• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.891-898
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• 2012

The study for the passenger's comfortableness of vehicles and the arousal of car drivers has been done widely. On the other hand, there are few studies for the locomotive engineers. Human error means that the mistakes made by human, recently it receives attention in the field of safety engineering and human engineering. Comparing the operating condition of train with car, because of the simplification of the visual stimulus, the arousal level on the train goes down easily. The arousal level down makes judgement down, the accident risk from human error is getting bigger. In this study, we measured bio-signals(ECG, EDA, PPG, respiration and EEG) from 6 locomotive engineers to evaluate their arousal state while they operated the train. Also we recorded the 3 axes acceleration signal showing the vibration state of train. Also, the existence of tunnels were simultaneously measured. At the station section where the train speed goes down, the size of vector's sum decreases because of reduced vibration. Beta component in EEG tends to increase at the entering point of each station and tunnel. It is due to the arousal reaction and tension growth. The mean SCR(skin conductance response) was more increased in neutral section. As the button control movement (body movement) increases in the neutral section, it is appeared that SCR increase. RR interval tends to gradually increase during train operation for 1 hour 40 minutes. However, It tends to sharply decrease at the stop station because strong concentration needed to stop train on the exact point. The engineer's arousal reaction can be checked through analysing the bio-signal change during train operation. Therefore, if this analysing result is adopted to the sleepiness prevention caution system, it will be useful for the safety train operation.

• The Journal of Advanced Prosthodontics
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• v.12 no.5
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• pp.316-321
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• 2020

PURPOSE. The stress distribution and microgap formation on an implant abutment structure was evaluated to determine the relationship between the direction of the load and the stress value. MATERIALS AND METHODS. Two types of three-dimensional models for the mandibular first molar were designed: bone-level implant and tissue-level implant. Each group consisted of an implant, surrounding bone, abutment, screw, and crown. Static finite element analysis was simulated through 200 N of occlusal load and preload at five different load directions: 0, 15, 30, 45, and 60°. The von Mises stress of the abutment and implant was evaluated. Microgap formation on the implant-abutment interface was also analyzed. RESULTS. The stress values in the implant were as follows: 525, 322, 561, 778, and 1150 MPa in a bone level implant, and 254, 182, 259, 364, and 436 MPa in a tissue level implant at a load direction of 0, 15, 30, 45, and 60°, respectively. For microgap formation between the implant and abutment interface, three to seven-micron gaps were observed in the bone level implant under a load at 45 and 60°. In contrast, a three-micron gap was observed in the tissue level implant under a load at only 60°. CONCLUSION. The mean stress of bone-level implant showed 2.2 times higher than that of tissue-level implant. When considering the loading point of occlusal surface and the direction of load, higher stress was noted when the vector was from the center of rotation in the implant prostheses.

• Journal of the Korean Society of Safety
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• v.15 no.1
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• pp.72-79
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• 2000

In recent, occupational diseases in harmful working places become a social issue. It is the well-known fact that a respiration in polluted working places exert a serious effect on health of workers. Accordingly, the cutting off contaminants air originally is the best way to improve working environments. In these cases, ventilation systems should be essentially installed to dilute or exhaust the contaminated indoor air. In this study, we investigated the characteristics of ventilation system of the noxious gas in working indoor places with natural ventilation by using COMET. The numerical simulations were carried out the natural ventilation with two phase(air, dust). For turbulent flow, Reynolds stresses were closed by the standard $\kappa$-$\varepsilon$ model. The results are as follows ; 1) In the natural exhaust in the working place, the flows of the central region have a more rapid velocity vector than the right and left one. 2) Numerical results show that the distribution of contaminants concentration have greater influence on convection than the case of diffusion by government of velocity vectors. 3) To observe the velocity variation with distance, three location of distance are considered. As results, it shows that the velocity are 0.075(m/s) at y=5(m), 10(m) and mean concentration are raised 10.6% at y=5(m), 10(m). 4) We have presented the useful data for the adequate counterplan in the harmful working places by carrying out the various investigation of the natural ventilation.

• Journal of Korea Multimedia Society
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• v.12 no.3
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• pp.383-396
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• 2009

Bone age assessment has been widely used in pediatrics to identify endocrine problems of children. Since the number of trained doctors is far less than the demands, there has been numerous requests for automatic estimation of bone age. Therefore, in this paper, we propose an automatic bone age assessment method that utilizes pattern classification techniques. The proposed method consists of three modules; a finger segmentation module, a normalized shape model generation module and a bone age estimation module. The finger segmentation module segments fingers and epiphyseal regions by means of various image processing algorithms. The shape model abstraction module employ ASM to improves the accuracy of feature extraction for bone age estimation. In addition, SVM is used for estimation of bone age. Features for the estimation include the length of bone and the ratios of bone length. We evaluated the performance of the proposed method through statistical analysis by comparing the bone age assessment results by clinical experts and the proposed automatic method. Through the experimental results, the mean error of the assessment was 0.679 year, which was better than the average error acceptable in clinical practice.

• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1302-1309
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• 2008

Traditional clustering methods, like k-means or fuzzy clustering, are prototype-based methods which are applicable only to convex clusters. On the other hand, spectral clustering tries to find clusters only using local similarity information. Its ability to handle concave clusters has gained the popularity recent years together with support vector machine (SVM) which is a kernel-based classification method. However, as is in SVM, the kernel width plays an important role and has a great impact on the result. Several methods are proposed to decide it automatically, it is still determined based on heuristics. In this paper, we proposed an adaptive method deciding the kernel width based on distance histogram. The proposed method is motivated by the fact that the affinity matrix should be formed into a block diagonal matrix to generate the best result. We use the tradition Euclidean distance together with the random walk distance, which make it possible to form a more apparent block diagonal affinity matrix. Experimental results show that the proposed method generates more clear block structured affinity matrix than the existing one does.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1370-1376
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• 2012

This paper proposes a gender recognition algorithm which classifies a male or female speaker. In this paper, characteristic vectors for the male and female speaker are analyzed, and recognition experiments for the proposed gender recognition by a neural network are performed using these characteristic vectors for the male and female. Input characteristic vectors of the proposed neural network are 10 LPC (Linear Predictive Coding) cepstrum coefficients, 12 LPC cepstrum coefficients, 12 FFT (Fast Fourier Transform) cepstrum coefficients and 1 RMS (Root Mean Square), and 12 LPC cepstrum coefficients and 8 FFT spectrum. The proposed neural network trained by 20-20-2 network are especially used in this experiment, using 12 LPC cepstrum coefficients and 8 FFT spectrum. From the experiment results, the average recognition rates obtained by the gender recognition algorithm is 99.8% for the male speaker and 96.5% for the female speaker.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1176-1194
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• 2018

The object classification using the images' contents is a big challenge in computer vision. The superpixels' information can be used to detect and classify objects in an image based on locations. In this paper, we proposed a methodology to detect and classify the image's pixels' locations using enhanced bag of words (BOW). It calculates the initial positions of each segment of an image using superpixels and then ranks it according to the region score. Further, this information is used to extract local and global features using a hybrid approach of Scale Invariant Feature Transform (SIFT) and GIST, respectively. To enhance the classification accuracy, the feature fusion technique is applied to combine local and global features vectors through weight parameter. The support vector machine classifier is a supervised algorithm is used for classification in order to analyze the proposed methodology. The Pascal Visual Object Classes Challenge 2007 (VOC2007) dataset is used in the experiment to test the results. The proposed approach gave the results in high-quality class for independent objects' locations with a mean average best overlap (MABO) of 0.833 at 1,500 locations resulting in a better detection rate. The results are compared with previous approaches and it is proved that it gave the better classification results for the non-rigid classes.

• Archives of Plastic Surgery
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• v.36 no.1
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• pp.1-10
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• 2009

Purpose: Partial necrosis of skin flaps remains a substantial problem in reconstructive surgery. We investigated the potential use of an adenovirus vector encoding the VEGF, COMP-angiopoietin-1 gene in an attempt to promote the viability of the inferior epigastric artery flap in a rat model. Methods: Three by six cm lower abdominal transverse skin flaps, supplied only by the left inferior epigastric artery, were designed. After skin flap elevation, the adenovirus VEGF and adenovirus COMP-angiopoietin-1 were injected into the distal portion of the flap, which has a high tendency of developing flap ischemia. Control animals were injected with the same volume of normal saline. On 3, 7 and 14 days after the flap elevation, the flap survival and vascularization were assessed using Visitrak digital$^{(R)}$, CD31 immunohistochemistry in addition to evaluating the general histological characteristics. Results: There was a significant increase in the mean percentage of flap viability by 89.8%, 91.1% and 94.8% in flaps transfected with adenovirus VEGF, COMP-angiopoietin-1, coadministraion of VEGF and COMP-angiopoietin-1 at seven days, and by 95.6%, 94.8% and 96.3% at 14 days. Histological assessment revealed that there were more blood vessels formed after adenovirus with VEGF, COMP-angiopoietin-1 or VEGF plus COMP-angiopoietin-1 than with adenovirus Lac Z. Conclusion: The results of this study suggest that adenovirus-mediated VEGF, COMP-angiopoietin-1 gene therapy, promote therapeutic angiogenesis in patients that undergo reconstructive procedures.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.11
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• pp.1009-1017
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• 2010

As rotating machines play an important role in industrial applications such as aeronautical, naval and automotive industries, many researchers have developed various condition monitoring system and fault diagnosis system by applying various techniques such as signal processing and pattern recognition. Recently, fault diagnosis systems using artificial neural network have been proposed. For effective fault diagnosis, this paper used MLP(multi-layer perceptron) network which is widely used in pattern classification. Since using obtained signals without preprocessing as inputs of neural network can decrease performance of fault classification, it is very important to extract significant features of captured signals and to apply suitable features into diagnosis system according to the kinds of obtained signals. Therefore, this paper proposes the decision method of the proper feature vectors about each fault signal for neural-network-based fault diagnosis system. We applied LPC coefficients, maximum magnitudes of each spectral section in FFT and RMS(root mean square) and variance of wavelet coefficients as feature vectors and selected appropriate feature vectors as comparing error ratios of fault diagnosis for sound, vibration and current fault signals. From experiment results, LPC coefficients and maximum magnitudes of each spectral section showed 100 % diagnosis ratios for each fault and the method using wavelet coefficients had noise-robust characteristic.

• The Journal of Korean Society of Virology
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• v.30 no.2
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• pp.141-150
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• 2000

The effectiveness of noninfectious recombinant adenovirus encoding murine granulocyte-macrophage colony stimulating factor (mGM-CSF) for the treatment of Meth A fibrosarcoma was investigated in syngeneic BALB/C model. Meth A and HeLa cells transduced with the recombinant adenovirus (Ad.mGM-CSF) produced substantial amounts of mGM-CSF, while WEH1164 cells transduced with the virus did not produce mGM-CSF. Mice inoculated subcutaneously with $1{\times}10^6$ Meth A cells, followed by injection of Ad.dE1 as a control, developed large tumors that reached a mean tumor size of 22 mm by day 30. However, tumor development and tumorigenicity were significantly inhibited in mice with a single intratumoral injection of Ad.mGM-CSF at $1{\times}10^8\;pfu$. Histological examination of the tumors injected with Ad.mGM-CSF revealed dense infiltrates of neutrophils, histiocytes, lymphocytes, and eosinophils associated with apoptotic cell death. The results suggest that the recombinant adenovirus encoding GM-CSF have a potential use for cancer gene therapy.