• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.105-120
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• 2007

The primary purpose of this study lies in developing an intelligence level measurement model which can be applied to information home appliances. To accomplish the study purpose, the literature on computer engineering and intelligence is comprehensively researched and critical elements necessary for measuring the intelligence of smart home appliances are extracted. Then an intelligence level measurement model is derived, and the model is validated by several academic and practical experts using Delphi technique. The measurement model developed in the study, on the one hand, can provide users with some objective standards to evaluate the intelligence level of smart home appliances. On the other hand, it can help home appliance product developers or related service providers decide the target intelligence level of the products or services more specifically. Consequently, the model can contribute to the revitalization of the smart home appliance industry as a whole.

• The Journal of Industrial Distribution & Business
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• v.12 no.1
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• pp.31-46
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• 2021

Purpose: The purpose of the study is to analyze the characteristics of emotional intelligence and the variables related to emotional intelligence in a comprehensive manner. In addition, the study intends to present research trends and future research directions of emotional intelligence in a Korean context by analyzing the effects of emotional intelligence and its mechanisms. Research Design, Data, and Methodology: 77 KCI listed studies were selected for the analysis, and the research perspective of emotional intelligence, measurement instruments, empirical research and research methods were analyzed. In addition, research directions were suggested based on the analysis results. Results: The results of the analysis were as follows: First, previous researchers used the ability model of emotional intelligence the most. Second, Previous studies tended to focus on behavioral factors as dependent variables affected by emotional intelligence, in addition to attitudes, affection. Third, there were few studies on the antecedents of emotional intelligence, however, most studies dealt with the consequences of emotional intelligence. Fourth, few studies dealt with moderators between emotional intelligence and dependent variables. Fifth, on the research type, most studies were quantitative studies, however, a few of them were qualitative studies (Literature review, in-depth interview). Sixth, with regard to the analysis level, almost all studies were conducted on the individual level of emotional intelligence, and most studies featured a cross-sectional research design (longitudinal research design was rare). Conclusion: First, from the perspective of emotional intelligence, additional research should be focused on not only the ability model of emotional intelligence but also on the trait model or the mixed model in the future. Second, since emotional intelligence is a multidimensional construct, it is necessary to study the profile of emotional intelligence by employing people-centered as well as variable-centered methods. Third, with regard to empirical studies, additional research is needed with respect to not only the emotional intelligence of the subordinate, but also the emotional intelligence of the supervisor (leader) and the emotional intelligence of the group. Fourth, it is necessary to actively utilize not only cross-sectional design but also longitudinal design, and qualitative research and meta-analysis methods should also be adopted.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.115-120
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• 1993

It is difficult to establish a mathematical furnace model and automatic-fumace control because of the difficulty in direct measurement of the inner condition of a blast furnace. To solve this problem, we has developed and actually operated a blast furnace operation control system using artificial intelligence tool to be applied to the blast furnace process computer system. Since this system has a function of automatic Treat level control, higher practicality has been proved than the previous guidance-level expert system. This paper introduces an outline of the system and the result of application.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.37-49
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• 2002

The purpose of this research is to investigate the level of knowledge management in Korea small firms. The research scheme was experimented through a questionnaire survey answered by 150 firms. The research model was composed of five groups : 1) knowledge management and business strategic, 2) a culture and structure for knowledge management, 3) learning process and community 4) information technology to support knowledge management 5) a reward and performance measurement. The results of this research indicated that the level of knowledge management is different according to the characteristic of small firms. The result of the empirical analysis can be summarized as follows : First, the business culture for knowledge management is not performed pertinently. Second, the learning process for knowledge management and a reward and performance measurement is insufficient. Third, the characteristics of a fm should be considered for measuring the level of knowledge management.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.133-147
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• 1998

Recently, many researchers have been involved in finding deterministic equations which can accurately predict future event, based on chaotic theory, or fractal theory. The theory says that some events which seem very random but internally deterministic can be accurately predicted by fractal equations. In contrast to the conventional methods, such as AR model, MA, model, or ARIMA model, the fractal equation attempts to discover a deterministic order inherent in time series data set. In discovering deterministic order, researchers have found that neural networks are much more effective than the conventional statistical models. Even though prediction accuracy of the network can be different depending on the topological structure and modification of the algorithms, many researchers asserted that the neural network systems outperforms other systems, because of non-linear behaviour of the network models, mechanisms of massive parallel processing, generalization capability based on adaptive learning. However, recent survey shows that prediction accuracy of the forecasting models can be determined by the model structure and data structures. In the experiments based on actual economic data sets, it was found that the prediction accuracy of the neural network model is similar to the performance level of the conventional forecasting model. Especially, for the data set which is deterministically chaotic, the AR model, a conventional statistical model, was not significantly different from the MLP model, a neural network model. This result shows that the forecasting model. This result shows that the forecasting model a, pp.opriate to a prediction task should be selected based on characteristics of the time series data set. Analysis of the characteristics of the data set was performed by fractal analysis, measurement of Hurst index, and measurement of Lyapunov exponents. As a conclusion, a significant difference was not found in forecasting future events for the time series data which is deterministically chaotic, between a conventional forecasting model and a typical neural network model.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.37-47
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• 2024

This study presents the results of designing a system that determines the location of a person in an indoor environment based on a single IMU sensor attached to the tip of a person's shoe in an area where GPS signals are inaccessible. By adjusting for human footfall, it is possible to accurately determine human location and trajectory by correcting errors originating from the Inertial Measurement Unit (IMU) combined with advanced machine learning algorithms. Although there are various techniques to identify stepping, our study successfully recognized stepping with 98.7% accuracy using an artificial intelligence model known as Long Short-Term Memory (LSTM). Drawing upon the enhancements in our methodology, this article demonstrates a novel technique for generating a 200-meter trajectory, achieving a level of precision marked by a 2.1% error margin. Indoor pedestrian navigation systems, relying on inertial measurement units attached to the feet, have shown encouraging outcomes.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.387-395
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• 2006

홈 네트워크는 유비쿼터스의 여러 응용분야 중 활발하게 연구 구현되고 있는 분야 중의 하나로, 최근 아파트 건설업체, 가전기기 업체, 통신서비스 업체들이 지능성을 갖춘 스마트 홈을 목적으로 다양한 시험제품과 솔루션을 출시 흑은 제시하면서 이를 자사의 중요한 마케팅전략으로 활용하고 있다. 스마트 홈 네트워크를 구성하는 다양한 스마트 홈 기기의 제품 경쟁력은 제품이 얼마나 지능성을 갖추어 사용자에게 편리성과 유용성을 제공할 수 있는가의 여부가 중요한 관건이 되고 있다. 따라서 지능형 홈 기기의 지능에 대한 측정기준 마련이 필요한 시점이다. 본 연구에서는 스마트 홈 네트워크를 구성하는 여러 요소 중에서 정보가전기기를 지능성 측정 대상으로 하여 지능등급 부여모델을 개발하고자 한다. 지능형 홈 기기의 지능을 측정하기 위하여 로봇분야의 다양한 문헌 고찰을 토대로 지능성 측정에 필요한 핵심 구성요소를 도출 및 재 정의하여 등급모델을 설계하였다. 특히 설계된 등급부여모델의 실질적 이용을 위해서는 평가방식에 있어서 계량화 절차가 요구된다. 따라서 평가모델의 특성상 다차원적인 지능성의 속성을 총합적으로 나타내기 위하여 퍼지이론(Fuzzy Theory)을 사용하였으며, 이를 정규화하기 위해 퍼지적분(Fuzzy Integral)을 이용하였다. 산출된 적분값을 다시 비퍼지화하여 지능성 등급을 부여하는 모델을 개발하였다. 제시된 지능성 등급부여 모델은 스마트 홈 네트워크 산업의 발전을 촉진하는 계기가 될 수 있으리라 기대한다.

• Corrosion Science and Technology
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• v.23 no.3
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• pp.228-234
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• 2024

Zinc wiping is a phenomenon used to control zinc-coating thickness on steel substrate during hot dip galvanizing by equipment called air knife. Uniformity of zinc coating weight in length and width profile along with surface quality are most critical quality parameters of galvanized steel. Deviation from tolerance level of coating thickness causes issues like overcoating (excess consumption of costly zinc) or undercoating leading to rejections due to non-compliance of customer requirement. Main contributor of deviation from target coating weight is dynamic change in air knives equipment setup when thickness, width, and type of substrate changes. Additionally, cold coating measurement gauge measure coating weight after solidification but are installed down the line from air knife resulting in delayed feedback. This study presents a coating weight control model (Galvantage) predicting critical air knife parameters air pressure, knife distance from strip and line speed for coating control. A reverse engineering approach is adopted to design a predictive, prescriptive, and descriptive model recommending air knife setups that estimate air knife distance and expected coating weight in real time. Implementation of this model eliminates feedback lag experienced due to location of coating gauge and achieving setup without trial-error by operator.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.1-36
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• 2020

This study is to reveal the acceptance factors of the Market Sentiment Index (MSI) created by reflecting the investor sentiment extracted by processing unstructured big data. The research model was established by exploring exogenous variables based on the rational behavior theory and applying the Technology Acceptance Model (TAM). The acceptance of MSI provided to investors in the stock market was found to be influenced by the exogenous variables presented in this study. The results of causal analysis are as follows. First, self-efficacy, investment opportunities, Innovativeness, and perceived cost significantly affect perceived ease of use. Second, Diversity of services and perceived benefits have a statistically significant impact on perceived usefulness. Third, Perceived ease of use and perceived usefulness have a statistically significant effect on attitude to use. Fourth, Attitude to use statistically significantly influences the intention to use, and the investment opportunities as an independent variable affects the intention to use. Fifth, the intention to use statistically significantly affects the final dependent variable, the intention to use continuously. The mediating effect between the independent and dependent variables of the research model is as follows. First, The indirect effect on the causal route from diversity of services to continuous use intention was 0.1491, which was statistically significant at the significance level of 1%. Second, The indirect effect on the causal route from perceived benefit to continuous use intention was 0.1281, which was statistically significant at the significance level of 1%. The results of the multi-group analysis are as follows. First, for groups with and without stock investment experience, multi-group analysis was not possible because the measurement uniformity between the two groups was not secured. Second, the analysis result of the difference in the effect of independent variables of male and female groups on the intention to use continuously, where measurement uniformity was secured between the two groups, In the causal route from usage attitude to usage intention, women are higher than men. And in the causal route from use intention to continuous use intention, males were very high and showed statistically significant difference at significance level 5%.

• Asia pacific journal of information systems
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• v.17 no.2
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• pp.1-28
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• 2007

The success of new product development is a key factor for getting competitive advantages. Marketing research has been investigating marketing capability, manufacturing technical capability, cross-functional integration, market knowledge competence, market orientation, and competitive environment as the key success factors of new product development. Recently, the role of IT infrastructure in enhancing new product advantage is assumed in the literature. However, the empirical studies on the role of IT infrastructure are lacking. The purpose of this study is to empirically exam the impacts of IT infrastructure on new product competitive advantage. In this study, IT infrastructure is conceptualized as the flexibility of IT infrastructure. Based on previous research, a conceptual model is established by incorporating the direct impact of IT infrastructure flexibility and its indirect impact through the key success factors on new product development. To empirically test the research model, data are surveyed from a pair of IS department and Marketing department of 92 consumer goods manufacturers. By employing PLS technique, the measurement reliability and reliability of research variables are tested and the path analysis is conducted to do the hypothesis testing. The path analysis shows that IT infrastructure flexibility has no direct effect on new product advantage, However, the indirect effect of IT infrastructure is found, which is mediated by marketing capability, manufacturing technical capability, cross-functional integration, and market orientation respectively. Hence, The flexible IT infrastructure increases cross-functional integration (H1), market orientation (H3), marketing capability (H5), and manufacturing technical capability (H6). All success factors of new product development excepts for competitive environment have a positive association with new product competitive advantages (from H10 to H14). Finally, the path from IT infrastructure flexibility to cross-functional integration, to market orientation, to market knowledge capability, and to new product advantage is found as the strongest path. These results indicate that the flexible IT infrastructure enhances information sharing with multiple departments and collaboration within a distributed innovation environment. The collaboration among departments positively affects the level of customer and competitor intelligence. The ability to obtain knowledge about customers and competitors makes firms to adapt to a changing environment quickly and to respond to customers' demands adequately. The flexible IT infrastructure also enhances the capability of organization to more rapidly respond to the changes in product design resulting in faster product development and reduced costs. In addition to, it enhances marketing capability by the two-way communications with customers and the analyses of various kinds of customer data. In brief, the finding of this study suggests that the flexible IT infrastructure allows many firms to pursue sustained new product competitive advantages. This study advances research on IT infrastructure in two important aspects. First, by Integrating marketing research and IS research, this study develops a conceptual model on the role of IT infrastructure in enhancing new product advantage. Second, it empirically finds the indirect impacts of IT infrastructure on new product advantage, which confirms the potential for the IS field to contribute to new product development research. The limitations of this study are also discussed to provide research directions for future research.