• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.1-11
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• 2021

The purpose of this study is to find out the main factors affecting air quality in urban physical space factors, and provide clues for environmental improvement. Nine monitoring stations in China's industrial city, Changchun, collected AQI concentration data from January 1, 2018 to December 31, 2019. This paper analyzes the types and distribution characteristics of urban physical facilities within a radius of 300m with the detection station as the center. The monitoring station is divided into three groups, and the difference in floating dust concentration among the three groups in different seasons is analyzed. The results show that AQI concentration is the highest in spring and winter, followed by summer, and the lowest in autumn. The place with the highest concentrations of AQI in spring are F (93.00), D (91.10), I (89.20), in summer are D (69.05), A (67.89), B (84.44), in autumn are I (62.80), G (60.84), D (53.27), D (53.27), in winter are I (95.82), H (95.60), f (94.04). Through SPSS analysis, it shows that the air index in a space with a diameter of 600 meters is related to forest land, grassland, bare land, water space, tree height, building area (average value), and building volume (average value). According to the statistical analysis results of spring and winter with the most serious pollution, forest land area (43,637m², 15.44%) and water surface area (18,736m², 6.63%) accounted for the majority, and group 1 (A, B, C) with the least average building area (448m², 0.17%) and average building volume (10,201m²) had the lowest pollution concentration. On the contrary, group 2 (D, E, F) had the highest AQI concentration, with less or no woodland (1,917m², 0.68%) and water surface area (0m², 0%), and the highest average building area (1,056m², 0.37%) and average building volume (17,470m³). It is confirmed that the characteristics of the area with the highest AQI concentration are that the more the site ratio of tree height above 12m, the smaller the site ratio of bare land, and the lower the pollution degree. On the contrary, the larger the area of bare land, the higher the pollution degree. By analyzing the characteristics of nine monitoring stations in Changchun, it can be seen that the air quality brought by the physical characteristics of urban space is closely related to the above factors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.98-105
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• 2016

Group play for sociality is a therapeutic method involving a mixture of various factors, such as targeted activities, perceptions, and physical mobility required in daily life, through group activities to encourage self-expression for the purpose of facilitating sociality. This study was conducted in order to verify its effects by applying it to autistic adolescents who lack communicative ability with others and ultimately to improve their interpersonal relationships and sociality. This study applied a single pre- and post-test experiment design to 8 autistic adolescents with lack of sociality who use a daycare center in Daejeon. The group play for sociality program consisted of two sessions a week for 7 weeks from October to December 2013 for a total of 14 sessions. The sociality of the adolescents before and after the intervention was analyzed by the Wilcoxon signed-rank test. As a result of the study, the total grades of the E-CLAC and social maturity test showed significant changes from $39.88{\pm}6.78$ to $47.00{\pm}4.28$ and $49.96{\pm}28.00$ to $61.36{\pm}21.75$, respectively. In detail, there were significant changes in the sub-items, such as adjustment in group, following guidance, and increasing behavioral frequency. In conclusion, it was shown that the combined effect of the group activities, including group play for sociality and play activities taking into consideration the developmental stage of the participants, led to a significant improvement in the sociality of the autistic adolescents.

• The korean journal of orthodontics
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• v.41 no.3
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• pp.174-183
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• 2011

Objective: Orthodontically induced root resorption (OIRR) involves partial loss of cementum and dentin of teeth caused by routine orthodontic treatment. It decreases root length and influences the function of affected teeth. In this study, the treatment and patient factors causing apical root resorption in Koreans were determined. The observed factors were extraction, gender, age, displacement of root apex, total treatment period, total teeth length, and shape of the root. Methods: The records of 137 patients treated with full, fixed edgewise appliances were obtained from the Department of Orthodontics, Dankook University Dental Hospital, from November 2007 to December 2008. Periapical radiographs of the maxillary central incisors and cephalometric radiographs of each patient were used to assess apical root resorption and type of tooth movement. Results: The mean amount of resorption was $1.62{\pm}1.58mm$. The amount of resorption in the extraction and non-extraction groups was $2.10{\pm}1.64mm$ and $1.18{\pm}1.39mm$, respectively. The amount of root resorption increased with the total tooth length. Severe root resorption (> 4 mm) was related to abnormal root shape (blunt, pointed, or eroded). Conclusions: The variables significantly related to OIRR were extraction, initial tooth length, and root shape.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.165-174
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• 2016

This paper examined opportunities and limitations of building an innovation cluster based on large scale research facilities (LSRF). For this purpose, success factors of innovation clusters were drawn from the literature, and categorized into knowledge & technology, transaction cost & agglomeration economies, hardware & software infrastructure, and government policy & strategy. Utilizing the categorization as an analytic framework, case studies of CERN and SPring-8 were performed. The results showed that there were various innovation processes for both cases, creating opportunities for developing innovation clusters in terms of knowledge and technology. On the other hand, in the case of SPring-8, there were disadvantages in the transaction cost and agglomeration economies, being located in a remote area due to the nature of the facility. Software & hardware infrastructure of SPring-8 limited its potential for innovation clusters. Regarding government policy and strategy, CERN, as a multinational institution, did not consider an innovation cluster in a specific region despite some advantages. An innovation cluster around SPring-8 was promoted by government policy despite some disadvantages. In other words, the advantages and disadvantages were enhanced or complemented by software & hardware infrastructure and government policy & strategy. Based on the results, this paper provides the implications for the Korean International Science-Business Belt.

• The KIPS Transactions:PartD
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• v.18D no.6
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• pp.501-508
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• 2011

A knowledge map, which has been recently applied in various fields, is discovering characteristics hidden in a large amount of information and showing a tangible output to understand the meaning of the discovery. In this paper, we suggested a knowledge map for research trend analysis based on keyword-relation networks which are constructed by using a database of the domestic journal articles in the computer engineering field from 2000 through 2010. From that knowledge map, we could infer influential changes of a research topic related a specific keyword through examining the change of sizes of the connected components to which the keyword belongs in the keyword-relation networks. In addition, we observed that the size of the largest connected component in the keyword-relation networks is relatively small and groups of high-similarity keyword pairs are clustered in them by comparison with the random networks. This implies that the research field corresponding to the largest connected component is not so huge and many small-scale topics included in it are highly clustered and loosely-connected to each other. our proposed knowledge map can be considered as a approach for the research trend analysis while it is impossible to obtain those results by conventional approaches such as analyzing the frequency of an individual keyword.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.851-858
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• 2009

Mobbing is not restricted to problem of young people but the bigger recent problem occurs in workspaces. According to reports of ILO and domestic case mobbing in the workplace is increasing more and more numerically from 9.1%('03) to 30.7%('08). These mobbing brings personal and social losses. The proposed algorithm makes it possible to grasp not only current mobbing victims but also potential mobbing victims through user profile and contribute to efficient personnel management. This paper extracts user profile related to mobbing, in a way of selecting seven factors and fifty attributes that are related to this matter. Next, expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and through this summation Mobbing-Value(MV) can be calculated . Finally by mapping MV of online social network users to G2 mobbing propensity classification model(4 Groups; Ideal Group of the online social network, Bullies, Aggressive victims, Victims) which is designed in this paper, can grasp mobbing propensity of users, which will contribute to efficient personnel management.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.3
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• pp.47-61
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• 2014

Many angel investors hesitate to invest in early-stage company. Most early-stage company has no sales and only R&D step project or in early approach of market. So it's impossible to evaluate early-stage company quantitatively. Therefore many angel investors depend on CEO's tendency to evaluate company and make decision for investment. The purpose of this study is discover the entrepreneurial characteristics of CEO and the importance level which affect on the angel investors decision making factors for investment. To identify the factors of entrepreneurial characteristics, survey was conducted by Delphi Technique which is involved by 20 experts who is angel investment club members, venture capitalists, CEOs and officers. Three rounds of survey results derived 10 elements of entrepreneurial characteristics for investment decision making factors including reliability, risk sensitivity, passion, perseverance, integrity, leadership, startup experience, organizational management skills, innovation and social networking. In addition, this study derived the importance level of elements of entrepreneurial characteristics based on the AHP(Analytic Hierarchy Process) theory and maintained the logical consistency by pair-wise comparison for each element. As a result of analyzing the importance of entrepreneurial characteristics, the sequence is reliability (18.1%), integrity (15.9%), leadership (11.7%), organizational management skills (10.0%), social networking (9.5%), passion(9.1%), perseverance(8.4%), innovation(8.1%), startup experience(5.3%) and risk sensitivity(3.9%) respectively. The significance of this study is somewhat decrease limit of the uncertainty arising from angel investors and angel investors can help a decision making, by discover factors of entrepreneurial characteristics that can be called the biggest influencing factors among Investor's investment decision-making In early stage companies and compare importance.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.91-105
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• 2017

Korea is rapidly becoming a multicultural society in recent years, and the number of multicultural families in 2015 exceeds 3.5% and 800,000. Also, as international marriage rate exceeds 10% by 2016, the number of multicultural families is expected to steadily increase. This study is a design of a metadata application profile as part of the foundation for providing learning resources and content tailored to the needs and preferences of married immigrant women and multicultural family members who need to adapt to Korean society. In order to verify the necessity of the research, we conducted an in-depth interview by screening consumer groups, and analyzed the relevant international and Korean national standards as de-jure standards for the design of metadata standard profiles. Then, we analyzed the contents characteristics for multicultural members, and organized the necessary metadata elements into profiles. We defined the mandatory/optional conditions to reflect the needs of content providers. This study is meaningful in that the study analyzes the educational needs of married immigrant women and presents the necessary metadata standards to develop and service effective educational content, such as korean-to-korean conversion system, personalized learning contents recommendation service, and learning management system.

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.791-800
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• 2009

Multicasting is fundamental to many ad hoc network applications requiring collaboration of multiple nodes in a group. A general approach is to construct an overlay tree and to deliver a multicast packet to multiple receivers over the tree. This paper proposes adaptive overlay trees (AOTs) on wireless ad hoc networks of static nodes for delay- and energy-efficient multicast. A tradeoff function is derived, and an algorithm for AOT construction is developed. Note here that the requirements of delay and energy consumption may vary with different classes of applications. By adjusting parameters in the tradeoff function, different AOTs can be adaptively chosen for different classes of applications. An AOT is constructed in O(ke) time where e is the number of wireless links in a network and k is the number of member nodes in a multicast group. The simulation study shows that AOT adaptively provides tradeoffs between the fastest multicast (which is the choice if delay is the most important factor) and the most energy efficient multicast (which is used when energy consumption is the primary concern). In other words, one of AOTs can be appropriately chosen in accordance with the operation requirement.