• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.1D
• /
• pp.169-175
• /
• 2006

Recently, slope failures are disastrous when they occur in mountainous area adjoining highways. The accidents associated with slope failures have increased due to rapid urbanization of mountainous area. Therefore, the inspection of slope is conducted to maintain road safety as well as road function. In this study, we apply to the remedy which is comparing existent description to advanced technology using GIS. We utilize a Terrestrial LiDAR, one of the advanced method, to generate precise and complete road slope model from expert point of view. In result, we extract hazardous slope information from external measurements referring to the evaluation criteria of external slope stability. We suggest not only the database but also the method of road risk evaluation based on internet GIS.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.35 no.10
• /
• pp.918-926
• /
• 2007

Military aircrafts usually operate at the area with lots of threats such as radars and surface-to-air missiles. Aircraft also faces with the unexpected or pop-up threats. Under this environment, a safe flight path should be generated to lead a mission successful. In this paper, a new path planning algorithm is proposed to provide less dangerous flight path efficiently. Of many path planning algorithms, a potential method is considered, because it has advantages of computation efficiency and smooth path generation. Trajectory generation under the condition of maximum range is studied so that the aircraft may reach the target area without refueling. The algorithm to cope with an unexpected situation is also proposed by adopting the concept of initial direction vector, additional force, and a new mapping function. The performance of the proposed algorithms is demonstrated for SEAD (Suppression of Enemy Air Defences) mission by numerical simulation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.19 no.3
• /
• pp.35-43
• /
• 2005

Matrix converters have been studied for eliminating dc link of conventional converter-inverter system, and various undulation strategy have been proposed. Therefore, matrix converter have no energy storage component except for small ac later for the elimination of switching ripple, and can be made compact and highly reliable compare with the do link inverter system. Matrix converter, however, directly connected the input and the output terminals by bidirectional static switch. As a result if the input voltage are asymmetrical, and contain harmonics, the influence of the distortions directly appear on the output terminal. This problem is a major obstacle to the matrix converter. A new control method using average comparison strategy have been proposed in this paper. This control method realizes sinusoidal input and output current unity input displacement factor regardless of load power factor. Moreover, compensation of the asymmetrical and/or harmonic containing input voltage is automatically realized, and calculation time of control function is reduced.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_4
• /
• pp.1341-1350
• /
• 2019

This research deals with algorithm for forest fire severity classification using multi-temporal KOMPSAT-3A image to mapping forest fire areas. The recent satellite of the KOMPSAT series, KOMPSAT-3A, demonstrates high resolution and multi-spectral imagery with infrared and high resolution electro-optical bands. However, there is a lack of research to classify forest fire severity using KOMPSAT-3A. Therefore, the purpose of this study is to analyze forest fire severity using KOMPSAT-3A images. In addition, this research used pre-fire and post-fire Sentinel-2 with differenced Normalized Burn Ratio (dNBR) to taking for burn severity distribution map. To test the effectiveness of the proposed procedure on April 4, 2019, Gangneung wildfires were considered as a case study. This research used the probability density function for the classification of forest fire damage severity based on R software, a free software environment of statistical computing and graphics. The burn severities were estimated by changing NDVI before and after forest fire. Furthermore, standard deviation of probability density function was used to calculate the size of each class interval. A total of five distribution of forest fire severity were effectively classified.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.6
• /
• pp.646-650
• /
• 2014

In this paper, in order to avoid the deterioration of the pattern classification performance which results from the curse of dimensionality, we propose a new feature selection method. The newly proposed feature selection method is based on Fuzzy C-Means clustering algorithm which analyzes the data points to divide them into several clusters and the concept of a function with fuzzy numbers. When it comes to the concept of a function where independent variables are fuzzy numbers and a dependent variable is a label of class, a fuzzy number should be related to the only one class label. Therefore, a good feature is a independent variable of a function with fuzzy numbers. Under this assumption, we calculate the goodness of each feature to pattern classification problem. Finally, in order to evaluate the classification ability of the proposed pattern classifier, the machine learning data sets are used.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.1
• /
• pp.1-8
• /
• 2023

It is impossible to overwrite on an already allocated page in SSDs, so whenever a write operation occurs a page replacement with a clean page is required. To resolve this problem, SSDs have an internal flash translation layer called FTL that maps logical pages managed by a file system of operating system to currently allocated physical pages. SSD pages discarded due to write operations must be recycled through initialization, but since the number of initialization times is limited the FTL provides a caching function to reduce the number of writes in addition to the page mapping function, which is a core function. In this study, we focus on the FTL cache methodologies reducing the number of page writes and analyze the related algorithms, and propose a write-only cache strategy. As a result of experimenting with the write-only cache using a simulator, it showed an improvement of up to 29%.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.12
• /
• pp.209-218
• /
• 2012

Recently, the Field Programmable Stateful Logic Array (FPSLA) was proposed as one of the most promising system integration technologies which will extend the life of the Moore's law. This work is the first proposal of the FPSLA design automation flow, and the approaches to logic synthesis, synchronization, physical mapping, and automatic placement of the FPSLA designs. The synchronization at each gate for pipelining determines the x-coordinates of cells, and reduces the placement to 1-dimensional problems. The objective function and its gradients for the non-linear optimization of the net length and placement density have been remodeled for the reduced global placement problem. Also, a recursive algorithm has been proposed to legalize the placement by relaxing the density overflow of bipartite bin groups in a top-down hierarchical fashion. The proposed model and algorithm are implemented, and validated by applying them to the ACM/SIGDA benchmark designs. The output state of a gate in an FPSLA needs to be duplicated so that each fanout gate can be connected to a dedicated copy. This property has been taken into account by merging the duplicated nets into a hyperedge, and then, splitting the hyperedge into edges as the optimization progresses. This yields additional 18.4% of the cell count reduction in the most dense logic stage. The practicality of the FPSLA can be further enhanced primarily by incorporating into the logic synthesis the constraint to avoid the concentrated fains of gates on some logic stages. In addition, an efficient algorithm needs to be devised for the routing problem which is based on a complicated graph. The graph models the nanowire crossbar which is trimmed to be embedded into the FPSLA fabric, and therefore, asymmetric. These CAD tools can be used to evaluate the fabric efficiency during the architecture enhancement as well as automate the design.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.2
• /
• pp.69-78
• /
• 2016

Ischemic stroke is a disease that the brain tissues cannot function by reducing blood flow due to thrombosis or embolisms. Due to the nature of the disease, it is most important to identify the status of cerebral vessel and the medical images are necessarily used for its diagnosis. Among many indicators, brain MRI is most widely utilized because experts can effectively obtain the semantic information such as cerebral anatomy aiding the diagnosis with it. However, in case of emergency diseases like ischemic stroke, even though a intelligent system is required for supporting the prompt diagnosis and treatment, the current systems have some difficulties to provide the information of medical images intuitively. In other words, as the current systems have managed the medical images based on the basic meta-data such as image name, ID and so on, they cannot consider semantic information inherent in medical images. Therefore, in this paper, to provide core information like cerebral anatomy contained in brain MRI, we suggest a template-driven medical images mapping method. The key idea of the method is defining the mapping characteristics between anatomic feature and representative images by using template images that can be representative of the whole brain MRI image set and revealing the semantic relations that only medical experts can check between images. With our method, it will be possible to manage the medical images based on semantic.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.3
• /
• pp.155-163
• /
• 2022

The optimization of long-range ensemble climate prediction for rice phenology model with advanced bias correction method is conducted. The daily long-range forecast(6-month) of mean/ minimum/maximum temperature and observation of January to October during 1991-2021 is collected for rice phenology prediction. In this study, the concept of "buffer period" is newly introduced to reduce the problem after bias correction by quantile mapping with constructing the transfer function by month, which evokes the discontinuity at the borders of each month. The four experiments with different lengths of buffer periods(5, 10, 15, 20 days) are implemented, and the best combinations of buffer periods are selected per month and variable. As a result, it is found that root mean square error(RMSE) of temperatures decreases in the range of 4.51 to 15.37%. Furthermore, this improvement of climatic variables quality is linked to the performance of the rice phenology model, thereby reducing RMSE in every rice phenology step at more than 75~100% of Automated Synoptic Observing System stations. Our results indicate the possibility and added values of interdisciplinary study between atmospheric and agriculture sciences.

• Information Systems Review
• /
• v.25 no.1
• /
• pp.93-110
• /
• 2023

Recently, attempts have been made to convert unstructured text into vectors and to analyze vast amounts of natural language for various purposes. In particular, the demand for analyzing texts in specialized domains is rapidly increasing. Therefore, studies are being conducted to analyze specialized and general-purpose documents simultaneously. To analyze specific terms with general terms, it is necessary to align the embedding space of the specific terms with the embedding space of the general terms. So far, attempts have been made to align the embedding of specific terms into the embedding space of general terms through a transformation matrix or mapping function. However, the linear transformation based on the transformation matrix showed a limitation in that it only works well in a local range. To overcome this limitation, various types of nonlinear vector alignment methods have been recently proposed. We propose a vector alignment model that matches the embedding space of specific terms to the embedding space of general terms through end-to-end learning that simultaneously learns the autoencoder and regression model. As a result of experiments with R&D documents in the "Healthcare" field, we confirmed the proposed methodology showed superior performance in terms of accuracy compared to the traditional model.