• 지능정보연구
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• 제4권1호
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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.

• 한국조경학회지
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• 제41권5호
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• pp.57-67
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• 2013

지금까지 별서정원과 관련된 연구들은 고문서 및 현장조사를 통한 통시적인 접근을 많이 해왔다. 전통조경공간의 상징성, 입지 특성 등 그 공간에 내재된 특성에 초점을 둔 연구들이 많았다. 하지만, 입지 특성 중 내원, 외원, 영향권에 대한 특성은 많았으나, 외원 규모에 대한 정량적 연구는 미진하였다. 사생활권역인 내원과 달리 공동생활권역으로서의 역할인 외원에 대하여 정량적인 분석을 하기 위해 서석지원를 대상으로 실시하였다. 서석지원를 대상으로 기존 문헌들과 GIS 프로그램을 통해 가시권 분석을 실시하였으며, 외원 규모를 추정하였다. 선행연구와 일부 차이가 있었지만, 부용봉과 입암 중심으로 확인해본 결과, 거의 유사한 면적으로 나타났다. 또한, 추정된 외원 규모를 통해 서석지원의 다양한 상징성에 대한 프랙탈 차원을 분석해본 결과, 주요 경관요소에서 프랙탈 차원이 상대적으로 집중화되는 경향을 알 수 있었다. 특히, 주요 경관요소는 청기천을 제외하고, 일반 자연경관(논, 밭 등)에 비해 상대적으로 높은 수치 및 넓은 범위의 프랙탈 차원을 가지고 있었다. 이를 통해 외원규모가 그동안 별서정원의 형태 중 내원에 대한 문화재 보호에서 벗어나, 외원에 대한 문화재 보호수단을 위한 기초자료로 활용될 수 있을 것으로 기대한다. 또한, 이번 연구가 경관분석 요소 중 하나로서 프랙탈 구조 개념을 도입하여 주요 경관요소에 대한 시각적 복잡성에 대해 고려하였지만, 각 경관요소에 대하여 시문학과 더불어 좀 더 융합적인 사고의 결과물에 대한 연구가 필요할 것으로 기대한다.

• 방송공학회논문지
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• 제4권1호
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• pp.76-85
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• 1999

프랙탈 부호화 방식에서의 블록 손실 효과는 DCT 기반 블록 부호화 방식에서와는 달리 손실 블록의 참조에 의한 에러 전파 효과 때문에 보다 심각한 화질 저하를 초래한다. 따라서 본 논문에서는 Jacquin 방법에 의해 프랙탈 부호화된 영상을 ATM 망과 같은 손실망을 통해 전송할 경우 발생할 수 있는 블록 손실을 복구하는 방법을 제안한다. Jacquin 의 프랙탈 부호화 체계는 중요도에 따라 머리부호와 본체 부호의 2계층 부호화 체계로 구성된다. 제안된 블록 손실 복구 알고리듬의 핵심 기법은 블록 특성이 손실 블록과 유사한 인접 치역 블록들의 축소 사상 파라미터들을 사용하여 손실 화소들을 추정하는 츠랙탈 외삽이며, 이는 복호화 과정에서 반복적으로 손실 블록들에 적용된다. 실험을 통하여, 제안된 복구 알고리듬이 주관적 화질 뿐만 아니라 PSNR 에서도 우수한 성능을 갖고 있음을 보인다.

• 디지털콘텐츠학회 논문지
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• 제5권3호
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• pp.199-204
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• 2004

저비트율에서도 우수한 화질을 제공하는 프랙탈 영상 압축 기법들이 갖고 있는 하나의 문제점은 복호화가 반복 처리를 통해 구현되며 그 복잡도가 각각의 영상에 따라 상이하다는 것이다. 이러한 문제를 해소하기 위해 본 논문은 복호 시간을 단축시키기 위해 반복 변환이 필요 없는 프랙탈 영상 복호 알고리즘을 제안하고 그 성능을 분석함에 그 목적이 있다. 제안된 프랙탈 복호 알고리즘은 복호기에서 사용할 초기 영상과 동일한 코드북 영상을 부호기에 보유하고 있는 상태에서 부호화 과정에서는 이 코드북 영상과 부호화하려는 영상의 유사성을 찾아 프랙탈 계수를 구한다. 이후, 수신단의 복호화 과정에서는 수신된 프랙탈 계수와 기설정된 초기 영상을 이용하여 반복 변환 없이 한 번에 영상을 복호함으로써 반복 변환 횟수의 역수배만큼 복호 소요 시간을 현저하게 단축시킬 수 있었다. 제안된 방법의 타당성과 보편성을 검증하기 위해 서로 다른 분포 특성을 갖는 복수의 정지 영상과 동영상을 대상으로 복호 소요 시간과 화질 측면에서 그 성능을 평가$\cdot$분석하였다.

• 한국정밀공학회지
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• 제20권1호
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• pp.63-69
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• 2003

This study proposes the construction of attractor simulator for cutting characteristics evaluation of non-ferrous metals. Also this paper aims to find the optimal cutting conditions of diamond turning machine by measuring surface form and roughness to perform the cutting experiment of non-ferrous metals, which are aluminum, with diamond tool. As well, according to change cutting conditions such as feed rate, cutting force and surface roughness are measured by tool dynamometer. Trajectory changes in the attractor indicated a substantial difference in fractal characteristics. Constructed attractor in this study can be used for cutting characteristics evaluation of non-ferrous metals

• 한국안전학회지
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• 제18권3호
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• pp.22-28
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• 2003

This study proposes the construction of chaos simulator for cutting characteristics evaluation of non-ferrous metals. Also this paper aims to find the optimal cutting conditions of diamond turning machine by measuring surface form and roughness to perform the cutting experiment of non-ferrous metals, which are aluminum, with diamond tool. As well, according to change cutting conditions such as fled rate, using diamond turning machine to perform cutting processing, by measuring cutting force and surface roughness and according to cutting conditions the aluminum about cutting properties. Trajectory changes in the attractor indicated a substantial difference in fractal characteristics. Constructed chaos simulator in this study can be used for cutting characteristics evaluation of non-ferrous metals.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.624-627
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• 2003

To achieve accurate and efficient extraction of the fractal feature, a progressive extraction method is developed. After establishing the boundaries of the targeted surface by enclosing it with internal and external covers, it determines the features of the surface by calculating the characteristics of such covers.

• 한국물환경학회지
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• 제21권5호
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• pp.500-504
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• 2005

Water samples were collected at 7 sites located along the River Nakdong on 30 occasions. Water qualities, size and fractal dimension ($d_F$) of suspended particles were measured. Laser light scattering method was used to obtain the size and $d_F$ of suspended particles. The average size of particles in this river ranged from $89{\mu}m$ and $169{\mu}m$, which appears to be relatively coarse compared with other rivers worldwide. The average $d_F$ of suspended particles in this study ranged from 1.8 to 1.9. The correlation analysis showed that DO, TN, $NO_3$ and chlorophyll-${\alpha}$ had significant positive relationships with particles size, whereas flow rates and TSS had negative relationships. Interestingly, the factors of which had positive relationships with particles size showed negative relationship with the fractal dimension ($d_F$) of suspended particles. Generally, as the size of particles increased, the fractal dimension of particles decreased which was indicating the shape of the larger particles became more irregular.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권12호
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• pp.5955-5977
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• 2018

Performance of the interpolation algorithm used in the technique of bi-dimensional empirical mode decomposition directly affects its popularization and application, so that the researchers pay more attention to the algorithm reasonable, accurate and fast. However, it has been a lack of an adaptive interpolation algorithm that is relatively satisfactory for the bi-dimensional empirical mode decomposition (BEMD) and is derived from the image characteristics. In view of this, this paper proposes an image interpolation algorithm based on the particle swarm and fractal. Its procedure includes: to analyze the given image by using the fractal brown function, to pick up the feature quantity from the image, and then to operate the adaptive image interpolation in terms of the obtained feature quantity. All parameters involved in the interpolation process are determined by using the particle swarm optimization algorithm. The presented interpolation algorithm can solve those problems of low efficiency and poor precision in the interpolation operation of bi-dimensional empirical mode decomposition and can also result in accurate and reliable bi-dimensional intrinsic modal functions with higher speed in the decomposition of the image. It lays the foundation for the further popularization and application of the bi-dimensional empirical mode decomposition algorithm.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.69-78
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• 2023

With the global rise of digital data, the uncontrolled quantity of data is susceptible to cyber warfare or cyber attacks. Therefore, it is necessary to improve cyber security systems. This research studies the behavior of malicious acts and uses Higuchi Fractal Dimension (HFD), which is a non-linear mathematical method to examine the intricacy of the behavior of these malicious acts and anomalies within the cyber physical system. The HFD algorithm was tested successfully using synthetic time series network data and validated on real-time network data, producing accurate results. It was found that the highest fractal dimension value was computed from the DoS attack time series data. Furthermore, the difference in the HFD values between the DoS attack data and the normal traffic data was the highest. The malicious network data and the non-malicious network data were successfully classified using the Receiver Operating Characteristics (ROC) method in conjunction with a scaling stationary index that helps to boost the ROC technique in classifying normal and malicious traffic. Hence, the suggested methodology may be utilized to rapidly detect the existence of abnormalities in traffic with the aim of further using other methods of cyber-attack detection.