• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3423-3440
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• 2023

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.377-386
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• 2001

In spatial database system, spatial view is supported for efficient access method to spatial database and is managed by materialization and non-materialization technique. In non-materialization technique, repeated execution on the same query makes problems such as the bottle-neck effect of server-side and overloads on a network. In materialization technique, view maintenance technique is very difficult and maintenance cost is too high when the base table has been changed. In this paper, the SVMT (Spatial View Materialization Technique) is proposed by using R-tree re-construction. The SVMT is a technique which constructs a spatial index according to the distribution ratio of objects in spatial view. This ratio is computed by using a SVHR (Spatial View Height in R-tree) and SVOC (Spatial View Object Count). If the ratio is higher than the average, a spatial view is materialized and the R-tree index is re-used. In this case, the root node of this index is exchanged a node which has a MBR (Minimum Boundary Rectangle) value that can contains the whole region of spatial view at a minimum size. Otherwise, a spatial view is materialized and the R-tree is re-constructed. In this technique, the information of spatial view is managed by using a SVIT (Spatial View Information Table) and is stored on the record of this table. The proposed technique increases the speed of response time through fast query processing on a materialized view and eliminates additional costs occurred from repeatable query modification on the same query. With these advantages, it can greatly minimize the network overloads and the bottle-neck effect on the server.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.684-687
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• 1997

In order to access to the Business Computer (B/C), the Process Computer(P/C), and the Database Server in one terminal, the Open Man Machine Interface (MMI) System has been developed. The testbed to develop the interface functions for B/C, P/C, DB server, and CCD camera were constructed, which consisted of Workstations and Personal Computers (PC). Graphic display programs Monitoring the process states of Tandem Cold Mill plant were developed using four Graphic User Interface tools: InTouch, FIX32, Open Interface Environment, and ILOG Views. With regard to the CPU utilization and response delay required to open new display, the performance tests have been carried out on each MMI platform.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1310-1313
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• 1997

Application of eddy current sensing principle for the non-contact estimation of very low concentration of electrolytic solution is presented in this paper. for this application, a new, simple, low-cost, low-power structure for the eddy current sensor is proposed. By measuring the eddy current produced in the conducting electrolytic solution, the concentration is estimated. Therefore, the unknown concentration can be estimated comparing with the database which is prepared as the relation between the change in inductance and various concentrations of electrolytic solution. The concentration, as low as l ppm of the solutioin can be detected by this sensor. It was tested on various low concentration solutions of NaCl. It shows distinct response for various concentrations.

• MALSORI
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• v.68
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• pp.75-93
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• 2008

An example-based dialogue system tries to utilize many pairs which are stored in a dialogue database. The most important part of the example-based dialogue system is to find the most similar utterance to user's input utterance. Modality, which is characterized as conveying the speaker's involvement in the propositional content of a given utterance, is one of the core sentence features. For example, the sentence "I want to go to school." has a modality of hope. In this paper, we have proposed a modality classification system which can predict sentence modality in order to improve the performance of example-based dialogue systems. We also define a modality tag set for a dialogue system, and validate this tag set using a rule-based modality classification system. Experimental results show that our modality tag set and modality classification system improve the performance of an example-based dialogue system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.10a
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• pp.187-192
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• 2001

In this paper, a practical method to generate task strategies applicable to charmfulness and high-precision assembly, is proposed. The difficulties in devising reliable assembly strategies result form various forms of uncertainty such as imperfect knowledge on the parts being assembled and functional limitations of the assembly devices. In approach to cope with these problems, the robot is provided with the capability of learning the corrective motion in response to the force signal through iterative task execution. The strategy is realized by adopting a learning algorithm and represented in a binary tree type database. To verify the effectiveness of the proposed algorithm, a series of simulations and experiments are carried out under assimilated real production environments. The results show that the sensory signal-to-robot action mapping can be acquired effectively and, consequently, the assembly task can be performed successfully.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.283-286
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• 2006

내용기반의 이미지 검색방법은 객체의 내부의 정보를 이용한 검색방법으로 색상, 모양, 질감과 같은 특징을 사용한다. 이러한 특징 중에 모양은 검색에 사용될 수 있는 점을 추출하여 유사도 계산에 사용한다. 유사도 계산은 점의 개수가 증가할수록 검색의 응답시간도 함께 증가한다는 문제점이 있다. 본 논문은 응답시간 향상을 위하여 특징점들에 대한 그리드 기반의 유사도 매칭 기법을 제안한다. 그리드 기반의 유사도 매칭 기법은 점들을 그리드로 나누어 검색의 범위를 좁힘으로써 매칭하는 횟수를 줄이는 방법이다. 특징점으로 사용된 점들은 이미지의 선으로부터 MPP(Minimum Perimeter Polygons) 알고리즘으로 추출하였으며, 특징 점들간의 거리값의 합을 유사도로 계산하였다. 실험에서는 400여개의 식물 잎 이미지로부터 점들을 추출하여 검색 시간을 비교하였다.

• IE interfaces
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• v.15 no.4
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• pp.374-381
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• 2002

In this paper, we design and implement a real-time route guidance system(RGS) in large-scale networks. Coupled with the well-known mathematical routing algorithms, we devise an RGS for knowledge aquisition and self-learning ability within the framework of the expert system. Through off-line construction of database, on-line treatment of unexpected traffic accidents, etc., the developed RGS can provide drivers with good quality real-time routing information. The practical effectiveness of the proposed system is demonstrated in terms of response time and route appropriateness.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.20-25
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• 2015

It is predicted the mass retirement of the post-war generation and the lack of young people according to reduces the recruitment. Therefore, industry fields are concerned by the low level of occupational safety and health from issued problem in a variety of industries; the charge of expanding business range/multi-functional, black box of technology, difficulty of systematic training, relative decrease in the skill of workers, loss of know-how in the field of information followed restricted site information. In response to these problems, it is necessary to establish the long-termly and actively based on for the adoption of a safety and health management techniques utilizing IT, which is digital assistant(tablet PC, PDA, etc.), RFID/USN/ICT, database systems, and etc. In this study, we developed and evaluated a worker's safety sensing apparatus using smart phone. The apparatus may be useful to prevent accidents in the construction industry as well as confined space work.

• MALSORI
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• no.49
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• pp.77-94
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• 2004

In this paper, new voice message system supporting massive outbound call is proposed. Basic idea of the proposed system is to pre-process all the text-to-speech conversion process, mixing of text and attached music file and to store the results of pre-process in the cache server which is connected to the IVR. New voice message system is optimized for the voice message system supporting massive outbound call by distributing the load of the web server caused by server-side script implementation which is accessing database and generating dynamic Voice XML document over client module and server module of web server. The proposed voice message system was test-deployed in one domestic voice message application service provider and it is shown that proposed voice message system reduced the response latency problem of test-bed voice message system.