• ETRI Journal
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• v.42 no.6
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• pp.815-826
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• 2020

We propose a two-dimensional (2D) scattering-center-extraction (SCE) method using sparse recovery based on the compressive-sensing theory, even with data missing from the received radar cross-section (RCS) dataset. First, using the proposed method, we generate a 2D grid via adaptive discretization that has a considerably smaller size than a fully sampled fine grid. Subsequently, the coarse estimation of 2D scattering centers is performed using both the method of iteratively reweighted least square and a general peak-finding algorithm. Finally, the fine estimation of 2D scattering centers is performed using the orthogonal matching pursuit (OMP) procedure from an adaptively sampled Fourier dictionary. The measured RCS data, as well as simulation data using the point-scatterer model, are used to evaluate the 2D SCE accuracy of the proposed method. The results indicate that the proposed method can achieve higher SCE accuracy for an incomplete RCS dataset with missing data than that achieved by the conventional OMP, basis pursuit, smoothed L0, and existing discrete spectral estimation techniques.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.451-458
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• 2021

Providing a secure and effective way to protect confidential and private data is an urgent process, and accordingly, we will present in this research paper a new method, which is called multiple rounds variable block method (MRVB) which depends on the use of a colored image that is kept secret to generate needed work and round keys. This method can be used to encrypt-decrypt data using various lengths private key and data blocks with various sizes. The number of rounds also will be variable starting from one round. MRVB will be implemented and compared with the encryption-decryption standards DES and AES to show the improvements provided by the proposed method in increasing the security level and in increasing the throughput of the process of data cryptography. The generated private key contents will depend on the used image_key and on the selected number of rounds and the selected number of bytes in each block of data.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.4 s.27
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• pp.35-43
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• 2003

Currently, the government has been driving numerous projects to build the e-government which can enable limitless access and utilization of the information through the accomplishment of the real time based various administrative services. In water resource field, a project to generate digital river thematic maps has been undergoing as a part of the computerization projects. As a partial results, the RIMGIS project has been completed and generation of the various river thematic maps has been required to fully utilize the DB built from RIMGIS project. For the effective generation of the thematic maps, a data model needs to be developed. A data model has been developed in this study to provide more efficient method to generate the thematic maps utilizing existing DB. The data model proposed from this study has defined the relationships between core feature data and framework Data along with relationships among data elements to represent the rivers in the real world more accurately. The core feature data and framework layers have been defined based on the survey of the domestic and foreign case studies along with requirement analysis of the users in the water resource field. The proposed core feature data has been defined based on the minimum unit of 'class', and the relationship between classes has been established based on the ArcGIS Hydro Data Model for the integrated processing of the river information. The proposed spatial data model can be judged to contribute establishing more efficient generation methodology of the river thematic maps.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.10 s.352
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• pp.34-44
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• 2006

A system-on-a-chip (SoC) design uses pre-verified IP hardware blocks in order to reduce design time. We need interface circuits to connect IPs with different protocols. In SoC design we should design interface circuits frequently and these tasks are somewhat time-consuming and error-prone. So it is necessary to generate the interface circuits automatically. Several studies have been made on generating interface circuits only from the communication protocols of IPs. With existing approaches, it is not easy to generate interface circuits connecting two IPs only from communication protocols: connection between IP with address and W without address, connection between IP with only one port to transfer address/data and IP with different ports for address and data connection between IP that transfer address and data together and IP that transfer only one address with a number of data in a burst. No consideration of various characteristics of IPs and no changed algorithm are responsible for it. In order to solve this problem, the proposed approach categorizes communication protocols of IPs, and takes characteristics matching of IPs into account during the interface synthesis. In experiments, we show that we could correctly generate and verify interface circuits for IPs with different characteristics.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• Geophysics and Geophysical Exploration
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• v.24 no.3
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• pp.89-97
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• 2021

Fault detection in seismic data is well suited to the application of machine learning algorithms. Accordingly, various machine learning techniques are being developed. In recent studies, machine learning models, which utilize synthetic data, are the particular focus when training with deep learning. The use of synthetic training data has many advantages; Securing massive data for training becomes easy and generating exact fault labels is possible with the help of synthetic training data. To interpret real data with the model trained by synthetic data, the synthetic data used for training should be geologically realistic. In this study, we introduce a method to generate realistic synthetic seismic data. Initially, reflectivity models are generated to include realistic fault structures, and then, a one-way wave equation is applied to efficiently generate seismic stack sections. Next, a migration algorithm is used to remove diffraction artifacts and random noise is added to mimic actual field data. A convolutional neural network model based on the U-Net structure is used to verify the generated synthetic data set. From the results of the experiment, we confirm that realistic synthetic data effectively creates a deep learning model that can be applied to field data.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.491-500
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• 2004

As the applications of 3D GIS rapidly increase, the need for acquisition and continuos update of urban models is increasingly emphasized. Particularly, building models has been considered as the most crucial component of urban models. Many researchers thus have focused on building extraction from mainly aerial photos or airborne LIDAR data but so far mostly failed to achieve satisfactory results in terms of both completeness and precision because of the intrinsic limitation of the sensory data themselves. Therefore, instead of the airborne sensors, we utilize a terrestrial LIDAR to generate precise and complete building models. This paper presents the overview of the sensors for data acquisition, describes data processing methods for building modelling from the acquired data and summerizes the experimental results.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.383-388
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• 2004

The fusion of a different kind sensor is fusion of the obtained data by the respective independent technology. This is a important technology for the construction of 3D spatial information. particularly, information is variously realized by the fusion of LiDAR and mobile scanning system and digital map, fusion of LiDAR data and high resolution, LiDAR etc. This study is to generate union DEM and digital ortho image by the fusion of LiDAR data and high resolution image and monitor precisely topology, building, trees etc in urban areas using the union DEM and digital ortho image. using only the LiDAR data has some problems because it needs manual linearization and subjective reconstruction.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.38-41
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• 2002

Many scientifc applications include manipulation of data points tying in a space. We describe a method, based on sector labeling to generate a space-filling curve for partitioning such given data points. Our method is straightforward and flexible, equipping a one-one correspondence between point-values on the curve and data points in space in more efficient than designated methods found in the literature. It is widely believed that the Hilbert curve achieves the desired properties on linear mappings due to the locality between data points. Therefore we focus on the Hilbert curve since, later on, we identify it as the most suitable for our application. We demonstrate on using our method for the data particles of an n-body simulation that based on Barnes-Hut algorithm.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.1-13
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• 2014

This study aims to show the risk reduction effects of round-the-clock trading environment. We analyse the trading results of the currency futures contracts in CME Globex which are open 23 hours a day. These include Euro FX, Japanese Yen, Australian Dollar, and British Pound from January 2005 to August 2013. We generate new price series using only daytime prices during about 7-hour period. This hypothetical "G" data series may have greater gap risk than the original "R" data series. Empirical results show the trading risk reduction effects, that is R data series have higher profits and lower risks than G data series.