• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.1-10
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• 2011

In this paper, we proposed the skin color based hand and finger detection technology for the gesture recognition in CCTV surveillance. The aim of this paper is to present the methodology for hand detection and propose the finger detection method. The detected hand and finger can be used to implement the non-contact mouse. This technology can be used to control the home devices such as home-theater and television. Skin color is used to segment the hand region from background and contour is extracted from the segmented hand. Analysis of contour gives us the location of finger tip in the hand. After detecting the location of the fingertip, this system tracks the fingertip by using only R channel alone, and in recognition of hand motions to apply differential image, such as the removal of useless image shows a robust side. We explain about experiment which relates in fingertip tracking and finger gestures recognition, and experiment result shows the accuracy above 96%.

• Journal of Korea Water Resources Association
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• v.50 no.9
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• pp.609-616
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• 2017

In this study, algorithm for the selecting the optimum monitoring location and leakage detection algorithm based on back tracing calculation method were developed and verified by the experiments in pilot plant of water distribution system. First of all, optimum monitoring locations were selected and pressure changes were measured due to artificial leakage by pressure gauges in pilot plant. Simulations of leakage detection was performed for the verification of back tracing calculation method as a leakage detection method. From the results, it was found that leakage locations and leakage amount were exactly estimated. Various leakage amount from $0.0005m^3/s$ to $0.0018m^3/s$ were reproduced and leakage location was detected by back tracing calculation method. It was verified that back tracing calculation method as a leakage detection method is effective.

• Journal of Environmental Health Sciences
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• v.42 no.5
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• pp.314-323
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• 2016

Objectives: Time location data are critical for accurately estimating personal exposures. This review papers summarized various measurement methods of time location pattern for air pollution exposure assessment. Methods: Forty manuscripts (papers, books and reports) were reviewed to comprehensively describe time location measurement methods. Results: This review included traditional methods such as time activity diary, questionnaire, observation, focus group and newly developed technical methods including global positioning system, web, radio frequency identification and ultrasound detection. Some research applied a combination of methods. Conclusion: Although various methods have been used to collect time location data, further development of accurate measurement methods for time location data is needed.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.96-102
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• 2005

Acoustic Emission(AE) technique has been applied to not only material characterization evaluation but also on-line monitoring of the structural integrity. The AE source location technique is very important to identify the source, such as crack, leak detection. Since the AE waveforms obtained from sensors are very difficult to distinguish the defect signals, therefore, it is necessary to consider the signal analysis of the transient wave-form. In this study, we have divided the region of interest into a set finite elements, and calculated the arrival time differences between sensors by using the velocities at every degree from 0 to 90. A new technique for the source location of acoustic emission in fiberboard plates has been studied by introducing Wavelet Transform(WT) do-noising technique. WT is a powerful tool for processing transient signals with temporally varying spectra. If the WT de-noising was employed, we could successfully filter out the errors of source location in fiberboard plates by arrival time difference method. The accuracy of source location appeared to be significantly improved.

• Transactions on Electrical and Electronic Materials
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• v.17 no.6
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• pp.363-368
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• 2016

Rectangular shape detection plays an important role in many image recognition systems. However, it requires continued research for its improved performance. In this study, we propose a strong rectangular shape detection algorithm, which combines the canny edge and line detection algorithms based on the perpendicularity and parallelism of a rectangle. First, we use the canny edge detection algorithm in order to obtain an image edge map. We then find the edge of the contour by using the connected component and find each edge contour from the edge map by using a DP (douglas-peucker) algorithm, and convert the contour into a polyline segment by using a DP algorithm. Each of the segments is compared with each other to calculate parallelism, whether or not the segment intersects the perpendicularity intersecting corner necessary to detect the rectangular shape. Using the perpendicularity and the parallelism, the four best line segments are selected and whether a determined the rectangular shape about the combination. According to the result of the experiment, the proposed rectangular shape detection algorithm strongly showed the size, location, direction, and color of the various objects. In addition, the proposed algorithm is applied to the license plate detecting and it wants to show the strength of the results.

• Smart Structures and Systems
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• v.14 no.2
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• pp.85-104
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• 2014

Damage detection is a challenging, complex, and at the same time very important research topic in civil engineering. Identifying the location and severity of damage in a structure, as well as the global effects of local damage on the performance of the structure are fundamental elements of damage detection algorithms. Local damage detection is essential for structural health monitoring since local damages can propagate and become detrimental to the functionality of the entire structure. Existing studies present several methods which utilize sensor data, and track global changes in the structure. The challenging issue for these methods is to be sensitive enough in identifYing local damage. Autoregressive models with exogenous terms (ARX) are a popular class of modeling approaches which are the basis for a large group of local damage detection algorithms. This study presents an algorithm, called Influence-based Damage Detection Algorithm (IDDA), which is developed for identification of local damage based on regression of the vibration responses. The formulation of the algorithm and the post-processing statistical framework is presented and its performance is validated through implementation on an experimental beam-column connection which is instrumented by dense-clustered wired and wireless sensor networks. While implementing the algorithm, two different sensor networks with different sensing qualities are utilized and the results are compared. Based on the comparison of the results, the effect of sensor noise on the performance of the proposed algorithm is observed and discussed in this paper.

• Biomedical Science Letters
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• v.24 no.4
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• pp.390-397
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• 2018

For the specific detection of human Parvovirus B19 (HuPaV-B19), we designed ten specific PCR primers from 3,800~4,500 nucleotides of HuPaV-B19 complete genome (NC_000883.2). Seventeen candidate PCR primer sets for specific detecting HuPaV-B19 were constructed. In specific reaction of HuPaV-B19, seventeen PCR primer sets showed specific band, however five PCR primer sets were selected basis of band intensity, amplicon size and location. In non-specific reaction with seven reference viruses, four PCR primer sets showed non-specific band, however one PCR primer set is not. Detection sensitivity of final selective PCR primer set was $100fg/{\mu}L$ for 112 minute, and PCR amplicon is 539 base pairs (bp). In addition, nested PCR primer set was developed, for detection HuPaV-B19 from a low concentration of contaminated samples. Selection of nested PCR primer set was basis of sensitivity and groundwater sample tests. Detection sensitivity of final selective PCR and nested PCR primer sets for the detection of HuPaV-B19 were $100fg/{\mu}L$ and $100ag/{\mu}L$ basis of HuPaV-B19 plasmid, it was able to rapid and highly sensitive detection of HuPaV-B19 than previous reports. We expect developed PCR primer set in this study will used for detection of HuPaV-B19 in various samples.

• Journal of IKEEE
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• v.25 no.2
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• pp.330-336
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• 2021

A typical way to reduce the number of hardware redundancy configurations is to implement them as analytical techniques for detecting, identifying and accepting failures with micro-controller. In this paper, one of the analytical techniques, the fault detection filter, is applied to aircraft turbofan engine system. The fault detection filter is a special type of observer that has the advantage of being able to determine the location of failures by maintaining a constant direction in the output space in the event of a particular failure. We present a single input/output dynamic system modeling of air turbine system in turbofan engine, a fault detection filter design, and simulation results applying it. Simulation results show that fault detection can be effectively applied as a sensitivity effect to the directionality of the detection filter.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.4
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• pp.1-8
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• 2008

The USN is important in technique, unmanned observation using wireless network camera, detection technique that use intrusion detection sensor. But these encrypted data transmission and processing technique through sensor network, method of the staff's location recognition and arrangement aren't serviced still as a integrated system in facility security industry. This paper proposed that improve facility management, the staff present recognition and system efficiency using RFID, USN and wireless camera.

• Proceedings of the Korea Concrete Institute Conference
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• 1991.04a
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• pp.105-110
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• 1991

The conventional high-frequency testing method is difficult to detect flaw in concrete because the high frequency stress wave is strongly attenuated due to the large grain size and heterogeneous structure. For restoration of this problem, we develop the stu요 of flaw detection in large concrete block containing various artificial flaws by low frequency spectrum anlysis of impact-echo waveforms. This impact-echo testing method is possible to determine the flaw size, shape and location in large concrete block even if required some attention in case of containing reinforcing steel bar.