• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.681-695
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• 2019

A Transient Storage Model (TSM) is one of the most widely used model accounting for complex solute transport in natural river to understanding natural river properties with four TSM key parameters. The TSM parameters are estimated via inverse modeling. Parameter estimation of the TSM is carried out by solving optimization problem about finding best fitted simulation curve with measured curve obtained from tracer test. Several studies have reported uncertainty in parameter estimation from non-convexity of the problem. In this study, we assessed best combination of optimization method and objective function for TSM parameter estimation using Cheong-mi Creek tracer test data. In order to find best optimization setting guaranteeing convergence and speed, Evolutionary Algorithm (EA) based global optimization methods, such as CCE of SCE-UA and MCCE of SP-UCI, and error based objective functions were compared, using Shuffled Complex-Self Adaptive Hybrid EvoLution (SC-SAHEL). Overall results showed that multi-EA SC-SAHEL with Percent Mean Squared Error (PMSE) objective function is the best optimization setting which is fastest and stable method in convergence.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.733-736
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• 2009

Power Line Communication(PLC) is need not additional communication line. So establishment expense is inexpensive and application is simple. Therefore, lower part network of various application field is possible. However, there are high subordinate interference and noise problem on limited transmission data and communication interference element. Wireless Sensor Network(WSN) is need not infrastructure, Self-regulating network architecture of sensor nodes is possible. So at short time, network construction is available. But, power consumption is increased by active sensing for QoS elevation and unnecessary information transmission, low electric power design and necessity of improve protocol are refered to life shortening problem and is studied. In this paper, supplement problem of power line communication and wireless sensor network mutually and because advantage becomes linkage integration control system using synergy effect of two technologies as more restriction be and tries to approach structurally control network that is improved for smooth network environment construction. Honeywell's hybrid sensor network does comparative analysis(benchmarking). Confirm performance elevation proposing teaming of power line communication and wireless sensor network. Through simulation, service delay decreases and confirms that performance elevation.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.671-679
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• 2008

The effect of Pre-cooled Turbojet Engine installation and nozzle exhaust jet on Hypersonic Turbojet EXperimental aircraft(HYTEX aircraft) were investigated by three-dimensional numerical analyses to obtain aerodynamic characteristics of the aircraft during its in-flight condition. First, simulations of wind tunnel experiment using small scale model of the aircraft with and without the rectangular duct reproducing engine was performed at M=5.1 condition in order to validate the calculation code. Here, good agreements with experimental data were obtained regarding centerline wall pressures on the aircraft and aerodynamic coefficients of forces and moments acting on the aircraft. Next, full scale integrated analysis of the aircraft and the engine were conducted for flight Mach numbers of M=5.0, 4.0, 3.5, 3.0, and 2.0. Increasing the angle of attack $\alpha$ of the aircraft in M=5.0 flight increased the mass flow rate of the air captured at the intake due to pre-compression effect of the nose shockwave, also increasing the thrust obtained at the engine plug nozzle. Sufficient thrust for acceleration were obtained at $\alpha=3$ and 5 degrees. Increase of flight Mach number at $\alpha=0$ degrees resulted in decrease of mass flow rate captured at the engine intake, and thus decrease in thrust at the nozzle. The thrust was sufficient for acceleration at M=3.5 and lower cases. Lift force on the aircraft was increased by the integration of engine on the aircraft for all varying angles of attack or flight Mach numbers. However, the slope of lift increase when increasing flight Mach number showed decrease as flight Mach number reach to M=5.0, due to the separation shockwave at the upper surface of the aircraft. Pitch moment of the aircraft was not affected by the installation of the engines for all angles of attack at M=5.0 condition. In low Mach number cases at $\alpha=0$ degrees, installation of the engines increased the pitch moment compared to no engine configuration. Installation of the engines increased the frictional drag on the aircraft, and its percentage to the total drag ranged between 30-50% for varying angle of attack in M=5.0 flight.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.4
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• pp.438-444
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• 2018

Korea has recently selected twenty-two ports for reinforcement breakwater installation of protection facilities, due to rise sea level caused by global warming and increase in the number of typhoon and tsunami. In addition, due to consistent enlargement of ship size, dredging for depth of water for large vessel's berthing and enlargement of berth is under construction. However, no definite construction plan for the reinforcement and lengthening of crown height, which has close relationship with the safe mooring of ships. In this study, domestic and foreign design criteria of crown height were analyzed, and the crown height evaluation index and evaluation method were developed by dividing it into environment and ship elements. In particular, in the case of ship evaluation index, each step was set up in 4 steps according to domestic and foreign regulations, weighted by each step, and the safety level of crown height was evaluated. As a result of the mooring safety simulation of the 100,000 ton cruise ship, the appropriate minimum crown height standard was derived to be 3 m above A.H.H.W. The results of this study are expected to be used as basic data to propose the crown height standard reflecting ship characteristics.

• Journal of the Korean Society for Railway
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• v.11 no.5
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• pp.441-448
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• 2008

Increasing urban sprawl and climate changes have been causing unexpected high-intensity rainfall events. Thus there are needs to enhance conventional disaster management system for comprehensive actions to secure safety. Therefore long-term and comprehensive flood management plans need to be well established. Recently torrential snowfall are occurring frequently, causing have snow traffic jams on the road. To secure safety and on-time operation of the Bi-modal tram system, well-structured disaster management system capable of analyzing the show pack melt/freezing due to unexpected snowfall are needed. To secure safety of the Bi-modal tram system due to torrential snow-fall, the snow melt simulation capability was investigated. The snow accumulation and snow melt were measured to validate the SWMM snow melt component. It showed that there was a good agreement between measured snow melt data and the simulated ones. Therefore, the Bi-modal tram disaster management system will be able to predict snow melt reasonably well to secure safety of the Bi-modal tram system during the winter. The Bi-modal tram disaster management system can be used to identify top priority area for know removal within the tram route in case of torrential snowfall to secure on-time operation of the tram. Also it can be used for detour route in the tram networks based on the disaster management system prediction.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.39-49
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• 2013

In this paper, security mechanism of internal network(CAN) of vehicle is a very incomplete state and the possibility of external threats as a way to build a test environment that you can easily buy from the market by the vehicle's ECU(Electric Control Unit) to verify and obtain a CAN message. Then, by applying it to ECU of the real car to try to attack is proposed. A recent study, Anyone can see plain-text status of the CAN message in the vehicle. so that in order to verify the information is vulnerable to attack from outside, analyze the data in a vehicle has had a successful attack, but attack to reverse engineering in the stationary state and buying a car should attempt has disadvantages that spatial, financial, and time costs occurs. Found through the car's ECU CAN message is applied to a real car for Potential threats outside of the car to perform an experiment to verify and equipped with a wireless network environment, the experimental results, proposed method through in the car to make sure the attack is possible. As a result, reduce the costs incurred in previous studies and in the information absence state of the car, potential of vehicle's ECU attack looks.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.29-35
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• 2020

In this paper, we propose a new structured entity recognition DeNERT model. Recently, the field of natural language processing has been actively researched using pre-trained language representation models with a large amount of corpus. In particular, the named entity recognition, which is one of the fields of natural language processing, uses a supervised learning method, which requires a large amount of training dataset and computation. Reinforcement learning is a method that learns through trial and error experience without initial data and is closer to the process of human learning than other machine learning methodologies and is not much applied to the field of natural language processing yet. It is often used in simulation environments such as Atari games and AlphaGo. BERT is a general-purpose language model developed by Google that is pre-trained on large corpus and computational quantities. Recently, it is a language model that shows high performance in the field of natural language processing research and shows high accuracy in many downstream tasks of natural language processing. In this paper, we propose a new named entity recognition DeNERT model using two deep learning models, DQN and BERT. The proposed model is trained by creating a learning environment of reinforcement learning model based on language expression which is the advantage of the general language model. The DeNERT model trained in this way is a faster inference time and higher performance model with a small amount of training dataset. Also, we validate the performance of our model's named entity recognition performance through experiments.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.5
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• pp.505-512
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• 2021

A 3D model was developed to calculate the UV intensity of a submerged-type UV disinfection reactor. Numerical experiments were conducted by inputting the design factors of an open channel-type disinfection reactor and a pipe-type disinfection reactor that were installed in an actual sewage treatment plant. The following data were obtained: The average UV intensity of the installed open channel-type reactor and pipe-type reactor was 7.87 mW/cm² and 13.09 mW/cm², respectively; the UV dose reflecting the UV irradiation time and taking into account attenuation effects such as mixing imbalance, lamp aging, temperature, and fouling, was expected to be 21.1 mJ/cm² and 24.8 mJ/cm², respectively, and these values are 5 % and 24 % higher than the target UV dose of 20 mJ/cm², respectively. By using the UV3D model, the optimal lamp position, which maximizes the average UV intensity without changing the size of the disinfection reactor or lamp output power, can be found. In this case, by only adjusting the lamp position, the average UV intensity can be increased by 0.9 % for the open channel-type and 0.5 % for the pipe-type, respectively. A better average UV intensity can be obtained by model simulation. By adjusting the horizontal and vertical ratio of the open channel-type reactor and by moving the lamp position, the average UV intensity can be increased by 7.4 % more than the present case.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.905-922
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• 2021

Cluster analysis is one of unsupervised learning techniques used for discovering clusters when there is no prior knowledge of group membership. K-means, one of the commonly used cluster analysis techniques, may fail when the number of variables becomes large. In such high-dimensional cases, it is common to perform tandem analysis, K-means cluster analysis after reducing the number of variables using dimension reduction methods. However, there is no guarantee that the reduced dimension reveals the cluster structure properly. Principal component analysis may mask the structure of clusters, especially when there are large variances for variables that are not related to cluster structure. To overcome this, techniques that perform dimension reduction and cluster analysis simultaneously have been suggested. This study proposes probabilistic reduced K-means, the transition of reduced K-means (De Soete and Caroll, 1994) into a probabilistic framework. Simulation shows that the proposed method performs better than tandem clustering or clustering without any dimension reduction. When the number of the variables is larger than the number of samples in each cluster, probabilistic reduced K-means show better formation of clusters than non-probabilistic reduced K-means. In the application to a real data set, it revealed similar or better cluster structure compared to other methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.195-205
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• 2021

As Coronavirus disease 2019 (COVID-19) became a pandemic, most nursing departments in Korea implemented online non-face-to-face practices rather than the existing practice method. This study was a qualitative study that analyzed the reflection diaries written by participants to understand what they experienced in the online non-face-to-face adult nursing practice process. The online non-face-to-face adult nursing practice was 90 hours for two credits and nine hours per day for a total of 10 days. This online practice consisted of computer-based simulation practice, computer-based nursing skills practice, video and educational material production, real-time online quiz, online lecture video, and discussion. As a result of analyzing the reflection diary, six categories, 13 subcategories, and 33 codes were derived. The six categories were 'Experience of various situations', 'Experience of new study', 'Fulfillment for the clinical practice', 'Building relations with professors', 'Fear of being a pre-nurse', and 'Ambivalence for the non-face-to-face practice'. These results are significant in that in the post-corona era, adult nursing practice was conducted as a non-face-to-face practice rather than a clinical practice institution, and various educational methods were operated. This study is expected to provide important basic data for the development and operation of non-face-to-face adult nursing practice.