• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.1
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• pp.68-75
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• 2019

This study aims to look at the application methods of landscape architecture in response to the 4th Industrial Revolution. The results of the analysis of trends in the 4th Industrial Revolution and the subsequent search for application methods to the field of landscape architecture are as follows. First, the 4th Industrial Revolution means innovative change based on digital technology and seeks to create value based on intelligent information technology, and continuous growth is being made through innovation. This requires expertise to collect large amounts of information and creatively rework it, and a strategy to flexibly cope with changes in the times. Second, the status of technological use in response to the 4th Industrial Revolution in the field of landscape architecture is generalizing the establishment of precise analysis results such as survey technology and global mapping using drones, three-dimensional design simulation, and VR. In the field of traditional landscape architecture, efforts are made to obtain accurate fact-finding data on landscape site components. Third, the application methods in the field of landscape science according to the 4th Industrial Revolution in the future are required to supply precision technology and supply programs in the technology sector, and to provide a shared platform. In addition, a systemically standardized process will need to be established for this. In addition, educational efforts should be continued to professional manpower training and provide economic support for the development of technologies.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.319-328
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• 2022

The purpose of this study was to investigate the relationship between depression due to the COVID-19 pandemic and park use behaviors using on line posts. During the period of the pandemic prevention activities, text data containing both 'park' and 'depression' were collected from blogs and cafes in the search engine of Naver and Daum, then analyzed using Text Mining and Social Network techniques. As a result, the main usage behaviors of park users who mentioned depression were 'look', 'stroll(walk)' and 'eat'. Other types of behaviors were connected centering around 'look', one of the communication behaviors. Also, from CONCOR analysis, as the cluster referred from communication behavior and dynamic behavior was formed as a single behavior type, it was considered park users with depression perceived the park as the space for communication and physical activities. As the spread of COVID-19 caused the restriction of communication activities, the users might consider parks as one of the solutions. In addition, it was considered that passive usage behaviors have prevailed rather than active ones due to the depression. Resulting outcomes would be useful to plan helpful urban park for citizens. It is necessary to further analyze the park use behavior of users in relation to the period of before/after the COVID-19 pandemic and the existence/nonexistence of depression.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.157-175
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• 2013

Since Korean government announced 'Smartwork promotion strategy' in 2010, Korean firms and government organizations have started to adopt smartwork. However, the smartwork has been implemented only in a few of large enterprises and government organizations rather than SMEs (small and medium enterprises). In USA, both Yahoo! and Best Buy have stopped their flexible work because of its reported low productivity and job loafing problems. In addition, according to the literature on smartwork, we could draw obstacles of smartwork adoption and categorize them into the three types: institutional, organizational, and technological. The first category of smartwork adoption obstacles, institutional, include the difficulties of smartwork performance evaluation metrics, the lack of readiness of organizational processes, limitation of smartwork types and models, lack of employee participation in smartwork adoption procedure, high cost of building smartwork system, and insufficiency of government support. The second category, organizational, includes limitation of the organization hierarchy, wrong perception of employees and employers, a difficulty in close collaboration, low productivity with remote coworkers, insufficient understanding on remote working, and lack of training about smartwork. The third category, technological, obstacles include security concern of mobile work, lack of specialized solution, and lack of adoption and operation know-how. To overcome the current problems of smartwork in reality and the reported obstacles in literature, we suggest a novel smartwork service model based on NFC(Near Field Communication). This paper suggests NFC-based Smartwork Service Model composed of NFC-based Smartworker networking service and NFC-based Smartwork space management service. NFC-based smartworker networking service is comprised of NFC-based communication/SNS service and NFC-based recruiting/job seeking service. NFC-based communication/SNS Service Model supplements the key shortcomings that existing smartwork service model has. By connecting to existing legacy system of a company through NFC tags and systems, the low productivity and the difficulty of collaboration and attendance management can be overcome since managers can get work processing information, work time information and work space information of employees and employees can do real-time communication with coworkers and get location information of coworkers. Shortly, this service model has features such as affordable system cost, provision of location-based information, and possibility of knowledge accumulation. NFC-based recruiting/job-seeking service provides new value by linking NFC tag service and sharing economy sites. This service model has features such as easiness of service attachment and removal, efficient space-based work provision, easy search of location-based recruiting/job-seeking information, and system flexibility. This service model combines advantages of sharing economy sites with the advantages of NFC. By cooperation with sharing economy sites, the model can provide recruiters with human resource who finds not only long-term works but also short-term works. Additionally, SMEs (Small Medium-sized Enterprises) can easily find job seeker by attaching NFC tags to any spaces at which human resource with qualification may be located. In short, this service model helps efficient human resource distribution by providing location of job hunters and job applicants. NFC-based smartwork space management service can promote smartwork by linking NFC tags attached to the work space and existing smartwork system. This service has features such as low cost, provision of indoor and outdoor location information, and customized service. In particular, this model can help small company adopt smartwork system because it is light-weight system and cost-effective compared to existing smartwork system. This paper proposes the scenarios of the service models, the roles and incentives of the participants, and the comparative analysis. The superiority of NFC-based smartwork service model is shown by comparing and analyzing the new service models and the existing service models. The service model can expand scope of enterprises and organizations that adopt smartwork and expand the scope of employees that take advantages of smartwork.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

• Journal of the Korean association of regional geographers
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• v.5 no.2
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• pp.1-14
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• 1999

In the course of modernization and globalization, each region in Korea has experienced deep subordination to the center of Seoul and the increase of colonization possibility by world capital. In order to overcome the current situation, above all, the strategies should be developed focusing on daily life and life space. The basis for the development of strategies is the establishment of regional identity on life space. It is because of the reason that life space, or small-scale region has drawn wide attention in the research of geography in recent years. Especially, humanistic geography and new regional geography have developed the concerning theory and methodology, and kept going on the research of small-scale regions. Generally speaking, there have been quite large amount of theoretical discussions on small-scale region in recent years in the field of geography. Empirical researches focusing on a particular small-scale region, however, have been rarely made. It seems related to the deficiency of data materials and the obscurity of research framework of small-scale regional geography. A community paper must be very helpful for the geographic research on small-scale region. As community paper is published based on county('gun'), small or mid-size city('si'), or district of large city('gu'), it deals with small news and daily life information closely attached to the region. Accordingly, it functions as a medium of the formation of regional identity. It is also a valuable source material for the validation of regional identity and for the analysis of identity-shaping mechanism. The geographic interests in community paper, first of all, should be taken shape by the work on the geographical distribution and the periodic change of publication situation of community papers in Korea. Another research subject on community paper is the examination of characteristics of the region by analyzing the news and the advertisements. The news in community paper must be a valuable data source of regional studies in geography. Also, the regional identification process of community people through the community paper could be and should be explored, and how the regional centrality, or self-generation based on the identity is achieved will be an important subject.

• Science of Emotion and Sensibility
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• v.17 no.3
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• pp.129-142
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• 2014

Due to the increase of the aged population and population of the disabled today, there is a growing demand for rehabilitation medical instruments. Furthermore, there is a growing demand for evaluation indices for services that should be provided for uses of the rehabilitation medical instruments. In order to evaluate rehabilitation medical instrument designs in this study, the basic index for design evaluations shall be identified to search for assessment plans. Through this, new evaluation indices will be deduced through discussions and analysis of rehabilitation medical experts, biomedical engineers, and designers. The results of this study are summarized as follows. First, the existing design evaluation indices were collected and analyzed to construct 10 rehabilitation medical instrument design evaluation indices and 44 sub-evaluation items. These will be important evaluation standards for designing rehabilitation medical instruments in the future. Second, the design evaluation indices that must be taken into consideration when developing health care rehabilitation medical instruments are the 10 design evaluation indices of usability, cognition, safety, learning, motility, durability, economic feasibility, space, aesthetics and environmental aspects. Third, design evaluation indices of environment, space, cognition, usability, economic feasibility and aesthetics are indices that must be taken into consideration for product design, while learning, safety, motility and durability are factors that must be given special consideration for rehabilitation medical instrument design evaluation indices. Fourth, if existing product design evaluation indices placed importance on environment, space, cognition, usability, economic feasibility and aesthetics of products for design evaluation indices, rehabilitation medical instrument design evaluation indices placed importance on learning, safety, motility and durability on top of usability and economic feasibility, which are the differences between the design evaluation indices of rehabilitation medical instrument and other product designs. The 10 rehabilitation medical device design evaluation indices and 44 sub-evaluation items were carried out in this study. This research is only on the overall rehabilitation medical device design evaluation indices. In future research, the evaluation indices will be applied in the actual rehabilitation medical design device through production of prototypes, while making revisions and supplementations where necessary.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.6 no.3
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• pp.15-24
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• 2007

According to an apartment house environment and the service provide method of major telecom operators, is providing optic-LAN service with installing the equipments of optical office center and optic distribution at MDF(Main Distribution Frame) and under-ground of apartment. therefore the distribute is deepening between service providers because of space securement to install equipments and spare pipe securement to reinstall UTP cable. These were reasons that operators leaned to subscriber collection and neglected to maintenance, in addition, insist the facilities invested by each operators is his own assets for all that in-plant of apartment house is private land. So, would not being touched by others. Accordingly, this study will search it through the field current condition examine that service's types and methods which various telecom operators and broadcast operators are providing, the current conditions of being maintained, the problems of being happened. etc. and would like to improve that the users could use the services safely by making the information & communication facilities maintenance mandatory under the regular size of apartment house circumstances through the analysis of various laws relations which are managed information & communication construction work law, telecommunication basis law, home network. etc. technical standards by the Ministry of Information and Communication and are managed housing law, construction law, the regulation related to house construct standards. etc. by the Ministry of Construction and Transportation.

• Journal of Navigation and Port Research
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• v.28 no.10 s.96
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• pp.869-874
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• 2004

Digital TV broadcasting's resolution or tone quality is very excellent than analog broadcasting and has many advantages including various multimedia functions such as home shopping, home banking, internet search, telecommuting, VOD, etc. In this study, it is essential to analyze the regional electromagnetic environment before Digital TV broadcasting, and therefore we analyzed Busan area's limitation using ETRI propagation model. For maintaining high-quality Digital TV signals, we measure electric field intensity wide and far in Busan including mountains area and high-rise buildings. Generally, it has lower value by a standard ETRI propagation model than simulated value about standard model, but distribution pattern are similar with it. Compared theoretical values with the measured results, they have similar values for flat area but very different values for crowded city area and mountains area So we conclude that ETRI propagation model and theoretical model are not suitable for Busan in a free space.