• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.529-536
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• 2007

Registration between image and object space is a fundamental step in photogrammetry and computer vision. Along with rapid development of sensors - multi/hyper spectral sensor, laser scanning sensor, radar sensor etc., the needs for registration between different sensors are ever increasing. There are two important considerations on different sensor registration. They are sensor invariant feature extraction and correspondence between them. Since point to point correspondence does not exist in image and laser scanning data, it is necessary to have higher entities for extraction and correspondence. This leads to modify first, existing mathematical and geometrical model which was suitable for point measurement to line measurements, second, matching scheme. In this research, linear feature is selected for sensor invariant features and matching entity. Linear features are incorporated into mathematical equation in the form of extended collinearity equation for registration problem known as photo resection which calculates exterior orientation parameters. The other emphasis is on the scheme of finding matched entities in the aide of RANSAC (RANdom SAmple Consensus) in the absence of correspondences. To relieve computational load which is a common problem in sampling theorem, deterministic sampling technique and selecting 4 line features from 4 sectors are applied.

• Progress in Superconductivity
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• v.9 no.2
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• pp.162-166
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• 2008

We are developing a sensitive gamma ray spectrometer based on superconducting transition edge sensors. The detector consists of a small piece of high purity Sn as an absorber and a Ti/Au bilayer as a temperature sensor. It is designed to measure the thermal signal caused by absorption of gamma rays. The mechanical support and the thermal contact between the absorber and the thermometer were made with Stycast epoxy. The bilayer was formed by e-beam evaporation and patterned by wet etching on top of a $SiN_X$ membrane. A sharp superconducting transition of the film was measured near 100 mK. When the film was biased to the edge of the transition, signals were observed due to single photon absorption emitted from an $^{241}Am$ source. The measured spectrum showed several characteristic peaks of the source including 59.5 keV gamma line. The full with at half maximum was about 900 eV for the 59.5 keV gamma line. The background was low enough to resolve low energy lines. Considerations to improve the energy resolution of the gamma ray spectrometer are also discussed.

• Journal of Sensor Science and Technology
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• v.12 no.4
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• pp.164-169
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• 2003

Recently, as the road capacity reaches the limit and environmental problems becomes serious, there is gradually increased a need for railroad vehicles that are environment-friendly and have time regularity, reliability and safety. Accordingly, in addition to conventional railroad vehicles, lots of vehicles are being newly developed. We developed the hardware and software of the measurement system for on-line test and evaluation of korean high speed train. The software controls the hardware of the mesurement data and acts as interface between users and the system hardware. In this paper, we is studied for electric apparatus performance of railway vehicle using sensor. In order to this test is developed signal conversion system. Using this system, we obtained important result for pantograph voltage, battery voltage, axle speed, and inverter current.

• Journal of Korean Society on Water Environment
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• v.24 no.1
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• pp.1-6
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• 2008

Biological and chemical sensors are the two most frequently used sensors to monitor the water resource. Chemical sensor is very accurate to pick up the types and to measure the concentration of the chemical substance. Drawback is that it works for just one type of chemical substance. Therefore a lot of expensive monitoring system needs to be installed to determine the safeness of the water, which costs too much expense. Biological sensor, on the contrary, can judge the degree of pollution of the water with just one monitoring system. However, it is not easy to figure out the type of contaminant with a biological sensor. In this study, an endeavor is made to identify the toxicant in the water using the shape of the chlorophyll fluorescence induction curve (FIC) from a biological monitoring system. Wem-tox values are calculated from the amount of flourescence of contaminated and reference water. Curve fitting is executed to find the representative curve of the raw data of Wem-tox values. Then the curves are digitalized at the same interval to train the neural network model. Taguchi method is used to optimize the neural network model parameters. The optimized model shows a good capacity to figure out the toxicant from FIC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2299-2318
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• 2019

Location-aware networks are of great importance for both civil lives and military applications. Methods based on line-of-sight (LOS) measurements suffer sever performance loss in harsh environments such as indoor scenarios, where sensors can receive both LOS and non-line-of-sight (NLOS) measurements. In this paper, we propose a data association (DA) process based on the expectation maximization (EM) algorithm, which enables us to exploit multipath components (MPCs). By setting the mapping relationship between the measurements and scatters as a latent variable, coefficients of the Gaussian mixture model are estimated. Moreover, considering the misalignment of sensor position, we propose a space-alternating generalized expectation maximization (SAGE)-based algorithms to jointly update the target localization and sensor position information. A two dimensional (2-D) circularly symmetric Gaussian distribution is employed to approximate the probability density function of the sensor's position uncertainty via the minimization of the Kullback-Leibler divergence (KLD), which enables us to calculate the expectation step with low computational complexity. Moreover, a distributed implementation is derived based on the average consensus method to improve the scalability of the proposed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms can perform close to the Monte Carlo-based method with much lower communication overhead and computational complexity.

• Journal of Information Technology Services
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• v.22 no.2
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• pp.57-70
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• 2023

In order to establish an autonomous driving environment, it is necessary to study traffic safety and demand prediction by analyzing information generated from the transportation infrastructure beyond relying on sensors by the vehicle itself. In this paper, we propose a real-time traffic information generation method using sensor convergence technology of transportation infrastructure. The proposed method uses sensors such as cameras and radars installed in the transportation infrastructure to generate information such as crosswalk pedestrian presence or absence, crosswalk pause judgment, distance to stop line, queue, head distance, and car distance according to each characteristic. create information An experiment was conducted by comparing the proposed method with the drone measurement result by establishing a demonstration environment. As a result of the experiment, it was confirmed that it was possible to recognize pedestrians at crosswalks and the judgment of a pause in front of a crosswalk, and most data such as distance to the stop line and queues showed more than 95% accuracy, so it was judged to be usable.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.387-396
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• 2002

Batch processes are a significant class of processes in the process industry and play an important role in the production of high quality speciality materials. Examples include the production of semiconductors, chemicals, pharmaceuticals, and biochemicals. With on-line sensors connected to most batch processes, massive amounts of data are being collected routinely during the batch on easily measured process variables such as temperatures, pressures, and flowrates. In this paper, multivariate SPC charts for on-line monitoring of the progress of new batches are developed which utilize the information in the on-line measurements in real-time. We propose the formation of statistical model which describes the normal operation of a batch at each time interval during the batch operation. An on-line monitoring scheme based on the proposed method can handle both cross-correlation among process variables at any one time and auto-correlation over time. And the control limits for the monitoring charts are established from sound statistical framework unlike previous researches which use the external reference distribution. The proposed charts perform real-time, on-line monitoring to ensure that the batch is progressing in a manner that will lead to a high-quality product or to detect and indicate faults that can be corrected prior to completion of the batch. This approach is capable of tracking the progress of new batch runs, identifying the time periods in which the fault occurred and detecting underlying cause.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1221-1228
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• 2022

With the development of modern technology, the use of unmanned automation equipment that can replace humans in logistics and industrial sites is increasing. The technology of one such automation facility, the Unmanned Carrier (AGV), includes Line Tracing, which allows you to recognize a line through infrared sensors and drive a predetermined route. In this paper, the shortest time algorithm using Arduino is configured in the line tracing technology to enable efficient driving. It is also designed to collect location and time information using RFID tags.

• Journal of Environmental Science International
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• v.13 no.3
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• pp.245-250
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• 2004

The SBR(Sequencing Batch Reactor) process is ideally suited to treat high loading wastewater due to its high dilution rate. SBR operates by a cycle of periods consisting of filling, reacting, settling, decanting and idling. The react phases such as aeration or non-aeration, organic oxidation, nitrification, denitrification and other bio-logical reactions can be achieved in a reactor. Although the whole reactions can be achieved in a SBR with time distributing, it is hard to manage the SBR as a normal condition without recognizing a present state. The present state can be observed with nutrient sensors such as ${NH_{4}}^{+}-N$, ${NO_{2}}^{-}-N$, ${NO_{3}}^{-}-N} and ${PO_{4}}^{ 3-}-P.$ However, there is still a disadvantage to use the nutrient sensors because of their high expense and inconvenience to manage. Therefore, it is very useful to use common on-line sensors such as DO, ORP and pH, which are less expensive and more convient. Moreover, the present states and unexpected changes of SBR might be predicted by using of them. This study was conducted to get basic materials for making an inference of SBR process from ORP(oxidation reduction potential) of synthetic wastewater. The profiles of ORP, DO, and pH were under normal nitrification and denitrification were obtained to compare abnormal condition. And also, nitrite and nitrate accumulation were investigated during reaction of SBR. The bending point on ORP profile was not entirely in the low COD/NOx ratio condition. In this case, NOx was not entirely removed, and minimum ORP value was presented over -300mV. Under suitable COD/NOx ratio which complete denitrification was achieved, ORP bending point was observed and minimum ORP value was under -300m V. Under high COD/NOx ratio, ORP bending point was not detected at the first subcycle because of the fast denitrification and minimum ORP value was under -300mV at the time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1271-1280
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• 2012

In the recent parking assistant systems, finding out the distance to the object behind a car is often performed by the range sensors such as ultrasonic sensors, radars. However, the installation of additional sensors on the used vehicle could be difficult and require extra cost. On the other hand, the motion stereo technique that extracts distance information using only an image sensor was also proposed. However, In the stereo rectification step, the motion stereo requires good features and exacts matching result. In this paper, we propose a fast algorithm that extracts the accurate distance information for the parallel parking situation using the consecutive images that is acquired by a rear-view camera. The proposed algorithm uses the quadrangle transform of the image, the horizontal line integral projection, and the blocking-based correlation measurement. In the experiment with the magna parallel test sequence, the result shows that the line-accurate distance measurement with the image sequence from the rear-view camera is possible.