• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.4
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• pp.120-127
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• 2013

Hybrid electric vehicles have applied electric parts for saving fuel consumption and reducing levels of environmental pollution. Electrification of automobiles is indispensable for entering into global market because of enhanced environment restriction. ISG (Integrated Starter & Generator) system is one of main electric parts and can improve fuel efficiency more than other components by using Idle Stop & Go function and regenerative braking system. However, if ISG motor and inverter work under the continuously high load condition, it will make them the decrease of performance and durability. So the ISG motor and inverter need to properly design the cooling system of them. In this study, we suggested the enhancement points by modifying the thermal design of ISG motor and then confirmed the improvement of the cooling performance.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.780-787
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• 2017

The propellant grain configuration is a design variable that determines the shape and performance of a solid rocket motor. Grain configuration variables have complicated effects on the motor performance; so the global optimization problem has to be solved in order to design the configuration variables. The grain performance has been analyzed by means of the grain burn-back and internal ballistic analysis, and the optimization technique searches for the configuration variables that satisfy the requirements. The deterministic and stochastic optimization techniques have been applied for the grain optimization, but the results are imperfect. In this study, the optimization design of the configuration variables has been performed using the hybrid optimization technique, which combines those two techniques. As a result, the hybrid optimization technique has proved to be efficient for the grain optimization design.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.393-396
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• 2005

Due to the fast growing rate of the global container trade, every major port is under the pressure of meeting the projected capacity demand. As a result, alternative solutions have been sought for improving capacity and meeting the growing demand for container storage area and terminal capacity. Moreover, material handling process re-engineering is now a critical issue for logistics and supply chain managers of airline, shipping lines, terminal and warehousing enterprises around the world. Therefore, the purpose of this paper is to develop the 3D simulator for executing performance valuation of port transportation systems. The developed 3D simulator system is to measure the effectiveness of the proposed total system and compare it with existing practices. The performance analysis variables are also defined for these comparisons

• Journal of Positioning, Navigation, and Timing
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• v.9 no.1
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• pp.7-13
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• 2020

As a countermeasure against the threat of jamming which can disrupt operation of the Global Positioning System (GPS) receivers, various kinds of technique to estimate the Direction-Of-Arrivals (DOAs) of incoming jamming signals have been widely studied, and among them, the MUltiple SIgnal Classification (MUSIC) algorithm is known to provide very high resolution. However, since the previous studies regarding the MUSIC algorithm does not consider the orientation of each antenna element of antenna arrays, there is a possibility that DOA estimation performance degrades in the case of a misaligned antenna array whose antenna elements are not oriented along the same direction. As an effort to solve this problem, there exists a previous work which presents an MUSIC-based method for DOA estimation. However, the error between the real and measured values of each antenna orientation is not taken into consideration. Therefore, in this paper, the effect of the aforementioned error on the DOA estimation performance in the case of a misaligned antenna array is analyzed by simulations.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.241-246
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• 2009

Advances in mobile and wireless networking technologies have enabled mobile ad hoc networks applicable to a wide range of areas. Many cases of even such ad hoc networks demand to be accessible to the global network. Owing to be diversified in features depending on applications, however, some those networks may consist of devices or nodes which do not facilitate all the same transport protocols. This results in unreachable situations of establishing ad hoc network: such as non-existence of all required access points, faults or contention in a path of particular protocol communication. Interworking between different transport protocols can alleviate such problems. This paper proposes an interworking scheme to improve data transport performance and network accessibility, especially in such a mobile ad hoc network that is applicable to data communications among ships or user's convenient u-health services. Modeling and simulation analysis are used to verify the improvement.

• Journal of Communications and Networks
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• v.5 no.3
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• pp.202-214
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• 2003

The central challenge in the design of ad-hoc networks is the development of dynamic routing protocol that efficiently finds route between mobile nodes. Several routing protocols such as DSR, AODV and DSDV have been proposed in the literature to facilitate communication in such dynamically changing network topology. In this paper, a Node Transition Probability (NTP) based routing algorithm, which determines stable routes using the received power from all other neighboring nodes is proposed. NTP based routing algorithm is designed and implemented using Global Mobile Simulator (GloMoSim), a scalable network simulator. The performance of this routing algorithm is studied for various mobility models and throughput, control overhead, average end-to-end delay, and percentage of packet dropped are compared with the existing routing protocols. This algorithm shows acceptable performance under all mobility conditions. The results show that this algorithm maximizes the bandwidth utilization during heavy traffic with lesser overhead.

• KCI Concrete Journal
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• v.12 no.1
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• pp.35-46
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• 2000

A research program was initiated at the University of Colorado at Boulder to develop computational models that can be used for seismic risk assessments. To assess the overall performance of bridge structures including the nonlinear effects of bridge piers, the research focused on two levels of capabilities, i.e. global and local pier levels. A 3-D concrete model was used to evaluate the behavior of individual piers under combined axial, bending, and shear loadings using 3-D finite element analysis. Whereby the response curve reached the peak strength of the R/C column under the constant axial and monotonically increasing lateral loads. Experimental results on reinforced concrete bridge piers, which were obtained at the University of California at San Diego were used to validate the seismic performance of bridge piers at the two levels, globa1 and local.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.291-291
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• 2002

DGPS(Differential Global Positioning System) and RTK(RealTime Kinematic) is in one of today's most widely used surveying techniques. But It's use is restricted by the distance between reference station and rover station and it is difficult to process data in realtime by it's own orgnizational limitation in precise measurement of positioning. To meet these new demands, In This paper, new DGPS and RTK correction data services through Internet and PSTN(Public Switched Telephony Network) have been proposed. For this purpose, we implemented performance a DGPS and RTK error correction data transmission system for long-distance using the internet and PSTN network which allows a mobile user to increase the distance at which the rover receiver is located from the reference in realtime. and we analyzed and compared DGPS and RTK performance by experiments through the Internet and PSTN network with the distance and the time.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.128-132
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• 2023

Recently, with the development of deep learning technology, research on pedestrian attribute recognition technology using deep neural networks has been actively conducted. Existing pedestrian attribute recognition techniques can be obtained in such a way as global-based, regional-area-based, visual attention-based, sequential prediction-based, and newly designed loss function-based, depending on how pedestrian attributes are detected. It is known that the performance of these pedestrian attribute recognition technologies varies greatly depending on the type of backbone network that constitutes the deep neural networks model. Therefore, in this paper, several backbone networks are applied to the baseline pedestrian attribute recognition model and the performance changes of the model are analyzed. In this paper, the analysis is conducted using Resnet34, Resnet50, Resnet101, Swin-tiny, and Swinv2-tiny, which are representative backbone networks used in the fields of image classification, object detection, etc. Furthermore, this paper analyzes the change in time complexity when inferencing each backbone network using a CPU and a GPU.

• Atmosphere
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• v.26 no.1
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• pp.1-18
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• 2016

Eleven Tropical Cyclone (TC) intensity guidance models in the western North Pacific have been validated over 2008~2014 based on various analysis methods according to the lead time of forecast, year, month, intensity, rapid intensity change, track, and geographical area with an additional focus on TCs that influenced the Korean peninsula. From the evaluation using mean absolute error and correlation coefficients for maximum wind speed forecasts up to 72 h, we found that the Hurricane Weather Research and Forecasting model (HWRF) outperforms all others overall although the Global Forecast System (GFS), the Typhoon Ensemble Prediction System of Japan Meteorological Agency (TEPS), and the Korean version of Weather and Weather Research and Forecasting model (KWRF) also shows a good performance in some lead times of forecast. In particular, HWRF shows the highest performance in predicting the intensity of strong TCs above Category 3, which may be attributed to its highest spatial resolution (~3 km). The Navy Operational Global Prediction Model (NOGAPS) and GFS were the most improved model during 2008~2014. For initial intensity error, two Japanese models, Japan Meteorological Agency Global Spectral Model (JGSM) and TEPS, had the smallest error. In track forecast, the European Centre for Medium-Range Weather Forecasts (ECMWF) and recent GFS model outperformed others. The present results has significant implications for providing basic information for operational forecasters as well as developing ensemble or consensus prediction systems.