• Journal of KIISE:Software and Applications
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• v.35 no.6
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• pp.357-365
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• 2008

Requirements traceability enables to reuse various kinds of software artifacts, which are the results from software development life cycle, rather than reuse source code only. To support requirements traceability for reuse of software artifacts, 1) artifacts should be described based on requirements and 2) a requirements tracing method should be supported. In this paper, we provide a description model for annotating requirements information to software artifacts by using requirements ontology. We also provide semantic tagging method users to efficiently annotate artifacts with the requirements ontology. And we finally present how requirements traceability is supported based on requirements ontology and also suggest the system architecture for requirements traceability support.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.1-13
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• 2011

In order to create an intelligent autonomous agent in virtual world, we need a sophisticated design for perception, recognition, judgement and behavior. We develop the perception and recognition functions for such an autonomous agent. Our perception mechanism identifies lines based on differences in color, the primitive visible data, and exploits those lines to grasp shapes and regions in the scene. We develop an inferencing algorithm that can infer the original shape from a damaged or partially hidden shape using its characteristics from the ontology in order to intelligently recognize the perceived shape. Several individually recognized 2D shapes and their spatial relations form 3D shapes and those 3D shapes in turn constitute a scene. Each 3D shape occupies its respective region, and an agent analyzes the associated objects and relevant scenes to recognize things and phenomena. We also develop a mechanism by which an agent uses this recognition function to accumulate and use her knowledge on the scene in the historical context. We implement these functions presented above against an example situation to demonstrate their sophistication and realism.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.382-382
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• 2011

최근의 극심한 기상이변으로 인하여 발생되는 유출량의 예측에 관한 사항은 치수 이수는 물론 방재의 측면에서도 역시 매우 중요한 관심사로 부각되고 있다. 강우-유출 관계는 유역의 수많은 시 공간적 변수들에 의해 영향을 받기 때문에 매우 복잡하여 예측하기 힘든 요소이며, 과거에는 추계학적 예측모형이나 확정론적 예측모형 혹은 경험적 모형 등을 사용하여 유출량을 예측하였으나 최근에는 인공신경망과 퍼지모형 그리고 유전자 알고리즘과 같은 인공지능기반의 모형들이 많이 사용되고 있다. 하지만 유출량을 예측하고자 할 때 학습자료 및 검정자료로써 사용되는 유출량은 수위-유량 관계곡선식으로부터 구하는 경우가 대부분으로 이는 이렇게 유도된 유출량의 경우 오차가 크기 때문에 그 신뢰성에 문제가 있을 것으로 판단된다. 따라서 본 논문에서는 수위를 직접 예측함으로써 이러한 오차의 문제점을 극복 하고자 한다. Neuro-Fuzzy 모형은 과거자료의 입 출력 패턴에서 정보를 추출하여 지식으로 보유하고, 이를 근거로 새로운 상황에 대한 해답을 제시하도록 하는 인공지능분야의 학습기법으로 인간이 과거의 경험과 훈련으로 지식을 축적하듯이 시스템의 입 출력에 의하여 소속함수를 최적화함으로서 모형의 구조를 스스로 조직화한다. 따라서 수학적 알고리즘의 적용이 어려운 강우와 유출관계를 하천유역이라는 시스템에서 발생된 신호체계의 입 출력패턴으로 간주하고 인간의 사고과정을 근거로 추론과정을 거쳐 수문계의 예측에 적용할 수 있을 것이다. 유전자 알고리즘은 적자생존의 생물학 원리에 바탕을 둔 최적화 기법중의 하나로 자연계의 생명체 중 환경에 잘 적응한 개체가 좀 더 많은 자손을 남길 수 있다는 자연선택 과정과 유전자의 변화를 통해서 좋은 방향으로 발전해 나간다는 자연 진화의 과정인 자연계의 유전자 메커니즘에 바탕을 둔 탐색 알고리즘이다. 즉, 자연계의 유전과 진화 메커니즘을 공학적으로 모델화함으로써 잠재적인 해의 후보들을 모아 군집을 형성한 뒤 서로간의 교배 혹은 변이를 통해서 최적 해를 찾는 계산 모델이다. 이러한 유전자 알고리즘은 전역 샘플링을 중심으로 한 수법으로 해 공간상에서 유전자의 개수만큼 복수의 탐색점을 설정할 뿐만 아니라 교배와 돌연변이 등으로 좁아지는 탐색점 바깥의 영역으로 탐색을 확장할 수 있기 때문에 지역해에 빠질 위험성이 크게 줄어든다. 따라서 예측과 패턴인식에 강한 뉴로퍼지 모형의 해 탐색방법을 유전자 알고리즘을 사용한다면 보다 정확한 해를 찾는 것이 가능할 것으로 판단된다. 따라서 본 논문에서는 선행우량 및 상류의 수위자료로부터 하류의 단시간 수위예측에 관해 연구하였으며, 이를 위해 유전자 알고리즘을 이용항여 소속함수를 최적화 시키는 형태의 Neuro-Fuzzy모형에 대하여 연구하였다.

• Knowledge Management Research
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• v.22 no.1
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• pp.155-181
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• 2021

The purpose of this study is to verify the correlation between leader's machiavellianism and turnover intention. To this end, we tried to investigate the overall mechanism of the research model through the mediating effect of hindsight bias. To verify the hypothesis, surveys were conducted twice with 335 employees working at companies with more than 300 employees in various occupations. As a result of the study, first, it was found that the machiavellianism of the leader had a positive significant effect on the employee turnover intention. Second, it was found that hindsight bias had a positive significant mediating effect between the leader's machiavellianism and employee turnover intention. It can be inferred that the higher the machiavellianism tendency of the leader, the higher the hindsight bias is experienced and the negative impact on the effectiveness of the organization, the higher the employee turnover intention. Therefore, this study in-depth verifies the mechanism between the leader's machiavellianism, hindsight bias, and employee turnover intentions, suggesting new implications from a perspective different from the existing research flow, and suggesting future research tasks and limitations on the role of leaders.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.685-690
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• 2022

Recent research on soft adhesives has sought to understand in depth how their chemical or mechanical structures interact strongly with living tissues. The aim is to optimally address the unmet needs of patients with acute or chronic diseases. Synergy adhesion, which includes both electrostatic (hydrogen bonds) and mechanical interactions (capillary stress), appears to be effective in overcoming challenges related to long-term unstable bonds to wet surfaces. Here, we report electrostatic and mechanically synergistic mechanisms of adhesion without chemical residues. To infer the mechanism, a thermodynamic model based on custom combination adhesives has been proposed. The model supported experimental results that thermodynamically controlled swelling of hydrogels embedded in elastomeric structures improves biofluidic insensitive on-site adhesion to wet surfaces and improves detachment without chemical residues in the direction of peeling.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4B
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• pp.243-251
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• 2012

To investigate the characteristics of rip current occurring at Haeundae beach, observations obtained from a buoy and a CCTV were analyzed and numerical experiments were conducted. During observed rip-current events, the CCTV images showed that a couple of wave-trains, which are close to regular waves with slightly different directions, propagated to the beach, and wavelet analyses of data from the buoy showed very narrow-banded spectra with a peak frequency. From the evidences, it was inferred that a known mechanism of generating rip current due to the nodal line area of honeycomb-patterned wave crest was one of the significant factors of rip current occurrences of Haeundae beach. The mechanism has been explained by the following: When two wave-trains with slightly different directions propagate to a beach, wave crests of the incident wave-trains form honeycomb pattern due to nonlinear interaction. The nodal lines of honeycomb pattern are developed in the cross-shore direction. And longshore currents flow toward the nodal line area which has very low wave energy. Consequently their mass flux is expelled through the area toward the sea direction. To confirm the generation, numerical experiments were performed using a nonlinear Boussinesq equation model. In the cases with two incident wave-trains with slightly different directions and with a monochromatic wave propagating over a submerged shoal, it was seen that the honeycomb pattern of wave crests was well developed, and thus rip currents were evolved along the nodal lines.

• Journal of The Korean Association For Science Education
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• v.33 no.2
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• pp.522-537
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• 2013

This study analyzed the relationship among the construct level of analogical reasoning, prediction and uncertainty, and the construction of an explanatory model that were produced during small group discussions for scientific problem solving. This study was participated in by 8 students of K University divided into 2 teams conducting scientific problem solving. The participants took part in discussions in groups after achieving scientific problem solving individually. Through individual interviews afterwards, changes in their thinking through discussion activities were looked into. The results are as follows: The analogy at the Entities/Attributes level was used to make people clearly understand the characteristics of certain objects or entities in the discussions. The analogy at the Configuration/Motion level that was produced during the discussions ensured other participants to predict the results of problem solving. The analogy at the Mechanism/Causation level changed the structure of problem situations either to help other participants to reconstruct the explanatory model or to come up with a new situation that was never been through before to justify the created mechanism and through this, the case of creating Thought Experiments during the discussions were observed. if looking into the changes of analogies, each individual's analogic paradigm during the discussions were shown as production paradigm, reception-production paradigm, production-reception paradigm, and reception paradigm. The construction and reconstruction of the explanatory model were shown in analogic production paradigm, and in the reception paradigm of an analogy, participants changed their predictions or their certainty.

• Asia pacific journal of information systems
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• v.11 no.1
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• pp.1-24
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• 2001

This paper is aimed at proposing a new inference mechanism for B-to-B electronic commerce decision-makings, named IMITAO(Integer Matrix-driven Inference based on Transformed And-Or graph) which is based on integer matrix operation to speed up the inference. During the B-to-B electronic commerce, many kinds of negotiations are needed for mutually satisfactory decision-makings. During such negotiations, several factors including subjective and objective constraints should be considered so as to reach satisfactory decisions. In this respect, we suggest first a Transformed AND-OR Graph(TAOG) which each firm's conditions or judgement are incorporated into, and then we propose a high-speedy inference mechanism named IMITAO which basically depends on TAOG. Firms engaged in B-to-B negotiations on the Internet can get an appropriate decision support from using IMITAO for their negotiation simulations. The proposed IMITAO inference mechanism is characterized by its fast inference because its main inference procedures are based on integer matrix operation. A real-world example for B-to-B negotiations was used to prove the validity of our proposed TAOG and IMITAO approach. Experimental results showed that our approach was very useful in performing the B-to-B electronic commerce decision-makings considering a wide variety of either subjective or objective constraints.

• Journal of Korea Technology Innovation Society
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• v.13 no.3
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• pp.513-537
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• 2010

According to the "FDI-as-market-discipline" hypothesis, inward FDI acts as a mechanism of change in market structure affecting innovative activities of domestic firms. We used panel KIS data for testing this hypothesis. Binary probit estimation shows that, in contrast to the German case of Bertschek (1995), FDI is insignificant in Korean case for explaining product innovation. 1his result maybe comes from the fact that the industries in Korea are more monopolistic or oligopolistic than those of Germany. Using panel data, we tried random parameter estimation using matrix weighted average of GLS and OLS. The result shows different estimates from cross-section outcome and panel estimation with parameter homogeneity, so we can infer large parameter heterogeneity across firms. But, interpretation for FDI variable is similar across panel and cross-section estimation.