• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2720-2724
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• 2007

Field measurements have revealed that the pressure drop over a borehole during drilling of a slim oil well or a well with a long reach can depend significantly on the rotation speed of the drill pipe. An accurate prediction of the annular frictional pressure drop is therefore important for conditions where the annular clearance is small. An experimental study was carried out to study solid-liquid two phase flow in a slim hole annulus. Annular velocities of carrier fluids varied from 0.2 m/s to 1.5 m/s. The carrier fluids which were utilized included tap water and CMC water solutions. Pressure drops and average flow rates were measured for the parameters such as inner-pipe rotary speed, carrier fluid velocity, hole inclination and particle injection rate. For both water and CMC solutions, the higher the concentration of the solid particles is, the larger the pressure gradients become.

• Journal of Environmental Science International
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• v.21 no.7
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• pp.769-778
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• 2012

Diesel DeNOx experiments using the SNCR process were performed by directly injecting NH3 into a simulated engine cylinder (966 $cm^3$) for which a diesel fuelled combustion-driven flow reactor was designed by simulating diesel engine geometry, temperature profiles, aerodynamics and combustion products. A wide range of air/fuel mixtures (A/F=20~45) were combusted for oxidizing diesel flue gas conditions where an initial NOx levels were 250~900 ppm and molar ratios (${\beta}=NH_3/NOx$) ranged from 0.5~2.0 for NOx reduction tests. Effective NOx reduction occurred over a temperature range of 1100~1350 K at cylinder injections where about 34% NOx reduction was achieved with ${\beta}$=1.5 and cylinder cooling at optimum flow conditions. The effects of simulated engine cylinder and exhaust parts, initial NOx levels, molar ratios and engine speeds on NOx reduction potential are discussed following temperature gradients and diesel engine environments. A staged injection by $NH_3$ and diesel fuel additive is tested for further NOx reduction, and more discussed for practical implication.

• Journal of the Korean Geosynthetics Society
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• v.7 no.2
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• pp.15-21
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• 2008

The advantages of prefabricated vertical drains over conventional sand drains include their relatively low costs, less disturbance to the soil mass, the easinees of installation, and their flexibility which ensures the integrity of the drains during installation. This study tested the change of discharge capacities with respect to the hydraulic gradients for each lateral pressure. From the test results, as increases the overburden pressure, the clay soil is being consolidated, and also lateral pressure to the PVD specimen is increased. Therefore, the discharge capacity is decreased. The size of opening space in the core of PVDs is proportionally related to the discharge capacity. The numerical analysis was performed with utilizing computer simulation with considering field conditions. The results of numerical analysis are compared well with the field measurements.

• Wind and Structures
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• v.6 no.6
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• pp.485-498
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• 2003

This paper presents a mechanical model of Rain-Wind Induced Vibration (RWIV) of stay cables. It is based on the physical interpretation of the phenomenon as given in Cosentino, et al. (2003, referred as Part I). The model takes into account all the main forces acting on cable, on the upper water rivulet (responsible of the excitation) and the cable-rivulet interaction. It is a simplified (cable cross-sectional and deterministic) representation of the actual (stochastic and three-dimensional) phenomenon. The cable is represented by its cross section and it is subjected to mechanical and aerodynamic (considering the rivulet influence) forces. The rivulet is supposed to oscillate along the cable circumference and it is subjected to inertial and gravity forces, pressure gradients and air-water-cable frictions. The model parameters are calibrated by fitting with experimental results. In order to validate the proposed model and its physical basis, different conditions (wind speed and direction, cable frequency, etc.) have been numerically investigated. The results, which are in very good agreement with the RWIV field observations, confirm the validity of the method and its engineering applicability (to evaluate the RWIV sensitivity of new stays or to retrofit the existing ones). Nevertheless, the practical use of the model probably requires a more accurate calibration of some parameters through new and specifically oriented wind tunnel tests.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.110-116
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• 2016

Autonomous vehicles must obey the traffic laws in order to drive actual roads. Traffic signs erected at the side of roads explain the road traffic information or regulations. Therefore, traffic sign recognition is necessary for the autonomous vehicles. In this paper, color characteristics are first considered to detect traffic sign candidates. Subsequently, we establish HOG (Histogram of Oriented Gradients) features from the detected candidate and recognize the traffic sign through a SVM (Support Vector Machine). However, owing to various circumstances, such as changes in weather and lighting, it is difficult to recognize the traffic signs robustly using only SVM. In order to solve this problem, we propose a tracking algorithm with RANSAC-based motion estimation. Using two-point motion estimation, inlier feature points within the traffic sign are selected and then the optimal motion is calculated with the inliers through a bundle adjustment. This approach greatly enhances the traffic sign recognition performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3712-3729
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• 2020

Smoke detection is helpful for early fire detection. With its large coverage area and low cost, vision-based smoke detection technology is the main research direction of outdoor smoke detection. We propose a two-stage smoke detection method combined with block Deep Normalization and Convolutional Neural Network (DNCNN) and visual change image. In the first stage, each suspected smoke region is detected from each frame of the images by using block DNCNN. According to the physical characteristics of smoke diffusion, a concept of visual change image is put forward in this paper, which is constructed by the video motion change state of the suspected smoke regions, and can describe the physical diffusion characteristics of smoke in the time and space domains. In the second stage, the Support Vector Machine (SVM) classifier is used to classify the Histogram of Oriented Gradients (HOG) features of visual change images of the suspected smoke regions, in this way to reduce the false alarm caused by the smoke-like objects such as cloud and fog. Simulation experiments are carried out on two public datasets of smoke. Results show that the accuracy and recall rate of smoke detection are high, and the false alarm rate is much lower than that of other comparison methods.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.345-351
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• 2014

This paper presents pedestrian recognition to improve performance for vehicle safety system or surveillance system. Pedestrian detection method using HOG (Histograms of Oriented Gradients) has showed 90% recognition rate. But if someone takes a picture in the rain, the image may be distorted by rain streaks and recognition rate goes down by 62%. To solve this problem, we applied image decomposition method using MCA (Morphological Component Analysis). In this case, rain removal method improves recognition rate from 62% to 70%. However, it is difficult to apply conventional image decomposition method using MCA on vehicle safety system or surveillance system as conventional method is too slow for real-time system. To alleviate this issue, we propose a rain removal method by using low-pass filter and DCT (Discrete Cosine Transform). The DCT helps separate the image into rain components. The image is removed rain components by Butterworth filtering. Experimental results show that our method achieved 90% of recognition rate. In addition, the proposed method had accelerated processing time to 17.8ms which is acceptable for real-time system.

• Journal of IKEEE
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• v.16 no.3
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• pp.182-188
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• 2012

Here we propose an image quality assessment (IQA) based on histogram of oriented gradients (HOG). This method makes use of the characteristic that the histogram of gradient image describes the state of input image. In the proposed method, the image quality is derived by the slope of the HOG obtained from the target image. The line representing the HOG is measured by a random sample consensus (RANSAC) on the HOG. Simulation results based on the LIVE image quality assessment database suggest that the proposed method aligns better with how the human visual system perceives image quality than several state-of-the-art IQAs.

• Journal of Preventive Medicine and Public Health
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• v.53 no.4
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• pp.220-227
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• 2020

Objectives: The aim of this study was to assess how different social determinants of health (SDoH) may be related to variability in coronavirus disease 2019 (COVID-19) rates in cities and towns in Massachusetts (MA). Methods: Data about the total number of cases, tests, and rates of COVID-19 as of June 10, 2020 were obtained for cities and towns in MA. The data on COVID-19 were matched with data on various SDoH variables at the city and town level from the American Community Survey. These variables included information about income, poverty, employment, renting, and insurance coverage. We compared COVID-19 rates according to these SDoH variables. Results: There were clear gradients in the rates of COVID-19 according to SDoH variables. Communities with more poverty, lower income, lower insurance coverage, more unemployment, and a higher percentage of the workforce employed in essential services, including healthcare, had higher rates of COVID-19. Most of these differences were not accounted for by different rates of testing in these cities and towns. Conclusions: SDoH variables may explain some of the variability in the risk of COVID-19 across cities and towns in MA. Data about SDoH should be part of the standard surveillance for COVID-19. Efforts should be made to address social factors that may be putting communities at an elevated risk.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1760-1778
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• 2018

For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.