• Smart Structures and Systems
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• v.30 no.6
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• pp.601-612
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• 2022

The prediction of structural mechanical behaviors is vital important to early perceive the abnormal conditions and avoid the occurrence of disasters. Especially for underground engineering, complex geological conditions make the structure more prone to disasters. Aiming at solving the problems existing in previous studies, such as incomplete consideration factors and can only predict the continuous performance, the deep attention fused temporal convolution network (DATCN) is proposed in this paper to predict the spatial mechanical behaviors of structure, which integrates both the temporal effect and spatial effect and realize the cross-time prediction. The temporal convolution network (TCN) and self-attention mechanism are employed to learn the temporal correlation of each monitoring point and the spatial correlation among different points, respectively. Then, the predicted result obtained from DATCN is compared with that obtained from some classical baselines, including SVR, LR, MLP, and RNNs. Also, the parameters involved in DATCN are discussed to optimize the prediction ability. The prediction result demonstrates that the proposed DATCN model outperforms the state-of-the-art baselines. The prediction accuracy of DATCN model after 24 hours reaches 90 percent. Also, the performance in last 14 hours plays a domain role to predict the short-term behaviors of the structure. As a study case, the proposed model is applied in an underwater shield tunnel to predict the stress variation of concrete segments in space.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1726-1748
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• 2024

Trajectory planning is vital for autonomous systems like robotics and UAVs, as it determines optimal, safe paths considering physical limitations, environmental factors, and agent interactions. Recent advancements in trajectory planning and future location prediction stem from rapid progress in machine learning and optimization algorithms. In this paper, we proposed a novel framework for Spatial-temporal transformer-based feed-forward neural networks (STTFFNs). From the traffic flow local area point of view, skip-gram model is trained on trajectory data to generate embeddings that capture the high-level features of different trajectories. These embeddings can then be used as input to a transformer-based trajectory planning model, which can generate trajectories for new objects based on the embeddings of similar trajectories in the training data. In the next step, distant regions, we embedded feedforward network is responsible for generating the distant trajectories by taking as input a set of features that represent the object's current state and historical data. One advantage of using feedforward networks for distant trajectory planning is their ability to capture long-term dependencies in the data. In the final step of forecasting for future locations, the encoder and decoder are crucial parts of the proposed technique. Spatial destinations are encoded utilizing location-based social networks(LBSN) based on visiting semantic locations. The model has been specially trained to forecast future locations using precise longitude and latitude values. Following rigorous testing on two real-world datasets, Porto and Manhattan, it was discovered that the model outperformed a prediction accuracy of 8.7% previous state-of-the-art methods.

• Communications of Mathematical Education
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• v.31 no.3
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• pp.257-277
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• 2017

The purpose of this research is divide into two kinds. First, develop the mathematical modeling program for mathematically gifted students focused on Voronoi diagram and Delaunay triangulation, and then gifted teachers can use it in the class. Voronoi diagram and Delaunay triangulation are Spatial partition theory use in engineering and geography field and improve gifted student's mathematical connections, problem solving competency and reasoning ability. Second, after applying the developed program to the class, I analyze gifted student's core competency. Applying the mathematical modeling program, the following findings were given. First, Voronoi diagram and Delaunay triangulation are received attention recently and suitable subject for mathematics gifted education. Second,, in third enrichment course(Student's Centered Mathematical Modeling Activity), gifted students conduct the problem presentation, division of roles, select and collect the information, draw conclusions by discussion. In process of achievement, high level mathematical competency and intellectual capacity are needed so synthetic thinking ability, problem solving, creativity and self-directed learning ability are appeared to gifted students. Third, in third enrichment course(Student's Centered Mathematical Modeling Activity), problem solving, mathematical connections, information processing competency are appeared.

• Journal of Korea Game Society
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• v.6 no.3
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• pp.33-42
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• 2006

This study is aimed to develop adventure-game style learning program for offering different levels curriculum in mathematics and figure areas in elementary schools. The 7th mathematics curriculum introduced different levels curriculum considering learners' ability, aptitude, requirement, interest so that it could improve learners' growth potential and educational efficiency. But in reality, it is quite difficult to increase educational efficiency by conducting individual learning classes according to students' ability due to the big differences among students' levels in addition to high population in each classroom. The purpose of this study is to offer different levels curriculum based on van Hiele theory and develop adventure-game style learning program to increase interests of the learners. This program can improve students' academic achievement by offering differentiated curriculums to learners who need advanced or supplementary learning materials. And it also enhances leaners' spatial-perceptual ability by offering various operating activities in figures learning.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.19-29
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• 2021

High-performing athletes possess the ability to read the game, known as the "sports brain". However, a cognitive battery to measure such sports brain has not been developed yet. The purpose of the study, thus, is to develop a computerized cognitive test battery to measure athletes' cognitive function. Based on a systematic review, information processing speed, execution function, and spatial ability were selected as sports-related cognitive functions. Simple and choice response times test, trail-making test, Flanker test, and mental rotation task were developed. After providing manual and practice trials, main tests were executed and all primary variables were statistically processed and automatically saved. The test battery is expected to aid in the discovery and recruitment of athletes in the future after verifying the validity and reliability of this battery.

• Nutrition Research and Practice
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• v.16 no.2
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• pp.173-193
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• 2022

BACKGROUND/OBJECTIVES: Alzheimer's disease (AD) is one of the most representative neurodegenerative disease mainly caused by the excessive production of amyloid beta (Aβ). Several studies on the antioxidant activity and protective effects of Populus tomentiglandulosa (PT) against cerebral ischemia-induced neuronal damage have been reported. Based on this background, the present study investigated the protective effects of PT against cognitive impairment in AD. MATERIALS/METHODS: We orally administered PT (50 and 100 mg/kg/day) for 14 days in an Aβ_25-35-induced mouse model and conducted behavioral experiments to test cognitive ability. In addition, we evaluated the levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) in serum and measured the production of lipid peroxide, nitric oxide (NO), and reactive oxygen species (ROS) in tissues. RESULTS: PT treatment improved the space perceptive ability in the T-maze test, object cognitive ability in the novel object recognition test, and spatial learning/long-term memory in the Morris water-maze test. Moreover, the levels of AST and ALT were not significantly different among the groups, indicating that PT did not show liver toxicity. Furthermore, administration of PT significantly inhibited the production of lipid peroxide, NO, and ROS in the brain, liver, and kidney, suggesting that PT protected against oxidative stress. CONCLUSIONS: Our study demonstrated that administration of PT improved Aβ_25-35-induced cognitive impairment by regulating oxidative stress. Therefore, we propose that PT could be used as a natural agent for AD improvement.

• Spatial Information Research
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• v.13 no.3 s.34
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• pp.309-321
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• 2005

To analyze travel demand fur transportation policy and transportation planning, it is important to construct realistic and reliable traffic data. And it needs a user friendly system to demonstrate transportation problems in the transportation planning and transportation management aspect. Generally, to construct network for analysis and collection about social and economical data is a core of transportation planning model. However, it takes a lot of time and effect. To overcome this problem GIS is more effective and efficient in data processing, such as selecting, editing and visualizing, etc. However, it is an early stage to use CIS in the transportation problems. This paper shows a new GIS-T system. The system can give traffic information and plan transportation planning using GIS which has ability as spatial representation and spatial analysis. To build this system, we design interfaces that are able to communicate transportation package for analysis with GIS and manage network efficiently, such as editing and examination. And we also develop a module for traffic information processing to handle spatial data and add it on the system. The proposed system shows more realistic transportation network modeling because the system presents more effective conditions to analyze network. And it can be a tool that can analyze various transportation problems.

• Journal of Educational Research in Mathematics
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• v.25 no.4
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• pp.571-598
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• 2015

This study aimed to assess the spatial cognition strategies and roles taken by students in the process of solving spatial tasks. For the analysis, this study developed two spatial tests based on the mental rotation test, which were taken by 63 students in their final year in elementary schools. The results of this study showed that in terms of the method of approaching the tasks, students took the comprehensive approach and the partial approach. When solving the tasks, the students were shown to use the imagery thinking or analytic thinking method. In terms of perspective, the students rotated the object or change their perspectives. A comparison of the methods used by the students revealed that when approaching the tasks, the group of students who chose the partial approach had higher scores. In terms of solving the tasks the analytic thinking method, and in terms of perspective, changing perspectives were shown to be more effective. Such effective methods were used more frequently in discrimination tasks than in recognition tasks, and in more complicated items, than in less complicated items. In conclusion, the results of this study suggested that the partial, analytic approach and the change of perspectives are useful strategies in solving tasks which require high cognitive effort.

• Journal of the Korean Geographical Society
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• v.45 no.1
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• pp.95-118
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• 2010

This study aims to investigate the spatial distribution of major soil types in Korea, and to assess the ability to predict soil distribution using environmental variables. A classification tree method was used to assess soil predictability. While the great soil groups can give more intuitive understandings on their spatial distributions, its predictability using environmental factors is much lower than that of the great groups. The most important factor to determine the spatial distribution of major soil types is the geomorphological characteristic of Korea that shows distinctive morphological difference between mountains and plains. Spatial distribution of climatic variables and catenary soil sequence along slopes play additional roles in determining the distribution of soil types. The classification tree models resulted in 35-75% of prediction accuracy, depends on the combination of different environmental variables brought in the models. While geomorphological variables are the best predictors for the great groups, climatic variables perform better for the great soil groups.

• Journal of The Korean Association of Information Education
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• v.6 no.3
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• pp.279-287
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• 2002

These days, school education is making every possible effort to bring up a human able to opposed creatively to 21 century social, because of society is global and informational step by step. For this, the special activity in the seventh curriculum is expended and reorganized from three areas to five areas. On the other hand, the special activity is pushed ahead with the developmental activity in consideration of student's ability and aptitude. However, the teachers are difficult to organize of the developmental activity in based on student's ability and aptitude. Because of developmental activity is organized in the beginning of a term, not only the teachers are fallen to realize student's ability and aptitude but also students ignore ability and aptitude themselves. Therefore this paper designs a program based on MI(Multiple Intelligence) theory to compose developmental activity effectively. Up to now, MI is introduced nine kinds of intelligence, Linguistic Intelligence, Logical-Mathematical Intelligence, Musical Intelligence, Spatial Intelligence, Bodily-Kinesthetic Intelligence, Interpersonal Intelligence, Intrapersonal Intelligence, Naturalist Intelligence, and Existentialist intelligence. this paper designs the K-MIDAS test[1] based on seven kinds of intelligence areas and implements developmental activity program suit to student's ability and aptitude based on the MI test result.