• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.207-215
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• 2016

The demand for spatial data service technologies is increasing lately with the development of realistic 3D spatial information services and ICT (Information and Communication Technology). Research is being conducted on the real-time provision of spatial data services through a variety of mobile and Web-based contents. Big data or cloud computing can be presented as alternatives to the construction of spatial data for the effective use of large volumes of data. In this paper, the process of building HLM (Hyper Live Map) using multi-source data to acquire stereo CCTV and other various data is presented and a big data service architecture design is proposed for the use of flexible and scalable cloud computing to handle big data created by users through such media as social network services and black boxes. The provision of spatial data services in real time using big data and cloud computing will enable us to implement navigation systems, vehicle augmented reality, real-time 3D spatial information, and single picture based positioning above the single GPS level using low-cost image-based position recognition technology in the future. Furthermore, Big Data and Cloud Computing are also used for data collection and provision in U-City and Smart-City environment as well, and the big data service architecture will provide users with information in real time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.244-257
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• 2017

Traffic congestion occurs from drivers' human factors such as driver reaction time, reckless lane change, and inexperienced driving. When Automated Vehicles are introduced, human factors are excluded, resulting in increased average vehicle speed, stabilizing traffic flow, and increasing road capacity. This study analyzed traffic flow changes through traffic volume-speed-density plots, and increased road capacity due to Automated Vehicles. As a result of the analysis, when rate of automated vehicles gests higher, the traffic flow became stable. Additionally, it was analyzed that when all vehicles were automated, the road capacity increased by about 120 %. It is expected that there will be a positive expectation in terms of traffic congestion and traffic demand management due to the introduction of Automated Vehicles.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.1
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• pp.43-56
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• 2013

Personal Rapid Transit(PRT), which is one of the next generation convergence transport technology, PRT system requires operation technology for controlling diverse vehicles and dealing with a variety of abnormal driving situations on a large scale trackway structures in expected operational area more efficiently and reliably. Before developing PRT control technology, it is essential that multiple testing procedures stepwise with building small scale test-tracks and develop real unmanned-vehicles. However, it is expected that the experiments demand huge amount of time and physical cost. Thus, simulation in virtual environment is efficient to develop wireless based control technology for multiple PRT vehicles prior to building real-test environment. In this paper, we propose a VR-based integrated simulator which physics engine is applied so that it enables simulation of front-wheel-steering PRT system rather than simple rail track system. The proposed simulator is also developed that it can reflect geographical features, infrastructures and network topology of expected driving region.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2745-2752
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• 2014

In recent years, Transport Demand Management has been conducted for the efficient management of transport. In ITS applications in particular, the prerequisite is accurate and reliable positioning. However, the major problems are satellite signal outage, and multipath. This paper proposes that outage and multipath measurement can be detected and estimated using elevation angle and signal to noise ratio data association relation in stand-alone GPS. In order to verify the performance of the proposed method, it is then evaluated by the car test. the evaluation test environment has low accuracy and unreliable positioning because of signal outage or multipath such as steep hill and high buildings. In the evaluation test result, 918times abnormal signal occurred and it was confirmed that the proposed method showed more improved 9.48m(RMS) horizontal positioning error than without proposed method.

• Journal of Information Technology Services
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• v.15 no.4
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• pp.97-109
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• 2016

The rapid deployment of millions of mobile sensors and smart devices has resulted in high demand for opportunistic encounter-based networking. For the cooperative video surveillance of dashboard cameras in nearby vehicles, a fast and energy-efficient asynchronous neighbor discovery protocol is indispensable because a dashboard camera is an energy-hungry device after the vehicle's engine has turned off. In the existing asynchronous neighbor discovery protocols, all nodes always try to discover all neighbors. However, a dashboard camera needs to discover nearby dashboard cameras when an event is detected. In this paper, we propose a fast and energy-efficient asynchronous neighbor discovery protocol, which enables nodes : 1) to have different roles in neighbor discovery, 2) to discover neighbors within a search range, and 3) to report promptly the exact discovery result. The proposed protocol has two modes: periodic wake-up mode and active discovery mode. A node begins with the periodic wake-up mode to be discovered by other nodes, switches to the active discovery mode on receiving a neighbor discovery request, and returns to the periodic wake-up mode when the active discovery mode finishes. In the periodic wake-up mode, a node wakes up at multiples of number ${\alpha}$, where ${\alpha}$ is determined by the node's remaining battery power. In the active discovery mode, a node wakes up for consecutive ${\gamma}$ slots. Then, the node operating in the active discovery mode can discover all neighbors waking up at multiples of ${\beta}$ for ${\beta}{\leq}{\gamma}$ within ${\gamma}$ time slots. Since the proposed protocol assigns one half of the duty cycle to each mode, it consumes equal to or less energy than the existing protocols. A performance comparison shows that the proposed protocol outperforms the existing protocols in terms of discovery latency and energy consumption, where the frequency of neighbor discovery requests by car accidents is not constantly high.

• Design & Manufacturing
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• v.13 no.3
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• pp.35-40
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• 2019

As the consumer market in the cosmetic, vehicle manufacturing and aerospace industries grows, the demand for manufacturing industries using on injection mold technology. Also, such manufacturing technology of metal machining is expensive, and the shape is limited. Cosmetic cushion fact products are divided into outer relevant to the exterior of the product and inner containers containing the actual contents. In the case of the inner container, it needs to be combined with the upper and lower cases. As environmental regulations are strengthened internationally, the use of a large number of component parts can result in significant losses in recycling and economics. Therefore, this study aims to perform injection molding analysis through injection molding simulation to develop a cushion fact container that can be recycled through the unification of products and materials using polypropylene to cope with environmental regulations. In the case of injection molding conditions, Injection Time(sec): 4.5, Cooling Time(sec): 13, Resin Temperature($^{\circ}C$): 240, and Pressure(MPa): 30 were determined. The results of injection molding simulation according to the two design methods were compared with the sync mark which shows the problem of filling and injection molding.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.780-783
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• 2009

The application of MOST150 technology has been required to satisfy the demand for the automotive infotainment system and the higher bandwidth requirements caused by the increase of the multimedia processing capacity. The Ethernet technology applied gateway was implemented for an efficient transmission of multimedia, a vehicle diagnosis, an external communication, a data processing between the MOST150 and the CAN communication method applied to many existing vehicles. The new algorithm and application were suggested in order to efficiently perform the data processing between other types of communication systems. The existing MOST150 frame is mainly composed of the Control Channel, the Legacy Packet Channel(async) and the Synchronous /Isochronous Channels and performs the data processing through these sequential channels. With the sense of this process, this study suggested the new algorithm that the Mapping method of the IETF's QoS Management was applied to the MOST150 technology for the efficient QoS.

• Journal of Powder Materials
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• v.26 no.2
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• pp.146-155
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• 2019

Rare earth magnets are the strongest type of permanent magnets and are integral to the high tech industry, particularly in clean energies, such as electric vehicle motors and wind turbine generators. However, the cost of rare earth materials and the imbalance in supply and demand still remain big problems to solve for permanent magnet related industries. Thus, a magnet with abundant elements and moderate magnetic performance is required to replace rare-earth magnets. Recently, $a^{{\prime}{\prime}}-Fe_{16}N_2$ has attracted considerable attention as a promising candidate for next-generation non-rare-earth permanent magnets due to its gigantic magnetization (3.23 T). Also, metastable $a^{{\prime}{\prime}}-Fe_{16}N_2$ exhibits high tetragonality (c/a = 1.1) by interstitial introduction of N atoms, leading to a high magnetocrystalline anisotropy constant ($K_1=1.0MJ/m^3$). In addition, Fe has a large amount of reserves on the Earth compared to other magnetic materials, leading to low cost of raw materials and manufacturing for industrial production. In this paper, we review the synthetic methods of metastable $a^{{\prime}{\prime}}-Fe_{16}N_2$ with film, powder and bulk form and discuss the approaches to enhance magnetocrystalline anisotropy of $a^{{\prime}{\prime}}-Fe_{16}N_2$. Future research prospects are also offered with patent trends observed thus far.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.104-113
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• 2019

The road management institute needs lots of cost to repair road surface damage. These damages are inevitable due to natural factors and aging, but maintenance technologies for efficient repair of the broken road are needed. Various technologies have been developed and applied to cope with such a demand. Recently, maintenance technology for road surface damage repair is being developed using image information collected in the form of a black box installed in a vehicle. There are various methods to extract the damaged region, however, we will discuss the image recognition technology of the deep neural network structure that is actively studied recently. In this paper, we introduce a new neural network which can estimate the road damage and its location in the image by region-based convolution neural network algorithm. In order to develop the algorithm, about 600 images were collected through actual driving. Then, learning was carried out and compared with the existing model, we developed a neural network with 10.67% accuracy.

• Advances in aircraft and spacecraft science
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• v.6 no.2
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• pp.117-144
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• 2019

High Altitude and Long Endurance (HALE) aircraft are capable of providing intelligence, surveillance and reconnaissance (ISR) capabilities over vast geographic areas when equipped with advanced sensor packages. As their use becomes more widespread, the demand for additional range, endurance and payload capability will increase and designers are exploring non-conventional configurations to meet the increasing demands. One such configuration is the joined-wing concept. A joined-wing aircraft is one that typically connects a front and aft wings in a diamond shaped planform. One such example is the Boeing SensorCraft configuration. While the joined-wing configuration offers potential benefits regarding aerodynamic efficiency, structural weight, and sensing capabilities, structural design requires careful consideration of elastic buckling resulting from the aft wing supporting, in compression, part of the forward wing structural loading. It has been shown already that this is a nonlinear phenomenon, involving geometric nonlinearities and follower forces that tend to flatten the entire configuration, leading to structural overload due to the loss of the aft wing's ability to support the forward wing load. Severe gusts are likely to be the critical design condition, with flight control system interaction in the form of Gust Load Alleviation (GLA) playing a key role in minimizing the structural loads. The University of Victoria Center for Aerospace Research (UVic-CfAR) has built a 3-meter span scaled and flexible wing UAV based on the Boeing SensorCraft design. The goal is to validate the nonlinear structural behavior in flight. The main objective of this research work is to perform Ground Vibration Tests (GVT) to characterize the dynamic properties of the scaled flight vehicle. Results from the experimental tests are used to characterize the modal dynamics of the aircraft, and to validate the numerical models. The GVT results are an important step towards a safe flight test program.