• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.171-180
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• 2017

The purpose of this study is to determine an effective training method to improve sequela, since traumatic brain injury sequela is a major factor in determining the quality of life. Neurofeedback training was conducted for an adolescent who had experienced traumatic brain injury during his childhood and who had difficulty in cognitive learning and emotional aspects. The assessment of an adolescent was conducted using K-WAIS-IV intelligence test and QEEG brain wave analysis. In the neurofeedback training, T3 alpha wave compensation and T4 alpha wave inhibition training were performed 36 times for 30 minutes three times a week. In addition to the neurofeedback training, respiratory meditation was also made available to the adolescent. As a result, the adolescent showed a stable condition as indicated by taking a good sleep, reducing test anxiety, and satisfaction with final exam results. This study revealed the possibility for hidden physical and psychological problems arising due to childhood brain trauma. It has also recently been discovered that a more diverse set of tools can be found. In addition, these childhood traumatic brain injuries can be improved through brain training and meditation. The study finding is meaningful for its suggestion of a fusion method for developing mind and body therapy in terms of brain science.

• Steel and Composite Structures
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• v.34 no.5
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• pp.743-767
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• 2020

Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R² = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R² = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9631-9634
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• 2014

Background: : In 2012, the breast cancer estimate worldwide stood at 1.67 million new cases, these accounting for 25% of all types of cancer diagnosed in women. For 2014, 57,120 new cases are expected, with a risk estimated at 56.1 cases for every 100,000 women. The objective of this study was to analyze the satisfaction regarding the use of external breast prostheses by women undergoing mastectomy. Materials and Methods: This cross-sectional study was conducted with 76 women who used an external breast prosthesis (EBP), registered in the services of the Cuiaba Center for Comprehensive Rehabilitation, Mato Grosso, Brazil, from 2009 to 2012. Data were collected from the records of women who had requested the opening of a process of external breast prosthesis concession. Results: Satisfaction with the EBP was identified in 56.6% of the women. Those satisfied with the EBP reported that its weight was not annoying (p<0.01). Although the women felt body sensations of stitches, pains, pulling, dormancy and phantom limb, they are satisfied with the EBP. The variable related to the displacement of the breast prosthesis during activity of everyday life has demonstrated that even though the women have reported the possibility of displacements, they are satisfied with the EBP. The satisfaction with the use of external breast prosthesis did not affect the sexuality of the women with mastectomy. Conclusions: Learning the specificities of the EBP, taking into consideration the satisfaction of its use, allows the rehabilitation team, by listening to their clientele more attentively, following up this woman throughout her life journey, supporting and guiding the best way of use, with an eye to her personal, emotional and social life, as well as to her self-esteem.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.125-140
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• 2018

As one of the processes in the manufacturing industry, quality inspection inspects the intermediate products or final products to separate the good-quality goods that meet the quality management standard and the defective goods that do not. The manual inspection of quality in a mass production system may result in low consistency and efficiency. Therefore, the quality inspection of mass-produced products involves automatic checking and classifying by the machines in many processes. Although there are many preceding studies on improving or optimizing the process using the data generated in the production process, there have been many constraints with regard to actual implementation due to the technical limitations of processing a large volume of data in real time. The recent research studies on big data have improved the data processing technology and enabled collecting, processing, and analyzing process data in real time. This paper aims to propose the process and details of applying big data for quality inspection and examine the applicability of the proposed method to the dairy industry. We review the previous studies and propose a big data analysis procedure that is applicable to the manufacturing sector. To assess the feasibility of the proposed method, we applied two methods to one of the quality inspection processes in the dairy industry: convolutional neural network and random forest. We collected, processed, and analyzed the images of caps and straws in real time, and then determined whether the products were defective or not. The result confirmed that there was a drastic increase in classification accuracy compared to the quality inspection performed in the past.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.145-154
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• 2017

It is aimed to examine the effect of literary therapy program on the improvement of friendship among elementary school students using various media and activities of literature. After the literature therapy program was conducted for elementary students, post-test was conducted. The results of the study are as follows. First, there was no significant difference between the experimental group and the comparative group in the post-test immediately after the end of the program, but in the follow-up test performed 5 weeks after the counseling, the average of the peer relations of the experimental group was significantly higher than that of the comparative group. Second, in the post-test, there was no significant difference between the experimental group and the comparative group in the "intimacy" sub-area of the peer relationship, but in the follow- up test, the "intimacy" sub-region average of the experimental group was significantly higher than the comparative group. Third, the level of 'interest' among the peer relationship sub-domains of the experimental group showed a significant difference in the follow-up test. As a result, literature therapy had no immediate effect on the improvement of friendship among adolescents, but it was effective after a long time.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.33-45
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• 2020

While venture creation is considered to be of high social and economic importance, entrepreneurial outcomes are inherently uncertain and that failure is thus a central feature of entrepreneurship. Although failure in entrepreneurship is pervasive and critical, the impact of prior failure on future entrepreneurship has not received significant attention in the literature. Although failure is a painful and costly experience for entrepreneurs, it can also provide a powerful learning opportunity for those experiencing it. It has been argued that entrepreneurial failure is not just a individual problem but a matter of social concern. As part of the restarting business support system, entrepreneurial re-education program is provided to support failed entrepreneurs. The aim of this study is to examine the effects of failed entrepreneurs' prior entrepreneurial experience and re-education on subsequent venture creation. Moreover, this study also examined the moderating effects of entrepreneurial motivation. For the analyses, we surveyed the entrepreneurs who tried to re-start the subsequent business after the entrepreneurial failure through the "Revitalization Center for Strained Entrepreneur". The result found that failed entrepreneurs who learned a lot from their previous founding experience were more likely to re-start their subsequent business. The failed entrepreneurs who learned a lot from entrepreneurial re-education program were more likely to re-start their subsequent business. Moreover, the positive effect of failed entrepreneurs' previous founding experience and entrepreneurial re-education program on re-starting subsequent business was found to be weaker when entrepreneurial extrinsic motivation was high.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.237-246
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• 2020

this paper, a data modeling method based on decision-making conditions is proposed for making combat and battlefield management systems to be intelligent, which are also a decision-making support system. A picture of a robot seeing and perceiving like humans and arriving a point it wanted can be understood and be felt in body. However, we can't find an example of implementing a decision-making which is the most important element in human cognitive action. Although the agent arrives at a designated office instead of human, it doesn't support a decision of whether raising the market price is appropriate or doing a counter-attack is smart. After we reviewed a current situation and problem in control & command of military, in order to collect a big data for making a machine staff's advice to be possible, we propose a data modeling prototype based on decision-making conditions as a method to change a current control & command system. In addition, a decision-making tree method is applied as an example of the decision making that the reformed control & command system equipped with the proposed data modeling will do. This paper can contribute in giving us an insight of how a future AI decision-making staff approaches to us.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.81-90
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• 2020

The purpose of this study is to study how to apply block-chain technology to prevent data forgery and alteration in the defense sector of AI(Artificial intelligence). AI is a technology for predicting big data by clustering or classifying it by applying various machine learning methodologies, and military powers including the U.S. have reached the completion stage of technology. If data-based AI's data forgery and modulation occurs, the processing process of the data, even if it is perfect, could be the biggest enemy risk factor, and the falsification and modification of the data can be too easy in the form of hacking. Unexpected attacks could occur if data used by weaponized AI is hacked and manipulated by North Korea. Therefore, a technology that prevents data from being falsified and altered is essential for the use of AI. It is expected that data forgery prevention will solve the problem by applying block-chain, a technology that does not damage data, unless more than half of the connected computers agree, even if a single computer is hacked by a distributed storage of encrypted data as a function of seawater.

• The Journal of Society for e-Business Studies
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• v.25 no.1
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• pp.13-33
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• 2020

This study proposes a Korean sentimental analysis algorithm that utilizes a letter-unit embedding and convolutional neural networks. Sentimental analysis is a natural language processing technique for subjective data analysis, such as a person's attitude, opinion, and propensity, as shown in the text. Recently, Korean sentimental analysis research has been steadily increased. However, it has failed to use a general-purpose sentimental dictionary and has built-up and used its own sentimental dictionary in each field. The problem with this phenomenon is that it does not conform to the characteristics of Korean. In this study, we have developed a model for analyzing emotions by producing syllable vectors based on the onset, peak, and coda, excluding morphology analysis during the emotional analysis procedure. As a result, we were able to minimize the problem of word learning and the problem of unregistered words, and the accuracy of the model was 88%. The model is less influenced by the unstructured nature of the input data and allows for polarized classification according to the context of the text. We hope that through this developed model will be easier for non-experts who wish to perform Korean sentimental analysis.

• Journal of the Korean Chemical Society
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• v.51 no.1
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• pp.56-64
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• 2007

This study examined the influences of cognitive conflict and anxiety induced by a discrepant event and an alternative hypothesis, attention, and effort on conceptual change. Two hundred three students having misconceptions about density were selected from 462 seventh graders based on the results of a preconception test. Tests of cognitive responses and anxiety to a discrepant event were administered before and after presenting an alternative hypothesis. Computer-assisted instruction (CAI) was then provided to students as a conceptual change intervention. Tests assessing attention and effort allocated to the CAI, and conceptual understanding were administered as posttests. Cognitive conflict induced by a discrepant event was found to increase after presenting an alternative hypothesis. Pre-cognitive conflict induced by only a discrepant event exerted a direct effect on post-cognitive conflict induced by a discrepant event and an alternative hypothesis. Post-cognitive conflict had a direct effect on conceptual change. Pre-anxiety decreased after presenting an alternative hypothesis. Pre-anxiety influenced post-anxiety, and this influenced on conceptual change via effort negatively. Attention had a direct effect as well as an indirect effect on conceptual change via effort. These results suggest that the strategy presenting both a discrepant event and an alternative hypothesis to students in concept learning could facilitate conceptual change by inducing more cognitive conflict or active participation of students through the decrease of anxiety than that presenting a discrepant event only.