• 대한안전경영과학회지
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• 제19권1호
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• pp.63-71
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• 2017

As the demand for automation (or autonmation) or clean workplace has grown, the interest in the knowledge and skill regarding safety is rising in manager duty. Moreover, the importance of severity rate of injury has increased due to the enlargement of industry scale, even safety management area has developed. Thus, it is important that production managers, the core of the line process, realize the safety in their production line, even if a safety manager acts as a staff. However, in the duty oriented National Competency Standard (NCS), the education about the safety duty of production management part is insufficient. According to NCS, it is calculated production managers receive only 6.7% of whole safety education regarding the duty related the safety management for production manager in mechanical industry. However, the ability in safety is more demanded from production managers as the concept of "production and safety" turns into the concept of "production with safety". And then in this paper, we will compare and analyze the safety management duty in Korean NCS and the safety management duty in State Leaders Connecting Learning to Work in US manufacturing industry, in terms of the duty of the production manage in mechanical industry (05). And, we will develop the safety duty education system for production manager, by classifying the safety education in domestic mechanical industry into knowledge education, skill education, and attitude education with using AHP(Analytic Hierarchy Process).

• 방사선산업학회지
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• 제10권1호
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• pp.1-5
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• 2016

In this study, the effect of high-energy proton irradiation on the optical properties of polyacrylonitrile (PAN) films was investigated. PAN thin films spin-coated on a substrate were irradiated 150 keV proton ions at various fluences. The changes in the chemical structure and optical properties were investigated by FT-IR and UV-vis spectroscopy. The results of the FT-IR analysis revealed that the cyclization reaction took place by proton irradiation and the degree of cyclization increased with an increasing fluence. Based on the UV-vis analysis, the optical band gap of PAN decreased from 2.84 to 2.52 eV with an increasing fluence due to the formation of carbon clusters by proton irradiation. In addition, the number of carbon atoms per carbon cluster and the number of carbon atoms per conjugation length were found to be increased with an increasing fluence.

• 환경영향평가
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• 제17권6호
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• pp.335-348
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• 2008

The purpose of this study is to classify the cities on sustainability assessment score studied in advance using cluster analysis, to present efficient management and policy direction based on analysis of sustainability index in 45 cities of all over Gyeongsangnam and Gyeongsangbuk-do. According to the results of cluster analysis, 45 cities were classed into 4 clusters by "livable-welfare city", "environmental -ecological city", "scientific-technological city", and "industrial-economic city". The livable-welfare cities must keep superior environmental sustainability, promote small and medium sized business on regional characteristic. The environmental-ecological cities have to change agriculture into future environmental industry such as ecotourism, bio-industry and landscape agriculture. The scientific-technological cities are going to need support of government scale such as income enlargement of citizen and stable job security. Finally, the industrial-economic cities must increase environmental management plants and improve quality of life through securing green spaces, maintaining public peace and applying UIS because of low quality of environment and life.

• 디지털산업정보학회논문지
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• 제6권3호
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• pp.19-29
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• 2010

A marketing model is changed from a customer acquisition to customer retention and it is being moved to a way that enhances the quality of customer interaction to add value to our customers. Such personalization is emerging from this background. The Web site is accelerate the adoption of a personalization, and in contrast to the rapid growth of data, quantitative analytical experience is required. For the automated analysis of large amounts of data and the results must be passed in real time of personalization has been interested in technical problems. A recommendation algorithm is an algorithm for the implementation of personalization, which predict whether the customer preferences and purchasing using the database with new customers interested or likely to purchase. As recommended number of users increases, the algorithm increases recommendation time is the problem. In this paper, to solve this problem, a recommendation system based on clustering and dimensionality reduction is proposed. First, clusters customers with such an orientation, then shrink the dimensions of the relationship between customers to low dimensional space. Because finding neighbors for recommendations is performed at low dimensional space, the computation time is greatly reduced.

• Asian Journal of Innovation and Policy
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• 제9권2호
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• pp.164-186
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• 2020

It is generally known that a Science and Technology Park - as a representative example of an Innovation Cluster - produces network synergy among industry, university, research institutes, and other innovation actors in a specific area, so that it has a competitive edge over other regions in technological innovation. However, as the novel Coronavirus (COVID-19) pandemic unfolds, it has become necessary to reduce face-to-face contacts and this could lead to lesser network synergy being produced in an Innovation Cluster. With this background, this research was designed and conducted to evaluate how COVID-19 has changed the activities in Innovation Clusters and explore future development scenarios. In order to find out the changes occurring in an Innovation Cluster, a survey was conducted among the people in Science and Technology Parks. The survey result shows that people are experiencing difficulties in technological innovation and support activities, and face-to-face contacts have been reduced in the Innovation Cluster. A scenario planning sought to explore the future development of the Innovation Cluster. It suggests that the transformation into a Digital Innovation Cluster, which is less affected by physical distance, but can still maintain the effectiveness of the networks, can be the key strategy for the future Innovation Cluster.

• 디지털산업정보학회논문지
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• 제4권2호
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• pp.29-37
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• 2008

Clustering allows hierarchical structures to be built on the nodes and enables more efficient use of scarce resources, such as frequency spectrum, bandwidth, and energy in wireless sensor networks (WSNs). This paper proposes a hierarchical clustering algorithm called EEHC which is more energy efficient than existing algorithms for WSNs, It introduces region node selection as well as cluster head election based on the residual battery capacity of nodes to reduce the costs of managing sensor nodes and of the communication among them. The role of cluster heads or region nodes is rotated among nodes to achieve load balancing and extend the lifetime of every individual sensor node. To do this, EEHC clusters periodically to select cluster heads that are richer in residual energy level, compared to the other nodes, according to clustering policies from administrators. To prove the performance improvement of EEHC, the ns-2 simulator was used. The results show that it can reduce the energy and bandwidth consumption for organizing and managing WSNs comparing it with existing algorithms.

• 디지털산업정보학회논문지
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• 제11권4호
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• pp.89-97
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• 2015

In this paper, a method of color image segmentation based on DBSCAN(Density Based Spatial Clustering of Applications with Noise) using compactness of superpixels and texture information is presented. The DBSCAN algorithm can generate clusters in large data sets by looking at the local density of data samples, using only two input parameters which called minimum number of data and distance of neighborhood data. Superpixel algorithms group pixels into perceptually meaningful atomic regions, which can be used to replace the rigid structure of the pixel grid. Each superpixel is consist of pixels with similar features such as luminance, color, textures etc. Superpixels are more efficient than pixels in case of large scale image processing. In this paper, superpixels are generated by SLIC(simple linear iterative clustering) as known popular. Superpixel characteristics are described by compactness, uniformity, boundary precision and recall. The compactness is important features to depict superpixel characteristics. Each superpixel is represented by Lab color spaces, compactness and texture information. DBSCAN clustering method applied to these feature spaces to segment a color image. To evaluate the performance of the proposed method, computer simulation is carried out to several outdoor images. The experimental results show that the proposed algorithm can provide good segmentation results on various images.

• 한국의류산업학회지
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• 제8권3호
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• pp.310-316
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• 2006

Fitness of clothes becomes a major concern in apparel industry. But male sports athletes had difficulties to buy ready-made clothes of good fit. Because ready-made clothes manufactured in companies are produced accordingly to the general person's body types. To solve this problem, it is necessary to classify athletes' upper body into several kinds of somatotypes. The purpose of this study was to classify upper body types of male sports athletes based on the analysis of their upper body types and to provide fundamental data on the development of ready-to-wear clothing appropriate for the upper body types. The subjects for anthropometric measurement were 189 male sports athletes of 20 to 29 year-old. The result of factor analysis indicated that 6 factors were extracted from anthropometric measurements through analysis and those factors comprise 73.807% of total variance. 3 clusters were categorized using 6 factor scores by cluster analysis. Type 1 was taller than other types, had average size in circumference, width and thickness and was bending somatotype. Type 2 exhibits a large circumference in the upper body and straight somatotype. Type 3 was characterized by short, exhibits a large circumference in waist, abdomen and hip and swayback somatotype.

• 한국의류산업학회지
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• 제23권3호
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• pp.380-389
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• 2021

This study aimed to reveal the perceptions and trends of digital fashion technology through an informational approach. A big data analysis was conducted after collecting the text shown in a web environment from April 2019 to April 2021. Key words were derived through text mining analysis and network analysis, and the structure of perception of digital fashion technology was identified. Using textoms, we collected 8144 texts after data refinement, conducted a frequency of emergence and central component analysis, and visualized the results with word cloud and N-gram. The frequency of appearance also generated matrices with the top 70 words, and a structural equivalent analysis was performed. The results were presented with network visualizations and dendrograms. Fashion, digital, and technology were the most frequently mentioned topics, and the frequencies of platform, digital transformation, and start-ups were also high. Through clustering, four clusters of marketing were formed using fashion, digital technology, startups, and augmented reality/virtual reality technology. Future research on startups and smart factories with technologies based on stable platforms is needed. The results of this study contribute to increasing the fashion industry's knowledge on digital fashion technology and can be used as a foundational study for the development of research on related topics.

• 디지털산업정보학회논문지
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• 제14권4호
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• pp.9-16
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• 2018

This study described partial discharge(PD) distribution analysis between the XLPE(Cross-Linked PolyEthylene)and EPDM(Ethylene Propylene Diene Monomer) interface with unsupervised classification. The ${\phi}-q-n$ patterns were analyzed using phase resolved partial discharge(PRPD). K-means cluster analysis forms a cluster based on similarities and distances among scattered individuals, and analyzes the characteristics of the formed clusters, dividing the multivariate data into several groups according to the similarity of each characteristic, Is a statistical analysis that makes it easier to navigate. It was confirmed that the phase angle of the cluster with the maximum discharge charge was concentrated around $0^{\circ}$ and $180^{\circ}$ at 30 kV after the initial phase distribution localized around $90^{\circ}$ and $300^{\circ}$ expanded to the whole phase angle according to the voltage rise. The Euclidean distance between the center of gravity and the discharge charge in the ${\Phi}-q$ cluster increased with increasing applied voltage.