• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.77-88
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• 2021

Duck industry had a rapid growth in recent years. Nevertheless, researches to improve duck house environment are still not sufficient enough. Moisture generation of duck house litter is an important factor because it may cause severe illness and low productivity. However, the measuring process is difficult because it could be disturbed with animal excrements and other factors. Therefore, it has to be calculated according to the environmental data around the duck house litter. To cut through all these procedures, we built several machine learning regression model forecasting moisture generation of litter by measured environment data (air temperature, relative humidity, wind velocity and water contents). 5 models (Multi Linear Regression, k-Nearest Neighbors, Support Vector Regression, Random Forest and Deep Neural Network). have been selected for regression. By using R-Square, RMSE and MAE as evaluation metrics, the best accurate model was estimated according to the variables for each machine learning model. In addition, to address the small amount of data acquired through lab experiments, bootstrapping method, a technique utilized in statistics, was used. As a result, the most accurate model selected was Random Forest, with parameters of n-estimator 200 by bootstrapping the original data nine times.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.463-471
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• 2019

This paper proposes a method for reducing the complexity of LIC (Local Illuminance Compensation) for bi-directional inter prediction. The LIC performs local illumination compensation using neighboring reconstruction samples of the current block and the reference block to improve the accuracy of the inter prediction. Since the weight and offset required for local illumination compensation are calculated at both sides of the encoder and decoder using the reconstructed samples, there is an advantage that the coding efficiency is improved without signaling any information. Since the weight and the offset are obtained in the encoding prediction step and the decoding step, encoder and decoder complexity are increased. This paper proposes two methods for low complexity LIC. The first method is a method of applying illumination compensation with offset only in bi-directional prediction, and the second is a method of applying LIC after weighted average step of reference block obtained by bidirectional prediction. To evaluate the performance of the proposed method, BD-rate is compared with BMS-2.0.1 using B, C, and D classes of MPEG standard experimental image under RA (Random Access) condition. Experimental results show that the proposed method reduces the average of 0.29%, 0.23%, 0.04% for Y, U, and V in terms of BD-rate performance compared to BMS-2.0.1 and encoding/decoding time is almost same. Although the BD-rate was lost, the calculation complexity of the LIC was greatly reduced as the multiplication operation was removed and the addition operation was halved in the LIC parameter derivation process.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.206-216
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• 2020

As the number of aging railway bridges in Korea increases, maintenance costs due to aging are increasing and continuous management is becoming more important. However, while the number of old facilities to be managed increases, there is a shortage of professional personnel capable of inspecting and diagnosing these old facilities. To solve these problems, this study presents an improved model that can detect Local damage to structures using machine learning techniques of AI technology. To construct a damage detection machine learning model, an analysis model of the bridge was set by referring to the design drawing of a non-ballasted plate-girder railroad bridge. Static strain data according to the damage scenario was extracted with the analysis model, and the Local damage index based on the reliability of the bridge was presented using statistical techniques. Damage was performed in a three-step process of identifying the damage existence, the damage location, and the damage severity. In the estimation of the damage severity, a linear regression model was additionally considered to detect random damage. Finally, the random damage location was estimated and verified using a machine learning-based damage detection classification learning model and a regression model.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.338-347
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• 2021

In this paper, the beta-ray sensor circuit used in the true random number generator was designed using DB HiTek's 0.18㎛ CMOS process. The CSA circuit proposed a circuit having a function of selecting a PMOS feedback resistor and an NMOS feedback resistor, and a function of selecting a feedback capacitor of 50fF and 100fF. And for the pulse shaper circuit, a CR-RC2 pulse shaper circuit using a non-inverting amplifier was used. Since the OPAMP circuit used in this paper uses single power instead of dual power, we proposed a circuit in which the resistor of the CR circuit and one node of the capacitor of the RC circuit are connected to VCOM instead of GND. And since the output signal of the pulse shaper does not increase monotonically, even if the output signal of the comparator circuit generates multiple consecutive pulses, the monostable multivibrator circuit is used to prevent signal distortion. In addition, the CSA input terminal, VIN, and the beta-ray sensor output terminal are placed on the top and bottom of the silicon chip to reduce capacitive coupling noise between PCB traces.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.2
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• pp.73-78
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• 2022

Since Traditional Korean medicine (TKM) doctors use various knowledge systems during treatment, diagnosis results may differ for each TKM doctor. However, it is difficult to explain all the reasons for the diagnosis because TKM doctors use both explicit and implicit knowledge. In this study, an upgraded random forest (RF)-based evaluation tool was proposed to extract clinical knowledge of TKM doctors. Also, it was confirmed to what extent the professor's clinical knowledge was delivered to the trainees by using the evaluation tool. The data used to construct the evaluation tool were targeted at 106 people who visited the Sasang Constitutional Department at Kyung Hee University Korean Medicine Hospital at Gangdong. For explicit knowledge extraction, four TKM doctors were asked to express the importance of symptoms as scores. In addition, for implicit knowledge extraction, importance score was confirmed in the RF model that learned the patient's symptoms and the TKM doctor's constitutional determination results. In order to confirm the delivery of clinical knowledge, the similarity of symptoms that professors and trainees consider important when discriminating constitution was calculated using the Jaccard coefficient. As a result of the study, our proposed tool was able to successfully evaluate the clinical knowledge of TKM doctors. Also, it was confirmed that the professor's clinical knowledge was delivered to the trainee. Our tool can be used in various fields such as providing feedback on treatment, education of training TKM doctors, and development of AI in TKM.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.280-288
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• 2022

This study examined the diagnostics of abnormalities and faults of equipment, whose rotational speed changes even during regular operation. The purpose of this study was to suggest a procedure that can properly apply machine learning to the time series data, comprising non-stationary characteristics as the rotational speed changes. Anomaly and fault diagnosis was performed using machine learning: k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), and Random Forest. To compare the diagnostic accuracy, an autoencoder was used for anomaly detection and a convolution based Conv1D was additionally used for fault diagnosis. Feature vectors comprising statistical and frequency attributes were extracted, and normalization & dimensional reduction were applied to the extracted feature vectors. Changes in the diagnostic accuracy of machine learning according to feature selection, normalization, and dimensional reduction are explained. The hyperparameter optimization process and the layered structure are also described for each algorithm. Finally, results show that machine learning can accurately diagnose the failure of a variable-rotation machine under the appropriate feature treatment, although the convolution algorithms have been widely applied to the considered problem.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.215-224
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• 2008

The effect of streamflow considering future land use change and vegetation index information by climate change scenario was assessed using SLURP (Semi-distributed Land-Use Runoff Process) model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for the upstream watershed ($260.4km^2$) of Gyeongan water level gauging station. By applying CA-Markov technique, the future land uses (2030, 2060, 2090) were predicted after test the comparison of 2004 Landsat land use and 2004 CA-Markov land use by 1996 and 2000 land use data. The future land use showed a tendency that the forest and paddy decreased while urban, grassland and bareground increased. The future vegetation indices (2030, 2060, 2090) were estimated by the equation of linear regression between monthly NDVI of NOAA AVHRR images and monthly mean temperature of 5 years (1998-2002). Using CCCma CGCM2 simulation result based on SRES A2 and B2 scenario (2030s, 2060s, 2090s) of IPCC and data were downscaled by Stochastic Spatio-Temporal Random Cascade Model (SST-RCM) technique, the model showed that the future runoff ratio was predicted from 13% to 34% while the runoff ratio of 1999-2002 was 59%. On the other hand, the impact on runoff ratio by land use change showed about 0.1% to 1% increase.

• Journal of IKEEE
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• v.27 no.4
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• pp.644-649
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• 2023

As the cell spacing decreases during the scaling process of DRAM(Dynamic Random Access Memory), the reduction in STI(Shallow Trench Isolation) thickness leads to an increase in sub-threshold leakage due to the passing word line effect. The increase in sub-threshold leakage current caused by the voltage applied to adjacent passing word lines affects the data retention time and increases the number of refresh operations, thereby contributing to higher power consumption in DRAM. In this paper, we identify the causes of the passing word line effect through TCAD Simulation. As a result, we confirm the DRAM operational conditions under which the passing word line effect occurs, and observe that this effect alters the proportion of the total leakage current attributable to different causes. Through this, we recognize the necessity to consider not only leakage currents due to GIDL(Gate Induced Drain Leakage) but also sub-threshold leakage currents, providing guidance for improving DRAM structure.

• Journal of Radiation Industry
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• v.17 no.4
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• pp.345-357
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• 2023

Nuclear forensics has been understood as a mendatory component in the international society for nuclear material control and non-proliferation verification. Radiochronometry of nuclear activities for nuclear forensics are decay series characteristics of nuclear materials and the Bateman equation to estimate when nuclear materials were purified and produced. Radiochronometry values have uncertainty of measurement due to the uncertainty factors in the estimation process. These uncertainties should be calculated using appropriate evaluation methods that are representative of the accuracy and reliability. The IAEA, US, and EU have been researched on radiochronometry and uncertainty of measurement, although the uncertainty calculation method using the Bateman equation is limited by the underestimation of the decay constant and the impossibility of estimating the age of more than one generation, so it is necessary to conduct uncertainty calculation research using computer simulation such as Monte Carlo method. This highlights the need for research using computational simulations, such as the Monte Carlo method, to overcome these limitations. In this study, we have analyzed mathematical models and the LHS (Latin Hypercube Sampling) methods to enhance the reliability of radiochronometry which is to develop an uncertainty algorithm for nuclear material radiochronometry using Bateman Equation. We analyzed the LHS method, which can obtain effective statistical results with a small number of samples, and applied it to algorithms that are Monte Carlo methods for uncertainty calculation by computer simulation. This was implemented through the MATLAB computational software. The uncertainty calculation model using mathematical models demonstrated characteristics based on the relationship between sensitivity coefficients and radiative equilibrium. Computational simulation random sampling showed characteristics dependent on random sampling methods, sampling iteration counts, and the probability distribution of uncertainty factors. For validation, we compared models from various international organizations, mathematical models, and the Monte Carlo method. The developed algorithm was found to perform calculations at an equivalent level of accuracy compared to overseas institutions and mathematical model-based methods. To enhance usability, future research and comparisons·validations need to incorporate more complex decay chains and non-homogeneous conditions. The results of this study can serve as foundational technology in the nuclear forensics field, providing tools for the identification of signature nuclides and aiding in the research, development, comparison, and validation of related technologies.

• Journal of Korean Academy of Nursing
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• v.4 no.2
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• pp.78-92
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• 1974

It is the purpose of this study to make clear the way in which people can lead a more desirable human life, that is, to ascertain the method of achieving therapeutic change through transaction between nurses and psychiatric patients. The various problems proposed by th9 above-stated aims of study can be shown, such as: What kind of influences does the method of a nurse′s communication have upon the response of psychiatric patients? 1) What are the general methods of communication used by the nurses? 2) Are there any differences between the control group and experimental group in the patients′ "Child" response? 3) Are there any differences between the control group and experimental group in the Patients "Adult" response? 4) What is the most desirable method of communication for therapeutic change in the patients? In an effort to solve the above questions this study attempted and managed to draw a random sampling of 200 patients being accommodated in the National Mental Hospital by dividing them into two groups, experimental groups and control groups, and recording the transactions between nurses and patients. In the course of carrying,: out this study, the experimental group was interviewed by the nurses specially trained In the P.A.C theory. and the control group interviewed at random by the nurses with no special training in communication. Further, the communication between nurses and patients in a free, relaxed atmosphere was allowed only for 15 minutes, whereupon the nurses were requested to make process-recording according to her memory of nurse patient transaction. The process-recording which recorded a series ol transactions between the nurses and the patients was analyzed according to Berne and Harris′transactional Analysis Standard. Through this standard, the writer of this study examined the significance of difference to compare the transactions brought forth between the experimental group and the control group. The following is a summary of the study which the writer of this thesis undertook. Hypothesis to The method of communication which the nurses usually apply to the patients will be higher in "Parent" than in "Adult". The communication which the nurses carried out in the control group turned out to be not significant between "Adult" and "Parent" Accordingly hypothesis 1. carne to be rejected. Hypothesis 2. The patients "Adult" response will be higher in the experimental group than in the control group. According to the result of a CR examination, as the communication showed a significant difference on P〈.01 level′ hypothesis 2 became affirmative. Hypothesis 3. The patients′"Child" response will be higher in the control group than in the experimental group. Hypothesis 3 proved affirmative since it showed an significant degree on P〈.01 level according to the result of a CR examination. Hypothesis 4 "Adult" response of the patient will be higher in frequency by nurses′"Adult" stimulus than nurse′s "Parent" stimulus Chi-square examination revealed significant difference on P〈.05 level. Hypo. 4 is affirmed. The following conclusions are drawn out based on the result of this study. 1) The generally used method of communication stimulus used by nurses for patients proved to be "Adult" and "Parent" in similar proportion. 2) The group in which the nurses could increase the patients "Adult" response proved to be higher in the experimental group than in the control group. Therefore, the communication (or stimulus) which has been applied in the experimental group can be said to be possible method of achieving therapeutic change. 3) Since the patients′"Child" response were higher in the control group than in the experimental group the communication method used In the control group was suggested as the less agreeable method of achieving therapeutic change than that used in the experimental Group. 4) "Adult" response of patient was elicited in significantly greater percentage when the "Adult" stimulus was used by the nurse. Therefore the most desirable method of-communication to give therapeutic change definitely was shown to be the "Adult" stimulus. Recommendations for further studies are as follows: 1) Studies on nurses′role perception in nurse-patient relationships. 2) Studies on patients′response to the method of communication used by nurses according to variables such as sex, social status, educational background, state of health. 3) Application of T.A, method to various groups of patients. 4) Study of various methods to improve student skill in use of process recording.