• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.65-72
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• 2021

We consider the joint optimization problem of transmit power level, MMSE receiver filter and access point(AP) selection for multi access points environment. In the previous work, transmit power and MMSE receiver filter were jointly optimized[1] and transmit power and best access point were optimized jointly[2]. For each case, the algorithm was proposed and its convergence which guarantees the minimum total transmit power was proved. In this paper, we further improve the algorithm by jointly optimizing three parameters. More specifically, 1) we propose the algorithm by considering transmit power, MMSE receiver filter and access point selection jointly. 2) we prove that the proposed algorithm guarantees convergence with minimum transmit power consumption. In the simulation results, it is shown that proposed algorithm outperforms two other algorithms, i.e., 1) algorithm with transmit power and MMSE receiver filter, and 2) algorithm with transmit power and best access point selection.

• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.145-159
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• 2021

Purpose: A statistical similarity evaluation to compare pharmacokinetics(PK) profile data between nonclinical and clinical experiments has become a significant issue on many drug development processes. This study proposes a new similarity index by considering important parameters, such as the area under the curve(AUC) and the time-series profile of various PK data. Methods: In this study, a new profile similarity index(PSI) by using the concept of a process capability index(Cp) is proposed in order to investigate the most similar animal PK profile compared to the target(i.e., Human PK profile). The proposed PSI can be calculated geometric and arithmetic means of all short term similarity indices at all time points on time-series both animal and human PK data. Designed simulation approaches are demonstrated for a verification purpose. Results: Two different simulation studies are conducted by considering three variances(i.e., small, medium, and large variances) as well as three different characteristic types(smaller the better, larger the better, nominal the best). By using the proposed PSI, the most similar animal PK profile compare to the target human PK profile can be obtained in the simulation studies. In addition, a case study represents differentiated results compare to existing simple statistical analysis methods(i.e., root mean squared error and quality loss). Conclusion: The proposed PSI can effectively estimate the level of similarity between animal, human PK profiles. By using these PSI results, we can reduce the number of animal experiments because we only focus on the significant animal representing a high PSI value.

• Journal of muscle and joint health
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• v.28 no.1
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• pp.30-40
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• 2021

Purpose: This study aims to present nurses' legal conflicts and legal basis through the precedent analysis of a crime of professional negligence resulting in death and injury for the past 20 years and provide vital references to cultivate the correct and high-level legal consciousness of nurses. Methods: This study was conducted in five stages of the systematic content analysis method. It amalyses the precedents of a crime of nurses' professional negligence resulting in death and injury from 2000 to 2020. The application system for the provision of the written judgment was used to collect precedents. A total of 67 cases were analyzed in this study, and they were classified according to the type of nursing error, and the contents were systematically analyzed. Results: A total of 52 cases (77.5%) of nursing errors were caused by independent nursing practices. They were classified as 38 cases (A1) in the violation of patient supervision obligations, 12 cases in the violation of progress observation obligations (A2), one case in the violation of medical equipment inspection obligations (A3), and one case in the violation of explanation and verification obligations. Among the non-independent nursing practices (code B), B1 was 10 cases related to administrative acts, one blood transfusion accident (B2), and one anesthesia accident (B3). Conclusion: To prevent nurses from being involved in legal confits, the advocation of systematic training such as nurses' legal obligations and judgment grounds through case-based learning from the recent precedent analysis and promote nurses' legal perspective, and preventive activities are essential.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.23-30
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• 2021

An Automated Industry and Occupation Coding System assigns statistical classification code to the enormous amount of natural language data collected from people who write about their industry and occupation. Unlike previous studies that applied information retrieval, we propose a system that does not need an index database and gives proper code regardless of the level of classification. Also, we show our model, which utilized KoBERT that achieves high performance in natural language downstream tasks with deep learning, outperforms baseline. Our method achieves 95.65%, 91.51%, and 97.66% in Occupation/Industry Code Classification of Population and Housing Census, and Industry Code Classification of Census on Basic Characteristics of Establishments. Moreover, we also demonstrate future improvements through error analysis in the respect of data and modeling.

• Journal of Korean Academy of Nursing
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• v.49 no.4
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• pp.437-448
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• 2019

Purpose: This study was conducted to test a path model for the factors related to undergraduate nursing students' clinical practicum stress, based on Lazarus and Folkman's stress-coping model. Methods: This study utilized a path analysis design. A total of 235 undergraduate nursing students participated in this study. The variables in the hypothetical path model consisted of clinical practicum, emotional intelligence, self-efficacy, Nun-chi, and nursing professionalism. We tested the fit of the hypothetical path model using SPSS/WIN 23.0 and AMOS 22.0. Results: The final model fit demonstrated a satisfactory statistical acceptance level: goodness-of-fit-index=.98, adjusted goodness-of-fit-index=.91, comparative fit index=.98, normed fit index=.95, Tucker-Lewis index=.92, and root mean square error of approximation=.06. Self-efficacy (${\beta}=-.22$, p=.003) and Nun-chi behavior (${\beta}=-.17$, p=.024) were reported as significant factors affecting clinical practicum stress, explaining 10.2% of the variance. Nursing professionalism (${\beta}=.20$, p=.006) and self-efficacy (${\beta}=.45$, p<.001) had direct effects on emotional intelligence, explaining 45.9% of the variance. Self-efficacy had indirect effects on Nun-chi understanding (${\beta}=.20$, p<.001) and Nun-chi behavior (${\beta}=.09$, p=.005) through emotional intelligence. Nursing professionalism had indirect effects on Nun-chi understanding (${\beta}=.09$, p=.005) and Nun-chi behavior (${\beta}=.09$, p=.005) through emotional intelligence. The variables for self-efficacy and nursing professionalism explained 29.1% of the Nun-chi understanding and 18.2% of the Nun-chi behavior, respectively. Conclusion: In undergraduate nursing education, it is important to identify and manage factors that affect clinical practicum stress. The findings of this study emphasize the importance of Nun-chi, self-efficacy, emotional intelligence, and nursing professionalism in the development of an educational strategy for undergraduate nursing students.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.101-106
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• 2019

This paper propose the VSS-FC-MMA algorithm that is possible to improve the equalization performance based on varying step size to the FC-MMA adaptive equalization algorithm in order to reducing the intersymbol interference effect occurred in the nonconstant modulus signal transmission, and improved performance were confirmed. The FC-MMA is possible to improve the convergence speed, and degrades the steady state performance based on the fixed step size and modified dispersion constant considering the level number of signal symbol for obtain the error signal in adaptive equalization compared to MMA. The proposed VSS-FC-MMA uses varying step size and current FC-MMA possible to improve the steady state equalization performance, it was confirmed by computer simulation. For this, the signal recovery capabilities and residual isi, MSE, SER were applied for performance comparison index in the same channel and signal to noise ratio. As a result of computer simulation, the proposed VSS-FC-MMA improve the risidual value in steady state and SER performance than the FC-MMA, but has 1.7 times slow convergence time by using varying step size.

• Journal of Korean Society on Water Environment
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• v.35 no.5
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• pp.425-431
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• 2019

Recently, people have been attracting attention to the good quality of water resources as well as water welfare. to improve the quality of life. This study is a papers on the prediction of benthic macroinvertebrate index (BMI), which is a aquatic ecological health, using the machine learning based CFS (Correlation-based Feature Selection) method and the random forest model to compare the measured and predicted values of the BMI. The data collected from the Han River's branch for 10 years are extracted and utilized in 1312 data. Through the utilized data, Pearson correlation analysis showed a lack of correlation between single factor and BMI. The CFS method for multiple regression analysis was introduced. This study calculated 10 factors(water temperature, DO, electrical conductivity, turbidity, BOD, $NH_3-N$, T-N, $PO_4-P$, T-P, Average flow rate) that are considered to be related to the BMI. The random forest model was used based on the ten factors. In order to prove the validity of the model, $R^2$, %Difference, NSE (Nash-Sutcliffe Efficiency) and RMSE (Root Mean Square Error) were used. Each factor was 0.9438, -0.997, and 0,992, and accuracy rate was 71.6% level. As a result, These results can suggest the future direction of water resource management and Pre-review function for water ecological prediction.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.23-30
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• 2020

In this study, the relationship between natural gas (NG) data and gas-related environmental elements was performed using machine learning algorithms to predict the level of gas leakage risk without directly measuring gas leakage data. The study was based on open data provided by the server using the IoT-based remote control Picarro gas sensor specification. The naturel gas leaks into the air, it is a big problem for air pollution, environment and the health. The proposed method is multivariate outlier removing method based Random Forest (RF) classification for predicting risk of NG leak. After, unsupervised k-means clustering, the experimental dataset has done imbalanced data. Therefore, we focusing our proposed models can predict medium and high risk so best. In this case, we compared the receiver operating characteristic (ROC) curve, accuracy, area under the ROC curve (AUC), and mean standard error (MSE) for each classification model. As a result of our experiments, the evaluation measurements include accuracy, area under the ROC curve (AUC), and MSE; 99.71%, 99.57%, and 0.0016 for MOL_RF respectively.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.445-460
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• 2011

The objective of this study was to construct and assess the applicability of the EFDC model for Saemangeum Reservoir as a 3D hydrodynamic and water quality modeling tool that is necessary for the effective management of water quality and establishment of conservation measures. The model grids for both reservoir system only and reservoir-ocean system were created using the most recent survey data to compare the effects of different downstream boundary conditions. The model was applied for the simulations of temperature, salinity, water quality variables including chemical oxygen demand (COD), chlorophyll-a (Chl-a), phosphorus and nitrogen species and algal biomass, and validated using the field data obtained in 2008. Although the model reasonably represented the temporal and spatial variations of the state variables in the reservoir with limited boundary forcing data, the salinity level was underestimated in the middle and upstream of the reservoir when the flow data were used at downstream boundaries; Sinsi and Garyuk Gates. In turn, the error caused to increase the bias of water quality simulations, and inaccurate simulation of density flow regime of river inflow during flood events. It is likely because of the loss of momentum of sea water intrusion at downstream boundaries. In contrast to flow boundary conditions, the mixing between sea water and freshwater was well reproduced when open water boundary condition was applied. Thus, it is required to improve the downstream boundary conditions that can accommodate the real operations of the sluice gates.

• Journal of Platform Technology
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• v.8 no.4
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• pp.47-58
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• 2020

DO-330 Software Tool Qualification Considerations is a guideline for development of tools used to develop/verify software and hardware installed on aircraft. And among several processes, the verification process is very crucial as it occupies a large proportion for DO-330. Especially, in order to qualify tool with high safety level, test objectives must be performed with independence, accordingly, more time, cost, and manpower are required than other objectives. In addition, even if the test cases or test procedures are well defined, the higher the complexity of the test the higher probability of human error occurs. In this paper, we propose Script-based Test Automation Agent software structure for efficient DO-330 verification process of A661UAGEN tool developed by Hanwha Systems. Compared to the test performed manually by the test engineer, testing time of the Script-based Test Automation Agent is reduced by 87.5% and testing productivity is increased by 43.75%.