• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.29-34
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• 2005

The wound induction motor can provide high starting torque and reduced starting current simultaneously by inserting large resistor externally when starting. And this technique is one of the well known methods among the induction motor starting methods and generally used for heavy load starting such as crane and cement factories. The conventional PI controller has been widely used in industrial application due to the simple control algorithm and is generally used for control of current torque, position, and speed for the wound induction motor drive system. However, the conventional control system for wound induction motor may result in poor performance because sensors have to be used but are often limited by the environmental condition. Recently, to overcome these problems, many sensorless vector control methods for the wound induction motor have been studied. This paper presents a MRAS method for sensorless vector control of the wound induction motor drive. In the conventional MRAS method, in low frequency, the stator resistance variation may result in poor performance. Therefore, this paper presents a MRAS method with stator and rotor resistance tuning for sensorless vector control of the wound induction motor to overcome several shortages of the conventional MRAS caused by parameter variation and to enhance the robustness of the sensorless vector control. The validity and effectiveness of the proposed method is verified through digital simulation.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.580-586
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• 2016

The ultra-long stroke engine was developed to generate greater power at lower speeds than previous designs to enhance the propulsion efficiency. The torsional exciting force, on the other hand, was increased significantly. Therefore, it is possible to control the torsional vibration of its shaft system equipped with the fuel efficient ultra-long stroke engine by adopting a damper although the torsional vibration could be controlled adequately by applying tuning and turning wheels on the engine previously. In this paper, the dynamic characteristics of a viscous-spring damper used to control the torsional vibration of the corresponding shaft system are reviewed and then examined to determine what vibration characteristics might be used to optimize the viscous-spring damper. In some cases, operators of eco-ships have recently experienced the problem of delayed RPM acceleration. It has been suggested that the proper measures for controlling the torsional vibration in the shaft system should involve adjusting the design parameters of its damper determined by the optimum damper design theory to avoid the fatigue damage of shafts.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.8
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• pp.36-44
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• 1999

This paper presents the design and fabrication of the duplexer for a Ka-band satellite transponder which is analyzed transmission characteristics by calculating the generalized scattering matrix using mode matching method. It is composed of 2 bandpass filters, coupled with H-plane T-junction having symmetrical inductive iris and E-plane metal insert structures. Compared with the size and weight of the Rx and Tx filter loaded with a transponders respectively, those of the duplexer can be effectively reduced. In a high power transmission, the variation of the filter characteristics is minimized by the scheme that irises are extended to the exterior of H-plane of the waveguide. This scheme needs no extra heat sinks for dissipating high power. The duplexer is designed to improve the simplification, durability and reliability by eliminating tuning screws, which have been used to compensate for the characteristics of fabricated filters. The bandpass filters of the duplexer show the insertion loss of less than 1.2 dB and the return loss in excess of 15 dB. The isolations of more than 65 dB have been achieved between Rx and Tx filter.

• International Area Studies Review
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• v.22 no.3
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• pp.255-292
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• 2018

This paper evaluates the new food policy adopted by the European Union to enhance the food safety after the mad cow crisis occurred in 1990's. Newly introduced rules at the EU level are characterized by two features. Firstly, an important part of them have the form of Regulation which is a binding legislative to all member countries. Secondly, most of them are horizontally applied to the whole food industry, irrespective of their kinds of performance, hygiene or labelling. According to theoretical studies on this topic, any food safety regulation for solving adverse selection problem or reducing negative externality in food consumption should be fine-tuning depending on the concrete demand and costs conditions of the food sector concerned. In this theoretical perspective, the food safety laws introduced at EU level after mad cow crisis have been over-regulated for improving social welfare. The true motivation for the transfer of the policy competence on food safety to the Union level is political rather than economic. Our analysis with a political economic perspective shows that how the EU food regulations have been embraced not only by the governments of member countries, but also by diverse interest groups like food processor & distributors, consumers and agro-livestock groups, and that they have been used as protectionist purpose specially against non-member developing countries. Taking into account the fact that the basic aim to form the Union is to establish a single market to enhance economic efficiency at the Union level, the EU is required to adopt some policy actions to reduce negative effects of too restrictive food safety regulations.

• Industry Promotion Research
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• v.7 no.1
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• pp.59-74
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• 2022

There are three main ways to interpret Zhouyi(周易). The first is to interpret it as a number, the second is to interpret it as an image symbolized by the Gwae(卦), and the third is to interpret it as the moral reason contained in it. Although YulRyeo(律呂) is not as widely known as Zhouyi, its use in ancient times was the same as that of the main character. First, the mathematical analysis method using the three-pronged method for tuning musical instruments, second, the symbolic interpretation using the musical meaning symbolized by YulRyeo, and third, the applied interpretation method that expands to the moral reason contained in YulRyeo. The purpose of this thesis is to organize the dictionary meaning of YulRyeo and various meanings of ancient YulRyeo. In addition, by studying ancient literature on the meaning of YulRyeo's magic spell mechanics(術數易學) and Naepeum and Five Elements(納音五行), which is the origin of Gobeop Myongriology, I classify and interpret them in detail. and to find ways to apply it to Myongriology. It is hoped that this study will give a more in-depth understanding of YulRyeo and will be of little help to related studies such as the mechanics of magic and Myongriology studies in the future.

• Journal of The Korean Association of Information Education
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• v.26 no.3
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• pp.197-207
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• 2022

In this paper, we develop a machine learning based block code generation and recommendation model for the purpose of reducing cognitive load of learners during coding education that learns the learner's block that has been made in the block programming environment using natural processing model and fine-tuning and then generates and recommends the selectable blocks for the next step. To develop the model, the training dataset was produced by pre-processing 50 block codes that were on the popular block programming language web site 'Entry'. Also, after dividing the pre-processed blocks into training dataset, verification dataset and test dataset, we developed a model that generates block codes based on LSTM, Seq2Seq, and GPT-2 model. In the results of the performance evaluation of the developed model, GPT-2 showed a higher performance than the LSTM and Seq2Seq model in the BLEU and ROUGE scores which measure sentence similarity. The data results generated through the GPT-2 model, show that the performance was relatively similar in the BLEU and ROUGE scores except for the case where the number of blocks was 1 or 17.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.309-328
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• 2022

This study empirically analyzed a Korean pre-trained language models (PLMs) designed for natural language generation. The performance of two PLMs - BART and GPT - at the task of abstractive text summarization was compared. To investigate how performance depends on the characteristics of the inference data, ten different document types, containing six types of informational content and creation content, were considered. It was found that BART (which can both generate and understand natural language) performed better than GPT (which can only generate). Upon more detailed examination of the effect of inference data characteristics, the performance of GPT was found to be proportional to the length of the input text. However, even for the longest documents (with optimal GPT performance), BART still out-performed GPT, suggesting that the greatest influence on downstream performance is not the size of the training data or PLMs parameters but the structural suitability of the PLMs for the applied downstream task. The performance of different PLMs was also compared through analyzing parts of speech (POS) shares. BART's performance was inversely related to the proportion of prefixes, adjectives, adverbs and verbs but positively related to that of nouns. This result emphasizes the importance of taking the inference data's characteristics into account when fine-tuning a PLMs for its intended downstream task.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.35-43
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• 2021

Recently, there has been a growing interest in zero-shot cross-lingual transfer, which leverages cross-lingual language models (CLLMs) to perform downstream tasks that are not trained in a specific language. In this paper, we point out the limitations of the data-centric aspect of quality estimation (QE), and perform zero-shot cross-lingual transfer even in environments where it is difficult to construct QE data. Few studies have dealt with zero-shots in QE, and after fine-tuning the English-German QE dataset, we perform zero-shot transfer leveraging CLLMs. We conduct comparative analysis between various CLLMs. We also perform zero-shot transfer on language pairs with different sized resources and analyze results based on the linguistic characteristics of each language. Experimental results showed the highest performance in multilingual BART and multillingual BERT, and we induced QE to be performed even when QE learning for a specific language pair was not performed at all.

• Journal of The Korean Association For Science Education
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• v.43 no.6
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• pp.573-582
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• 2023

This study aimed to explore the potential use of artificial intelligence in science education for gifted students by analyzing the structure of abstracts written by students at a gifted science academy and comparing the performance of various elements extracted using AI. The study involved an analysis of 263 graduation theses from S Science High School over five years (2017-2021), focusing on the frequency and types of background, objectives, methods, results, and discussions included in their abstracts. This was followed by an evaluation of their accuracy using AI classification methods with fine-tuning and prompts. The results revealed that the frequency of elements in the abstracts written by gifted students followed the order of objectives, methods, results, background, and discussions. However, only 57.4% of the abstracts contained all the essential elements, such as objectives, methods, and results. Among these elements, fine-tuned AI classification showed the highest accuracy, with background, objectives, and results demonstrating relatively high performance, while methods and discussions were often inaccurately classified. These findings suggest the need for a more effective use of AI, through providing a better distribution of elements or appropriate datasets for training. Educational implications of these findings were also discussed.

• Korean Journal of Radiology
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• v.24 no.6
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• pp.541-552
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• 2023

Objective: Detection of pneumoperitoneum using abdominal radiography, particularly in the supine position, is often challenging. This study aimed to develop and externally validate a deep learning model for the detection of pneumoperitoneum using supine and erect abdominal radiography. Materials and Methods: A model that can utilize "pneumoperitoneum" and "non-pneumoperitoneum" classes was developed through knowledge distillation. To train the proposed model with limited training data and weak labels, it was trained using a recently proposed semi-supervised learning method called distillation for self-supervised and self-train learning (DISTL), which leverages the Vision Transformer. The proposed model was first pre-trained with chest radiographs to utilize common knowledge between modalities, fine-tuned, and self-trained on labeled and unlabeled abdominal radiographs. The proposed model was trained using data from supine and erect abdominal radiographs. In total, 191212 chest radiographs (CheXpert data) were used for pre-training, and 5518 labeled and 16671 unlabeled abdominal radiographs were used for fine-tuning and self-supervised learning, respectively. The proposed model was internally validated on 389 abdominal radiographs and externally validated on 475 and 798 abdominal radiographs from the two institutions. We evaluated the performance in diagnosing pneumoperitoneum using the area under the receiver operating characteristic curve (AUC) and compared it with that of radiologists. Results: In the internal validation, the proposed model had an AUC, sensitivity, and specificity of 0.881, 85.4%, and 73.3% and 0.968, 91.1, and 95.0 for supine and erect positions, respectively. In the external validation at the two institutions, the AUCs were 0.835 and 0.852 for the supine position and 0.909 and 0.944 for the erect position. In the reader study, the readers' performances improved with the assistance of the proposed model. Conclusion: The proposed model trained with the DISTL method can accurately detect pneumoperitoneum on abdominal radiography in both the supine and erect positions.