• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.745-752
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• 2009

Management of social infrastructure has been advanced from facility management (FM) to asset management (AM), which adopts the aggressive and proactive methods in predicting the deterioration of infrastructure, prevents failures, and eventually saves maintenance cost. Infrastructure asset management is not a simple engineering technique, but it is a new paradigm evolved from facility management practices. To implement the infrastructure asset management successfully, organizational reform is very important. This paper suggests critical success factors and key performance indicators to implement the infrastructure asset management for facility managers of government owned social infrastructures such as roads and bridges. Reorganizing the facility management group requires new vision, objectives, strategies for the paradigm-changing asset management. This paper uses Balanced Score Card (BSC) which is a proven method in measuring and setting new objectives for an organization. Once the performance indicators are reviewed repeatedly by facility managers through experts workshops, developed BSC can be used in practice. This paper discusses the development of robust BSC scoring method through in depth literature reviews and investigation of asset management practices of domestic and international cases.

• Information Systems Review
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• v.24 no.1
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• pp.105-123
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• 2022

Thanks to the remarkable success of Artificial Intelligence (A.I.) techniques, a new possibility for its application on the real-world problem has begun. One of the prominent applications is the bankruptcy prediction model as it is often used as a basic knowledge base for credit scoring models in the financial industry. As a result, there has been extensive research on how to improve the prediction accuracy of the model. However, despite its impressive performance, it is difficult to implement machine learning (ML)-based models due to its intrinsic trait of obscurity, especially when the field requires or values an explanation about the result obtained by the model. The financial domain is one of the areas where explanation matters to stakeholders such as domain experts and customers. In this paper, we propose a novel approach to incorporate financial domain knowledge into local rule generation to provide explanations for the bankruptcy prediction model at instance level. The result shows the proposed method successfully selects and classifies the extracted rules based on the feasibility and information they convey to the users.

• Korean Journal of Cognitive Science
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• v.35 no.1
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• pp.23-48
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• 2024

Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Journal of the Korean Society of Food Culture
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• v.7 no.2
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• pp.149-155
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• 1992

This study was carried out to find out the effect of dietary intake on cognitive function retardation in old age using dietary survey and cognitive function test. The subjects were 332 men of 50-94 years old and their activities of daily living were very similar. The cognitive function was tested by Mini Mental State Examination (MMSE)-K which was translated from MMSE, and the 24-hour recall method was used for dietary survey. Scoring of MMSE-K was a little different from MMSE, that is, in case of no education, one to four points were added to exclude the effect of education which has been considered as a confounder by many researchers. The number of subjects belonging to below 23 of MMSE-K score was increased by increasing age. Even though points were added in case of no education, the ratio of below 23 MMSE-K score group was diminished by increasing education. Therefore, education seems not to be a confounder but a independent variable on cognitive function. Income, past occupation, family type, self-evaluated health status did not play any effect on cognitive function significantly. On the other hand, the correlation between each nutrients and the score of cognitive function test showed that the more consumption of vitamin A and protein, the higher cognitive function score was obtained. In case of iron and Ca, even though it was not statistically significant, there was a tendency of increasing cognitive function score by increasing the intake of those nutrients. This study suggests that micronutrient intakes might be more related to cognitive function than macronutrients.

• Bulletin of the Korean Chemical Society
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• v.33 no.5
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• pp.1707-1714
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• 2012

Grb2 is an adapter protein involved in the signal transduction and cell communication. The Grb2 is responsible for initiation of kinase signaling by Ras activation which leads to the modification in transcription. Ligand based pharmacophore approach was applied to built the suitable pharmacophore model for Grb2. The best pharmacophore model was selected based on the statistical values and then validated by Fischer's randomization method and test set. Hypo1 was selected as a best pharmacophore model based on its statistical values like high cost difference (182.22), lowest RMSD (1.273), and total cost (80.68). It contains four chemical features, one hydrogen bond acceptor (HBA), two hydrophobic (HY), and one ring aromatic (RA). Fischer's randomization results also shows that Hypo1 have a 95% significant level. The correlation coefficient of test set was 0.97 which was close to the training set value (0.94). Thus Hypo1 was used for virtual screening to find the potent inhibitors from various chemical databases. The screened compounds were filtered by Lipinski's rule of five, ADMET and subjected to molecular docking studies. Totally, 11 compounds were selected as a best potent leads from docking studies based on the consensus scoring function and critical interactions with the amino acids in Grb2 active site.

• Journal of Science Education
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• v.39 no.3
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• pp.376-388
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• 2015

The purpose of this study was to develop the experiment-based problem for evaluating scientific ability of elementary scientifically gifted students, and to examine its potential of application for them. The problem for evaluating scientific ability was related to the plant vascular structure of 'the structure and function of plants' unit of elementary school science, and consisted of three components such as observing and inferring, designing an experiment, and concluding. In order to apply for scientifically gifted students, scoring criteria were detailed. For the observing and inferring domain, the arrangement and structure of vascular bundles of the dicotyledon and the monocotyledon, xylem position, reason of putting plants in ink were included. Those of designing an experiment domain were method of dissecting stems of plants, and design experimental procedures, those of concluding were the prediction of experimental results, and comparison and verification with prediction and results. Finally, the scientific ability evaluation problem was applied for 22 scientifically gifted students, who had been taught in the Science Education Institute for the Gifted adjacent University, and we had found the potential of utilization for scientifically gifted students.

• Journal of Korea Water Resources Association
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• v.53 no.1
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• pp.45-56
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• 2020

This study aims to quantify the uncertainty that can be induced by the objective function when calibrating SWAT parameters using SWAT-CUP. SWAT model was constructed to estimate runoff in Naesenong-cheon, which is the one of mid-watershed in Nakdong River basin, and then automatic calibration was performed using eight objective functions (R², bR², NS, MNS, KGE, PBIAS, RSR, and SSQR). The optimum parameter sets obtained from each objective function showed different ranges, and thus the corresponding hydrologic characteristics of simulated data were also derived differently. This is because each objective function is sensitive to specific hydrologic signatures and evaluates model performance in an unique way. In other words, one objective function might be sensitive to the residual of the extreme value, so that well produce the peak value, whereas ignores the average or low flow residuals. Therefore, the hydrological similarity between the simulated and measured values was evaluated in order to select the optimum objective function. The hydrologic signatures, which include not only the magnitude, but also the ratio of the inclining and declining time in hydrograph, were defined to consider the timing of the flow occurrence, the response of watershed, and the increasing and decreasing trend. The results of evaluation were quantified by scoring method, and hence the optimal objective functions for SWAT parameter calibration were determined as MNS (342.48) and SSQR (346.45) with the highest total scores.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.4
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• pp.29-41
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• 2014

The Korean government has purchased land properties alongside any significant water bodies before setting up the buffers to secure water qualities. Since the annual budgets are limited, however, there has always been the issue of which land parcels ought to be given the priority. Therefore, this study aims to develop efficient mechanism for land acquisition priorities in stream corridors that would ultimately be vegetated for riparian buffer zones. The criteria of land acquisition priority were driven through literary review along with experts' advice. The relative weights of their value and priorities for each criterion were computed using the Analytical Hierarchy Process(AHP) method. Major findings of the study are as follows: 1. The decision-making structural model for land acquisition priority focuses mainly on the reduction of non-point source pollutants(NSPs). This fact is highly associated with natural and physical conditions and land use types of surrounding areas. The criteria were classified into two categories-NSPs runoff areas and potential NSPs runoff areas. 2. Land acquisition priority weights derived for NSPs runoff areas and potential NSPs runoff areas were 0.862 and 0.138, respectively. This implicates that much higher priority should be given to the land parcels with NSPs runoff areas. 3. Weights and priorities of sub-criteria suggested from this study include: proximity to the streams(0.460), land cover(0.189), soil permeability(0.117), topographical slope(0.096), proximity to the roads(0.058), land-use types(0.036), visibility to the streams(0.032), and the land price(0.012). This order of importance suggests, as one can expect, that it is better to purchase land parcels that are adjacent to the streams. 4. A standard scoring system including the criteria and weights for land acquisition priority was developed which would likely to allow expedited decision making and easy quantification for priority evaluation due to the utilization of measurable spatial data. Further studies focusing on both point and non-point pollutants and GIS-based spatial analysis and mapping of land acquisition priority are needed.

• Journal of Preventive Medicine and Public Health
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• v.11 no.1
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• pp.98-109
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• 1978

The study was carried out for 101 establishments in Kyong-In areas to evaluate the industrial health management status utilizing the scoring method by Webb's model during the period from 1 September to October 30, 1977. To compare the results, reevaluation was made with the 45 questions' model prepared by 6 Korean professionals who were specialized in industrial health fields. The results were as follows: 1. The mean rate of affirmative answers for 101 establishments was 51.6%. The mean weighted score rate of affirmative answers was 52.3%. 2. The mean rate of affirmative answers on components of the philosophy and facility resource for 101 establishments was higher than that of average rate. The mean rate of affirmative answers on components of the health evaluation and health management among the health service program was lower than that of average rate. 3. The mean rate of affirmative answers on components was highter among the establishments with more than 500 employees. The mean rate of affirmative answers of chemical establishment was lower than that of others. 4. The mean rate of affirmative answers on 45 questions' model for 101 establishments were 67.1%. The mean weighted score rate of affirmative answers was 70.0%. 5. In case of 45 questions' model, the mean rate of affirmative answers on components of philosophy and treatment was higher than that of average rate and the mean rate of affirmative answers on components of the facility resource and the health evaluation was lower than that of average rate. 6. The mean rate of affirmative answers of the 45 Questions' model was higher than that of Webb's model in size and class of 101 establishments. Author concluded that Webb's model must be suitable for evaluating higher conditions of occupational health management than is presently used in Korean establishments. According to the results, however, there were no significant differences between Webb's model and the 45 questions' model. So it could be used to evaluate Occupational Health Program. For this objective, in Korean occupational situations, further study also must be made comprehensively thereafter.