• Geomechanics and Engineering
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• v.34 no.3
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.231-237
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• 2024

Brain injury causes persistent disability in survivors, and epidural hematoma(EDH) and subdural hematoma (SDH) resulting from cerebral hemorrhage can be considered one of the major clinical diseases. In this study, we attempted to automatically segment and hematomas due to cerebral hemorrhage in three dimensions based on computed tomography(CT) images. An improved GVF(gradient vector flow) algorithm was implemented for automatic segmentation of hematoma. After calculating and repeating the gradient vector from the image, automatic segmentation was performed and a 3D model was created using the segmentation coordinates. As a result of the experiment, accurate segmentation of the boundaries of the hematoma was successful. The results were found to be good even in border areas and thin hematoma areas, and the intensity, direction of spread, and area of the hematoma could be known in various directions through the 3D model. It is believed that the planar information and 3D model of the cerebral hemorrhage area developed in this study can be used as auxiliary diagnostic data for medical staff.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.81-86
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• 2010

Since CORDIC (COordinate Rotation DIgital Computer) is able to carry out the phase operation, such as vector to phase conversion or rotation of vectors, with adders and shifters, it is well suited for the design of the frequency synchronization unit in OFDM receivers. It is not easy, however, to fully utilize the CORDIC in the OFDM demodulator because of the non-linear characteristics of the direction sequence (DS), which is the representation of the phase in CORDIC. In this paper a new representation method is proposed to linearize the direction sequence approximately. The maximum phase error of the linearized binary direction sequence (LBDS) is also discussed. For the purpose of designing the hardware, the architectures for the binary DS (BDS) to LBDS converter and the LBDS to BDS inverse converter are illustrated. Adopting LBDS, the overall frequency synchronization hardware for OFDM receivers can be implemented fully utilizing CORDIC and general arithmetic operators, such as adders and multipliers, for the phase estimation, loop filtering of the frequency offset, derotation for the frequency offset correction. An example of the design of 22 bit LBDS for the T-DMB demodulator is also presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.827-830
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• 2011

In this paper, a wind speed & direction module and the DSP(Digital Signal Processor) sensor interface circuit board are proposed. This DSP system accepts and process the informations from a wind speed & direction module, the atmospheric pressure sensor, the ambient air temperature sensor and transfers it to the PC monitering system. Especially, a wind speed & direction module and a DSP hardware are directly designed and applied. A wind speed & direction module have a construction that it have four film type RTD(Resistive Temperature Detectors) or film type Piezo sensors adhered around the circular metal body for obtaining vector informations about wind. By this structure, the module is enabled precise measurement having a robustness about vibration, humidity, corrosion. A sensor signal processing circuit is using TMS320F2812 TI(Texas Instrument) Corporation high speed DSP.

• Journal of Coastal Disaster Prevention
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• v.4 no.1
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• pp.7-19
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• 2017

In this study, waves and currents observed by acoustic AWAC, VECTOR and Aquadopp Profiler in Anmok coastal waters were analysed to account for the variability of wave and current and to understand the mechanism of sediment transport generated by wave-induced current in the surf-zone. The monthly variation of wave and residual currents were analysed and processed with long-term observed AWAC data at station W1, located at the water depth of about 18m measured during from February 2015 to September 2016. Wave-induced currents were also analysed with intensive field measurements such as wave, current, suspended sediment, and bathymetry data observed at the surf-zone during in winter and summer. The statistical result of wave data shows that high waves coming from NNE and NE in winter (DEC-FEB) are dominant due to strong winds from NE. But in the other season waves coming from NE and ENE are prevalent due to the seasonal winds from E and SE. The residual currents with southeastern direction parallel to the shoreline are dominant throughout a year except in winter showing in opposite direction. The speed of ebb-dominant southeastern residual currents decreasing from surface to the bottom is strong in summer and fall but weak in winter and spring. By analysing wave-induced current, we found that cross-shore current were generated by swell waves mainly in winter with incoming wave direction about $45^{\circ}$ normal to the shoreline. Depending on the direction of incoming waves, longshore currents in the surf-zone were separated to southeastern and northwestern flows in winter and summer respectively. The variation of observed currents near crescentic bars in the surf-zone shows different direction of longshore and cross-shore currents depending on incoming waves implying to the reason of beach erosion generating the beach cusp and sandbar migration during high waves at Anmok.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.755-767
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• 2014

In this study, detailed air flow characteristics in an urban areas were analyzed using GIS data and a Computational Fluid Dynamics (CFD) model. For this, a building construction algorithm optimized for Geographic Information System (GIS) data with a vector format (Los Angeles region imagery acquisition consortium 2 geographic information system, LARIAC2 GIS) was used. In the LARIAC2 GIS data, building vertices were expressed as latitude and longitude. Using the model buildings constructed by the algorithm as the surface boundary data in the CFD model, we performed numerical simulations for two building-congested areas in Los Angeles using inflow information provided by California Air Resources Board. Comparing with the inflow, there was a marked difference in wind speed and direction within the target areas, which was mainly caused by the secondarily induced local circulations such as street-canyon vortices, horse-shoe vortices, and recirculation zones. In street canyons parallel to the inflow direction, wind speed increased due to a channeling effect and, in street canyons perpendicular to the inflow direction, vertically well developed vortices were induced. In front of a building, a horse-shoe vortex was developed near the surface and, behind a building, a recirculation zone was developed. Near the surface in the areas where the secondarily induced local circulations, wind speed remarkably increased. Overall, wind direction little (largely) changed at the areas where wind speed largely increased (decreased).

• Journal of radiological science and technology
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• v.33 no.4
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• pp.379-386
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• 2010

This study evaluated the motion of tumors during the entire period of therapy and the accuracy of radiosurgery among forty eight lung tumor patients who were underwent radiosurgery using the CyberKnife Synchrony Respiratory Tracking System. The motion of lung tumor was measured by the coordinates of a gold acupuncture needle inserted into the tumor or the area around the tumor using the CyberKnife image guided system. Then the accuracy of radiosurgery was evaluated based on the error of correlation computed with the motion tracking system. The lung tumor motion is Cranio-Caudal direction by an average of $2.63{\pm}1.87\;mm$, moved left-right direction by $1.13{\pm}0.71\;mm$, and anterior-posterior direction by $1.74{\pm}1.16\;mm$. The degree of rotational movement was $1.66{\pm}1.66^{\circ}$ on X axis, $1.20{\pm}0.97^{\circ}$ on Y axis, and $1.18{\pm}0.73^{\circ}$ on Z axis. The vector of translation movement was measured to be $3.78{\pm}2.00\;mm$ on the average. The results show that directions of Cranio-Caudal(p < 0.001), anterior-posterior direction(p < 0.029), and three dimensional vector value(p < 0.002) showed statistical significance, because the lower side of tumor showed more intensive movement compared to the upper side of tumor. The radiosurgery was carried out by compensating the motion of tumor after accurate investigation of the correlation error with the average of $0.95{\pm}0.62\;mm$ during the lung tumor radiosurgery with the CyberKnife Synchrony Respiratory Tracking System.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.77-83
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• 2023

In this study, the expressions of magnetic vector and magnetic gradient tensor due to an elliptical cylinder were derived. Igneous intrusions and kimberlite structures are often shaped like elliptical cylinders with axial symmetry and different radii in the strike and perpendicular directions. The expressions of magnetic fields due to this elliptical cylinder were derived from the Poisson relation, which includes the direction of magnetization in the gravity gradient tensor. The magnetic gradient tensor due to an elliptical cylinder is derived by differentiating the magnetic fields. This method involves obtaining a total of 10 triple derivative functions acquired by differentiating the gravitational potential of the elliptical cylinder three times in each axis direction. As the order of differentiation and integration can be exchanged, the magnetic gradient tensor was derived by differentiating the gravitational potential of the elliptical cylinder three times in each direction, followed by integration in the depth direction. The remaining double integration was converted to a complex line integral along the closed boundary curve of the elliptical cylinder in the complex plane. The expressions of the magnetic field and magnetic gradient tensor derived from the complex line integral in the complex plane were shown to be perfectly consistent with those of the circular cylinder derived by the Lipschitz-Hankel integral.

• Information Systems Review
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• v.22 no.4
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• pp.21-39
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• 2020

Recently, deep learning has shown high performance in various applications such as pattern analysis and image classification. Especially known as a difficult task in the field of machine learning research, stock market forecasting is an area where the effectiveness of deep learning techniques is being verified by many researchers. This study proposed a deep learning Convolutional Neural Network (CNN) model to predict the direction of stock prices. We then used the feature selection method to improve the performance of the model. We compared the performance of machine learning classifiers against CNN. The classifiers used in this study are as follows: Logistic Regression, Decision Tree, Neural Network, Support Vector Machine, Adaboost, Bagging, and Random Forest. The results of this study confirmed that the CNN showed higher performancecompared with other classifiers in the case of feature selection. The results show that the CNN model effectively predicted the stock price direction by analyzing the embedded values of the financial data

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.78-85
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• 2011

In this paper, a research on multi-agent is carried out in order to develop a system that can provide drivers with real-time route recommendation by reflecting Dynamic Environment Information which acts as an agent in charge of Driver's trait, road condition and Route recommendation system. DEI is equivalent to number of n multi-agent and is an environment variable which is used in route recommendation system with optimal routes for drivers. Route recommendation system which reflects DEI can be considered as a new field of topic in multi-agent research. The representative research of Multi-agent, the Prey Pursuit Problem, was used to generate a fresh solution. In this thesis paper, you will be able to find the effort of indulging the lack of Prey Pursuit Problem,, which ignored practicality. Compared to the experiment, it was provided a real practical experiment applying the algorithm, the new Ant-Q method, plus a comparison between the strategies of the established direction vector was put into effect. Together with these methods, the increase of the efficiency was able to be proved.