• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.580-586
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• 2021

The CAT methodology is a numerical analysis technique using CAE. Recently, a methodology of applying artificial intelligence techniques to a simulation has been studied. A previous study compared the deformation results according to the injection molding process using a machine learning technique. Although MLP has excellent prediction performance, it lacks an explanation of the decision process and is like a black box. In this study, data was generated using Autodesk Moldflow 2018, an injection molding analysis software. Several Machine Learning Algorithms models were developed using RapidMiner version 9.5, a machine learning platform software, and the root mean square error was compared. The decision-tree showed better prediction performance than other machine learning techniques with the RMSE values. The classification criterion can be increased according to the Maximal Depth that determines the size of the Decision-tree, but the complexity also increases. The simulation showed that by selecting an intermediate value that satisfies the constraint based on the changed position, there was 7.7% improvement compared to the previous simulation.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.127-134
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• 2022

Steganography is a hidden technique in which secret messages are hidden in various multimedia files, and it is widely exploited for cyber crime and attacks because it is very difficult for third parties other than senders and receivers to identify the presence of hidden information in communication messages. Botnet typically consists of botmasters, bots, and C&C (Command & Control) servers, and is a botmasters-controlled network with various structures such as centralized, distributed (P2P), and hybrid. Recently, in order to enhance the concealment of botnets, research on Stego Botnet, which uses SNS platforms instead of C&C servers and performs C&C communication by applying steganography techniques, has been actively conducted, but image or video media-oriented stego botnet techniques have been studied. On the other hand, audio files such as various sound sources and recording files are also actively shared on SNS, so research on stego botnet based on audio steganography is needed. Therefore, in this study, we present the results of comparative analysis on hidden capacity by file type and tool through experiments, using a stego botnet that performs C&C hidden communication using audio files as a cover medium in Telegram Messenger.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.498-509
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• 2023

Purpose: This paper proposes a method detecting the falling of a maintenance worker in the underground utility tunnel, by applying deep learning techniques using CCTV video, and evaluates the applicability of the proposed method to the worker monitoring of the utility tunnel. Method: Each rule was designed to detect the falling of a maintenance worker by using the inference results from pre-trained YOLOv5 and OpenPose models, respectively. The rules were then integrally applied to detect worker falls within the utility tunnel. Result: Although the worker presence and falling were detected by the proposed model, the inference results were dependent on both the distance between the worker and CCTV and the falling direction of the worker. Additionally, the falling detection system using YOLOv5 shows superior performance, due to its lower dependence on distance and fall direction, compared to the OpenPose-based. Consequently, results from the fall detection using the integrated dual deep learning model were dependent on the YOLOv5 detection performance. Conclusion: The proposed hybrid model shows detecting an abnormal worker in the utility tunnel but the improvement of the model was meaningless compared to the single model based YOLOv5 due to severe differences in detection performance between each deep learning model

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Journal of the Korea Fashion and Costume Design Association
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• v.15 no.3
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• pp.109-118
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• 2013

Fashion icons of 21st century are not only the fashion leaders that show fashion trend but also the typical fashion signs or symbols that show visually changes in sensibility trends. The purpose of this study was to analyze the framework of 21st century fashion by the public to recognize through these changes. In this study, the background of the occurrence of various 21st century fashion icons and their characteristics were investigated and the changes of revealed features and symbolic meanings were examined compared with them of 20th century. The 24 celebrities which have been called as the bests of fashion icons since year 2000 were selected by searching the most popular search engines such as daum, yahoo and google, and 13 of them were picked as the highest in preference and awareness by surveying 50 students majoring in fashion. And then their fashion styles, backgrounds, and influence on the public fashion were studied. As a result, the 21st century fashion icons reflecting the cultural characteristics such as convergence and exaggeration and the sensitivities of fusion, collaboration, hybrid sensibility in art were powerful enough to create innovative styles destroying the era and the standard. Their styles have constantly created new looks. The exposed new individual sensitivities on media-fusion of two or more sensibility and coordination techniques without being tied to the existing anchorage system-were as influential as high fashion and leaded the imitation and reproduction by dazzling the public. As the media become more powerful, the influence of fashion icons interacted more closely with the public and has been evolved through the sensitivity of the reversal, cultural, economic, visual, or temporal fusions. To sum up, it is shown that the outstanding fashion styles suggested by the leading fashion designers have approach to the public more closely by the fashion icons.

• Journal of IKEEE
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• v.9 no.2 s.17
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• pp.170-178
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• 2005

The video data corrupted by the transmission error due to packet loss induce error propagation in decoded video data, and cause poor video quality. To remedy these corrupted video data, there have been introduced two types of error concealment techniques: spatial or temporal error concealment algorithm. Computational overhead by using spatial error concealment algorithm is a serious disadvantage in mobile video data streaming environment. In this paper, we propose hybrid type error concealment technique recovering video quality of mobile device using MPEG-4 video streaming on error-prone wireless network. Our algorithm is implemented in MPEG-4 decoder. The algorithm adopts Intel Wireless MMX technology to provide high performance of portable embedded multimedia mobile device. It is proven that the proposed algorithm shows expected performance for a mobile streaming system(PDA) on IP channels. Our approach showed better processing speed and better video quality comparing with traditional error concealment algorithm.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1
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• pp.17-23
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• 2004

The mobile radio channel can be simulated as a complex-valued random process with narrow-band spectrum. This paper describes a real-time implementation of that process using a INS320C6414 digital signal processor and XC2VP30 Virtex FPGA. The simulator presented here is not only a comprehensive model of the flat fading but also frequency selective fading mobile channel conditions. To replicate the statistical characteristics of the multipath fading environment with the minimum computational burden, multi-rate techniques are employed to resolve practical problems such as variable sampling rate. The simulator produces accurate and consistent results due to digital implementation. It is very flexible and simple to program for various field conditions in mobile communications with a graphical user interface.

• Advances in aircraft and spacecraft science
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• v.5 no.1
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• pp.1-19
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• 2018

The present work shows many aspects concerning the use of a numerical wave-based methodology for the computation of the structural response of periodic structures, focusing on cylinders. Taking into account the periodicity of the system, the Bloch-Floquet theorem can be applied leading to an eigenvalue problem, whose solutions are the waves propagation constants and wavemodes of the periodic structure. Two different approaches are presented, instead, for computing the forced response of stiffened structures. The first one, dealing with a Wave Finite Element (WFE) methodology, proved to drastically reduce the problem size in terms of degrees of freedom, with respect to more mature techniques such as the classic FEM. The other approach presented enables the use of the previous technique even when the whole structure can not be considered as periodic. This is the case when two waveguides are connected through one or more joints and/or different waveguides are connected each other. Any approach presented can deal with deterministic excitations and responses in any point. The results show a good agreement with FEM full models. The drastic reduction of DoF (degrees of freedom) is evident, even more when the number of repetitive substructures is high and the substructures itself is modelled in order to get the lowest number of DoF at the boundaries.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1664-1673
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• 2016

Lithium rechargeable cells are used in many industrial applications, because they have high energy density and high power density. For an effective use of these lithium cells, it is essential to build a reliable battery management system (BMS). Therefore, the state of charge (SOC) estimation is one of the most important techniques used in the BMS. An appropriate modeling of the battery characteristics and an accurate algorithm to correct the modeling errors in accordance with the simplified model are required for practical SOC estimation. In order to implement these issues, this approach presents the comparative analysis of the SOC estimation performance using equivalent electrical circuit modeling (EECM) and noise suppression technique (NST) in three representative $LiCoO_2/LiFePO_4/LiNiMnCoO_2$ cells extensively applied in electric vehicles (EVs), hybrid electric vehicles (HEVs) and energy storage system (ESS) applications. Depending on the difference between some EECMs according to the number of RC-ladders and NST, the SOC estimation performances based on the extended Kalman filter (EKF) algorithm are compared. Additionally, in order to increase the accuracy of the EECM of the $LiFePO_4$ cell, a minor loop trajectory for proper OCV parameterization is applied to the SOC estimation for the comparison of the performances among the compared to SOC estimation performance.

• Journal of Power Electronics
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• v.17 no.2
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• pp.476-489
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• 2017

Under partial shading conditions (PSCs), multiple maximums may be exhibited on the P-U curve of string inverter photovoltaic (PV) systems. Under such conditions, heuristic methods are invalid for extracting a global maximum power point (GMPP); intelligent algorithms are time-consuming; and model-based methods are complex and costly. To overcome these shortcomings, a novel hybrid MPPT (MPF-IP&O) based on a model-based peak forecasting (MPF) method and an improved perturbation and observation (IP&O) method is proposed. The MPF considers the influence of temperature and does not require solar radiation measurements. In addition, it can forecast all of the peak values of the PV string without complex computation under PSCs, and it can determine the candidate GMPP after a comparison. Hence, the MPF narrows the searching range tremendously and accelerates the convergence to the GMPP. Additionally, the IP&O with a successive approximation strategy searches for the real GMPP in the neighborhood of the candidate one, which can significantly enhance the tracking efficiency. Finally, simulation and experiment results show that the proposed method has a higher tracking speed and accuracy than the perturbation and observation (P&O) and particle swarm optimization (PSO) methods under PSCs.