• Journal of Aerospace System Engineering
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• v.16 no.2
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• pp.63-72
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• 2022

As interest in microsatellites increases, research has been actively conducted recently on the performance and use, as well as the orbital design and deployment techniques, for the microsatellite constellations. The purpose of this study was to investigate orbital deployment techniques using thrust and differential atmospheric drag control (DADC) for the Walker-delta constellation. When using thrust, the time and thrust required for orbital deployment vary, depending on the separation speed and direction of the satellite with respect to the launch vehicle. A control strategy to complete the orbital deployment with limited performance of the propulsion system is suggested and it was analyzed. As a result, the relationship between the deployment period and the total thrust consumption was derived. It takes a relatively longer deployment time using differential air drag rather than consuming thrusts. It was verified that the satellites can be deployed only with differential air drag at a general orbit of a microsatellite constellation. The conclusion of this study suggests that the deployment strategy in this paper can be used for the microsatellite constellation.

• Composites Research
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• v.35 no.5
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• pp.347-358
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• 2022

Carbon fiber is an excellent structural material, which has been proven in many industries, and the shipbuilding industry is no exception. In particular, in advanced maritime countries, special ships of the Navy and Coast Guard with carbon fiber composite hulls have already been deployed. In Korea, carbon fiber composite materials have been applied to a 10-ton class leisure craft or a 30-ton class patrol, but no research has been done on a hundred of tons or more vessels. In this study, the feasibility study of a 500-ton patrol vessel with a carbon fiber composite hull was conducted through an analysis of similar cases abroad. As a result, it was recognized that the developed hull can be reduced in weight by about 21% to 25% compared to the existing aluminum or FRP hull. It was also confirmed that this light-weight effect can induce the improvement of the maximum speed and the improvement of the operating range via simulations.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.4
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• pp.215-226
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• 2022

Significant efforts have been devoted to developing high-performance composite materials by emulating the structure of biological creatures with superior mechanical characteristics. Nacre has been one of the most sought-after natural structures due to its exceptional fracture toughness compared with the constituent materials. However, the effect of manipulating the nacre-like geometry on the impact performance has not been fully investigated thus far. In this study, composites of randomly manipulated nacreous geometry are numerically developed and the impact performance is analyzed. We develop an algorithm by which the planar area of platelets in the nacre-like design is randomly resized. Thereafter, the numerical models of nonuniform nacre-patterned multi-layer structures are developed and the drop-weight impact simulation is performed. The impact behaviors of the model are evaluated by using the ratio of absorbed energy, the von Mises stress distribution, and the impact force-time curve. Therefore, the effect of the geometric irregularity on the nacre-patterned design is elucidated. This insight can be efficiently utilized in establishing the optimum design of the nacre-patterned structure.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.449-456
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• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.331-338
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• 2022

Successor representation (SR) is a model of human reinforcement learning (RL) mimicking the underlying mechanism of hippocampal cells constructing cognitive maps. SR utilizes these learned features to adaptively respond to the frequent reward changes. In this paper, we evaluated the performance of SR under the context where changes in latent variables of environments trigger the reward structure changes. For a benchmark test, we adopted SR-Dyna, an integration of SR into goal-driven Dyna RL algorithm in the 2-stage Markov Decision Task (MDT) in which we can intentionally manipulate the latent variables - state transition uncertainty and goal-condition. To precisely investigate the characteristics of SR, we conducted the experiments while controlling each latent variable that affects the changes in reward structure. Evaluation results showed that SR-Dyna could learn to respond to the reward changes in relation to the changes in latent variables, but could not learn rapidly in that situation. This brings about the necessity to build more robust RL models that can rapidly learn to respond to the frequent changes in the environment in which latent variables and reward structure change at the same time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.189-196
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• 2023

As the manufacturing paradigm shifts, various collaborative robots are creating new markets. Demand for collaborative robots is increasing in all industries for the purpose of easy operation, productivity improvement, and replacement of manpower who do simple tasks compared to existing industrial robots. However, accidents frequently occur during work caused by collaborative robots in industrial sites, threatening the safety of workers. In order to construct an industrial site through robots in a human-centered environment, the safety of workers must be guaranteed, and there is a need to develop a collaborative robot guard system that provides reliable communication without the possibility of dispatch. It is necessary to double prevent accidents that occur within the working radius of cobots and reduce the risk of safety accidents through sensors and computer vision. We build a system based on OPC UA, an international protocol for communication with various industrial equipment, and propose a collaborative robot guard system through image analysis using ultrasonic sensors and CNN (Convolution Neural Network). The proposed system evaluates the possibility of robot control in an unsafe situation for a worker.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.41-49
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• 2009

Flash memory has become increasingly requestion for the importance and the demand as a storage due to its low power consumption, cheap prices and large capacity medium. This research is to design a high performance flash memory structure for the substitution of a hard-disk by dynamic prefetching of aggressive spatial locality from the spatial smart buffer system. The proposed buffer system in a NAND flash memory consists of three parts, i.e., a fully associative victim buffer for temporal locality, a fully associative spatial buffer for spatial locality, and a dynamic fetching unit. We proposed new dynamic prefetching algorithm for aggressive spatial locality. That is to use the flash memory instead of the hard disk, the proposed flash system can achieve better performance gain by overcoming many drawbacks of the flash memory by the new structure and the new algorithm. According to the simulation results, compared with the smart buffer system, the average miss ratio is reduced about 26% for Mediabench applications. The average memory access times are improved about 35% for Mediabench applications, over 30% for Spec2000 applications.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.240-257
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• 2022

Autonomous vehicles use various local sensors such as camera, radar, and lidar to perceive the surrounding environment. However, it is difficult to predict the movement of vulnerable road users using only local sensors that are subject to limits in cognitive range. This is true especially when these users are blocked from view by obstacles. Hence, this paper developed an algorithm for collision avoidance with VRU using V2X information. The main purpose of this collision avoidance system is to overcome the limitations of the local sensors. The algorithm first evaluates the risk of collision, based on the current driving condition and the V2X information of the VRU. Subsequently, the algorithm takes one of four evasive actions; steering, braking, steering after braking, and braking after steering. A simulation was performed under various conditions. The results of the simulation confirmed that the algorithm could significantly improve the performance of the collision avoidance system while securing vehicle stability during evasive maneuvers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.799-808
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• 2008

The analysis of vehicular loads reflecting the domestic traffic circumstances is necessary for the development of adequate design live load models in the analysis and design of cable-supported bridges or the development of fatigue load models to predict the remaining lifespan of the bridges. This study intends to develop an ANN(artificial neural network)-based Bridge WIM system and Influence line-based Bridge WIM system for obtaining information concerning the loads conditions of vehicles crossing bridge structures by exploiting the signals measured by strain gauges installed at the bottom surface of the bridge superstructure. This study relies on experimental data corresponding to the travelling of hundreds of random vehicles rather than on theoretical data generated through numerical simulations to secure data sets for the training and test of the ANN. In addition, data acquired from 3 types of vehicles weighed statically at measurement station and then crossing the bridge repeatedly are also exploited to examine the accuracy of the trained ANN. The results obtained through the proposed ANN-based analysis method, the influence line analysis method considering the local behavior of the bridge are compared for an example cable-stayed bridge. In view of the results related to the cable-stayed bridge, the cross beam ANN analysis method appears to provide more remarkable load analysis results than the cross beam influence line method.

• Membrane Journal
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• v.33 no.6
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• pp.352-361
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• 2023

Steam methane reforming is currently the most widely used technology for producing hydrogen, a clean fuel. Hydrogen produced by steam methane reforming contains impurities such as carbon monoxide, and it is essential to undergo an appropriate post-purification step for commercial usage, such as fuel cells. Recently, membrane separation technology has been gaining great attention as an effective purification method; in this study, we evaluated the feasibility of using commercial polysulfone membranes for biogas upgrading to separate and recover hydrogen from a hydrogen/carbon monoxide gas mixture. Initially, we examined the physicochemical properties of the commercial membrane used. We then conducted performance evaluations of the commercial membrane module under various conditions using mixed gas, considering factors such as stage-cut and operating pressure. Finally, based on the evaluation results, we carried out simulations for process design. The maximum H₂ permeability and H₂/CO separation factor for the commercial membrane process were recorded at 361 GPU and 20.6, respectively. Additionally, the CO removal efficiency reached up to 94%, and the produced hydrogen concentration achieved a maximum of 99.1%.