• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.77-89
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• 2023

The purpose of this study is to empirically confirm what is an important variable of organizational change by intelligent technology acceptance and whether is a difference in important variables in the organization level of acceptance of intelligent technology. Recently, business models using intelligent technologies such as chat-bots, self-driving cars, credit-prevention fraud, face recognition, and health-care are emerging. External situation factors such as artificial intelligence, big data, COVID-19, and the ESG management are changing the direction of a company's management strategy. This research method established a structural equation model. As a result of the analysis, we found that the leadership, organizational culture, and organizational cooperation variables had a positive effect on human resource development variables. Human resource development found a positive effect on the performance of intelligent technology. In addition, we found the independent variables of leadership, organizational culture, and organizational cooperation had partial mediating effects on the performance of intelligent technology. Each group of levels of intelligent technology found performance differences. The organizational culture variables appeared as important variables in all groups. On the other hand, the leadership variable appeared as an important variable in the middle and lower groups of intelligent technology. The theoretical background of this study is that the business theory was updated through artificial intelligence and intelligent technology theory. As a practical implication, the organization adopting intelligent technology is necessary to prepare a systematic plan for organizational culture change.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.3
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• pp.10-17
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• 2001

We need to how about activity types, lighting conditions and physical features in a plate that is a object for the reasonable and economic lighting design. Thus, lighting designer analyzes spare features and completes lighting design by using luminaire that has a suitable luminous intensity distribution. There are special data in this study from analysing about activity types, lighting conditions and physical features of intelligent buildings that are getting an essential infrastructure in the information society. Intelligent building could be classified with office space, passing space, high ceiling space, one-side working space for the analysis. Also, four luminous intensity distributions and fluorescent fixtures, which are the mutt used luminaires in office building, are designed from the data of intelligent building.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.695-700
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• 2001

We design the intelligent diagnosis system for deciding on operation of TMS Analysis in this paper. We propose the method to model the neuro-fuzzy model for diagnosing the operation state of analyzer by using input and output signals of TMS and Expert's experiment data. Validity of the proposed system is asserted by numerical simulation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.5
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• pp.114-120
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• 2009

In outdoor visible light communication channels and LED road illumination communications for the intelligent transport systems (ITS), inter symbol interference (ISI) due to multipath propagation prevents high data rate transmission. Indoor wireless optical communication systems utilizing white LED lights and on the road illumination have been studying about it. Generally, plural lights are installed in room and considered to the traffic information system using existing LED traffic lights. Therefore, their optical path difference must be considered. In this paper, the influence of an optical path difference has been investigated and two approaches against this problem are introduced. One uses on-off keying, return-to-zero (OOK-RZ) coding and the other uses optical orthogonal frequency division multiplexing(OFDM).

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.133-138
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• 2008

In this paper, we propose a novel anchor shot detection system, named to MASD (Multi-phase Anchor Shot Detection), which is a core step of the preprocessing process for the news video analysis. The proposed system is composed of four modules and operates sequentially: 1) skin color detection module for reducing the candidate face regions; 2) face detection module for finding the key-frames with a facial data; 3) vector representation module for the key-frame images using a non-negative matrix factorization; 4) one class SVM module for determining the anchor shots using a support vector data description. Besides the qualitative analysis, our experiments validate that the proposed system shows not only the comparable accuracy to the recently developed methods, but also more faster detection rate than those of others.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.162-170
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• 2014

Appearance-based subspace models such as eigenfaces have been widely recognized as one of the most successful approaches to face recognition and tracking. The success of eigenfaces mainly has its origins in the benefits offered by principal component analysis (PCA), the representational power of the underlying generative process for high-dimensional noisy facial image data. The sparse extension of PCA (SPCA) has recently received significant attention in the research community. SPCA functions by imposing sparseness constraints on the eigenvectors, a technique that has been shown to yield more robust solutions in many applications. However, when SPCA is applied to facial images, the time and space complexity of PCA learning becomes a critical issue (e.g., real-time tracking). In this paper, we propose a very fast and scalable greedy forward selection algorithm for SPCA. Unlike a recent semidefinite program-relaxation method that suffers from complex optimization, our approach can process several thousands of data dimensions in reasonable time with little accuracy loss. The effectiveness of our proposed method was demonstrated on real-world face recognition and tracking datasets.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.268-273
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• 2005

We propose the specialized product-line development methodology for developing the embedded system of an MSDFS (Multi Sensor Data Fusion System : called MSDFS). The product-line methodology provides a simultaneous design between software and hardware, high level reusability. However this is insufficient in requirement analysis stage due to be focused on software architecture, detailed design and code. Thus we apply the business model based on IDEF0 technique to traditional methodology. In this paper, we describe the processes of developing Core-Asset, which are requirement analysis, feature modeling, validation. The proposed model gives the efficient result for eliciting features, and ensures the high level reusability of modules performing on embedded system.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.20-25
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• 2023

Increasing demand for increasing higher data rate in order to solve computationally tasks timely and connecting many user equipment simultaneously have requested researchers to develop novel technology in the area of mobile communications. Intelligent reflecting surface (IRS) have been enabling technologies for commercialization of the fifth generation (5G) networks and the sixth generation (6G) systems. In this paper, we investigate a bit-error rate (BER) analysis on IRS technologies for non-orthogonal multiple access (NOMA) systems. First, we derive a BER expression for IRS-NOMA systems with Rician fading channels. Then, we validate the BER expression by Monte Carlo simulations, and show numerically that BER expressions are in good agreement with simulations. Moreover, we investigate the BER of IRS-NOMA systems with Rician fading channels for various numbers of IRS elements, and show that the BERs improve as the number of IRS elements increases.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.107-113
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• 2003

A new GA-based methodology using information granules is suggested for the construction of fuzzy classifiers. The proposed scheme consists of three steps: selection of information granules, construction of the associated fuzzy sets, and tuning of the fuzzy rules. First, the genetic algorithm (GA) is applied to the development of the adequate information granules. The fuzzy sets are then constructed from the analysis of the developed information granules. An interpretable fuzzy classifier is designed by using the constructed fuzzy sets. Finally, the GA are utilized for tuning of the fuzzy rules, which can enhance the classification performance on the misclassified data (e.g., data with the strange pattern or on the boundaries of the classes). To show the effectiveness of the proposed method, an example, the classification of the Iris data, is provided.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.16-25
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• 1998

In this paper, we propose features extraction method using Rough sets theory for efficient data classifications in hyperspectral environment. First, analyze the properties of multispectral image data, then select the most efficient bands using discemibility of Rough sets theory based on analysis results. The proposed method is applied Landsat TM image data, from this, we verify the equivalence of traditional bands selection method by band features and bands selection method using Rough sets theory that pmposed in this paper. Finally, we present theoretical basis to features extraction in hyperspectral environment.