• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.294-304
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• 2011

Enhancing continuous queries over data streams with temporal functions and predicates enriches the expressive power of those queries. While traditional continuous queries retrieve only the values of attributes, temporal continuous queries retrieve the valid time intervals of those values as well. Correctly evaluating such queries requires the coalescing of adjacent timestamps for value-equivalent tuples prior to evaluating temporal functions and predicates. For many stream applications, the available computing resources may be too limited to produce exact query results. These limitations are commonly addressed through load shedding and produce approximated query results. There have been many load shedding mechanisms proposed so far, but for temporal continuous queries, the presence of coalescing makes theses existing methods unsuitable. In this paper, we propose a new accuracy metric and load shedding algorithm that are suitable for temporal query processing when memory is insufficient. The accuracy metric uses a combination of the Jaccard coefficient to measure the accuracy of attribute values and $\mathcal{PQI}$ interval orders to measure the accuracy of the valid time intervals in the approximate query result. The algorithm employs a greedy strategy combining two objectives reflecting the two accuracy metrics (i.e., value and interval). In the performance study, the proposed greedy algorithm outperforms a conventional random load shedding algorithm by up to an order of magnitude in its achieved accuracy.

• Korean Journal of Child Studies
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• v.13 no.2
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• pp.203-216
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• 1992

The purpose of this study was to investigate the utility of the Luria-Nebraska Battery-Children's Revision (LNNB-CR) in the clinical situation in Korea: LNNB-CR was applied clinically in order to examine how well it differentiates brain damaged children from normals. Subjects were 30 children with the average age of 10 years. Among them 15 were diagnosed as the 'brain damaged' group, and the remaining 15 were normal. All subjects of the two groups were tested on all items in accordance with LNNB-CR manual. Data were analyzed by percentage, correlation coefficient, and t-test. The results were (1) the degree of consistency between testers averaged 97.2％ which confirmed the stability of the scoring system. (2) Split-half reliability was ranged from .75 on the Tactile Scale (C3) to .95 on the Memory Scale (C10). Thus, consistency of items within the scales appeared high. (3) Internal consistency reliability ranged from .74 on the Visual Scale (C4) to .98 on the Reading Scale (C9). Thus, the homogenity of items within the scales appeared high. (4) In the diagnostic discriminative power test between the two groups, both individual scales and total scores showed significant differences at the level of p<.001. (5) The discriminative power test between two groups on all items showed significant differences at the level of p<.05 or better in 126(85％) out of 149 items. These results are supportive of the diagnostic utility of the application of LNNB-CR to the clinical situation in Korea. However, extensive additional research is needed in order to prove its worth.

• Journal of the Korean Society of Physical Medicine
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• v.10 no.3
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• pp.47-55
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• 2015

PURPOSE: Stoke is one of most common disabling conditions and it is still lacking of measuring patient's functioning level. The aim of the study was to develop Korean language version of stroke impact scale 3.0. METHODS: Korean version of stroke impact scale 3.0 was developed in idiomatic modern Korean with a standard protocol of multiple forward and backward translations and an expert reviews to achieve equivalence with the original English version. Interviews with clinicians who were currently managing patients with stroke were also conducted for language evaluation. A reliability test was performed to make final adaptation using a pre-final version. To assess the reliability of the translated questionnaire, the intraclass correlation coefficient (ICC) was calculated for each domain of the scale. RESULTS: Thirty subjects (16 male, 14 female) aged from 20 to 75 years old participated to review the translated questionnaire. Reliability of each domain of the questionnaire was found to be good in strength (ICC=0.74), ADL (ICC=0.81), mobility (ICC=0.90), hand function (ICC=0.80) and social participation (ICC=0.79), communication (ICC=0.77) with total (ICC=0.76). However, domains of memory and thinking (ICC=0.66), and emotion (ICC=0.27) and showed poor reliability. CONCLUSION: This study indicates that the Korean version of SIS 3.0 was successfully developed. Future study needed for obtaining the validity of the Korean version of SIS 3.0.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.1
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• pp.149-159
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• 2009

The purposes of this study are to evaluate physical performance of metallic Jacquard fabrics, and to contribute to the research and development of the women's suit made of the metallic Jacquard fabrics. First, eight fabrics were woven with two kinds of warp yarns(nylon and rayon) and weft yarn blended with various contents(0, 7, 14, 21%) of metallic yarn. Second, the mechanical properties were measured by using the KES-FB system, and physical properties such as tensile strength, tearing strength, abrasion resistance, drape, pilling, snagging, degree of crease resistance, flexural stiffness, specular gloss, folding endurance and electrostatic propensity were measured. The results were as follows. As the metal fiber content increased, bending, shear, thickness and weight increased, which imply low recovery of wrinkles. It means that metallic Jacquard fabrics enable to use as a memory fabric. 7% metallic Jacquard fabric showed a low value at total hand value, but there was little change. As the metal fiber content increased, tensile strength, tearing strength, drape coefficient, specular gloss and flexural stiffness increased, however the degree of crease resistance, electrostatic propensity and folding endurance decreased. The metallic Jacquard fabrics were excellent in snagging, abrasion resistance and pilling.

• 한국정보디스플레이학회:학술대회논문집
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• 2000.01a
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• pp.115-116
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• 2000

Influence of sustain pulse-width on electro-luminous efficiency is experimentally investigated for surface discharge of AC-PDP. It is found that the firing voltage is decreased as the pulse-width is increased from $2\;{\mu}s$ to $8\;{\mu}s$ with sweeping frequency range of 10 kHz to 50 kHz. It has been found that the optimal sustain pulse-width is in the range of $3{\sim}4\;{\mu}s$ under driving frequency range of 30 kHz and 50 kHz, based on observations of memory coefficient, wall charge, and wall voltage as well as luminous efficiency.

• Applied Science and Convergence Technology
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• v.23 no.2
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• pp.72-82
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• 2014

Lithium-ion batteries (LIBs) have become popular electrochemical devices. Due to the unique advantages of LIBs in terms of high operating voltage, high energy density, low self-discharge, and absence of memory effects, their application range, which was primarily restricted to portable electronic devices, is now being extended to high-power applications, such as electric vehicles (EVs) and hybrid electrical vehicles (HEVs). Among various anode materials, $Li_4Ti_5O_{12}$ (LTO) is believed to be a promising anode material for high-power LIBs due to its advantages of high working potential and outstanding cyclic stability. However, the rate performance of LTO is limited by its intrinsically low electronic conductivity and poor $Li^+$ ion diffusion coefficient. This review highlights the recent progress in improving the rate performance of LTO through doping, compositing, and nanostructuring strategies.

• Smart Structures and Systems
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• v.24 no.4
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• pp.459-474
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• 2019

This study develops a novel recursive algorithm to significantly enhance the computation efficiency of a recently proposed stochastic subspace identification (SSI) methodology based on an alternative stabilization diagram. Exemplified by the measurements taken from the two investigated office buildings, it is first demonstrated that merely one sixth of computation time and one fifth of computer memory are required with the new recursive algorithm. Such a progress would enable the realization of on-line and almost real-time monitoring for these two steel framed structures. This recursive SSI algorithm is further applied to analyze 20 months of monitoring data and comprehensively assess the environmental effects. It is certified that the root-mean-square (RMS) response can be utilized as an excellent index to represent most of the environmental effects and its variation strongly correlates with that of the modal frequency. More detailed examination by comparing the monthly correlation coefficient discloses that larger variations in modal frequency induced by greater RMS responses would typically lead to a higher correlation.

• Geomechanics and Engineering
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• v.30 no.1
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• pp.75-91
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• 2022

This paper aims to show how to use several Machine Learning (ML) methods to estimate the TBM penetration rate systematically (TBM-PR). To this end, 1125 datasets including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), punch slope index (PSI), distance between the planes of weakness (DPW), orientation of discontinuities (alpha angle-α), rock fracture class (RFC), and actual/measured TBM-PRs were established. To evaluate the ML methods' ability to perform, the 5-fold cross-validation was taken into consideration. Eventually, comparing the ML outcomes and the TBM monitoring data indicated that the ML methods have a very good potential ability in the prediction of TBM-PR. However, the long short-term memory model with a correlation coefficient of 0.9932 and a route mean square error of 2.68E-6 outperformed the remaining six ML algorithms. The backward selection method showed that PSI and RFC were more and less significant parameters on the TBM-PR compared to the others.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.37-37
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• 2023

There is currently a high-accuracy modern forecasting method that uses machine learning algorithms or artificial neural network models to forecast river water levels or flowrate. As a result, this study aims to develop a mathematical model based on artificial neural networks to effectively forecast river water levels upstream of Tranh Culvert in North Vietnam's Bac Hung Hai irrigation system. The mathematical model was thoroughly studied and evaluated by using hydrological data from six gauge stations over a period of twenty-two years between 2000 and 2022. Furthermore, the results of the developed model were also compared to those of the long-short-term memory neural networks model. This study performs four predictions, with a forecast time ranging from 6 to 24 hours and a time step of 6 hours. To validate and test the model's performance, the Nash-Sutcliffe efficiency coefficient (NSE), mean absolute error, and root mean squared error were calculated. During the testing phase, the NSE of the model varies from 0.981 to 0.879, corresponding to forecast cases from one to four time steps ahead. The forecast results from the model are very reasonable, indicating that the model performed excellently. Therefore, the proposed model can be used to forecast water levels in North Vietnam's irrigation system or rivers impacted by tides.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.230-230
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• 2023

딥러닝 알고리즘 중 과거의 정보를 저장하는 문제(장기종속성 문제)가 있는 단순 RNN(Simple Recurrent Neural Network)의 단점을 해결한 LSTM(Long short-term memory)이 등장하면서 특정한 유역의 강우-유출 모형을 구축하는 연구가 증가하고 있다. 그러나 하나의 모형으로 모든 유역에 대한 유출을 예측하는 지역화 강우-유출 모형은 서로 다른 유역의 식생, 지형 등의 차이에서 발생하는 수문학적 행동의 차이를 학습해야 하므로 모형 구축에 어려움이 있다. 따라서, 본 연구에서는 국내 12개의 유역에 대하여 LSTM 기반 분포형 지역화 강우-유출 모형을 구축한 이후 강우 이외의 보조 자료에 따른 정확도를 살펴보았다. 국내 12개 유역의 7년 (2012.01.01-2018.12.31) 동안의 49개 격자(4km²)에 대한 10분 간격 레이더 강우, MODIS 위성 이미지 영상을 활용한 식생지수 (Normalized Difference Vegetation Index), 10분 간격 기온, 유역 평균 경사, 단순 하천 경사를 입력자료로 활용하였으며 10분 간격 유량 자료를 출력 자료로 사용하여 LSTM 기반 분포형 지역화 강우-유출 모형을 구축하였다. 이후 구축된 모형의 성능을 검증하기 위해 학습에 사용되지 않은 3개의 유역에 대한 자료를 활용하여 Nash-Sutcliffe Model Efficiency Coefficient (NSE)를 확인하였다. 식생지수를 보조 자료를 활용하였을 경우 제안한 모형은 3개의 검증 유역에 대하여 하천 흐름을 높은 정확도로 예측하였으며 딥러닝 모형이 위성 자료를 통하여 식생에 의한 차단 및 토양 침투와 같은 동적 요소의 학습이 가능함을 나타낸다.