• Journal of KIISE
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• v.45 no.1
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• pp.94-98
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• 2018

We propose Wide Inception ResNet (WIR Net) an optimized neural network architecture as a real-time semantic segmentation method for autonomous driving. The neural network architecture consists of an encoder that extracts features by applying a residual connection and inception module, and a decoder that increases the resolution by using transposed convolution and a low layer feature map. We also improved the performance by applying an ELU activation function and optimized the neural network by reducing the number of layers and increasing the number of filters. The performance evaluations used an NVIDIA Geforce GTX 1080 and TX1 boards to assess the class and category IoU for cityscapes data in the driving environment. The experimental results show that the accuracy of class IoU 53.4, category IoU 81.8 and the execution speed of $640{\times}360$, $720{\times}480$ resolution image processing 17.8fps and 13.0fps on TX1 board.

• Journal of Aerospace System Engineering
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• v.18 no.3
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• pp.41-47
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• 2024

Recently, as the practical application and commercialization of unmanned aerial vehicles (UAVs) is pursued, interest in ensuring the safety of the UAV is increasing. Because UAV accidents can result in property damage and loss of life, it is important to develop technology to prevent accidents. For this reason, a technique to detect the abnormal flight state of UAVs has been developed based on the AutoEncoder model. However, the existing detection technique is limited in terms of performance and real-time processing. In this paper, we propose a U-Net based abnormal flight detection technique. In the proposed technique, abnormal flight is detected based on the increasing rate of Mahalanobis distance for the reconstruction error obtained from the U-Net model. Through simulation experiments, it can be shown that the proposed detection technique has superior detection performance compared to the existing detection technique, and can operate in real-time in an on-board environment.

• Journal of environmental and Sanitary engineering
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• v.22 no.3
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• pp.65-76
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• 2007

Values and attitude towards the environment begin to form in elementary school. Thus, environmental education is effective to promote children's sensibility on the environment, to increase their interest and concern on it, and to make them have friendly attitudes towards it. As a measure of such education, experiential learning activities are being emphasized, where children can see, feel and experience for themselves in a familiar environment surrounding them. Based on the results of this research, the following proposals can be made for environmental education necessary for elementary school children. i) the contents of environmental education should be selected and organized according to grades. Also, schedule should be secured to provide environmental education in certain time. ii) program should be developed to fit into local characteristics and academic level, providing connective and consistent environmental education. iii) activities for environmental education in elementary school can be effective only if connective guidances are provided among school, home and local community. iv) the recycling and separate collection activity program used in this research was limited to 3rd graders in small-size rural schools. Additional research may be necessary to see how long their attitudes last according to different grades.

• Education of Primary School Mathematics
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• v.19 no.4
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• pp.349-360
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• 2016

This cross-national study examines the similarities and differences between Korean and U.S. pre-service teachers' views on equitable mathematics teaching. Pre-service teachers enrolled in mathematics education courses at the two sites (Korea, n=51; U.S., n=33) were administered a survey consisting of the following: (a) items about pre-service teachers' views on equity relative to mathematical ability, classroom policies and practices, and access to learning opportunities, (b) items about pre-service teachers' agreement in their views on recommended practices, and (c) items about participants' past learning experiences in an equitable learning environment as students. Similarities were found between the sites regarding the following: (a) advocating for equitable mathematics teaching, and (b) conceptualizing equitable teaching as a way to support the learning of less capable students. Differences were found with regard to nurturing growth mindsets in mathematics; positioning toward equal opportunities and outcomes in learning; and relating to grouping as collaborative learning strategies.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1679-1692
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• 2023

South Korea is a country that emits a large amount of pollutants as a result of population growth and industrial development and is also severely affected by transboundary air pollution due to its geographical location. As pollutants from both domestic and foreign sources contribute to air pollution in Korea, the location of air pollutant emission sources is crucial for understanding the movement and distribution of pollutants in the atmosphere and establishing national-level air pollution management and response strategies. Based on this background, this study aims to effectively acquire spatial information on domestic and international air pollutant emission sources, which is essential for analyzing air pollution status, by utilizing high-resolution optical satellite images and deep learning-based image segmentation models. In particular, industrial parks and quarries, which have been evaluated as contributing significantly to transboundary air pollution, were selected as the main research subjects, and images of these areas from multi-purpose satellites 3 and 3A were collected, preprocessed, and converted into input and label data for model training. As a result of training the U-Net model using this data, the overall accuracy of 0.8484 and mean Intersection over Union (mIoU) of 0.6490 were achieved, and the predicted maps showed significant results in extracting object boundaries more accurately than the label data created by course annotations.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.175-187
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• 2011

Since insects play important roles in existence of plants and other animals in the natural environment, they are considered as necessary biological resources from the perspectives of those biodiversity conservation and national utilization strategy. For the conservation and utilization of insect species, an observational learning environment is needed for non-experts such as citizens and students to take interest in insects in the natural ecosystem. The insect identification is a main factor for the observational learning. A current time-consuming search method by insect classification is inefficient because it needs much time for the non-experts who lack insect knowledge to identify insect species. To solve this problem, we proposed an smart phone-based insect identification inference system that helps the non-experts identify insect species from observational characteristics in the natural environment. This system is based on the similarity between the observational information by an observer and the biological insect characteristics. For this system, we classified the observational characteristics of insects into 27 elements according to order, family, and species, and proposed similarity indexes to search similar insects. In addition, we developed an insect identification inference prototype system to show this study's viability and performed comparison experimentation between our system and a general insect classification search method. As the results, we showed that our system is more effective in identifying insect species and it can be more efficient in search time.

• Journal of The Korean Association of Information Education
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• v.10 no.2
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• pp.209-217
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• 2006

For its maximum impact on the scene of school as the educational equipment, it is necessary to understand equipmental characteristics of PDA and study the basis for utilizing it educationally. In this point of view, to inquire how PDA is helpful for education more than PC, the typical educational equipment in the past, PDA-based English vocabulary learning game is developed in this study, and after that it is applied on the scene of education. The result of study showed PDA can access the content more easily than PC, and learners expressed more curiosity and expectation of PDA than PC in a recent poll. In addition, under the condition of learner's voluntary use, the present study has found that learning with PDA is helpful to enhance the academic achievement more than one with PC.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1062-1072
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• 2006

Recently, new intelligent service frameworks, such as ubiquitous computing are proposed. So, the necessity of adaptive agent system has been increased. In this paper, we propose an intelligent service agent to help that ubiquitous computing system offer user suitable service in ubiquitous computing environment. In order to offer user suitable uT-service, an intelligent service agent mediates the gap between the context information in uT-service system, and user preference is reflected in it. Therefore, we focus on following three components; the first is suitable multi agent framework-agent communication analysis and applicable method of inference engine, the second is uT-ontologies to describe various context information-context information sharing between agents and context information understanding between agents, the third is learning method of user profile to apply in uT-service system. This approach enables us to build adaptive uT-service system to offer suitable service according to user preference.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.5
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• pp.535-546
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• 2020

Land cover maps are derived from satellite and aerial images by the Ministry of Environment for the entire Korea since 1998. Even with their wide application in many sectors, their usage in research community is limited. The main reason for this is the map compilation cycle varies too much over the different regions. The situation requires us a new and quicker methodology for generating land cover maps. This study was conducted to automatically generate land cover map using aerial ortho-images and Landsat 8 satellite images. The input aerial and Landsat 8 image data were trained by Residual U-Net, one of the deep learning-based segmentation techniques. Study was carried out by dividing three groups. First and second group include part of level-II (medium) categories and third uses group level-III (large) classification category defined in land cover map. In the first group, the results using all 7 classes showed 86.6 % of classification accuracy The other two groups, which include level-II class, showed 71 % of classification accuracy. Based on the results of the study, the deep learning-based research for generating automatic level-III classification was presented.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.203-213
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• 2014

In this study, we proposed a new model with ISOIA (Insect Search by Observation based on Insect Appearance) method based on observation by insect appearance to improve user satisfaction, and compared it with the ISBC and ISOBC methods. In order to test these three insect search systems with AHP method, we derived three evaluation criteria for user satisfaction and three sub-evaluation criteria by evaluation criterion. In the ecological environment, non-experts need insect search systems to identify insect species and to get u-Learning contents related to the insects. To assist the public the non-experts, ISBC (Insect Search by Biological Classification) method based on biological classification to search insects and ISOBC (Insect Search by Observation based on Biological Classification) method based on the inference that identifies the observed insect through observation according to biological classification have been provided. In the test results, we found the order of priorities was ISOIA, ISOBC, and ISBC. It shows that the ISOIA system proposed in this study is superior in usage and quality compared with the previous insect search systems.