• Journal of KIISE
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• v.42 no.1
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• pp.107-113
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• 2015

In a database system, updates on pages that are made by a transaction should be stored in a secondary storage before the commit is complete. Generic secondary storages have volatile DRAM caches to hide long latency for non-volatile media. However, as logs that are only written to the volatile DRAM cache don't ensure durability, logging latency cannot be hidden. Recently, a flash SSD with capacitor-backed DRAM cache was developed to overcome the shortcoming. Storage devices, like those with a non-volatile cache, will increase transaction throughput because transactions can commit as soon as the logs reach the cache. In this paper, we analyzed performance in terms of transaction throughput when the SSD with capacitor-backed DRAM cache was used as log storage. The transaction throughput can be improved over three times, by committing right after storing the logs to the DRAM cache, rather than to a secondary storage device. Also, we showed that it could acquire over 73% of the ideal logging performance with proper tuning.

• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.247-258
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• 2003

Principal component analysis (PCA) based algorithms form the basis of numerous algorithms and studies in the face recognition literature. PCA is a statistical technique and its incorporation into a face recognition system requires numerous design decisions. We explicitly take the design decisions by in-troducing a generic modular PCA-algorithm since some of these decision ate not documented in the literature We experiment with different implementations of each module, and evaluate the different im-plementations using the September 1996 FERET evaluation protocol (the do facto standard method for evaluating face recognition algorithms). We experiment with (1) changing the illumination normalization procedure; (2) studying effects on algorithm performance of compressing images using JPEG and wavelet compression algorithms; (3) varying the number of eigenvectors in the representation; and (4) changing the similarity measure in classification process. We perform two experiments. In the first experiment, we report performance results on the standard September 1996 FERET large gallery image sets. The result shows that empirical analysis of preprocessing, feature extraction, and matching performance is extremely important in order to produce optimized performance. In the second experiment, we examine variations in algorithm performance based on 100 randomly generated image sets (galleries) of the same size. The result shows that a reasonable threshold for measuring significant difference in performance for the classifiers is 0.10.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.3
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• pp.555-562
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• 2008

In this paper we proposed a practical low-power design technique using clock-gating in RTL. An efficient low-power methodology is that a high-level designer analyzes a generic system and designs a controller for clock-gating. Also the desirable flow is to derive clock-gating in normal synthesis process by synthesis tool than to insert directly gate to clock line. If low-power is considered in coding process, clock is gated in coding process. If not considered, after analyzing entire operation. clock is Bated in periods of holding data. After analyzing operation for clock-gating, a controller was designed for it, and then a low-power circuit was generated by synthesis tool. From result, we identified that the consumed power of register decreased from 922mW to 543mW, that is the decrease rate is 42%. In case of synthesizing the test circuit using synthesizer of Power Theater, it decreased from 322mW to 208mW (36.5% decrease).

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.163-171
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• 2005

I have developed a processor for synthetic aperture radar (SAR) raw data compression using range-doppler algorithm for educational purpose. The program realized a generic SAR focusing algorithm so that it can deal with any SAR system if the specification is known. It can run efficiently on a low-cost computer by selecting minimum size out of a whole dataset, and can produce intermediate images during the process. Especially, the program is designed for educational purpose in such a way that Doppler centroid and azimuth ambiguity can be determined graphically by the user. By distributing the source code and the algorithm to public, I intend to maximize the educational effect on understanding and utilizing SAR data. This paper introduces the principle of SAR focusing algorithm embedded on the eSAR processor and shows an example of data processing using ERS-1 raw data.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1187-1198
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• 2021

Sea wind isrecently drawing attraction as one of the sources of renewable energy. Thisstudy describes a new method to produce a 10 m resolution sea wind field using Sentinel-1 images and low-resolution NWP (Numerical Weather Prediction) data with artificial intelligence technique. The experiment for the South East coast in Korea, 2015-2020,showed a 40% decreased MAE (Mean Absolute Error) than the generic CMOD (C-band Model) function, and the CC (correlation coefficient) of our method was 0.901 and 0.826, respectively, for the U and V wind components. We created 10m resolution sea wind maps for the study area, which showed a typical trend of wind distribution and a spatially detailed wind pattern as well. The proposed method can be applied to surveying for wind power and information service for coastal disaster prevention and leisure activities.

• Journal of Korean Medicine for Obesity Research
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• v.19 no.1
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• pp.12-23
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• 2019

Objectives: Obesity is associated with a high mortality risk and impairment in health-related quality of life (HRQOL). The aim of this article is to examine the impact of weight loss on HRQOL and which questionnaires sensitively reflect weight loss effects on HRQOL. Methods: PubMed, Scopus, Research Information Sharing Service, and Korean Studies Information Service System were searched for the studies related to weight loss and HRQOL, published from 2009 to 2018. A total of 28 studies were eligible for inclusion. HRQOL results after weight loss from selected studies were classified and reported according to questionnaires. Results: Twenty-two studies reported statistically significant HRQOL improvements after weight loss and especially, all of studies with weight loss of more than 5% reported HRQOL improvements. HRQOL questionnaires were classified as generic, obesity-related and depression questionnaires. The most commonly used questionnaires were Short-Form health survey 36 (SF-36), Impact of Weight on Quality Life-Lite (IWQOL-Lite) and Beck Depression Inventory (BDI) respectively. SF-36 had a tendency to reflect physical health. IWQOL-Lite score was tended to be changed sensitively according to weight change. Depression questionnaires including BDI reported improvement of depression while mental aspects of SF-36 not changed in same studies. Conclusions: Improvements of HRQOL were noted in studies with weight loss of more than 5%. The main questionnaires for evaluating HRQOL were SF-36, IWQOL-Lite and BDI. It is suggested to use these questionnaires together for evaluating multiple aspects of impact of weight loss on HRQOL.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.817-824
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• 2019

We propose an ATR (Adaptive Tone Reservation) scheme based on clipping noise for PAPR (Peak-to-Average Power Ratio) reduction of OFDM (Orthogonal Frequency Division Multiplexing) signals. The proposed scheme is composed of three steps: clipping, tone selection, and TR procedures. In the first step, the peak samples in the IFFT (Inverse Fast Fourier Transform) outputs are scaled down by clipping. In the second step, the sub-carrier position where the power of the clipping noise is the maximum, is selected. Finally, the generic TR procedure is performed. Simulation results show that the proposed scheme does not require all the possible combinations for the original TR procedures, while maintaining the PAPR reduction performance.

• Journal of English Language & Literature
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• v.55 no.4
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• pp.567-596
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• 2009

A staple of feminist literary anthologies which was instrumental in reevaluating the writer Susan Glaspell, Trifles(1916) has received numerous comments from feminist scholars so far. Most of them tend to concentrate on the themes of female solidarity and justice challenging the androcentric system of law and order. Lacking in the plethora of thematic approaches to the play's feminist subject, however, are formal analyses considering the way in which the play's generic form assists in communicating such thematic concerns of feminism. An alternative to the typical scenario at the courtroom whose mistreatment of women must have loomed large to the young Glaspell as she revisited the old trial of a midwestern murderess which she had covered as a journalist for a local newspaper in Iowa, Trifles serves as a corrective to the courtroom dynamics offering a 'dramatic justice' as opposed to a strictly legal procedure. What this article discovers at the heart of this dramatic justice is the celebration of the unsayable, or what Wolfgang Iser termed negativity, of women's experience which has no room for reflection in the legal discourse at the courtroom tyrannized by the sayable and the evident. Examining how the dramatic form of Trifles gives a voice to the unsayable of woman's experience, which can not be properly represented at the courtroom governed by the straightforward and definitive male rhetoric, the article argues that the play is a better form than its fictional adaptation "A Jury of Her Peers"(1917) in that it syntactically suppresses the monopolizing operation of the verbal by giving precedence to the scenic and non-verbal which is constituted of setting, props, gesture and eye contacts. As a theoretical frame of reference with which to examine the modes of the unsayable in the play the article brings the concept of 'negativity,' defined by Iser as textual effects or modes of the unspeakable and unsaid, into the discussion of the taciturnity of the absent heroine and the non-verbal representation of drama.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.312-320
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• 2023

Recently, there has been an increasing attempt to replace defect detection inspections in the manufacturing industry using deep learning techniques. However, obtaining substantial high-quality labeled data to enhance the performance of deep learning models entails economic and temporal constraints. As a solution for this problem, semi-supervised learning, using a limited amount of labeled data, has been gaining traction. This study assesses the effectiveness of semi-supervised learning in the defect detection process of manufacturing using the MixMatch algorithm. The MixMatch algorithm incorporates three dominant paradigms in the semi-supervised field: Consistency regularization, Entropy minimization, and Generic regularization. The performance of semi-supervised learning based on the MixMatch algorithm was compared with that of supervised learning using defect image data from the metal casting process. For the experiments, the ratio of labeled data was adjusted to 5%, 10%, 25%, and 50% of the total data. At a labeled data ratio of 5%, semi-supervised learning achieved a classification accuracy of 90.19%, outperforming supervised learning by approximately 22%p. At a 10% ratio, it surpassed supervised learning by around 8%p, achieving a 92.89% accuracy. These results demonstrate that semi-supervised learning can achieve significant outcomes even with a very limited amount of labeled data, suggesting its invaluable application in real-world research and industrial settings where labeled data is limited.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.499-505
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• 2015

Trend Impact Analysis(: TIA) is an advanced forecasting tool used in futures studies for identifying, understanding and analyzing the consequences of unprecedented events on future trends. An adaptive neuro-fuzzy inference system is a kind of artificial neural network that integrates both neural networks and fuzzy logic principles, It is considered to be a universal estimator. In this paper, we propose an advanced mechanism to generate more justifiable estimates to the probability of occurrence of an unprecedented event as a function of time with different degrees of severity using Adaptive Neuro-Fuzzy Inference System(: ANFIS). The key idea of the paper is to enhance the generic process of reasoning with fuzzy logic and neural network by adding the additional step of attributes simulation, as unprecedented events do not occur all of a sudden but rather their occurrence is affected by change in the values of a set of attributes. An ANFIS approach is used to identify the occurrence and severity of an event, depending on the values of its trigger attributes. The trigger attributes can be calculated by a stochastic dynamic model; then different scenarios are generated using Monte-Carlo simulation. To compare the proposed method, a simple simulation is provided concerning the impact of river basin drought on the annual flow of water into a lake.