• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.4
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• pp.40-48
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• 2023

This study is part of a foundational research effort aimed at developing a suitability index for breeding grounds related to avian activities along the domestic South and West coasts, including islands. Focus Group Interviews (FGI) and Analytic Hierarchy Process (AHP) analyses were conducted. The results are as follows. First, as a result of determining the value of the suitability of coastal bird breeding sites, the 'Natural Value(0.763)' was higher than the 'Artificial Value(0.237)'. Other artificial values were identified as sub-ranked except for 'Protected Areas' to ensure continuous integrity of breeding spaces. Second, as a result of re-establishing the 25 evaluation items classified in the two-time FGI as higher concepts, nine natural values and five artificial values were finally selected as a total of 14. Third, the results of the mid-classification evaluation of the importance of the suitability of coastal bird breeding sites were identified in the order of 'Ecological Value(0.392)', 'Topographic Value(0.251)', 'Passive Interference(0.124)', 'Geological Value(0.120)', and 'Active Interference(0.113)'. Fourth, the results of the priority of evaluation items of coastal bird breeding sites were in the order of 'Vegetation Distribution (0.187)', 'Area of Mudflats(0.118)', 'Presence or Absence of Mudflats(0.092)', 'Appearance of Natural Enemies(0.087)', 'Protected Areas(0.08)', 'Island Area (0.069)', 'Over-Breeding devastation(0.064)', 'Soil Composition Ratio(0.056)', 'Distance from Land(0.054)', 'Ocean farm area (0.045)', 'Cultivated land area(0.041)', 'Cultivation behavior(0.038)', 'Angle of the Surface(0.036)', and 'Land Use(0.033)'. It is judged that the weighting result value of the evaluation items derived in this study can be used for priority evaluation focusing on the coastal bird breeding area space. However, it seems that the correlation with the unique habitat suitability of bird individuals needs to be supplemented, and spatial analysis research incorporating species-specific characteristics will be left as a future task.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.241-253
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• 2023

In the current rapidly changing environment, each country continues to make efforts to create jobs and strengthen technological competitiveness. In particular, support and revitalization policies for venture companies and start-ups are known to play a role in increasing national competitiveness. Companies should make appropriate replacements amid growing uncertainties in the environment in which business life is shortened and customer needs are diversified due to intensifying competition. First of all, it is important for companies to make efforts to strengthen their internal capabilities on their own. However, venture companies lack internal resources and capabilities, so support from the external environment is important enough to lead to the survival of the company(Timmons, 1994). Financial support and certification systems are being operated at the national level to strengthen the competitiveness of companies. However, financial support can lower a company's self-sustainability depending on the situation, so non-financial support such as R&D support and start-up education is considered to be helpful in the long term for venture growth(Aghion et al., 2012; Jeon & Ko, 2021). Non-financial support is divided into commercialization, facilities, space, childcare, manpower, and certification systems, and this study confirmed the benefits of the venture company confirmation system, which is a certification system. To this end, the 2021 venture company precision survey data and venture company sales data were used, and analyzed using the SPSS 26.0 package and SPSS PROCESS MACRO. As a result of the analysis, it was confirmed that the level of the management environment of venture companies has a positive effect on the benefits of the venture confirmation system or increasing the level of venture company capabilities, but it is difficult to lead to actual management performance. In addition, it was confirmed that the level of venture company competency mediates the relationship between the level of the venture company's business environment and management performance. As a result, even if the level of the venture company's business environment is positive or venture-friendly, it can be said that companies with internal capabilities to digest support from the external environment increase management performance.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.63-76
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• 2024

Multi-family housing plays a crucial role as a living and experiencing space, and its environment has a direct impact on the well-being and stability of its residents. Therefore, Crime Prevention Design (CPTED) for multi-family housing is of utmost importance. However, crime-related data in China is not disclosed to the public because of its specificity, making it difficult for researchers to conduct further in-depth studies based on accurate crime data. As a result, the establishment and application of CPTED theory in terms of crime prevention is limited and delayed. This study aims to explore three aspects of CPTED in multi-family housing as perceived by home-buying consumers. It investigated consumer perception of the CPTED, the importance of each element and ways to increase awareness of CPTED in multifamily housing in order to effectively improve multifamily crime prevention design principles and further enhance public safety. This study examined the current state and future trends of CPTED in China by analyzing relevant research reports and literature, aiming to gain insights into the crime prevention awareness of Chinese homeowners. In addition, a survey was conducted on Chinese consumers to unravel the importance of CPTED and increase awareness of its various elements in multifamily-family. This study used a Likert scale and SPSS reliability analysis to determine the cognitive status of multi-family CPTED, the importance of each element, and proposed an improvement plan based on the analysis results. As this study was limited by the difficulty of implementation and the lack of validation of its practical effectiveness, it is recommended that future research needs to validate the effectiveness of crime prevention designs and produce more practical results. Furthermore, it is crucial to utilize this study to inform the implementation of security solutions that are tailored to the unique characteristics of each district. Additionally, it is important to offer guidance on how to enhance community safety by increasing residents' awareness of security through education and information dissemination. The author hopes that the representative multi-family CPTED awareness, the importance of each element, and plans for improvement shall be summarized from this study, and provide foundational data for the future development of CPTED based on the Chinese region.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Korean Journal of Heritage: History & Science
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• v.45 no.3
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• pp.60-79
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• 2012

Environment of ancient Chinese Buddhist temple can be classified to three types such as regional society(鄕村), famous mountain(名山), and urban areas(都市). This made differences in environment where a temple existed and in turn, affected development of Buddhism. And this made another type in relationship between Buddhist temple and a society. This study explains influences which regional society gave on not only Buddhist temple and a monk but also existence and development of Buddhism. When temples are placed in different environmental position, that is, urban areas and regional society, among a social structure, they eventually should adapt to a different society externally and internally. As told in above, ancient Chinese Buddhist temple was located in regional society, famous mountain, and urban areas. Since Eastern Jin and Sixteen Kingdoms, as number of temple much increased, and temples and monks were concentrated on famous mountain, temples in famous mountains and urban areas had developed showing similar aspects each other. But because temples in regional society were influenced a little differently, this study focused on the point. There are four kinds of influences between temples and monks in regional areas. Monks in regional areas had a comparatively close relationship with a society because they came from same area or surrounding areas. Therefore,powers of regional areas restrict influences made by monk group in temple. Second, temples in regional areas shared their joys and sorrows depending on regional economy. Temples in regional areas became a public place for the society and often a market place. In fact, construction and existence of a temple originally became a driving force in regional economy. This is because construction of temple needs artisans and materials and some temples had visitors and included market economy like consumption of incense and candles, though the economic size was large or small. And when regional areas experienced natural disaster or man-made disaster or had poor harvest or economy was in depression, monks left temples and then, temples themselves could not exist. Third, the relationship between temples in regional areas and Buddhists was distinguished from the temples in urban areas and famous mountains. This is because temples in China were places where monks practiced and at the same time, places where general Buddhists worshipped. So there were always a number of Buddhists around the temples. Forth, Buddhism in resional areas was connected to regional Folk beliefs. As a result, Buddhism was spread across the nation, worship with local color often was changed to Buddhist belief or was tinged with Buddhism. While temples in regional areas maintained a close relationship with regional society.they were influenced by the region or gave influences. As a representative example, temples in regional areas showed model behaviors instead of roles of facilities related to various cultures with comparatively advanced level - for example, school, hospital etc. The temples highly affected funerary rites in regional areas. Chinese tombs were mainlymade in regional areas. After death,people living in urban areas were buried in hometown or at least, they were buried in suburbs not urban areas. Temples in regional areas generally participated in funerary rites. Above shows that though most of famous Buddhist temples were located in urban areas not in famous mountains,majority of temples were located in vast regional areas. Through mutual interaction between temples and regional society, the temples in the regional areas were related to Chinese people of over 90% and regional areas became the most important foundation for Buddhism in China. Mutual influences between temples in regional areas and the general public in regions were omnidirectional and spreaded to every aspects of social life in small or large degree. Thus Tombs in temple were widely spreaded across regional areas over time and space. This is enough to explain a close relationship between Buddhist temples and rural society in ancient China.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.40 no.3
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• pp.20-35
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• 2022

This study was conducted on the locational results of the 'Yusanggoksu(流觴曲水)' petroglyphs located in Hwanggak-dong(黃閣洞), Shinsong-ri, Geumma-myeon, Iksan-si through literature study, analysis of old maps and aerial photos, field observations, drone photography, elevation surveys, and interviews with residents. It was attempted for the purpose of illuminating and preserving the relics of the domestic Yusanggoksu garden by clarifying the spatiality of this place by tracing the spatiality and examining the possibility of enjoying the Yusanggoksu water system in this place. The conclusion of this study is as follows. The area around Hwanggak-dong, where the Yusanggoksu remains, has been selected as the most beautiful scenic spot in Iksan in various documents. The origin of 'Hwanggak' is considered to be closely related to the nickname of Uijeongbu(議政府). In other words, he paid attention to the relationship with Yanggok, So Se-yang(蘇世讓), who served as Chan-seong Jwa(左贊成). In particular, he paid attention to the relationship with his birthplace, Taeheojeong, a separate book, and Toehyudang, a retreat hall), tombs, and posthumous Confucian academies were distributed in the vicinity. Haseo-dae(荷鋤臺), a wide rock on which a hoe is hung on a rock after field work, seems to express a leisurely rural life and a simple and hermit life, based on the examples of Chinese and Korean poetry. The dark blood on the upper part of the Seobwi Rock with the inscription 'Yusanggoksu', which is the core of this site, is identified as a chailgong(遮日孔) to support the water system, and Ilgan-pavilion and Mojeong(茅亭) nearby are to support the yusanggoksu. It seems to have performed a spatial function for The inscription 'Hwanggak-dong' engraved on the front of Deungzanbawi is the gateway to Hwanggakdongcheon(黃閣洞天) and identified the idealized world existing in the village. Judging from the documentary records of the Iksan-gun 『Chongswaelog(叢瑣錄)』, the rock letters 'Hwanggak-dong' and 'Haseodae' were engraved on March 29, 1901, the 5th year of Gwangmu, the 5th year of the Korean Empire, by Iksan-gun Governor Oh Haeng-mook(吳宖默) and his acquaintance Seokseong Kim In-gil(金寅吉) Confirmed. Also, considering the tense of Lee Bong-gu's 「Hwanggakdongun(黃閣洞韻)」 and So Jin-deok, a descendant of Yanggok, 「Hwanggakdongsihoe(黃閣洞詩會)」, it is presumed that it was related to Goksuyeon(曲水宴) in Hwanggak-dong. It can be inferred that the current affairs meetings were held at least until the early days of Japanese colonial rule. Meanwhile, the maximum width of the current curved waterway was calculated as 11.3m and the transverse slope was 15.0%. If so, it is estimated that the width and extension distance of the curved waterway would have been much longer. Judging from the use of mochun(暮春), drinking and poetry, the tense 'Hwanggakdongsihoe' related to the Yusanggoksu relics in Hwanggak-dong, and the existence of a pavilion presumed to be Yusangjeong(流觴亭) called Ilgan-pavilion in the nearby Yusanggoksu site It is confirmed that it was a space where Yusanggoksuyeon(流觴曲水宴) spread at least until the end of the Joseon Dynasty. Unfortunately, it remains a limitation of the study that it cannot be confirmed due to lack of data on the rock characters of 'Yusanggoksu' and those who enjoyed it before the end of the Joseon Dynasty. This is an area that needs to be elucidated through continuous efforts to find data on this issue in the future.

• Journal of Distribution Science
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• v.10 no.3
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• pp.51-61
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• 2012

This study seeks to understand how the choice of a coffee shop is related to a customer's loyalty and which characteristics of a shop influence this choice. It considers large-sized coffee shops brands whose market scale has gradually grown. The users' choice of shop is determined by price, employee service, shop location, and shop atmosphere. The study investigated the effects of these four properties on the brand attitudes of coffee shops. The effects were found to vary depending on users' characteristics. The properties with the largest influence were shop atmosphere and shop location Therefore, the purpose of the study was to examine the properties that could help coffee shops get loyal customers, and the choice properties that could satisfy consumers' desires The study examined consumers' perceptions of shop properties at selection of coffee shop and the difference between perceptual difference and coffee brand in order to investigate customers' desires and needs and to suggest ways that could supply products and service. The research methodology consisted of two parts: normative and empirical research, which includes empirical analysis and statistical analysis. In this study, a statistical analysis of the empirical research was carried out. The study theoretically confirmed the shop choice properties by reviewing previous studies and performed an empirical analysis including cross tabulation based on secondary material. The findings were as follows: First, coffee shop choice properties varied by gender. Price advantage influenced the choice of both men and women; men preferred nearer coffee shops where they could buy coffee easily and more conveniently than women did. The atmosphere of the coffee shop had the greatest influence on both men and women, and shop atmosphere was thought to be the most important for age analysis. In the past, customers selected coffee shops solely to drink coffee. Now, they select the coffee shop according to its interior, menu variety, and atmosphere owing to improved quality and service of coffee shop brands. Second, the prices of the brands did not vary much because the coffee shops were similarly priced. The service was thought to be more important and to elevate service quality so that price and employee service and other properties did not have a great influence on shop choice. However, those working in the farming, forestry, fishery, and livestock industries were more concerned with the price than the shop atmosphere. College and graduate school students were also affected by inexpensive price. Third, shop choice properties varied depending on income. The shop location and shop atmosphere had a greater influence on shop choice. The customers in an income bracket of less than 2 million won selected low-price coffee shops more than those earning 6 million won or more. Therefore, price advantage had no relation with difference in income. The higher income group was not affected by employee service. Fourth, shop choice properties varied depending on place. For instance, customers at Ulsan were the most affected by the price, and the ones at Busan were the least affected. The shop location had the greatest influence among all of the properties. Among the places surveyed, Gwangju had the least influence. The alternate use of space in a coffee shop was thought to be important in all the cities under consideration. The customers at Ulsan were not affected by employee service, and they selected coffee shops according to quality and preference of shop atmosphere. Lastly, the price factor was found to be a little higher than other factors when customers frequently selected brands according to shop properties. Customers at Gwangju reacted to discounts more than those in other cities did, and the former gave less priority to the quality and taste of coffee. Brand preference varied depending on coffee shop location. Customers at Busan selected brands according to the coffee shop location, and those at Ulsan were not influenced by employee kindness and specialty. The implications of this study are that franchise coffee shop businesses should focus on customers rather than aggressive marketing strategies that increase the number of coffee shops. Thus, they should create an environment with a good atmosphere and set up coffee shops in places that customers have good access to. This study has some limitations. First, the respondents were concentrated in metropolitan areas. Secondary data showed that the number of respondents at Seoul was much more than that at Gyeonggi-do. Furthermore, the number of respondents at Gyeonggi-do was much more than those at the six major cities in the nation. Thus, the regional sample was not representative enough of the population. Second, respondents' ratio was used as a measurement scale to test the perception of shop choice properties and brand preference. The difficulties arose when examining the relation between these properties and brand preference, as well as when understanding the difference between groups. Therefore, future research should seek to address some of the shortcomings of this study: If the coffee shops are being expanded to local areas, then a questionnaire survey of consumers at small cities in local areas shall be conducted to collect primary material. In particular, variables of the questionnaire survey shall be measured using Likert scales in order to include perception on shop choice properties, brand preference, and repurchase. Therefore, correlation analysis, multi-regression, and ANOVA shall be used for empirical analysis and to investigate consumers' attitudes and behavior in detail.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.