• Water for future
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• v.29 no.5
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• pp.185-202
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• 1996

The newly-developed method for estimating the instream flow, proposed by the authors (1996), was applied to the main channel reach of the Kum River basin in Korea. Performance of the suggested method was tested through the evaluations of the required flow, instream flow, and river-management flow which were estimated at five main reaches with each representative station. The mean drought flow was used as the object flow to evaluate the minimum instream flow for the mid- and large-size rivers. Water quality prediction by using the QUAL2E model was made for both cases that the planned wastewater treatment facilities may and may not be constructed. The required flow for the fish habitat was evaluated for 9 representative fish species. The instream flows required for the riverine aesthetics at Kong-ju and Puyo scenary points, for river navigation at natural channel conditions, and for current and potential recreation activities were evaluated, respectively. The instream flows required for other items are not quantified. On the whole, it is shown that the instream flow to maintain the natural riverine functions such as fish habitat, and riverine aesthetics govern the upstream reaches of the Kum River, and the artificial riverine functions such as conservation of water quality, navigation and recreations govern the middle and downstream reaches. Especially, it is found that the instream flow requirement depends largely upon the construction of wastewater treatment facilities at the Kum River basin.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.315-326
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• 2013

Users in social media post various types of opinions such as product reviews and movie reviews. It is a common trend that customers get assistance from the opinions in making their decisions. However, as opinion usage grows, distorted feedbacks also have increased. For example, exaggerated positive opinions are posted for promoting target products. So are negative opinions which are far from common evaluations. Finding these biased opinions becomes important to keep social media reliable. Techniques of opinion mining (or sentiment analysis) have been developed to determine sentiment polarity of opinionated documents. These techniques can be utilized for finding the biased opinions. However, the previous techniques have some drawback. They categorize the text into only positive and negative, and they also need a large amount of training data to build the classifier. In this paper, we propose methods for discovering the biased opinions which are skewed from the overall common opinions. The methods are based on angle based outlier detection and personalized PageRank, which can be applied without training data. We analyze the performance of the proposed techniques by presenting experimental results on a movie review dataset.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.110-122
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• 2014

As multimedia technologies develop, three-dimensional (3D) technologies are attracting increasing attention from researchers. In particular, video quality assessment (VQA) has become a critical issue in stereoscopic image/video processing applications. Furthermore, a human visual system (HVS) could play an important role in the measurement of stereoscopic video quality, yet existing VQA methods have done little to develop a HVS for stereoscopic video. We seek to amend this by proposing a 3D visual attention (3DVA) model which simulates the HVS for stereoscopic video by combining multiple perceptual stimuli such as depth, motion, color, intensity, and orientation contrast. We utilize this 3DVA model for pooling on significant regions of very poor video quality, and we propose no-reference (NR) stereoscopic VQA (SVQA) method. We validated the proposed SVQA method using subjective test scores from our results and those reported by others. Our approach yields high correlation with the measured mean opinion score (MOS) as well as consistent performance in asymmetric coding conditions. Additionally, the 3DVA model is used to extract information for the region-of-interest (ROI). Subjective evaluations of the extracted ROI indicate that the 3DVA-based ROI extraction outperforms the other compared extraction methods using spatial or/and temporal terms.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.55-64
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• 2017

In this paper, we propose and implement an IoT based mobile smart monitoring system in the view point of safety inspection for solar power generation. The main features and contributions of proposed system are as follows. First, the proposed system model can evaluate periodically in the view point of safety inspection the conditions of the system and structure of solar power generation. Second, the proposed system automatically re-processes the measurement data of the system and structure for solar power generation and save it into database. Third, using the re-processed and saved information, the proposed system can provide the monitoring information with webpage form to both administrator and owner of solar power generation system, thus they can measure and confirm directly in the view point of safety inspection the conditions of the solar generation structure without visiting those places. Fourth, the provided web pages for the monitoring of solar power generation can be accessed regardless of the system structures. The performance evaluations of the proposed system show that the proposed monitoring system can save efficiently the data received from the sensors installed in the structure of solar power generation into the data base in the collecting server. And the proposed system can support that both administrator and user of solar power generation system access webpage in real time without considering places by using mobile phone and desktop computer and obtain the information for the conditions of the system and structure of solar power generation with graph forms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.86-98
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• 2018

Since 2015, the Korea Expressway Corporation has provided predicted travel time information, which is reproduced from DSRC systems over the extended expressway network in Korea. When it is open for public information, it helps travelers decide optimal routes while minimizing traffic congestions and travel cost. Although, sutiable evaluations to investigate the reliability of travel time forecast information have not been conducted so far. First of all, this study seeks to find out a measure of effectiveness to evaluate the reliability of travel time forecast via various literatures. Secondly, using the performance measurement, this study evaluates concurrent travel time forecast information in highway quantitatively and examines the forecast error by exploratory data analysis. It appears that most of highway lines provided reliable forecast information. However, we found significant over/under-forecast on a few links within several long lines and it turns out that such minor errors reduce overall reliability in travel time forecast of the corresponding highway lines. This study would help to build a priority for quality control of the travel time forecast information system, and highlight the importance of performing periodic and sustainable management for travel time forecast information.

• Management & Information Systems Review
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• v.37 no.1
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• pp.41-53
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• 2018

This study validates the trading rules based market anomalies and technical analysis in the Korean stock market. For the analysis, we built decile portfolios on the basis of corporate characteristics factors that clearly demonstrate specific patterns of stock returns including the firm size, book-to-market equity, and accruals. This portfolio was used to develop a portfolio based on the moving average trading strategy which was used for popular technical analysis tools, and then that was evaluated using the Sharpe ratio. We also created a zero-cost portfolio to identify the profitability and success rate of the moving average trading strategy. We lastly sought to ensure a more robust evaluation by calculating the Sortino ratio of the portfolio based on the moving average trading strategy with various lags. Key findings from this validation are as follows. First, a smaller firm size, a higher book-to-market equity, and lower accruals led to larger average returns. Second, the risk-adjusted performance of the moving average trading strategy was the highest in terms of the firm size, followed by book-to-market equity and accruals. Third, the returns of the zero-cost portfolios all had a positive value, with its overall success rate hovering over 68.8%, demonstrating the successfulness of the moving average trading strategy. Fourth, various evaluations revealed the economic usefulness of our trading strategy that used market anomalies and technical analysis.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9101-9105
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• 2014

Background: The purpose of this study was to compare the accuracy and effectiveness of automated breast volume scanning (ABVS) and hand-held ultrasound (HHUS) in the detection of breast cancer in a large population group with a long-term follow-up, and to investigate whether different ultrasound systems may influence the estimation of cancer detection. Materials and Methods: Institutional review board approval was obtained for this retrospective study, and informed consent was waived. From September 2010 to August 2011, a total of 1,866 ABVS and 3,700 HHUS participants, who underwent these procedures at our institute, were included in this study. Cancers occurring during the study and subsequent follow-up were evaluated. The reference standard was a combination of histology and follow-up imaging (${\geq}12months$). The recall rate, cancer detection yield, diagnostic accuracy, sensitivity, specificity, and positive (PPV) and negative (NPV) predictive values were calculated with exact 95% confidence intervals. Results: The recall rate was 2.57 per 1,000 (48/1,866) for ABVS and 3.57 per 1,000 (132/3,700) for HHUS, with a significant difference (p=0.048). The cancer detection yield was 3.8 per 1,000 for ABVS and 2.7 per 1,000 for HHUS. The diagnostic accuracy was 97.7% for ABVS and 96.5% for HHUS with statistical significance (p=0.018). The specificity of ABVS and HHUS were 97.8%, 96.7%, respectively (p=0.022). Conclusions: ABVS shows a comparable diagnostic performance to HHUS. ABVS is an effective supplemental tool for mammography in breast cancer detection in a large population.

• Geophysics and Geophysical Exploration
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• v.2 no.2
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• pp.86-95
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• 1999

This paper presents an efficient three-dimensional (3-D) modeling algorithm using the extended approximation to an electric field integral equation. Numerical evaluations of Green's tensor integral are performed in the spatial wavenumber domain. This approach makes it possible to reduce computing time, to handle smoothly varying conductivity model and to remove singularity problems encountered in the integration of Green's tensor at a source point. The responses obtained by 3-D modeling algorithm developed in this study are compared with those by the full integral equation for a thin-sheet EM scattering. The extensive analyses on the performance of modeling algorithm are made with the conductivity contrasts and source frequencies. These results show that the modeling algorithm are accurate up to the conductivity contrast of 1:16 and the frequency range of 100 Hz-100 kHz. The extended Born approximation, however, may produce inaccurate results for some source and model configurations in which the electric field is discontinuous across the conductivity boundary. We performed the modeling of a composite model of which conductivity varies continuously and this shows the modeling algorithm developed in this study is efficient for 3-D EM modeling. For a cross-hole source-receiver configuration a composite model of which conductivity varies continuously can be successfully simulated using this algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.253-261
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• 2004

Game theory is mathematical analysis developed to study involved in making decisions. In 1928, Von Neumann proved that every two-person, zero-sum game with finitely many pure strategies for each player is deterministic. As well, in the early 50's, Nash presented another concept as the basis for a generalization of Von Neumann's theorem. Another central achievement of game theory is the introduction of evolutionary game theory, by which agents can play optimal strategies in the absence of rationality. Not the rationality but through the process of Darwinian selection, a population of agents can evolve to an Evolutionary Stable Strategy (ESS) introduced by Maynard Smith. Keeping pace with these game theoretical studies, the first computer simulation of co-evolution was tried out by Hillis in 1991. Moreover, Kauffman proposed NK model to analyze co-evolutionary dynamics between different species. He showed how co-evolutionary phenomenon reaches static states and that these states are Nash equilibrium or ESS introduced in game theory. Since the studies about co-evolutionary phenomenon were started, however many other researchers have developed co-evolutionary algorithms, in this paper we propose Game theory based Co-Evolutionary Algorithm (GCEA) and confirm that this algorithm can be a solution of evolutionary problems by searching the ESS.To evaluate newly designed GCEA approach, we solve several test Multi-objective Optimization Problems (MOPs). From the results of these evaluations, we confirm that evolutionary game can be embodied by co-evolutionary algorithm and analyze optimization performance of GCEA by comparing experimental results using GCEA with the results using other evolutionary optimization algorithms.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.369-380
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• 2004

In this paper, we propose a web page weighting scheme based on WordNet-based collaborative evaluation and hyperlink to improve the precision of web search engine. Generally search engines use keyword matching to decide web page ranking. In the information retrieval from huge data such as the Web, simple word comparison cannot distinguish important documents because there exist too many documents with similar relevancy. In this paper, we implement a WordNet-based user interface that helps to distinguish different senses of query word, and constructed a search engine in which the implicit evaluations by multiple users are reflected in ranking by accumulating the number of clicks. In accumulating click counts, they are stored separately according to lenses, so that more accurate search is possible. Weighting of each web page by using collaborative evaluation and hyperlink is reflected in ranking. The experimental results with several keywords show that the precision of proposed system is improved compared to conventional search engines.