• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.1
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• pp.38-47
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• 2002

This paper demonstrates a regional analysis of landslide occurrence potential by applying geographic information system to the Kumi City selected as a pilot study area. The estimate criteria related to natural and humane environmental factors which affect landslides were first established. A slope map and a aspect map were extracted from DEM, which was generated from the contour layers of digital topographic maps, and a NDVI vegetation map and a land cover map were obtained through satellite image processing. After the spatial database was constructed, indexes of landslide occurrence potential were computed and then a few landslide-potential areas were extracted by an overlay method. It was ascertained that there are high landslide-potential at areas of about 30% incline, aspects including either south or east at least, adjacent to water areas or pointed end of the water system, in or near fault zones, covered with medium vegetable. For more synthetic and accurate analysis, soil data, forest data, underground water level data, meteorological data and so on should be added to the spatial database.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.173-178
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• 2024

This study presents a technique for assessing the dimensional quality of assembly parts in Prefabricated Steel Structures (PSS) using a stereo vision sensor. The stereo vision system captures images and point cloud data of the assembly area, followed by applying image processing algorithms such as fuzzy-based edge detection and Hough transform-based circular bolt hole detection to identify bolt hole locations. The 3D center positions of each bolt hole are determined by correlating 3D real-world position information from depth images with the extracted bolt hole positions. Principal Component Analysis (PCA) is then employed to calculate coordinate axes for precise measurement of distances between bolt holes, even when the sensor and structure orientations differ. Bolt holes are sorted based on their 2D positions, and the distances between sorted bolt holes are calculated to assess the assembly part's dimensional quality. Comparison with actual drawing data confirms measurement accuracy with an absolute error of 1mm and a relative error within 4% based on median criteria.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.284-293
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• 2015

The objective of this paper is to determine the conditions of road surface by utilizing the images collected from closed-circuit television (CCTV) cameras installed on roadside. First, a technique was examined to detect wet surfaces at nighttime. From the literature reviews, it was revealed that image processing using polarization is one of the preferred options. However, it is hard to use the polarization characteristics of road surface images at nighttime because of irregular or no light situations. In this study, we proposes a new discriminant for detecting wet and dry road surfaces using CCTV image data at night. To detect the road surface conditions with night vision, we applied the wavelet packet transform for analyzing road surface textures. Additionally, to apply the luminance feature of night CCTV images, we set the intensity histogram based on HSI(Hue Saturation Intensity) color model. With a set of 200 images taken from the field, we constructed a detection criteria hyperplane with SVM (Support Vector Machine). We conducted field tests to verify the detection ability of the wet road surfaces and obtained reliable results. The outcome of this study is also expected to be used for monitoring road surfaces to improve safety.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.4
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• pp.305-317
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• 2003

Underwater shape and hook depth in tuna longline gear are important factors to decide fishing performance. It also should be considered that management and analysis of hooked rate data from hooked fish species and sizes, and each fishing would be used as a reference data in the future fishing. In this research, after analyzing underwater shape of tuna longline gear by current direction and speed using simulation, experiments were executed in flume tank to verify accuracy of the analysis. Also using the depth of each hook from the simulation, a database system was setup to process the data of bait and hooked fish species. The results were as follows；1. When the attack angle and the shortening rate are fixed, a decrease of the hook depth is proportion to an increase of current speed. 2. When the shortening rate and current speed are fixed, a decrease of hook depth is proportion to an increase of attack angle. 3. When the attack angle and velocity of flow are fixed, a decrease of hook depth is proportion to an increase of shortening rate 4. As a result of comparison between the underwater shape by simulation and that by model gear, the result of the simulation was very close to that of model gear within $$ {\pm}3%$$ 3% error range. 5. In this research, hooked rate database system using hook depth of simulation can analyze the species and size of fish by the parameter; bait. hook depth, so It could be helpful to manage and analyze the hooked data on the field.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.21-29
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• 2024

Reducing the radiation dose during CT scanning can lower the risk of radiation exposure, but not only does the image resolution significantly deteriorate, but the effectiveness of diagnosis is reduced due to the generation of noise. Therefore, noise removal from CT images is a very important and essential processing process in the image restoration. Until now, there are limitations in removing only the noise by separating the noise and the original signal in the image area. In this paper, we aim to effectively remove noise from CT images using the wavelet transform-based GAN model, that is, the WT-GAN model in the frequency domain. The GAN model used here generates images with noise removed through a U-Net structured generator and a PatchGAN structured discriminator. To evaluate the performance of the WT-GAN model proposed in this paper, experiments were conducted on CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. As a result of the performance experiment, the WT-GAN model is better than the traditional filter, that is, the BM3D filter, as well as the existing deep learning models, such as DnCNN, CDAE model, and U-Net GAN model, in qualitative and quantitative measures, that is, PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measure) showed excellent results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.57-64
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• 2006

Multiprocessor system on chip (MPSoC) platforms has set a new innovative trend for the SoC design. Quality of service parameters and performance matrix are leading to the adoption of new design methodology for SoC, which will incorporate highly scalable, reusable, predictable, cost and energy efficient platform not only for underlying communication backbone but also for the entire system architecture of NOC. Like the layered architecture for the communication backbone of NOC, we have proposed the entire system architecture for NOC to be a seven layered architecture in itself. Such a platform can separate the domain specific issues which will model concurrency along with the synchronization issues more effectively. For such a layered architecture, model of computation will provide a framework to that can model concurrency and synchronization issues which are natural for any application. Therefore it becomes extremely important to use a right computation model in a specific NOC region.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.59-71
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• 2018

This study was initiated to develop an optimal signal control algorithm for coordinated signalized intersections using individual vehicle's information which can be collected in a format of prove vehicle data (PVD) via V2I (Vehicle to Infrastructure) communication environment. For developing this signal optimization algorithm, three modules were developed for phase group length computation, split distribution, and phase sequence assignment. The simulation analysis using the microscopic simulation model, Vissim, was conducted for evaluating the effectiveness of the developed algorithm. The analysis result represented that the performance of the developed algorithm is far superior to that of the fixed coordinated signal control method which is the most common signal control method for coordinated signalized intersections in Korea.

• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.1-14
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• 2011

This paper analyzes the fairness and efficiency of channel sharing when heterogeneous wireless networks that have different transmission power and/or coverage coexist with the contention-based channel access protocol. First, we show that the existing CSMA (carrier sensing multiple access) protocol, that is a prevailing contention-based mechanism, results in significant unfairness of channel access because of (1) the asymmetric capability of carrier sensing and (2) the blindness of binary exponential backoff and link adaptation mechanisms to the interference-driven transmission failures. Next, we derive the feasible region of carrier sensing thresholds that assures spatial reuse and fair channel sharing simultaneously. Moreover, we establish an analytical model for per-system throughput and investigate the effect of contention window size and transmission rate on the fairness and efficiency of channel sharing. Finally, we compare the performance of several approaches for fair channel sharing via simulations under various network configurations.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.5
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• pp.496-505
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• 2000

Clusters of workstations (COW) are becoming an attractive option for parallel scientific computing, a field formerly reserved to the MPPs, because their cost-performance ratio is usuallybetter than that of comparable MPPS, and their hardware and software can be easily enhanced to thelatest generations. In this paper we present the design and implementation of our runtime library forclusters of workstations, called "Collective I/O Clustering". The library provides a friendlyprogramming model for the I/O of irregular applications on clusters of workstations, being completelyintegrated with the underlying communication and I/O system. In the collective I/O clustering, two I/Oconfigurations are possible. In the first I/O configuration, all processors allocated can act as I/Oservers as well as compute nodes. In the second I/O configuration, only a subset of processors canact as I/O servers, The compression and software caching facilities have been incorporated into thecollective 1/0 clustering to optimize the communication and I/O costs. All the performance results wereobtained on the IBM-SP machine, located at Argonne National Labs.