• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.4
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• pp.112-123
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• 2015

The purpose of this study is to analyze the biotope characteristics of Korean cities and set up biotope type structures for Korean cities based on biotope type classification, dominant biotope type, city's human and nature environmental characteristics and cluster analysis. The findings of the study are summarized as follows: First, regarding the analysis of biotope type classification, cities showed differences in terms of the standard of biotope classification and classification hierarchy. Next, the analysis of dominant biotope types showed the type of forest represents the largest area in most cities. Moreover, a city's characteristic analysis revealed large differences between cities. As a result of cluster analysis, cities were classified into five clusters overall. First, Cluster A showed a lower population level and urbanization level. Unlike other cities, Cluster A revealed that it has the largest percentage of agricultural areas. Cluster C showed very high levels in terms of population amount and urbanization conditions was named the 'Large-sized metropolitan cities-center of forest biotope area' based on it's characteristics. The findings of this study as summarized above are considered to play an important role in enabling detailed classification and preservation of biotope types fit for the characteristics of cities and minimizing the confusion caused by different biotope mapping methods when revising and complementing biotope maps.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.527-531
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• 2012

In this paper, a novel DPSO-QI (Distributed PSO with quantum-infusion mechanism) algorithm improving one of the fatal defect, the so-called premature convergence, that degrades the performance of the conventional PSO algorithms is proposed. The proposed scheme has the following two distinguished features. First, a concept of neighborhood of each particle is introduced, which divides the whole swarm into several small groups with an appropriate size. Such a strategy restricts the information exchange between particles to be done only in each small group. It thus results in the improvement of particles' diversity and further minimization of a probability of occurring the premature convergence phenomena. Second, a quantum-infusion (QI) mechanism based on the quantum mechanics is introduced to generate a meaningful offspring in each small group. This offspring in our PSO mechanism improves the ability to explore a wider area precisely compared to the conventional one, so that the degree of precision of the algorithm is improved. Finally, some numerical results are compared with those of the conventional researches, which clearly demonstrates the effectiveness and reliability of the proposed DPSO-QI algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.77-88
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• 2018

This paper proposes a RBFNN(Radial Basis Function Neural Network) based decentralized adaptive tracking control scheme using PSO(Particle Swarm Optimization) for an uncertain electrically driven robot system with input saturation. Practically, the magnitudes of input voltage and current signals are limited due to the saturation of actuators in robot systems. The proposed controller overcomes this input saturation and does not require any robot link and actuator model parameters. The fitness function used in the presented PSO scheme is expressed as a multi-objective function including the magnitudes of voltages and currents as well as the tracking errors. Using a PSO scheme, the control gains and the number of the RBFs are tuned automatically and thus the performance of the control system is improved. The stability of the total control system is guaranteed by the Lyapunov stability analysis. The validity and robustness of the proposed control scheme are verified through simulation results.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.586-591
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• 2014

In this study, we introduce Radial Basis Function Neural Networks(RBFNNs) classifier using Artificial Bee Colony(ABC) algorithm in order to classify between precipitation event and non-precipitation event from given radar data. Input information data is rebuilt up through feature analysis of meteorological radar data used in Korea Meteorological Administration. In the condition phase of the proposed classifier, the values of fitness are obtained by using Fuzzy C-Mean clustering method, and the coefficients of polynomial function used in the conclusion phase are estimated by least square method. In the aggregation phase, the final output is obtained by using fuzzy inference method. The performance results of the proposed classifier are compared and analyzed by considering both QC(Quality control) data and CZ(corrected reflectivity) data being used in Korea Meteorological Administration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.456-463
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• 2021

In this paper, Ultra Wide-Band(UWB) radar sensor is employed to detect flying drones and avoid collision in dense clutter environments. UWB signal is preferred when high resolution range measurement is required for moving targets. However, the time varying motion of flying drones may increase clutter noises in return signals and deteriorates the target detection performance, which lead to the performance degradation of anti-collision radars. We adopt a dynamic clutter suppression algorithm to estimate the time-varying distances to the moving drones with enhanced accuracy. A modified Constant False Alarm Rate(CFAR) is developed using an adaptive filter algorithm to suppress clutter while the false detection performance is well maintained. For this purpose, a velocity dependent CFAR algorithm is implemented to eliminate the clutter noise against dynamic target motions. Experiments are performed against flying drones having arbitrary trajectories to verify the performance improvement.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.4
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• pp.574-584
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• 1997

Benthic marine algae of Shinjido located on the southern coast of Korea have been investigated to know the floristic composition and community structure. The study was conducted from the intertidal to subtidal zones at two different locations (Kangdok and Donggori) using a line transect method from January to October, 1994. A total of 120 species of marine algae were identified, and they includes 15 green algae, 31 brown algae and 74 red algae. Of these, 87 and 104 species of marine algae occurred at Kangdok and Donggori, respectively. Algal vegetations were divided into three different zonations: the upper, the middle and the lower zones. The representative species are Enteromorpha compressa, Ulva pertusa, Porphyra suborbiculata, lshige okamurae in the upper zone; Hizikia fusiformis, Sargassum thunbergii, Gigatina intermedia, Corallina pilulifera in the middle zone; Pachymeniopsis elliptica, Gelidium amansii, Sargassum horneri in the lower zone. In terms of biomass the dominant species were U. pertusa, I. okamurae, H. fusiformis, C. thunbergii, C. pilulifera, C. amansii, C. tenella. The flora could be classified into six functional form groups such as the coarsely branched form $(36.7\%)$ the filamentous form $(27.5\%)$, the sheet form $(15.8\%)$, the thick leathery form $(10.0\%)$, the jointed calcarious form $(5.0\%)$ and the crustose form $(5.0\%)$.

• Korean Journal of Microbiology
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• v.37 no.4
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• pp.265-272
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• 2001

The diversity of acid-tolerant epiphytic bacterial communities on deciduous oak tree (Quercus dentate Thunb.) leaves was examined both in the natural forest area with a clean air and in the industrial estate to assess effects of acidic depositions to the phyllosphere using 16S rDNA sequence data. A total of 444 acid-tolerant epiphytic bacterial clones were obtained, resulting in 17 phylotypes by performing a analysis of restriction fragment length polymorphism (RFLP) for PCR-amplified 16S rDNA products. A very low diversity of dominating acid tolerant bacterial communities in both areas was found, just 2 subphyla groups, $\gamma$-Proteobacteria and low-G+C gram-positive bacteria. As tree leaves grow older, diversities of acid-tolerant bacteria on them significantly increased. The community structure of acid-tolerant epiphytic bacteria consisted of Pseudomonas and Enterobacteriaceae groups in the $\gamma$-Proteobacteria subphylum, and Streptococcaceae and Staphylococcus groups in the low-G+C gram-positive bacteria subphylum. The direct influence of acidic depositions on bacterial phylogenetic composition could not be detected especially when higher taxonomic levels such as subphylum, but at narrower or finer levels it could be observed by a detection of Xanthomonadales group belonged to the $\gamma$-Proteobacteria only in the industrial area and of Acetobacteraceae group belonged to the $\alpha$-Proteobacteria. There remains that these specific acid-tolerant epiphytic bacterial groups could be used as indicators for assessing effects of acidic depositions on the phyllosphere.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1349-1365
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• 2020

In recent years, in the fields of smart cities and digital twins, research on model generation is increasing due to the advantage of acquiring actual 3D coordinates by using point clouds. In addition, there is an increasing demand for a solid model that can easily modify the shape and texture of the building. In this paper, we propose a method to create a clustered solid building model based on point cloud data. The proposed method consists of five steps. Accordingly, in this paper, we propose a method to create a clustered solid building model based on point cloud data. The proposed method consists of five steps. In the first step, the ground points were removed through the planarity analysis of the point cloud. In the second step, building area was extracted from the ground removed point cloud. In the third step, detailed structural area of the buildings was extracted. In the fourth step, the shape of 3D building models with 3D coordinate information added to the extracted area was created. In the last step, a 3D building solid model was created by giving texture to the building model shape. In order to verify the proposed method, we experimented using point clouds extracted from unmanned aerial vehicle images using commercial software. As a result, 3D building shapes with a position error of about 1m compared to the point cloud was created for all buildings with a certain height or higher. In addition, it was confirmed that 3D models on which texturing was performed having a resolution of less than twice the resolution of the original image was generated.

• Korean Journal of Ecology and Environment
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• v.51 no.4
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• pp.287-298
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• 2018

The zooplankton community and environmental factor were investigated on a weekly basis from March to November 2015 in Lake Paldang, Korea. The seasonal succession of zooplankton community structure was influenced by hydraulic and hydrological factors such as inflow, outflow and rainfall. However, the hydraulic retention time in 2015 (16.3 day) was affected by the periods of water shortage that had continued since 2014 and increased substantially compared to 2013 (7.3 day). Therefore, the inflow and outflow discharge were decreased, and the water quality (COD, BOD, TOC, TP, Chl-a) of Lake Paldang (St.1) was the same characteristics as the river type Bukhan river (St.3), compared with the lake type Namhan river (St.2) and Gyeongan stream (St.4). Zooplankton community dominated by rotifers (Keratella cochlearis, Synchaeta oblonga) in spring (March to May). However, Copepod (Nauplius) and Cladoceran (Bosmina longirostris) dominated in St.4. In summer (June to August), there was a few strong rainfall event and the highest number of individuals dominated by Keratella cochlearis (Rotifera) and Difflugia corona (Protozoa) were shown during the study period. In autumn (October to November), the water temperature was decreased with decrease in the total number of individuals showing Nauplius (Copepoda) as the dominant species. As a result of the statistical analysis about zooplankton variation in environmental factors, the continuous periods of water shortage increased the hydraulic retention time and showed different characteristic for each site. St.1, St.3 and St.2, St.4 are shown in the same group (p<0.05), showing the each characteristics of river type and lake type. Therefore, the water quality of catchment area and distribution of zooplankton community would be attributed to hydraulic and hydrological factors.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.23-27
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• 2002

본 논문에서는 정보보호에서 지능형 침입탐지시스템(Intrusion Detection System :IDS) 의한 모델을 제안한다. 이 모델은 데이터 마이닝 분야와 정보보호 분야의 결합된 방법을 이용한다. 즉, 계산환경을 격상하거나 새로운 공격 방법들 때문에 내장된 IDS를 보완 할 필요가 종종 있다. 현재 사용하고 있는 많은 IDS들은 전문적인 지식을 손으로 작성했기 때문에 IDS들의 변환은 가격이 매우 비싸며, 속도가 느리다는 단점이 있다. 이에 본 모델은 침입탐지 모델을 적응 적으로 구축하는데 데이터 마이닝 구조를 활용한다. 데이터 마이닝(Data Mining : DM)의 기술인 연관 규칙, 순차 패턴, 분류, 군집화, 유전자 알고리즘 기법(GA)인 Selection, Crossover, Mutation, Evaluation, Fitness Function의 기능을 접목하여 단점을 보안하고 처리 성능을 최대로 하는 즉, 보다 안전한 지능형 침입 탐지 시스템(IDS) 모델을 제안한다.