• The Journal of the Acoustical Society of Korea
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• v.23 no.5
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• pp.400-409
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• 2004

In this paper. a voice personality transformation method is proposed. which makes one person's voice sound like another person's voice. To transform the voice personality. vocal tract transfer function is used as a transformation parameter. Comparing with previous methods. the proposed method makes transformed speech closer to target speaker's voice in both subjective and objective points of view. Conversion between vocal tract transfer functions is implemented by classification of entire vector space followed by linear transformation for each cluster. LPC cepstrum is used as a feature parameter. A joint classification and transformation method is proposed, where optimum clusters and transformation matrices are simultaneously estimated in the sense of a minimum mean square error criterion. To evaluate the performance of the proposed method. transformation rules are generated from 150 sentences uttered by three male and on female speakers. These rules are then applied to another 150 sentences uttered by the same speakers. and objective evaluation and subjective listening tests are performed.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.196-202
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• 2013

Basal cell carcinoma (BCC) is the most common skin cancer and its incidence is increasing rapidly. In this paper, we propose a diagnosis method of basal cell carcinoma by Raman spectra of skin tissue using the NMF(non-negative matrix factorization) algorithm. After preprocessing steps, measured Raman spectra is used classification experiments. The weight and the basis can be obtained in a simple matrix operation and a column vector of the matrix decompsed by the NMF. Linear combination of bases and weights, it is possible to approximate the average of Raman spectra. The classification method is to select the class which to minimize the root mean square of the difference of the linear combination and the objective spectrum. According to the experimental results, the proposed method shows the promising results to diagnosis BCC. In addition, it confirmed that the proposed method compared with the previous research result could be effectively applied in the analysis of the Raman spectra.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.3
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• pp.16-21
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• 2010

In this paper, the linear source and relay precoders are designed for AF MIMO relay systems. In order to minimize mean squared error (MSE) of received symbol vector, the source and relay precoders are proposed, and MMSE receiver which is suitable to those precoders is utilized at the destination node. As the optimal precoders for source and relay nodes are not represented in closed form and induced by iterative method, we suggest a simple precoder design scheme. Simulation results show that the performance of the proposed precoding scheme is comparable with that of optimal scheme and outperforms other relay precoding schemes. Moreover, in high SNR region, it is revealed that SNR between source and relay node is more influential than SNR between relay and destination node in terms of bit error rate.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• Journal of the korean society of oceanography
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• v.35 no.2
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• pp.109-123
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• 2000

Depositional processes of fine-grained sediments were investigated on the basis of sediment transport vector analysis and identification of benthic foraminiferal assemblages in Yoja Bay, southern coast of Korea. The bay is a semi-enclosed embayment where extensive mud flats occur with a width up to about 4 km. Most surface sediments are poorly sorted (sorting values: 1.9-3.0 ${\phi}$) mud and silt (mean grain size: 6.0-8.7 ${\phi}$), except for the tidal inlets with basement rocks locally exposed. Grain-size distribution shows a fining tendency toward the basin center near the Yoja Island, implying a possible existence of turbidity maximum and relatively rapid settling of fine-grained sediments. The agglutinated foraminiferal taxa are dominant in the inner bay and decrease in abundance toward the mouth of the bay. Species diversities are higher in the outer bay, due to mixing of the offshore faunas with those of the bay. Four groups of benthic foraminiferal assemblages, identified by cluster analysis, represent the bay. Biofacies I and ll with relatively lower diversities are dominated by Ammobaculites exiguus and Ammonia beccarii, suggestive of influx of fresh water. In contrast, biofacies III and IV with relatively higher diversities include increased amounts of calcareous genus Elphidium and Quinquelocuzina, accounting for strong influence of sea water from the offshore. The fluvial discharge in summer floods appears to develop a bay-wide, clockwise lateral circulation in Yoja Bay, a typical of well-mixed estuaries. Accordingly, the foraminiferal assemblages of the surface sediments well show a sign of this circulation. The dominant inflow of the offshore water into the western part of the bay has resulted in more extensive muddy tidal flats compared to the eastern narrower counterpart.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.21-28
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• 2018

To help users who are experiencing difficulties finding the right learning course corresponding to their level of proficiency, we developed a recommendation model for personalized learning course for Intelligence Tutoring System(ITS). The Personalized Learning Course Recommendation model for ITS analyzes the learner profile and extracts the keyword by calculating the weight of each word. The similarity of vector between extracted words is measured through the cosine similarity method. Finally, the three courses of top similarity are recommended for learners. To analyze the effects of the recommendation model, we applied the recommendation model to the Women's ability development center. And mean, standard deviation, skewness, and kurtosis values of question items were calculated through the satisfaction survey. The results of the experiment showed high satisfaction levels in accuracy, novelty, self-reference and usefulness, which proved the effectiveness of the recommendation model. This study is meaningful in the sense that it suggested a learner-centered recommendation system based on machine learning, which has not been researched enough both in domestic, foreign domains.

• 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.