• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.233-262
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• 2024

Due to the rapid evolution of vehicular ad hoc networks (VANETs), effective communication and security are now essential components in providing secure and reliable vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. However, due to their dynamic nature and potential threats, VANETs need to have strong security mechanisms. This paper presents a novel approach to improve VANET security by combining the Vehicular Delay-Tolerant Network (VDTN) protocol with the Deep Reinforcement Learning (DRL) technique known as the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. A store-carry-forward method is used by the VDTN protocol to resolve the problems caused by inconsistent connectivity and disturbances in VANETs. The TD3 algorithm is employed for capturing and detecting Worm Hole Attack (WHA) behaviors in VANETs, thereby enhancing security measures. By combining these components, it is possible to create trustworthy and effective communication channels as well as successfully detect and stop rushing attacks inside the VANET. Extensive evaluations and simulations demonstrate the effectiveness of the proposed approach, enhancing both security and communication efficiency.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.183-193
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• 2019

Process mining is an analytical technique aimed at obtaining useful information about a process by extracting a process model from events log. However, most existing process models are deterministic because they do not include stochastic elements such as the occurrence probabilities or execution times of activities. Therefore, available information is limited, resulting in the limitations on analyzing and understanding the process. Furthermore, it is also important to develop an efficient methodology to discover the process model. Although genetic process mining algorithm is one of the methods that can handle data with noises, it has a limitation of large computation time when it is applied to data with large capacity. To resolve these issues, in this paper, we define a stochastic process tree and propose a tabu search-genetic process mining (TS-GPM) algorithm for a stochastic process tree. Specifically, we define a two-dimensional array as a chromosome to represent a stochastic process tree, fitness function, a procedure for generating stochastic process tree and a model trace as a string of activities generated from the process tree. Furthermore, by storing and comparing model traces with low fitness values in the tabu list, we can prevent duplicated searches for process trees with low fitness value being performed. In order to verify the performance of the proposed algorithm, we performed a numerical experiment by using two kinds of event log data used in the previous research. The results showed that the suggested TS-GPM algorithm outperformed the GPM algorithm in terms of fitness and computation time.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.658-668
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• 2011

Over the past decade, the improvement of communications technologies and the rapid spread of www (World Wide Web) have brought on the exponential growth of users using Internet and real time multimedia multicast services like video conferencing, tele-immersive virtual reality, and Internet games. The dense-wavelength division multiplexing (DWDM) networks have been widely accepted as a promising approach to meet the ever-increasing bandwidth demands of Internet users, especially in next generation Internet backbone networks for nation-wide or global coverage. A major challenge in the next generation Internet backbone networks based on DWDM technologies is the resolution of the multicasting RWA (Routing and Wavelength Assignment) problem; given a set of wavelengths in the DWDM network, we set up light-paths by routing and assigning a wavelength for each connection so that the multicast connections are set-upped as many as possible. Finding such optimal multicast connections has been proven to be Non-deterministic Polynomial-time-complete. In this paper, we suggest a new heuristic multicast routing and wavelength assignment method for multicast sessions called DVS-PMIPMR (Differentiated Virtual Source-based Priority Minimum Interference Path Multicast Routing algorithm). We measured the performance of the proposed algorithm in terms of number of wavelength and wavelength channel. The simulation results demonstrate that DVS-PMIPMR algorithm is superior to previous multicast routing algorithms.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.1
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• pp.36-41
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• 2009

In general, accurate attitude information is essential to perform the mission. Two algorithms are well-known to determine the attitude through two or more vector observations. One is deterministic method such as TRIAD algorithm, the other is optimal method such as QUEST algorithm. This Paper suggests the idea to improve performance of the TRIAD algorithm and to determine the attitude by combination of different sensors. First, we change the attitude matrix to Euler angle instead of using orthogonalization method and also use covariance in place of variance, then apply an unbiased minimum variance formula for more accurate solutions. We also suggest the methodology to determine the attitude when more than two measurements are given. The performance of the Averaging TRIAD algorithm upon the combination of different sensors is analyzed by numerical simulation in terms of standard deviation and probability.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.8
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• pp.884-894
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• 1999

순서적 동기화 및 내포 병렬성을 포함하는 공유메모리 병렬 프로그램에서의 경합(race)은 프로그램 수행에서 원하지 않은 비결정성(nondeterminism)을 야기할 수 있기 때문에 반드시 탐지되어져야 한다. 특히 프로그램 수행에서 최초경합(first race)을 탐지하는 것은 중요한데, 그 이유는 이 경합을 제거하면 다른 경합이 나타나지 않을 수도 있기 때문이다. 본 논문에서는 결정적 공유메모리 병렬프로그램을 위한 2단계 수행중 (two-pass on-the-fly) 최초경합 탐지 기법을 제시하며, 이것은 공유메모리 병렬 프로그램의 특정 수행에서 "최초로 발생되는" 경합들을 탐지하는 기법이다. 그리고 HPF 컴파일러를 이용하여 본 탐지 프로토콜을 공인된 벤치마크 프로그램에 적용하여, 병렬 프로그램 디버깅 시 고려하여야 할 파라미터들에 대한 실험으로부터 본 기법의 효율성을 보였다.Abstract Detecting races is important in debugging shared-memory parallel programs which have ordered synchronization and nested parallelism, because the races result in unintended non- deterministic executions of the programs. The first races are important in debugging, because the removal of such races may make other races disappear. It is even possible that all races reported would disappear once the first races are removed. This paper presents a new two-pass on-the-fly algorithm to detect the first races in such parallel programs. The algorithm reported in this paper is an on-the-fly algorithm that detects the races that "occur first" in a particular execution of shared-memory parallel programs. The experiment has accomplished, where two certified benchmark programs which can be executed under High Performance Fortran environments to get some parameters which improve debugging performance with our algorithm. with our algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.98-105
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• 2003

We propose a new technique of deinterleaving multiple radar pulse sequences by means of genetic algorithm for threat identification in electronic warfare(EW) system. The conventional approaches based on histogram or continuous wavelet transform are so deterministic that they are subject to failing in detection of individual signal characteristics under real EW signal environment that suffers frequent signal missing, noise, and counter-EW signal. The proposed algorithm utilizes the probabilistic optimization procedure of genetic algorithm. This method, a time-of-arrival(TOA) only strategy, constructs an initial chromosome set using the difference of TOA. To evaluate the fitness of each gene, the defined pulse phase is considered. Since it is rare to meet with a single radar at a moment in EW field of combat, multiple solutions are to be derived in the final stage. Therefore it is designed to terminate genetic process at the prematured generation followed by a chromosome grouping. Experimental results for simulated and real radar signals show the improved performance in estimating both the number of radar and the pulse repetition interval.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.4
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• pp.298-307
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• 2016

Attitude determination of satellite is categorized by deterministic and recursive method. The recursive algorithm using Kalman filter is widely used. Cubesat has limitation for payload to minimize then only two attitude sensors are installed which are sun sensor and magnetometer. Sun sensor measurements are useless during eclipse, however cubesat keeps estimating attitude to complete the successful mission. In this paper, Attitude determination algorithm based on Kalman filter is developed by additional term which considering the dynamics for SNUSAT-1 with disturbance torque. Verification of attitude accuracy of the algorithm is conducted during eclipse. Attitude determination algorithm is simulated to compare the performance between typical method and proposed algorithm. In addition, Attitude errors are analysed with various magnitude of disturbance torque caused by space environment.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.13-20
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• 2019

For customized education, it is essential to search the learning path for the learner. The genetic algorithm makes it possible to find optimal solutions within a practical time when they are difficult to be obtained with deterministic approaches because of the problem's very large search space. In this research, based on genetic algorithm, the learning paths to learn 200 chords in 27 music sheets were optimized to maximize the learning effect by balancing and minimizing learner's burden and learning size for each step in the learning paths. Although the permutation size of the possible learning path for 27 learning contents is more than $10^{28}$, the optimal solution could be obtained within 20 minutes in average by an implemented tool in this research. Experimental results showed that genetic algorithm can be effectively used to design complex learning path for customized education with various purposes. The proposed method is expected to be applied in other educational domains as well.

• Smart Media Journal
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• v.11 no.1
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• pp.38-45
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• 2022

A lot of research is being going until this day in order to obtain stable profit in the stock market. Trading algorithms are widely used, accounting for over 80% of the trading volume of the US stock market. Despite a lot of research, there is no trading algorithm that always shows good performance. In other words, there is no guarantee that an algorithm that performed well in the past will perform well in the future. The reason is that there are many factors that affect the stock price and there are uncertainties about the future. Therefore, in this paper, we propose a model using TimeGAN that predicts future returns well and selects algorithms that are expected to have high returns based on past records of the returns of algorithms. We use TimeGAN becasue it is probabilistic, whereas LSTM method predicts future time series data is deterministic. The advantage of TimeGAN probabilistic prediction is that it can reflect uncertainty about the future. As an experimental result, the method proposed in this paper achieves a high return with little volatility and shows superior results compared to many comparison algorithms.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.2
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• pp.33-44
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• 2008

Most of the civil structure - bridges, offshore structures, plant, etc. - have been designed by the classical approaches which deal with all the design parameters as deterministic variables. However, some more advanced techniques are required to evaluate the inherent randomness and uncertainty of each design variable. In this research, a seismic safety assessment algorithm based on the structural reliability analysis has been formulated and computerized for more reasonable seismic design of turbine-generator foundations. The formulation takes the design parameters of the system and loading properties as random variables. Using the proposed method, various kinds of parametric studies have been performed and probabilistic characteristics of the resulted structural responses have been evaluated. Afterwards, the probabilistic safety of the system has been quantitatively evaluated and finally presented as the reliability indexes and failure probabilities. The proposed procedure is expected to be used as a fundamental tool to improve the existing design techniques of turbine-generator foundations.