• Journal of Biomedical Engineering Research
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• v.43 no.3
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• pp.131-135
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• 2022

Due to COVID-19, Correct method of wearing mask is important to prevent COVID-19 and the other respiratory tract infections. And the deep learning technology in the image processing has been developed. The purpose of this study is to create the type of mask wearing dataset for deep learning models and select the deep learning model to detect the wearing mask correctly. The Image dataset is the 2,296 images acquired using a web crawler. Deep learning classification models provided by tensorflow are used to validate the dataset. And Object detection deep learning model YOLOs are used to select the detection deep learning model to detect the wearing mask correctly. In this process, this paper proposes to validate the type of mask wearing datasets and YOLOv5 is the effective model to detect the type of mask wearing. The experimental results show that reliable dataset is acquired and the YOLOv5 model effectively recognize type of mask wearing.

• The Journal of Economics, Marketing and Management
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• v.11 no.6
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• pp.1-8
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• 2023

Purpose: In the era of the Fourth Industrial Revolution, individuals equipped with fundamental understanding and practical skills in artificial intelligence (AI) are essential. This study aimed to validate the effectiveness of AI education for enhancing AI literacy among business major student. Research design, data and methodology: Data for analyzing the effectiveness of the AI Fundamental Education Program for business major students were collected through surveys conducted at the beginning and end of the semester. Structural equation modeling was employed to perform basic statistical analyses regarding gender, grade, and prior software (SW) education duration. To validate the effectiveness of AI education, seven variables - AI interest, AI perception, data analysis/utilization, AI projects, AI literacy, AI self-efficacy, and AI learning persistence - were defined and derived. Results: All seven operationally defined variables showed statistically significant positive changes. The average differences were observed as follows: 0.47 for AI interest, 0.32 for AI perception, 0.37 for data analysis/utilization, 0.27 for AI projects, 0.25 for AI literacy, 0.39 for AI self-efficacy, and 0.41 for AI learning persistence. Statistically, AI interest exhibited the most substantial average difference. Conclusions: Through this study, the applied AI education was confirmed to enhance learners' overall competencies in AI, proving its utility and effectiveness in AI literacy education for business major students. Future research endeavors should build upon these results, focusing on ongoing studies related to AI education programs tailored to learners from diverse academic backgrounds and conducting continuous efficacy evaluations.

• Journal of Research and Publication Ethics
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• v.5 no.2
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• pp.7-10
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• 2024

Purpose: The effectiveness of research ethics education in enabling researchers to think and judge ethically in conducting research. It is a fundamental solution for the establishment of research ethics in the research field, not only for current researchers but also for the next generation. It measured various variables related to ethics that can lead to ethical behavior through a quasi-experimental design to support the reliability of the study. Research Design, data and methodology: Examine prior research on research ethics and explore current research ethics education and practice. It aims to study how to effectively implement and validate specific aspects of research ethics. To investigate, study, and validate research ethics education and research ethics systems. Results: It is defined as the effectiveness or value of training as measured by changes in knowledge and behavior in reaction, learning, behavior, and outcome evaluations measured after learning. Conclusions: For the effectiveness of research ethics education, various support measures need to be mobilized for the spread and establishment of research ethics education. Formalized and continuous research ethics education is needed. It is important that the knowledge acquired through long-term and consistent research ethics training is transferred to ethical behavior in the research field.

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.1-22
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• 2016

News contents has been collected, selected, edited and sometimes distorted by the news recommendation mechanisms of online portals in nowadays. Prior studies had not confirmed the consensus of newsworthiness, and they had not tried to empirically validate the impacts of newsworthiness on audience reactions. This study challenged to summarize the concepts of newsworthiness and validate the impact of representativeness of both editor's and audience's perspective on audience reactions as perceived news quality, trust on news portal, perceived usefulness, service satisfaction, loyalty, continuous usage intention, and word-of-mouth intention by adopting the representativeness heuristics method and information adoption model. 357 valid data had been collected using a scenario survey method. Subjects in each groups are exposed by 3 news recommendation mechanisms: 1) the time-priority news exposure mechanism (control group), 2) the reference-score-based news recommendation mechanism (a single treatment group), and 3) the major-news-priority exposure mechanism sorting by the reference scores made by peer audiences (the mixed treatment group). Data had been analyzed by the MANOVA and PLS method. MANOVA results indicate that only mixed method of both editor and audience recommendation mechanisms impacts on perceived news quality and trust. PLS results indicate that perceived news quality and trust could significantly affect on the perceived usefulness, service satisfaction, loyalty, continuance usage, and word-of-mouth intention. This study would contributions to empathize the role of information technology in media industry, to conceptualize the news value in the balanced views of both editors and audiences, and to empirically validate the benefits of news recommendation mechanisms in academy. For practice, the results of this study suggest that online news portals would be better to make mixed news recommendation mechanisms to attract audiences.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.161-170
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• 2005

The Certificate Revocation List(CRL) or the Online Certificate Status Protocol(OCSP)has been used to validate certificates. However, the CRL cannot validate certificates in realtime because of the Time-Gap problem and the OCSP server overloads in a large scale secure system. In addition, the client cannot access a wired LAN until the client has been authenticated by the authentication server on the IEEE 802. 1x framework. Therefore, the client cannot validate the authentication server's certificate using a certificate validation server. Thus, the client cannot authenticate the authentication server in realtime. To solve these problems this paper designed a secure system that can protect the content of communications and authenticate users in realtime on a wireless LAN The designed certificate validation protocol was proved that the stability and efficiency of the system was very high, the result of the validation had the presence, the speed of the validation was not affected by the system scale, the number of authorities user must trust was reduced to one, and the overload of the validation server was Protected. And the designed user authentication and key exchange protocols were Proved that the mutual authentication was possible in realtime and the fact of the authentication could be authorized by the CA because of using the authorized certificates.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1753-1764
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• 2014

Numerical flow simulation models in the riverine environments have been widely utilized for analyzing flow dynamics in various degrees in researches and practical applications. However, most of the simulated results have been validated based on the data from indoor experimental models or very limited in-situ measurements. Therefore, it has been required to more accurately validate the performance of the numerical models in terms of the detailed field observations. In particular, it was also hard to validate the performances of the existing numerical models in the real meandered river channels that encompass more sophisticated flow and geometric structures. Recently, advancements of the modern flow measuring instrumentations such as acoustic Doppler current profilers (ADCPs) enabled us to efficiently acquire the detailed flow field in the broad range of river channels, thus that it became to be possible to accurately validate any numerical models with the field observations. In this study, based on the detailed flow measurements in a actual meandered river channel using ADCP, we validated FaSTMECH model in iRIC in terms of water surface elevation, which is relatively new but began to get highlighted in the research areas. As the validation site, a meandering channel in River Experiment Center of KICT was chosen, which has 6.5 m of width, 0.38m of flow depth, 1.54 m3/s of flow discharge, 0.61 m/s of mean flow velocity, and 1.2 of sinuosity. As results, whereas the FaSTMECH precisely simulated water surface elevation, simulated velocity field in the bend did not match well with ADCP dataset.

• Journal of Power Electronics
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• v.5 no.1
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• pp.1-10
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• 2005

This paper presents the application of a simple neuro-based speed control scheme of a permanent magnet (PM) dc motor. To validate its efficiency, the performance characteristics of the proposed simple neuro-based scheme are compared with those of a Neural Network controller and those of a Fuzzy Logic controller under different operating conditions. The comparative results show that the simple neuro-based speed control scheme is robust, accurate and insensitive to load disturbances.

• ETRI Journal
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• v.35 no.3
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• pp.542-545
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• 2013

State-of-the-art voice codecs have been developed to extend the input bandwidth to enhance quality while maintaining interoperability with a legacy codec. Most of them employ a modified discrete cosine transform (MDCT) for coding their extended band. We propose a source filter model-based coding algorithm of MDCT spectral coefficients, apply it to the ITU-T G.711.1 super wideband (SWB) extension codec, and subjectively test it to validate the model. A subjective test shows a better quality over the standardized SWB codec.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2654-2659
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• 2003

In this paper, we present biomimetic hopping strategy which is more human-like for legged robot through stiffness modulation. Stiffness value is calculated from the motion of body center of gravity. This method enable to reduce impact force on touch-down, adaption on ground stiffness change and height modulation. Simple selected models will be used to validate this method. For general model, singular perturbation is used for control and simulation using stiffness modulation is presented.

• KDI Journal of Economic Policy
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• v.39 no.4
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• pp.69-94
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• 2017

This paper re-examines the impacts an institutional arrangement may have on labour market outcomes such as the employment and unemployment rates. Based on the results from a generalized econometric model, the generosity of unemployment insurance benefits, organized labour and active labour market policy have effects on a labour market in line with previous findings. However, taxes on labour and the degree of employment protection are found to affect neither the employment rate nor the unemployment rate. Thus, some findings in this paper validate earlier findings, whereas others do not.