• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.4
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• pp.97-107
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• 2017

This study is to determine the coefficients of regression equations and to select the optimal regression equation in the LOADEST model after classifying the whole study period into 5 flow conditions for 16 watersheds located in the Nakdonggang waterbody. The optimized coefficients of regression equations were derived using the gradient descent method as a learning method in Tensorflow which is the engine of machine-learning method. In South Korea, the variability of streamflow is relatively high, and rainfall is concentrated in summer that can significantly affect the characteristic analysis of pollutant loads. Thus, unlike the previous application of the LOADEST model (adjusting whole study period), the study period was classified into 5 flow conditions to estimate the optimized coefficients and regression equations in the LOADEST model. As shown in the results, the equation #9 which has 7 coefficients related to flow and seasonal characteristics was selected for each flow condition in the study watersheds. When compared the simulated load (SS) to observed load, the simulation showed a similar pattern to the observation for the high flow condition due to the flow parameters related to precipitation directly. On the other hand, although the simulated load showed a similar pattern to observation in several watersheds, most of study watersheds showed large differences for the low flow conditions. This is because the pollutant load during low flow conditions might be significantly affected by baseflow or point-source pollutant load. Thus, based on the results of this study, it can be found that to estimate the continuous pollutant load properly the regression equations need to be determined with proper coefficients based on various flow conditions in watersheds. Furthermore, the machine-learning method can be useful to estimate the coefficients of regression equations in the LOADEST model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.12
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• pp.1537-1542
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• 2011

This paper presents the power management strategies for a compound hybrid excavator. The compound hybrid excavator has been replaced the hydraulic swing motor to the electric swing motor. This excavator requires a proper control algorithm to regulate the energy flow between the mechanical coupling and the electric devices. The controller should improve fuel economy and maintain the super capacitor voltage within a proper range. A thermostat controller and ECMS controller are designed such that these objectives can be achieved. The thermostat controller regulates the power of the engine-assist motor on the basis of the super capacitor voltage, and the ECMS controller determines it using the real-time fuel minimization strategy based on the concept of equivalent fuel. Simulation results showed that by using the hybrid excavator, the fuel economy becomes about 20% higher than that obtained using the conventional excavator and that the ECMS controller outperforms the thermostat controller.

• Journal of Sensor Science and Technology
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• v.9 no.1
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• pp.1-8
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• 2000

One of today's very critical and sensitive accurate accelerometer which can be used higher temperature than $200^{\circ}C$ and corrosive environment, is particularly demanded for automotive engine. Because silicon is a material of large temperature dependent coefficient, and the piezoresistors are isolated with p-n junctions, and its leakage current increase with temperature, the performance of the silicon accelerometer degrades especially after $150^{\circ}C$. In this paper, The temperature characteristic of a accelerometer using silicon on insulator (SOI) structure is studied theoretically, and compared with experimental results. The temperature coefficients of sensitivity and offset voltage (TCS and TCO) are related to some factors such as thermal residual stress, and are expressed numerically. Thermal stress analysis of the accelerometer has also been carried out with the finite-element method(FEM) simulation program ANSYS. TCS of this accelerometer can be reduced to control the impurity concentration of piezoresistors, and TCO is related to factors such as process variation and thermal residual stress on the piezoresistors. In real packaging, The avarage thermal residual stress in the center support structure was estimated at around $3.7{\times}10^4Nm^{-2}^{\circ}C^{-1}$ at sensing resistor. The simulated ${\gamma}_{pT}$ of the center support structure was smaller than one-tenth as compared with that of the surrounding support structure.

• Spatial Information Research
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• v.18 no.2
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• pp.25-34
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• 2010

This study simulated flood inundation each frequency rainfall using GIS spatial information and FLUMEN model for part of Muju-Namdae Stream. To create geomorphology for the analysis of flood inundation, Triangle Irregular Network(TIN) was constructed using GIS spatial interpolation method based on digital topographic map and river profile data, unique data source to represent real topography of the river areas. And also flood inundation was operated according to the levee collapse to consider extremely flood damage scenarios. As the analysis of result, the inundation area in the left levee collapse showed more high as 3.13, 3.69, and 4.17 times comparing with one of right levee for 50, 100, and 200 year frequency rainfall and showed 1.00, 2.15, and 3.34 times comparing with one of right levee in the inundation depth with over 1.0 meter, which can cause casualties. As the analysis of inundation area of the inundation depth with over 1.0 meter, which can cause casualties in left levee collapse, it increased more high as 263% and 473% when 50 year frequency change into 100 and 200 year frequency. Also As the analysis of inundation area of the inundation depth with over 1.0 meter in right levee collapse, it increased high as 123% and 142% when 50 year frequency change into 100 and 200 year frequency. Especially, the inundation area of the inundation depth with 3.0~3.5m showed more high as 263% and 489% when 50 year frequency change into 100 and 200 year frequency. It is expected that flood inundation map of this paper could be important decision making data to establish land use planning and water treatment measures.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.1
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• pp.31-36
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• 2012

Military vehicles, compared to conventional vehicles, require higher driving performance, quieter operation, and longer driving distances with minimal fuel supplies. The series hybrid electric vehicle can be driven with no noise and has high initial startup performance, because it uses only a traction motor that has a high startup torque to drive the vehicle. Moreover, the fuel economy can be improved if the vehicle is hybridized. In series hybrid electric vehicles, the electric generation system, which consists of an engine and a generator, supplies electric energy to a battery or traction motor depending on the vehicle driving state and battery state of charge (SOC). The control strategy determines the operation of the generation system. Thus, the fuel economy of the series hybrid electric vehicle relies on the control strategy. In this study, thermostat, power-follower, and combined strategies were compared, and a 37% improvement in the fuel economy was implemented using the combined control strategy suggested in this study.

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.523-530
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• 2005

When a PCI 2.2 bus master requests data using Memory Read command, a target device may hold PCI bus without data to be transferred for long time because a target device needs time to prepare data infernally. Because the usage efficiency of the PCI bus and the data transfer efficiency are decreased due to this situation, the PCI specification recommends to use the Delayed Transaction mechanism to improve the system performance. But the mechanism cann't fully improve performance because a target device doesn't know the exact size of prefetched data. In the previous work, we propose a new method called Prefetch Request when a bus master intends to read data from the target device. In this paper, we design PCI 2.2 controller and local device that support the proposed method. The designed PCI 2.2 controller has simple local interface and it is used to convert the PCI protocol into the local protocol. So the typical users, who don't know the PCI protocol, can easily design the PCI target device using the proposed PCI controller. We propose the basic behavioral verification, hardware design verification, and random test verification to verify the designed hardware. We also build the test bench and define assembler instructions. And we propose random testing environment, which consist of reference model, random generator ,and compare engine, to efficiently verify corner case. This verification environment is excellent to find error which is not detected by general test vector. Also, the simulation under the proposed test environment shows that the proposed method has the higher data transfer efficiency than the Delayed Transaction about $9\%$.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.99-107
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• 2016

Korea has been known as volcanic disaster free area. However, recent surveying result shows that Baekdu mountain located in northernmost in the Korean peninsula is not a dormant volcano anymore. When Baekdu mountain is erupting, various damages due to the volcanic ash are expected in South Korea area. Especially, volcanic ash in the air may cause big aviation accident because it can hurt engine or gauges in the airplane. Therefore, it is a crucial issue to interrupt airplane navigation, whose route is overlapped with volcanic ash, after predicting three dimensional dispersion of volcanic ash. In this paper, we deals with 3D visualization techniques for volcanic ash dispersion prediction results. First, we introduce the data acquisition of the volcanic ash dispersion prediction. Dispersion prediction data is obtained from Fall3D model, which is volcanic ash dispersion simulation program. Next, three 3D visualization techniques for volcanic ash dispersion prediction are proposed. Firstly proposed technique is so called 'Cube in the Air', which locates the semitransparent cubes having different color depends on its particle concentration. Second technique is a 'Cube in the Cube' which divide the cube in proportion to particle concentration and locates the small cubes. Last technique is 'Semitransparent Volcanic Ash Plane', which laminates the layer, whose grids present the particle concentration, and apply the semitransparent effect. Based on the proposed techniques, the user could 3D visualize the volcanic ash dispersion prediction results upon his own purposes.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.177-183
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• 2002

Current state-of-the-art of VMS control is based upon simple knowledge-based inference engine with message set and each message's priority. And R&Ds of the VMS control are focused on the accurate detection and estimation of traffic condition of the subject roadways. However VMS display itself cannot achieve a desirable traffic allocation among alternative routes in the network In this context, VMS display strategy is the most crucial part in the VMS control. VMS itself has several limitations in its nature. It is generally known that VMS causes overreaction and concentration problems, which may be more serious in urban network than highway network because diversion should be more easily made in urban network. A feedback control algorithm is proposed in this paper to address the above-mentioned issues. It is generally true that feedback control approach requires low computational effort and is less sensitive to models inaccuracy and disturbance uncertainties. Major features of the proposed algorithm are as follows: Firstly, a regulator is designed to attain system optimal traffic allocation among alternative routes for each VMS in the network. Secondly, strategic messages should be prepared to realize the desirable traffic allocation, that is, output of the above regulator. VMS display strategy module is designed in this context. To evaluate Probable control benefit and to detect logical errors of the Proposed feedback algorithm, a offline simulation test is performed using real network in Daejon, Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.311-316
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• 2017

The network analysis method has emerged as a new methodology for various disciplines, due to its ability to provide a representative knowledge network of references, co-authors and keywords. Bulletproof technology is an interdisciplinary field involving various disciplines, such as material mechanics, structural mechanics, and ballistics, so it is essential to keep up with the recent trends in technological research. In this research, the recent R&D trends in the field of bulletproof materials were analyzed using keyword based network analysis. From the results, the core keywords were identified as 'Composite', 'Model' and 'Head' using the scholar search engine, google scholar. The centrality analysis for the core keywords showed that bulletproof technology has developed in 3 different areas, viz. material, structure and effects. To the best of our knowledge, this is the first application of (network analysis?) to bulletproof technology. Moreover, we are also convinced that the results of this study will be useful for defense technology planning and determining the direction of R&D in the field of bulletproof technology.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.114-123
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• 2016

The effective feature extraction method for unmanned aerial vehicle (UAV) detection is proposed and verified in this paper. The UAV engine sound is harmonic complex tone whose frequency ratio is integer and its variation is continuous in time. Using these characteristic, we propose the feature vector composed of a mean and standard deviation of difference value between fundamental frequency with 1st overtone as well as mean variation of their frequency. It was revealed by simulation that the suggested feature vector has excellent discrimination in target signal identification from various interfering signals including frequency variation with time. By comparing Fisher scores, three features based on frequency show outstanding discrimination of measured UAV signals with low signal to noise ratio (SNR). Detection performance with simulated interference signal is compared by MFCC by using ELM classifier and the suggested feature vector shows 37.6% of performance improvement As the SNR increases with time, the proposed feature can detect the target signal ahead of MFCC that needs 4.5 dB higher signal power to detect the target.