• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.287-293
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• 2005

Predicting RNA secondary structure as accurately as possible is very important in functional analysis of RNA molecules. However, different prediction methods and related parameters including terminal GU pair of helices, minimum length of helices, and free energy systems often give different prediction results for the same RNA sequence. Then, which structure is more important than the others? i.e. which combinations of the methods and related parameters are the optimal? In order to investigate above problems, first, three prediction methods, namely, random stacking of helical regions (RS), helical regions distribution (HD), and Zuker's minimum free energy algorithm (ZMFE) were compared by taking 1139 tRNA sequences from Rfam database as the samples with different combinations of parameters. The optimal parameters are derived. Second, Zuker's dynamic programming method for prediction of RNA secondary structure was revised using the above optimal parameters and related software BJRNAFold was developed. Third, the effects of short-range interaction were studied. The results indicated that the prediction accuracy would be improved much if proper short-range factor were introduced. But the optimal short-range factor was difficult to determine. A user-adjustable parameter for short-range factor was introduced in BJRNAFold software.

• 한국정보통신학회논문지
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• 제7권4호
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• pp.758-766
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• 2003

본 논문에서는 효율적인 비디오 데이터베이스를 구축하기 위하여 카메라와 객체 파라미터를 이용한 트리-기반 계층형 영상 모자이크 시스템을 제시한다. 장면 전환 검출을 위하여 그레이-레벨 히스토그램 차이와 평균 명암도 차이를 이용한 방법을 제시하였다. 카메라 파라미터는 최소 사각형 오류 기법과 어파인 모델을 이용하여 측정하고, 두 입력 영상의 유사성을 측정하기 위하여 차영상을 이용한다. 또한 동적 객체는 매크로 블록 설정에 의하여 검색되고 영역 분할과 4-분할 탐색에 의하여 추출한다. 동적 객체의 표현은 동적 궤도 평가 함수에 의하여 수행되고 블러링을 통하여 부드럽고 완만한 모자이크 영상을 구축한다.

• 대한산업공학회지
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• 제24권2호
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• pp.297-309
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• 1998

Numerical parameters have been developed to diagnose L4/L5 disc patients during repetitive flexions and extensions. Electromyography(EMG) has been used to define the muscle excitation and movement cycle in this study. Twenty healthy subjects and twenty L4/L5 disc patients were recruited for the experiment. The subjective pain levels of patients were recorded as $3.7{\pm}1.6$ according to visual analogue scale where 10 was the maximum pain level. Variance ratio of motion cycle was suggested as a new parameter to examine the consistency of the trunk movement. The results indicated that the temporal EMG pattern such as peak time difference between Quadriceps and Hamstrings, the duration of coexcitation between Erector spinae and Rectus abdominis muscle pairs showed a statistically significant difference between healthy subjects and patients. Variance ratio of External oblique and Internal oblique also showed a statistically significant difference. It is expected that those results could be used for diagnosis by building a database for various back pain patients and healthy subjects. This method can eventually help physicians for early diagnosis and prevention of low back disorders.

• Computers and Concrete
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• 제16권1호
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• pp.99-123
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• 2015

In this study, structural vulnerability of reinforced concrete moment resisting frames (RC-MRFs) by considering the Iran-specific characteristics is investigated to manage the earthquake risk in terms of multicomponent seismic excitations. Low and medium rise RC-MRFs, which constitute approximately 80-90% of the total buildings stock in Iran, are focused in this fragility-based assessment. The seismic design of 3-12 story RC-MRFs are carried out according to the Iranian Code of Practice for Seismic Resistant Design of Buildings (Standard No. 2800), and the analytical models are formed accordingly in open source nonlinear platforms. Frame structures are categorized in three subclasses according to the specific characteristics of construction practice and the observed seismic performance after major earthquakes in Iran. Both far and near fields' ground motions have been considered in the fragility estimation. An optimal intensity measure (IM) called Sa, avg and beta probability distribution were used to obtain reliable fragility-based database for earthquake damage and loss estimation of RC buildings stock in urban areas of Iran. Nonlinear incremental dynamic analyses by means of lumped-parameter based structural models have been simulated and performed to extract the fragility curves. Approximate confidence bounds are developed to represent the epistemic uncertainties inherent in the fragility estimations. Consequently, it's shown that including vertical ground motion in the analysis is highly recommended for reliable seismic assessment of RC buildings.

• 대한의용생체공학회:의공학회지
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• 제30권4호
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• pp.294-305
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• 2009

The bio signals essentially have different characteristics in each person. And the main purpose of automatic diagnosis algorithm based on bio signals focuses on discriminating differences of abnormal state from personal differences. In this paper, we propose automatic ECG diagnosis algorithm which discriminates normal heart beats from premature ventricular contraction using optimization of wavelet parameterization to solve that problem. The proposed algorithm optimizes wavelet parameter to let energy of signal be concentrated on specific scale band. We can reduce the personal differences and consequently highlight the differences coming from arrhythmia via this process. The proposed algorithm using ELM as a classifier show high discrimination performance between normal beat and PVC. From the experimental results on MIT-BIH arrhythmia database the performances of the proposed algorithm are 98.1% in accuracy, 93.0% in sensitivity, 96.4% in positive predictivity, and 0.8% in false positive rate. This results are similar or higher then results of existing researches in spite of small human intervention.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.536-538
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• 2006

The most important factor of mobile robot is to build a map for surrounding environment and estimate its localization. This paper proposes a real-time localization and map building method through 3-D reconstruction using scale invariant feature from monocular camera. Mobile robot attached monocular camera looking wall extracts scale invariant features in each image using SIFT(Scale Invariant Feature Transform) as it follows wall. Matching is carried out by the extracted features and matching feature map that is transformed into absolute coordinates using 3-D reconstruction of point and geometrical analysis of surrounding environment build, and store it map database. After finished feature map building, the robot finds some points matched with previous feature map and find its pose by affine parameter in real time. Position error of the proposed method was maximum. 8cm and angle error was within $10^{\circ}$.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권2호
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• pp.167-172
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• 2006

As ubiquitous devices are fast spreading, the communication problem between humans and these devices is on the rise. The use of context is important in interactive application such as handhold and ubiquitous computing. Context is not crisp data, so it is necessary to introduce the fuzzy concept. The proxity relation is represented by the degree of closeness or similarity between data objects of a scalar domain. A context manager of context-awareness system evaluates imprecise queries with the proximity relations. in this paper, a systematic proximity elicitation method are proposed. The proposed generation method is simple and systematic. It is based on the well-known fuzzy set theory and applicable to the real world applications because it has tuning parameter and weighting factor. The proposed representations of proximity relation is more efficient than the ordinary matrix representation since it reflects some properties of a proximity relation to save space. We show an experiments of quantitative calculate for the proximity relation. And we analyze the time complexity and the space occupancy of the proposed representation method.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 2010년도 춘계국제학술대회
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• pp.235-247
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• 2010

Introduction of ICE(Integrated Collaboration Environment) has a great effect on corporate performance. In particular, it is expected that information sharing and collaboration among transaction partners will be an important factor which mediates ICE and its performance. Under such a background, this research intends to identify the influence of ICE by manufacturing industry on corporate performance through role of the parameter of information sharing and collaboration. The result of this research may be summed up as follows: ICE promotes information sharing and collaboration among enterprises, it accelerates integration of supply chain network among enterprises and cooperation. In particular, ICE has a great effect on information sharing. And information sharing has a direct effect on collaboration and performance. However, when we classify corporate performance into the "performance due to introduction", which is direct performance, and the "overall performance", which is indirect performance, the result of this research is as follows: information sharing has a great effect on the performance due to introduction, but does not have a meaningful effect on indirect performance. On the other hand, collaboration does not have any effect on the performance due to introduction, but has a meaningful effect on the overall performance, which is indirect performance. It is necessary to study and analyze additional this result in future.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집B
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• pp.288-293
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• 2001

A critical heat flux (CHF) prediction method using an artificial neural network (ANN) was evaluated for application to the high-heat-flux (HHF) subcooled flow boiling. The developed ANN predictions were compared with the experimental database consisting of a total of 3069 CHF data points. Also, the prediction performance by the ANN was compared with those by mechanistic models and a look up table technique. The parameter ranges of the experimental data are: $0.33{\leq}D{\leq}37.5mm$, $0.002{\leq}L{\leq}4m$, $0.37{\leq}G{\leq}134Mg/m^2s$, $0.1{\leq}P{\leq}20MPa$, $50\leq{\Delta}h_{sub,in}\leq1660kJ/kg$, and $1.1{\leq}q_{CHF}\leq276MW/m^2$. $276MW/m^2$. It was found that 91.5% of the total data points were predicted within $a{\pm}20%$ error band, which showed the best prediction performance among the existing CHF prediction methods considered.

• Structural Engineering and Mechanics
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• 제63권2호
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• pp.237-249
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• 2017

The Self-Organization Feature Map as an unsupervised network is very widely used these days in engineering science. The applied network in this paper is the Self Organization Feature Map with constant weights which includes Kohonen Network. In this research, Reinforced Concrete Shear Wall buildings with different stories and heights are analyzed and a database consisting of measured fundamental periods and characteristics of 78 RC SW buildings is created. The input parameters of these buildings include number of stories, height, length, width, whereas the output parameter is the fundamental period. In addition, using Genetic Algorithm, the structure of the Self-Organization Feature Map algorithm is optimized with respect to the numbers of layers, numbers of nodes in hidden layers, type of transfer function and learning. Evaluation of the SOFM model was performed by comparing the obtained values to the measured values and values calculated by expressions given in building codes. Results show that the Self-Organization Feature Map, which is optimized by using Genetic Algorithm, has a higher capacity, flexibility and accuracy in predicting the fundamental period.