterized by higher bandwidth requirements to provide seamless playback. The existing HTTP adaptive streaming scheme periodically requests video segment of lower quality than the available bandwidth in the steady state. In the steady state, the On-Off pattern is repeated due to the difference of the available bandwidth and the encoding rate of the content. And the repeated Off interval is causing the problem that can not efficiently use the available bandwidth. In the wireless environment where the delay and loss rate are higher with large bandwidth fluctuations, this problem is exacerbated because the available bandwidth is estimated inaccurately. Therefore, in this paper, we propose a segment scheduling scheme for efficient bandwidth utilization of UHD contents streaming in wireless environment. Proposed scheme is a group segment that simultaneously reqeusts multiple segments in one request message in order to reduce frequency of OFF interval. Through simulation, Our scheme improves bandwidth utilization.

• Journal of Industrial Convergence
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• v.17 no.2
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• pp.15-20
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• 2019

The purpose of this study is to provide customized experience learning service platform that enables consumers to easily search for various content information about on - site experiential learning, exhibitions, events, and culture, and to provide services. To provide customized experiential learning information that meets the requirements of the consumer. Beacon technology implemented through this study is a BLE technology that broadcasts a URL in Eddystone format developed by Google. This means that even if a user does not install a separate application, Making it easier and faster to access. Based on this, when the database of local cultural contents is completed, it will be expanded to the whole country, and it is expected that more diverse and high quality self - directed cultural contents experiential learning activity education programs will be provided to consumers by diversifying contents and expanding the market.