• Journal of Industrial Convergence
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• v.18 no.2
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• pp.95-100
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• 2020

Among the customer-oriented data used to comprehend the customer, the user review data has received much attention as it provides insights into customer opinion in a detailed and large-scale manner; many customers have come to rely upon and trust the user reviews. Many application developers are cognizant of the importance of user reviews, so they monitor and respond to these reviews. However, due to the absence of a systematic method, developers have been investing their time and money without clear correlation to the customer satisfaction. Therefore, this paper suggests a systematic method to select user reviews from the application market using the Kano Model that deals with customer satisfaction and service quality, thereby maximizing the customer satisfaction under the given time period and budget. This method is constructed in the following phases: the user review collection and requirement elicitation phase in which the developers collect user reviews from the application market and elicit requirements, the Kano Model application and selection phase in which the Kano Model is applied to the elicited requirements and selection occurs based on the quality type, and the stakeholder review and redefinition phase in which relevant personnel gather to review and redefine requirements from an internal perspective.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.165-178
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• 2019

In an environment transformed by smart factories, measuring the current level of the manufacturing system, deriving improvement targets and tasks and increasing the level of manufacturing competitiveness become the basic activities of the company. However, research on the component analysis and maturity assessment to ensure the future competitiveness of the company is in progress and in the early stages. This study analyzed the existing research on various models, development process, and framework for manufacturing system. In addition, we designed a structural model by deriving the components of future manufacturing system through smart factory related maturity assessment studies. We designed a meta-model that includes an assesment model and a transformation model, and derived the framework development process to propose an integrated framework for the maturity assessment of the future manufacturing system. We verified it by applying it into an actual evaluation project of smart factory.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.270-270
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• 2023

습지 생태계는 복잡한 물리적 생지화학적 프로세스의 상호작용이 있으나, 습지 생태계의 건강성 회복을 위한 첫 번째 단계는 습지 생태계에서의 물순환에 대한 정확한 이해일 것이다. 또한 지역적인 물 균형 및 생태계 보전에서 습지를 활용하기 위해서도 습지 물순환에 대한 정량적인 이해는 필수적이다. 그러나, 습지 물순환의 이해를 위해 필수적인 관측 자료들은 현장 측정으로 획득하기 어려운 자료이거나 비용적인 문제로 인하여 관측이 어려운 실정이다. 이에 본 연구에서는 Sentinel-2 위성 자료를 활용하여 습지의 유입량을 추정하기 위한 절차를 제시하고자 한다. 이를 위해 한반도 동남부의 낙동강에 위치한 주요 다목적댐의 자료를 활용한 분류 기반의 인공지능 모델이 설계된다. 인공지능의 학습을 위한 입력자료는 아래와 같은 절차에 의해 만들어진다. 1) 다목적댐의 수위-물 체적 관계를 이용하여 수위-수표면적 관계 곡선 도출. 2) 수위-수표면적 관계 곡선과 DEM을 활용하여 물과 육지 영역을 구분하는 식별자를 도출. 3) Sentinel-2 위성 정보와 물-육지 식별자를 비교하는 랜덤 포레스트 모델을 설계. 4) 위성 정보의 물-육지 정보로부터 미계측 습지 지역의 물과 육지를 식별할 수 있는 식별자 도출. 이러한 과정을 경유하여 추정된 습지의 수표면적과 습지 지역의 DEM을 결합함으로써 습지의 수위-수표면적-물 체적 관계 곡선이 산정되어, 최종적으로 습지의 유입량이 모의된다. 모의된 습지 유입량은 다양한 수문 모델의 매개변수를 추정하는데 활용될 수 있을 것이며, 검증된 수문 모델을 활용하여 습지의 물순환의 이해도를 증진시킬 수 있을 것으로 기대된다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.31-34
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• 2024

태양광 에너지는 탄소 중립 이행을 위한 주요 방안으로 많은 주목을 받고 있다. 태양광 발전량은 여러 환경적 요인에 따라 크게 달라질 수 있으므로, 정확한 발전량 예측은 전력 네트워크의 안정성과 효율적인 에너지 관리에 근본적으로 중요하다. 대표적인 인공지능 기술인 신경망(Neural Network)은 불안정한 환경 변수와 복잡한 상호작용을 효과적으로 학습할 수 있어 태양광 발전량 예측에서 우수한 성능을 도출하였다. 하지만, 신경망은 모델의 구조나 초매개변수(Hyperparameter)를 최적화하는 것은 복잡하고 시간이 많이 드는 작업이므로, 에너지 분야에서 실제 산업 적용에 한계가 존재한다. 본 논문은 2단계 신경망 최적화를 통한 태양광 발전량 예측 기법을 제안한다. 먼저, 태양광 발전량 데이터 셋을 훈련 집합과 평가 집합으로 분할한다. 훈련 집합에서, 각기 다른 은닉층의 개수로 구성된 여러 신경망 모델을 구성하고, 모델별로 Optuna를 적용하여 최적의 초매개변숫값을 선정한다. 다음으로, 은닉층별 최적화된 신경망 모델을 이용해 훈련과 평가 집합에서는 각각 5겹 교차검증을 적용한 발전량 추정값과 예측값을 출력한다. 마지막으로, 스태킹 앙상블 방식을 채택해 기본 초매개변숫값으로 설정해도 우수한 성능을 도출하는 랜덤 포레스트를 이용하여 추정값을 학습하고, 평가 집합의 예측값을 입력으로 받아 최종 태양광 발전량을 예측한다. 인천 지역으로 실험한 결과, 제안한 방식은 모델링이 간편할 뿐만 아니라 여러 신경망 모델보다 우수한 예측 성능을 도출하였으며, 이를 바탕으로 국내 에너지 산업에 이바지할 수 있을 것으로 기대한다.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.285-301
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• 2023

Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

• Journal of Service Research and Studies
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• v.11 no.3
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• pp.75-97
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• 2021

This study was conducted to derive a society and education system model that will improve the happiness and sustainability of human society. An ideological model for making human society a happy society was derived, and a society and education system structure and operation model based on this was presented. A fair society, a justice society, a mutually considerate society, and a society where individuals are happy are the conditions for a sustainable society. After analyzing the current situation of freedom and equality pursued by capitalism and democracy, which are currently adopted by most societies, an improvement model was derived from the perspective of a sustainable society. The cost of freedom and equality were analyzed and a new alternative system was discussed. The social solidarity and class mobility issues were discussed together and servicism was derived as an alternative solution. It is a system in which two opposing opponents of individual freedom and social norms form a symmetrical balance, and material and spiritual values are balanced. Servicism is a dynamic balance model. That is, the dimensions of time and space are involved. It is a model that maintains a thorough balance through a dialectical process as time and space change, and one value can dominate the other at a specific time or space. The service-oriented society and education system is a system that simultaneously pursues the goals of individual happiness and sustainable development of the social community.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.635-647
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• 2006

Korean construction companies first advanced to the international markets in 1960's and so far have brought more than 4,900 projects which account for 193 billion dollars approximately. With the large increase of national employment and income being followed by the achievement, Korea's construction industry has made an enormous contribution to the improvement of domestic economy for the last 40 years. However, recently the increased risk in international markets as well as the sharpening competition with foreign companies promising in terms of advanced technologies and low labor cost have been driving Korean construction away from the market shares. According to ENR (Engineering News Record, 1994~2003), it is revealed that 15.1% of top 225 global contractors are suffering from loss in international construction markets. This phenomenon is largely due to the highly uncertain characteristics of international projects, which are inherently exposed to various and complicated risky situations. Furthermore, especially for Korean construction companies, it is often the case that the failure in an international construction project cannot be offset by even a sufficient number of successful domestic achievements. Therefore, not only the selective screening among the nominated projects which have strong possibility of collapse but the systematic strategies for controlling potential risk factors are also considered indispensable in international construction portfolio management. The purpose of this study is to first analyze the causal relationships of the profit-influencing variables and the project success, and develop the profitability forecasting model in international construction projects.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.7
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• pp.9-16
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• 2008

In this paper, a simple analytical model for deriving the threshold voltage of a short-gate SOI MESFET is suggested. Using the iteration method, the Poisson equation in the fully depleted silicon channel and the Laplace equation in the buried oxide region are solved two-dimensionally, Obtained potential distributions in each region are expressed in terms of fifth-order of $\chi$, where $\chi$ denotes the coordinate perpendicular to the silicon channel direction. From them, the bottom channel potential is used to describe the threshold voltage in a closed-form. Simulation results show the dependencies of the threshold voltage on the various device geometry parameters and applied bias voltages.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.10
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• pp.54-61
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• 2011

In this paper, a simple analytical model for deriving the I-V characteristics of a cylindrical surrounding gate SOI MOSFET with intrinsic silicon core is suggested. The Poisson equation in the intrinsic silicon core and the Laplace equation in the gate oxide layer are solved analytically. The surface potentials at both source and drain ends are obtained by means of the bisection method. From them, the surface potential distribution is used to describe the I-V characteristics in a closed-form. Simulation results seem to show the dependencies of the I-V characteristics on the various device parameters and applied bias voltages within a range of satisfactory accuracy.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2072-2087
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• 1999

As software size ever increases and user's requirements become more and more sophisticated., the importance of software quality is more and more emphasized. However, we are not satisfied for the present techniques on detecting errors and checking consistency in the object-oriented design model. This paper proposes a systematic approach which produces implementable rules to detect errors and check consistency. At first, the meta-models for UML diagrams are constructed, generalized meta-rules are reduced from the meta-models, and then the meta-rules are applied to produce the implementable rules. This approach enables to pursue the completeness of the rules and the automation of rule application. An example of rule application shows the feasibility of the rule application.