Journal of the Korea Institute of Information and Communication Engineering
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v.27
no.1
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pp.54-61
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2023
With the development of IoT technologies and artificial intelligent, diverse digital image equipments are being used in industrial sites. Because image data can be easily damaged by noise while it's obtained with a camera or a sensor and the damaged image has a bad effect on the process of image processing, noise removal is being demanded as preprocessing. In this thesis, for the restoration of image damaged by the noise of random impulse, a switching filter algorithm based on noise estimation was suggested. With the proposed algorithm, noise estimation and error distraction were carried out according to the similarity of the pixel values in the local mask of the image, and a filter was chosen and switched depending on the ratio of noise existing in the local mask. Simulations were conducted to analyze the noise removal performance of the proposed algorithm, and as a result of magnified image and PSNR comparison, it showed superior performance compared to the existing method.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2022.10a
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pp.570-573
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2022
This paper presents the identification of void diameters for a cast-resin transformer using an artificial neural network (ANN) model. A PD signal was measured by the Rogowski coil sensor which has the planar and thin structures fabricated on a printed circuit board (PCB), and the PD electrode system was fabricated to simulate a PD defect by a void. In addition, void samples with different diameters were fabricated by injecting air in a cylindrical aluminum frame using a syringe during the epoxy curing process. To identify the diameter of void defects, PD characteristics such as the discharge magnitude, pulse count, and phase angle were extracted and back propagation algorithm (BPA) was designed using virtual instrument (VI) based on the Labview program. From the experimental results, the BPA algorithm proposed in this paper has over 90% accurate rate to identify the diameter of void defects and is expected to use reference data of maintenance and replacement of insulation for cast-resin transformers in the on-site PD measurement.
Jo, Sang-Woo;Park, Jin-Woo;Kwon, Yong-Moo;Ahn, Sang-Chul
한국HCI학회:학술대회논문집
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2006.02a
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pp.355-361
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2006
In large scale environments like airport, museum, large warehouse and department store, autonomous mobile robots will play an important role in security and surveillance tasks. Robotic security guards will give the surveyed information of large scale environments and communicate with human operator with that kind of data such as if there is an object or not and a window is open. Both for visualization of information and as human machine interface for remote control, a 3D model can give much more useful information than the typical 2D maps used in many robotic applications today. It is easier to understandable and makes user feel like being in a location of robot so that user could interact with robot more naturally in a remote circumstance and see structures such as windows and doors that cannot be seen in a 2D model. In this paper we present our simple and easy to use method to obtain a 3D textured model. For expression of reality, we need to integrate the 3D models and real scenes. Most of other cases of 3D modeling method consist of two data acquisition devices. One for getting a 3D model and another for obtaining realistic textures. In this case, the former device would be 2D laser range-finder and the latter device would be common camera. Our algorithm consists of building a measurement-based 2D metric map which is acquired by laser range-finder, texture acquisition/stitching and texture-mapping to corresponding 3D model. The algorithm is implemented with laser sensor for obtaining 2D/3D metric map and two cameras for gathering texture. Our geometric 3D model consists of planes that model the floor and walls. The geometry of the planes is extracted from the 2D metric map data. Textures for the floor and walls are generated from the images captured by two 1394 cameras which have wide Field of View angle. Image stitching and image cutting process is used to generate textured images for corresponding with a 3D model. The algorithm is applied to 2 cases which are corridor and space that has the four wall like room of building. The generated 3D map model of indoor environment is shown with VRML format and can be viewed in a web browser with a VRML plug-in. The proposed algorithm can be applied to 3D model-based remote surveillance system through WWW.
In this paper, we present preliminary feasibility studies on three types of solar observation payloads for future Korean Science and Technology Satellite (STSAT) programs. The three candidates are (1) an UV imaging telescope, (2) an UV spectrograph, and (3) an X-ray spectrometer. In the case of UV imaging telescope, the most important constraint seems to be the control stability of a satellite in order to obtain a reasonably good spatial resolution. Considering that the current pointing stability estimated from the data of the Far ultraviolet Imaging Spectrograph (FIMS) onboard the Korean STSAT-1, is around 1 arc minutes/sec, we think that it is hard to obtain a spatial resolution sufficient for scientific research by such an UV Imaging Telescope. For solar imaging missions, we realize that an image stabilization system, which is composed of a small guide telescope with limb sensor and a servo controller of secondary mirror, is quite essential for a very good pointing stability of about 0.1 arcsec. An UV spectrograph covering the solar full disk seems to be a good choice in that there is no risk due to poor pointing stability as well as that it can provide us with valuable UV spectral irradiance data valuable for studying their effects on the Earth's atmosphere and satellites. The heritage of the FIMS can be a great advantage of developing the UV spectrograph. Its main disadvantage is that two major missions are in operation or scheduled. Our preliminary investigations show that an X-ray spectrometer for the full disk Sun seems to be the best choice among the three candidates. The reasons are : (1) high temporal and spectral X-ray data are very essential for studying the acceleration process of energetic particles associated with solar flares, (2) we have a good heritage of X-ray detectors including a rocket-borne X-ray detector, (3) in the case of developing countries such as India and Czech, solar X-ray spectrometers were selected as their early stage satellite missions due to their poor pointing stabilities, and (4) there is no planned major mission after currently operating Reuven Ramaty High-Energy Solar Spectroscopic Imager (RHESSI) mission. Finally, we present a preliminary design of a solar X-ray spectrometer covering soft X-ray (2 keV) to gamma ray (10 MeV).
KSCE Journal of Civil and Environmental Engineering Research
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v.44
no.1
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pp.85-93
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2024
The monitoring of environmental information (e.g. noise, dust, vibration, temperature, humidity) is crucial to the safe and sustainable operation of a construction site. However, commercial sensors exhibit certain drawbacks when applied on-site. First, the installation cost is prohibitively high. Second, these sensors have been engineered without considering the rugged and harsh conditions of a construction site, resulting in error-prone sensing. Third, construction sites are compelled to allocate additional resources in terms of manpower, expenses, and physical spaces to accommodate individual sensors. This research developed an integrated sensing module to measure the environmental information in construction site. The sensing module slashes the installation cost to 3.3%, is robust enough to harsh and outdoor sites, and consolidates multiple sensors into a single unit. The sensing module also supports GPS, LTE, and real-time sensing. The evaluation showed remarkable results including 97.5% accuracy and 99.9% precision in noise measurement, an 89.7% accuracy in dust measurement, and a 93.5% reliability in data transmission. This research empowers the collection of substantial volumes and high-quality environmental data from construction sites, providing invaluable support to decision-making process. These encompass objective regulatory compliance checking, simulations of environmental data dispersion, and the development of environmental mitigation strategies.
In order to optimize process conditions for manufacturing retorted Kimchi soup by using stationary and rotary types systems were applied for sterilization process. For investigating the differences in heat penetration characteristics during sterilization, Kimchi soup was packed into retort pouches, and sterility ($F_0$ value) at various positions in the product was measured through a wireless $F_0$ sensor. Heat penetration characteristics were significantly affected by sterilization method. From data analysis, optimum ranges of sterilization temperature and time was determined to be $120.7^{\circ}C$, 13 min for rotary type and $120.7^{\circ}C$, 20 min for stationary type. At those conditions, they had similar sterility ($F_0$ value). The results showed that rotation provides faster heat penetration and more uniform sterility than various positions of the product. These results derived a lot of advantages from related industry. For instance, many of the more viscous semi-liquid products and heat sensitive natural products could be sterilized in the lager pouch sizes without overcooking or scorching. Hence, current study suggests that rotary type retort would make it possible not only to reduce processing times as 35~45%, but also to improve the quality of product as overall taste, flavor, color, and texture with significant difference (p<0.05).
Journal of the Institute of Electronics and Information Engineers
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v.52
no.3
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pp.181-189
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2015
Powered prosthesis is used to assist walking of people with an amputated lower limb and/or weak leg strength. The accurate gait phase classification is indispensable in smooth movement control of the powered prosthesis. In previous gait phase classification using physical sensors, there is limitation that powered prosthesis should be simulated as same as the speed of training process. Therefore, we propose EMG signal based gait phase recognition method to classify stairs ascending and stairs descending into four steps without using physical sensors, respectively. RMS, VAR, MAV, SSC, ZC, WAMP features are extracted from EMG signal data and LDA(Linear Discriminant Analysis) classifier is used. In the training process, the AHRS sensor produces various ranges of walking steps according to the change of knee angles. The experimental results show that the average accuracies of the proposed method are about 85.6% in stairs ascending and 69.5% in stairs descending whereas those of preliminary studies are about 58.5% in stairs ascending and 35.3% in stairs descending. In addition, we can analyze the average recognition ratio of each gait step with respect to the individual muscle.
KIPS Transactions on Software and Data Engineering
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v.5
no.7
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pp.345-350
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2016
This research suggests the keyword filtering about disaster and the method of detecting area in real-time event detecting system by analyzing contents of twitter. The diffusion of smart-mobile has lead to a fast spread of SNS and nowadays, various researches based on studying SNS are being processed. Among SNS, the twitter has a characteristic of fast diffusion since it is written in 140 words of short paragraph. Therefore, the tweets that are written by twitter users are able to perform a role of sensor. By using these features the research has been constructed which detects the events that have been occurred. However, people became reluctant to open their information of location because it is reported that private information leakage are increasing. Also, problems associated with accuracy are occurred in process of analyzing the tweet contents that do not follow the spelling rule. Therefore, additional designing keyword filtering and the method of area detection on detecting real-time event process were required in order to develop the accuracy. This research suggests the method of keyword filtering about disaster and two methods of detecting area. One is the method of removing area noise which removes the noise that occurred in the local name words. And the other one is the method of determinating the area which confirms local name words by using landmarks. By applying the method of keyword filtering about disaster and two methods of detecting area, the accuracy has improved. It has improved 49% to 78% by using the method of removing area noise and the other accuracy has improved 49% to 89% by using the method of determinating the area.
The land surface parameters should be determined with sufficient accuracy, because these play an important role in climate change near the ground. As the surface reflectance presents strong anisotropy, off-nadir viewing results a strong dependency of observations on the Sun - target - sensor geometry. They contribute to the random noise which is produced by surface angular effects. The principal objective of the study is to provide a database of accurate surface reflectance eliminated the angular effects from MODIS 250m reflective channel data over Korea. The MODIS (Moderate Resolution Imaging Spectroradiometer) sensor has provided visible and near infrared channel reflectance at 250m resolution on a daily basis. The successive analytic processing steps were firstly performed on a per-pixel basis to remove cloudy pixels. And for the geometric distortion, the correction process were performed by the nearest neighbor resampling using 2nd-order polynomial obtained from the geolocation information of MODIS Data set. In order to correct the surface anisotropy effects, this paper attempted the semiempirical kernel-driven Bi- directional Reflectance Distribution Function(BRDF) model. The algorithm yields an inversion of the kernel-driven model to the angular components, such as viewing zenith angle, solar zenith angle, viewing azimuth angle, solar azimuth angle from reflectance observed by satellite. First we consider sets of the model observations comprised with a 31-day period to perform the BRDF model. In the next step, Nadir view reflectance normalization is carried out through the modification of the angular components, separated by BRDF model for each spectral band and each pixel. Modeled reflectance values show a good agreement with measured reflectance values and their RMSE(Root Mean Square Error) was totally about 0.01(maximum=0.03). Finally, we provide a normalized surface reflectance database consisted of 36 images for 2001 over Korea.
In this study, a method to assess and monitor hydrological drought using remote sensing was investigated for use in regions with limited observation data, and was applied to the Upper Namhangang basin in South Korea, which was seriously affected by the 2008-2009 drought. Drought information may be obtained more easily from meteorological data based on water balance than hydrological data that are hard to estimate. Air temperature data at 2 m above ground level (AGL) were estimated using remotely sensed data, evapotranspiration was estimated from the air temperature, and the correlations between precipitation minus evapotranspiration (P-PET) and streamflow percentiles were examined. Land Surface Temperature data with $1{\times}1km$ spatial resolution as well as Atmospheric Profile data with $5{\times}5km$ spatial resolution from MODIS sensor on board Aqua satellite were used to estimate monthly maximum and minimum air temperature in South Korea. Evapotranspiration was estimated from the maximum and minimum air temperature using the Hargreaves method and the estimates were compared to existing data of the University of Montana based on Penman-Monteith method showing smaller coefficient of determination values but smaller error values. Precipitation was obtained from TRMM monthly rainfall data, and the correlations of 1-, 3-, 6-, and 12-month P-PET percentiles with streamflow percentiles were analyzed for the Upper Namhan-gang basin in South Korea. The 1-month P-PET percentile during JJA (r = 0.89, tau = 0.71) and SON (r = 0.63, tau = 0.47) in the Upper Namhan-gang basin are highly correlated with the streamflow percentile with 95% confidence level. Since the effect of precipitation in the basin is especially high, the correlation between evapotranspiration percentile and streamflow percentile is positive. These results indicate that remote sensing-based P-PET estimates can be used for the assessment and monitoring of hydrological drought. The high spatial resolution estimates can be used in the decision-making process to minimize the adverse impacts of hydrological drought and to establish differentiated measures coping with drought.
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