• International Journal of Air-Conditioning and Refrigeration
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• v.6
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• pp.36-44
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• 1998

R-410a and R-407c which have the best potential among R-22 alternatives were tested as drop-in refrigerants against a set of R-22 baseline tests. The performance evaluations were carried out in a psychometric calorimeter test facility using the residential spilt type air conditioner under the ARI rating conditions. Except the lubricant and hand-operated expansion valve, the other parts of the air conditioner were the same with the commercial system. Performance characteristics were measured; compressor power, capacity, VCR, mass flow rate and COP. The tests showed that R-407c can be directly charged into the current refrigeration system because its vapor pressure and other thermochemical properties are similar to those of R-22. However, it is required to change the volume flow rate of compressor in order to achieve the volumetric capacity of R-22. This results from its relatively small VCR and capacity. Meanwhile, R-410a has vapor pressure values too high to be substituted for the current system and this resulted relatively low COP of R-410a compared to that of R-22.

• Journal of the Korean Solar Energy Society
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• v.31 no.6
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• pp.125-131
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• 2011

Recently, the application of renewable energy to building is steadily increasing in domestic due to the energy saving efforts around the world. Among the all, wind energy is one of the rising energy source because of its high technological maturity. Domestic wind power market has rapidly increased in recent years but the certification system for wind turbine has not been activated since it was introduced in 2009. Thus, this study aims to propose the improvement of certification system for wind turbine by comparing domestic certification system with international certification system. The result of this study are as follows. First, domestic certification system needs to be subdivided and established by systematic standards. Second, it is considered that education about rating standards is required to wind turbine makers to activate domestic certification system. Third, domestic certification agenciesand test agencies need to be unified and reduced.

• Journal of the Microelectronics and Packaging Society
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• v.23 no.4
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• pp.35-41
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• 2016

Ceramic-metal based high power LED array package was developed via thick film LTCC technology using a glass-ceramic insulation layer and a silver conductor patterns directly printed on the aluminum heat sink substrate. The thermal resistance measurement using thermal transient tester revealed that ceramic-metal base LED package exhibited a superior heat dissipation property to compare with the previously known packaging method such as FR-4 based MCPCB. A prototype LED package sub-module with 50 watts power rating was fabricated using a ceramic-metal base chip-on-a board technology with minimized camber deformation during heat treatment by using partially covered glass-ceramic insulation layer design onto the aluminum heat spread substrate. This modified circuit design resulted in a camber-free packaging substrate and an enhanced heat transfer property compared with conventional MCPCB package. In addition, the partially covered design provided a material cost reduction compared with the fully covered one.

• Fibers and Polymers
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• v.7 no.4
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• pp.450-456
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• 2006

The objectives of this study were to investigate physiological and psychological responses to the rustling sound of Korean traditional silk fabrics and to figure out objective measurements such as sound parameters and mechanical properties determining the human responses. Five different traditional silk fabrics were selected by cluster analysis and their sound characteristics were observed in terms of FFT spectra and some calculated sound parameters including level pressure of total sound (LPT), Zwicker's psychoacoustic parameters - loudness(Z), sharpness(Z), roughness(Z), and fluctuation strength(Z), and sound color factors such as ${\Delta}L\;and\;{\Delta}f$. As physiological signals, the ratio of low frequency to high frequency (LF/HF) from the power spectrum of heart rate variability, pulse volume (PV), heart rate (HR), and skin conductance level (SCL) evoked by the fabric sounds were measured from thirty participants. Also, seven aspects of psychological state including softness, loudness, sharpness, roughness, clearness, highness, and pleasantness were evaluated when each sound was presented. The traditional silk fabric sounds were likely to be felt as soft and pleasant rather than clear and high, which seemed to evoke less change of both LF/HF and SCL indicating a negative sensation than other fabrics previously reported. As fluctuation strength(Z) were higher and bending rigidity (B) values lower, the fabrics tended to be perceived as sounding softer, which resulted in increase of PV changes. The higher LPT was concerned with higher rating for subjective loudness so that HR was more increased. Also, compression linearity (LC) affected subjective pleasantness positively, which caused less changes of HR. Therefore, we concluded that such objective measurements as LPT, fluctuation strength(Z), bending rigidity (B), and compression linearity (LC) were significant factors affecting physiological and psychological responses to the sounds of Korean traditional silk fabrics.

• The Journal of Korean Medicine
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• v.28 no.2 s.70
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• pp.80-92
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• 2007

Objectives : Functional dyspepsia (FD) is one of the most common gastrointestinal diseases. Nevertheless, there are many unknown mechanisms of autonomic functioning in FD patients. This study was designed to investigate the relationship between FD and biosignals from heart rate variability (HRV) and Yangdorak diagnosis. Methods : 32 patients (22 female, 10 male; mean age 40) and 32 healthy volunteers (21 female, 11 malemean; age 38) participated in this study. First gastrointestinal symptoms rating scale (GSRS) was assessed by questionnaires in both groups to evaluate the types of gastrointestinal symptoms. Second, HRV and Yangdorak diagnosis were measured in both groups. Results : 1. The FD group in this study mainly had the complaint of 'bloating' symptoms. 2. There was statistically no significant difference between Yangdorak (total average and 24 acupoints) and HRV values except logarithmic low-frequency band (lnLF) and total power (TP) in frequency domain. 3. There was statistically no significant relationship between HRV and Yangdorak in either group. However, most Yangdorak values were positively related with some HRV values (low-frequency, low-frequency/high-frequency ratio and high-frequency, etc) in the control group. Conclusions : FD patients had relatively lesser sympathetic domain than healthy subjects, indicated by decreased lnLF and TP. Particularly, there were positive relationships and significant differences between Yangdorak and HRV in young healthy subjects. This suggests that biosignals from HRV may be a useful method that can differentiate FD from healthy state in those of young age.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.8
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• pp.33-39
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• 2005

The maximum output torque and power developed by the machine is ultimately depended on the allowable inverter current rating and maximum voltage which the inverter can supply to the machine. Therefore, considering the limited voltage and current capacities, it is desirable to consider a control method which yields the best possible torque per ampere. In this paper, we propose fuzzy neural network(FNN) controller that combines a fuzzy control and the neural network for high performance control of induction motor drive. This controller composes antecedence of the fuzzy rules and consequence by a clustering method and a multi-layer neural networks. This controller is compounding of advantages that robust control of a fuzzy control and high-adaptive control of the neural networks. Also, this paper is proposed control of maximum torque per ampere(MTPA) of induction moor. This strategy is reposed which is simple in structure and has the honest goal of minimizing the stator current magnitude for given load torque. The performance of the proposed induction motor drive with maximum torque control using FNN controller is verified by analysis results at dynamic operation conditions.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of Clinical Otolaryngology Head and Neck Surgery
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• v.29 no.2
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• pp.212-222
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• 2018

Background and Objectives : The purpose of this study was to compare the measured values of acoustic and auditory perceptual assessments between normal and functional dysphonia (FD) groups. Materials and Methods : 102 subjects with FD and 59 normal voice groups were participated in this study. Mid-vowel portion of the sustained vowel /a/ and two sentences of 'Sanchaek' were edited, concatenated, and analyzed by Praat script. And then auditory-perceptual (AP) rating was completed by three listeners. Results : The FD group showed higher acoustic voice quality index version 2.02 and version 3.01 (AVQIv2 and AVQIv3), slope, Hammarberg index (HAM), grade (G) and overall severity (OS), values than normal group. Additionally, smoothed cepstral peak prominence in Praat (PraatCPPS), tilt, low-to high spectral band energies (L/H ratio), long-term average spectrum (LTAS) in FD group were lower than normal voice group. And the correlation among measured values ranged from -0.250 to 0.960. In ROC curve analysis, cutoff values of AVQIv2, AVQIv3, PraatCPPS, slope, tilt, L/H ratio, HAM, and LTAS were 3.270, 2.013, 13.838, -22.286, -9.754, 369.043, 27.912, and 34.523, respectively, and the AUC of each analysis was over .890 in AVQIv2, AVQIv3, and PraatCPPS, over 0.731 in HAM, tilt, and slope, over 0.605 in LTAS and L/H ratio. Conclusions : In conclusion, AVQI and CPPS showed the highest predictive power for distinguishing between normal and FD groups. Acoustic analyses and AP rating as noninvasive examination can reinforce the screening capability of FD and help to establish efficient diagnosis and treatment process plan for FD.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.232-237
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• 2004

In many application of DC-DC converters, loads cannot be specified in advance, i.e., their amplitudes are suddenly changed from the zero to the maximum rating. Generally, design conditions are changed for each load and then each controller is re-designed. Then, a so-called robust DC-DC converter which can cover such extensive load changes and also input voltage changes with one controller is needed. Analog control IC is used usually for the controller of DC-DC converter. Simple integral control etc. are performed with the analog control IC. However it is difficult to retain sufficient robustness of DC-DC converter by these techniques. The authors proposed the method of designing an approximate 2-degree-of-freedom (2DOF) controller of DC-AC converter. This controller has an ability to attain sufficient robustness against extensive load and DC power supply changes. For applying this approximate 2DOF controller to DC-DC converter, it is necessary to improve the degree of approximation for better robustness. In this paper, we propose a method of designing good approximate 2DOF digital controller which makes the control bandwidth wider, and at the same time makes a variation of the output voltage very small at a sudden change of resistive load. The proposed good approximate 2DOF digital controller is actually implemented on a DSP and is connected to a DC-DC converter. Experimental studies demonstrate that this type digital controller can satisfy given specifications.

• Anxiety and mood
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• v.2 no.2
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• pp.101-107
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• 2006

Object : Since autonomic nerve system dysfunction was known as the mechanism of panic disorder, many researchers used heart rate variability (HRV) as means of measuring autonomic nerve function of patients with panic disorder. We aimed to examine the effect of paroxetine medication for 3 months on symptom improvement and change of heart rate variability of the patients with panic disorder. Methods : The subjects were patients with panic disorder who visited the psychiatric outpatient clinic of Samsung Medical Center in Seoul. We included panic disorder patients who were aged from 20 to 50 and in normal BMI range (from 18 to 30) to minimize the effect of age and weight on HRV data. We excluded the patients with EKG abnormalities, hypertension or other major psychiatric disorders. They took 20-40 mg paroxetine medication a day for 3 months. Alprazolam was used only during the first month to control the acute panic symptoms and was tapered off after that. We measured the acute panic inventory (API), Hamilton rating scale for anxiety and depression (HAM-A & HAM-D), Spielberger state-trait anxiety inventory (STAIS, STAIT), and Beck depression inventory (BDI) in order to assess clinical improvement of the patients. And we measured time and frequency domain HRV in the resting, standing and cognitive stress states to assess the change of HRV. All measurements were done before and after paroxetine treatment. Result : After paroxetine medication, patients showed significant improvement in all psychiatric scales. In time domain of HRV, standard deviations of all R-R intervals (SDNN) were significantly increased in all states. In frequency domain of HRV, the ratio of high frequency to total power (HF/TP) in the standing state was significantly increased. Conclusion : After 3 months paroxetine medication, panic disorder patients showed significant clinical improvement and change in HRV data such as SDNN in all states and HF/TP ratio in the standing state. This result suggests that paroxetine medication is effective for the improvement of autonomic nerve system dysfunction in panic disorder patients.