• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.111-116
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• 2014

Human-robot co-operation becomes increasingly frequent due to the widespread use of service robots. However, during such co-operation, robots have a high chance of colliding with humans, which may result in serious injury. Thus, many solutions were proposed to ensure collision safety, and among them, collision detection algorithms are regarded as one of the most practical solutions. They allow a robot to quickly detect a collision so that the robot can perform a proper reaction to minimize the impact. However, conventional collision detection algorithms required the precise model of a robot, which is difficult to obtain and is subjected to change. Also, expensive sensors, such as torque sensors, are often required. In this study, we propose a novel collision detection algorithm which only requires motor encoders. It detects collisions by monitoring the high-pass filtered version of the velocity error. The proposed algorithm can be easily implemented to any robots, and its performance was verified through various tests.

• Design & Manufacturing
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• v.11 no.3
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• pp.35-40
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• 2017

PCR(Polymerase chain reaction) is a technique to replicate and amplify a desired part of DNA. It is used in various aspects such as DNA fingerprint analysis and rare DNA amplification of an extinct animal. Especially in the medical diagnosis field, it provides various measurement methods at the molecular level such as genetic diagnosis, and is a basic tool for molecular diagnostics. The internal shape of the plastic vial tube for PCR analysis used in the DNA detection process, and the surface roughness and internal cleanliness can affect detection and discrimination results. The plastic vial tube demanded by the developer of the PCR analysis equipment should be changed to a structure that eliminates the residual washing solution in the washing process to ensure the internal cleanliness. Thus the internal structure and the internal surface design for improving the PCR amplification efficiency are key issues to develop the plastic vial tube for the DNA detection process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.1
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• pp.9-19
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• 2024

Deep learning-based computer vision anomaly detection algorithms are widely utilized in various fields. Especially in the manufacturing industry, the difficulty in collecting abnormal data compared to normal data, and the challenge of defining all potential abnormalities in advance, have led to an increasing demand for unsupervised learning methods that rely on normal data. In this study, we conducted a comparative analysis of deep learning-based unsupervised learning algorithms that define and detect abnormalities that can occur when transparent contact lenses are immersed in liquid solution. We validated and applied the unsupervised learning algorithms used in this study to the existing anomaly detection benchmark dataset, MvTecAD. The existing anomaly detection benchmark dataset primarily consists of solid objects, whereas in our study, we compared unsupervised learning-based algorithms in experiments judging the shape and presence of lenses submerged in liquid. Among the algorithms analyzed, EfficientAD showed an AUROC and F1-score of 0.97 in image-level tests. However, the F1-score decreased to 0.18 in pixel-level tests, making it challenging to determine the locations where abnormalities occurred. Despite this, EfficientAD demonstrated excellent performance in image-level tests classifying normal and abnormal instances, suggesting that with the collection and training of large-scale data in real industrial settings, it is expected to exhibit even better performance.

• Korea Information Processing Society Review
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• v.26 no.1
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• pp.26-32
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• 2019

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.5
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• pp.515-523
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• 2015

In this paper, we fabricated and evaluated the gas sensor for the detection of CO gas and $NO_X$ gas among the vehicle exhaust emission gasses. The $SnO_2$ (tin dioxide) layer is used as the detection material, and the thin-film type and the nano-fiber type layers are deposited with various thicknesses using sputtering method and electro spinning method, respectively. The experiments are performed in the chamber where the gas concentration is controlled with mass flow controller. The fabricated devices are applied to the CO and $NO_X$ gas, where the device with the thinner $SnO_2$ layer shows better sensitivity. The nano-fiber has the larger surface area, and the shorter response time and recovery time are obtained. From the experimental results, both types of gas sensors successfully detect CO and $NO_X$ gases, which can be applied to measure those gases from the vehicle emissions.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.481-487
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• 2020

Radiation measurement technology has steadily improved and its usage is expanding in various industries such as nuclear medicine, security search, satellite, nondestructive testing, environmental industries and the domain of nuclear power plants (NPPs). Especially, the simultaneous measurements of gamma rays and neutrons can be even more critical for nuclear safety management of spent nuclear fuel and monitoring of the nuclear material. A semiconductor detector comprising cadmium, zinc, and tellurium (CZT) enables to detect gamma-rays due to the significant atomic weight of the elements via immediate neutron and gamma-ray detection. Semiconductor sensors might be used for nuclear safety management by monitoring nuclear materials and spent nuclear fuel with high spatial resolution as well as providing real-time measurements. We aim to introduce a portable nuclide-analysis device that enables the simultaneous measurements of neutrons and gamma rays using a CZT sensor. The detector has a high density and wide energy band gap, and thus exhibits highly sensitive physical characteristics and characteristics are required for performing neutron and gamma-ray detection. Portable nuclide-analysis device is used on NPP-decommissioning sites or the purpose of nuclear nonproliferation, it will rapidly detect the nuclear material and provide radioactive-material information. Eventually, portable nuclide-analysis device can reduce measurement time and economic costs by providing a basis for rational decision making.

• ETRI Journal
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• v.39 no.5
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• pp.652-661
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• 2017

A mention has a noun or noun phrase as its head and constructs a chunk that defines any meaning, including a modifier. Mention detection refers to the extraction of mentions from a document. In mentions, coreference resolution refers to determining any mentions that have the same meaning. Pointer networks, which are models based on a recurrent neural network encoder-decoder, outputs a list of elements corresponding to an input sequence. In this paper, we propose mention detection using pointer networks. This approach can solve the problem of overlapped mention detection, which cannot be solved by a sequence labeling approach. The experimental results show that the performance of the proposed mention detection approach is F1 of 80.75%, which is 8% higher than rule-based mention detection, and the performance of the coreference resolution has a CoNLL F1 of 56.67% (mention boundary), which is 7.68% higher than coreference resolution using rule-based mention detection.

• Fire Science and Engineering
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• v.28 no.2
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• pp.54-63
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• 2014

The purpose of this study is to test the adaptability of the CO sensor as a fire detector by analyzing its sensing characteristics on fire. In order to test the applicability, we designed and made a fire testing ground whose size is similar to that regulated by UL 268, carried out real fire tests suggested by UL 268, and conducted a comparison analysis on the sensing characteristics between the CO sensor and a photoelectric smoke detector by different types of fire source. The experiment result to the sensing characteristics of the CO sensor is about twice to three times faster than that of the photoelectric smoke detector, proceeding with incomplete combustion such as paper and wood fire source in the initial fire. Especially in case of wood smoldering fire, sensing characteristics of the CO sensor is very excellent.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.5
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• pp.383-392
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• 2007

This study focuses on co-registration and band selection, which are one of the pre-processing steps to apply the change detection technique using hyperspectral images. We carried out automatic co-registration by using the SIFT algorithm which performance was already established in the computer vision fields, and selected the bands fur change detection by estimating the noise of image through the PIFs reflecting the radiometric consistency. The EM algorithm was also applied to select the band objectively. Hyperion images were used for the proposed techniques, and non-calibrated bands and striping noises contained in Hyperion image were removed. Throughout the results, we could develop the reliable co-registration procedure which coincided with accuracy within 0.2 pixels (RMSE) for change detection, and verified that band selection depending on the visual inspection could be objective by extracting the PIFs.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.255-265
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• 2015

Very high resolution (VHR) satellite imagery provide valuable information on urban change monitoring due to multi-temporal observation over large areas. Recently, there has been increased interest in the urban change detection technique using VHR Synthetic Aperture Radar (SAR) imaging system, because it can take images regardless of solar illumination and weather condition. In this paper, we proposed a texture-based urban change detection method using the VHR SAR texture features generated from Gray-Level Co-Occurrence Matrix (GLCM). In order to evaluate the efficiency of the proposed method, the result was compared, visually and quantitatively, with the result of Non-Coherent Change Detection (NCCD) which is widely used for the change detection of VHR SAR image. The experimental results showed the greater detection accuracy and the visually satisfactory result compared with the NCCD method. In conclusion, the proposed method has shown a great potential for the extraction of urban change information from VHR SAR imagery.