• Journal of KIISE:Databases
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• v.34 no.1
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• pp.1-17
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• 2007

As XML is becoming a de facto standard for distribution and sharing of information, the need for an efficient yet secure access of XML data has become very important. To enforce the fine-level granularity requirement, authorization models for regulating access to XML documents use XPath which is a standard for specifying parts of XML data and a suitable language for both query processing. An access control environment for XML documents and some techniques to deal with authorization priorities and conflict resolution issues are proposed. Despite this, relatively little work has been done to enforce access controls particularly for XML databases in the case of query access. Developing an efficient mechanism for XML databases to control query-based access is therefore the central theme of this paper. This work is a proposal for an efficient yet secure XML access control system. The basic idea utilized is that a user query interaction with only necessary access control rules is modified to an alternative form which is guaranteed to have no access violations using tree-aware metadata of XML schemes and set operators supported by XPath 2.0. The scheme can be applied to any XML database management system and has several advantages over other suggested schemes. These include implementation easiness, small execution time overhead, fine-grained controls, and safe and correct query modification. The experimental results clearly demonstrate the efficiency of the approach.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.99-110
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• 2017

Improving tracking performance by estimating the status of multiple targets using radar is important. In a clutter environment, a joint event occurs between the track and measurement in multiple target tracking using a tracking filter. As the number increases, the joint event increases exponentially. The problem to be considered when multiple target tracking filter design in such environments is that first, the tracking filter minimizes the rate of false track alarmsby eliminating the false track and quickly confirming the target track. The purpose is to increase the FTD performance. The second consideration is to improve the track maintenance performance by allocating each measurement to a track efficiently when an event occurs. Through two considerations, a single target tracking data association technique is extended to a multiple target tracking filter, and representative algorithms are JIPDAF and LM-IPDAF. In this study, a probabilistic evaluation of many hypotheses in the assignment of measurements was not performed, so that the computation amount does not increase nonlinearly according to the number of measurements and tracks, and the track existence probability based on the track density The LM-IPDAF algorithm was introduced. This paper also proposes a method to reduce the computational complexity by improving the clutter density estimation method for calculating the track existence probability of LM-IPDAF. The performance was verified by a comparison with the existing algorithm through simulation. As a result, it was possible to reduce the simulation processing time by approximately 20% while achieving equivalent performance on the position RMSE and Confirmed True Track.

• Smart Media Journal
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• v.8 no.4
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• pp.58-63
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• 2019

The growth of the mobile device market has changed the education market and led to the quantitative growth of various media education. In particular, smart devices, which have better interaction than existing PCs or consoles, can develop more user-friendly content, allowing various types of educational content and inducing changes in traditional education methods for consumers. Although many researchers recently suggest viable development methods or marketing elements of contents, development companies, and developers, until now, merely rely on the human senses. Therefore, it is necessary to study the actual user's smart-device based usability and experience environment. This study aims to propose an intuitive statistical processing method for analyzing the usability of game-type educational contents in terms of form, for popular games that have been released as a basis for analyzing the user experience environment. In particular, because the game industry has a sufficient number of similar examples, it is possible to conduct research based on big data and to use them for immediate decision-making between multiple co-developers through the analysis method proposed by the research. It is expected to become an analytical model that can communicate with other industries because it is effective in securing data sources.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.5
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• pp.17-30
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• 2001

In this paper, we implemented a scalar multiplier needed at an elliptic curve cryptosystem over standard basis in $GF(2^{163})$. The scalar multiplier consists of a radix-16 finite field serial multiplier and a finite field inverter with some control logics. The main contribution is to develop a new fast finite field inverter, which made it possible to avoid time consuming iterations of finite field multiplication. We used an algorithmic transformation technique to obtain a data-independent computational structure of the Extended Euclid GCD algorithm. The finite field multiplier and inverter shown in this paper have regular structure so that they can be easily extended to larger word size. Moreover they can achieve 100% throughput using the pipelining. Our new scalar multiplier is synthesized using Hyundai Electronics 0.6$\mu\textrm{m}$ CMOS library, and maximum operating frequency is estimated about 140MHz. The resulting data processing performance is 64Kbps, that is it takes 2.53ms to process a 163-bit data frame. We assure that this performance is enough to be used for digital signature, encryption & decryption and key exchange in real time embedded-processor environments.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.579-586
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• 2021

Time series forecasting refers to predicting future time information based on past time information. Accurately predicting future information is crucial because it is used for establishing strategies or making policy decisions in various fields. Recently, a transformer model has been mainly studied for a time series prediction model. However, the existing transformer model has a limitation in that it has an auto-regressive structure in which the output result is input again when the prediction sequence is output. This limitation causes a problem in that accuracy is lowered when predicting a distant time point. This paper proposes a sequential decoding model focusing on the style transformation technique to handle these problems and make more precise time series forecasting. The proposed model has a structure in which the contents of past data are extracted from the transformer-encoder and reflected in the style-based decoder to generate the predictive sequence. Unlike the decoder structure of the conventional auto-regressive transformer, this structure has the advantage of being able to more accurately predict information from a distant view because the prediction sequence is output all at once. As a result of conducting a prediction experiment with various time series datasets with different data characteristics, it was shown that the model presented in this paper has better prediction accuracy than other existing time series prediction models.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1761-1775
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• 2022

Due to unpredictable climate change, the frequency of occurrence of water-related disasters and the scale of damage are also continuously increasing. In terms of disaster management, it is essential to identify the damaged area in a wide area and monitor for mid-term and long-term forecasting. In the field of water disasters, research on remote sensing technology using Synthetic Aperture Radar (SAR) satellite images for wide-area monitoring is being actively conducted. Time-series analysis for monitoring requires a complex preprocessing process that collects a large amount of images and considers the noisy radar characteristics, and for this, a considerable amount of time is required. With the recent development of cloud computing technology, many platforms capable of performing spatiotemporal analysis using satellite big data have been proposed. Google Earth Engine (GEE)is a representative platform that provides about 600 satellite data for free and enables semi real time space time analysis based on the analysis preparation data of satellite images. Therefore, in this study, immediate water disaster damage detection and mid to long term time series observation studies were conducted using GEE. Through the Otsu technique, which is mainly used for change detection, changes in river width and flood area due to river flooding were confirmed, centered on the torrential rains that occurred in 2020. In addition, in terms of disaster management, the change trend of the time series waterbody from 2018 to 2022 was confirmed. The short processing time through javascript based coding, and the strength of spatiotemporal analysis and result expression, are expected to enable use in the field of water disasters. In addition, it is expected that the field of application will be expanded through connection with various satellite bigdata in the future.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.511-522
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• 2014

During the development of the software, a variety of bugs are reported. Several bug tracking systems, such as, Bugzilla, MantisBT, Trac, JIRA, are used to deal with reported bug information in many open source development projects. Bug reports in bug tracking system would be triaged to manage bugs and determine developer who is responsible for resolving the bug report. As the size of the software is increasingly growing and bug reports tend to be duplicated, bug triage becomes more and more complex and difficult. In this paper, we present an approach to assign bug reports to appropriate developers, which is a main part of bug triage task. At first, words which have been included the resolved bug reports are classified according to each developer. Second, words in newly bug reports are selected. After first and second steps, vectors whose items are the selected words are generated. At the third step, TF-IDF(Term frequency - Inverse document frequency) of the each selected words are computed, which is the weight value of each vector item. Finally, the developers are recommended based on the similarity between the developer's word vector and the vector of new bug report. We conducted an experiment on Eclipse JDT and CDT project to show the applicability of the proposed approach. We also compared the proposed approach with an existing study which is based on machine learning. The experimental results show that the proposed approach is superior to existing method.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.110-119
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• 2010

In this paper, we propose an automatic segmentation of the prostate using intensity distribution and gradient information in MR images. First, active shape model using adaptive intensity profile and multi-resolution technique is used to extract the prostate surface. Second, hole elimination using geometric information is performed to prevent the hole from occurring by converging the surface shape to the local optima. Third, the surface shape with large anatomical variation is corrected by using 2D gradient information. In this case, the corrected surface shape is often represented as rugged shape which is generated by the limited number of vertices. Thus, it is reconstructed by using surface modelling and smoothing. To evaluate our method, we performed the visual inspection, accuracy measures and processing time. For accuracy evaluation, the average distance difference and the overlapping volume ratio between automatic segmentation and manual segmentation by two radiologists are calculated. Experimental results show that the average distance difference was 0.3${\pm}$0.21mm and the overlapping volume ratio was 96.31${\pm}$2.71%. The total processing time of twenty patient data was 16 seconds on average.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.896-904
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• 2004

In this paper, We present an efficient variable rate speech coder for spectral efficiency and packet processing technique for packet loss compensation of a voice codec with 10msec frame in VoIP service. Through disconnecting the users from the spectral resource during silence interval of about 60% period, a variable rate voice coder based on a voice activity detection(VAD) can increase spectral gain by two times. The performance of the method was analyzed by variation of detected voice activity factor and degraded speech frame ratio under various background noise level, and compared those of G.729B of ITU-T 8kbps standard speech codec. A method to compensate lost packets utilized addition of recovery data to a main stream and error concealment scheme for speech quality enhancement, the performance is verified by reconstructed speech quality. The proposed scheme can achieve spectral gain by two times or enhance speech quality by 3dB through reserved bandwidth of VAD. Therefore, the proposed method can enhance a spectral efficiency or speech quality of VoIP.