• Journal of Digital Convergence
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• v.14 no.11
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• pp.233-240
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• 2016

Information system development projects, have a mechanism for many of the costs generated by a variety of risk factors. In general, the probability that the software project of the information system is carried out successfully in the delivery time is very low. This prediction of a formal cost is needed as the most important factor since it can prevent the project from being failed. However, objectivity of most of the project scale calculation during the calculation criteria is insufficient. Further, it is the actual situation that the management of the base line is not properly made during the project. Therefore, in this paper, we propose a model to calculate the number of steps it takes to develop on the basis of a methodology in an attempt to overcome the limitation of being unpractical in the early stage of the information system development project. It is expected to be a tool to estimate the effort and cost required by the information system development business through these convergence proposals model.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.37-43
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• 2021

This study proposed an effective automatic classification technique to identify dropout patterns of university students, and based on this, an intelligent recommender system to prevent dropouts. To this end, 1) a data processing method to improve the performance of machine learning was proposed based on actual enrollment/dropout data of university students, and 2) performance comparison experiments were conducted using five types of machine learning algorithms. 3) As a result of the experiment, the proposed method showed superior performance in all algorithms compared to the baseline method. The precision rate of discrimination of enrolled students was measured to be up to 95.6% when using a Random Forest(RF), and the recall rate of dropout students was measured to be up to 80.0% when using Naive Bayes(NB). 4) Finally, based on the experimental results, a method for using a counseling recommender system to give priority to students who are likely to drop out was suggested. It was confirmed that reasonable decision-making can be conducted through convergence research that utilizes technologies in the IT field to solve the educational issues, and we plan to apply various artificial intelligence technologies through continuous research in the future.

• Journal of Climate Change Research
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• v.4 no.1
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• pp.63-75
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• 2013

The purpose of this study is to analyze the green-house gas emission reduction of the pump scheduling system applied to the water-supply facilities in all objectivity with AMS-II.C/Version 13 in CDM methodology. To calculate the baseline and project emission in Paldang Pumping Station (III) the data about water flow, water level, electricity consumption, etc. before and after the implementation of project was used. This study considers internal facility (mostly for lighting) electricity consumption and grid loss in order to get more accurate emission reductions. The methodology used in this study will be able to apply to different energy improvement techniques to calculate emission reductions in water supply facilities.

• Korean Journal of Cognitive Science
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• v.34 no.3
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• pp.197-226
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• 2023

Generative Text Summarization is one of the Natural Language Processing tasks. It generates a short abbreviated summary while preserving the content of the long text. ROUGE is a widely used lexical-overlap based metric for text summarization models in generative summarization benchmarks. Although it shows very high performance, the studies report that 30% of the generated summary and the text are still inconsistent. This paper proposes a methodology for evaluating the performance of the summary model without using the correct summary. AggreFACT is a human-annotated dataset that classifies the types of errors in neural text summarization models. Among all the test candidates, the two cases, generation summary, and when errors occurred throughout the summary showed the highest correlation results. We observed that the proposed evaluation score showed a high correlation with models finetuned with BART and PEGASUS, which is pretrained with a large-scale Transformer structure.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.253-259
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• 2024

This paper proposes a new speech enhancement model based on a complex nested U-Net with a dual-branch decoder. The proposed model consists of a complex nested U-Net to simultaneously estimate the magnitude and phase components of the speech signal, and the decoder has a dual-branch decoder structure that performs spectral mapping and time-frequency masking in each branch. At this time, compared to the single-branch decoder structure, the dual-branch decoder structure allows noise to be effectively removed while minimizing the loss of speech information. The experiment was conducted on the VoiceBank + DEMAND database, commonly used for speech enhancement model training, and was evaluated through various objective evaluation metrics. As a result of the experiment, the complex nested U-Net-based speech enhancement model using a dual-branch decoder increased the Perceptual Evaluation of Speech Quality (PESQ) score by about 0.13 compared to the baseline, and showed a higher objective evaluation score than recently proposed speech enhancement models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.126-134
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• 2017

There have been numerous studies on extracting the R-peak from electrocardiogram (ECG) signals. However, most of the detection methods are complicated to implement in a real-time portable electrocardiograph device and have the disadvantage of requiring a large amount of calculations. R-peak detection requires pre-processing and post-processing related to baseline drift and the removal of noise from the commercial power supply for ECG data. An adaptive filter technique is widely used for R-peak detection, but the R-peak value cannot be detected when the input is lower than a threshold value. Moreover, there is a problem in detecting the P-peak and T-peak values due to the derivation of an erroneous threshold value as a result of noise. We propose a robust R-peak detection algorithm with low complexity and simple computation to solve these problems. The proposed scheme removes the baseline drift in ECG signals using an adaptive filter to solve the problems involved in threshold extraction. We also propose a technique to extract the appropriate threshold value automatically using the minimum and maximum values of the filtered ECG signal. To detect the R-peak from the ECG signal, we propose a threshold neighborhood search technique. Through experiments, we confirmed the improvement of the R-peak detection accuracy of the proposed method and achieved a detection speed that is suitable for a mobile system by reducing the amount of calculation. The experimental results show that the heart rate detection accuracy and sensitivity were very high (about 100%).

• Journal of the Korean Society for Precision Engineering
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• v.30 no.2
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• pp.206-215
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• 2013

In recent years, many companies have heavily invested in introducing production informatization systems in order to strengthen the competitiveness and to satisfy consumer's desires in quickly changing market environment. However, it is not effective due to the lack of understanding of systems and of non-existence of an optimal system for each company. Therefore, in this paper, manufacturing companies were classified according to its properties; size of the firm, type of business, production method and job production. After that, a model has been built to calculate the production informatization level, and it has been applied to 450 companies. Results of 450 surveys would be the base for figuring out strategies of introducing the production informatization to the companies which are wishing to build production informatization systems. Finally, Developed in this paper rule base system refer customized guideline to company that wants to adapt production information system.

• Journal of the Korean Vacuum Society
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• v.20 no.2
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• pp.146-154
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• 2011

The adhesive-tape of a liquid leak film sensor including the alarm system is developed. The sensing film is composed of three layers such as base film layer, conductive line layer, and protection film layer. The thickness of film is 300~500 um, the width is 3.55 cm, and the unit length is 200 m. On the conductive line layer, three conducting lines and one resistive line are formulated by the electronic printing method with a conducting ink of silver-nano size. When a liquid leaks for the electricity to be conducted between the conductive line and the resistive line, the position of leakage is monitored by measuring the voltage varied according to the change of resistance between two lines. The error range of sensing position of 200 m film sensor is ${\pm}1m$.

• Convergence Security Journal
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• v.5 no.1
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• pp.19-27
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• 2005

This paper presents the content regarding electronic medical examination chart and data processing for efficient medical examination and fast treatment by realizing remote medical examination system of mutual conversation type among 3 parties(patient, doctor, pharmacist) on internet base, and establishment of database enabled system integration for efficient data processing in both on-line and off-line mode by interconnecting ASP and SQL on IIS 4.0 web server, consultation between patient and doctor, medical examination on off-line mode, transmission of prescription sheet to the pharmacist designated by patient, preparation of medicine, semieternal storage of medical examination data owing to storage and check of medical examination data, more accurate medical examination and prescription using this medical examination data by patient and doctor, and so on. And, data processing between doctor and pharmacist is differently performed based on class such as general member and charge member, and service access right pursuant to this is endowed, so that certification of each member must follow by all means.

• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.1-10
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• 2012

This paper proposes design space exploration methodology of many-core processors including multimedia specific instructions to support high-performance and low power ultrasound imaging for portable devices. To explore the impact of multimedia instructions, we compare programs using multimedia instructions and baseline programs with a same many-core processor in terms of execution time, energy efficiency, and area efficiency. Experimental results using a $256{\times}256$ ultrasound image indicate that programs using multimedia instructions achieve 3.16 times of execution time, 8.13 times of energy efficiency, and 3.16 times of area efficiency over the baseline programs, respectively. Likewise, programs using multimedia instructions outperform the baseline programs using a $240{\times}320$ image (2.16 times of execution time, 4.04 times of energy efficiency, 2.16 times of area efficiency) as well as using a $240{\times}400$ image (2.25 times of execution time, 4.34 times of energy efficiency, 2.25 times of area efficiency). In addition, we explore optimal PE architecture of many-core processors including multimedia instructions by varying the number of PEs and memory size.