• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.35-44
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• 2016

Seed viability is one of the most important parameters that is directly related with seed germination performance and seedling emergence. In this study, a hyperspectral imaging (HSI) system having a range of 1000-2500 nm was used to classify viable watermelon seeds from nonviable seeds. In order to obtain nonviable watermelon seeds, a total of 96 seeds were artificially aged by immersing the seeds in hot water ($25^{\circ}C$) for 15 days. Further, hyperspectral images for 192 seeds (96 normal and 96 aged) were acquired using the developed HSI system. A germination test was performed for all the 192 seeds in order to confirm their viability. Spectral data from the hyperspectral images of the seeds were extracted by selecting pixels from the region of interest. Each seed spectrum was averaged and preprocessed to develop a classification model of partial least square discriminant analysis (PLS-DA). The developed PLS-DA model showed a classification accuracy of 94.7% for the calibration set, and 84.2% for the validation set. The results demonstrate that the proposed technique can classify viable and nonviable watermelon seeds with a reasonable accuracy, and can be further converted into an online sorting system for rapid and nondestructive classification of watermelon seeds with regard to viability.

• Journal of Animal Environmental Science
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• v.18 no.sup
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• pp.55-64
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• 2012

We investigated the effect of the clay mineral fortified with complex trace elements by specific fermentation microbes on growth performance and a quality of pork in this study. For the declared experimental animal, 80 heads of crossbred with Large White and Yorkshire were randomly splitted into a control group and a test group. Each group were assigned with 4 replicates and 10 heads of each replicate. When 0.3% of the fermentation product of the clay mineral (FCM) was added into feed stuff and fed for 9 weeks of experimental feeding period, the results of the feed intake, weight gains, pH of carcass, lightness of meat color, and brightness of the muscle semimembranosus were similar to those of the control group. However, dressing percentage, reddishness of carcass, and water holding capacity were improved, respectively, as much as 2.7%, 12%, and 10%, and reduced by 6% in cooking loss. In order to investigate the immune modulatory effect of fermented clay mineral, pheripheral blood mononuclear cells (PBMC) were isolated and Immune modulatory parameters were measured. The proliferation activity of PBMC from pigs fed the fermented clay mineral were significantly increased compared to control group pigs, and also those results were more clearly observed as activated with lipopolysaccharide and concanavaline A. The secretion of TNF-${\alpha}$ of the FCM group pigs showed an increasing tendency. Therefore it was suggested that the feeding of FCM which was high in cation metathesis and the value of infrared ray, activated the immune responses, and thus the production of the environment-friendly high quality pork without the use of antibiotics would be possible.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5164-5171
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• 2011

In fuzzy modeling for nonlinear process, typically using the given data, the fuzzy rules are formed by the input variables and the space division by selecting the input variable and dividing the input space for each input variables. The premise part of the fuzzy rule is identified by selection of the input variables, the number of space division and membership functions and the consequent part of the fuzzy rule is identified by polynomial functions in the form of simplified and linear inference. In general, formation of fuzzy rules for nonlinear processes using the given data have the problem that the number of fuzzy rules exponentially increases. To solve this problem complex nonlinear process can be modeled by separately forming the fuzzy rules by means of fuzzy division of each input space. Therefore, this paper utilizes individual input space to generate fuzzy rules. The premise parameters of the fuzzy rules are identified by Min-Max method using the minimum and maximum values of input data set and membership functions are used as a series of triangular, gaussian-like, trapezoid-type membership functions. And lastly, using the data which is widely used in nonlinear process we evaluate the performance and the system characteristics.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1372-1380
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• 1999

본 논문에서는 자연언어 문장의 객관적 정량적인 질 측정 방법의 구축에 대해 설명하고, 이를 문장 퇴고 시스템의 사례에 적용해 본다. 문장의 질을 평가한다는 것은 본질적으로 주관적이고 정량화가 어려운 작업이기 때문에, 이 과정에서 질의 객관적 계량화가 가능한지 여부가 가장 중요한 문제가 된다. 이 논문에서는 이러한 문제를 해결하기 위해 유전자 알고리즘을 이용한 진화적 접근 방법을 통해 객관적이고 정량적인 질의 측정 공식을 유도하는 방법론을 제시하였다. 이 논문에서 제시한 방법론의 핵심은 간단히 말해서 사람이 행하는 정성적인 판단을, 이에 가장 근접하는 정량적 측정 체계로 전환시키는 것이라고 보면 된다. 이것을 위해 정량화 문제를 문장의 단순 언어 특징들의 변화값을 이용한 최적화 문제로 환원시키고, 다시 이 최적화 문제를 유전자 알고리즘을 이용해 해결함으로써 문제를 효과적으로 해결할 수 있었다. 실험 결과를 보면, 본 논문에서 제시한 최적화 방법은 주어진 훈련용 예제와 검증용 예제 중 각각 99.84%, 99.88%를 만족시키는 해를 찾아내었으므로 정량적 질 평가 공식의 유도에 매우 효과적임을 알 수 있었다. 또한 도출된 측정 공식을 이용해서 실제 퇴고 시스템 평가에 적용한 결과 문장 질의 측정에 매우 유용하게 이용될 수 있음을 알 수 있었다. 이와 같이 질의 정량적 평가가 가능하다는 사실이 갖는 또 한가지 중요한 의미는 최종 사용자의 구매 의사나 개발자의 공학적 의사 결정을 위한 객관적 성능 평가 자료의 제공에 이 방법이 유용하게 사용될 수 있다는 점이다.Abstract This paper describes a method of building a quantitative measure of the quality of natural language sentences, particularly produced by document revision systems. Evaluating the quality of natural language sentences is intrinsically subjective, so what is most important as to the evaluation is whether the quality can be measured objectively. To solve such problem of objective measurability, genetic algorithm, an evolutionary learning method, is employed in this paper. The underlying standpoint of this approach is that building the quality measures is a task of constructing a formulae that produces as close results as can to the qualitative decisions made by humans. For doing this, the problem of measurability has been simply reduced to an optimization problem using the change of the values of simple linguistic parameters found in sentences, and the reduced problem has been solved effectively by the genetic algorithm. Experimental result shows that the optimization task satisfied 99.84% and 99.88% of the given objectives for training and validation samples, respectively, which means the method is quite effective in constructing the quantitative measure of the quality of natural language sentences. The actual evaluation result of a revision system shows that the measure is useful to quantize the quality of sentences. Another important contribution of this measure would be to provide an objective performance evaluation data of natural language systems on a basis of which end-users and developers can make their decision to fit their own needs.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.1
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• pp.26-32
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• 2009

The multi-level storage architecture has been widely adopted in servers and data centers. However, while prefetching has been shown as a crucial technique to exploit sequentiality in accesses common for such systems and hide the increasing relative cost of disk I/O, existing multi-level storage studies have focused mostly on cache replacement strategies. In this paper, we show that prefetching algorithms designed for single-level systems may have their limitations magnified when applied to multi-level systems. Overly conservative prefetching will not be able to effectively use the lower-level cache space, while overly aggressive prefetching will be compounded across levels and generate large amounts of wasted prefetch. We design and implement a hierarchy-aware lower-level prefetching strategy called PMS(Prefetching strategy for Multi-level Storage system) that applicable to any upper level prefetching algorithms. PMS does not require any application hints, a priori knowledge from the application or modification to the va interface. Instead, it monitors the upper-level access patterns as well as the lower-level cache status, and dynamically adjusts the aggressiveness of the lower-level prefetching activities. We evaluated the PMS through extensive simulation studies using a verified multi-level storage simulator, an accurate disk simulator, and access traces with different access patterns. Our results indicate that PMS dynamically controls aggressiveness of lower-level prefetching in reaction to multiple system and workload parameters, improving the overall system performance in all 32 test cases. Working with four well-known existing prefetching algorithms adopted in real systems, PMS obtains an improvement of up to 35% for the average request response time, with an average improvement of 16.56% over all cases.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.747-752
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• 2006

In this paper, the adaptive fuzzy sliding mode controller with two systems is designed. The existing sliding mode controller used to $approximation{\^{u}}(t)$ with discrete sgn function and sat function for keeping the state trajectories on the sliding surface[1]. The proposed controller decrease the disturbance for uncertain control gain and This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems ate used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system, we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem, and convergence and robustness properties ate demonstrated. Futhermore, fuzzy tuning improve tracking abilities by changing some sliding conditions. In the traditional sliding mode control, ${\eta}$ is a positive constant. The increase of ${\eta}$ has led to a significant decrease in the rise time. However, this has resulted in higher overshoot. Therefore the proposed ${\eta}$ tuning AFSMC improve the performances, so that the controller can track the trajectories faster and more exactly than ordinary controller. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.124-131
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• 2016

Baseline correction is very important due to influence on performance of spectral analysis in application of spectroscopy. Baseline is often estimated by parameter selection using visual inspection on analyte spectrum. It is a highly subjective procedure and can be tedious work especially with a large number of data. For these reasons, it is an objective and automatic procedure is necessary to select optimal parameter value for baseline correction. Asymmetrically reweighted penalized least squares (arPLS) based on penalized least squares was proposed for baseline correction in our previous study. The method uses a new weighting scheme based on the generalized logistic function. In this study, we present an automatic selection of optimal parameter for baseline correction using arPLS. The method computes fitness and smoothness values of fitted baseline within available range of parameters and then selects optimal parameter when the sum of normalized fitness and smoothness gets minimum. According to the experimental results using simulated data with varying baselines, sloping, curved and doubly curved baseline, and real Raman spectra, we confirmed that the proposed method can be effectively applied to optimal parameter selection for baseline correction using arPLS.

• Korean Journal of Optics and Photonics
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• v.12 no.2
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• pp.77-82
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• 2001

Error characteristics of a mirror loss measurement system using an exponential decay method were studied, with the two samples having about 200-ppm-loss and 30-ppm-loss, respectively. In order to minimize the decay signal deviation from an exponential curve due to cavity length fluctuation, a data average method was tried. The data average method significantly improved the exponential curve fitting error of the decay signal, so that for a 6 decay signal data average the loss measurement error was reduced by about 2.4 times for the 200-ppm-loss mirror and 1.3 times for the 30-ppm-loss mirror compared with a single shot measurement. Day-to-day mirror loss repeatability error for the two samples was investigated. The repeatability error was measured to be about 5% for the 200-ppm-loss mirror and about 26.4% for the 30-ppm-loss mirror. Low decay signal average effect and high repeatability error in the low loss mirror measurement were explained with non-uniform spatial loss distribution of the sample and contamination from the environment, in addition to the error sources of the mirror loss measurement system itself. The influence of cavity length fluctuation and cavity length measurement error on the mirror loss measurement system performance was theoretically calculated. It confirmed that the requirement for the cavity length parameters was not so strict in the mirror loss measurement system of several ppm resolution. ution.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.557-565
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• 2021

Path-following control is considered as one of the most fundamental skills to realize autonomous navigation of marine vessels in the ocean. This study addresses with the path-following control for a ship in which there are environmental disturbances in the directions of the surge, sway, and yaw motions. The guiding principle and back-stepping method was utilized to solve the ship's tracking problem on the reference path generated by a virtual ship. For path-following control, error dynamics is one of the most important skills, and it extends to the research fields of automatic collision avoidance and automatic berthing control. The algorithms for the guiding principles and error variables have been verified by numerical simulation. As a result, most error variables converged to zero values with the controller except for the yaw angle error. One of the most interesting results is that the tracking errors of path-following control between two ships are smaller than the existing safe passing distances considering interaction forces from near passing ships. Moreover, a trade-off between tracking performance and the ship's safety should be considered for determining the proper control parameters to prevent the destructive failure of actuators such as propellers, fins, and rudders during the path-following of marine vessels.

• Food Engineering Progress
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• v.15 no.1
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• pp.75-79
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• 2011

Analytical methods for food antioxidants including ascorbic acid, erythorbic acid, ascorbyl palmitate (AP), and ascorbyl stearate (AS), were validated using high performance liquid chromatography. Validation parameters such as linearity, limit of detection (LOD), limit of quantification (LOQ), and recovery were tested using lard and cider as food model systems. Linearity of ascorbic acid and erythorbic acid were both higher than ($R^2$> 0.99), LOD of these compounds were 0.46 and 0.48 ${\mu}g/mL$, respectively and LOQ were 1.39 and 1.45 ${\mu}g/mL$, respectively. The recovery rates of these compounds were 86.35-94.78% and 84.76-95.02%, respectively. However, the concentration of AP and AS decreased in methanol stock solution. Four other solvents including ethanol, acetonitrile, mixture of methanol and acetonitrile, and mixture of ethanol and acetonitrile were tested to increase the stability of AP and AS under room temperature and refrigerated temperature. Ethanol provided better stability of AP and AS under both room and refrigerated temperature. This study can help to accurately analyze the content of ascorbic acid and its derivatives in processed foods.