• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3021-3023
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• 1999

엄격한 시간 제약성에 의해 특성화되는 실시간 시스템의 성능을 평가하기 위해서 퍼지-랜덤 변수가 포함된 이산 사건 모델을 제시한다. 실시간 시스템의 정확성은 출력의 논리적 결과 뿐 아니라 반응시간에도 의존하므로, 본 논문에서는 실시간 시스템의 성능을 유연하게 평가하기 위해서 퍼지-랜덤 변수에 의해 적절하게 변형된 상태 오토마타를 제시하고 그 오토마타를 적용한 수치 예제를 제시한다.

• Journal of Korean Society of Transportation
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• v.12 no.4
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• pp.5-19
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• 1994

The new concept of level of service for the airport system indicates that there must be strong stimulation to proceed with the current stereotyped service standards which are being criticised due to their being based on, either physical capacity/volume or temporal/spatial standards that directly incorporates the perception of passengers. Quantitative factors have been dealt with the main service measurements when evaluating level of service. However, the passenger's perception for the provision service at the airport system is definitely important consideration to assess level of service. To enhance the reliability of service level evaluation from the passenger's point of view, this study has adopted three main evaluation factors ; temporal/spatial factors as quantitative measurements and comfort and reasonable service factors as qualitative measurements. The multi-decision model was constructed using Fuzzy Set Theory and applied to a case study at Seoul Kimpo International Airport. Results are presented in terms of passenger satisfaction with a variety of different values.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.563-572
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• 2007

Transportation infrastructure is critical to economic growth of a country such as China. Careful evaluation of investments in traffic infrastructure projects is therefore pertinent. As traditional evaluation methods do not consider the uncertainty of future cash flows and mobility during project execution, the real option approach is gradually gaining recognition in the context of valuing construction and infrastructure projects. However, many of the cases only evaluate individual options separately although multiple options often exist in a typical large infrastructure project. Using a highway project in China as a case study, this paper first evaluates a deferment option and a growth option embedded in the project. Subsequently, the values are combined using the fuzzy analytical hierarchy process. It is found that the combined value is less than the sum of the two option values. This finding is consistent with the theoretical observations given in past real option literature despite the use of a different approach.

• Smart Structures and Systems
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• v.32 no.2
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• pp.111-121
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• 2023

This study proposes an automated assembly performance evaluation method for prefabricated steel structures (PSSs) using machine learning methods. Assembly component images were segmented using a modified version of the receptive field pyramid. By factorizing channel modulation and the receptive field exploration layers of the convolution pyramid, highly accurate segmentation results were obtained. After completing segmentation, the positions of the bolt holes were calculated using various image processing techniques, such as fuzzy-based edge detection, Hough's line detection, and image perspective transformation. By calculating the distance ratio between bolt holes, the assembly performance of the PSS was estimated using the k-nearest neighbors (kNN) algorithm. The effectiveness of the proposed framework was validated using a 3D PSS printing model and a field test. The results indicated that this approach could recognize assembly components with an intersection over union (IoU) of 95% and evaluate assembly performance with an error of less than 5%.

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.45-49
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• 2024

Blockchain has gone beyond the proof-of-concept level and is converging with various industries and fields, moving toward the service development and commercialization stage. However, although various blockchain technologies and services are emerging, their development is quite slow and their widespread application to various industries is difficult. Accordingly, it is necessary to identify areas with high introduction utility when applying blockchain services in actual industries and to develop a method to evaluate the utility of blockchain services for this purpose. This paper proposes a framework for evaluating the utility of blockchain services using a multi-criteria decision-making model. Through a case study on the utility evaluation of blockchain services, the proposed framework was applied to domestic and foreign blockchain services to evaluate its utility and verify its applicability. It is expected that the proposed framework will be able to identify industrial and functional characteristics where actual blockchain services can be introduced and demonstrate effective utility and can be used to develop blockchain services in various industrial fields.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.61-70
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• 2004

It is difficult to find an appropriate web site because exponentially growing web contains millions of web documents. Personalization of web search can be realized by recommending proper web sites using user profile but more efficient method is needed for estimating preference because user's evaluation on web contents presents many aspects of his characteristics. As user profile has a property of non-linearity, estimation by classifier is needed and combination of classifiers is necessary to anticipate diverse properties. Structure adaptive self-organizing map (SASOM) that is suitable for Pattern classification and visualization is an enhanced model of SOM and might be useful for web mining. Fuzzy integral is a combination method using classifiers' relevance that is defined subjectively. In this paper, estimation of user profile is conducted by using ensemble of SASOM's teamed independently based on fuzzy integral and evaluated by Syskill ＆ Webert UCI benchmark data. Experimental results show that the proposed method performs better than previous naive Bayes classifier as well as voting of SASOM's.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.373-378
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• 2006

Recently the technical advances and complexities have generated much of the difficulties in managing the project resources, for both scheduling and costing to accomplish the project in the most efficient manner. The project manager is frequently required to render judgments concerning the schedule and resource adjustments. This research develops an analytical model for a schedule-cost and risk analysis based on visual PERT/CPM. We used a three-step approach: 1) in the first step, a deterministic PERT/CPM model for the critical path and estimating the project time schedule and related resource planning and we developed a heuristic model for crash and stretch out analysis based upon a time-cost trade-off associated with the crash and stretch out of the project. 2) In second step, we developed web-based risk evaluation model for project analysis. Major technologies used for this step are AHP (analytic hierarchy process, fuzzy-AHP, multi-attribute analysis, stochastic network simulation, and web based decision support system. Also we have developed computer programs and have shown the results of sample runs for an R&D project risk analysis. 3) We developed an optimization model for project resource allocation. We used AHP weighted values and optimization methods. Computer implementation for this model is provided based on GUI-Type objective-oriented programming for the users and provided displays of all the inputs and outputs in the form of GUI-Type. The results of this research will provide the project managers with efficient management tools.

• International Journal of Automotive Technology
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• v.2 no.1
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• pp.17-23
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• 2001

Measurements of the initial values lead to an inverse and mathematically unprecisely formulated problem. A precise definition of an inverse problem is possible. It is to state a mathematical model of a physical process with clearly defined initial and exit values for the system behind the process. One can grasp the idea of an inverse problem by considering the tire as a copy of the objects of nature in a room with observations. Interpretation of nature is generally a result of an inverse problem. On one hand, the tire may be represented through the sensory organs and the nervous system as well as the experiences of the developer's existing apparatus of the projection of reality. On the other hand, it may be represented by a physical law or a model that can be confirmed or is to be refuted with the help of suitable measurements. During reconstruction of a measuring signal and the identification of a black box that can be assumed to be linear and causal, the tire becomes a first type Volterra integral equation of the convolution type. But measurements of the initial values are always fuzzy, the errors grow and the system behavior can no longer be forecasted. Thus, we have to deal with a chaotic system. This chaos produces fractals in a natural way. These are self-similar geometric structures. This self-similarity is clearly visible in the design.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.5
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• pp.98-107
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• 1995

The in-process detection of drill wear and breakage is one of the most importnat technical problems in unmaned machining system. In this paper, the monitoring system is developed to monitor abnormal drilling states such as drill breakage, drill wear and unstable cutting using motor current. Drill breakage is detected by level monitoring. Tool wear is classified by fuzzy pattern recognition. The key feature for classification of tool wear is the estimated flank wear which is calculated by the proposed flank wear model. The characteristic of the model is not sensitive to the variation of cutting conditions but is sensitive to drill wear state. Unstable cutting states due to the unsmooth chip disposal and the overload are monitored by the variance/mean ratio of spindle motor current. Variance/mean ratio also includes the information about the prediction of drill wear and drill breakage. The evaluation experiments have shown that the developed system works very well.

• Advances in Energy Research
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• v.8 no.3
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• pp.175-184
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• 2022

The dual-fuel technology, which uses gaseous fuel as the main fuel and liquid as the pilot fuel, is an appealing technology for reducing the exhaust emissions. The current study proposes emission models based on ANFIS for a dual-fuel using producer gas (PG)-diesel engine. Emissions measurements were taken at different engine load levels and fuel injection timings. The proposed model predictions were examined using statistical methods. With R2 values in the range of 0.9903 to 0.9951, the established ANFIS model was found to be consistently robust in predicting emission characteristics. The mean absolute percentage deviate in range 1.9 to 4.6%, and mean squared error varies in range 0.0018 to 13.9%. The evaluation of the ANFIS model developed shows a reliable claim of intrinsic sensitivity, strength, and outstanding generalization. The presented meta-model can be used to simulate the engine's operation in order to create an efficient control tool.