• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.164-173
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• 2009

Automotive systems have tended to be equipped with many electronic contents to satisfy safety, comport, convenience, and entertainment services over the past years. As a result, the amount of vehicle embedded software in electrical/electronic(E/E) systems is steadily increasing to manage these requirements. This leads to the traditional, document-based software development in the vehicle embedded systems being increasingly displaced by a model-based development in order to reduce software development time and cost. Due to the application of model-based development, a great evolution is being realized in the aspect of efficiency, but the development is being made without sufficient testing. So, erroneous automotive embedded software may cause serious problems such as car accidents which relate to human safety. Therefore, efficient methods for model-based test and validation are needed to improve software reliability in the stage of embedded software development. This paper presents the model-based development and test method for AUTOSAR embedded software to improve its reliability and safety, and it is demonstrated based on the case study.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.3 no.2
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• pp.183-199
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• 1996

The Purpose of this study is to develop and test a nursing model which can be applied to prediction of the quality of life for the patient receiving hemodialysis. A hypothetical model was constructed on Johns & Meleis's empowerment model framework which has 3 contsructs(stress, resource, empowerment). 6 Factors(perceived stress, self-esteem as personal resource, perceived social support as social resource, perceived fertigue, perceived health status & self efficacy as empowerment) were selected to pre dict the quality of life of receiving hemodialysis patients. 4 Factors(self-esteem, perceived social support, perceived health status & self efficacy) had direct effects on the quality of life significantly. Self-esteem had indirect effect on the quality of life via perceived heath status significantly. Perceived social support had indirect effect on the quality of life via self-effcacy significantly. Perceived stress had no direct and indirect effect on the quality of life significantly. Revised model from hypothetical model showed better fit to the data by eliminating unsignificant path. From results of this study we suggest that to improve quality of life of hemodialysis patient nurses provide nursing interventions which improve self-esteem, perceived social support, self-efficacy & perceived health status.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.79-83
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• 2021

This paper proposes a novel image classification method based on few-shot learning, which is mainly used to solve model overfitting and non-convergence in image classification tasks of small datasets and improve the accuracy of classification. This method uses model structure optimization to extend the basic convolutional neural network (CNN) model and extracts more image features by adding convolutional layers, thereby improving the classification accuracy. We incorporated certain measures to improve the performance of the model. First, we used general methods such as setting a lower learning rate and shuffling to promote the rapid convergence of the model. Second, we used the data expansion technology to preprocess small datasets to increase the number of training data sets and suppress over-fitting. We applied the model to 10 monkey species and achieved outstanding performances. Experiments indicated that our proposed method achieved an accuracy of 87.92%, which is 26.1% higher than that of the traditional CNN method and 1.1% higher than that of the deep convolutional neural network ResNet50.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.738-754
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• 2024

Side-channel analysis (SCA) is a cryptanalytic technique that exploits physical leakages, such as power consumption or electromagnetic emanations, from cryptographic devices to extract secret keys used in cryptographic algorithms. Recent studies have shown that training SCA models with semi-supervised learning can effectively overcome the problem of few labeled power traces. However, the process of training SCA models using semi-supervised learning generates many pseudo-labels. The performance of the SCA model can be reduced by some of these pseudo-labels. To solve this issue, we propose the HWFilter method to improve semi-supervised SCA. This method uses a Hamming Weight Pseudo-label Filter (HWPF) to filter the pseudo-labels generated by the semi-supervised SCA model, which enhances the model's performance. Furthermore, we introduce a normal distribution method for constructing the HWPF. In the normal distribution method, the Hamming weights (HWs) of power traces can be obtained from the normal distribution of power points. These HWs are filtered and combined into a HWPF. The HWFilter was tested using the ASCADv1 database and the AES_HD dataset. The experimental results demonstrate that the HWFilter method can significantly enhance the performance of semi-supervised SCA models. In the ASCADv1 database, the model with HWFilter requires only 33 power traces to recover the key. In the AES_HD dataset, the model with HWFilter outperforms the current best semi-supervised SCA model by 12%.

• Journal of KIISE
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• v.42 no.11
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• pp.1386-1396
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• 2015

Graphical user interface testing (GUI testing) techniques have been widely used to test the functionality of Android applications (apps) and to detect faults for verification of the reliability and usability of apps. To adequately test the behaviors of apps, a number of studies on model-based GUI testing techniques have been performed on Android apps. However, the effectiveness of model-based techniques greatly depends on the quality of the GUI model, because model-based GUI testing techniques generate test inputs based on this model. Therefore, in order to improve testing effectiveness in model-based techniques, accurate and efficient GUI model generation has to be achieved using an improved model generation technique with concrete definition of GUI states. For accurate and efficient generation of a GUI model and test inputs, this study suggests a hierarchical GUI state comparison technique and evaluates this technique through comparison with the existing model-based techniques, considering activities as GUI states. Our results show that the proposed technique outperforms existing approaches and has the potential to improve the performance of model-based GUI testing techniques for Android apps.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.177-187
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• 2021

The purpose of the research to evaluate the efficiency and productivity growth rate of some Vietnamese commercial banks in the period 2008-2020. Using input and output selection theory, the author selected 2 models, estimating the efficiency for model 1 and estimating the yield change for both the models. We have built a model to estimate the efficiency and calculate as well as decompose the productivity growth of Vietnamese commercial banks during the period of active mergers and acquisitions activities in the banking system. Based on the results of the efficiency estimation, TFP shows during mergers and acquisitions, efficiency fluctuates but in an inverted U-shape (increasing from 2008-2011 but decreasing from 2013 to 2020). The estimated results of the impact assessment model show that FDI reduces the efficiency of banks. Productivity analysis shows that 6 out of 23 banks in the study period had positive TFP growth (tfpch > 1) due to technical progress and management efficiency. The findings of this study suggest that Vietnam's commercial banking system has many opportunities to improve operational efficiency in many aspects. In which, there are opportunities to increase credit, improve governance as well as improve the technology level of each bank. In addition, along with traditional products such as deposits and loans, diversification with a wide range of products and services is an important factor to enhance customer experience and demand in commercial banks.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.205-205
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• 2021

Surface soil moisture, which governs the partitioning of precipitation into infiltration and runoff, plays an important role in the hydrological cycle. The assimilation of satellite soil moisture retrievals into a land surface model or hydrological model has been shown to improve the predictive skill of hydrological variables. This study aims to improve streamflow prediction with Weather Research and Forecasting model-Hydrological modeling system (WRF-Hydro) by assimilating Soil Moisture Active and Passive (SMAP) data at 3 km and analyze its impacts on hydrological components. We applied Cumulative Distribution Function (CDF) technique to remove the bias of SMAP data and assimilate SMAP data (April to July 2015-2019) into WRF-Hydro by using an Ensemble Kalman Filter (EnKF) with a total 12 ensembles. Daily inflow and soil moisture estimates of major dams (Soyanggang, Chungju, Sumjin dam) of South Korea were evaluated. We investigated how hydrologic variables such as runoff, evaporation and soil moisture were better simulated with the data assimilation than without the data assimilation. The result shows that the correlation coefficient of topsoil moisture can be improved, however a change of dam inflow was not outstanding. It may attribute to the fact that soil moisture memory and the respective memory of runoff play on different time scales. These findings demonstrate that the assimilation of satellite soil moisture retrievals can improve the predictive skill of hydrological variables for a better understanding of the water cycle.

• Journal of Information Technology Services
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• v.22 no.6
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• pp.37-53
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• 2023

With the development of the 4th industrial revolution, companies are trying to introduce new AI technologies and improve their performance. In particular, chatbot technology has developed and can not only communicate smoothly with humans, but also perform many complex tasks, so it has high market potential. However, there is still little research on chatbots in the field of e-commerce. Accordingly, this study aims to suggest ways to improve corporate performance through chatbot user satisfaction analysis. With the rapid development of China's e-commerce platform, In this study, through previous studies, the characteristics of chatbots were classified into accessibility, accuracy, empathy, reliability, and intimacy as factors influencing perceived usefulness, perceived ease, and perceived enjoyment of the Technology Acceptance Model (TAM). Five were selected and used as independent variables, and a model that affects customer satisfaction was set up. This paper sets user satisfaction as an important indicator of chatbot service and analyzes the path that affects user satisfaction, thereby improving chatbot service technology. It is important in that it provides a way to improve the smart chatbot service by understanding the degree of user acceptance in depth.

• Journal of Digital Contents Society
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• v.10 no.2
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• pp.299-307
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• 2009

It is well-known that the scenic visibility achieved in our naked eyes is related with the quality of aerosol condition which is composed of primary and secondary air pollutants. In recent, the IMPROVE organization in U.S.A. has developed two algorithms to estimate the visible length depending on the elements of air pollutant. Using these algorithms, we are to represent the condition of aerosol quality with the well-known scenic images of the observing area so that any one that have no sufficient chemical knowledge may feel and understand the level of air pollution in visuality.

• Journal of KIISE
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• v.43 no.9
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• pp.953-962
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• 2016

Model-based testing is a technique for performing the test by using a model that represents the behavior of the system as a system specification. Industrial domains such as automotive, military/aerospace, medical, railway and nuclear power generation require model-based testing and code coverage-based testing to improve the quality of software. Despite the fact that both model-based testing and code coverage-based testing are required, difficulty in achieving a high coverage using model-based testing caused by the abstraction level difference between the test model and the source code, results in the need for performing model-based testing separately. In this study, to overcome the limitations of the existing model-based testing, we proposed the state machine transformation method to effectively improve the code coverage using the protocol state machine, one of the typical modeling methods is used as the test model in model-based testing, as the test model. In addition, we performed a case study of both systems and analyzed the effectiveness of the proposed method.