• Journal of Korean Society for Atmospheric Environment
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• v.34 no.5
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• pp.735-747
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• 2018

Rainfall depth is an important meteorological information. Generally, high spatial resolution rainfall data such as road-level rainfall data are more beneficial. However, it is expensive to set up sufficient Automatic Weather Systems to get the road-level rainfall data. In this paper, we propose to use deep learning to recognize rainfall depth from road surveillance videos. To achieve this goal, we collect a new video dataset and propose a procedure to calculate refined rainfall depth from the original meteorological data. We also propose to utilize the differential frame as well as the optical flow image for better recognition of rainfall depth. Under the Temporal Segment Networks framework, the experimental results show that the combination of the video frame and the differential frame is a superior solution for the rainfall depth recognition. The final model is able to achieve high performance in the single-location low sensitivity classification task and reasonable accuracy in the higher sensitivity classification task for both the single-location and the multi-location case.

• Transactions of Materials Processing
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• v.27 no.2
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• pp.81-86
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• 2018

In the cold forming process, it is not easy to fabricate a asymmetric type nut, due to the difficulty in the exact prediction of metal-flow. As we have identified, in that case, it often results in the various forging defects such as burrs, and an incomplete shape, as well as other problems because of this issue. In the current study, we introduce the development of an unparalleled shape Weld Nut by using a forging analysis tool (AFDEX). For the multi-forming machine, the optimized shapes of each intermediate product (step product) could be found by the use of a model for the prediction and analysis of various types, sizes and heights. Chiefly, forging tools were prepared based on the simulation results and an unparalleled shape could be prepared at one time without any burrs, incomplete shape and size.

• Journal of Korean Society of Water and Wastewater
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• v.21 no.5
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• pp.609-619
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• 2007

The objective of this paper is to evaluate the feasibility of conjunctive Operation between Multi-regional water supply networks from multiple source as a effective way to meet two conditions: to minimize the electric cost for providing water demanded and meet the water flow rate for satisfying customers. EPAnet Model is used to calculate a hydraulic water distribution condition based on an integrated operation of water supply systems located in short distance. The modeling was conducted on several simulation cases including the individual operation by existing inter-regional water supply networks within short distance, the conjunctive operation of more than two existing networks with valve fully closed and full open constraint. As a study distribution system, water supplying systems of the Geojae-city in the Geongsang Namdo Province was selected and investigated. It was found that a well-allocated water supply scheme based on a conjunctive operation promises to save the electric cost and satisfy all operational goals such as stability and revenues during the period. The result such as unit district costs, pareto optimum pump combination sets will be applied to the optimization for a conjunctive operation of existing inter-regional water supply networks within short distance.

• Wind and Structures
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• v.21 no.2
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• pp.119-158
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• 2015

The characteristics of the coherence functions of X axial, Y axial, and RZ axial (i.e., body axis) wind forces on the Shanghai World Trade Centre - a 492 m super-tall building with section varying along height are studied via a synchronous multi-pressure measurement of the rigid model in wind tunnel simulating of the turbulent, and the corresponding mathematical expressions are proposed there from. The investigations show that the mathematical expressions of coherence functions in across-wind and torsional-wind directions can be constructed by superimposition of a modified exponential decay function and a peak function caused by turbulent flow and vortex shedding respectively, while that in along-wind direction need only be constructed by the former, similar to that of wind speed. Moreover, an inductive analysis method is proposed to summarize the fitted parameters of the wind force coherence functions of every two measurement levels of altitudes. The comparisons of the first three order generalized force spectra show that the proposed mathematical expressions accord with the experimental results well. Later, the influences of coherence functions on wind-induced dynamic responses are analyzed in detail based on the proposed mathematical expressions and the frequency-domain method of random vibration theory.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.41.1-41.1
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• 2016

The Galactic center, Sagittarius A* (Sgr A*), is the closest supermassive black hole and emits synchrotron radiation. It provides great opportunity to study the origin of mm/sub-mm emission. Currently, two competing models have been suggested as a jet base and a radiatively inecient accretion flow (RIAF). To unveil the properties, the extremely high resolution(${\sim}10{\mu}as$) corresponding to the projected Schwarzschild radius of ~0.1AU is necessary. With KVN, a jet model can be tested by multi- frequency simultaneous observations because the optically thick surface in a jet (i.e. radio core) moves toward the center at a higher frequency. We conducted 8 observations with KVN at 43/86GHz in 2015, and found that the measured positional shift to the reference calibrator, J1744-3116, was ~0.3 mas to the south of Sgr A* using the source frequency phase referencing (SFPR) at Q/W bands for the first time. With the result, in the future, we will attempt to measure the variation of source position shifts that can constrain the direction of approaching jets and the variability of black hole activity of Sgr A*.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.44-58
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• 2017

The purpose of this study is to prove the Korean Internet company, Kakao's resilience capacity. For it, this paper reviews the previous literatures regarding Kakao's business models and discusses 'resilience' theory. Then, it organizes the research questions based on the theoretical background and explains the research methodology. It investigates the case of Kakao's business and organization. The case analysis shows that five levers of resilience are a good indicator for a successful platform business evolution. The five levers are composed of coordination, cooperation, clout, capability, and connection: First lever, coordination that makes the company to restructure its silo governance in order to respond to actual business flow starting from the basic asset like game and music content; second lever, cooperation where the firm provides creative people with playground for startups such as KakaoPage; third lever, clout where the company shares its data by opening its API of AI and chatbot to $3^{rd}$ party developers; fourth lever, capability where the firm establishes AI R&D center, KakaoBrain as the function of multi-domain generalist for developing diverse platforms tackling customer needs; and the last fifth lever, connection where the firm continues to expand its platform business to the peripheries, O2O businesses such as KakaoTaxi, KakaoOrder, KakaoPay, and KakaoBank. In conclusion, this study proposes Internet companies to be a resilient platform utilizing those five levers of resilience in order to form successful platform. This study contributes to the agile innovation of Internet platform with ecological sense.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.3
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• pp.405-412
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• 2017

In the present study, two phase flows around a projectile vertically launched from an underwater platform have been numerically investigated by using a three dimensional multi-phase RANS flow solver based on pseudo-compressibility and a homogeneous mixture model on unstructured meshes. The relative motion between the platform and projectile was described by six degrees of freedom(6DOF) equations of motion with Euler angles and a chimera technique. The propulsive power of the projectile was modeled as the fluid force acting on the lower surface of the body by the compressed air emitted from the platform. Qualitative analysis was conducted for the time history of vapor volume fraction distributions. Uncorking pressure around the projectile and platform was analyzed to predict impact force acting on the surfaces. The results of 6DOF analysis presented similar tendency with the surficial pressure distributions.

• Nuclear Engineering and Technology
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• v.48 no.4
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• pp.1022-1035
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• 2016

A double-tube once-through steam generator (DOTSG) consisting of an outer straight tube and an inner helical tube is studied in this work. First, the structure of the DOTSG is optimized by considering two different objective functions. The tube length and the total pressure drop are considered as the first and second objective functions, respectively. Because the DOTSG is divided into the subcooled, boiling, and superheated sections according to the different secondary fluid states, the pitches in the three sections are defined as the optimization variables. A multi-objective optimization model is established and solved by particle swarm optimization. The optimization pitch is small in the subcooled region and superheated region, and large in the boiling region. Considering the availability of the optimum structure at power levels below 100% full power, we propose a new operating scheme that can fix the boundaries between the three heat-transfer sections. The operation scheme is proposed on the basis of data for full power, and the operation parameters are calculated at low power level. The primary inlet and outlet temperatures, as well as flow rate and secondary outlet temperature are changed according to the operation procedure.

• 전자공학회논문지 IE
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• v.48 no.2
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• pp.19-25
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• 2011

This paper presented neural network modeling method using vehicle data to predict fuel consumption. To acquire data for training and testing the proposed neural network, medium-class gasoline vehicle drove at downtown and parameters measured include speed, engine rpm, throttle position sensor (TPS), and mass air flow (MAF) as input data, and fuel consumption as target data from OBD-II port. Multi layer perception network was used for nonlinear mapping between the input and the output data. It was observed that the neural network model can predict the vehicle quite well with mean squared error was $1.306{\times}10^{-6}$ for the fuel consumption.

• Journal of the Korean Society of Propulsion Engineers
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• v.19 no.2
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• pp.29-37
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• 2015

This paper presents a numerical investigation on detonation of a kerosene-air mixture in the copper tube and the structural response associated with combustion instability in liquid rocket engine. A single step Arrehnius rate law and Johnson-Cook strength model are used to describe the chemical reaction of kerosene-air mixture detonation and the plastic deformation of the copper tube. The changes of flow field and tube stress which are induced by plastic deformation, are investigated on the different tube thicknesses and nozzle configurations.