• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.5
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• pp.271-279
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• 2014

In this paper, the two design techniques of the embedded system which provides a wireless image observation with temporary ad-hoc network are proposed and developed. The first method is based on the embedded system design technique for a nearly real-time wireless short observation application, having a specific remote monitoring node with a built-in image processing function, and having the maximum rate of 1 fps (frame per second) wireless image transmission capability of a $160{\times}128$size image. The second technique uses the embedded system for a general wireless long observation application, consisting of the main node, the remote monitoring node, and the system controller with built-in image processing function, and the capability of the wireless image transmission rate of 1/3 fps. The proposed system uses the wireless ad-hoc network which is widely accepted as a short range, low power, and bidirectional digital communication, the hardware are consisted of the general developed modules, a small digital camera, and a PC, and the embedded software based upon the Zigbee stack and the user interface software are developed and tested on the implemented module. The wireless environment analysis and the performance results are presented.

• Journal of the Korean Society of Radiology
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• v.7 no.4
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• pp.277-284
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• 2013

This study aims to find out geometric parameters which practitioner adjustable to reduce dose in coronary angiography. We take fluoroscopy and cine exposure by use of phantom, and got dose use the dose-area product(DAP) meter of angiography device, than convert DAP to effective dose. As results, Cine exposure shows higher dose measurement about 6-7 times than fluoroscopy. Dose in frame per second(FPS) mode could be decrease down to 70%, as lower FPS. In view of X-ray tube angle, LAO $45^{\circ}$+Caudal $30^{\circ}$ shows highest dose measurement. More use of Collimator, lower dose measurement. Source-image intensifier distance(SID) get longer to 10cm, dose of each fluoroscopy and cine exposure increase up to 25-30%. Image magnification of field of view(FOV) could increase dose up to 1.21-2 times. Also table-image intensifier distance get longer to 10cm, dose increased 1.11-1.25 times. Practitioner can adjust several geometric parameters, as FPS mode, tube angle, Collimation, SID, table-image intensifier distance, FOV. And each factors can reduce radiation dose in coronary angiography.

• Journal of KIISE
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• v.42 no.5
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• pp.566-572
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• 2015

We proposed a novel energy optimization technique for smartphone GPUs, more aggressively lowering the GPU frequency while obtaining higher energy efficiency with a negligible negative impact on the GPU performance. In order to achieve the Quality of Service (QoS) specified by the smartphone application, the proposed optimization technique employed the minimal acceptable GPU frequency based on average Frames per Second (FPS) for each GPU frequency level. Our experimental results on a smartphone development board showed that the proposed technique can reduce the GPU energy consumption by up to 23% over the default DVFS algorithm with only a 0.45 frame drop.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1017-1021
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• 2013

The traffic signal has been widely used in the transport system with a fixed time interval currently. This kind of setting time was determined based on experience for vehicles to generate a waiting time while allowing pedestrians crossing the street. However, this strict setting causes inefficient problems in terms of economic and safety crossing. In this research, we propose a monitoring algorithm to detect, track and check pedestrian crossing the crosswalk by the patterns of behavior. This monitoring system ensures the safety for pedestrian and keeps the traffic flow in efficient. In this algorithm, pedestrians are detected by using HOG feature which is robust to illumination changes in outdoor environment. According to a complex computation, the parallel process with the GPU as well as CPU is adopted for real-time processing. Therefore, pedestrians are tracked by the relationship of hue channel in image sequence according to the predefined pedestrian zone. Finally, the system checks the pedestrians' crossing on the crosswalk by its HOG based behavior patterns. In experiments, the parallel processing by both GPU and CPU was performed so that the result reaches 16 FPS (Frame Per Second). The accuracy of detection and tracking was 93.7% and 91.2%, respectively.

• ETRI Journal
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• v.44 no.5
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• pp.849-858
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• 2022

Dynamic voltage frequency scaling (DVFS) has been widely adopted for runtime power management of various processing units. In the case of neural processing units (NPUs), power management of neural network applications is required to adjust the frequency and voltage every layer to consider the power behavior and performance of each layer. Unfortunately, DVFS is inappropriate for layer-wise run-time power management of NPUs due to the long latency of voltage scaling compared with each layer execution time. Because the frequency scaling is fast enough to keep up with each layer, we propose a layerwise dynamic frequency scaling (DFS) technique for an NPU. Our proposed DFS exploits the highest frequency under the power limit of an NPU for each layer. To determine the highest allowable frequency, we build a power model to predict the power consumption of an NPU based on a real measurement on the fabricated NPU. Our evaluation results show that our proposed DFS improves frame per second (FPS) by 33% and saves energy by 14% on average, compared with DVFS.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.1-8
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• 2023

In this paper, we propose a black ice detection platform framework using Convolutional Neural Networks (CNNs). To overcome black ice problem, we introduce a real-time based early warning platform using CNN-based architecture, and furthermore, in order to enhance the accuracy of black ice detection, we apply a multi-scale dilation convolution feature fusion (MsDC-FF) technique. Then, we establish a specialized experimental platform by using a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Experimental results of a real-time black ice detection platform show the better performance of our proposed network model compared to conventional image segmentation models. Our proposed platform have achieved real-time segmentation of road black ice areas by deploying a road black ice area segmentation network on the edge device Jetson Nano devices. This approach in parallel using multi-scale dilated convolutions with different dilation rates had faster segmentation speeds due to its smaller model parameters. The proposed MsCD-FF Net(2) model had the fastest segmentation speed at 5.53 frame per second (FPS). Thereby encouraging safe driving for motorists and providing decision support for road surface management in the road traffic monitoring department.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.4 s.148
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• pp.422-430
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• 2006

The horn and movable parts around the gap of the conventional semi-spade rudder are visualized by high speed CCD camera with the frame rate of 4000 fps (frame per second) to study the unsteady cavity pattern on the rudder surface and gap. In addition, the pressure measurements are conducted on the rudder surface and inside the gap to find out the characteristics of the flow behavior. The rudder without propeller wake is tested at the range of $1.0{\leq}{\sigma}_v\;1.6$ and at the rudder deflection angle of $-8{\leq}{\theta}{\leq}10^{\circ}$. The time resolved cavity images are captured and show strong cavitation around the rudder gap in all deflection angles. As the deflection angle gets larger, the flow separated from the horn surface increases the strength of cavitation. The accelerated flow along the horn decreases its pressure and the separated flow from the horn increases the pressure abruptly. The pressure distribution inside the gap reveals the flow moving from the pressure to suction side. In the negative deflection angle, the turning area on the movable part initiates the flow separation and cavitation on it.

• Korean Journal of Applied Biomechanics
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• v.24 no.2
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• pp.181-187
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• 2014

In this study, a real-time evaluation system for quantitative dynamic fitting during pedaling was developed. The system is consisted of LED markers, a digital camera connected to a computer and a marker detecting program. LED markers are attached to hip, knee, ankle joint and fifth metatarsal in the sagittal plane. Playstation3 eye which is selected as a main digital camera in this paper has many merits for using motion capture, such as high FPS (Frame per second) about 180FPS, $320{\times}240$ resolution, and low-cost with easy to use. The maker detecting program was made by using Labview2010 with Vision builder. The program was made up of three parts, image acquisition & processing, marker detection & joint angle calculation, and output section. The digital camera's image was acquired in 95FPS, and the program was set-up to measure the lower-joint angle in real-time, providing the user as a graph, and allowing to save it as a test file. The system was verified by pedalling at three saddle heights (knee angle: 25, 35, $45^{\circ}$) and three cadences (30, 60, 90 rpm) at each saddle heights by using Holmes method, a method of measuring lower limbs angle, to determine the saddle height. The result has shown low average error and strong correlation of the system, respectively, $1.18{\pm}0.44^{\circ}$, $0.99{\pm}0.01^{\circ}$. There was little error due to the changes in the saddle height but absolute error occurred by cadence. Considering the average error is approximately $1^{\circ}$, it is a suitable system for quantitative dynamic fitting evaluation. It is necessary to decrease error by using two digital camera with frontal and sagittal plane in future study.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.1-10
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• 2014

This paper proposes a parallel implementation of the video based 4-stage fire detection algorithm using a general-purpose graphics processing unit (GPGPU) to support real-time processing of the high computational algorithm. In addition, this paper compares the performance of the GPGPU based fire detection implementation with that of the CPU implementation to show the effectiveness of the proposed method. Experimental results using five fire included videos with an SXGA ($1400{\times}1050$) resolution, the proposed GPGPU implementation achieves 6.6x better performance that the CPU implementation, showing 30.53ms per frame which satisfies real-time processing (30 frames per second, 30fps) of the fire detection algorithm.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.1-10
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• 2015

In this paper, we propose an efficient parallel implementation method of a widely used complex four-stage fire detection algorithm using a graphics processing unit (GPU) to improve the performance of the algorithm and analyze the performance of the parallel implementation method. In addition, we use seven different resolution videos (QVGA, VGA, SVGA, XGA, SXGA+, UXGA, QXGA) as inputs of the four-stage fire detection algorithm. Moreover, we compare the performance of the GPU-based approach with that of the CPU implementation for each different resolution video. Experimental results using five different fire videos with seven different resolutions indicate that the execution time of the proposed GPU implementation outperforms that of the CPU implementation in terms of execution time and takes a 25.11ms per frame for the UXGA resolution video, satisfying real-time processing (30 frames per second, 30fps) of the fire detection algorithm.