• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.184-191
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• 2020

Avionics System Integration Laboratory is the integrated test environment for integration and verification of avionics systems. When real equipment can not be used in the laboratory for various reasons, software models should be needed. Because there hasn't been any standardized method for the models so that it is difficult to reuse the developed models, the need for a framework to develop the avionics software models was emerged. We adopted DEVS(discrete event system specification) formalism as the standardized modeling method for the avionics software models. Due to DEVS formalism is based on event-driven algorithm, it doesn't accord a legacy system which has sequential and periodic algorithms. In this paper, we propose real-time event-driven modeling and simulation method for SIL to overcome these restrictions and to maximize reusability of avionics models through the analysis of the characteristics and the limitations of avionics models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9B
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• pp.1073-1081
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• 2011

An URL parameter can hold some information that is confidential or vulnerable to illegitimate tampering. We propose Link-E-Param(Link with Encrypted Parameters) to protect the whole URL parameter names as well as their values. Unlike other techniques concealing only some of the URL parameters, it will successfully discourage attacks based on URL analysis to steal secret information on the Web sites. We implement Link-E-Param in the form of a servlet filter to be deployed on any Java Web server by simply copying a jar file and setting a few configuration values. Thus it can be used for any existing Web application without modifying the application. It also supports numerous encryption algorithms to choose from. Experiments show that our implementation induces only 2~3% increase in user response time due to encryption and decryption, which is deemed acceptable.

• Spatial Information Research
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• v.20 no.1
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• pp.27-38
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• 2012

The recent development of CFD techniques are being involved w ith Environmental Impact Assessment and Environmental DesignroThey are being applied to the Site Planning and Engineering Design works as a new trendroHowever, CFD laboratory works are not extended to the field works in Industrial Project due to inaccuracy of the data input process that is cause by absence of regional height informationsroHence, in this study, we promote to build a new initial input data processing steps and algorithms for CFD Model generation. ENVI-met model is very popular, efficient, and freely downloadable CFD model. Light Detection And Ranging (LiDAR) are well known state of art technology and dataset proving a reliable accuracy for CFD. We use LiDAR data as a input source for CFD input producing process and algorithm development and evaluation. CFD initial input data generation process and results derived from am development and set is very useful and efficient for rapid CFD input data producing and maklomore reliable CFD Model forec st for atmospheric and climatic analysis for planning and design engineering industry.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1235-1242
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• 2013

This study deals with the BIM (Building Information Modeling)-based energy performance analysis implemented in EnergyPlus. The BIM model constructed at Revit is updated at Design Builder, adding HVAC models and converted compatibly with the EnergyPlus. We can obtain the input values about HVAC system and building environment such as HVAC system efficient, the number of air changes and energy consumption of equipment on applying GAs (Genetic algorithms). After modification about HVAC system, Optimization about HVAC system energy consumption can be analyzed. In order to maximize the building energy performance, a genetic algorithm (GA)-based optimization technique is applied to the modified HVAC models. Throughout the proposed building energy simulation, finally, the best optimized HVAC control schedule for the target building can be obtained in the form of "supply air temperature schedule". Throughout the supply air temperature schedule is applied to energy performance simulation, we obtained energy saving effect result on simulation.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.391-400
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• 2007

According to the recent advances in multimedia computing, storage and searching technology have made large volume of music contents become prevalent. Also there has been increasing needs for the study on efficient categorization and searching technique for music contents management. In this paper, a new classifying method using the local information of music content and music tone feature is proposed. While the conventional classifying algorithms are based on entire information of music content, the algorithm proposed in this paper focuses on only the specific local information, which can drastically reduce the computing time without losing classifying accuracy. In order to improve the classifying accuracy, it uses a new classification feature based on music tone. The proposed method has been implemented as a part of MuSE (Music Search/Classification Engine) which was installed on various systems including commercial PDAs and PCs.

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.563-572
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• 2002

Wireless mobile networks tend to drop a large portion of packets due to propagation errors rather than congestion. To Improve reliability over noisy wireless channels, wireless networks can employ forward error correction (FEC) techniques. Static FEC algorithms, however, can degrade the performance by poorly matching their overhead to the degree of the underlying channel error, especially when the channel path loss rate fluctuates widely. This paper investigates the benefits of an adaptable FEC mechanism for wireless networks with severe packet loss by analytical analysis or measurements over a real wireless network called sensor network. We show that our adaptive FEC named FECA (FEC-level Adaptation) technique improves the performance by dynamically tuning FEC strength to the current amount of wireless channel loss. We quantify these benefits through a hybrid simulation integrating packet-level simulation with bit-level details and validate that FECA keeps selecting the appropriate FEC-level for a constantly changing wireless channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.676-684
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• 2008

In digital video broadcasting-terrestrial (DVB-T), which is the European digital terrestrial television standard, the orthogonal frequency division multiplexing (OFDM) has been adopted for signal transmission. The main reasons using OFDM are to increase the robustness against the frequency selective fading and impulse noise, and to use available bandwidth efficiently. However, channel variation within an OFDM symbol destroys orthogonality between subcarriers, resulting in inter-carrier interference (ICI), which increases an error floor in proportional to maximum Doppler spread. This paper provides an ICI analysis in both time and frequency domains while existing literatures analyze the ICI effects mainly in frequency domain and proposes the algorithms that estimate the channel impulse response and channel variation using least square (LS) algorithm which is the most simple channel estimation technique. And we propose adaptive channel estimation algorithm that estimates the velocity of terminals. The simulation results show that proposed algorithm has similar performance with about 1.5% computational complexity of noise and ICI reduction LS algorithm in low speed environments.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.521-537
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• 2000

Ultrasonic imaging is the most widely used modality among modern imaging device for medical diagnosis and the system performance has been improved dramatically since early 90's due to the rapid advances in DSP performance and VLSI technology that made it possible to employ more sophisticated algorithms. This paper describes "main stream" digital signal processing functions along with the associated implementation considerations in modern medical ultrasound imaging systems. Topics covered include signal processing methods for resolution improvement, ultrasound imaging system architectures, roles and necessity of the applications of DSP and VLSI technology in the development of the medical ultrasound imaging systems, and array signal processing techniques for ultrasound focusing.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.56-68
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• 2022

Recently, as the demand for real-time processing increases, studies on a dynamic graph that changes over time has been actively done. There is a connected components processing algorithm as one of the algorithms for analyzing dynamic graphs. GPUs are suitable for large-scale graph calculations due to their high memory bandwidth and computational performance. However, when computing the connected components of a dynamic graph using the GPU, frequent data exchange occurs between the CPU and the GPU during real graph processing due to the limited memory of the GPU. The proposed scheme utilizes the Weighted-Quick-Union algorithm to process large-scale graphs on the GPU. It supports fast connected components computation by applying the size to the connected component label. It computes the connected component by determining the parts to be recalculated and minimizing the data to be transmitted to the GPU. In addition, we propose a processing structure in which the GPU and the CPU execute asynchronously to reduce the data transfer time between GPU and CPU. We show the excellence of the proposed scheme through performance evaluation using real dataset.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.3
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• pp.555-564
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• 2022

Recently, cyberattacks are using hacking techniques utilizing intelligent and advanced malicious codes for non-face-to-face environments such as telecommuting, telemedicine, and automatic industrial facilities, and the damage is increasing. Traditional information protection systems, such as anti-virus, are a method of detecting known malicious URLs based on signature patterns, so unknown malicious URLs cannot be detected. In addition, the conventional static analysis-based malicious URL detection method is vulnerable to dynamic loading and cryptographic attacks. This study proposes a technique for efficiently detecting malicious URLs by dynamically learning malicious URL data. In the proposed detection technique, malicious codes are classified using machine learning-based feature selection algorithms, and the accuracy is improved by removing obfuscation elements after preprocessing using Weighted Euclidean Distance(WED). According to the experimental results, the proposed machine learning-based malicious URL detection technique shows an accuracy of 89.17%, which is improved by 2.82% compared to the conventional method.