• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.6
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• pp.128-135
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• 2004

The author present a modified multi-loop algorithm including feedforward for controlling a 55kW step down chopper in the power supply of Maglev. The control law for the duty cycle consists of three terms. The first is the feedforward term. which compensates for variations in the input voltaga. The second term consists of the difference between the slowly moving inductor current and output current. The third term consists of proportional and integral terms involving the perturbation in the output voltage. This perturvation is derived by subtracting the desired output voltage from the actual output voltage. The proportional and integral action stabilizes the system and minimizes output voltage error. In order to verify the validity of the proposed multi-loop controller, simulation study was tried using Matlab simulink

• Nuclear Engineering and Technology
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• v.41 no.1
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• pp.1-10
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• 2009

The safe and reliable performance of fusion and fission plants depends on the choice of suitable materials and an assessment of long-term materials degradation. These materials are degraded by their exposure to extreme conditions; it is necessary, therefore, to address the issue of long-term damage evolution of materials under service exposure in advanced plants. The empirical approach to the study of structural materials and fuels is reaching its limit when used to define and extrapolate new materials, new environments, or new operating conditions due to a lack of knowledge of the basic principles and mechanisms present. Materials designed for future Gen IV systems require significant innovation for the new environments that the materials will be exposed to. Thus, it is a challenge to understand the materials more precisely and to go far beyond the current empirical design methodology. Breakthrough technology is being achieved with the incorporation in design codes of a fundamental understanding of the properties of materials. This paper discusses the multi-scale, multi-code computations and multi-dimensional modelling undertaken to understand the mechanical properties of these materials. Such an approach is envisaged to probe beyond currently possible approaches to become a predictive tool in estimating the mechanical properties and lifetimes of materials.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.707-720
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• 2021

To improve the accuracy of the recommendation system, multi-criteria recommendation systems have been widely researched. However, it is highly complicated to extract the preferred features of users and items from the data. To this end, subjective indicators, which indicate a user's priorities for personalized recommendations, should be derived. In this study, we propose a method for generating recommendation candidates by predicting multi-criteria ratings from reviews and using them to derive user priorities. Using a deep learning model based on convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), multi-criteria prediction ratings were derived from reviews. These ratings were then aggregated to form a linear regression model to predict the overall rating. This model not only predicts the overall rating but also uses the training weights from the layers of the model as the user's priority. Based on this, a new score matrix for recommendation is derived by calculating the similarity between the user and the item according to the criteria, and an item suitable for the user is proposed. The experiment was conducted by collecting the actual "TripAdvisor" dataset. For performance evaluation, the proposed method was compared with a general recommendation system based on singular value decomposition. The results of the experiments demonstrate the high performance of the proposed method.

• KNOM Review
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• v.24 no.2
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• pp.13-23
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• 2021

Recently, as networks become more complex due to the activation of IoT devices, research on long-term traffic prediction beyond short-term traffic prediction is being activated to predict and prepare for network congestion in advance. The recursive strategy, which reuses short-term traffic prediction results as an input, has been extended to multi-step traffic prediction, but as the steps progress, errors accumulate and cause deterioration in prediction performance. In this paper, an LSTM-based multi-step traffic prediction method using a multi-output strategy is introduced and its performance is evaluated. As a result of experiments based on actual DNS request traffic, it was confirmed that the proposed LSTM-based multiple output strategy technique can reduce MAPE of traffic prediction performance for non-stationary traffic by 6% than the recursive strategy technique.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1826-1829
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• 2003

Fine chemical production must assure high-standard product quality as well as characterized as multi-product production in small volumes. Installing high-precision batch distillation is one of the common elements in the successful manufacturing of fine chemicals, and the importance of the process operation strategy with quality assurance cannot be overemphasized. In this study, we investigate the optimal operation strategy and production planning of a sequential multi-purpose plants consisting of batch processes and batch distillation with unlimited intermediate storage. We formulated this problem as an MILP model. A mixed-integer linear programming model is developed based on the time slot, which is used to determine the production sequence and the production path of each batch. Illustrative examples show the effectiveness of the approach.

• Journal of Advanced Marine Engineering and Technology
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• v.21 no.1
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• pp.66-70
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• 1997

In this paper a new learning algorithm for curvature smoothing and improved generalization for multi-layer neural networks is proposed. To enhance the generalization ability a constraint term of hidden neuron activations is added to the conventional output error, which gives the curvature smoothing characteristics to multi-layer neural networks. When the total cost consisted of the output error and hidden error is minimized by gradient-descent methods, the additional descent term gives not only the Hebbian learning but also the synaptic weight decay. Therefore it incorporates error back-propagation, Hebbian, and weight decay, and additional computational requirements to the standard error back-propagation is negligible. From the computer simulation of the time series prediction with Santafe competition data it is shown that the proposed learning algorithm gives much better generalization performance.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.97-106
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• 2020

The objective of this paper is to suggest a new quantification method for multi-unit probabilistic safety assessment (PSA) that removes the overestimation error caused by the existing delete-term approximation (DTA) based quantification method. So far, for the actual plant PSA model quantification, a fault tree with negates have been solved by the DTA method. It is well known that the DTA method induces overestimated core damage frequency (CDF) of nuclear power plant (NPP). If a PSA fault tree has negates and non-rare events, the overestimation in CDF drastically increases. Since multi-unit seismic PSA model has plant level negates and many non-rare events in the fault tree, it should be very carefully quantified in order to avoid CDF overestimation. Multi-unit PSA fault tree has normal gates and negates that represent each NPP status. The NPP status means core damage or non-core damage state of individual NPPs. The non-core damage state of a NPP is modeled in the fault tree by using a negate (a NOT gate). Authors reviewed and compared (1) quantification methods that generate exact or approximate Boolean solutions from a fault tree, (2) DTA method generating approximate Boolean solution by solving negates in a fault tree, and (3) probability calculation methods from the Boolean solutions generated by exact quantification methods or DTA method. Based on the review and comparison, a new intersection removal by probability (IRBP) method is suggested in this study for the multi-unit PSA. If the IRBP method is adopted, multi-unit PSA fault tree can be quantified without the overestimation error that is caused by the direct application of DTA method. That is, the extremely overestimated CDF can be avoided and accurate CDF can be calculated by using the IRBP method. The accuracy of the IRBP method was validated by simple multi-unit PSA models. The necessity of the IRBP method was demonstrated by the actual plant multi-unit seismic PSA models.

• IE interfaces
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• v.22 no.2
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• pp.165-173
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• 2009

This paper considers a two-component assembly system that makes different types of purchasing contracts by component type and studies the issue of coordinating those contracts. Acquisition of type 1 component is based on the long-term contract. In contrast, type 2 component is intermittently purchased under the sort-term contract. We identify the structural properties of the optimal short-term contract and investigate how the changes in system parameters affect the optimal performance. To provide managerial insights, we compare the short-term and long-term contracts for type 2 component and discuss the conditions that make the short-term contract preferable to the long-term contract. We also present a result which shows that coordinating the contracts of type 1 and type 2 components can be significantly profitable over uncoordinating them.

• Wind and Structures
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• v.26 no.2
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• pp.69-74
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• 2018

Nowadays, using math logic in great civil projects is considered by the clients to achieve the goals of project including quality optimization, costs, avoiding individual, emotional and political decision making, long-term and short-term goals and they are the main requirements of each project and should be considered by the decision makers to avoid the illogical decision making applied on the majority of civil projects and this imposes great financial and spiritual costs on our country. The present study attempts to present one of the civil projects (Ghasre Shirin storage dam) whose client was not ministry of energy for the first time and the short-term and long-term goals of the private sector were applied based on the triangle of quality, cost and time. Also, the math logic and model (multi-criteria decision making method and decision making matrix) is used in one of the most important sections of project, sealing element, policies and new materials (Geosynthetics) are considered and this leads to suitable decision making in this regard. It is worth to mention that this method is used for other sections of a dam including body, water diversion system, diaphragm and other sectors or in other civil projects of building, road construction, etc.

• Journal of Engineering Education Research
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• v.23 no.2
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• pp.49-60
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• 2020

The purpose of this study is to empirically verify whether there are differences according to group characteristics in the effect of job characteristic requirements on practice performance in university long-term on-site training. Specifically, the relationship between job characteristics (job scope, job content, coaching, benefits), practical satisfaction, and occupational competencies was examined according to the group characteristics (gender types, major types, corporation types). For this purpose, the survey data were collected and analyzed for 752 students who participated in K university long-term on-site training. As a result of the analysis, first, it was found that the job characteristics (job scope job content, coaching, benefits) had structural relationship affecting occupational competence through mediation of practice satisfaction. Second, As for the differences according to the group characteristics, there were differences in the relations. Based on the result, theoretical and practical implications and follow-up studies were proposed.