• 한국지구과학회지
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• 제43권5호
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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.

• 한국초등과학교육학회지:초등과학교육
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• 제17권2호
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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.

• 대한원격탐사학회지
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• 제26권6호
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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.

• 한국공간구조학회논문집
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• 제20권4호
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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.

• 지역연구
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• 제15권1호
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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.

• 한국가구학회지
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• 제24권1호
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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.

• 산업경영시스템학회지
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• 제46권3호
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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.

• 대한수학교육학회지:학교수학
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• 제12권3호
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• pp.353-370
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• 2010

본 연구는 초등 수학 영재를 대상으로 폴리큐브라는 소재를 활용한 교수 학습용 자료 개발의 과정에서 드러나는 여러 가지 논의점을 바탕으로 차후 또 다른 교수 학습용 자료 개발에 주는 시사점을 도출하는 것을 목적으로 한다. 본 연구는 공간능력의 하위 요소들을 바탕으로 폴리큐브 과제와 관련되는 13개의 주제를 추출하여 이들 중 학년과 수준을 고려한 9개의 주제를 실제로 반영한 수학 영재 교수 학습 자료를 개발하였다. 이 자료들을 가지고 두 차례 현장 적용을 하는 동안 4명의 개별 학생들이 보여주는 공간능력 활용 사례를 집중 분석하면서 활동들의 연계성과 난이도, 과제 제시방법 및 발문, 학습 형태, 보조 자료의 활용, 수업 소요 시간과 같은 항목들을 점검하고 수학 영재 교수 학습자료 개발방향에 따라 평가, 수정, 보완하였다. 이를 통해 수학 영재 교수 학습 자료의 개발 과정에 필요한 7가지 시사점을 제안하였다.

• 교육시설
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• 제12권5호
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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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• 제21권6호
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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.