• Journal of Energy Engineering
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• v.18 no.3
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• pp.175-190
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• 2009

This study examines the influence of scale economy, technology, financing capability and market competition on economic performance by value chain in Korean solar energy companies, using the multiple logistic regression analysis. The current profit ratio is analyzed to have been positively affected by financing capability, while negatively by market competition. The scale economy and technology are analyzed to have no statistical significance on the economic performance. The current profit ratio for companies creating higher value in the sourcing process is negatively affected by technology while positively by financial capability. The one in the manufacturing process is affected positively by technology and financing capability, and the one in the marketing process is affected positively by financing capability while negatively by market competition. The implications of this study are as follows: Korean solar energy industry is recommended i) to establish the specific innovation system for technology development, ii) to set up advanced financial system, iii) to carry out the fractal system, the manufacturing system through the network of the firms owning core competence per value chain.

• Journal of Korea Multimedia Society
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• v.4 no.6
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• pp.518-523
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• 2001

This paper proposes the new method which is adopted in extracting character features and recognizing characters using fractal dimension of the Chaos theory which highly recolonizes a minute difference with strange attractor created from Henon system. This paper implements a high precision character recognition system. firstly, it gets features of mesh, projection and cross distance feature from character images. And their feature is converted into data of time series. Then using modified Henon system suggested in this paper, each characters attractor about standard Korean Character, KSC 5601 is reconstructed. Secondly, in order to analyze the Chaotic degree of each characters attractor, it gets last features of character image after calculating box-counting Dimension, Natural Measure, Information Bit, Information Dimension which are meant fractal dimension. An experimental result shows 97.49% character classification rates for 2350 Korean characters using proposed method in this paper.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.84-93
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• 2000

The conventional fractal decoding was implemented to IFS(iterated function system) for every range regions But a part of the range regions can be decoded without the iteration and there is a data dependence regions In order to decode $R{\times}R$ range blocks, It needs $2R{\times}2R$ domain blocks This decoding can be analyzed to the dependence graph The vertex of the graph represents the range blocks, and the vertex is classified into the vertex of the range and domain The edge indicates that the vertex is referred to the other vertices The in-degree and the out-degree are defined to the number of the edge that is entered and exited, respectively The proposed method is analyzed by a dependence graph to the fractal code, and the decoding order is recomposed by the information of the out-degree That is, If the out-degree of the vertex is zero, then this vertex can be used to the vertex with data dependence Thus, the proposed method can extend the data dependence regions by the recomposition of the decoding order As a result, the Iterated regions are minimized without loss of the image quality or PSNR(peak signal-to-noise ratio), Therefore, it can be a fast decoding by the reducing to the computational complexity for IFS in the fractal Image decoding.

• Proceedings of the KAIS Fall Conference
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• 2002.05a
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• pp.115-117
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• 2002

In this paper, the degree-n bifurcation set as well as the Julia sets is defined by extending the concept of the Mandelbrot set to the complex polynomial $z^{n}{\;}+{\;}c(c{\;}\in{\;}C,{\;}n{\;}\geq{\;}2)$. Some properties of the degree-n bifurcation set and the Julia sets have been theoretically investigated including the symmetry, periodicity, boundedness, connectedness and the bifurcation points as well as the governing equation for the component centers. An efficient algorithm constructing both the degree-n bifurcation set and the Julia sets is proposed using theoretical results. The mouse-operated software calico "MANJUL" has been developed for the effective construction of the degree-n bifurcation set and the Julia sets in graphic environments with C++ programming language under the windows operating system. Simple mouse operations can construct and magnify the degree-n bifurcation set as well as the Julia sets. They not only compute the component period, bifurcation points and component centers but also save the images of the degree-n bifurcation set and the Julia sets to visually confirm various properties and the geometrical structure of the sets. A demonstration has verified the useful versatility of MANJUL.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.1205-1210
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• 2005

The behavior of rock mass and solute(e.g. groundwater, radioactivity) flow in fractured rock can be directly influenced by joint roughness. The characteristics of joint roughness is also a main factor for the rock classification(e.g. RMR, Q system) which is usually used in tunnel design. Nevertheless, most of JRC estimation has been carried out only by the examination with the naked eye. This JRC estimation has a lack of objectivity because each investigator judges JRC by his subjective opinion. Therefore, it will be desirable that the assessment of JRC is performed by a numerical analysis which can give a quantitative value corresponding to the characteristics of a roughness curve. Meanwhile, roughness curves for joint surfaces which are observed in drill cores have been obtained only along linear profiles. Although roughness curves are measured in the same joint surface, they can frequently show diverse aspects in a standpoint of roughness characteristics. If roughness curves can be measured along the elliptical circumferences of joint surfaces from core scanning images or Televiewer images, they will certainly be more comprehensive than those measured along linear profiles for roughness characteristics of joint surfaces. This study is focus on dealing with (1) extracting automatically roughness curves from core scan image or Televiewer image, (2) improving the accuracy of quantitative assessment of JRC using fractal dimension concept.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.167-174
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• 1998

The ultrasonic test is recognized for its significance as a non-destructive testing method to detect volume defects such as porosity and incomplete penetration which reduce strength in the weld zone. This paper illustrates the defect detection in the weld zone of ferritic carbon steel using ultrasonic wave and the evaluation of pattern recognition by chaotic feature extraction using time series signal of detected defects as data. Shown in the time series data were that the time delay was 4 and the embedding dimension was 6 which indicate the geometric dimension of the subject system and the extent of information correlation. Based on fractal dimension and lyapunov exponent in quantitative chaotic feature extraction, feature value of 2.15, 0.47 is presented for porosity and 2.24, 0.51 for incomplete penetration The precision rate of the pattern recognition is enhanced with these values on the total waveform of defect signal in the weld zone. Therefore, we think that the ultrasonic pattern recognition method of weld zone defects of ferritic carbon steel by ultrasonic-chaotic feature extraction proposed in this paper can boost precision rate further than the existing method applying only partial waveform.

• KIEE International Transactions on Electrophysics and Applications
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• v.11C no.2
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• pp.6-11
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• 2001

Abstract- In this paper, a new Partial Discharge (PD) detection using Pockels cell was proposed and considerable apparent chaotic characteristics were discussed. For this purpose, PD was generated from needle-plane electrode in air and detecte by optical measuring system using Pockels cell, based on Mach-Zehner interferometer, consisting of He-Ne laser, single mode optical fiber, 50/50 beam splitter and photo detector. In addition, the presence of chaos of the PD signals has been investigated by examining their means of qualitative and quantitative information. For the former, return map and 3-dimensional strange attractor have been drawn in order to investigate the presence of chaotic characteristics relevant to PD signals, detected through CT and Peckels sensor respectively, in the normalized time series. The presence of strange attractor indicates the existence of fractal structures in it's phase space. For the latter, several dimension values of strange attractor were verified sequentially. Throughout this paper, it is likely that the chaotic characteristics regarding the PD signals under air are verified.

• Smart Structures and Systems
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• v.33 no.3
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• pp.227-241
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• 2024

Safety and structural integrity of civil structures, like bridges and buildings, can be substantially enhanced by employing appropriate structural health monitoring (SHM) techniques for timely diagnosis of incipient damages. The information gathered from health monitoring of important infrastructure helps in making informed decisions on their maintenance. This ensures smooth, uninterrupted operation of the civil infrastructure and also cuts down the overall maintenance cost. With an early warning system, SHM can protect human life during major structural failures. A real-time online damage localization technique is proposed using only the vibration measurements in this paper. The concept of the 'Degree of Scatter' (DoS) of the vibration measurements is used to generate a spatial profile, and fractal dimension theory is used for damage detection and localization in the proposed two-phase algorithm. Further, it ensures robustness against environmental and operational variability (EoV). The proposed method works only with output-only responses and does not require correlated finite element models. Investigations are carried out to test the presented algorithm, using the synthetic data generated from a simply supported beam, a 25-storey shear building model, and also experimental data obtained from the lab-level experiments on a steel I-beam and a ten-storey framed structure. The investigations suggest that the proposed damage localization algorithm is capable of isolating the influence of the confounding factors associated with EoV while detecting and localizing damage even with noisy measurements.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.5
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• pp.61-71
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• 1998

Genetic Algorithm(GA) is a method of approaching optimization problems by modeling and simulating the biological evolution. GA needs large time-consuming, so ti had better do on a parallel computer architecture. Our proposed system has a VLSI-oriented interconnection network, which is constructed from a viewpoint of fractal geometry, so that self-similarity is considered in its configuration. The approach to Parallel Genetic Algorithm(PGA) on our proposed system is explained, and then, we construct the classifier system such that the set of samples is classified into weveral classes based on the features of each sample. In the process of designing the classifier system, We have applied PGA to the Traveling Salesman Problem and classified the sample set in the Euclidean space into several categories with a measure of the distance.

• Electrical & Electronic Materials
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• v.11 no.11
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• pp.1-8
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• 1998

This paper presents an arificial neuro-fuzzy technique based prtial discharge (PD) pattern classifier to power system application. This may require a complicated analysis method employ -ing an experts system due to very complex progressing discharge form under exter-nal stress. After referring briefly to the developments of artificical neural network based PD measurements, the paper outlines how the introduction of new emerging technology has resulted in the design of a number of PD diagnostic systems for practical applicaton of residual lifetime prediction. The appropriate PD data base structure and selection of learning data size of PD pattern based on fractal dimentsional and 3-D PD-normalization, extraction of relevant characteristic fea-ture of PD recognition are discussed. Some practical aspects encountered with unknown stress in the neuro-fuzzy techniques based real time PD recognition are also addressed.