• Title/Summary/Keyword: 다변수 시스템

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Classification of Very High Concerns HRCT Images using Extended Bayesian Networks (확장 베이지안망을 적용한 고위험성 HRCT 영상 분류)

  • Lim, Chae-Gyun;Jung, Yong-Gyu
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.49 no.2
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    • pp.7-12
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    • 2012
  • Recently the medical field to efficiently process the vast amounts of information to decision trees, neural networks, Bayesian Networks, including the application method of various data mining techniques are investigated. In addition, the basic personal information or patient history, family history, in addition to information such as MRI, HRCT images and additional information to collect and leverage in the diagnosis of disease, improved diagnostic accuracy is to promote a common status. But in real world situations that affect the results much because of the variable exists for a particular data mining techniques to obtain information through the enemy can be seen fairly limited. Medical images were taken as well as a minor can not give a positive impact on the diagnosis, but the proportion increased subjective judgments by the automated system is to deal with difficult issues. As a result of a complex reality, the situation is more advantageous to deal with the relative probability of the multivariate model based on Bayesian network, or TAN in the K2 search algorithm improves due to expansion model has been proposed. At this point, depending on the type of search algorithm applied significantly influenced the performance characteristics of the extended Bayesian network, the performance and suitability of each technique for evaluation of the facts is required. In this paper, we extend the Bayesian network for diagnosis of diseases using the same data were carried out, K2, TAN and changes in search algorithms such as classification accuracy was measured. In the 10-fold cross-validation experiment was performed to compare the performance evaluation based on the analysis and the onset of high-risk classification for patients with HRCT images could be possible to identify high-risk data.

인공신경망을 이용한 부실기업예측모형 개발에 관한 연구

  • Jung, Yoon;Hwang, Seok-Hae
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 1999.03a
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    • pp.415-421
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    • 1999
  • Altman의 연구(1965, 1977)나 Beaver의 연구(1986)와 같은 전통적 예측모형은 분석자의 판단에 따른 예측도가 높은 재무비율을 선정하여 다변량판별분석(MDA:multiple discriminant analysis), 로지스틱회귀분석 등과 같은 통계기법을 주로 이용해 왔으나 1980년 후반부터 인공지능 기법인 귀납적 학습방법, 인공신경망모형, 유전모형 등이 부실기업예측에 응용되기 시작했다. 최근 연구에서는 인공신경망을 활용한 변수 및 모형개발에 관한 보고가 있다. 그러나 지금까지의 연구가 주로 기업의 재무적 비율지표를 고려한 모형에 치중되었으며 정성적 자료인 비재무지표에 대한 검증과 선정이 자의적으로 이루어져온 경향이었다. 또한 너무 많은 입력변수를 사용할 경우 다중공선성 문제를 유발시킬 위험을 내포하고 있다. 본 연구에서는 부실기업예측모형을 수립하기 위하여 정량적 요인인 재무적 지표변수와 정성적 요인인 비재무적 지표변수를 모두 고려하였다. 재무적 지표변수는 상관분석 및 요인분석들을 통하여 유의한 변수들을 도출하였으며 비재무적 지표변수는 조직생태학내에서의 조직군내 조직사멸과 관련된 생태적 과정에 대한 요인들 중 조직군 내적요인으로 조직의 연령, 조직의 규모, 조직의 산업밀도를 도출하여 4개의 실험집단으로 분류하여 비재무적 지표변수를 보완하였다. 인공신경망은 다층퍼셉트론(multi-layer perceptrons)과 역방향 학습(back-propagation)알고리듬으로 입력변수와 출력변수, 그리고 하나의 은닉층을 가지는 3층 퍼셉트론(three layer perceptron)을 사용하였으며 은닉층의 노드(node)수는 3개를 사용하였다. 입력변수로 안정성, 활동성, 수익성, 성장성을 나타내는 재무적 지표변수와 조직규모, 조직연령, 그 조직이 속한 산업의 밀도를 비재무적 지표변수로 산정하여 로지스틱회귀 분석과 인공신경망 기법으로 검증하였다. 로지스틱회귀분석 결과에서는 재무적 지표변수 모형의 전체적 예측적중률이 87.50%인 반면에 재무/비재무적 지표모형은 90.18%로서 비재무적 지표변수 사용에 대한 개선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.

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Analysis of Fish Ecology and Water Quality for Health Assessments of Geum - River Watershed (금강본류의 건강성 평가를 위한 어류생태 및 수질 특성분석)

  • Park, Yun-Jeong;Lee, Sang-Jae;An, Kwang Guk
    • Korean Journal of Environment and Ecology
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    • v.33 no.2
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    • pp.187-201
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    • 2019
  • This study examined the physicochemical water quality and evaluated the ecological health in 14 sites of Geum River (upstream, mid-stream, and downstream) using the fish community distribution and guilds and eight multi-variable matrices of FAI (Fish Assessment Index) during June 2008-May 2009. The analysis of the water quality variables showed no significant variation in the upstream and mid-stream but a sharp variation due to the accumulation of organic matter from the point where the treated water of Gap and Miho streams flew. The analysis of physicochemical water properties showed that BOD, COD, TN, TP, Cond, and Chl-a tended to increase while DO decreased to cause eutrophication and algae development from the downstream where Miho and Gap stream merged. The analysis of fish community showed that the species richness index and species diversity index increased in the mid-stream area but decreased in the downstream area, indicating the stable ecosystem in the upper stream and the relatively unstable ecosystem in the downstream. The analysis of the species distribution showed that the dominant species were Zacco platypus that accounted for 20.9% of all fish species and Zacco koreanus that accounted for 13.1%. The analysis of the fish tolerance and feeding guild characteristics showed that the sensitive species, the insectivore species, and the aquatic species were dominant in the mid-stream point. On the other hand, contaminants from the sewage water treatment plant of Miho stream had a profound effect in the downstream to show the dominance of tolerant species, omnivorous species, and lentic species. Therefore, it is necessary to improve water quality by reducing the load of urban pollutants and to pay attention to the conservation and restoration of aquatic ecosystems.

A Comparative Study on Data Augmentation Using Generative Models for Robust Solar Irradiance Prediction

  • Jinyeong Oh;Jimin Lee;Daesungjin Kim;Bo-Young Kim;Jihoon Moon
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.11
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    • pp.29-42
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    • 2023
  • In this paper, we propose a method to enhance the prediction accuracy of solar irradiance for three major South Korean cities: Seoul, Busan, and Incheon. Our method entails the development of five generative models-vanilla GAN, CTGAN, Copula GAN, WGANGP, and TVAE-to generate independent variables that mimic the patterns of existing training data. To mitigate the bias in model training, we derive values for the dependent variables using random forests and deep neural networks, enriching the training datasets. These datasets are integrated with existing data to form comprehensive solar irradiance prediction models. The experimentation revealed that the augmented datasets led to significantly improved model performance compared to those trained solely on the original data. Specifically, CTGAN showed outstanding results due to its sophisticated mechanism for handling the intricacies of multivariate data relationships, ensuring that the generated data are diverse and closely aligned with the real-world variability of solar irradiance. The proposed method is expected to address the issue of data scarcity by augmenting the training data with high-quality synthetic data, thereby contributing to the operation of solar power systems for sustainable development.

Application of SP Monitoring in the Pohang Geothermal Field (포항 지열 개발지역에서의 SP 장기 관측)

  • Lim Seong Keun;Lee Tae Jong;Song Yoonho;Song Sung-Ho;Yasukawa Kasumi;Cho Byong Wook;Song Young Soo
    • Geophysics and Geophysical Exploration
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    • v.7 no.3
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    • pp.164-173
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    • 2004
  • To delineate geothermal water movement at the Pohang geothermal development site, Self-Potential (SP) survey and monitoring were carried out during pumping tests. Before drilling, background SP data have been gathered to figure out overall potential distribution of the site. The pumping test was performed in two separate periods: 24 hours in December 2003 and 72 hours in March 2004. SP monitoring started several days before the pumping tests with a 128-channel automatic recording system. The background SP survey showed a clear positive anomaly at the northern part of the boreholes, which may be interpreted as an up-flow Bone of the deep geothermal water due to electrokinetic potential generated by hydrothermal circulation. The first and second SP monitoring during the pumping tests performed to figure out the fluid flow in the geothermal reservoir but it was not easy to see clear variations of SP due to pumping and pumping stop. Since the area is covered by some 360 m-thick tertiary sediments with very low electrical resistivity (less than 10 ohm-m), the electrokinetic potential due to deep groundwater flow resulted in being seriously attenuated on the surface. However, when we compared the variation of SP with that of groundwater level and temperature of pumping water, we could identify some areas responsible to the pumping. Dominant SP changes are observed in the south-west part of the boreholes during both the preliminary and long-term pumping periods, where 3-D magnetotelluric survey showed low-resistivity anomaly at the depth of $600m\~1,000m$. Overall analysis suggests that there exist hydraulic connection through the southwestern part to the pumping well.

Analysis Method for Full-length LiDAR Waveforms (라이다 파장 분석 방법론에 대한 연구)

  • Jung, Myung-Hee;Yun, Eui-Jung;Kim, Cheon-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.44 no.4 s.316
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    • pp.28-35
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    • 2007
  • Airbone laser altimeters have been utilized for 3D topographic mapping of the earth, moon, and planets with high resolution and accuracy, which is a rapidly growing remote sensing technique that measures the round-trip time emitted laser pulse to determine the topography. The traveling time from the laser scanner to the Earth's surface and back is directly related to the distance of the sensor to the ground. When there are several objects within the travel path of the laser pulse, the reflected laser pluses are distorted by surface variation within the footprint, generating multiple echoes because each target transforms the emitted pulse. The shapes of the received waveforms also contain important information about surface roughness, slope and reflectivity. Waveform processing algorithms parameterize and model the return signal resulting from the interaction of the transmitted laser pulse with the surface. Each of the multiple targets within the footprint can be identified. Assuming each response is gaussian, returns are modeled as a mixture gaussian distribution. Then, the parameters of the model are estimated by LMS Method or EM algorithm However, each response actually shows the skewness in the right side with the slowly decaying tail. For the application to require more accurate analysis, the tail information is to be quantified by an approach to decompose the tail. One method to handle with this problem is proposed in this study.

A Study on the Analysis of R&D Trends and the Development Plan of Electronic Attack System (전자공격체계 연구개발 동향 분석과 발전방안에 대한 연구)

  • Sim, Jaeseong;Park, Byoung-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.6
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    • pp.469-476
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    • 2021
  • An electronic attack (EA) system is an essential weapon system for performing electronic warfare missions that contain signal tracking and jamming against multiple threats using electromagnetic waves, such as air defense radars, wireless command and communication networks, and guided missiles. The combat effectiveness can be maximized, and the survivability of militarily protecting combat power can be enhanced through EA mission operations, such as disabling the functions of multiple threats. The EA system can be used as a radio frequency jamming system to respond to drone attacks on the core infrastructure, such as airports, power plants, and communication broadcasting systems, in the civilian field. This study examined the criteria for classification according to the electronic attack missions of foreign EA systems based on an aviation platform. The foreign R&D trends by those criteria were investigated. Moreover, by analyzing the R&D trends of domestic EA systems and future battlefields in the domestic security environments, this paper proposes technological development plans of EA systems suitable for the future battlefield environments compared to the foreign R&D trends.

Electronic Sensors and Multivariate Approaches for Taste and Odor in Korean Soups and Stews (전자센서와 다변량 분석을 이용한 국내 국·탕류의 향미 특성 분석)

  • Boo, Chang Guk;Hong, Seong Jun;Cho, Jin-Ju;Shin, Eui-Cheol
    • Journal of Food Hygiene and Safety
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    • v.35 no.5
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    • pp.430-437
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    • 2020
  • This is an approach study on the sensory properties (taste and odor) of 15 types of Korean conventional soups and stews using electronic nose and tongue. The relative sensor intensity for the taste components of the samples using electronic tongue was demonstrated. By SRS (sourness) sensor, sogogi-baechuguk (beef and cabbage soup) had the highest rate of 9.0. The STS (saltiness) sensor showed the highest score of 8.2 for ojingeoguk (squid soup). For the UMS (umami) sensor, which identifies savoriness, the sogogi-baechuguk was the highest at 10.1. The SWS (sweetness) sensors showed relatively little difference, with sigeumchi-doenjangguk (spinach and bean paste soup) at the highest of 7.3. According to the BRS sensor, which tests for bitterness, the siraegi-doenjangguk (dried radish green and bean paste soup) was the highest at 7.8. By principal component analysis (PCA), we observed variances of 56.21% in principal component 1 (PC1) and 25.23% in PC2. For each flavor component, we observed -0.95 and -0.20 for factor loading of PC1 and PC2 for SRS sensors, 0.96 and 0.14 for STS sensors, and -0.94 and 0.22 for PC1 and PC2 for UMS sensors, and PC1 and 0.22 for PC1 and PC2 loading for SWS sensors. The similarity between the samples identified by clustering analysis was largely identified by 4 clusters. A total of 25 kinds of volatile compounds in 15 samples were identified, and the ones showing the highest relative content in all samples were identified as ethanol and 2-methylthiophhene. The main ingredient analysis confirmed variances of 28.54% in PC1 and 20.80% in PC2 as a result of the pattern for volatile compounds in 15 samples. In the cluster analysis, it was found to be largely classified into 3 clusters. The data in this study can be used for a sensory property database of conventional Korean soups and stews using electronic sensors.

Sewer Decontamination Mechanism and Pipe Network Monitoring and Fault Diagnosis of Water Network System Based on System Analysis (시스템 해석에 기초한 하수관망 오염 매카니즘과 관망 모니터링 및 이상진단)

  • Kang, OnYu;Lee, SeungChul;Kim, MinJeong;Yu, SuMin;Yoo, ChangKyoo
    • Korean Chemical Engineering Research
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    • v.50 no.6
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    • pp.980-987
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    • 2012
  • Nonpoint source pollution causes leaks and overtopping, depending on the state of the sewer network as well as aggravates the pollution load of the aqueous water system as it is introduced into the sewer by wash-off. According, the need for efficient sewer monitoring system which can manage the sewage flowrate, water quality, inflow/infiltration and overflow has increased for sewer maintenance and the prevention of environmental pollution. However, the sewer monitoring is not easy since the sewer network is built in underground with the complex nature of its structure and connections. Sewer decontamination mechanism as well as pipe network monitoring and fault diagnosis of water network system on system analysis proposed in this study. First, the pollution removal pattern and behavior of contaminants in the sewer pipe network is analyzed by using sewer process simulation program, stormwater & wastewater management model for expert (XP-SWMM). Second, the sewer network fault diagnosis was performed using the multivariate statistical monitoring to monitor water quality in the sewer and detect the sewer leakage and burst. Sewer decontamination mechanism analysis with static and dynamic state system results showed that loads of total nitrogen (TN) and total phosphorous (TP) during rainfall are greatly increased than non-rainfall, which will aggravate the pollution load of the water system. Accordingly, the sewer outflow in pipe network is analyzed due to the increased flow and inflow of pollutant concentration caused by rainfall. The proposed sewer network monitoring and fault diagnosis technique can be used effectively for the nonpoint source pollution management of the urban watershed as well as continuous monitoring system.

Brain F-18 FDG PET for localization of epileptogenic zones in frontal lobe epilepsy: visual assessment and statistical parametric mapping analysis (전두엽 간질에서 F-18-FDG PET의 간질병소 국소화 성능: 육안 판독과 SPM에 의한 분석)

  • Kim, Yu-Kyeong;Lee, Dong-Soo;Lee, Sang-Kun;Chung, Chun-Kee;Yeo, Jeong-Seok;Chung, June-Key;Lee, Myung-Chul
    • The Korean Journal of Nuclear Medicine
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    • v.35 no.3
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    • pp.131-141
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    • 2001
  • Purpose: We evaluated the sensitivity of the F-18 FDG PET by visual assessment and statistical parametric mapping (SPM) analysis for the localization of the epileptogenic zones in frontal lobe epilepsy. Materials and Methods: Twenty-four patients with frontal lobe epilepsy were examined. All patients exhibited improvements after surgical resection (Engel class I or II). Upon pathological examination, 18 patients revealed cortical dysplasia, 4 patients revealed tumor, and 2 patients revealed cortical scar. The hypometabolic lesions were found in F-18 FDG PET by visual assessment and SPM analysis. On SPM analysis, cutoff threshold was changed. Results: MRI showed structural lesions in 12 patients and normal results in the remaining 12. F-18 FDG PET correctly localized epileptogenic zones in 13 patients (54%) by visual assessment. Sensitivity of F-18 FDG PET in MR-negative patients (50%) was similar to that in MR-positive patients (67%). On SPM analysis, sensitivity decreased according to the decrease of p value. Using uncorrected p value of 0.05 as threshold, sensitivity of SPM analysis was 53%, which was not statistically different from that of visual assessment. Conclusion: F-18 FDG PET was sensitive in finding epileptogenic zones by revealing hypometabolic areas even in MR-negative patients with frontal lobe epilepsy as well as in MR-positive patients. SPM analysis showed comparable sensitivity to visual assessment and could be used as an aid in the diagnosis of epileptogenic zones in frontal lobe epilepsy.

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