• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.595-598
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• 2002

Laser scanners are getting used more and more in reverse engineering and inspection. For CNC-driven laser scanners, it is important to automate the scanning operations to improve the accuracy of capture point data and to reduce scanning time in industry. However, there are few research works on laser scan planning system. In addition, it is difficult to directly analyze multi-patched freeform models. In this paper, we propose an STL (Stereolithography) mesh based laser scan planning system for complex freeform surfaces. The scan planning system consists of three steps and it is assumed that the CAD model of the part exists. Firstly, the surface model is approximated into STL meshes. From the mesh model, normal vector of each node point is estimated. Second, scan directions and regions are determined through the region growing method. Also, scan paths are generated by calculating the minimum-bounding rectangle of points that can be scanned in each scan direction. Finally, the generated scan directions and paths are validated by checking optical constraints and the collision between the laser probe and the part to be scanned.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2948-2963
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• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.

• Journal of Biosystems Engineering
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• v.26 no.1
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• pp.11-20
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• 2001

Experiments under the stationary and harvesting condition, were performed in order to investigate the vibration characteristics of a head-feeding combine. 6 degrees of freedom components of acceleration at the location of the center of the gravity, and 3 degrees of freedom components of acceleration at the location of the operator seat were measured independently. The vibration characteristics of the combine were estimated with the power spectral density of the time series data of accelerations. From this research, the following results were obtained. 1. Vibration of a head-feeding combine under the stationary condition(engine, thresher and cutter are driven without harvesting) is mainly influenced by the engine. Further, 1/3, 1/2 (sub-harmonic) frequency components of the engine are observed besides engine driving frequency component(45Hz). 2. Vibration of a head-feeding combine under the harvesting condition is influenced by the engine, threshing unit and driving unit. Namely, some kinds of vibration frequency components in harvesting are observed compared with stationary condition. Further, sub-harmonic frequency components of the engine are observed besides engine driving frequency component as same as stationary condition. From these results, it may be concluded that vibration of a head-feeding combine is characteristics of semi-periodic and nonlinear vibration.

• Journal of Communications and Networks
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• v.17 no.3
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• pp.306-320
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• 2015

Due to an explosive growth in services running in different datacenters, there is need for service selection and routing to deliver user requests to the best service instance. In current solutions, it is generally the client that must first select a datacenter to forward the request to before an internal load-balancer of the selected datacenter can select the optimal instance. An optimal selection requires knowledge of both network and server characteristics, making clients less suitable to make this decision. Information-Centric Networking (ICN) research solved a similar selection problem for static data retrieval by integrating content delivery as a native network feature. We address the selection problem for services by extending the ICN-principles for services. In this paper we present Queue and Latency, a network-driven service selection algorithm which maps user demand to service instances, taking into account both network and server metrics. To reduce the size of service router forwarding tables, we present a statistical method to approximate an optimal load distribution with minimized router state required. Simulation results show that our statistical routing approach approximates the average system response time of source-based routing with minimized state in forwarding tables.

• Annual Conference on Human and Language Technology
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• 1999.10e
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• pp.184-190
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• 1999

본 논문에서는 Text-to-Speech 시스템에서 사용할 억양 모델을 위해 음성 DB에서 모델 파라미터와 피치 검색테이블(lookup-table)을 추출하여 미리 구성하고, 합성시에는 이를 추정하여 최종 F0 값을 생성하는 자료기반 접근방식(data-driven approach)을 사용한다. 어절 경계강도(break-index)는 경계강도의 특성에 따라 고정적 경계강도와 가변적 경계강도로 세분화하여 사용하였고, 예측된 경계강도를 기준으로 억양구(Intonation Phrase)와 액센트구(Accentual Phrase)를 설정하였다. 특히, 액센트구 모델은 인지적, 음향적으로 중요한 정점(peak)을 정확하게 모델링하는 것에 주안점을 두어 정점(peak)의 시간축, 주파수축 값과 이를 기준으로 한 앞뒤 기울기를 추정하여 4개의 파라미터로 설정하였고, 이 파라미터들은 CART(Classification and Regression Tree)를 이용하여 예측규칙을 만들었다. 경계음조가 나타나는 조사, 어미는 정규화된(normalized) 피치값과 key-index로 구성되는 검색테이블을 만들어 보다 정교하게 피치값을 예측하였다. 본 논문에서 제안한 억양 모델을 본 연구실에서 제작한 음성합성기를 통해 합성하여 청취실험을 거친 결과, 기존의 상용 Text-to-Speech 시스템에 비해 자연스러운 합성음을 얻을 수 있었다.

• Journal of Auto-vehicle Safety Association
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• v.9 no.2
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• pp.6-12
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• 2017

An autonomous driving system based on a precise digital map is developed. The system is implemented to the Hyundai's Tucsan fuel cell car, which has a camera, smart cruise control (SCC) and Blind spot detection (BSD) radars, 4-Layer LiDARs, and a standard GPS module. The precise digital map has various information such as lanes, speed bumps, crosswalks and land marks, etc. They can be distinguished as lane-level. The system fuses sensed data around the vehicle for localization and estimates the vehicle's location in the precise map. Objects around the vehicle are detected by the sensor fusion system. Collision threat assessment is performed by detecting dangerous vehicles on the precise map. When an obstacle is on the driving path, the system estimates time to collision and slow down the speed. The vehicle has driven autonomously in the Hyundai-Kia Namyang Research Center.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1251-1258
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• 2008

The purpose of this research is to introduce the new temporary earth retaining wall system using landslide stabilizing piles. This system is a self-supported retaining wall(SSR) without installing supports such as tiebacks, struts and rakers. The SSR is a kind of gravity structures consisting of twin parallel lines of piles driven below dredge level, tied together at head of soldier piles and landslide stabilizing piles by beams. There are three types of excavation wall structures: standard method for medium retained heights(<8.0m), internal excavation method and slope excavation method for deep-excavation applications(>8.0m). In the present study, the measured data from seven different sites which the SSR was used for excavation were collected and analyzed to investigate the characteristic behavior lateral wall movements associated with urban excavations in Korea.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.609-614
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• 2015

Implanted telemetry systems provide the ability to monitor different species of animals while they move within their cages. Species monitored include mice, rats, rabbits, dogs, pigs, primates, sheep, horses, cattle, and others. A miniature transmitter implanted in each animal measures one or more parameters. Parameters measured include arterial pressure, intra-pleural pressure, left ventricular pressure, intra-ocular pressure, bladder pressure, ECG, EMG, EEG, EOG, temperature, activity, and other parameters and transmits the data via radio frequency signals to a nearby receiver. Every conventional dedicated transmitter contains one or more sensors, cpu and battery. Due to the expected life of the battery, the measuring time is limited. To overcome these problems, electromagnetic inductive coupling based wireless power transmission technology using multiple transmit coils were proposed, with each coil having a different active area driven by the coil driver. In this research, a parallel resonance based coil driver and serial resonance based coil driver are proposed. From the experiments we see that the parallel coil driver shows better performance under a low impedance and multiple coils configuration. However, the serial coil driver is more efficient for high impedance transmit coils.

• Transactions on Electrical and Electronic Materials
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• v.18 no.4
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• pp.190-194
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• 2017

Present-day solar panels incorporate inverters as their core components. Switching devices driven by specialized power controllers are operated in a transformerless inverter topology. However, some challenges associated with this configuration include the absence of isolation, causing leakage currents to flow through various components toward ground. This inevitably causes power losses, often being also the primary reason for the power inverters' analog equipment failure. In this paper, various aspects of the leakage currents are studied using different circuit analysis methods. The primary objective is to convert the leakage current energy into a usable DC voltage source. The research is focused on harvesting the leakage currents for producing circa 1.1 V, derived from recently developed rectifier circuits, and driving a $200{\Omega}$ load with a power in the milliwatt range. Even though the output voltage level is low, the harvested power could be used for charging small batteries or capacitors, even driving light loads.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.908-914
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• 2019

Fusion power shutdown system (FPSS) is a safety system to stop plasma in case of accidents or incidents. The gas injection system for the FPSS presented in this work is designed to research the flow development in a closed system. As the efficiency of the system is a crucial property, plenty of experiments are executed to get optimum parameters. In this system, the flow is driven by the pressure difference between a gas storage tank and a vacuum vessel with a source pressure. The idea is based on a constant volume system without extra source gases to guarantee rapid response and high throughput. Among them, valves and gas species are studied because their properties could influence the velocity of the fluid field. Then source pressures and volumes are emphasized to investigate the volume flow rate of the injection. The source pressure has a considerable effect on the injected volume. From the data, proper parameters are extracted to achieve the best performance of the FPSS. Finally, experimental results are used as a quantitative benchmark for simulations which can add our understanding of the inner gas flow in the pipeline. In generally, there is a good consistency and the obtained correlations will be applied in further study and design for the FPSS.