• Journal of Korea Spatial Information System Society
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• v.8 no.3
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• pp.15-26
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• 2006

Building related information is one of the most important framework data for the management of local government. However, building related registers have its own characteristics and problems, it have limitation to be used as an important data. Those situations are obstacle for the efficient and scientific urban management in the information era. This research focused on three aspects first, analyzed characteristics and problems of building related registers, second, set the direction to improve accuracy of building related information, and finally suggested solution to improve the accuracy of building information according to its problem type. This research contributes to set detail guideline to improve building related information, which could be immediately used in local government for the systematic urban management.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.2
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• pp.73-82
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• 2009

The traffic volume of Seoul is extremely high in comparison to other major cities in Korea, and the result has been harmful physical and mental exposure to pollution by Seoulites on a regular basis. The street air pollution is more important than the others, because the air pollution generated by street traffic directly impacts the health of nearby pedestrians. This problem requires urgent attention and resolution. Among the factors creating the air pollution originating from the street, is the configuration of streets, which have emerged as the most significant because it is related to air and pollutant dispersion. Therefore, this study was conducted under the assumption that street form affects the air quality. Study sites were classified by street characteristics, and air quality was analyzed in each class. Then the OSPM (Operational Street Pollution Model) was employed to simulate the relationship between street configuration and air quality of streets within the old city center and new city center in Seoul. After that this study analyzed the correlation between air pollution and the spatial configuration of urban streets (ex. street width, building height, building density, etc.) to determine their contributions to air pollution. The outcome of this study is as follows : First, the result that was derived from the correlation analysis between street configuration and air quality hewed that the air pollution of the street is influenced by the average height of building, width of the roads as well as traffic volume. On the roadside, the concentration level of $NO_2$ is mainly affected by the average height of building and the deviation of building height along the street and CO is affected by street width. The outcome of this study can be used as a basis for more sound urban design policies, and the promotion of desirable street environments for pedestrians.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.5
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• pp.39-48
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• 2009

Many super-resolution reconstruction algorithms have been proposed since it was the first proposed in 1984. The spatial domain approach of the super-resolution reconstruction methods is accomplished by mapping the low resolution image pixels into the high resolution image pixels. Generally, a super-resolution reconstruction algorithm by using the spatial domain approach has the noise problem because the low resolution images have different noise component, different PSF, and distortion, etc. In this paper, we proposed the new super-resolution reconstruction method that uses the L1 norm to minimize noise source and also uses the Huber norm to preserve edges of image. The proposed algorithm obtained the higher image quality of the result high resolution image comparing with other algorithms by experiment.

• Journal of Multimedia Information System
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• v.7 no.1
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• pp.1-10
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• 2020

The image analysis is an important and predominant task for classifying the different parts of the image. The analysis of complex image analysis like histopathological define a crucial factor in oncology due to its ability to help pathologists for interpretation of images and therefore various feature extraction techniques have been evolved from time to time for such analysis. Although deep reinforcement learning is a new and emerging technique but very less effort has been made to compare the deep learning and deep reinforcement learning for image analysis. The paper highlights how both techniques differ in feature extraction from complex images and discusses the potential pros and cons. The use of Convolution Neural Network (CNN) in image segmentation, detection and diagnosis of tumour, feature extraction is important but there are several challenges that need to be overcome before Deep Learning can be applied to digital pathology. The one being is the availability of sufficient training examples for medical image datasets, feature extraction from whole area of the image, ground truth localized annotations, adversarial effects of input representations and extremely large size of the digital pathological slides (in gigabytes).Even though formulating Histopathological Image Analysis (HIA) as Multi Instance Learning (MIL) problem is a remarkable step where histopathological image is divided into high resolution patches to make predictions for the patch and then combining them for overall slide predictions but it suffers from loss of contextual and spatial information. In such cases the deep reinforcement learning techniques can be used to learn feature from the limited data without losing contextual and spatial information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.910-920
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• 2006

We consider the problem of estimating a code-timing of DS-CDMA signal in antenna array systems in the presence of flat fading channels and near-far environments. We derive an approximate maximum likelihood algorithm of estimating the code-timing of a desired user for DS-CDMA systems to better utilize the time-varying characteristics of the fading process. In the development of code timing estimator, the given observation bits are divided into many sets of sub-windows with each sufficiently large. The proposed method uses sub-windows with equal size associated with the coherence time of channel fading. The alternative approach is that without the estimation of the fading rate, the sufficiently given observation bits are simply separated into two consecutive sets of sub-windows. The derivation of the proposed algorithms is based on multiple antennas partially correlated in space. The impacts of spatial fading correlation on acquisition and men acquisition time performance of the proposed algorithms are also examined.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.1096-1101
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• 2005

An efficient method of estimating the spatial gaps between the connected components has been prposed to separatethe individual words from a handwritten legal amount on bank check. Owing to the inherent problem of underestimation or overestimation, the previous gap measures have much difficulty in being applied to the legal amounts that usually include the great shape variability by writer's unconstrained writing style and touching or irregular gaps between words by space limitation. In order to alleviate such burden and improve word separation performance, we have developed a modified version of each distance measure. Through a series of word separation experiments, we found that the modified distance measures show a better performance with over $2-3\%$ of the word separation rate than their corresponding original distance measures.

• Ocean and Polar Research
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• v.27 no.2
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• pp.189-195
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• 2005

Several models predict large and potentially abrupt ocean circulation changes due to anthropogenic greenhouse-gas emissions. These circulation changes drive-in the models-considerable oceanic oxygen trend. A sound estimate of the observed oxygen trends can hence be a powerful tool to constrain predictions of future changes in oceanic deepwater formation, heat and carbon dioxide uptake. Estimating decadal scale oxygen trends is, however, a nontrivial task and previous studies have come to contradicting conclusions. One key potential problem is that changes in the historical observation network might introduce considerable errors. Here we estimate the likely magnitude of these errors for a subset of the available observations in the Southern Ocean. We test three common data analysis methods south of Australia and focus on the decadal-scale trends between the 1970's and the 1990's. Specifically, we estimate errors due to sparsely sampled observations using a known signal (the time invariant, temporally averaged, World Ocean Atlas 2001) as a negative control. The crossover analysis and the objective analysis methods are for less prone to spatial sampling location biases than the area averaging method. Subject to numerous caveats, we find that errors due to sparse sampling for the area averaging method are on the order of several micro-moles $kg^{-1}$. for the crossover and the objective analysis method, these errors are much smaller. For the analyzed example, the biases due to changes in the spatial design of the historical observation network are relatively small compared to the tends predicted by many model simulations. This raises the possibility to use historic oxygen trends to constrain model simulations, even in sparsely sampled ocean basins.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.799-807
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• 2017

Environmental impact assessment is a regulation that is implemented to reduce harmful environmental impacts of development projects. However, The environmental value is difficult to quantify and the uncertainty, There is a problem of objectivity and reliability of the system is consistently pointed out. Therefore, the necessity of the data-based environmental impact assessment system is gradually increasing. Especially, environmental impact assessment is highly applicable to environmental spatial information because it contains about the development of a particular area. Also with the introduction of EIA Follow-up management system, there is a demand for a system for providing and utilizing environmental information in a time series. This study derives the necessity of information provision system and analyz existing environmental information utilization system based on the institutional characteristics of environmental impact assessment. And suggest ways to provide environmental spatial information to find policy implications for improving the limit of environmental impact assessment system.

• Journal of Internet Computing and Services
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• v.1 no.1
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• pp.47-62
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• 2000

Geographic Information System(GIS) deal with data which can potentially be useful for a wida range of applications. However, the information needs of each application usually vary, specially in resolution, detail level, and representation style, as defined in the modeling phase of the geographic database design. To be able to deal with such diverse needs, the GIS must after features that allow multiple representations for each geographic entity of phenomenon. This paper addresses the problem of formal definition of the objects and their relationships on geographical information systems. The geographical data is divided in two main classes: geo-objects and geo-fields, which describe discrete and continuous representations of spatial reality. I will study the classes and the roles of relationships over geo-fields, geo-objects and nongeo-objects. Therefore, this paper will contribute the efficient design of geographical class hierarchy schema by means of formalizing attribute-domains of classes.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.37-48
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• 2010

In this paper, we analyze the shortcomings of the previous declustering methods, which are based on grid-like partitioning and a mapping function from a cell to a disk number, for high-dimensional space and propose a solution. The problems arise from the fact that the number of splitting is small(for the most part, binary-partitioning is sufficient), and the side length of a range query whose selectivity is small is quite large. To solve this problem, we propose a mathematical model to estimate the performance of a grid-like partitioning method. With the proposed estimation model, we can choose a good grid-like partitioning method among the possible schemes and this results in overall improvement in declustering performance. Several experimental results show that we can improve the performance of a previous declustering method up to 2.7 times.