• Journal of the Korean Statistical Society
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• v.9 no.2
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• pp.181-193
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• 1980

A class of nonparametric estimators of the ratio of scale parameters is proposed. The estimators are based on the distribution-free rank-like test suggested by Fligner and Killeen (1976). An explicit form of the estimator is the median of the ratios of absolute deviations from the combined sample median. A small-sample Monte Carlo study shows that the proposed estimator is more efficient than the Bhattacharyya (1977) estimator. The proposed estimator is is reasonably insensitive to small failures in the assumption of equal medians. A modified estimator is also considered when the meidans are unequal.

• Journal of Photoscience
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• v.6 no.3
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• pp.123-128
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• 1999

Dynamics of many ultrafast processes are markedly slowed down in various organized molecular assemblies compared to ordinary liquids. We will show that the solvation dynamics of water molecules is affected amost dramatically and is retarded by 3 ∼4 orders of magnitude in microemulsions, micells and lipids. We will also discuss how the access to fewer water molucules and the drastically altered local pH in an organized asembly affected the excited state proton transfer processes. Finally, we will show how surface second haromonic generation can be used to study the air-water surface.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.6
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• pp.91-98
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• 2011

This paper proposes an efficient and accurate vision based recognition and tracking framework for texture free objects. We approached this problem with a two phased algorithm: detection phase and tracking phase. In the detection phase, the algorithm extracts shape context descriptors that used for classifying objects into predetermined interesting targets. Later on, the matching result is further refined by a minimization technique. In the tracking phase, we resorted to meanshift tracking algorithm based on Bhattacharyya coefficient measurement. In summary, the contributions of our methods for the underwater robot vision are four folds: 1) Our method can deal with camera motion and scale changes of objects in underwater environment; 2) It is inexpensive vision based recognition algorithm; 3) The advantage of shape based method compared to a distinct feature point based method (SIFT) in the underwater environment with possible turbidity variation; 4) We made a quantitative comparison of our method with a few other well-known methods. The result is quite promising for the map based underwater SLAM task which is the goal of our research.

• CELLMED
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• v.6 no.1
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• pp.6.1-6.6
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• 2016

Polycystic Ovarian Syndrome (PCOS) has now become more common in occurrence in women of reproductive age, particularly in urban and semi-urban population in India. So there is a need to investigate this phenomenon taking into consideration various aspects including possible treatment method to ameliorate/eradicate this syndrome, which has far reaching socio-economic impact and consequences, in view of infertility and irregular menstrual cycles frequently associated with this syndrome. Homeopathy is a branch of traditional alternative medicine which is gaining popularity in India and some other developing countries, as also in some of the developed countries in Europe. With this background scenario, we have made an attempt to treat cases of confirmed PCOS and tried to compare the relative efficacy of two potentized homeopathic drugs, namely, Lycopodium clavatum (Lyco) and Calcarea carbonica (Calc), most frequently used by homeopathic practitioners, selecting different potencies of the drugs, depending on condition/guiding symptom(s) of the patients. While the main focus was pointed on total/partial removal of cysts, data pertaining to different PCOS associated symptoms were also compared for the sake of learning if the two drugs had differential effects on these symptoms also. The study parameters in this investigation included: regularity/irregularity of menstrual cycle, presence/absence of acne, hirsutism, male type alopecia, acanthosis nigricans, body/mass index (BMI) and waist-hip ratio. Overall results provided clear evidences that both these homeopathic drugs had great ameliorating effects on PCOS, although each drug had a little different effect in respect of the individual parameters of this study.

• CELLMED
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• v.6 no.1
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• pp.7.1-7.7
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• 2016

In view of greater attention given to the incidence of Polycystic Ovarian Syndrome (PCOS) in women of reproductive age, particularly in urban and semi-urban population in India, research works in both the regimens of orthodox and complementary and alternative medicines have been rejuvenated in recent years. We report here relative efficacy of two potentized homeopathic remedies, Calcarea carbonica (Calc) and Lycopodium clavatum (Lyco) used traditionally for the removal of ovarian cysts. These drugs are most frequently used based on guiding symptoms of individual patients. Effects of either of these remedies on its ability of removing cysts, along with amelioration of certain other hormones and hormone-related parameters of PCOS, such as follicle stimulating hormone, luteinizing hormone, Estradiol, Testosterone (Free/Total), Dehydroepiandosterone, Prolactine, Progesterone (17- Hydroxyprogesterone), TSH including T₃, T₄, and Insulin were studied. The Insulin-related parameters like changes in fasting or postprandial glucose levels were also studied. The mentioned hormones play some- direct or indirect roles in causing irregular menstrual cycle and PCOS. The data collected at three fixation time points, namely, at 6, 12, and 18 months were considered. Results showed that out of 40 patients initially having PCOS, cysts were totally removed in 21 patients along with amelioration of other relevant symptoms. Both Calc and Lyco had amelioration of similar nature. Results of this study therefore validate safe and effective use of both Calc and Lyco in homeopathy, to patients with basic guiding symptoms for either drug, and can be recommended for patients with PCOS as they do not have any reported side-effects.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5A
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• pp.375-387
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• 2012

This paper proposes a new real-time object tracking algorithm using particle filters with color and texture features in moving CCD camera images. If the user selects an initial object, this region is declared as a target particle and an initial state is modeled. Then, N particles are generated based on random distribution and CS-LBP (Centre Symmetric Local Binary Patterns) for texture model and weighted color distribution is modeled from each particle. For observation likelihoods estimation, Bhattacharyya distance between particles and their feature models are calculated and this observation likelihoods are used for weights of individual particles. After weights estimation, a new particle which has the maximum weight is selected and new particles are re-sampled using the maximum particle. For performance comparison, we tested a few combinations of features and particle filters. The proposed algorithm showed best object tracking performance when we used color and texture model simultaneously for likelihood estimation.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.177-183
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• 2010

In continuous vocabulary recognition system by statistical method vocabulary recognition to be performed using probability distribution it also modeling using phoneme clustering for based sample probability parameter presume. When vocabulary search that low recognition rate problem happened in express vocabulary result from presumed probability parameter by not defined phoneme and insert phoneme and it has it's bad points of gaussian model the accuracy unsecure for one clustering modeling. To improve suggested probability distribution mixed gaussian model to optimized for based resemble Euclidean and Bhattacharyya distance measurement method mixed clustering modeling that system modeling for be searching phoneme probability model in clustered model. System performance as a result of represent vocabulary dependence recognition rate of 98.63%, vocabulary independence recognition rate of 97.91%.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.385-400
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• 2009

The adverse effect of harmful plankton on the marine ecosystem is a topic of deep concern. To investigate the role of such phytoplankton, a mathematical model containing distinct dynamical equations for toxic and non-toxic phytoplankton is analyzed. Stability analysis of the resulting three equation model is carried out. A continuous time variation in toxin liberation process is incorporated into the model and a stability analysis of the resulting delay model is performed. The distributed delay model is then extended to include the spatial distribution of plankton and the delay-diffusion model is analyzed with spatial and spatiotemporal kernels. Conditions for diffusion-driven instability in both the cases are derived and compared to explore the significance of these kernels. Numerical studies are performed to justify analytical findings.

• Journal of Korean Society for Quality Management
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• v.36 no.2
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• pp.36-44
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• 2008

In this paper a novel feature extraction and selection is carried out in order to improve the discriminating capability between healthy and damaged structure using vibration signals. Although many feature extraction and selection algorithms have been proposed for vibration signals, most proposed approaches don't consider the discriminating ability of features since they are usually in unsupervised manner. We proposed a novel feature extraction and selection algorithm selecting few wavelet coefficients with higher class discriminating capability for damage detection and class visualization. We applied three class separability measures to evaluate the features, i.e. T test statistics, divergence, and Bhattacharyya distance. Experiments with vibration signals from truss structure demonstrate that class separabilities are significantly enhanced using our proposed algorithm compared to other two algorithms with original time-based features and Fourier-based ones.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1363-1368
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• 2015

Recently, computer form were smaller than before because of computing technique's development and many wearable device are formed. So, computer's cognition of human emotion has importantly considered, thus researches on analyzing the state of emotion are increasing. Human voice includes many information of human emotion. This paper proposes a discriminative feature vector selection for emotion classification based on speech. For this, we extract some feature vectors like Pitch, MFCC, LPC, LPCC from voice signals are divided into four emotion parts on happy, normal, sad, angry and compare a separability of the extracted feature vectors using Bhattacharyya distance. So more effective feature vectors are recommended for emotion classification.