• Journal of the military operations research society of Korea
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• v.32 no.2
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• pp.131-142
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• 2006

Nowadays, most enterprises have introduced both EA methodology to optimize an entire enterprise and CBD methodology to improve a software reusability. The Korea Government not only have developed many EA guiding products such as EA framework, Reference Model, Guideline, etc. but also have instituted a law to optimize a government-wide enterprise. The Minister of National Defense(MND) have developed the MND-AF as a standard methodology for EA and the ADDMe as a standard methodology for CBD. But it is possible to develop products of WD-AF and ADDMe redundantly because the process of MND-AF and ADDMe is not quitely aligned. The purpose of this paper is to present a scheme that ADDMe can reuse the artifacts of MND-AF by analyzing the relationships between two processes. In order to identify the relationships between two processes, we first identify the relation of a 'definition' part of two processes and then identify the relation of an 'attribute' part based on the relation of a 'detailed definition' part. As a result we found that 113 attributes of MND-AF are related to 49 attributes of ADDMe. Therefore the proposed study will decrease the development cost and time and will be a good example for aligning the process of EA and CBD methodology.

• Management & Information Systems Review
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• v.32 no.2
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• pp.1-19
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• 2013

The purpose of this study is to provide the model for goal planning system and explore the affecting factors in suitability of goal planning system and possibility of goal attainment. The findings in a factor analysis of the sample of Korean firms indicate that the factors suggested by theories and previous studies can be summarized to 40 implications and then 7 groups including attachment of top managers, systemicity, participation system, motivation, alignment of top-down & bottom-up. adjustment for environmental changes, goal content. In addition, the findings in multiple regression analyses show that goal content, alignment of top-down & bottom-up, and adjustment for environmental changes are positively, significantly influence the recognition level of employees on the suitability of goal planning system. On the other hand, goal content, attachment of top managers, and motivation are significantly influence the recognition level of employees on the possibility of goal attainment. This study provides the checklist for the suitability of goal planning system and various implications for practitioners.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.73-81
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• 2020

This study demonstrated the effect of IT Ssupports for Iintegration Ccompetency(ITSIC) on organizational performance by using organizational temperance and absorption capacity as medium. The research model was verified with Smart PLS 3.0 based on the survey conducted overa total a total of of 126 pparticipantseople's surveys for the employees. First, the ITSIC had a positive effect on both the alignment and adaptability and also on absorption capacity. Second, it was confirmed that organizational temperance hads a positive effect on absorption capacity. Third, when the organizational temperance was mediated in the relationship between ITSIC and absorption capacity, it had a indicated a positive effect. Fourth, absorption capacity had a positive impact on organizational performance. The implications of this study differ from the existing studies through by validating validation of correlations correlations by extending IT technology and organizational performance to organizational ethical factors. In addition, it has been established that the ethical factors of the organization also act as leading factors of absorption capacity. ITSIC helps managers make balanced decision-making, which can contribute to improving absorption capacity by giving members a positive perception, ultimately having a positive impact on organizational performance. It suggests the importance of building appropriate IT infrastructure and cultivating organizational virtues in order to improve the performance of organizations in which absorption capacity is essential.

• 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.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.453-462
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• 2009

Studies on software plagiarism detection, prevention and judgement have become widespread due to the growing of interest and importance for the protection and authentication of software intellectual property. Many previous studies focused on comparing all pairs of submitted codes by using attribute counting, token pattern, program parse tree, and similarity measuring algorithm. It is important to provide a clear-cut model for distinguishing plagiarism and collaboration. This paper proposes a source code clustering algorithm using a probability model on extreme value distribution. First, we propose an asymmetric distance measure pdist($P_a$, $P_b$) to measure the similarity of $P_a$ and $P_b$ Then, we construct the Plagiarism Direction Graph (PDG) for a given program set using pdist($P_a$, $P_b$) as edge weights. And, we transform the PDG into a Gumbel Distance Graph (GDG) model, since we found that the pdist($P_a$, $P_b$) score distribution is similar to a well-known Gumbel distribution. Second, we newly define pseudo-plagiarism which is a sort of virtual plagiarism forced by a very strong functional requirement in the specification. We conducted experiments with 18 groups of programs (more than 700 source codes) collected from the ICPC (International Collegiate Programming Contest) and KOI (Korean Olympiad for Informatics) programming contests. The experiments showed that most plagiarized codes could be detected with high sensitivity and that our algorithm successfully separated real plagiarism from pseudo plagiarism.

• Journal of the Korea Computer Graphics Society
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• v.26 no.3
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• pp.49-59
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• 2020

In this paper, we propose a speech animation synthesis specialized in Korean through a rule-based co-articulation model. Speech animation has been widely used in the cultural industry, such as movies, animations, and games that require natural and realistic motion. Because the technique for audio driven speech animation has been mainly developed for English, however, the animation results for domestic content are often visually very unnatural. For example, dubbing of a voice actor is played with no mouth motion at all or with an unsynchronized looping of simple mouth shapes at best. Although there are language-independent speech animation models, which are not specialized in Korean, they are yet to ensure the quality to be utilized in a domestic content production. Therefore, we propose a natural speech animation synthesis method that reflects the linguistic characteristics of Korean driven by an input audio and text. Reflecting the features that vowels mostly determine the mouth shape in Korean, a coarticulation model separating lips and the tongue has been defined to solve the previous problem of lip distortion and occasional missing of some phoneme characteristics. Our model also reflects the differences in prosodic features for improved dynamics in speech animation. Through user studies, we verify that the proposed model can synthesize natural speech animation.

• Journal of Korean Society of Transportation
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• v.32 no.1
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• pp.50-62
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• 2014

The number of traffic accidents has been decreased since 2000; however, the downward trend of crash occurrence has been slower after 2006. A few decades ago, physical improvement projects such as alignment improvement and the installation of safety facilities were usually implemented to decrease the occurrence of traffic accidents, but the effects of physical improvement on safety have been gradually decreased. The main objective of this study is to identify how the drivers' characteristics affect and/or are related to traffic accidents. Most of previous works have focused on revealing the difference of the nature of the drivers between the drivers who have no experience and the drivers with experience of traffic accidents. This study tries to analyze the habitual accidents proneness through a survey of drivers' personalities for drivers who were involved in traffic accidents at least once. As a result, nine personality factors were found to be statistically significant: Neuroticism(N), Lie(L), Psychoticism* Neuroticism(PN), Psychoticism*Lie(PL), Extraversion*Lie(EL), Neuroticism*Lie(NL), Impulsiveness(IMP), Venturesomeness(VEN), Empathy(EMP). Among these factors, single character factors were found to increase accidents, whereas complex factors were found to decrease the occurrence of accidents.

• Tunnel and Underground Space
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• v.30 no.3
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• pp.214-225
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• 2020

Uniaxial compressive strength (UCS) of rock is one of the important factors to determine the advance speed during shield TBM tunnel excavation. UCS can be obtained through the Geotechnical Data Report (GDR), and it is difficult to measure UCS for all tunneling alignment. Therefore, the purpose of this study is to predict UCS by utilizing TBM machine driving data and machine learning technique. Several machine learning techniques were compared to predict UCS, and it was confirmed the stacking model has the most successful prediction performance. TBM machine data and UCS used in the analysis were obtained from the excavation of rock strata with slurry shield TBMs. The data were divided into 8:2 for training and test and pre-processed including feature selection, scaling, and outlier removal. After completing the hyper-parameter tuning, the stacking model was evaluated with the root-mean-square error (RMSE) and the determination coefficient (R²), and it was found to be 5.556 and 0.943, respectively. Based on the results, the sacking models are considered useful in predicting rock strength with TBM excavation data.

• The Korean Journal of Pesticide Science
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• v.11 no.2
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• pp.59-66
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• 2007

Three dimensional quantitative structure-activity relationships (3D-QSARs) on the fungicidal activity of N-phenyl-O-phenylthionocarbamate analogues against resistant and sensitive gray mold (Botrytis cinerea) (RBC & SBC) were studied quantitatively using CoMFA and CoMSIA methods. The correlation coefficient and predict- ability of optimized CoMFA model with the atom based fit alignment were better ($r^2$ & $q^2=CoMFA{\gg}CoMSIA$) than that of CoMSIA model. And statistical values of the models on the fungicidal activity against SBC were showed higher ($r^2=SBC{\gg}RBC$) than that of RBC. In CoMFA models, steric field on the activity was more influenced than electrostatic field. And in case of CoMSIA models, the influence of CoMSIA field on the activity against RBC and SBC was differ from each other but the influence of H-bond donor field was same to the two fungi. It is revealed that the selectivity factor with CoMFA model on the fungicidal activity between the two fungi was caused on the difference of steric field. Therefore, it is predicted that the large steric field with meta- and para-substituents on the N-phenyl ring will be improved to the fungicidal activity with SBC.

• Reproductive and Developmental Biology
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• v.30 no.3
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• pp.169-174
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• 2006

To search of a new porcine pheromonal odorants, the comparative molecular similarity indices analysis(CoMSIA) between porcine odorant binding protein(pOBP) as receptor and ligands of green odorants 2-(Cyclohexyloxy)tetrahydrofurane derivatives as substrate molecule were conducted and disscused quantitatively. In the optimized CoMSIA model(I-AI) with chirality($I:\;C_{1'}(R),\;C_2(S)$) in substrate molecules and atom based fit alignment(AE) of the odorants the statistical PLS results showed the best predictability of the binding affinities based on the LOO cross-validated value ${r^2}_{cv.}\;(q^2=0.856)$ and non cross-validated conventional coefficient(${r^2}_{ncv.}=0.964)$). The structural distinctions of the highest active molecules were able to understand from the interaction between pOBP and green odorants in the contour maps with CoMSIA model.