• 대한기계학회논문집A
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• 제40권7호
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• pp.629-635
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• 2016

이 논문은 꽃잎들, 나비나 민들레 씨앗들과 같은 생물체 시스템의 불규칙한 운동을 파티클 필터링 이론에 근거하여 예측하고 추적하는 유용한 방법을 제안한다. 생물체 모사 시스템 설계에 있어서, 생체 시스템의 운동에 대한 관측과 생체 시스템 운동학에 대한 새로운 설계원리가 어떻게 자연스럽게 운동하는가에 대한 인상을 얻는데 중요하다. 공기 중에서 비행하는 꽃잎에 대한 시스템 모델링이 베이지안 확률 규칙을 사용하여 수행되었다. 실험결과는 제안된 방법이 공기의 난류로부터 유도된 랜덤한 외란이 있는 경우에도 잘 예측함을 보여준다.

• Fibers and Polymers
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• 제7권2호
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• pp.203-212
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• 2006

The purpose of this study was to examine the effects of the structural properties of plain knit fabrics on the subjective perception of textures, sensibilities, and preference among consumers. This study, then, aimed to provide useful information with respect to planning and designing knitted fabrics by predicting the subjective characteristics analyzed according to their structural properties. For this purpose, we employed statistical analysis tools, such as factor and regression analysis and an adaptive-network-based fuzzy inference system(ANFIS), thereby combining the merits of fuzzy and neural networks and presupposing a non-linear relationship. Through factor analysis, we also categorized the subjective textures into 'roughness', 'softness', 'bulkiness' and 'stretch-ability' with R2=70.32%: and categorized the sensibilities into 'Stable/Neat', 'Natural/Comfortable' and 'Feminine/Elegant' with R2=68.12%. We analyzed subjective textures, sensibilities, and preference with ANFIS, assuming non-linear relationships; consequently, we were able to generate three or four fuzzy rules using wool/rayon fiber content and loop length as input data. The textures of roughness and softness exhibited a linear relationship, but other subjective characteristics demonstrated a non-linear input-output relationship. Compared with linear regression analysis, the ANFIS exhibited had higher predictive power with respect to predicting subjective characteristics.

• Geomechanics and Engineering
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• 제10권3호
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• pp.269-284
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• 2016

Simplified techniques based on in situ testing methods are commonly used to assess seismic liquefaction potential. Many of these simplified methods were developed by analyzing liquefaction case histories from which the liquefaction boundary (limit state) separating two categories (the occurrence or non-occurrence of liquefaction) is determined. As the liquefaction classification problem is highly nonlinear in nature, it is difficult to develop a comprehensive model using conventional modeling techniques that take into consideration all the independent variables, such as the seismic and soil properties. In this study, a modification of the Multivariate Adaptive Regression Splines (MARS) approach based on Logistic Regression (LR) LR_MARS is used to evaluate seismic liquefaction potential based on actual field records. Three different LR_MARS models were used to analyze three different field liquefaction databases and the results are compared with the neural network approaches. The developed spline functions and the limit state functions obtained reveal that the LR_MARS models can capture and describe the intrinsic, complex relationship between seismic parameters, soil parameters, and the liquefaction potential without having to make any assumptions about the underlying relationship between the various variables. Considering its computational efficiency, simplicity of interpretation, predictive accuracy, its data-driven and adaptive nature and its ability to map the interaction between variables, the use of LR_MARS model in assessing seismic liquefaction potential is promising.

• 한국임상약학회지
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• 제3권1호
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• pp.15-20
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• 1993

The ability to precisely predict serum digoxin concentration using 7 published methods in a group of 50 patients was undertaken. Two methods of estimating creatinine clearance and two estimates of lean body weight were employed as input variables using the 7 dosing methods. TDX was used to determine the nadir SDCs(serum digoxin concentrations) in 50 in patients meeting predetermined study criteria. All patients, whose ages ranged 19-71 years, had steady-state digoxin levels, were in oral digoxin, and were free from liver dysfunction, thyroid dysfunction and renal failure. The correlation coefficients(r) of predicted versus observed SDCs were determined,. and mean error(ME) was determined for each method to reflect bias, respectively. No substantial differance in predictive reliabliity was evident among the methods studied in total group. Poor correlations existed between predicted and observed SDCs(r<0.4) and these correlations were not significantly affected by age and gender. But relatively higher correlation and lower ME was founded for the CHF group in Jelliffe method(r=0.5, p<0.05).

• 융합보안논문지
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• 제8권4호
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• pp.135-143
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• 2008

일반적인 HMI system은 원격 감시제어를 네트워크를 통하여 하고 있으나 기능이 제한 적이다. 본 논문에서는 산업용 HMI 시스템을 변형된 상태분할 알고리즘을 적용 하였다. 이 방법은, 미리 예상되는 질의어에 대한 데이터들을 갖고 모델링을 하였다. 그 결과, 모델링하는데 많은 시간이 절약되었고, 시스템을 안정적이고 정밀하게 구성하여 98.15%의 높은 인식률을 나타냈다. 음성 HMI 시스템을 산업용에 적용하여 인간이 직접적으로 활동할 수 없는 작업 환경에서도 산업용 기기들을 안정적으로 구동시킬 수 있다. HMI 시스템 엔진의 성능을 최적화하였다.

• 통합자연과학논문집
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• 제9권3호
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• pp.190-198
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• 2016

Xanthine Oxidase is an enzyme, which oxidizes hypoxanthine to xanthine, and xanthine to uric acid. It is widely distributed throughout various organsincluding the liver, gut, lung, kidney, heart, brain and plasma. It is involved in gout pathogenesis. In this study, we have performed Comparative Molecular Field Analysis (CoMSIA) on a series of 2-(indol-5-yl) thiazole derivatives as xanthine oxidase (XO) inhibitors to identify the structural variations with their inhibitory activities. Ligand based CoMSIA models were generated based on atom-by-atom matching alignment. In atom-by-atom matching, the bioactive conformation of highly active molecule 11 was generated using systematic search. Compounds were aligned using the bioactive conformation and it is used for model generation. Different CoMSIA models were generated using different alignments and the best model yielded across-validated $q^2$ of 0.698 with five components and non-cross-validated correlation coefficient ($r^2$) of 0.992 with Fisher value as 236.431, and an estimated standard error of 0.068. The predictive ability of the best CoMSIA models was found to be $r{^2}_{pred}$ 0.653. The study revealed the important structural features required for the biological activity of the inhibitors and could provide useful for the designing of novel and potent drugs for the inhibition of Xanthine oxidase.

• 통합자연과학논문집
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• 제10권3호
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• pp.141-147
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• 2017

Vascular endothelial growth factor (VEGF) is an important signaling protein involved in angiogenesis, which is the formation of new blood vessels from pre-existing vessels. Consequently, blocking of the vascular endothelial growth factor receptor (VEGFR-2) by small molecule inhibitors leads to the inhibition of cancer induced angiogenesis. In this study, we performed a two dimensional quantitative structure activity relationship (2D-QSAR) study of 38 N-Phenyl-N'-{4-(4-quinolyloxy) phenyl} urea derivatives as VEGFR-2 inhibitors based on hologram quantitative structure-activity (HQSAR). The model developed showed reasonable $q^2=0.521$ and $r^2=0.932$ values indicating good predictive ability and reliability. The atomic contribution map analysis of most active compound (compound 7) indicates that hydrogen and oxygen atoms in the side chain of ring A and oxygen atom in side chain of ring C contributes positively to the activity of the compounds. The HQSAR model developed and the atomic contribution map can serve as a guideline in designing new compounds for VEGFR-2 inhibition.

• 한국임상수의학회지
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• 제34권2호
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• pp.65-69
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• 2017

Thromboembolic complications are increasing in veterinary medicine. Thromboelastography (TEG) is a more comprehensive method for assessing the clotting process than standard plasma-based coagulation tests. This study compared the ability of TEG and standard coagulation tests to analyze the overall hemostatic state of dogs. The study involved 40 dogs with underlying diseases that predispose to hypercoagulability, including neoplasia, hyperadrenocorticism, immune-mediated diseases, gastrointestinal diseases, and protein-losing nephropathies and enteropathies, and 20 healthy dogs. Their overall hemostatic functional state was evaluated by TEG and routine coagulation assays, including activated partial thromboplastin time, prothrombin time, platelet count, and D-dimer concentration. TEG analysis showed significant differences in clot formation time, ${\alpha}$ angle, and maximum amplitude (MA) between diseased and control dogs (P < 0.001 each). Increased MA was the most frequent abnormality on TEG and was indicative of hypercoagulability. TEG was useful in detecting hemostatic dysfunction in dogs with diseases associated with hypercoagulability. Dogs with TEG tracings indicative of hypercoagulability are likely to be in procoagulant states. Future prospective studies are needed to evaluate whether TEG tracings indicative of hypercoagulability are predictive of thrombosis in dogs.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1516-1529
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• 2016

While global manufacturing is becoming more competitive due to variety of customer demand, increase in production cost and uncertainty in resource availability, the future ability of manufacturing industries depends upon the implementation of Smart Factory. With the convergence of new information and communication technology, Smart Factory enables manufacturers to respond quickly to customer demand and minimize resource usage while maximizing productivity performance. This paper presents the development of a big data analytics platform architecture for Smart Factory. As this platform represents a conceptual software structure needed to implement data-driven decision-making mechanism in shop floors, it enables the creation and use of diagnosis, prediction and optimization models through the use of data analytics and big data. The completion of implementing the platform will help manufacturers: 1) acquire an advanced technology towards manufacturing intelligence, 2) implement a cost-effective analytics environment through the use of standardized data interfaces and open-source solutions, 3) obtain a technical reference for time-efficiently implementing an analytics modeling environment, and 4) eventually improve productivity performance in manufacturing systems. This paper also presents a technical architecture for big data infrastructure, which we are implementing, and a case study to demonstrate energy-predictive analytics in a machine tool system.

• International Journal of Advanced Culture Technology
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• 제9권2호
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• pp.18-31
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• 2021

The purpose of the present study was to present evidence for driving interventions for the elderly by conducting programs that can improve visual perception and cognitive function in a driving simulator for elderly drivers and analyse their effects. Three elderly subjects who were 65 years or older, did not have physical and cognitive impairments, and were able to drive themselves participated in the present study. A total of 12 intervention sessions, of which subjects participated in 10 sessions of nine different visual perception and cognitive function programs available in a driving simulator, were conducted and pre- and post-program assessments were conducted (two assessments in total). The assessments included the evaluation of visual perception, frontal lobe function, concentration, safe driving behaviour, and self-efficacy. The results showed positive effects of the driving simulator program on the visual perception, frontal lobe function, concentration, safe driving behaviour, and self-efficacy of all subjects. Changes in the simulator results showed remarkable improvement in the response evaluation, judgment evaluation, and predictive power evaluation, but showed difficulties in interference tasks and depth perception in common. The results showed positive effects of driving simulator training on the driving ability of the elderly, and consistent provision of such training is expected to improve the quality of life of the elderly by securing the safety of driving and actively supporting social participation.