• Structural Engineering and Mechanics
• /
• v.68 no.6
• /
• pp.691-700
• /
• 2018

Ground granulated blast furnace slag (GGBS) is a by product obtained from iron and steel industries, useful in the design and development of high quality cement paste/mortar and concrete. This paper investigates the applicability of relevance vector machine (RVM) based regression model to predict the compressive strength of various GGBS based concrete mixes. Compressive strength data for various GGBS based concrete mixes has been obtained by considering the effect of water binder ratio and steel fibres. RVM is a machine learning technique which employs Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM is an extension of support vector machine which couples probabilistic classification and regression. RVM is established based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Compressive strength model has been developed by using MATLAB software for training and prediction. About 70% of the data has been used for development of RVM model and 30% of the data is used for validation. The predicted compressive strength for GGBS based concrete mixes is found to be in very good agreement with those of the corresponding experimental observations.

• Journal of Radiation Protection and Research
• /
• v.44 no.3
• /
• pp.90-96
• /
• 2019

The contributions of nuclear science and technology in enhancing prosperity and quality of life all over the world and its potential to achieve many important Sustainable Developments Goals (SDGs) of the United Nations are well recognized. It also is now recognized that with fewer students getting attracted to Science, Technology, Engineering and Mathematics (STEM) in general and nuclear science and technology (NST) in particular; hence, there is a vital need to reach out to young students to provide the crucial human resources needed for these endeavours to continue in this highly specialized area. The success of a recently completed IAEA project related to introducing NST during 2012-2016 in secondary schools in the Asia-Pacific region countries encouraged the formulation of a new IAEA TC project RAS0079 entitled "Educating Secondary Students and Science Teachers on Nuclear Science and Technology" for 2018-2021, focusing on enhancing existing educational approaches through training and development opportunities both for teachers and students. The project aims at reaching a million students during the project duration while keeping the depth of learning between teacher and student. The strategy of executing the project, implementation status and its impact so far is presented in this paper.

• ETRI Journal
• /
• v.41 no.4
• /
• pp.415-425
• /
• 2019

Generative adversarial networks (GAN) have been successfully used in many image restoration tasks, including image denoising, super-resolution, and compression artifact reduction. By fully exploiting its characteristics, state-of-the-art image restoration techniques can be used to generate images with photorealistic details. However, there are many applications that require faithful rather than visually appealing image reconstruction, such as medical imaging, surveillance, and video coding. We found that previous GAN-training methods that used a loss function in the form of a weighted sum of fidelity and adversarial loss fails to reduce fidelity loss. This results in non-negligible degradation of the objective image quality, including peak signal-to-noise ratio. Our approach is to alternate between fidelity and adversarial loss in a way that the minimization of adversarial loss does not deteriorate the fidelity. Experimental results on compression-artifact reduction and super-resolution tasks show that the proposed method can perform faithful and photorealistic image restoration.

• International Journal of Advanced Culture Technology
• /
• v.7 no.1
• /
• pp.8-13
• /
• 2019

Despite technical advances in healthcare, the rates of hospital-acquired pressure injury (HAPI) are still high although many are potentially preventable. The purpose of this study was to determine whether tree-based prediction modeling is suitable for assessing the risk of HAPI in ICU patients. Retrospective cohort study has been carried out. A decision tree model was constructed with Age, Weight, eTube, diabetes, Braden score, Isolation, and Number of comorbid conditions as decision nodes. We used RStudio for model training and testing. Correct prediction rate of the final prediction model was 92.4 and the Area Under the ROC curve (AUC) was 0.699, which means there is about 70% chance that the model is able to distinguish between HAPI and non-HAPI. The results of this study has limited generalizability as the data were from a single academic institution. Our research finding shows that the data-driven tree-based prediction modeling may potentially support ICU sensitive risk assessment for HAPI prevention.

• Journal of Korean Biological Nursing Science
• /
• v.21 no.1
• /
• pp.1-11
• /
• 2019

Purpose: The purpose of this review was to evaluate the effects of emergency nursing simulation program on nursing students and nurses. Methods: This systematic review was performed as per the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and using the R program meta package (version 4.9-2). RISS, KISS, and DBpia Library databases were searched for studies published between June 2000 and August 2018 using the following key words: ($Emerge^*$ OR nursing) AND ($nurs^*$ OR simulation). Selected studies were assessed for methodological quality using Risk of Bias for Non randomized Studies. Results: 7 studies were identified and all of them met the inclusion criteria. The outcome variables were significant clinical performance, self-efficacy except knowledge, and problem-solving ability. Conclusion: This review provides updated evidence of the simulation-based education program in emergency nursing. Further studies are required to increase generalizability using randomized population, research design and controlled trials with sufficient sample size. Moreover, valid measurements are needed to assess the main outcomes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.442-444
• /
• 2019

Fabric defect classification is an important issue in fabric quality control. However, automated classification is difficult because it is hard to identify various types of defects in images. classification of fabric defects mostly rely on human ability. In this paper, to solve this problem we apply Convolutional Neural Networks (CNN) for fabric defect classification. To make training CNN easier, we propose a method that is manually attentive defect regions in images. we compare the proposed method with the original image and confirm that the proposed method is effective for learning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.319-322
• /
• 2019

There are many techniques for locating users in an indoor spot. Among them, WiFi fingerprinting technique which is widely used is phased into a data collection step and a positioning step. In the data collection step, all surrounding Wi-Fi signals are collected and managed as a list. The more data collected, the better the accuracy of the indoor position based on Wi-Fi fingerprint. Existing high-quality data collection and management methods are time consuming and costly, and many operations are required to extract and generate data necessary for machine learning. Therefore, we research how to collect and manage large amount of data in limited resources. This paper presents efficient data collection methods and data generation for learning.

• Journal of Agricultural Extension & Community Development
• /
• v.25 no.4
• /
• pp.211-224
• /
• 2018

The presence of agricultural and rural society in South Korea has been threatened due to aging as well as depopulation. This study aims to explore the Japanese support scheme for new farmers and the role of local group in new farmers' successful settlement in agricultural and rural society. The case study area is Biratori-cho, Hokkaido, Japan. Firstly, this study identified the systemic support scheme for new farmers of Biratori-cho, which provides with two years' training program, mentoring, rental housing and financial aid. Secondly, we focused on the birth and the supporting role of local group, which is called 'Neo-frontier'. Lastly, we analysed the relationship of new farmers and local residents based on the in-depth interview of 11 new farmers' household. As conclusions, we emphasized the value of quality-based support scheme of local government, unlike the quantity-based policy focused on the number of in-migrants. Also, we discussed the meaning of social network in new farmers' successful settlement in agricultural and rural society.

• The Korean Journal of Emergency Medical Services
• /
• v.24 no.3
• /
• pp.89-106
• /
• 2020

Purpose: This study attempts to improve the status of emergency care for major trauma patients transferred by 119 paramedics by analyzing the status of emergency care and the obstacles to the spinal motion restriction (SMR) for major trauma patients. Methods: A total of 600 rescue logs were collected from major trauma patients transported by 119 paramedics in the C fire department from Jan. 1, 2015, to Dec. 31, 2017. And then, 280 questionnaires were collected from the 119 paramedics in C fire department from May 3 to Jun. 3, 2019. Data were analyzed using SPSS 24.0 version. Results: Among 499 spinal motion restriction adaptive patients, the spinal motion restriction rate was 51.1% (255 individuals). Lack of human resources and quality control problems were among the obstacles to spinal motion restriction. Conclusion: The 119 paramedics should improve their activeness and skills in performing emergency care, and since training and experience are of crucial importance, they should expand various education systematized according to demand.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.1
• /
• pp.1063-1069
• /
• 2021

The purpose of this study is to explore and empirically analyze the factors affecting transparency and public accountability in local government, which have not been sufficiently researched in terms of human resource management, and good governance implementation. In particular, this study intends to examine human resource management activities focusing on the government effectiveness dimension. This study uses a qualitative approach and phenomenological method to examine the phenomenon of participant experience along with documents that are in the setting under study. Participants consisted of nine people from the Regional Government Work Unit of Tasikmalaya City, the private sector, and the community. The researcher divided data analysis into three sub-indicators, including effectiveness and efficiency, responsiveness, and public service. The Results show Regional Financial and Asset Management Agency (BPKAD) of Tasikmalaya City as sufficient in terms of human resources, this can be verified from the number of leaders and staff, which amounts to 58 people, of which 80% are economic graduates. Although the quantity is adequate, the quality of human resources in BPKAD in Tasikmalaya City is still weak. In Conclusion of this study it is inferred that the application of the government effectiveness dimension in BPKAD Tasikmalaya City is not optimal and need adequate training to improve employee performance in financial management.