• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.21-30
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• 2023

As the adoption and high-performance enhancement of Electric Vehicles continue, the demand for high-output motors and high-capacity Magnetizer for producing large-scale IPMSM is increasing. The maximum peak current of the magnetization and the capacitor discharge time, which are important factors in the magnetization process, are determined by the circuit constants of the magnetizer. In this paper, we analyze the magnetizing system using MATLAB SIMULINK to design the circuit constant of the magnetizing yoke for magnetizing design and present the design procedure for Design the circuit constant. As a result, the parameters of the magnetizing yoke were derived to be 0.015[ohm] and 0.035[mH] based on the capacitance of 15,000[uF] and voltage of 5,000[V].

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.109-126
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• 2023

Early detection of forest fires is essential in preventing large-scale forest fires. Predicting forest fires serves as a vital early detection method, leading to various related studies. However, many previous studies focused solely on climate and geographic factors, overlooking human factors, which significantly contribute to forest fires. This study aims to develop forest fire prediction models that take into account human, weather and geographical factors. This study conducted a comparative analysis of four machine learning models alongside the logistic regression model, using forest fire data from Gangwon-do spanning 2003 to 2020. The results indicate that XG Boost models performed the best (AUC=0.925), closely followed by Random Forest (AUC=0.920), both of which are machine learning techniques. Lastly, the study analyzed the relative importance of various factors through permutation feature importance analysis to derive operational insights. While meteorological factors showed a greater impact compared to human factors, various human factors were also found to be significant.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.920-929
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• 2014

Recently, embedded system which demand is explosively increasing in the fields of communication, traffic, medical and industry facilities, expands to cyber physical system (CPS) which monitors and controls the networked embedded systems. In addition, internet of things(IoT) technology using wearable devices such as Google Glass, Samsung Galaxy Gear and Sony Smart Watch are gaining attention. In this situation, Samsung Smart Home and LG Home Chat are released one after another. However, since these services can be available only between smart phones and home appliances, there is a disadvantage that information cannot be passed to other terminals without commercial global messaging server. In this paper, to solve above issues, we propose the structure of an indoor location network based on unit space, which prevents the information of the devices or each individual person from leaking to outside and can selectively communicate to all existent terminals in the network using IoT chatting. Also, it is possible to control general devices and prevent external leakage of private information.

• Cartoon and Animation Studies
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• s.27
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• pp.177-198
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• 2012

Development of digital media and interest in education bring big progress at digital device of education globally. UK which is advanced country of education is using digital education devices such as digital chalkboards, digital desks etc. and Japan plan digital text book's through the state. At 2011, Korea which is advanced country of internet adopted digital text book 2007 with mathematics, through science and English digital text book through the state. Korea's digital textbook is in a transition period, that needs case-study of advanced country of education for setting design guide and educational effect to Digital text book plan. All researches are based on LG europe design center at London, UK and target countries are UK and Sweden which is advanced country of education and a welfare state. Analysis by using FGI, KJ, survey of questionnaire, heuristic method, concentration observation. Through analytical researches prefer using digital text book with paper text book to using solo that can offer each advantage to user and teacher. Especially Interactive GUI design of digital text book to easy to access for teacher whom not friendly with digital device. When plan Digital text book content and design needs methodical design guide for target who students and teachers an in-depth study of the appraisal and method. The results of the research are introduce the design plan as a basic research and giving useful design plan to make digital text book and digital educational media in industrial aspect.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.556-559
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• 2013

The purpose of the current research is to develop a strategy to activate the domestic Cloud Date Center (CDC), which allows various cloud services as a fundamental infrastructure in the rising cloud market. Specifically, the paper is proceeded based on three steps; (1) in the first step, the authors analyzes the overall CDC market including leading domestic as well as international CDC companies (e.g., EMC, HP, IBM, Samsung SDS, LG CNS, SK C&C) focusing on revenue, firm size, employee numbers, total energy consumption, market share, and so on. (2) In the next step, the study derives strengths and weaknesses based on the results of the first step. These strengths and weaknesses help us to deduct the factors which should be reinforced or complimented for the domestic CDC's competitive advantage in the global CDC market. Finally, considering these strengths and weaknesses in the second step, the authors suggest a strategy to activate the domestic CDC. Thus, this research will focus on the development of the strategic direction for the domestic CDC, which includes a checklist of strengths and weaknesses by analyzing the overall CDC market situation.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.247-254
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• 2021

As COVID-19 spread, non-face-to-face activities were required, and the use of service robots is gradually increasing. This paper analyzed the relationship between the increasing trend of service robots before and after COVID-19 through keyword search containing the keyword 'service robot AND non-face-to-face' over the past three years (2018.10-20219) using BigKines, a news big data analysis system. As a result, there were 0 cases in the first period (2018.10~2019.9), 52 cases in the second period (2019.10~2020.9) and 112 cases in the third period (2020.10~2021.9), an increase of 115% compared to the second period. The keywords commonly mentioned in the analysis of related words in the second and third periods were COVID-19, AI, the Ministry of Trade, Industry, and Energy, and LG Electronics, and the weight of COVID-19 was the largest, confirming that the analysis keyword. Due to the spread of Corona 19, non-face-to-face is required, and with the development of information and communication technology, the field of application of service robots is rapidly increasing. Accordingly, for the commercialization of service robots that will lead the non-face-to-face economy, there is an urgent need to nurture human resources that require standardization and expertise in safety and performance fields.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.115-123
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• 2021

In recent years, the automobile industry has been facing a major change with the introduction of new technologies represented by autonomous driving, electrification, and digitalization. Major domestic and overseas automakers are trying to use a systematic approach to customer satisfaction through user interfaces to provide customers with a special experience and value beyond just making products with high performance. This study proposes the Kano model as a systematic and qualitative research method for satisfaction. As a case study, 17 functions of a product were sorted (3 operation functions, 7 safety functions, and 7 convenience functions). This was done by analyzing the use case and the customers' requirements for a smart trunk system. 18 new functions were derived via creative ideation codes. In addition, a scientific analysis method is proposed for product quality attributes and the strength of customer satisfaction. Using the Kano methodology, 25 functions were classified into quality attributes: 18 attractive qualities, 3 one-dimensional qualities, and 4 complex qualities, which are combinations of one-dimension qualities and must-have qualities. The functions that have one-dimensional quality and complex qualities were found to have higher customer ratings than the functions that have attractive qualities. Based on this, enterprises could effectively reduce customer complaints and enhance customer satisfaction.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• The KIPS Transactions:PartA
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• v.17A no.4
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• pp.203-212
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• 2010

Recently, in automotive industry, there have been many researches related with hardware components and embedded software which controls hardware components. Since most of embedded software is tightly dependent on car manufacturers, there were some problems in reusability and interoperability of automotive software. In order to solve these problems, AUTOSAR standardized the component-based software architecture of automotive software. In AUTOSAR, several modeling diagrams should be described and their dependencies are also checked. Currently, a few company developed the prototypes of tools supporting AUTOSAR. In this paper, a component modeling tool based on AUTOSAR 3.0 is developed for enhancing the usability of existing tools using Eclipse GMF. The tool is composed of a graphical component modeling tool and a graphical network topology tool. Since these tools are generated based on GMF without hard coding, it is relatively easy to customize the tools for adopting company‘s needs and easy to follow the improvement of the standard and development environments.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.79-88
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• 2007

Demand for the technology for access to device control network in industry and for access to building automation system via internet is on the increase. In such technology integration of a device control network with a data network such as internet and organizing wide-ranging DCS(distributed control system) is needed, and it can be realized in the framework of VDN(virtual device network)[1,2]. Specifications for device control network and data network are quite different because of the differences in application. So a router that translates the communication protocol between device control network and data network and efficiently transmits information to destination is needed for implementation of the VDN, This paper proposes the concept of NCS(networked control system) based on VDN(virtual device network) and suggests the routing algorithm that uses embedded system.[3]