• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.556-562
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• 2002

This paper studies the identification of a combustion model, which is used to design a linear controller of a steam generation quantity and harmful exhaust gases of a Refuse Incineration Plant(RIP). Even though the RIP has strong nonlinearities and complexities, it is identified as a MIMO parametric ARX model from experimental input-output data sets. Unknown model parameters are decided from experimental input-output data sets, using system identification algorithm based on Instrumental Variables(IV) method. It is shown that the identified model well approximates the input-output combustion characteristics.

• Journal of Korea Technology Innovation Society
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• v.2 no.2
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• pp.249-265
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• 1999

This study examines the efficiency of engineering education using DEA(data envelopment analysis) which is often used in the efficiency evaluation of public services. We evaluate 27 mechanical engineering departments according to academy-basis, general basis, and employment-basis considering students' academic level and input costs as input factors. Our empirical results suggest that an evaluation method using DEA can give us useful informations such as benchmarks to improve education specialization where it is desirable, decisions about whether a department should expand its gross input or not, and proper directions about which input factors should be controlled and how much control is needed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1707-1714
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• 2006

In order to enhance sustainable war fighting capabilities, it is important to maintain a good ammunition support system. In this paper, we evaluate the performance of Ammunition companies using Imprecise Data Envelopment Analysis (IDEA)-BCC and IDEA-Additive model, which can deal with imprecise data in DEA. In order to select a list of input and output variables, we used a multiple regression analysis. We could choose input variables that have significant effects on the output performance with stepwise regression model. From the regression analysis, the number of soldiers, officers, and ammunition warehouses were selected as the input variables. Seven out of sixteen Ammunition companies were found to be inefficient by the IDEA-BCC model. And using IDEA-Additive model, we could identify the input excess and the output shortfall in reaching at a point on the efficiency frontier.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.585-590
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• 2000

Recently, It is gradually raised necessity that thickness of thin film is measured accuracy and managed in industrial circles and medical world. Ultrasonic Signal processing method is likely to become a very powerful method for NDE method of detection of microdefects and thickness measurement of thin film below the limit of Ultrasonic distance resolution in the opaque materials, provides useful information that cannot be obtained by a conventional measuring system. In the present research, considering a thin film below the limit of ultrasonic distance resolution sandwiched between three substances as acoustical analysis model, demonstrated the usefulness of ultrasonic Signal processing technique using information of ultrasonic frequency for NDE of measurements of thin film thickness, sound velocity, and step height, regardless of interference phenomenon. Numeral information was deduced and quantified effective information from the image. Also, pattern recognition of a defected input image was performed by neural network algorithm. Input pattern of various numeral was composed combinationally, and then, it was studied by neural network. Furthermore, possibility of pattern recognition was confirmed on artifical defected input data formed by simulation. Finally, application on unknown input pattern was also examined.

• Journal of Power System Engineering
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• v.6 no.2
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• pp.24-32
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• 2002

A program is developed to analyze and design the frequency and rigidity of the corrugated plates with various corrugation shapes (the considered corrugation shapes are triangular and trapezoidal) and 36 kinds of boundary conditions using smeared theory. The system is consisted of input, solution and output routines, and its routine is made up pull-down menu type and run in Window basis using Visual Basic Language. The input routine helps the design engineers to make the input data user-friendly. The solution routine uses the homemade solver. In the output routine, automatic designs can be done using AutoCAD and Intent Tool package by interfacing the input data.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.700-705
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• 2004

Shell finite elements are widely used for the analysis of thin section objects such as sheet metal parts, automobile bodies and et al. due to their computational efficiency. Since many of input data for finite element analysis are given as solid models or triangulated surface models, one should extract midsurface information from these input data initially and then construct shell meshes on the extracted midsurfaces. In this paper, a method of generating shell elements on midsurfaces directly from input models have been proposed. In order to construct shell meshes, the input models should be triangulated on surfaces first, and then tetrahedral elements are generated by using an advancing front method, and finally mid shell surfaces are obtained from tetrahedral meshes. Some examples are given to demonstrate the efficiency of the proposed method.

• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1107-1120
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• 2004

This study proposes a new scheme for the sampled-data representation of nonlinear systems with time-delayed multi-input. The proposed scheme is based on the Taylor-series expansion and zero-order hold assumption. The mathematical structure of a new discretization scheme is explored. On the basis of this structure, the sampled-data representation of nonlinear systems including time-delay is derived. The new scheme is applied to nonlinear systems with two inputs and then the delayed multi-input general equation is derived. The resulting time-discretization provides a finite-dimensional representation of nonlinear control systems with time-delay enabling existing controller design techniques to be applied to them. In order to evaluate the tracking performance of the proposed scheme, an algorithm is tested for some of the examples including maneuvering of an automobile and a 2-DOF mechanical system.

• Computers and Concrete
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• v.24 no.5
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• pp.399-412
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• 2019

In this investigation, Elman neural networks were utilized for predicting the mechanical properties of Self-Compacting Concretes (SCCs). Elman models were designed by using experimental data of many different concrete mixdesigns of various types of SCC that were collected from the literature. In order to investigate the effectiveness of the selected input variables on the network performance in predicting intended properties, utilized data in artificial neural networks were considered in two sets of 8 and 140 input variables. The obtained outcomes showed that not only can the developed Elman ANNs predict the mechanical properties of SCCs with high accuracy, but also for all of the desired outputs, networks with 140 inputs, compared to ones with 8, have a remarkable percent improvement in the obtained prediction results. The prediction accuracy can significantly be improved by using a more complete and accurate set of key factors affecting the desired outputs, as input variables, in the networks, which is leading to more similarity of the predicted results gained from networks to experimental results.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.226-230
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• 2013

In the tall building construction, the slab formwork largely impacts on construction cost. Because productivity of a slab formwork is influenced by a number of and the efficiency of equipment, using the equipment-based construction method, an appropriate equipment input planning is crucial for the productivity. Meanwhile, the general equipment input planning is conducted by intuition based on experience due to the lack of equipment productivity data. Thus, this study develop a simulation model to analyze table formwork productivity and to propose an optimum equipment input plan that reflects the construction process, based on the full consideration of the economic factors. This study developed a simulation model by using CYCLONE and the data for the model was collected by measuring the duration of each unit activity in the tall building where table forms were applied. It is expected that a simulation model helps users to make better decision on the equipment input planning of slab formwork.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.47-56
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• 2024

This paper proposes a method for fine-tuning BERT-based natural language processing models to perform sentiment analysis on Korean review data. By varying the input sequence length during this process and comparing the performance, we aim to explore the optimal performance according to the input sequence length. For this purpose, text review data collected from the clothing shopping platform M was utilized. Through web scraping, review data was collected. During the data preprocessing stage, positive and negative satisfaction scores were recalibrated to improve the accuracy of the analysis. Specifically, the GPT-4 API was used to reset the labels to reflect the actual sentiment of the review texts, and data imbalance issues were addressed by adjusting the data to 6:4 ratio. The reviews on the clothing shopping platform averaged about 12 tokens in length, and to provide the optimal model suitable for this, five BERT-based pre-trained models were used in the modeling stage, focusing on input sequence length and memory usage for performance comparison. The experimental results indicated that an input sequence length of 64 generally exhibited the most appropriate performance and memory usage. In particular, the KcELECTRA model showed optimal performance and memory usage at an input sequence length of 64, achieving higher than 92% accuracy and reliability in sentiment analysis of Korean review data. Furthermore, by utilizing BERTopic, we provide a Korean review sentiment analysis process that classifies new incoming review data by category and extracts sentiment scores for each category using the final constructed model.