• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.485-489
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• 2002

The concepts from OOP have been integrated in a concurrency, leading to the emergence of concurrent OOP. Concurrency of concurrent OOP and various model technique of OOP language are integrated had been proposed. Concurrent programming and OOP technique unite that can gain various kinds advantage to develop concurrency application program. There have been a number of models proposed for integrating concurrency and OOP However, concurrency and inheritance are two paradigms which are difficult to combine in a suitable manner. The inheritance anomaly is the conclicted phenomena, which occurs only when concurrency is integrated with inheritance. The inheritance anoay is referred to as the serious difficulty in integrating inheritance and concurrency in a simple and efficient manner within a concurrent OOP. Concurrency and inheritance with integrated that Drop reusability of object remarkably and require re-justice of code that is inherited in subclass. So concurrency and inheritance with integrated Collision that happen between two special qualitys or Interference phenomenon is inheritance anomaly. Effect of inheritance anomaly minimum Much study findings announced about access method to improve code reusability. Wish to approach in paper that is division by synchronization code and method code to solve interference problem between and concurrency.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.543-554
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• 2013

Model-Driven Development(MDD) helps developers verify requirements and design issues of a software system in the early stage of development process by taking advantage of a software model which is the most highly abstracted form of a software system. In practice, however, many software systems have been developed through a code-centric method that builds a software system bottom-up rather than top-down. So, without support of appropriate tools, it is not easy to introduce MDD to real development process. Although there are many researches about extracting a model from code to help developers introduce MDD to code-centrically developed system, most of them only extracted base-level models. However, using concept of abstract component one can continuously extract higher level model from base-level model. In this paper we propose a practical method for automatic extraction of base level abstract component from source code, which is the first stage of continuous extraction process of abstract component, and validate the method by implementing an extraction tool based on the method. Target code chosen is the source code of TinyOS, an operating system for wireless sensor networks. The tool is applied to the source code of TinyOS, written in nesC language.

• The Korean Nurse
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• v.37 no.2
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• pp.53-62
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• 1998

ursing as a profession is characterized by its holistic, mind-body-spirit approach to the patient. Also, nurses have historically been the leaders in health education and promotion. Parish nursing has a great potential for providing primary preventive health care. services as well as assisting people to access the health care system. While working in the community, parish nurses see the church as the new arena for delivering health care services. The parish nurse program was introduced by Granger Westberg in 1984. The concept of parish nursing is based on several beliefs; health is multidimensional and affects all aspects of an individual-physical, psychological, social, and spiritaul being. Parish nursing is one model in which churches can cooperatively work with health care institutions to address the needs of their parishioners. The role of the parish nurse is emphasized in four basic area: a) health education, b) health counseling, c) referal services, and d) facilitation and organization of support groups within the congregation. The parish nurse programs work chiefly in congregation or commuity where a certain language of faith is ready at hand. This means that the parish nurse works in an ecology of meanings and care which encourages the drawing on the message of God's grace, the practices and habits it encourages. The parish nurse may be involved in the church's health ministries and may work on either paid or volunteer basis; however, one of the most important qualification of the parish nurse is to have the nursing knowledge and skills to practice within the standards of Nursing Practice Act. The completion of standards of practice for professional nurses practicing as parish nurses had been identified as a priority by the HMA Executive Board (1996, HMA). In conclusion, parish nursing promotes health and healing by empowering the faith community, family, or individual to incorporate health and healing practices. There are several preconditions that should proceed to establish the foundation for successful development of the parish nursing program in Korea. First, reciprocal relationship with home health nursing should be considered. Second, correct terms and concepts of parish nursing should be studied and understood. Third, systematic study and investigation should be followed for further development of parish nursing. Fourth, strengths and weaknesses of different models should be studied to develop proper model of parish nursing for Korean situation. Finally, consensus of standardized education program and corporation with various religious communities as well as health institutions should be established. When these preconditions are met, the role of parish nursing as a new program for the promotion of holistic health will be established.

• Communications of Mathematical Education
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• v.33 no.1
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• pp.1-19
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• 2019

This study deals with the case of student-centered discrete mathematics class with cyber lab. First, we provided lecture notes and cyber labs we developed. In particular, discrete mathematics is a course that covers the principles of algorithms. The purpose of this study is to provide students with basic mathematics, aiming to actively participate in the learning process, to improve their abilities and to reach the ultimate goal of student success with confidence. Second, based on interactions, students were able to prepare for the lectures, review, question, answer, and discussion through an usual learning management system of the school. Third, all the students generated materials through one semester, which were reported, submitted, presented and evaluated. It was possible to improve the learning effectiveness through the discussions and implementation of using some easy open source programming language and codes. Our discrete math laboratory could be practiced without any special knowledge of coding. These lecture models allow students to develop critical thinking skills while describing and presenting their learning and problem-solving processes. We share our experience and our materials including lecture note and cyber lab as well as a possible model of student-centered mathematics class that does not give too much of work load for instructors. This study shares a model that demonstrates that any professor will be able to have an individualized, customized, and creative discrete education without spending much of extra time and assistant, unlike previous research.

• Journal of Korean Neurosurgical Society
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• v.64 no.1
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• pp.125-135
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• 2021

Objective : This study aimed to validate the Korean version of the Repeatable Battery for the Assessment of Neuropsychological Status Update (K-RBANS). Methods : We performed a retrospective analysis of 283 psychiatric and neurosurgery patients. To investigate the convergent validity of the K-RBANS, correlation analyses were performed for other intelligence and neuropsychological test results. Confirmatory factor analysis was used to test a series of alternative plausible models of the K-RBANS. To analyze the various capabilities of the K-RBANS, we compared the area under the receiver operating characteristic (ROC) curves (AUC). Results : Significant correlations were observed, confirming the convergent validity of the K-RBANS among the Total Scale Index (TSI) and indices of the K-RBANS and indices of intelligence (r=0.47-0.81; p<0.001) and other neuropsychological tests at moderate and above significance (r=0.41-0.63; p<0.001). Additionally, the results testing the construct validity of the K-RBANS showed that the second-order factor structure model (model 2, similar to an original factor structure of RBANS), which includes a first-order factor comprising five index scores (immediate memory, visuospatial capacity, language, attention, delayed memory) and one higher-order factor (TSI), was statistically acceptable. The comparative fit index (CFI) (CFI, 0.949) values and the goodness of fit index (GFI) (GFI, 0.942) values higher than 0.90 indicated an excellent fit. The root mean squared error of approximation (RMSEA) (RMSEA, 0.082) was considered an acceptable fit. Additionally, the factor structure of model 2 was found to be better and more valid than the other model in χ2 values (Δχ2=7.69, p<0.05). In the ROC analysis, the AUCs of the TSI and five indices were 0.716-0.837, and the AUC of TSI (AUC, 0.837; 95% confidence interval, 0.760-0.896) was higher than the AUCs of the other indices. The sensitivity and specificity of TSI were 77.66% and 78.12%, respectively. Conclusion : The overall results of this study suggest that the K-RBANS may be used as a valid tool for the brief screening of neuropsychological patients in Korea.

• Analytical Science and Technology
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• v.34 no.6
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• pp.241-250
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• 2021

Calibration curves are essential in quantitative methods and for improving the accuracy of analyte measurements in biological samples. In this study, a statistical analysis model built in the R language (The R Foundation for Statistical Computing) was used to identify a set of weighting factors and regression models based on a stepwise selection criteria. An LC-MS/MS method was used to detect the presence of urinary methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹ -tetrahydrocannabinol in a sample set. Weighting factors for the calibration curves were derived by calculating the heteroscedasticity of the measurements, where the presence of heteroscedasticity was determined via variance tests. The optimal regression model and weighting factor were chosen according to the sum of the absolute percentage relative error. Subsequently, the order of the regression model was calculated using a partial variance test. The proposed statistical analysis tool facilitated selection of the optimal calibration model and detection of methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹-tetrahydrocannabinol in urine. Thus, this study for the selection of weighting and the use of a complex regression equation may provide insights for linear and quadratic regressions in analytical and bioanalytical measurements.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.347-364
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• 2022

Fraudulent companies or sellers strategically manipulate reviews to influence customers' purchase decisions; therefore, the reliability of reviews has become crucial for customer decision-making. Since customers increasingly rely on online reviews to search for more detailed information about products or services before purchasing, many researchers focus on detecting manipulated reviews. However, the main problem in detecting manipulated reviews is the difficulties with obtaining data with manipulated reviews to utilize machine learning techniques with sufficient data. Also, the number of manipulated reviews is insufficient compared with the number of non-manipulated reviews, so the class imbalance problem occurs. The class with fewer examples is under-represented and can hamper a model's accuracy, so machine learning methods suffer from the class imbalance problem and solving the class imbalance problem is important to build an accurate model for detecting manipulated reviews. Thus, we propose an OpenAI-based reviews generation model to solve the manipulated reviews imbalance problem, thereby enhancing the accuracy of manipulated reviews detection. In this research, we applied the novel autoregressive language model - GPT-3 to generate reviews based on manipulated reviews. Moreover, we found that applying GPT-3 model for oversampling manipulated reviews can recover a satisfactory portion of performance losses and shows better performance in classification (logit, decision tree, neural networks) than traditional oversampling models such as random oversampling and SMOTE.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.31-31
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• 2023

During December 2022, the northeast monsoon, which dominates the south and the Gulf of Thailand, had significant rainfall that impacted the lower southern region, causing flash floods, landslides, blustery winds, and the river exceeding its bank. The Golok River, located in Narathiwat, divides the border between Thailand and Malaysia was also affected by rainfall. In flood management, instruments for measuring precipitation and water level have become important for assessing and forecasting the trend of situations and areas of risk. However, such regions are international borders, so the installed measuring telemetry system cannot measure the rainfall and water level of the entire area. This study aims to predict 72 hours of water level and evaluate the situation as information to support the government in making water management decisions, publicizing them to relevant agencies, and warning citizens during crisis events. This research is applied to machine learning (ML) for water level prediction of the Golok River, Lan Tu Bridge area, Sungai Golok Subdistrict, Su-ngai Golok District, Narathiwat Province, which is one of the major monitored rivers. The eXtreme Gradient Boosting (XGBoost) algorithm, a tree-based ensemble machine learning algorithm, was exploited to predict hourly water levels through the R programming language. Model training and testing were carried out utilizing observed hourly rainfall from the STH010 station and hourly water level data from the X.119A station between 2020 and 2022 as main prediction inputs. Furthermore, this model applies hourly spatial rainfall forecasting data from Weather Research and Forecasting and Regional Ocean Model System models (WRF-ROMs) provided by Hydro-Informatics Institute (HII) as input, allowing the model to predict the hourly water level in the Golok River. The evaluation of the predicted performances using the statistical performance metrics, delivering an R-square of 0.96 can validate the results as robust forecasting outcomes. The result shows that the predicted water level at the X.119A telemetry station (Golok River) is in a steady decline, which relates to the input data of predicted 72-hour rainfall from WRF-ROMs having decreased. In short, the relationship between input and result can be used to evaluate flood situations. Here, the data is contributed to the Operational support to the Special Water Resources Management Operation Center in Southern Thailand for flood preparedness and response to make intelligent decisions on water management during crisis occurrences, as well as to be prepared and prevent loss and harm to citizens.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.23-31
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• 2023

Software development involves a series of stages, including requirements analysis, design, implementation, unit testing, and integration testing, similar to those used in the system engineering process. This study utilized MathWorks' model-based design platform to develop multi-function radar software and evaluated its feasibility and efficiency. Because the development of conventional radar software is performed by a unit algorithm rather than in an integrated form, it requires additional efforts to manage the integrated software, such as requirement analysis and integrated testing. The mode-based platform applied in this paper provides an integrated development environment for requirements analysis and allocation, algorithm development through simulation, automatic code generation for deployment, and integrated requirements testing, and result management. With the platform, we developed multi-level models of the multi-function radar software, verified them using test harnesses, managed requirements, and transformed them into hardware deployable language using the auto code generation tool. We expect this Model-based integrated development to reduce errors from miscommunication or other human factors and save on the development schedule and cost.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.21-30
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• 2023

The study proposes a model that utilizes Python-based deep learning text classification techniques to detect the legality of illegal financial advertising posts on the internet. These posts aim to promote unlawful financial activities, including the trading of bank accounts, credit card fraud, cashing out through mobile payments, and the sale of personal credit information. Despite the efforts of financial regulatory authorities, the prevalence of illegal financial activities persists. By applying this proposed model, the intention is to aid in identifying and detecting illicit content in internet-based illegal financial advertisining, thus contributing to the ongoing efforts to combat such activities. The study utilizes convolutional neural networks(CNN) and recurrent neural networks(RNN, LSTM, GRU), which are commonly used text classification techniques. The raw data for the model is based on manually confirmed regulatory judgments. By adjusting the hyperparameters of the Korean natural language processing and deep learning models, the study has achieved an optimized model with the best performance. This research holds significant meaning as it presents a deep learning model for discerning internet illegal financial advertising, which has not been previously explored. Additionally, with an accuracy range of 91.3% to 93.4% in a deep learning model, there is a hopeful anticipation for the practical application of this model in the task of detecting illicit financial advertisements, ultimately contributing to the eradication of such unlawful financial advertisements.