• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1388-1395
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• 2020

Daily monitoring of the heart rate can facilitate detection of heart-related diseases in their early stages. Therefore, providing an easy-to-use and noninvasive heart rate monitoring system has been a very popular research topic in the field of healthcare. One of good candidate methods is to use commonly available cameras and extract information that can help to estimate heart rate from a human face. Generally, such information can be retrieved using two different approaches: photoplethysmography (PPG) and ballistocardiography (BCG). PPG exploits slight color changes caused by blood volume variations during heartbeats; thus, it tends to be vulnerable to unstable lighting conditions. BCG exploits subtle head motions caused by pumped blood travelling through the carotid artery during heartbeats; thus, it is vulnerable to the voluntary head movements that are not related to heartbeats. Nevertheless, most related works use either to estimate the heart rate. In this paper, we propose to combine two approaches to be robust to challenging conditions. Specifically, we explore possible ways to combine raw signals obtained from two approaches and verify that the proposed combination shows better accuracies under challenging conditions, such as voluntary head movements and ambient lighting changes.

• Smart Structures and Systems
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• v.6 no.4
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• pp.405-421
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• 2010

This paper proposes a method for early warning of hazard for pipelines. Many pipelines transport dangerous contents so that any damage incurred might lead to catastrophic consequences. However, most of these damages are usually a result of surrounding third-party activities, mainly the constructions. In order to prevent accidents and disasters, detection of potential hazards from third-party activities is indispensable. This paper focuses on recognizing the running of construction machines because they indicate the activity of the constructions. Acoustic information is applied for the recognition and a novel pipeline monitoring approach is proposed. Principal Component Analysis (PCA) is applied. The obtained Eigenvalues are regarded as the special signature and thus used for building feature vectors. One-class Support Vector Machine (SVM) is used for the classifier. The denoising ability of PCA can make it robust to noise interference, while the powerful classifying ability of SVM can provide good recognition results. Some related issues such as standardization are also studied and discussed. On-site experiments are conducted and results prove the effectiveness of the proposed early warning method. Thus the possible hazards can be prevented and the integrity of pipelines can be ensured.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.5
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• pp.29-36
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• 2002

In the maintenance and retrofit planning of a bridge system, the optimal strategy for inspection and repair are suggested by minimizing the expected total life-cycle cost, which includes the initial cost, the costs of inspection, repair, and failure. Degradation of seismic performance is modeled by using a damage function. And failure probability is computed according to the degree of damage detection by random vibration theory and the event tree analysis. As an example to illustrate the proposed approach, a 10-span continuous bridge structure is used. The numerical results show that the optimum number of the inspection and the repair are increased, as the seismic intensity is increased and the soil condition of a site becomes more flexible.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.10
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• pp.1503-1507
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• 2006

Goats' milk adulteration with cows' milk is becoming a big problem. In the past, the urea-polyacrylamide gel electrophoresis assay with different motility of ${\alpha}S1$-casein has been applied for the identification of cows' milk adulteration. The detection sensitivity is 1.0%. The aim of this study was to develop a faster and more sensitive method to detect cows' milk which may be present in adulterated goats' milk and goats' milk powder. The published primer was targeted at highly conserved regions in bovine mitochondrial DNA (a 271 bp amplicon). This amplicon was cloned and sequenced to further confirm bovine specific sequence. The chelex-100 was used to separate bovine somatic cells from goats' milk or goats' milk powder samples. Random sampling of different brands of goats' milk powder and tablets from various regions of Taiwan showed the adulterated rate was 20 out of 80 (25%) in goats' milk powders and 12 out of 24 (50%) in goats' milk tablets. With this system, as low as 0.1% cows' milk or cows' milk powder in goat milk or goat milk powder could be identified. This chelex DNA isolation approach provides a fast, highly reproducible and sensitive method for detecting the adulteration of goats' milk products.

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.29-34
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• 2015

Traffic lights are common in cities and are important cues for the path planning of intelligent vehicles. In this paper, we propose a robust and efficient algorithm for recognizing traffic lights from video sequences captured by a low cost off-the-shelf camera. Instead of using color information for recognizing traffic lights, a shape based approach is adopted. In learning and detection phase, Histogram of Oriented Gradients (HOG) feature is used and a cascade classifier based on Adaboost algorithm is adopted as the main classifier for locating traffic lights. To decide the color of the traffic light, a technique based on histogram analysis in HSV color space is utilized. Experimental results on several video sequences from typical urban environment prove the effectiveness of the proposed algorithm.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.506-513
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• 2014

In recent years, research on user's activity recognition using a smart phone has attracted a lot of attentions. A smart phone has various sensors, such as camera, GPS, accelerometer, audio, etc. In addition, smart phones are carried by many people throughout the day. Therefore, we can collect log data from smart phone sensors. The log data can be used to analyze user activities. This paper proposes an approach to inferring a user's physical activities based on the tri-axis accelerometer of smart phone. We propose recognition method for four activity which is physical activity; sitting, standing, walking, running. We have to convert accelerometer raw data so that we can extract features to categorize activities. This paper introduces a recognition method that is able to high detection accuracy for physical activity modes. Using the method, we developed an application system to recognize the user's physical activity mode in real-time. As a result, we obtained accuracy of over 80%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11B
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• pp.1020-1029
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• 2008

This paper proposes an high speed pattern matching algorithm and its implementation. The pattern matcher is used to check patterns from realtime input packet. The proposed algorithm can find exact string, range of string values, and combination of string values from input packet at high speed. Given string and rule set are modelled as a state transition graph which can find overlapped strings simultaneously, and the state transition graph is partitioned according to input implicants to reduce implementation complexity. The pattern matcher scheme uses the transformed state transition graph and input packet as an input. The pattern matcher was modelled and implemented in VHDL language. Experimental results show the proprieties of the proposed approach.

• Journal of Satellite, Information and Communications
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• v.11 no.2
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• pp.48-54
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• 2016

As the nonlinear viewing patterns are getting generalized, the needs for VOD service of consumers are increasing in TV, webTV. But today's VOD system is all automated, except the part for posting contents. This study proposes the method for automation of the content posting. For this we analyzed the broadcast program structures by genre in order to detect the transition point between the advertisement and the contents. It was found that regular black frames were set in the transition during fade in and out. We propose an efficient approach to automatically detect the black frames using RGB values of each frame that enable VOD content posting and replace an advertisement in VOD service.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_2
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• pp.643-651
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• 2012

Object recognition belongs to high-level processing that is one of the difficult and challenging tasks in computer vision. Digital photogrammetry based on the computer vision paradigm has begun to emerge in the middle of 1980s. However, the ultimate goal of digital photogrammetry - intelligent and autonomous processing of surface reconstruction - is not achieved yet. Object recognition requires a robust shape description about objects. However, most of the shape descriptors aim to apply 2D space for image data. Therefore, such descriptors have to be extended to deal with 3D data such as LiDAR(Light Detection and Ranging) data obtained from ALS(Airborne Laser Scanner) system. This paper introduces extension of chain code to 3D object space with hierarchical approach for segmenting point cloud data. The experiment demonstrates effectiveness and robustness of the proposed method for shape description and point cloud data segmentation. Geometric characteristics of various roof types are well described that will be eventually base for the object modeling. Segmentation accuracy of the simulated data was evaluated by measuring coordinates of the corners on the segmented patch boundaries. The overall RMSE(Root Mean Square Error) is equivalent to the average distance between points, i.e., GSD(Ground Sampling Distance).

• Nuclear Engineering and Technology
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• v.30 no.5
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• pp.435-443
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• 1998

Leak-before-break(LBB) approach has been shown to be both cost effective and risk reductive when applied to high energy Piping in nuclear Power Plants. For the Korean Next Generation Reactor (KNGR) development, LBB application is considered for the Main Steam Line(MSL) piping inside containment. Unlike the primary system leakages, the MSL leak detection systems must be based on principles other than radioactivity measurements. Among humidity, heat and acoustic noise currently being considered as indicators of leakage, we explored humidity as an effective one and developed ceramic-based humidity sensor which can be qualified for LBB applications. The ceramic material, sintered and annealed MgCr$_2$O$_4$-TiO$_2$, is shown to increase its electrical conductivity drastically upon water vapor adsorption over the entire temperature range of interest. With this ceramic sensor specimen, we suggested installation-inside-the-piping method by which we can detect leakage more rapidly and sensitively. In this paper, we describe the progress in the development and characterization of ceramic humidity sensor for the LBB application to the MSL of KNGR.