• Geomechanics and Engineering
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• v.13 no.6
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• pp.893-906
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• 2017

Automatic large scale soil model generation is very critical stage for earthquake hazard simulation of urban areas. Manual model development may cause some data losses and may not be effective when there are too many data from different soil observations in a wide area. Geographic information systems (GIS) for storing and analyzing spatial data help scientists to generate better models automatically. Although the original soil observations were limited to soil profile data, the recent developments in mapping technology, interpolation methods, and remote sensing have provided advanced soil model developments. Together with advanced computational technology, it is possible to handle much larger volumes of data. The scientists may solve difficult problems of describing the spatial variation of soil. In this study, an algorithm is proposed for automatic three dimensional soil and velocity model development of southern part of the European side of Istanbul next to Sea of Marmara based on GIS data. In the proposed algorithm, firstly bedrock surface is generated from integration of geological and geophysical measurements. Then, layer surface contacts are integrated with data gathered in vertical borings, and interpolations are interpreted on sections between the borings automatically. Three dimensional underground geology model is prepared using boring data, geologic cross sections and formation base contours drawn in the light of these data. During the preparation of the model, classification studies are made based on formation models. Then, 3D velocity models are developed by using geophysical measurements such as refraction-microtremor, array microtremor and PS logging. The soil and velocity models are integrated and final soil model is obtained. All stages of this algorithm are carried out automatically in the selected urban area. The system directly reads the GIS soil data in the selected part of urban area and 3D soil model is automatically developed for large scale earthquake hazard simulation studies.

• Journal of IKEEE
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• v.25 no.4
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• pp.766-769
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• 2021

In order to perform tasks such as design, control, optimization, and prediction of flight vehicle trajectories based on machine learning techniques including deep learning, a certain amount of flight vehicle trajectory data is required. However, there are cases in which it is difficult to secure more than a certain amount of flight vehicle trajectory data for various reasons. In such cases, synthetic data generation could be one way to make machine learning possible. In this paper, to explore this possibility, we generated and evaluated synthetic flight vehicle trajectory data using time-series generative adversarial neural network. In addition, various ablation studies (comparative experiments) were performed to explore the possibility of using synthetic data in the aircraft trajectory prediction task. The experimental results presented in this paper are expected to be of practical help to researchers who want to conduct research on the possibility of using synthetic data in the generation of synthetic flight vehicle trajectory data and the work related to flight vehicle trajectories.

• Journal of Families and Better Life
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• v.14 no.2
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• pp.97-110
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• 1996

The purpose of this study was to compare the caregiver burden and rewards in new generation and middle-aged couples. Data were collected from 207 new generation couples and 196 middle-aged couples who had either of older parents and lived in Seoul. Major findings are as fallows; 1. The burden were constituted with restriction of privacy physical burden strain psychological burden economic cost and guilt. The rewards were constituted with recognition pride maturity improving relationship and assistance of household and childcare. 2. The caregiver burden of new generation and middle-aged wives were hgiher than husbands. Hwever the caregiver rewards of new generation and middle-aged husbands were higher than wives. 3. The caregiver burden of middle-aged husbands were higher than new generation husbands bur there was no significant difference between new generation and middle-aged wives. 4. The caregiver rewards of middle-aged wives were higher than new generation wives but there was no significant difference between new generation and middle-aged husbands.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4B
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• pp.397-402
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• 2002

The IFSAR technique using SAR data has various applications and is the only latest technology to produce high precision height information from the radar phase data. This paper describes the whole implementation algorithm of IFSAR technique. Also it suggests the algorithms for azimuth aliasing resolution and interferogram generation of SAR data. Those are proved through the experiment: azimuth aliasing is resolved and interferogram is generated properly. Therefore, it proposes the method for interferogram generation, an essential process in extracting high precision height data, and the development approach to principal modules of IFSAR algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.5
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• pp.197-212
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• 1997

The performance of a torque converter can be expressed by the performance parameters such as flow radius and flow angle, on the mean flow path. The geometric analysis of the torque converter is required to determine these parameters for the modeling of the torque converter. In general, the blade shape is depicted by three dimensional data at the mid-surface of blade or those of the pressure and suction side. To generate three dimensional model of the blade using the data mentioned above, a consistent data format and a shape generation algorithm are required. This paper presents a useful consistent data format of the blades and an algorithm for the geometrical shape generation. By the geometric analysis program to which the shape generation algorithm is embedded, the variation of blade angles in rotating element analyzed. Then finally, the analyzed results of geometric profile of a blade are compared with those of the blade design principle, so called forced vortex theorem.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.21-26
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• 2018

Recently, data analysis technology through artificial intelligence is attracting major attention in various industrial fields. In addition, with the increase in personal income, nowadays, the importance of heterogeneous leisure life is becoming more prominent. However, there is a problem that the tourism industry is not out of the traditional service framework. For the ultimate development of the tourism industry, it is time to provide more scientific and systematic tourism services. In this paper, various data analysis techniques in the field of computer science are applied to the field of tourism to realize next generation tourism services. To this end, the scope of this study is limited to the aviation service, and a natural ecosystem of the aviation industry for future-oriented services of aviation tourism that can improve the efficiency of aviation service gradually is established. The proposed method effectively solves the problems of traditional aviation services through data analysis techniques with artificial intelligence techniques in computer science. We expect that it will enhance the customized satisfaction of customers through personalized service and foster loyal customers in aviation companies through the method proposed.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.6
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• pp.269-279
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• 2020

This paper presents the design and implementation of embedded systems and autonomous path generation for autonomous speed sprayer. Autonomous Orchard Systems can be divided into embedded controller and path generation module. Embedded controller receives analog sensor data, on/off switch data and control linear actuator, break, clutch and steering module. In path generation part, we get 3D cloud point using Velodyne VLP16 LIDAR sensor and process the point cloud to generate maps, do localization, generate driving path. Then, it finally generates velocity and rotation angle in real time, and sends the data to embedded controller. Embedded controller controls steering wheel based on the received data. The developed autonomous speed sprayer is verified in test-bed with apple tree-shaped artworks.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.5
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• pp.392-399
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• 2023

This research paper investigates the effectiveness of using computer graphics(CG) based synthetic data for deep learning in military vehicle detection. In particular, we explore the use of synthetic image generation techniques to train deep neural networks for object detection tasks. Our approach involves the generation of a large dataset of synthetic images of military vehicles, which is then used to train a deep learning model. The resulting model is then evaluated on real-world images to measure its effectiveness. Our experimental results show that synthetic training data alone can achieve effective results in object detection. Our findings demonstrate the potential of CG-based synthetic data for deep learning and suggest its value as a tool for training models in a variety of applications, including military vehicle detection.

• Electronics and Telecommunications Trends
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• v.39 no.5
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• pp.21-30
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• 2024

Memory can refer to a storage device that collects data, and it has evolved to increase the reading/writing speed and reduce the power consumption. As large amounts of data are processed by artificial intelligence services, the memory data capacity requires expansion. Dynamic random-access memory (DRAM) is the most widely used type of memory. In particular, graphics double date rate and high-bandwidth memory allow to quickly transfer large amounts of data and are used as memory solutions for artificial intelligence semiconductors. We analyze development trends in DRAM from the perspectives of processing speed and power consumption. We summarize the characteristics required for next-generation memory by comparing DRAM and other types of memory implementations. Moreover, we examine the shortcomings of DRAM and infer a next-generation memory for their compensation. We also describe the operating principles of spin-torque transfer magnetic random access memory, which may replace DRAM in next-generation devices, and explain its characteristics and advantages.

• Journal of Digital Contents Society
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• v.15 no.3
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• pp.365-371
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• 2014

In the era of big data, algorithms for the existing IT environment cannot accept on a distributed architecture such as hadoop. Thus, new distributed algorithms which apply a distributed framework such as MapReduce are needed. Lloyd's algorithm commonly used for vector quantization is developed using MapReduce recently. In this paper, we proposed a decombined distributed VQ codebook generation algorithm based on a distributed VQ codebook generation algorithm using MapReduce to get a result more fast. The result of applying the proposed algorithm to big data showed higher performance than the conventional method.