• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.143-152
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• 2015

The 'Quality Competitiveness Index' (QCI) is defined as an quantitative and disinterested indicator that measures and compares the quality of products across the world. The purpose of this study is to suggest the 'Quality Competitiveness Assessment Model' (QCAM) and calculate QCI of a popular UHF RFID Label tag (Global ISO 18000-3C supported) available these days in a global apparel market. The model was based on KS-QEI(Korean Standard-Quality Excellence Index), and was composed with the following 4 evaluation categories, a process capability test, an environmental reliability test, a durability test and a design margin test. The QCI score can be calculated with the following formula, using the weighted arithmetic mean between a score of each evaluation category ($X_1$, $X_2$, $X_3$, $X_4$) and each weight($w_1$, $w_2$, $w_3$, $w_4$). The actual weights was determined by an result of AHP survey to which was conducted for the related Industry-University-Institute experts. The proposed index shows the results of comparisons with global competitor's products as well as the high-quality domestic RFID label tags. In addition, it will play an important role for manufacturers when developing their future products.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• Land and Housing Review
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• v.14 no.2
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• pp.125-135
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• 2023

Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

• Journal of Venture Innovation
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• v.6 no.3
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• pp.165-184
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• 2023

Since municipal welfare institutions operate for different purposes from general companies or public enterprises, ESG practice items and model construction should be conducted through various and comprehensive social welfare studies. Since there are not many studies available in domestic welfare institutions yet and there are no suitable ESG management utilization indicators, the Cheonan Welfare Foundation's strategy and management strategy system were established to spread the model to other welfare institutions and become a leading foundation through education and training. The foundation and front-line welfare institutions selected issues identification and key issues through the foundation's empirical analysis and criticality analysis, focusing on understanding ESG management and ways to establish a practice model that positively affects institutional image and business performance. Based on this, the promotion system was examined by establishing a performance management plan after deriving appropriate strategies and establishing a strategic system for social welfare institutions. Environmental and social responsibility, transparent management, safety management system establishment, emergency and prevention, user (customer) satisfaction system establishment, anti-corruption prevention and integrity ethics monitoring and evaluation, responsible supply chains, and community contribution programs. This study attempted to specifically present efforts to settle ESG management through the consideration of the Cheonan Welfare Foundation. Therefore, it is considered to be useful data for developing ESG management by referring to the systematic development process of the Cheonan City Restoration Foundation to develop ESG measurement indicators.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.449-457
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• 2024

AIoT, the intelligent Internet of Things, refers to a technology that collects data measured by IoT devices and applies machine learning technology to create and utilize predictive models. Existing research on AIoT technology education focused on building an educational AIoT platform and teaching how to use it. However, there was a lack of case studies that taught the process of automatically creating and utilizing machine learning models from data measured by IoT devices. In this paper, we developed a case study using a machine learning model for AIoT technology education. The case developed in this paper consists of the following steps: data collection from AIoT devices, data preprocessing, automatic creation of machine learning models, calculation of accuracy for each model, determination of valid models, and data prediction using the valid models. In this paper, we considered that sensors in AIoT devices measure different ranges of values, and presented an example of data preprocessing accordingly. In addition, we developed a case where AIoT devices automatically determine what information they can predict by automatically generating several machine learning models and determining effective models with high accuracy among these models. By applying the developed cases, a variety of educational contents using AIoT, such as prediction-based object control using AIoT, can be developed.

• Journal of Korean Society of Forest Science
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• v.113 no.3
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• pp.349-360
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• 2024

This study aimed to analyze the main forest environmental factors affecting the discernment of slow-moving landslide-prone areas in the Republic of Korea, based on data from a detailed landslide survey conducted from 2019 to 2021. Field survey data from 256 sites were collected covering 29 forest environmental factors in seven categories, including geology, soil, and topography. The analysis was conducted using the Random Forest model (AUC = 0.910) and XGBoost model (Accuracy = 0.808, Kappa = 0.594, F1 - measure = 0.494), which were evaluated as having high classification accuracy during the machine learning model development process. Consequently, factors with a high mean decrease Gini (MDG), representing classification importance, were identified as the presence of cracks (average MDG of both models: 22.1), peak elevation (14.8), and the presence of steps (7.0), indicating that these were significant factors in determining slow-moving landslide-prone areas. The presence of cracks and steps aligned well with the characteristics of slow-moving landslides, suggesting that their importance should be emphasized in future detailed landslide surveys. However, the influence of the peak elevation was considered somewhat overestimated due to the characteristics of the input data used in the analysis. These findings are expected to further improve the accuracy and efficiency of final judgments in detailed landslide surveys.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.126-138
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• 2017

Recently, the national interest in environment is increasing and for dealing with water environment-related issues swiftly and accurately, the demand to facilitate the analysis of water environment data using a GIS is growing. To meet such growing demands, a spatial network data-based stream network analysis map(Korean Reach File; KRF) supporting spatial analysis of water environment data was developed and is being provided. However, there is a difficulty in delineating catchment areas, which are the basis of supplying spatial data including relevant information frequently required by the users such as establishing remediation measures against water pollution accidents. Therefore, in this study, the development of a computer program was made. The development process included steps such as designing a delineation method, and developing an algorithm and modules. DEM(Digital Elevation Model) and FDR(Flow Direction) were used as the major data to automatically delineate catchment areas. The algorithm for the delineation of catchment areas was developed through three stages; catchment area grid extraction, boundary point extraction, and boundary line division. Also, an add-in catchment area delineation module, based on ArcGIS from ESRI, was developed in the consideration of productivity and utility of the program. Using the developed program, the catchment areas were delineated and they were compared to the catchment areas currently used by the government. The results showed that the catchment areas were delineated efficiently using the digital elevation data. Especially, in the regions with clear topographical slopes, they were delineated accurately and swiftly. Although in some regions with flat fields of paddles and downtowns or well-organized drainage facilities, the catchment areas were not segmented accurately, the program definitely reduce the processing time to delineate existing catchment areas. In the future, more efforts should be made to enhance current algorithm to facilitate the use of the higher precision of digital elevation data, and furthermore reducing the calculation time for processing large data volume.

• Journal of Navigation and Port Research
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• v.38 no.4
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• pp.409-419
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• 2014

In accordance with the global age, countries in the world try to dedicate to collaboration among them through ODA (Official Development Assistance), in order to solve the-rich-get-richer and the poor-get-poorer problems among countries, to develop the developing countries' economies, and to improve their level of social welfare. Also, Korea is so active in ODA as a member of OECD, even if it is in the initial process. Nowadays, in Korea, the importance of ODA in the field of port has been brought into relief. Accordingly, the paper intends to analyze the dilemma structure of port ODA from the perspectives both of new institutionalism and Samaritan's dilemma game, and it tries to seek the improvements of ODA institutions to create effective outcomes based on the analysis. Through the analysis, dilemma structure was identified regarding the institutions of port ODA. And the results of the analysis suggested the improvements of port ODA institutions including strengthening of on-the-spot aid system, establishment of payoffs system for inducing recipient countries' efforts, and institutionalization of reliable threat. It would contribute to develop the theoretical model of ODA analysis and create effective outcomes of ODA in the field of ports.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.256-270
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• 2016

This purpose of this study is to present a new theoretical framework on birthrate recovery in advanced countries in the 21st century. As a result of socioeconomic development and individualism diffusion, the central axis of the family has transformed from the vertical axis of the father-son relation, to the horizontal axis of the husband-wife relation. This process is divided into 2 stages. In the industrialization stage, a nation or a society achieves equality of the individual in family formation, including marriage or divorce. In the post-industrialization stage, it accomplishes the couple equality in family maintenance, including child rearing and household labor. This paper grouped 33 OECD member countries as post- industrialization countries and 103 countries as industrialization countries. This study utilizes 6 variables affecting marriage and childbearing based on previous research. Research results find that during the industrialization stage, the birthrate falls as the education level of women is higher. In the post-industrialization stage, the birthrate rises as gender equality level is higher.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.6
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• pp.131-142
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• 2016

Since global circumstances have become competitive, entrepreneurship has been regarded as the most important factors in economic revitalization not only in korea but also internationally. According to these changes, public entrepreneurship education has been started from the year of 2004 establishing Entrepreneurial Graduate School as a part of governmental plan. Although entrepreneurship education history is not long enough in korea, but the need for entrepreneurship education in social is now going ahead of the public education systems such as universities and graduate schools. Therefore, this study is conducted for the purpose of drawing the subject frame for systematized integration curriculum of entrepreneurship education through evaluating the importance of the subjects by Analytic Hierarchy Process analysis after being composed of 6 modularity in the Entrepreneurship subjects. This was structured based on studying the current status for entrepreneurship education in domestic universities and graduate schools. The research findings under the condition of Judgement consistency ratio 0.1 are as follows. The most important factors are in order as following; "Entrepreneurial Issues for Fund"(.242), "Entrepreneurship Plan"(.195), "Entrepreneurship & Entrepreneurship mindset"(.161), "Entrepreneurial Issues for Growth & Development"(.160), "Management Skill & Strategy"(.150), and "Special Entrepreneurship"(.093). Then, these findings also represent subfactors as well. The results of this study provide the practical guidelines where the curriculums needed for the entrepreneurship education at graduate schools by suggesting consistency for the systematic and comprehensive curriculum design. It was reflected the survey result from the graduate students taking the entrepreneurship subjects. Therefore, it will contribute the foundation of the present curriculum of Entrepreneurial Graduate School.