• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.127-135
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• 2015

Universal design is defined as the design process of products and environments usable by all people to the greatest extent possible, without the need for adaptation or specialized design. The benefits of universal design have been promoted primarily through illustrative 'success stories' of public, residential and occupational environments and products. While case examples may be informative, they may unfortunately be limited in terms of generality to other designs or tasks. Therefore, design methods and criteria that can be applied systematically in a range of situations to encourage universal design are needed. In addition, the seven principles of universal design are intended to guide the design process. The principles provide a framework that allows a systematic evaluation of new or existing designs and assists in educating both designers and consumers about the characteristics of more usable products and environments. However, exactly how these principles are incorporated into the design process has beenleft up to the designer. Since the introduction of universal design, designers have become familiar with the principles of universal design, and they have developed many products based on universal design. However, the principles of universal design are qualitative, which means designers cannot quantitatively evaluate their designs. Some have worked to develop more systematic ways to evaluate products and environments by providing design guidelines for each of the principles. However, recommendations have not yet been made regarding how to integrate performance measures of universal design into the product design process before the product is mass produced. Furthermore, there are sets of requirements regarding each user group that has different age and ability. Consequently, there is an urgent need for design methods, based on a better understanding of age and ability related factors, which will lead to a universally designed product or environment. The authors have proposed the PSD (Preference Set-Based Design) method that can generate a ranged set of feasible solutions (i.e., robust and flexible solution set) instead of single point solution that satisfies changing sets of design targets. The objective of this paper is to develop a general method for systematically supporting the universal design process. This paper proposes the applicability of PSD method to universal design. Here, the proposed method is successfully illustrated with a universal design problem.

• The Journal of Society for e-Business Studies
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• v.20 no.3
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• pp.47-58
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• 2015

Recently, new information security vulnerabilities have proliferated with the convergence of information security environments and information and communication technology. Accordingly, new types of cybercrime are on the rise, and security breaches and other security-related incidents are increasing rapidly because of security problems like external cyberattacks, leakage by insiders, etc. These threats will continue to multiply as industry and technology converge. Thus, the main purpose of this paper is to design and present security subjects in order to train professional security management talent who can deal with the enhanced threat to information. To achieve this, the study first set key information security topics for business settings on the basis of an analysis of preceding studies and the results of a meeting of an expert committee. The information security curriculum taxonomy is developed with reference to an information security job taxonomy for domestic conditions in South Korea. The results of this study are expected to help train skilled security talent who can address new security threats in the future environment of industrial convergence.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.71-90
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• 2012

Although it has been studied for a long time in various disciplines, most of control theories remain being developed by analyzing relatively simple tasks. Even recent research on control of information systems development explains only a small part of control phenomena observed in the real world projects. This research focuses on identifying and analyzing the concepts and structures in order to make them useful for understanding and explaining control of information systems development comprehensively This investigation utilizes the complementary relationship between views on control from organizational and economic perspectives. A conceptual framework developed by integrating previous research on control allows us to analyze the development of information systems for control purposes. The results of discussion about control mechanisms and network can be used as guidelines for designing control systems in real projects. Analysis of control networks shows that control of development projects requires quite complex networks intertwining a variety of controllers and controlees. The results of this research are expected to contribute to correcting the unbalanced status of IS research which has emphasized too heavily on planning and implementation, and deepening and widening our understanding about controlling development projects. Practitioners can use the results as guidelines for designing control mechanisms and networks, and get alerted by them about the agency risks inherent in outsourced developments.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.251-264
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• 2008

One of the crucial elements to fully facilitate the various benefits of intelligent transportation systems (ITS) is to obtain more reliable traffic monitoring in real time. To date, point and section-based traffic measurements have been available through existing surveillance technologies, such as loops and automatic vehicle identification (AVI) systems. However, seamless and more reliable traffic data are required for more effective traffic information provision and operations. Technology advancements including vehicle tracking and wireless communication enable the acceleration of the availability of individual vehicle travel information. This study presents a UBIquitous PRObe vehicle Surveillance System (UBIPROSS) using vehicle-to-vehicle (V2V) wireless communications. Seamless vehicle travel information, including origin-destination information, speed, travel times, and other data, can be obtained by the proposed UBIPROSS. A set of parameters associated with functional requirements of the UBIPROSS, which include the market penetration rate (MPR) of equipped vehicles, V2V communication range, and travel time update interval, are investigated by a Monte Carlo simulation- (MCS) based evaluation framework. In addition, this paper describes prototypical implementation. Field test results and identified technical issues are also discussed. It is expected that the proposed system would be an invaluable precursor to develop a next-generation traffic surveillance system.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.433-441
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• 2020

The advent of the intelligent information society and artificial intelligence education for fostering future talents is attracting the attention of the education community, and the AI graduate course for teachers is also being opened and operated. The curriculum of the AI education graduate school, which was established this year, is self-contained considering the conditions of each university. Are organized. Accordingly, this study seeks to explore the direction of curriculum development so that AI curriculum that can be more effective and enhance educational value in the graduate school of education can be developed in the future. Based on the Backward design, the AI curriculum proposed in this study includes Bloom's digital taxonomy, Bruner's spiral curriculum composition principle, and three elements such as 'content domain', 'level', and 'teacher learning method'. It was intended to consist of. Based on the direction of AI curriculum development suggested in the study, we hope that the AI curriculum of domestic graduate schools of education will be more substantial, and this framework will be revised and supplemented in the future to be used in the composition of the AI curriculum in elementary and secondary schools.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.49-57
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• 2022

Currently, the problem of food shortage is emerging in our society due to climate problems and an increase population in the world. As a solution to this problem, we propose a multi-remote control smart farm that combines artificial intelligence (AI) and information and communication technology (ICT) technologies. The proposed smart farm integrates ICT technology to remotely control and manage crops without restrictions in space and time, and to multi-control the growing environment of crops. In addition, using Arduino and deep-learning technology, a smart farm capable of multiple control through a smart-phone application (APP) was proposed, and Ai technology with various data securing and diagnosis functions while observing crop growth in real-time was included. Various sensors in the smart farm are controlled by using the Arduino, and the data values of the sensors are stored in the built database, so that the user can check the stored data with the APP. For multiple control for multiple crops, each LED, COOLING FAN, and WATER PUMP for two or more growing environments were applied so that the user could control it conveniently. And by implementing an APP that diagnoses the growth stage through the Tensor-Flow framework using deep-learning technology, we developed an application that helps users to easily diagnose the growth status of the current crop.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.397-412
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• 2023

In order for social robots to take root in human life, it is important to consider the technical implementation of social robots and human psychology toward social robots. This study aimed to derive potential social robot clusters based on the emotions consumers feel about social robot appearance design, and to identify and compare important design characteristics and emotional differences of each cluster. In our study, we established a social robot emotion framework to measure and evaluate the emotions consumers feel about social robots, and evaluated the emotions of social robot designs based on the semantic differential method, an kansei engineering approach. We classified 30 social robots into 4 clusters by conducting a multidimensional scaling method and K-means cluster analysis based on the emotion evaluation results, confirmed the characteristics of design elements for each cluster, and conducted a comparative analysis on consumer emotions. We proposed a strategic direction for successful social robot design and development from a human-centered perspective based on the design characteristics and emotional differences derived for each cluster.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.91-110
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• 2023

The importance of manuals is emphasized because chemical accidents require swift response and recovery, and often result in environmental pollution and casualties. In this regard, the OECD revised OECD Guidelines for the Prevention, Preparedness, and Response to Chemical Accidents (referred to as the OECD Guidelines), in June 2023. Moreover, while existing research primarily raises awareness about chemical accidents, highlighting the need for a system-wide response including laws, regulations, and manuals, it was difficult to find comparative research on the attributes of manuals. So, this paper aims to compare and analyze the second and third editions of the OECD Guidelines, in order to uncover the information attributes and implications of the revised version. Specifically, TF-IDF (Term Frequency-Inverse Document Frequency) was applied to understand which keywords have become more important, and Word2Vec was applied to identify keywords that were used similarly and those that were differentiated. Lastly, a 2×2 matrix was proposed, identifying the topics within each quadrant to provide a deeper comparison of the information attributes of the OECD Guidelines. This study offers a framework to help researchers understand information attributes. From a practical perspective, it appears valuable for the revision of standard manuals by domestic government agencies and corporations related to chemistry.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.1-22
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• 2009

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction and integration both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of techniques for Web service discovery have been proposed, but the discovery challenge has not been satisfactorily addressed. Unfortunately, most existing solutions are either too rudimentary to be useful or too domain dependent to be generalizable. In this paper, we propose a Web service organizing framework that combines clustering techniques with string matching and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. Our proposed approach has several appealing features : (1) It minimizes the requirement of prior knowledge from both service consumers and publishers; (2) It avoids exploiting domain dependent ontologies; and (3) It is able to visualize the semantic relationships among Web services. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service registries. We report on some preliminary results demonstrating the efficacy of the proposed approach.