• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.383-386
• /
• 2005

This study proposes a case based reasoning system with two dimensional reduction techniques. In this study, vertical and horizontal dimensions of the research data are reduced through hybrid feature and instance selection process using genetic algorithms. We applied the proposed model to customer classification model which utilizes customers' demographic characteristics as inputs to predict their buying behavior for the specific product. Experimental results show that the proposed technique may improve the classification accuracy and outperform various optimized models of typical CBR system.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.12 no.1
• /
• pp.95-104
• /
• 2010

The "admission officer system" of the Korea National College of Agriculture and Fisheries does the school life records (50%), a engaging in agriculture and fishery base (33.3%) and an interview (16.7%) with typical element and selects the freshmen. The system of admission officer the instance of domestic and the foreign nation university is suitable in founding goal of the Korea National College of Agriculture and Fisheries which agriculture and fishery manager education. Also the selection of the well rounded student there is character and an aptitude to agriculture and fishery is possible. Also the agriculture and fishery high school curriculum and connectedness of our college between could be strengthened. Consequently the Korea National College of Agriculture and Fisheries was investigated with the fact that the "admission officer system" is necessary

• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.2
• /
• pp.101-108
• /
• 2014

As browsing and sharing multimedia contents through various social network services have become very common these days. there has been a rising demand for effectively provide appropriate multimedia contents to users depending on their interest and characteristics. Especially, considering the enormous volume of multimedia contents created daily, user satisfaction heavily depends on effective selection of appropriate multimedia contents. For instance, if the acquisition of contents is based on friends or related people, then it is usually considered to be more trustworthy. Facebook page is one of the social spaces where people can obtain various information of interest. Still, users have difficulty in finding proper information because Facebook generates tremendous amount of data daily. In this paper, we proposed a scheme to extract and select Facebook page contents effectively. In our proposed scheme, users are grouped based on mutual intimacy and Facebook pages of interest are selected based on the ranking of importance. We show the performance of our scheme through experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.342-345
• /
• 2014

Network intrusion detection system based on machine learning methods is quite dependent on the selected features in terms of accuracy and efficiency. Nevertheless, choosing the optimal combination of features from generally used features to detect network intrusion requires extensive computing resources. For instance, the number of possible feature combinations from given n features is $2^n-1$. In this paper, to tackle this problem we propose a optimal feature selection algorithm. Proposed algorithm is based on the local search algorithm, one of representative meta-heuristic algorithm for solving optimization problem. In addition, the accuracy of clusters which obtained using selected feature components and k-means clustering algorithm is adopted to evaluate a feature assembly. In order to estimate the performance of our proposed algorithm, comparing with a method where all features are used on NSL-KDD data set and multi-layer perceptron.

• Journal of the Korean association of regional geographers
• /
• v.11 no.5
• /
• pp.440-457
• /
• 2005

The purpose of this study was to examine the importance and satisfaction of exhibition and convention destinations from the MICE(meeting, incentive tour, convention, and exhibition) planners. Overall, four results were revealed from this study. First, considering the importance of selection attributes, soundproofing, lighting, temperature, A V facilities, the space of main convention hall and exhibition were the most important attributes. Second, hypothesis 1 suggested that there were statistically significant differences in the attributes of convention destination selection based on the socio-demographic variables. More specifically, a statistically significant was found in the 17 attributes out of 5 factors and 4 demographic variables. Third, hypothesis 2 suggested that there were statistically significant in the attributes of convention destination selection based on the planning characteristics of MICE. For instance, statistically significants were found 9 attributes out of 5 factors and the 4 planning characteristics. Fourth, the regional space of exhibition and convention was the most influential to the intention to revisit, followed by exhibition and convention facilities and use cost. And also, considering the recommendation to the other MICE planners who recently have used exhibition and convention centers, the facilities was the most influential, followed by use cost and tourism space surrounding exhibition and convention centers.

• Journal of Environmental Impact Assessment
• /
• v.4 no.3
• /
• pp.87-94
• /
• 1995

At both international and national levels, such as in the Rio Declaration and the EU's Fifth Environmental Action Plan, governments have committed themselves to the adoption of the precautionary principle (UNCED 1992, CEC 1992). These commitments mean that the existence of uncertainty in appraising policies and proposals for development should be acknowledged. Uncertainty arise in both the prediction of impacts and in the evaluation of their significance, particularly of those cumulative impacts which are individually insignificant but cumulatively damaging. The EC network of EIA experts, stated at their last meeting in Athens that indirect effects and the treatment of uncertainty are one of the main deficiencies of current EIA practice. Uncertainties in decision-making arise where choices have been made in the development of the policy or proposal, such as the selection of options, the justification for that choice, and the selection of different indicators to comply with different regulatory regimes. It is also likely that a weighting system for evaluating significance will have been used which may be implicit rather than explicit. Those involved in decision-making may employ different tolerances of uncertainty than members of the public, for instance over the consideration of the worst-case scenario. Possible methods for dealing with these uncertainties include scenarios, sensitivity analysis, showing points of view, decision analysis, postponing decisions and graphical methods. An understanding of the development of cumulative environmental impacts affords not only ecologic but also socio-economic investigations. Since cumulative impacts originate mainly in centres of urban or industrial development, in particular an analysis of future growth effects that might possibly be induced by certain development impacts. Not least it is seen as an matter of sustainability to connect this issue with ecological research. The serious attempt to reduce the area of uncertainty in environmental planning is a challenge and an important step towards reliable planning and sustainable development.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.6
• /
• pp.287-295
• /
• 2007

This paper proposes a novel data editing techniques with genetic algorithm (GA) in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in compelax problem solving. Nonetheless, compared to other machine teaming techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However. designing a good matching and retrieval mechanism for CBR system is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for data editing in CBR.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.19 no.1
• /
• pp.9-17
• /
• 2024

It is widely recognized that for 3D human pose estimation (HPE), dataset acquisition is expensive and the effectiveness of augmentation techniques of conventional visual recognition tasks is limited. We address these difficulties by presenting a simple but effective method that augments input images in terms of viewpoints when training a 3D human pose estimation (HPE) model. Our intuition is that meaningful variants of the input images for HPE could be obtained by viewing a human instance in the images from an arbitrary viewpoint different from that in the original images. The core idea is to synthesize new images that have self-occlusion and thus are difficult to predict at different viewpoints even with the same pose of the original example. We incorporate this idea into the training procedure of the 3D HPE model as an augmentation stage of the input samples. We show that a strategy for augmenting the synthesized example should be carefully designed in terms of the frequency of performing the augmentation and the selection of viewpoints for synthesizing the samples. To this end, we propose a new metric to measure the prediction difficulty of input images for 3D HPE in terms of the distance between corresponding keypoints on both sides of a human body. Extensive exploration of the space of augmentation probability choices and example selection according to the proposed distance metric leads to a performance gain of up to 6.2% on Human3.6M, the well-known pose estimation dataset.

• Journal of Intelligence and Information Systems
• /
• v.24 no.4
• /
• pp.155-170
• /
• 2018

Predicting a company's financial bankruptcy is traditionally one of the most crucial forecasting problems in business analytics. In previous studies, prediction models have been proposed by applying or combining statistical and machine learning-based techniques. In this paper, we propose a novel intelligent prediction model based on the simulated annealing which is one of the well-known optimization techniques. The simulated annealing is known to have comparable optimization performance to the genetic algorithms. Nevertheless, since there has been little research on the prediction and classification of business decision-making problems using the simulated annealing, it is meaningful to confirm the usefulness of the proposed model in business analytics. In this study, we use the combined model of simulated annealing and machine learning to select the input features of the bankruptcy prediction model. Typical types of combining optimization and machine learning techniques are feature selection, feature weighting, and instance selection. This study proposes a combining model for feature selection, which has been studied the most. In order to confirm the superiority of the proposed model in this study, we apply the real-world financial data of the Korean companies and analyze the results. The results show that the predictive accuracy of the proposed model is better than that of the naïve model. Notably, the performance is significantly improved as compared with the traditional decision tree, random forests, artificial neural network, SVM, and logistic regression analysis.

• Korean Institute of Interior Design Journal
• /
• v.22 no.6
• /
• pp.58-67
• /
• 2013

Since environmental pollution emerges as an important issue, integration of academic discipline has been accomplished for development of environmental ethics. Combination of Buddhism and Ecology is the instance of this background. The background of this research is the assumption that from Seon Ecology standpoint, Buddhist temple would define conception of Seon Ecology specifically. The study based on advanced study about Seon Ecology, the peculiarity of Seon Ecology was dependent originations, order, the nature of Buddha, moderation, and impersonated nature. In addition, this study researched how these peculiarity has relation with traditional temples. This attempt has a significance in that finding a new approach of interpreting traditional temple and possibility of Seon Ecology Seon Ecology space formative concepts of traditional temple is cyclical allness, transitory balance, Denial of perfection and natural void characteristics from Seon Ecological studies. This study examined how characteristic of Seon Ecology is reflected in traditional temple, through analyzing Buseoksa-Anyangru, Bongjeongsa-Yeonsanam, Seonamsa simgeomdang, Songgwangsa woohwagak, Hwaamsa woohwaru which have remarkable characteristic of selection using above space formative concepts. traditional temple was filled with life coexisted with dynamics, independence, and equality within interrelationship between nature and architecture.