• Asian Pacific Journal of Cancer Prevention
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• v.14 no.9
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• pp.5257-5261
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• 2013

The micronucleus frequency (MNF) in peripheral blood lymphocytes (PBL) is a biomarker of chromosomal damage and genome instability in human populations.The relationship of micronucleus frequency with prognosis of patients with acute leukemia is not clear. We therefore investigated MNF in mitogen-activated peripheral blood lymphocytes from patients with hematologic diseases and solid tumours. Patients included 50 with acute leukemia, 49 diagnosed with myelodysplastic syndrome (MDS), 54 with benign blood diseases, and 45 with solid tumours, examined with 50 healthy controls. The mean MNF was significantly higher in cases of hematologic diseases and solid tumor patients than in healthy controls (P<0.001). There was no evident difference between MNF in the acute leukemia ($7.15{\pm}2.18$) and solid tumor groups ($7.11{\pm}1.47$), but both were higher than in the MDS group ($5.12{\pm}1.29$) and benign blood diseases group ($3.08{\pm}1.08$). Taking 7.15‰, the average MNF of the acute leukemia group as standard, and dividing 50 cases of acute leukemia patients into high MNF group ($MNF{\geq}7.15$‰) and low MNF group (MNF<7.15‰). The overall response (complete remission + partial remission) rates of the low MNF group were significantly higher than in the high MNF group (P=0.001). The high MNF group further showed lower overall survival rates than the low MNF group. MNF expression and progression-free survival seemed to have a opposite relationship, with a correlation coefficient of -0.702. These data indicate that MNF in peripheral blood lymphocytes is important for evaluation of prognosis of acute leukemia patients, and it can reflect progression of disease to a certain degree.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.4769-4775
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• 2014

This paper discusses the dynamics stress of each boom, which occurs as a result of the conflicts on a multi-joint boom at the end effector and structure. In this process, CATIA was applied to create 3D modeling, ADAMS and ANSYS were then performed using mesh analysis by obtaining the stress data to create a MNF(Modal Neutral File) of multi-joint boom. Two types of MNF models were analyzed using ADAMS FFT(Fast Fourier Transform) performing to check the validity of each model. In this process, the models were verified by ADAMS, which performs the dynamic characteristics of conflict. The ADAMS Durability was used to analyze the maximum stress between the multi-joint boom and structure.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.3
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• pp.311-320
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• 1999

This study conducts to analyze comparative accuracy when both Image Transformation Methods and Supervised Classifications on multi-spectral TM using a case of Lower Tumen River Area. In terms of overall classification accuracy, maximum likelihood method turns out higher than other one, but in a case of vegetation only, MNF and TC image transformation methods produce a better quality of the result. Especially, seven dimensional images including MNF, TC, and NDVI create better image than three dimensional one. Among these transformation methods, maximum likelihood method results out the best one. Multi-spectral image could be useful as an important basic material for site selection of industrial allocation as well as Tumen River Area Economic Development Plan.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.8
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• pp.1497-1505
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• 2010

The present study was performed to investigate the effect of aging on muscular activity of older subjects under the condition of fixed load muscle contraction. SEMG signals were recorded from old (46 women) and young (45 women) groups performing sustained isometric elbow flexion contraction with a fixed load during 30 seconds. Linear regression and mean square error (MSE) analysis with four characteristic variables (ARV, RMS, MDF, MNF) were used to compare the age-related difference (of local muscle fatigue and fluctuation of the amplitude and frequency) in the SEMG signal. The main results can be summarized as follows: During sustained muscle contraction with a fixed load: i) the MSE values of amplitude (ARV, RMS) and frequency (MDF, MNF) variables were more than 30% higher for the young than for the old adults; ii) the measures of local muscle fatigue (slope of the MDF and MNF) indicated greater fatigue in the old; and iii) the rate of increase of the SEMG amplitude was higher for the young than the old.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.6 no.1
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• pp.59-65
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• 2012

In this study, muscle fatigue of biceps and triceps during isometric exercise depending on concentric contraction and eccentric contraction was evaluated using EMG. 12 healthy male volunteers was performed concentric exercise and eccentric exercise by maximum flection and extension of elbow joint. Integrated EMG (IEMG) in time domain and mean power frequency (MNF) in frequency domain were calculated. MNF of the biceps and triceps was decreased, whereas IEMG was increased during concentric contraction and eccentric contraction. But muscle fatigue index appeared higher at region of stretched muscle length. in this result, muscle fatigue occurs at both biceps and triceps muscle during concentric and eccentric exercise, and muscle fatigue was affected by muscle contraction and extension.

• Journal of the Korean association of regional geographers
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• v.12 no.4
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• pp.496-507
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• 2006

A hybrid approach integrating both high-resolution and hyperspectral data sets was used to map vegetation cover of a coastal lowland area in the Hawaii Volcanoes National Park. Three common grass species (broomsedge, natal redtop, and pili) and other non-grass species, primarily shrubs, were focused in the study. A 3-step, hybrid approach, combining an unsupervised and a supervised classification schemes, was applied to the vegetation mapping. First, the IKONOS 1-m high-resolution data were classified to create a binary image (vegetated vs. non--vegetated) and converted to 20-meter resolution percent cover vegetation data to match AVIRIS data pixels. Second, the minimum noise fraction (MNF) transformation was used to extract a coherent dimensionality from the original AVIRIS data. Since the grasses and shubs were sparsely distributed and most image pixels were intermingled with lava surfaces, the reflectance component of lava was filtered out with a binary fractional cover analysis assuming that tile total reflectance of a pixel was a linear combination of the reflectance spectra of vegetation and the lava surface. Finally, a supervised approach was used to classify the plant species based on tile maximum likelihood algorithm.

• Journal of the Ergonomics Society of Korea
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• v.29 no.2
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• pp.183-188
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• 2010

The purpose of this study is to investigate the stationarity of the electromyographic signal in various flexion angles, loads, and window sizes, which influence the result of the mean power frequency (MPF) and median frequency (MNF) analysis. Six healthy subjects participated in the experiment. They were tested in the combination of 3-level flexion angles (0 degree, 22.5 degree, 45 degree) and 3-level loads (0Nm, 30Nm, 60Nm). Electromyographic data were collected for 20 seconds during isometric contraction. The stationarity of collected data were analyzed with four different window sizes including 250, 500, 1000 and 2000ms. Two test methods for stationarity such as Reverse Arrangements Test and Modified Reverse Arrangements Test were used. In order to show the effect of nonstationarity, the increasing/decreasing trend of MPF and MNF trend were discussed. In results, the stationarity of the electromyographic signal decreased as flexion angle increased and load decreased while window size decreased based on Reverse Arrangements Test. The highest stationarity was shown at 500 ms window in Modified Reverse Arrangements Test. The inclination of MNF and MPF indicated 3.6-6.3%, 3.8-5.1% discrepancy compared to the result from stationary data.

• Journal of Biosystems Engineering
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• v.34 no.2
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• pp.127-132
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• 2009

In the working population, muscle fatigue and musculoskeletal discomfort are common, which, in the case of insufficient recovery may lead to musculoskeletal pain. Workers suffering from musculoskeletal pains need to be rehabilitated for recovery. Isokinetic testing has been used in physical strengthening, rehabilitation and post-operative orthopedic surgery. Frequency analysis of electromyography (EMG) signals using the mean frequency (MNF) has been widely used to characterize muscle fatigue. During isokinetic contractions, EMG signals present strong nonstationarities. Hilbert-Haung transform (HHT) and autoregressive (AR) model have been known more suitable than Fourier or wavelet transform for nonstationary signals. Moreover, several analyses have been performed within each active phase during isokinetic contractions. Thus, the aims of this study were i) to determine which one was better suitable for the analysis of MNF between HHT and AR model during repetitive maximum isokinetic extensions and ii) to investigate whether the analysis could be repeated for sequential fixed epoch lengths. Seven healthy volunteers (five males and two females) performed isokinetic knee extensions at $60^{\circ}/s$ and $240^{\circ}/s$ until 50% of the maximum peak torque was reached. Surface EMG signals were recorded from the rectus femoris of the right thigh. An algorithm detecting the onset and offset of EMG signals was applied to extract each active phase of the muscle. Following the results, slopes from the least-square error linear regression of MNF values showed that muscle fatigue of all subjects occurred. The AR model is better suited than HHT for estimating MNF from nonstationary EMG signals during isokinetic knee extensions. Moreover, the linear regression can be extracted from MNF values calculated by sequential fixed epoch lengths (p> 0.0I).

• Aerospace Engineering and Technology
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• v.7 no.1
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• pp.216-222
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• 2008

Purpose of this research is estimation of water depth by hyperspectral remote sensing in area that access of ship is difficult. This research used EO-l Hyperion satellite imagery. Atmospheric and geometric correction is executed. Compress of band used MNF transforms. Diffuse Attenuation Coefficient of target area is decided in imagery for water depth estimation. Determination of Emdmember in pixel is using Linear Spectral Unmixing techniques. Water depth estimated using this result.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.633-639
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• 2018

High-resolution images using remote sensing (RS) is importance to secure for spatial classification depending on the characteristics of the complex and various factors that make up the river environment. The purpose of this study is to evaluate the accuracy of the classification results and to suggest the possibility of applying the high resolution hyperspectral images obtained by using the drone to perform spatial classification. Hyperspectral images obtained from study area were reduced the dimensionality with PCA and MNF transformation to remove effects of noise. Spatial classification was performed by supervised classifications such as MLC(Maximum Likelihood Classification), SVM(Support Vector Machine) and SAM(Spectral Angle Mapping). In overall, the highest classification accuracy was showed when the MLC supervised classification was used by MNF transformed image. However, it was confirmed that the misclassification was mainly found in the boundary of some classes including water body and the shadowing area. The results of this study can be used as basic data for remote sensing using drone and hyperspectral sensor, and it is expected that it can be applied to a wider range of river environments through the development of additional algorithms.