• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1214-1221
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• 2007

Ad-hoc network is soft wireless communication network that is consisted of mobile node and clusters without helping of infrastructure. We propose a new ad hoc multicast routing protocol for based on the ontology scheme called inference network. Ontology knowledge-based is one of the structure of context-aware. Proposed structure is consisted of context awareness parameters as like distance between each nodes. The proposed architecture performs two types of routing discovery. One is Flooding Discovery Routing(FDR) for comparing analysis step and Local Discovery Routing(LDR) to compose path of node forecast(preservation) step from node's state value. The inference network structure of proposed RODMRP(Resilient Ontology-based Dynamic Multicast Routing Protocol) adopts a tree structure to enhance an efficient packet in various environment between mobile node. We will have developed an algorithm that will desist multi-hierarchy Layered networks to simulate a desired system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.942-947
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• 2008

A cluster server usually consists of a front end node and multiple backend nodes. Though increasing the number of bookend nodes can result in the more QoS(Quality of Service) streams for clients, the possibility of failures in backend nodes is proportionally increased. The failure causes not only the stop of all streaming service but also the loss of the current playing positions. In this paper, when a backend node becomes a failed state, the recovery mechanisms are studied to support the unceasing streaming service. The basic techniques are hewn as providing very high speed data transfer rates suitable for the video streaming. However, without considering the architecture of cluster-based VOD server, the application of these basic techniques causes the performance bottleneck of the internal network for recovery and also results in the inefficiency CPU usage of backend nodes. To resolve these problems, we propose a new failure recovery mechanism based on the pipeline computing concept.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.4
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• pp.3-14
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• 2019

The purpose of this study is to analyze the distribution characteristics of the agency-managed shared housings in Seoul and draw the possible implications from it. The needed data for the study was obtained from an on-line shared housing portal service which provides housing information from various shared housing management agencies. By mapping out the locations and other related data into a GIS(Geographic Information System) program, this study shows that shared housings in Seoul can be sorted into four large clusters. Each cluster has a different ratio of housing types and room capacities reflecting each regional circumstance and common causes. Women-only shared housing takes up 79% of the overall shared housing ratio and, while multi-family housing type has the most count, the apartment type has a noticeably high ratio in women-only housing compared to the apartment type ratio among the other gender-specific housings. Given the high crime rate against the single-person household of young adult women, the reason for the popularity of shared-apartment housing among young women can be deduced. However, the potential tenants' practical choices and their concern for safety are not the only causes that drive the current shared housing market. The young adults in their 20's and 30's choose to live in popular places where they can engage social activities. A new tier of shared housing market has also appeared in places where young adults could not have afforded if they lived alone. Choosing where we live is no longer about just meeting the requirements for a house based on what she/he needs but also about satisfying the preferences for a living based on what she/he desires. This paper indicates that although there is an undeniable premise that 'sharing a house' revolves around the realm of housing welfare and is not a typical topic for the upper-income households, the way we live and how we choose our place to live is shifting.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1105-1114
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• 2021

Due to the recent surge in popularity of cryptocurrency, the threat of cryptojacking, a malicious code for mining cryptocurrencies, is increasing. In particular, web-based cryptojacking is easy to attack because the victim can mine cryptocurrencies using the victim's PC resources just by accessing the website and simply adding mining scripts. The cryptojacking attack causes poor performance and malfunction. It can also cause hardware failure due to overheating and aging caused by mining. Cryptojacking is difficult for victims to recognize the damage, so research is needed to efficiently detect and block cryptojacking. In this work, we take representative distinct symptoms of cryptojacking as an indicator and propose a new architecture. We utilized the K-Nearst Neighbors(KNN) model, which trained computer performance indicators as behavior-based dynamic analysis techniques. In addition, a K-means model, which trained the frequency of malicious script words for script similarity-based static analysis techniques, was utilized. The KNN model had 99.6% accuracy, and the K-means model had a silhouette coefficient of 0.61 for normal clusters.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.81-89
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• 2022

This study aims to analyze the images of Instagram posts and to draw implcations regarding the exhibition of . This study collects and crawl 24,295 images from Instagram posts as a dataset. We use the Google Cloud Vision API for labeling the images and a total of 212,567 clusters of labels are finally classified into 9 categories using Word2Vec. The categories of museum spaces, photo zone, architecture category are dominant along with people category. In conclusion, visitors curate their experiences and memories of physical places and spaces while they are experiencing with the exhibition. This result reproves the results of previous studies which emphasize a sense of social presence and place making. The convergent approach of art management and art technology used in this study help museum professionals have an insight on big data based visitor research on a practical level.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.603-616
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• 2023

In this study, machine learning-based clustering and classification of residential noise in apartment buildings was conducted using frequency and temporal characteristics. First, a residential noise source dataset was constructed . The residential noise source dataset was consisted of floor impact, airborne, plumbing and equipment noise, environmental, and construction noise. The clustering of residential noise was performed by K-Means clustering method. For frequency characteristics, L_eq and L_max values were derived for 1/1 and 1/3 octave band for each sound source. For temporal characteristics, Leq values were derived at every 6 ms through sound pressure level analysis for 5 s. The number of k in K-Means clustering method was determined through the silhouette coefficient and elbow method. The clustering of residential noise source by frequency characteristic resulted in three clusters for both L_eq and L_max analysis. Temporal characteristic clustered residential noise source into 9 clusters for L_eq and 11 clusters for L_max. Clustering by frequency characteristic clustered according to the proportion of low frequency band. Then, to utilize the clustering results, the residential noise source was classified using three kinds of machine learning. The results of the residential noise classification showed the highest accuracy and f1-score for data labeled with L_eq values in 1/3 octave bands, and the highest accuracy and f1-score for classifying residential noise sources with an Artificial Neural Network (ANN) model using both frequency and temporal features, with 93 % accuracy and 92 % f1-score.

• Korean Journal of Environment and Ecology
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• v.30 no.3
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• pp.344-352
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• 2016

The goal of this study was to identify the water temperature and sound environment of oviposition sites of the Huanren brown frog (Rana huanrensis), which breeds in valleys in early spring. The study was conducted in Chiak National Park, central Korea, between March 23 and April 24, 2015. Correlation analysis of the physical factors of oviposition sites revealed that the number of egg clutches was positively correlated (p < 0.05) with the water temperature and negatively correlated (p < 0.05) with the sound volume of the oviposition sites. However, no correlation was found between clutch number and the total area or depth of water. The water temperature of the oviposition sites was $2.2^{\circ}C$ higher on average than that of the mainstream (p < 0.001). To avoid the low early spring temperatures, R. huanrensis spawned in sites with accumulated water, in which the depths were less than 10cm and the temperature was relatively high. Further, eggs were spawned in clusters in small spaces to maximize the thermal insulation effect. In terms of noise levels, oviposition sites were found to be 6.9 dB quieter than the mainstream (p<0.001). In conclusion, R. huanrensis was found to spawn in warm, quiet, and small oviposition sites in valleys to avoid low early spring temperatures and loud water noise. This study is significant because it is the first to characterize the sound environment of amphibian oviposition sites.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.1
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• pp.57-68
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• 2012

This research was conducted to understand the extent to which visitors to the DMZ Pyeonghwa Nuri-gil Trail(located in one of the most Ecologically Sensitive Areas(ESA) of Korea) are motivated by perceived constraints and loyalty to the trail. Self-administered questionnaires were distributed to the participants of the '2010 DMZ Border Trekking Course', which resulted in collecting 317 valid responses. For statistical tests, the respondents were divided into three clusters(accidental, activity-driven, and nature-driven) by their motivation for the visit. ANOVA was conducted to examine if the three groups differ in terms of the perceived constraints and loyalty to the DMZ Pyeonghwa Nuri-gil Trail. The results showed that nature-driven visitors were more likely to perceive "psychological constraints" than accidental or activity-driven visitors. As for loyalty, accidental visitors displayed the lowest level of loyalty while nature-driven visitors indicated the highest level of loyalty. These results illustrate that nature-driven visitors not only have the strongest desire to experience and learn about ESAs but also possess the highest sense of loyalty to the trail. It can further be argued that nature-driven visitors are the ones with the greatest concern for the trail's well-being. The paper concludes with the contention that understanding the demand and characteristics of trail visitors is critical to the future development of the trail.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.465-472
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• 2017

In the past, researchers mainly used the supervised learning technique of machine learning to analyze power data and investigated the identification of patterns through the data mining technique. Data analysis research, however, faces its limitations with the old data classification and analysis techniques today when the size of electric power data has increased with the possible real-time provision of data. This study thus set out to propose a clustering architecture to analyze large-sized electric power data. The clustering process proposed in the study supplements the K-means algorithm, an unsupervised learning technique, for its problems and is capable of automating the entire process from the collection of electric power data to their analysis. In the present study, power data were categorized and analyzed in total three levels, which include the row data level, clustering level, and user interface level. In addition, the investigator identified K, the ideal number of clusters, based on principal component analysis and normal distribution and proposed an altered K-means algorithm to reduce data that would be categorized as ideal points in order to increase the efficiency of clustering.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.158-170
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• 2013

With the recent 'Creative economy' and 'Cultural prosperity' coming to the fore as a new code to build up a city or a region, it is necessary to focus on strengthening the regional creative capacity as well as developing spontaneous regional culture. In such trend this research aims to explore the Kyunglidan-gil, Seoul, Korea in which creative-class are appearing autogenously in clusters and forming new cultural landscape, to identify the factors of their accumulation and changing aspect of cultural landscape. This study has the following purposes: First, Investigating the historical context of the Kyunglidan-gil's landscape. Second, considering the process of the creative-class being flowed into the Kyunglidan-gil as the subject leading to the modification of the region. Third, their activity was analyzed to consider the unique aspect of forming the cultural landscape at the Kyunglidan-gil. Regarding why the creative-class should flow in, results of the study drew five factors including region in issue compared to inexpensive rents, coexistence with nature, quiet atmosphere seeming isolated from the urban confusion, location possible to test and share individual materials one likes, and a site with synergy effect of activity through the network with acquaintances. Also, five characteristics of cultural landscape forming by the people's activity were drawn - space of communication for increasing creativity, temporary and flexible spatial use, expression of one's identity and taste, distinguishing, and positive use of the existing facilities. Like this, by exposing the 'creative-class', a subject of the leader in changing process of the Kyunglidan-gil, this research identified the aspect of forming cultural landscape.