• Computers and Concrete
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• v.32 no.2
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• pp.149-163
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• 2023

One of the main design parameters traditionally utilized in projects of geotechnical engineering is the uniaxial compressive strength. The present paper employed three artificial intelligence methods, i.e., the stochastic fractal search (SFS), the multi-verse optimization (MVO), and the vortex search algorithm (VSA), in order to determine the compressive strength of concrete (CSC). For the same reason, 1030 concrete specimens were subjected to compressive strength tests. According to the obtained laboratory results, the fly ash, cement, water, slag, coarse aggregates, fine aggregates, and SP were subjected to tests as the input parameters of the model in order to decide the optimum input configuration for the estimation of the compressive strength. The performance was evaluated by employing three criteria, i.e., the root mean square error (RMSE), mean absolute error (MAE), and the determination coefficient (R²). The evaluation of the error criteria and the determination coefficient obtained from the above three techniques indicates that the SFS-MLP technique outperformed the MVO-MLP and VSA-MLP methods. The developed artificial neural network models exhibit higher amounts of errors and lower correlation coefficients in comparison with other models. Nonetheless, the use of the stochastic fractal search algorithm has resulted in considerable enhancement in precision and accuracy of the evaluations conducted through the artificial neural network and has enhanced its performance. According to the results, the utilized SFS-MLP technique showed a better performance in the estimation of the compressive strength of concrete (R²=0.99932 and 0.99942, and RMSE=0.32611 and 0.24922). The novelty of our study is the use of a large dataset composed of 1030 entries and optimization of the learning scheme of the neural prediction model via a data distribution of a 20:80 testing-to-training ratio.

• 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.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.6
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• pp.915-936
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• 2017

In this study, current status of Korean hazard mitigation guideline for tunnel operation is summarized. It shows that requirement for CCTV installation has been gradually stricted and needs for tunnel incident detection system in conjunction with the CCTV in tunnels have been highly increased. Despite of this, it is noticed that mathematical algorithm based incident detection system, which are commonly applied in current tunnel operation, show very low detectable rates by less than 50%. The putative major reasons seem to be (1) very weak intensity of illumination (2) dust in tunnel (3) low installation height of CCTV to about 3.5 m, etc. Therefore, an attempt in this study is made to develop an deep-learning based tunnel incident detection system, which is relatively insensitive to very poor visibility conditions. Its theoretical background is given and validating investigation are undertaken focused on the moving vehicles and person out of vehicle in tunnel, which are the official major objects to be detected. Two scenarios are set up: (1) training and prediction in the same tunnel (2) training in a tunnel and prediction in the other tunnel. From the both cases, targeted object detection in prediction mode are achieved to detectable rate to higher than 80% in case of similar time period between training and prediction but it shows a bit low detectable rate to 40% when the prediction times are far from the training time without further training taking place. However, it is believed that the AI based system would be enhanced in its predictability automatically as further training are followed with accumulated CCTV BigData without any revision or calibration of the incident detection system.

• Journal of the Korean Chemical Society
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• v.60 no.1
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• pp.69-81
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• 2016

The purpose of this study was to find out the validation of instructional strategies using the Advanced Laboratory Equipment (ALE class) by investigating science high school students’ perception on ALE in chemistry classrooms and to consider the need for development of teaching materials on ALE class. 7 sessions of ALE including experiments with innovative equipment were developed and applied to 21 students in D Science High School. At the end of the sessions, questionnaire was given to the students. We also collected qualitative data by interviewing 9 students who participated in the questionnaire. We analyzed the data collected by In-depth interviews and students’ experimental reports. The result showed that ALE class was effective to enhance students’ understanding of learning concepts because the experimental time was shortened in real time data processing. Some students showed creative performance on solving scientific problems by using everyday materials in experimental process and developed perceptions of practical inquiry. Through this process, students’ positive attitudes and interests in science and heuristic inquiry skills were also enhanced. Developing ALE lesson materials will be helpful for students to understand science and technology and the domain of science in broader contexts.

• Physical Therapy Korea
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• v.15 no.2
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• pp.11-19
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• 2008

Studies of attentional focus effects, have shown that the performer's attentional focus plays an important role in the performance and learning of motor tasks. We examined the influence of attentional focus on the performance of dual tasks (a postural task and a suprapostural task) and used electromyography (EMG) to examine whether the differences between external and internal focus were also manifest at the neuromuscular level. The subjects (n=40) stood on a balance board (postural task) and held a bar horizontally (suprapostural task). All of the subjects performed under different attentional focus conditions: external (balancer on balance board) or internal (feet) focus on the postural task, and external (balancer on bar) or internal (hand) focus on the suprapostural task. The mean displacement velocity of the bar and the percent reference voluntary contraction (%RVC) of the biceps brachii were reduced when the subjects adopted an external focus on the suprapostural task (p<.05). In addition, the mean displacement velocity of the balance board and %RVC of the tibialis anterior were reduced when the subjects adopted an external focus on the postural task (p<.05). When the subjects adopted an external focus on the suprapostural task, the mean displacement velocity of the balance board and %RVC of the tibialis anterior were also reduced (p<.05). When the subjects' attentional focus was on the postural task, there were no differences in the mean displacement and %RVC of the biceps brachii between attentional focuses. The performance of each task was enhanced when subjects focused on the respective task. The suprapostural task goals had a stronger influence on postural control than vice versa. These results reflect the propensity of the motor system to optimize control processes based on the environmental outcome, or movement effect, that the performer wants to achieve.

• Journal of The Korean Association For Science Education
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• v.35 no.1
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• pp.53-64
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• 2015

This research was performed of high school science classes. These science classes progressed by using Scratch, and surveyed students' perception after finishing each class. This research was conducted of male students who want to choose department of natural science in the next grade. Those classes are consisted of four classes. This study produced a journal, and contained expressions of their thinking and feeling based on experiences during attending classes and projects. Consequently, that journal was analyzed in view of understanding and perception of Scratch using science classes, and it was also included of utilizing Scratch program. Research shows following three conclusions. First, students preferred Scratch using class to general one. They attend more active with high interest, and they felt senses of accomplishment while they make output by themselves. Second, their studies passed through three stages. These are problem perception, problem solving, and producing. Problem solving stage is especially complicated and difficult stage to students. This stage is consisted of Scratch side and Science side. Scratch side has Design and applying process, and Science side has data gathering and analyzing. Students' comprehension of scientific knowledge is increased and is preserved long time through this stage. Last, students had a hard time using Scratch. Because, it is the first time to them to use that program. Therefore, we deemed that they needed to start this kind of experience at lower grade than they are now, such as middle school stage. It is expected that this type of classes are getting more expanded and more populated as a part of students' core ability.

• Journal of the Korean Wood Science and Technology
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• v.5 no.1
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• pp.3-8
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• 1977

A bark comprises about 10 to 20 percents of a typical log by volume, and is generally considered as an unwanted residue rather than a potentially valuable resource. As the world has been confronted with decreasing forest resources, natural resources pressure dictate that a bark should be a raw material instead of a waste. The utilization of the largely wasted bark of genus Quercus grown in Korea can be enhanced by learning its anatomical structure and properties. In this paper, bark characteristics of Quercus grown in Korea are described. In bark anatomy, general features such as color of rhytidome, exfoliating form, color of periderm, arrangement of periderm, and thickness of the inner and outer hark. etc., arc discussed. Studies on the microscopic structure include sieve tube, companion cell, parenchyma, pholem fiber, ray, periderm(phelloderm, phelloogen, phellem), sclereid, and crystal, etc. The results may be summarized as follows: 1. In general characteristics of rhytidomes, exfoliating is not easy and sclereids are distint to the naked eye. Inner bark is thicker than that of outer bark except in case of Q. variabilis. 2. It is not clear to distinguish between phelloderm and phellogen in Quercus bark. The phellem is developed conspicuously in Q. variabilis but that of Q. accutissima is composed of thinwalled phellem and thickwalled stone cell. 3. Quercus Bark has sieve tube, companion cell, phloem fiber and sclereid. Sclereids of Quercus bark are the most distinguished characteristics comparing with pinus and populus. The volume percent of sclereids are higher than that of fiber. 4. Rays are 1~3 seriate, and multiseriate ranging with from 15 to 20. 5. Parenchyma cell contains two types, polygonal and druses crystal.

• Korean Journal of Cognitive Science
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• v.27 no.2
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• pp.159-219
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• 2016

Mathematical ability is important for academic achievement and technological renovations in the STEM disciplines. This study concentrated on the relationship between neural basis of mathematical cognition and its mechanisms. These cognitive functions include domain specific abilities such as numerical skills and visuospatial abilities, as well as domain general abilities which include language, long term memory, and working memory capacity. Individuals can perform higher cognitive functions such as abstract thinking and reasoning based on these basic cognitive functions. The next topic covered in this study is about individual differences in mathematical abilities. Neural efficiency theory was incorporated in this study to view mathematical talent. According to the theory, a person with mathematical talent uses his or her brain more efficiently than the effortful endeavour of the average human being. Mathematically gifted students show different brain activities when compared to average students. Interhemispheric and intrahemispheric connectivities are enhanced in those students, particularly in the right brain along fronto-parietal longitudinal fasciculus. The third topic deals with growth and development in mathematical capacity. As individuals mature, practice mathematical skills, and gain knowledge, such changes are reflected in cortical activation, which include changes in the activation level, redistribution, and reorganization in the supporting cortex. Among these, reorganization can be related to neural plasticity. Neural plasticity was observed in professional mathematicians and children with mathematical learning disabilities. Last topic is about mathematical creativity viewed from Neural Darwinism. When the brain is faced with a novel problem, it needs to collect all of the necessary concepts(knowledge) from long term memory, make multitudes of connections, and test which ones have the highest probability in helping solve the unusual problem. Having followed the above brain modifying steps, once the brain finally finds the correct response to the novel problem, the final response comes as a form of inspiration. For a novice, the first step of acquisition of knowledge structure is the most important. However, as expertise increases, the latter two stages of making connections and selection become more important.