• 한국정밀공학회지
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• 제21권12호
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• pp.100-108
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• 2004

In reverse engineering, data acquisition methodology can generally be categorized into contacting and non-contacting types. Recently, researches on hybrid or sensor fusion of the two types have been increasing. In addition, efficient construction of a geometric model from the measurement data is required, where considerable amount of user interaction to classify and localize regions of interest is inevitable. Our research focuses on the classification of each bounded region into a pre-defined feature shape fer a hybrid measuring scheme, where the overall procedures are described as fellows. Firstly, the physical model is digitized by a non-contacting laser scanner which rapidly provides cloud-of-points data. Secondly, the overall digitized data are approximated to a z-map model. Each bounding curve of a region of interest (featured area) can be 1.aced out based on our previous research. Then each confined area is systematically classified into one of the pre-defined feature types such as floor, wall, strip or volume, followed by a more accurate measuring step via a contacting probe. Assigned to each feature is a specific digitizing path topology which may reflect its own geometric character. The research can play an important role in minimizing user interaction at the stage of digitizing path planning.

• 한국가스학회지
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• 제10권2호
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• pp.61-67
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• 2006

폴리에틸렌(PE) 배관 전기융착부에 대하여 위상배열초음파기술을 이용하여 전기융착부에 대한 비파괴검사를 실시하였다. 사례 1은 직경 300 mm의 PE배관 전기융착부에 대하여 3.5 MHz 배열초음파 센서를 이용하여 건전성 평가를 실시하였으며 사례 2는 직경 350 mm 3개의 새들융착부에 대하여 건전성을 평가하였고 사례 3은 400 mm 전기융착부에 대하여 3.5 MHz 배열초음파 센서를 가지고 비파괴검사를 실시하였다. 그리고 검사한 결과를 절단시험 결과와 비교하였다. 사례 4는 도시가스의 공급압력이 300 kPa인 400 mm PE배관 전기융착부를 탐상하고 그 결과를 살펴보았다.

• 전기학회논문지P
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• 제66권4호
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• pp.252-257
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• 2017

In this paper for developing and implementing the HD level triple streaming hybrid security camera which output the three type of video outputs(HD-SDI, EX-SDI, Analog). We design the hardware and program the firmware supporting the main and sub functions. We use MN34229PL as image sensor, EN778, EN331 as image processor, KA909A as reset, iris, day&night function part, A3901SEJTR-T as zoom/focus control part. We request the performance test of developed security camera at the broadcasting and communication fusion testing department of TTA (Telecommunication Technology Association). We can get the three outputs (HD-SDI, EX-SDI, Analog) from the developed security camera, get the world best level at the jitter and eye pattern amplitude value and exceed the world best level at the signal/noise ratio, and minium illumination, power consumption part. The HD level triple streaming hybrid security camera in this paper will be widely used at the security camera because of the better performance and function.

• 한국산학기술학회논문지
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• 제13권9호
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• pp.4131-4138
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• 2012

본 논문에서는 GPS 수신 불가지역에서 저가형 관성센서를 활용한 보행자용 위치정보시스템을 제안한다. 제안 기법은 보행자의 자세/방향각, 걸음검출 및 보폭 크기를 추정하고, 보조센서 등을 활용하여 위치오차를 줄인다. 제안 시스템은 보행자가 휴대할 수 있는 소형/경량화/저전력 설계된 H/W 모듈 형태로 구현을 하였으며, 건물 내에서의 보행자 이동 실험을 통해 제안 시스템의 성능을 검증하였다. 실험결과를 통해 보행자가 약 160m 이동시 약 2.4%의 위치오차율을 갖는 결과를 얻었다.

• 한국정밀공학회지
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• 제29권10호
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• pp.1128-1136
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• 2012

In this paper, the states and parameters in a dynamic system are estimated by applying an Unscented Kalman Filter (UKF). The UKF is widely used in various fields such as sensor fusion, trajectory estimation, and learning of Neural Network weights. These estimations are necessary and important in determining the stability of a mobile system, monitoring, and predictions. However, conventional approaches are difficult to estimate based on the experimental data, due to properties of non-linearity and measurement noises. Therefore, in this paper, UKF is applied in estimating the states and parameters needed. An experimental dynamic system has been set up for obtaining data and the experimental data is collected for parameter estimation. The measurement noises are primarily reduced by applying the Low Pass Filter (LPF). Given the simulation results, the estimated error rate is 39 percent more efficient than the results obtained using the Least Square Method (LSM). Secondly, the estimated parameters have an average convergence period of four seconds.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권11호
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• pp.2016-2034
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• 2011

Ubiquitous Healthcare (u-Healthcare) is the intelligent delivery of healthcare services to users anytime and anywhere. To provide robust healthcare services, recognition of patient daily life activities is required. Context information in combination with user real-time daily life activities can help in the provision of more personalized services, service suggestions, and changes in system behavior based on user profile for better healthcare services. In this paper, we focus on the intelligent manipulation of activities using the Context-aware Activity Manipulation Engine (CAME) core of the Human Activity Recognition Engine (HARE). The activities are recognized using video-based, wearable sensor-based, and location-based activity recognition engines. An ontology-based activity fusion with subject profile information for personalized system response is achieved. CAME receives real-time low level activities and infers higher level activities, situation analysis, personalized service suggestions, and makes appropriate decisions. A two-phase filtering technique is applied for intelligent processing of information (represented in ontology) and making appropriate decisions based on rules (incorporating expert knowledge). The experimental results for intelligent processing of activity information showed relatively better accuracy. Moreover, CAME is extended with activity filters and T-Box inference that resulted in better accuracy and response time in comparison to initial results of CAME.

• 한국자동차공학회논문집
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• 제16권2호
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• pp.66-73
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• 2008

In this paper, ultrasonic range system which detects parking lot in parking area is studied. The important part for detecting parking lot accurately is to detect the first and second corners of possible parking lot, and for that, new method using multiple echo function is introduced in this paper. Many probabilistic methods have been used to reduce uncertainties of ultrasonic sensor for distance and location of objects. Method using multiple echo, however, gives accurates results as well as simple algorithm. For experiments in parking space, ultrasonic range system was attached to a Pioneer AT-2 and final parking space map was created in a fusion with position information from wheels of a Pioneer AT-2. We will show the results are compared with error of another methods.

• 한국농공학회논문집
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• 제53권6호
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• pp.7-16
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• 2011

This study discussed the applicability of satellite SAR (Synthetic Aperture Radar) imagery with regard to reservoir monitoring, and tried the extraction of reservoir storage from multi-temporal C-band RADARSAT-1 SAR backscattering images of Yedang and Goongpyeong agricultural reservoirs, acquired from May to October 2005. SAR technology has been advanced as a complementary and alternative approach to optical remote sensing and in-situ measurement. Water bodies in SAR imagery represent low brightness induced by low backscattering, and reservoir storage can be derived from the backscatter contrast with the level-area-volume relationship of each reservoir. The threshold segmentation over the routine preprocessing of SAR images such as speckle reduction and low-pass filtering concluded a significant correlation between the SAR-derived reservoir storage and the observation record in spite of the considerable disagreement. The result showed up critical limitations for adopting SAR data to reservoir monitoring as follows: the inappropriate specifications of SAR data, the unreliable rating curve of reservoir, the lack of climatic information such as wind and precipitation, the interruption of inside and neighboring land cover, and so on. Furthermore, better accuracy of SAR-based reservoir monitoring could be expected through different alternatives such as multi-sensor image fusion, water level measurement with altimeters or interferometry, etc.

• 한국인공지능학회지
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• 제6권1호
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• pp.1-10
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• 2018

Compressed Air is an important energy source used in most factories nowadays. The automation trend using air compressor has been gradually increasing with the interest of the 4th industry in recent years. With the air compressor system, it is possible to construct the device at low cost and easily achieve automation and energy saving. In addition, With trend of FA, miniaturation and light weight manufacturing trend expand their use in the electronics, medical, and food sectors. Research method is to design the technology for the remote control of the following information as USN base. Development of flexible sensing module from real time observation module for fusion of IT technology in compressed air systems, design and manufacture of flexible sensing module, and realiability assessment. Design of real-time integrated management system for observation data of compressed air system - Ability to process observation data measured in real time into pre-processing and analysis data. This study expects unconventionally decreasing effect of energy cost that takes up 60~70% of air compressor layout and operation and maintenance management cost through USN(Ubiquitous Sensor Network) technology by using optimum operational condition from real time observation module. In addition, by preventing maintenance cost from malfunction of air compressor beforehand, maintenance cost is anticipated to cut back.

• IEIE Transactions on Smart Processing and Computing
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• 제5권6호
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• pp.430-439
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• 2016

Estimation and analysis of traffic jams plays a vital role in an intelligent transportation system and advances safety in the transportation system as well as mobility and optimization of environmental impact. For these reasons, many researchers currently mainly focus on the brilliant machine learning-based prediction approaches for traffic prediction systems. This paper primarily addresses the analysis and comparison of prediction accuracy between two machine learning algorithms: Naïve Bayes and K-Nearest Neighbor (K-NN). Based on the fact that optimized estimation accuracy of these methods mainly depends on a large amount of recounted data and that they require much time to compute the same function heuristically for each action, we propose an approach that applies multi-threading to these heuristic methods. It is obvious that the greater the amount of historical data, the more processing time is necessary. For a real-time system, operational response time is vital, and the proposed system also focuses on the time complexity cost as well as computational complexity. It is experimentally confirmed that K-NN does much better than Naïve Bayes, not only in prediction accuracy but also in processing time. Multi-threading-based K-NN could compute four times faster than classical K-NN, whereas multi-threading-based Naïve Bayes could process only twice as fast as classical Bayes.