• International Journal of Knowledge Content Development & Technology
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• v.11 no.1
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• pp.29-48
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• 2021

The paper discusses the ICT infrastructure as far as the availability of (computers, local or wide area networks, Internet connectivity and its reliability, size of the bandwidth and its optimization, etc.) in the S&T research institution. It also examined the profile of the research scientists and looked at the type of ICT infrastructure that is available for their use as well as the reliability of the Internet connectivity within these research institutions. It looked at the broadband capacities of the research institutions and the ICT capabilities in respect of the technical and managerial support back-up that are available to the research institutions. The study used the survey research method with a questionnaire as well as personal observation to gather the data. From the data gathered, it was realized that the internet connectivity and the size of the bandwidth that the R&D institutions subscribed to differed significantly. Again, the extent to which the research scientists were able to access the internet in their respective institutions depended on the quality of the local network in place. Generally, the investments in ICT were made for different management objectives, and these were meant to facilitate the generation of new knowledge as well as make measurable improvements in R&D activities.

• Design & Manufacturing
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• v.15 no.4
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• pp.1-7
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• 2021

A study on in-mold punching technology for hole piercing during molding of hollow plastic parts was conducted. Considering the non-linearity of the HDPE plastic material, mechanical properties were obtained according to the change in temperature and load speed. A standard specimen for the in-mold punching test was designed to implement the in-mold punching process, and the specimen was obtained through injection molding. In order to analyze the influence of process variables during in-mold punching, an in-mold punching mold capable of controlling variables such as temperature and support pressure of the specimen was designed and manufactured. Mold heating characteristics were confirmed through finite element analysis, and punching simulations for changes in process conditions were performed to analyze punching characteristics and reflected in the experiment. Through simulations and experiments, it was found that the heating temperature, punch shape, punching speed, and pressure of the back side of the specimen were very important during in-mold punching of HDPE materials, and optimal conditions were acquired within a given range.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.467-479
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• 2022

Working memory (WM), which plays a vital role in daily activities, is a memory system that temporarily stores and processes information when people are engaged in complex cognitive activities. The influence of music on WM has been widely studied. In this work, we conducted a series of n-back memory experiments with different task difficulties and multiple trials on 14 subjects under the condition of no music and Alpha wave leading music. The analysis of behavioral data show that the change of music condition has significant effect on the accuracy and time of memory reaction (p<0.01), both of which are improved after the stimulation of Alpha wave music. Behavioral results also suggest that short-term training has no significant impact on working memory. In the further analysis of electrophysiology (EEG) data recorded in the experiment, auto-regressive (AR) model is employed to extract features, after which an average classification accuracy of 82.9% is achieved with support vector machine (SVM) classifier in distinguishing between before and after WM enhancement. The above findings indicate that Alpha wave leading music can improve WM, and the combination of AR model and SVM classifier is effective in detecting the brain activity changes resulting from music stimulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1935-1950
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• 2023

The arrival of the Internet of Things and 5G technology enables users to rely on edge computing platforms to process massive data. Data sharing based on edge computing refines the efficiency of data collection and analysis, saves the communication cost of data transmission back and forth, but also causes the privacy leakage of a lot of user data. Based on attribute-based encryption and blockchain technology, we design a fine-grained access control scheme for data in edge computing, which has the characteristics of verifiability, support for outsourcing decryption and user attribute revocation. User attributes are authorized by multi-attribute authorization, and the calculation of outsourcing decryption in attribute encryption is completed by edge server, which reduces the computing cost of end users. Meanwhile, We implemented the user's attribute revocation process through the dual encryption process of attribute authority and blockchain. Compared with other schemes, our scheme can manage users' attributes more flexibly. Blockchain technology also ensures the verifiability in the process of outsourcing decryption, which reduces the space occupied by ciphertext compared with other schemes. Meanwhile, the user attribute revocation scheme realizes the dynamic management of user attribute and protects the privacy of user attribute.

• Wind and Structures
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• v.38 no.1
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• pp.75-91
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• 2024

Reliable wind signal reconstruction can be beneficial to the operational safety of long-span bridges. Non-Gaussian characteristics of wind signals make the reconstruction process challenging. In this paper, non-Gaussian wind signals are converted into a combined prediction of two kinds of features, actual wind speeds and wind angles of attack. First, two decomposition techniques, empirical mode decomposition (EMD) and variational mode decomposition (VMD), are introduced to decompose wind signals into intrinsic mode functions (IMFs) to reduce the randomness of wind signals. Their principles and applicability are also discussed. Then, four artificial intelligence (AI) algorithms are utilized for wind signal reconstruction by combining the particle swarm optimization (PSO) algorithm with back propagation neural network (BPNN), support vector regression (SVR), long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM), respectively. Measured wind signals from a bridge site in a deep-cutting gorge are taken as experimental subjects. The results showed that the reconstruction error of high-frequency components of EMD is too large. On the contrary, VMD fully extracts the multiscale rules of the signal, reduces the component complexity. The combination of VMD-PSO-Bi-LSTM is demonstrated to be the most effective among all hybrid models.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.3
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• pp.265-273
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• 2012

The business environment is changing rapidly because of the global crisis. In order to survive and enhance competitiveness in the global market, global manufacturing companies are trying to overcome the crisis through the convergence of production infrastructure and IT technology. The importance of systems to support the integration of manufacturing processes, collaboration in product development, and information integration of providers and producers is therefore increasing. In this paper, research is conducted on the design and implementation of a collaboration system to support a power-boat manufacturing company in this situation of increased demand for collaboration and information integration. The system was designed through product-structure and production-process analysis, support product data management, and enterprise contents management. The company involved in the power-boat development project is expected to show an improvement in productivity through the integrated management of information and collaboration provided by this system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4694-4702
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• 2012

The purpose of this study was a descriptive research that identified the levels of health-promoting behaviors, previous related behavior, perceived benefits/barriers, self-efficacy, and social support. In addition, it was to establish the relations among the variables, and determine the factors affecting the health-promoting behaviors. Study participants were 311 middle aged between 55-64 in urban areas, and the data were collected through self-reported structured questionnair. According to the results, the mean score for the levels of health-promoting behaviors of the late middle aged was 2.64. Also, among the variables related to health-promoting behaviors, perceived benefits were the highest score (30.7), and perceived barriers were the lowest one (2.08). Meaningful positive correlations were found among health-promoting behaviors and previous related behavior, social support, perceived benefits, and self-efficacy, but perceived barriers showed weakly negative correlations. In addition, the factors affecting health promoting behaviors were revealed in order as following: Previous health related behavior(${\beta}$=.35, p<.001), perceived benefits(${\beta}$=.32, p<.001), social support(${\beta}$=.28, p<.001), and life satisfaction(${\beta}$=.13, p<.001), and this model's explanatory power was 68.8%(F=166.71, p<.001). Based on the findings from the study, in order for the late middle aged to have a well-being old age, an health promoting education program including exercises and stress management should be provided to maintain and improve proper health promoting behaviors. The network with the same age groups also should be supported to share useful information and back up one another.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.77-85
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• 2013

Objective: The aim of this study sets factors from previous research known to impact transfer effects as the independent variables, and examines their relationship with the dependent variables, near transfer effects and far transfer effects. Background: Transfer of Training refers to the application of what learners acquire knowledge and skills in training programs to their job. The ultimate goal of training is to apply what employees learn in training sessions to their workplace. In this sense, transfer of training has been a vital concern for training effectiveness. For training to be effective, trainees(learners) should be able to use what they learn in training program back on the job. Method: For this research purpose, this study conducted a survey on 170 nuclear operators in nuclear education and training center. Of these, survey result from the 167 recruits were sampled. Theoretical model of this study is based on Holton & Baldwin's(2003) distance model of transfer effects. This study sets transfer effects(near transfer, far transfer) as the main dependent variables. Meanwhile, the independent variables are trainee characteristics, training characteristics, organizational transfer climate. Each independent variable has subordinate variables. Subordinate variables of trainee characteristics are self-efficacy, motivation to learn, motivation to transfer and ability to transfer. Subordinate variables of training characteristics are training contents, ability of trainers, training design, training climate. The last Subordinate variables of organizational transfer climate are support of supervisors, support of peer, support of organization. Conclusion: As a analysis result, trainee characteristics appeared to be in effect only significant influence near far transfer of training, the effect of the far transfer of training, there is no significant. In addition, the training characteristics appeared to be having a significant influence on near and far transfer effects. Organizational transfer climate appeared to be having a significant influence on near and far transfer effects. Finally, near transfer effect appeared to be having a significant influence on far transfer effects. Application: Results of this analysis in the study to training organization and training characteristics of the transition environment effects on nuclear power institutions and operators training organization having a significant impact that says. The transfer of knowledge and technology, as well as that can be applied to a new situation in terms of education and training are important characteristics.

• Journal of Agricultural Extension & Community Development
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• v.3 no.2
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• pp.197-209
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• 1996

Bangladesh that is known as the poorest country of the world has the large land of fertile soil and very good environment to live, even though we think she may be very bad to live. People being habituated to that good environment, the population explosion made the people to be starven, but the treatment has been simple support without deep analysis of the root of poverty. As the result it is general that the poverty is severer and severer in spite of continuous support. For the last century Korea changed from the country of poverty and despair to that of development and hope, to be model mid vision of under development countries including Bangladesh. At this point it is necessary to look back the way of development to help them to solve their poverty problem. That is the goal of this project, and this thesis is the result of it. It is evaluated for the 1st 5 years work of the project to apply the result to the next 5 years plan. This project had been proceeded from 1. Jul. 1990 to 30. Jun. 1995 at Chilmari area of Bangladesh, with teaching and training to wake up the mentality of the people, demonstration farming and cooperative association. It was proceeded as the Agriculture project of KDAB(Korean Development Association in Bangladesh, an NGO registered to Bangladesh) supported by Good Neighbors, KOICA and many churches and individuals. Especially the teaching and training work was proceeded as the branch of the Canaan Farmer`s School of Korea with instruction and support. After the basic survey for project, the confirmation of working place and the preparation of training facility, 10 times of long term training(3 months worse, boarding) was completed, with many times of short term training, informal training, demonstration farm, various demonstrating works. The results of the work are understanding of the not of problem by participatory observation, making plan to solve it, getting the trust from the people and beginning the practical work with the trainees for development of economy and living situation. The biggest problem of Bangladesh is being understood losing the desire to solve the poverty problem and the self-confidence to be able to do it. It is the conclusion that after solving the problem of thought and mentality, the education, technology and money can be effective for development. So the 1st 5 year project is evaluated as the basic work to analyse the root of problem, to chance mentality of people and to search income source. The next goal is to promote practical living level of people. For that it is necessary to develope die mentality of people including responsibility and self-confidence by teaching and training, to educate cooperative association and technology for economical development, to proceed integrated rural development work with economical development, educational improvement and reformation of environment. It is very important result that they decided to grow poultry for main economical source of Chilmari area, to do economical development work by joint operation of poultry through cooperative association.