• Molecules and Cells
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• v.42 no.1
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• pp.45-55
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• 2019

The liver is involved in a wide range of activities in vertebrates and some other animals, including metabolism, protein synthesis, detoxification, and the immune system. Until now, various methods have been devised to study liver diseases; however, each method has its own limitations. In situ liver perfusion machinery, originally developed in rats, has been successfully adapted to mice, enabling the study of liver diseases. Here we describe the protocol, which is a simple but widely applicable method for investigating the liver diseases. The liver is perfused in situ by cannulation of the portal vein and suprahepatic inferior vena cava (IVC), with antegrade closed circuit circulation completed by clamping the infrahepatic IVC. In situ liver perfusion can be utilized to evaluate immune cell migration and function, hemodynamics and related cellular reactions in each type of hepatic cells, and the metabolism of toxic or other compounds by changing the composition of the circulating media. In situ liver perfusion method maintains liver function and cell viability for up to 2 h. This study also describes an optional protocol using density-gradient centrifugation for the separation of different types of hepatic cells, allowing the determination of changes in each cell type. In summary, this method of in situ liver perfusion will be useful for studying liver diseases as a complement to other established methods.

• Steel and Composite Structures
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• v.38 no.3
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• pp.337-353
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• 2021

Micro-electro-mechanical systems (MEMS) are widely employed in sensors, biomedical devices, optic sectors, and micro-accelerometers. New reinforcement materials such as carbon nanotubes as well as graphene platelets provide stiffer structures with controllable mechanical specifications by changing the graphene platelet features. This paper deals with buckling analyses of functionally graded graphene platelets micro plates with two piezoelectric layers subjected to external applied voltage. Governing equations are based on Kirchhoff plate theory assumptions beside the modified couple stress theory to incorporate the micro scale influences. A uniform temperature change and external electric field are regarded along the micro plate thickness. Moreover, an external in-plane mechanical load is uniformly distributed along the micro plate edges. The Hamilton's principle is employed to extract the governing equations. The material properties of each composite layer reinforced with graphene platelets of the considered micro plate are evaluated by the Halpin-Tsai micromechanical model. The governing equations are solved by the Navier's approach for the case of simply-supported boundary condition. The effects of the external applied voltage, the material length scale parameter, the thickness of the piezoelectric layers, the side, the length and the weight fraction of the graphene platelets as well as the graphene platelets distribution pattern on the critical buckling temperature change and on the critical buckling in-plane load are investigated. The outcomes illustrate the reduction of the thermal buckling strength independent of the graphene platelets distribution pattern while meanwhile the mechanical buckling strength is promoted. Furthermore, a negative voltage, -50 Volt, strengthens the micro plate stability against the thermal buckling occurrence about 9% while a positive voltage, 50 Volt, decreases the critical buckling load about 9% independent of the graphene platelet distribution pattern.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.63-73
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• 2022

A more accurate understanding of the irrigation water supply is necessary for efficient agricultural water management. Although we measure water levels in an irrigation canal using ultrasonic water level gauges, some errors occur due to malfunctions or the surrounding environment. This study aims to apply CNN (Convolutional Neural Network) Deep-learning-based image classification and segmentation models to the irrigation canal's CCTV (Closed-Circuit Television) images. The CCTV images were acquired from the irrigation canal of the agricultural reservoir in Cheorwon-gun, Gangwon-do. We used the ResNet-50 model for the image classification model and the U-Net model for the image segmentation model. Using the Natural Breaks algorithm, we divided water level data into 2, 4, and 8 groups for image classification models. The classification models of 2, 4, and 8 groups showed the accuracy of 1.000, 0.987, and 0.634, respectively. The image segmentation model showed a Dice score of 0.998 and predicted water levels showed R² of 0.97 and MAE (Mean Absolute Error) of 0.02 m. The image classification models can be applied to the automatic gate-controller at four divisions of water levels. Also, the image segmentation model results can be applied to the alternative measurement for ultrasonic water gauges. We expect that the results of this study can provide a more scientific and efficient approach for agricultural water management.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.54-63
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• 2023

Pedestrian traffic needs to be accurately quantified to predict effectively pedestrian traffic accidents, however, pedestrian traffic is more difficult to measure than vehicle traffic. In this study, we suggest the time-and cost-effective application of mobile closed-circuit television (CCTV) using a smartphone as an alternative that can collect and analyze real-time data with little. In the present investigation, the pedestrian-vehicle conflict that can develop into an accident was defined as the pedestrian accident exposure. After installing mobile CCTV in 40 sections of Dongseong-ro, Daegu, the pedestrian accident exposure was estimated through negative binomial regression analysis using the collected data. The results of the analysis showed statistically significant changes in the pedestrian accident exposure variables. Based on the present results, a pedestrian accident exposure estimation model was developed which can be used in sections where pedestrian accidents may occur.

• Journal of IKEEE
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• v.27 no.4
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• pp.512-517
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• 2023

In this study, we propose a liquid crystal-based polarization control technology that can control polarization by adjusting the voltage applied to the liquid crystal, and apply it to a Closed-circuit Television (CCTV) to transmit only the desired angle of polarized light. CCTV with conventional polarizing films cannot control polarization because they focus on backlight compensation, so light reflected from the water surface or highlights reflected from vehicles interfere with subject identification. However, the Vertical Alignment mode allows the polarization to be adjusted electrically, so that only the polarized light at the user's desired angle is transmitted, eliminating reflected highlights. The images obtained using this technique are optimized by computer software. Liquid crystal polarization panels, which can electrically control the polarization angle, transmittance, and polarization rate, have been applied to polarized image monitoring device to improve subject identification in conventional CCTV.

• Journal of the Korean Applied Science and Technology
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• v.40 no.4
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• pp.786-796
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• 2023

The purpose of this study was to examine the influencing factors of perceived safety for CCTV(Closed Circuit Television), and to confirm the correlation between fear of crime, social disorder, physical disorder in the community, and perceived safety for CCTV. Subjects were 140 students from one college located in H city using survey from June 17, 2022 to August 25, 2022. Data was analyzed by descriptive statistics, Pearson's correlation, and Stepwise multiple regression using the SPSS 23.0 program. As a result of the study, fear of crime was correlated with social disorder, physical disorder among community characteristics, and perceived safety of CCTV. Also, social disorder among community characteristics was correlated with physical disorder, perceived safety of CCTV, and physical disorder was correlated with perceived safety of CCTV. The factors affecting perceived safety for CCTV were fear of crime and social disorder, and the explanatory power was 57.2%(Adjusted R²=.572). In conclusion, it is necessary to improve the perceived safety of CCTV by improving the awareness of fear of crime and social disorder.

• Computers and Concrete
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• v.33 no.4
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• pp.425-443
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• 2024

Floods are among the most common natural hazards in urban areas. To mitigate the problems caused by flooding, unstructured data such as images and videos collected from closed circuit televisions (CCTVs) or unmanned aerial vehicles (UAVs) have been examined for flood management (FM). Many computer vision (CV) techniques have been widely adopted to analyze imagery data. Although some papers have reviewed recent CV approaches that utilize UAV images or remote sensing data, less effort has been devoted to studies that have focused on CCTV data. In addition, few studies have distinguished between the main research objectives of CV techniques (e.g., flood depth and flooded area) for a comprehensive understanding of the current status and trends of CV applications for each FM research topic. Thus, this paper provides a comprehensive review of the literature that proposes CV techniques for aspects of FM using ground camera (e.g., CCTV) data. Research topics are classified into four categories: flood depth, flood detection, flooded area, and surface water velocity. These application areas are subdivided into three types: urban, river and stream, and experimental. The adopted CV techniques are summarized for each research topic and application area. The primary goal of this review is to provide guidance for researchers who plan to design a CV model for specific purposes such as flood-depth estimation. Researchers should be able to draw on this review to construct an appropriate CV model for any FM purpose.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.80-87
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• 2006

SONY corporation preoccupies $80\%$ of a market of the CCD used in a CCTV system. The CCD of SONY have high duality which can not follow the progress of capability. But there are some problems which differ the clock frequency used in CCD from the frequency used in common video encoder. To get the result by using common video encoder, the system needs a scaler that could adjust image size and PLL that synchronizes CCD's with encoder's clock So, this paper proposes the video encoder that is activated at equal clock used in CCD without scaler and PLL. The encoder converts ITU-R BT.601 4:2:2 or ITU-R BT.656 inputs from various video sources into NTSC or PAL signals in CVBS. Due to variable clock, property of filters used in the encoder is automatically changed by clock and filters adopt multiplier-free structures to reduce hardware complexity. The hardware bit width of programmable digital filters for luminance and chrominance signals, along with other operating blocks, are carefully determined to produce hish-quality digital video signals of ${\pm}1$ LSB error or less. The proposed encoder is experimentally demonstrated by using the Altera Stratix EP1S80B953C6ES device.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.284-293
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• 2015

The objective of this paper is to determine the conditions of road surface by utilizing the images collected from closed-circuit television (CCTV) cameras installed on roadside. First, a technique was examined to detect wet surfaces at nighttime. From the literature reviews, it was revealed that image processing using polarization is one of the preferred options. However, it is hard to use the polarization characteristics of road surface images at nighttime because of irregular or no light situations. In this study, we proposes a new discriminant for detecting wet and dry road surfaces using CCTV image data at night. To detect the road surface conditions with night vision, we applied the wavelet packet transform for analyzing road surface textures. Additionally, to apply the luminance feature of night CCTV images, we set the intensity histogram based on HSI(Hue Saturation Intensity) color model. With a set of 200 images taken from the field, we constructed a detection criteria hyperplane with SVM (Support Vector Machine). We conducted field tests to verify the detection ability of the wet road surfaces and obtained reliable results. The outcome of this study is also expected to be used for monitoring road surfaces to improve safety.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.