• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.23-33
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• 2016

The current smart lighting is shaped to offer the lighting environment suitable for current context, after identifying user's action and location through a sensor. The sensor-based context awareness technology just considers a single user, and the studies to interpret many users' various context occurrences and conflicts lack. In existing studies, a fuzzy theory and algorithm including ReBa have been used as the methodology to solve context conflict. The fuzzy theory and algorithm including ReBa just avoid an opportunity of context conflict that may occur by providing services by each area, after the spaces where users are located are classified into many areas. Therefore, they actually cannot be regarded as customized service type that can offer personal preference-based context conflict. This paper proposes a priority-based LED lighting control system interpreting multiple context conflicts, which decides services, based on the granted priority according to context type, when service conflict is faced with, due to simultaneous occurrence of various contexts to many users. This study classifies the residential environment into such five areas as living room, 'bed room, study room, kitchen and bath room, and the contexts that may occur within each area are defined as 20 contexts such as exercising, doing makeup, reading, dining and entering, targeting several users. The proposed system defines various contexts of users using an ontology-based model and gives service of user oriented lighting environment through rule based on standard and context reasoning engine. To solve the issue of various context conflicts among users in the same space and at the same time point, the context in which user concentration is required is set in the highest priority. Also, visual comfort is offered as the best alternative priority in the case of the same priority. In this manner, they are utilized as the criteria for service selection upon conflict occurrence.

• Korean Journal of Heritage: History & Science
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• v.52 no.4
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• pp.56-77
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• 2019

Bi-Seok is a treasure trove of funeral rites and an important cultural asset that can shed light on the historical and social history of calligraphy, but research of the topic is still insignificant. In particular, research on the production method of Bi-Seok remains an unproven field. The production of Bi-Seok can be roughly divided into ma-jeong (refining stone), sculpture, and the Buk-chil (process of engraving letters) process. This article reveals some facts: First, performing ma-jeong to the Sang-Seok, Honyu-Seok, Bi-seok, which are known to be God's things. This process is needed because of the change in the perception of the Honyu-Seok due to the settlement and propagation of Confucian ceremonial rituals in the times of hardship in 1592 and 1636. As the crafting process of ma-jeong did not remain concrete, it was only possible to examine the manufacturing process of Bi-Seok through its materials and tools. Second, the rapid proliferation of Oh-Seok and Sa-jeo-chwi-yong (purchase of things made by private citizens) in the Yeongjo era has great importance in social and cultural history. When the Gang-Hwa-Seok of the commodity were exhausted, the Oh-Seok that was used by Sadebu (upper civil class) were used in the tomb of Jangneung, which made Oh-Seok popular among people. In particular, the use of Oh-Seok and the Ma-Jeong process could minimize chemical and physical damage. Third, the writing method of the Bi-seok is Buk-chil. After Buk-Chil of Song Si-Yeol was used on King Hyojong's tomb, the Buk-Chil process ( printing the letters on the back of the stone and rubbing them to make letters) became the most popular method in Korea and among other East Asian countries, and the fact that it was institutionalized to this scale was quite impressive. Buk-Chil became more sophisticated by using red ink rather than black ink due to the black color that results from Oh-Seok. Fourth, the writing method changes in the late Joseon Dynasty. Until the time of Yeongjo's regime, when inscribing, the depth of the angle was based on the thickness of the stroke, thus representing the shade. This technique, of course, did not occur at every Pyo-Seok or Shindobi, but was maintained by outstanding artisans belonging to government agencies. Therefore, in order to manufacture Bi-Seok, Suk-seok, YeonJeong, Ma-jeong, Jeong-Gan, ChodoSeoIp, Jung-Cho, Ip-gak, Gyo-Jeong, and Jang-Hwang, a process was needed to make one final product. Although all of these methods serve the same purpose of paying respects and propagandizing the great work of deceased persons, through this analysis, it was possible to see the whole process of Pyo-Seok based upon the division of techniques and the collaboration of the craftsmen.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• MISULJARYO - National Museum of Korea Art Journal
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• v.98
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• pp.154-175
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• 2020

Most Korean Buddhist paintings from the late Joseon period were produced through collaborative projects (bulsa) between clans of Buddhist monks and monk artists (hwaseung), in which the monk clans would select themes and iconography for works that would then be produced by the artists and their school. Thus, any attempt to understand the Buddhist paintings of this period must consider not only the stylistic characteristics of the monk artists, but also the conditions at the respective temple at the time of production. Applying this methodology, this paper examines the collaboration between the Buhyu monk clan and the monk artist Uigyeom and his fellow artists (hereinafter, the "Uigyeom School") that took place in Honam (湖南) and surrounding areas in the eighteenth century. In particular, the paper reveals the strong influence that the Buhyu clan exerted on paintings that the Uigyeom School produced in 1724 and 1725 at Songgwangsa Temple, the clan's main temple. Following the paintings for Songgwangsa Temple, the Uigyeom School actively participated in similar projects at regional temples under the auspices of the Buhyu clan in Honam, Hoseo (湖西), and Yeongnam (嶺南). Consequently, the Buhyu clan granted Uigyeom several honorable titles-including "Hoseon" (毫仙), "Jonsuk" (尊宿), and "Daejeonggyeong" (大正經)-that were rarely conferred to a monk artist. Such acclaim helped Uigyeom's style of Buddhist painting to become widespread throughout the three southern provinces of Korea. The paintings for Songgwangsa Temple exemplify how the Buhyu clan and Uigyeom School collaborated to visualize the thoughts and philosophies of the Buhyu clan. For the Uigyeom School, this project served as the foundation for building the reputation and esteem of Uigyeom, who became one of the most esteemed and influential monk artists of the late Joseon period. As such, the paintings created for Songgwangsa Temple in 1724 and 1725 have great significance not only for Korean Buddhism, but also for art history in general.