• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.9
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• pp.1242-1248
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• 2012

Electric vehicle usage is currently very low, but it will be increase with development of electric vehicle technology and a good government policy. Moreover in 2020, advanced electric vehicle manufacturing system will give high performance for its price and mass production. Electric vehicle will become widespread in Korea. From an operational and a planned viewpoint, the electric power demand should be considered in relation to diffusion of electric vehicles. This paper presents the impact of the various battery charge systems. A comparison is performed for electric vehicle charging methods such as, normal charging, fast charging, and battery swapping. In addition, economic evaluation for the replaceable battery system and the quick battery charging system is performed through basic information about charging Infrastructure installation cost. The results of the evaluation show that replaceable battery system is more economical and reliable in side of electric power demand than quick battery charging system.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.65-72
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• 2009

Component based development has increasingly become important in the software industry. However, in the current component based development approach with UML, the absence of behavioral description of components brings about a cost problem which causes semantic errors on the testing phase. Accordingly we cannot grasp the usage pattern of component by its provided interfaces which refer to an abstraction of software component. And we cannot guarantee the behavioral conformance of the provided and required interfaces of components. In order to solve these problems, we describe the behaviors of component interfaces by state machine diagram and guarantee their behavior conformance at the modeling phase. We also propose a method to guarantee the behavior conformance of component interfaces with concept of observation equivalence and invocation consistency. And we provide an analyzing tool which checks interface behavior conformance.

• International Journal of Contents
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• v.17 no.1
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• pp.1-10
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• 2021

Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins' prices were high. Emotional language strategies on social media did not affect cryptocurrencies' reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.53-59
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• 2021

When using Medical Information Retrieval services, a typical retrieval method is to use the Anatomic Therapyutic Chemical Classification (ATC) code. Traditional ATC code-based medical information retrieval is very useful for single ingredient product retrieval with single ingredient. However, in the case of complex, retrieval errors often occur. The cause of this problem is that ATC code-based retrieval proceeds by pattern matching ATC code.In this work, we design the mapping scheme based on ATC code by analyzing the requirement scenarios for retrieval based on main ingredient in ATC code-based retrieval. the mapping scheme based on ATC is a schema that stores the ATC code of the complex and all the ATC code of the single agent included in the complex. ATC code-based retrieval using this schema retrieves a complex as ingredient of a single ingredient product, thus having higher accuracy than existing methods. the mapping scheme based on ATC is expected to increase the efficiency of doctors' prescription of patients and increase the accuracy of drug safety use services.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.567-575
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• 2020

As online social networks are used as a critical medium for modern people's information sharing and relationship, their users are increasing rapidly every year. This not only increases usage but also surpasses the existing media in terms of information credibility. Therefore, emerging marketing strategies are deliberately attacking social networks. As a result, public opinion, which should be formed naturally, is artificially formed by online attacks, and many people trust it. Therefore, many studies have been conducted to detect agents attacking online social networks. In this paper, we analyze the trends of researches attempting to detect such online social network attackers, focusing on researches using social network graph characteristics. While the existing content-based techniques may represent classification errors due to privacy infringement and changes in attack strategies, the graph-based method proposes a more robust detection method using attacker patterns.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.407-413
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• 2011

This paper presents an electrical power monitoring system for home energy management and an automatic appliance-identification algorithm based on the electricity-usage patterns collected during the monitoring tests. This paper also discusses the results of the field tests of which the proposed system was voluntarily deployed at 13 homes. The proposed monitoring system periodically measures the amount of power consumption of each appliance with a pre-specified time interval and effectively displays the essential information provided by the monitored data which is required users to know in order to save power consumption. Regarding the field tests of the monitoring system, the households responded that the system was useful in saving electricity and especially the electricity-usage patterns per appliances. They also considered that the predicted amount of the monthly power consumption was effective. The proposed appliance-identification algorithm uses 4 patterns: Zero-Crossing Rate(ZC), Variation of On State(VO), Slope of On State(SO) and Duty Cycle(DC), which are applied over the 2 hour interval with 25% of it on state, and it yielded 82.1% of success rate in identifying 5 kinds of appliances: refrigerator, TV, electric rice-cooker, kimchi-refrigerator and washing machine.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.19-29
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• 2011

Due to the development of web technologies and the increasing use of smart devices such as smart phone, in recent various web services are widely used in many application fields. In this environment, the topic of supporting personalized and intelligent web services have been actively researched, and an analysis technique on a web-click stream generated from web usage logs is one of the essential techniques related to the topic. In this paper, for efficient analyzing a web-click stream of sequences, a sequential pattern mining technique is proposed, which satisfies the basic requirements for data stream processing and finds a refined mining result. For this purpose, a concept of interesting sequential patterns with a time-interval constraint is defined, which uses not on1y the order of items in a sequential pattern but also their generation times. In addition, A mining method to find the interesting sequential patterns efficiently over a data stream such as a web-click stream is proposed. The proposed method can be effectively used to various computing application fields such as E-commerce, bio-informatics, and USN environments, which generate data as a form of data streams.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.275-281
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• 2016

In modern society, which boomed it became easier to obtain the necessary information to the emergence of a variety of smart devices. Due to this, the frequency of using the content based on the Web is growing rapidly. In addition, companies are turning into a production and modify the content using the CMS under the web-based. It can be a very important part to provide users with the content. Currently web services are designing a UI to the device and provided. To improve the ease of use, they are enhancing services only by survey and analysis of the patterns of all users. Most are designed without considering the UX only in the technical aspects. In this paper, to break the limits that apply to all users of the Web service pattern analysis, we propose a visualization system via the animation based on the individual user's movement patterns and usage patterns. Through this convergence is expected to be able to transform the web from the central manager to the user UX and the planning aspects researchers.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.35-46
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• 2010

Sequential pattern mining is one of the essential data mining tasks, and it is widely used to analyze data generated in various application fields such as web-based applications, E-commerce, bioinformatics, and USN environments. Recently data generated in the application fields has been taking the form of continuous data streams rather than finite stored data sets. Considering the changes in the form of data, many researches have been actively performed to efficiently find sequential patterns over data streams. However, conventional researches focus on reducing processing time and memory usage in mining sequential patterns over a target data stream, so that a research on mining more interesting and useful sequential patterns that efficiently reflect the characteristics of the data stream has been attracting no attention. This paper proposes a mining method of sequential patterns over data streams with a gap constraint, which can help to find more interesting sequential patterns over the data streams. First, meanings of the gap for a sequential pattern and gap-constrained sequential patterns are defined, and subsequently a mining method for finding gap-constrained sequential patterns over a data stream is proposed.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.3
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• pp.51-70
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• 2013

This paper develops a model to predict the adoption and level of usage of network technology in a two-level supply chain with buyer-supplier relationships. A firm's adoption of a new technology depends not only on its own beliefs of the new technology's costs and benefits, but also on the adoption decisions of other firms in the supply chain. A model first analyzes an individual supplier's decision about a new technology adoption considering with multiple suppliers and buyers. Individual suppliers' decisions are aggregated with a population model to project how new technology diffuses across the supply chain and examine the pattern of diffusion process. This study found that as more firms adopt in initial periods, the total amount of information to the potential adopters in the population increases, and then the number of firms persuaded by the information increases as the process moves up the distribution of adoption process. We consider three factors influencing the diffusion speed of the new technology in a supply chain network : mean benefits, cost sharing, and information provision. This study examines how such factors affect the reduction of threshold levels, which implies that reductions in threshold levels have an aggregate effect by accelerating the rate of adoption. In particular, we explore relationship factors available in practice in a buyer-supplier relationship and numerically examines how these relationship factors contribute to increase the diffusion speed of the technology in a two-level supply chain.