• Journal of the Korean earth science society
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• v.43 no.5
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• pp.647-658
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• 2022

The purpose of this study is to analyze students' learning characteristics regarding spatial ability, orienteering ability and earth science content learning ability and their relationship through development and application of earth science activities using orienteering. The programme aims to improve students' spatial ability using orienteering activity which requires spatial ability. Topics in the programme included map, compass, contour, movement of celestial, and constellation application. Students were to orienteer in the field using the method they learned in class. This programme was applied to five 7th graders. The results are, first, students who have positive attitude toward science and do well at school tended to perceive their orienteering ability high. Second, all parts of spatial ability, spatial visualization, spatial orientation, spatial relation were used during orienteering, especially spatial visualization and spatial orientation. The relationship between spatial ability, orienteering ability, and earth science content learning abilities was not clear. However, orienteering ability and earth science content learning ability were in similar tendency.

• Journal of Korean Elementary Science Education
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• v.17 no.2
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• pp.103-111
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• 1998

The purpose of this study was to investigate the relationship among spatial ability, learning styles, visual-perception- recall abiltiy, and the conceptual construction of the earth and moon's motion. Four paper-and-pencil tests were used to measure students' cognitive variables. Spatial ability was measured by Spatial Visualization Test, visual-perception-recall ability was measured by Rey's Figure which also have used to test visual- perception-recall ability of right-temporal lobes, and VVT were used to investigate students' learning styles. further, the test of concept construction was consisted of 15 items about the earth and moon's motion developed by researcher One hundred and twenty-seven 6th-, one hundred and sixteen 7th-, eighty-seven 9th-grade, ninety-three college students were participated in the investigation of the effects of age and learning style on conceptual construction. In the analysis of students' performances, spatial ability, visual-perception-recall ability, and conceptual achievement showed an increasing pattern with grading. In addition, visual learner's conceptual achievement showed a significantly higher score on conceptual test than verbal learner's(p<0.05). The results of the present study supported tile hypothesis that learning styles would differently influence to learning atmospheric concepts by students'learning styles. This study also indicated to be considered the students' spatial ability in learning atmospheric concepts.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.693-703
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• 2010

High spectral resolution of hyperspectral data enables analysis of complex natural phenomena that is reflected on the data nonlinearly. Although many manifold learning methods have been developed for such problems, most methods do not consider the spatial correlation between samples that is inherent and useful in remote sensing data. We propose a manifold learning method which directly combines the spatial proximity and the spectral similarity through kernel PCA framework. A gain factor caused by spatial proximity is first modelled with a heat kernel, and is added to the original similarity computed from the spectral values of a pair of samples. Parameters are tuned with intelligent grid search (IGS) method for the derived manifold coordinates to achieve optimal classification accuracies. Of particular interest is its performance with small training size, because labelled samples are usually scarce due to its high acquisition cost. The proposed spatial kernel PCA (KPCA) is compared with PCA in terms of classification accuracy with the nearest-neighbourhood classification method.

• Journal of Korean Association for Spatial Structures
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• v.20 no.4
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• pp.111-121
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• 2020

There has been increasing interest in UHPC (Ultra-High Performance Concrete) materials in recent years. Owing to the superior mechanical properties and durability, the UHPC has been widely used for the design of various types of structures. In this paper, machine learning based compressive strength prediction methods of the UHPC are proposed. Various regression-based machine learning models were built to train dataset. For train and validation, 110 data samples collected from the literatures were used. Because the proportion between the compressive strength and its composition is a highly nonlinear, more advanced regression models are demanded to obtain better results. The complex relationship between mixture proportion and concrete compressive strength can be predicted by using the selected regression method.

• Journal of the Korean Regional Science Association
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• v.15 no.1
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• pp.93-116
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• 1999

Recently the concept of learning has become very fashionable among academics from different economic disciplines. Economic geographers and spatial planners joined this fashion by increasingly speaking about the 'learning region'. This paper makes clear that this learning region'. This paper makes clear that this learning region concept has been launched from three angles; as spatial outcome of grand societal changes, as spatial concentration of entrepreneurial learning for innovation and as regional development concept. Despite the deficits and flaws such a young concept is faced with, such as vague definitions, the lack of empirical research and an insufficiently clear separation from existing concepts, the learning region concept might provide economic geography with more insight in agglomeration effects, stronger links with policy-making and more knowledge on path dependency and thus on unravelling the distinction between 'good' and 'bad' industrial agglomerations.

• Journal of the Korea Furniture Society
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• v.24 no.1
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• pp.42-50
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• 2013

The objective of this study is to explore basic type of character of humans and to suggest a design method of establishing a spatial construction environment for developing effective learning ability based on such type of character. As a range of research, spatial formative language was deduced and space design strategy for the children was suggested through an analysis of spatial requirements by exploring connectivity depending on features of 9 types of character through Enneagram. As a method of research, a process of suggesting a concrete method after defining an element of spatial construction and deducing a formative language for developing and strengthening effective learning ability for each type of character. As a result of research, the methods of children space design strategy for enhancing learning ability for leadership in a future specific fields were suggested through 9 different type of character with image of case study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.275-284
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• 2023

Land monitoring involves systematically understanding changes in land use, leveraging spatial information such as satellite imagery and aerial photographs. Recently, the integration of deep learning technologies, notably object detection and semantic segmentation, into land monitoring has spurred active research. This study developed a web service to facilitate such integrations, allowing users to analyze aerial and drone images using CNN models. The web service architecture comprises AI, WEB/WAS, and DB servers and employs three primary deep learning models: DeepLab V3, YOLO, and Rotated Mask R-CNN. Specifically, YOLO offers rapid detection capabilities, Rotated Mask R-CNN excels in detecting rotated objects, while DeepLab V3 provides pixel-wise image classification. The performance of these models fluctuates depending on the quantity and quality of the training data. Anticipated to be integrated into the LX Corporation's operational network and the Land-XI system, this service is expected to enhance the accuracy and efficiency of land monitoring.

• School Mathematics
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• v.12 no.3
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• pp.353-370
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• 2010

The purpose of this study was threefold: (1) to select the components of spatial ability that could be associated with the implementation of a polycube task, embody the selected components of spatial ability as learning elements and develop the prototype of polycube teaching-learning materials applicable to gifted education, (2) to make a close analysis of the development process of the teaching-learning materials to ensure the applicability of the prototype, (3) to give some suggestions on the development of teaching-learning materials geared toward mathematically gifted classes. The findings of the study were as follows: As for the first purpose of the study, relevant literature was reviewed to make an accurate definition of spatial ability, on which there wasn't yet any clear-cut explanation, and to find out what made up spatial ability. After 13 components of spatial ability that were linked to a polycube task were selected, the prototype of teaching-learning materials for gifted education in mathematics was developed by including nine components in consideration of children's grade and level. Concerning the second purpose of the study, materials for teachers and students were separately developed based on the prototype, and the materials were modified and finalized in light of when selected students exerted their spatial ability well or didn't in case of utilizing the developed materials in class. And then the materials were finalized after being finetuned two times by regulating the learning type, sequence and degree of learning difficulty. Regarding the third purpose of the study, the polycube task performed in this study might not be generalizable, but there are seven suggestions on the development process of teaching-learning materials.

• Journal of the Korean Institute of Educational Facilities
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• v.12 no.5
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• pp.13-24
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• 2005

This study is the second that aims at offering the basic information on the appropriate spatial organization of the special classes by looking at the relationship between a group of learning activities and a group of playing activities in Elementary and Middle Schools The learning space unit of the special classes should be more flexible for the various learning activities and be prepared in order to correspond to the needs of a territory for different learning appeared according to the degree of handicap, learning ability and the contents of learning. This study dealt with the learning space unit to tackle the problems of special classes. In fact, it is unwise to offer so many different kinds of learning spaces in every school. Due to the manifold and multiple characteristics of handicap, the problem of special classes should be approached by the overall educational system of special educational facilities rather than by a special classes space alone. In this respect, it can be said that this problem should be tackled by reorganization of the special classes in the community through specialization and network system of special class facilities in order to make more effective educational environment.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.207-212
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• 2021

Clustering Unlabeled Spatial-datasets to convert them to Labeled Spatial-datasets is a challenging task specially for geographical information systems. In this research study we investigated the NYC Taxi Limousine Commission dataset and discover that all of the spatial-temporal trajectory are unlabeled Spatial-datasets, which is in this case it is not suitable for any data mining tasks, such as classification and regression. Therefore, it is necessary to convert unlabeled Spatial-datasets into labeled Spatial-datasets. In this research study we are going to use the Clustering Technique to do this task for all the Trajectory datasets. A key difficulty for applying machine learning classification algorithms for many applications is that they require a lot of labeled datasets. Labeling a Big-data in many cases is a costly process. In this paper, we show the effectiveness of utilizing a Clustering Technique for labeling spatial data that leads to a high-accuracy classifier.