• Bulletin of the Korean Chemical Society
• /
• v.33 no.2
• /
• pp.415-419
• /
• 2012

Electrochemical characteristics of nitrite ion were investigated at a poly(methylene blue)-modified glassy carbon electrode by cyclic voltammetry and differential pulse voltammetry. The poly(methylene blue)-modified glassy carbon electrode exhibited enhanced anodic signals for nitrite. The effects of key parameters on the detection of nitrite were evaluated at the modified electrode, such as pH, accumulation time, and scan rate. Under optimum condition, the chemically modified electrode can detect nitrite in the concentration range $2.0{\times}10^{-6}$ to $5.0{\times}10^{-4}$ M with the detection limit of $2.0{\times}10^{-6}$ M and a correlation coefficient of 0.999. The detection of nitrite using the chemically modified electrode was not affected by common ions such as $Na^+$, $K^+$, $Ca^{2+}$, $Cl^-$, $HPO_4^{2-}$ and $H_2PO_4^- $. The modified electrode showed good stability and reproducibility. The practical application of the present method was successfully applied to the determination of nitrite ion in cabbage samples.

• KIISE Transactions on Computing Practices
• /
• v.24 no.2
• /
• pp.59-66
• /
• 2018

In this paper, we propose a system to detect various damage automatically inflicted on road pavement by collecting and analyzing data from acceleration and camera sensors in real time. The proposed system sends the collected images, acceleration signals, and GPS coordinates to the road manager and the database in the remote server, shortly after detecting the damage to the road pavement. Our study makes three key contributions. The proposed system 1) enables road managers to maintain road conditions quickly, accurately, and conveniently; 2) allows road mangers to take care of various kinds of damage to the road pavement at the initial stage; and finally 3) even makes it possible to track the damage, which suggests that the integration of a high-level decision support function becomes affordable. We tested the sensitivity and precision of the proposed system against real-time data obtained from the vehicles driving on the highway at an average speed of 100 km/h. With ten iterations, the proposed system achieved an average sensitivity of 74% and an average precision of 84% in road pavement damage detection, which is comparable with the best competing schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.2
• /
• pp.800-816
• /
• 2018

In recent years, video surveillance research has been able to recognize various behaviors of pedestrians and analyze the overall situation of objects by combining image analysis technology and deep learning method. Human Activity Recognition (HAR), which is important issue in video surveillance research, is a field to detect abnormal behavior of pedestrians in CCTV environment. In order to recognize human behavior, it is necessary to detect the human in the image and to estimate the pose from the detected human. In this paper, we propose a novel approach for 2D Human Pose Estimation based on object detection using RGB-D information. By adding depth information to the RGB information that has some limitation in detecting object due to lack of topological information, we can improve the detecting accuracy. Subsequently, the rescaled region of the detected object is applied to ConVol.utional Pose Machines (CPM) which is a sequential prediction structure based on ConVol.utional Neural Network. We utilize CPM to generate belief maps to predict the positions of keypoint representing human body parts and to estimate human pose by detecting 14 key body points. From the experimental results, we can prove that the proposed method detects target objects robustly in occlusion. It is also possible to perform 2D human pose estimation by providing an accurately detected region as an input of the CPM. As for the future work, we will estimate the 3D human pose by mapping the 2D coordinate information on the body part onto the 3D space. Consequently, we can provide useful human behavior information in the research of HAR.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2014.06a
• /
• pp.258-261
• /
• 2014

The era of realistic broadcast with high fidelity has come after the wide-spread distribution of UHD display and the transmission of UHD experimental broadcast in CATV. However, UHD broadcast now has constraint because it requires much amount of bandwidth and data in broadcasting transmission and production system. Not only HEVC(High Efficiency Video Codec) which has more than two times higher compression rate but also cloud-based editing system would be the key to solve the problems above. Also, fast scene change detection of videos is needed to index and search UHD videos smoothly. In this paper, therefore, a method is proposed to index and search the scene change information of large volume UHD videos compressed with high-efficiency codec. Application usages of fast detection of scene change information in various UHD video environments are considered by using this algorithm.

• Journal of KIISE:Software and Applications
• /
• v.30 no.7_8
• /
• pp.773-779
• /
• 2003

Locating exact position of facial components is a key preprocessing for realizing highly accurate and reliable face recognition schemes. In this paper, we propose a simple but powerful method for detecting isolated facial components such as eyebrows, eyes, and a mouth, which are horizontally oriented and have relatively dark gray levels. The method is based on the shape-resolving locally optimum thresholding that may guarantee isolated detection of each component. We show that pure facial regions can be determined by grouping facial features satisfying simple geometric constraints on unique facial structure. In the test for over 1000 images in the AR -face database, pure facial regions were detected correctly for each face image without wearing glasses. Very few errors occurred in the face images wearing glasses with a thick frame because of the occluded eyebrow -pairs. The proposed scheme may be best suited for the later stage of classification using either the mappings or a template matching, because of its capability of handling rotational and translational variations.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.11
• /
• pp.196-201
• /
• 2016

Digital watermarking is a technique used to hide information within digital media. Digital watermarking techniques can be classified as either robust watermarking or fragile watermarking. Robust watermarking techniques are generally used for the purpose of copyright protection. In addition, fragile watermarking techniques are used for the authentication and integrity verification of a digital image. Therefore, fragile watermarks should be easily breakable for trivial tampering of a watermarked image. This paper proposes an efficient fragile watermarking method for image tamper detection in the spatial domain. In the proposed method, a hash code and symmetric key encryption algorithm are used. The proposed method of inserting a watermark by dividing the original image into many blocks of small sizes is not weak against attacks, such as cut and paste. The proposed method can detect the manipulated parts of a watermarked image without testing the entire block of the image.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.7
• /
• pp.47-55
• /
• 2020

In this paper, we propose one stage multi-scale face detector based Fully Convolution Network using anchor free method. Recently almost all state-of-the-art face detectors which predict location of faces using anchor-based methods rely on pre-defined anchor boxes. However this face detectors need to hyper-parameters and additional computation in training. The key idea of the proposed method is to eliminate hyper-parameters and additional computation using anchor free method. To do this, we apply two ideas. First, by eliminating the pre-defined set of anchor boxes, we avoid the additional computation and hyper-parameters related to anchor boxes. Second, our detector predicts location of faces using multi-feature maps to reduce foreground/background imbalance issue. Through Quantitative evaluation, the performance of the proposed method is evaluated and analyzed. Experimental results on the FDDB dataset demonstrate the effective of our proposed method.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.18
• /
• pp.7583-7588
• /
• 2014

Background: Colorectal cancer (CRC) is a major cause of cancer-related death and cancer-related incidence worldwide. The potential of microRNA-21 (miR-21) as a biomarker for CRC detection has been studied in several studies. However, the results were inconsistent. Therefore, we conducted the present meta-analysis to systematically assess the diagnostic value of miR-21 for CRC. Materials and Methods: Using a random-effect model, the pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were calculated to evaluate the diagnostic performance of miR-21 for CRC. A summary receiver operating characteristic (SROC) curve and an area under the curve (AUC) were also generated to assess the diagnosis accuracy of miR-21 for CRC. Q test and I2 statistics were used to assess between-study heterogeneity. Publication bias was evaluated by the Deeks' funnel plot asymmetry test. Results: A total of 986 CRC patients and 702 matched healthy controls from 8 studies were involved in the meta-analysis. The pooled results for SEN, SPE, PLR, NLR, DOR, and AUC were 57% (95%CI: 39%-74%), 87% (95%CI: 78%-93%), 4.4 (95%CI: 2.4-8.0), 0.49 (95%CI: 0.32-0.74), 9 (95%CI: 4-22), and 0.83 (95%CI: 0.79-0.86), respectively. Subgroup analyses further suggested that blood-based studies showed a better diagnostic accuracy compared with feces-based studies, indicating that blood may be a better matrix for miR-21 assay and CRC detection. Conclusions: Our findings suggest that miR-21 has a potential diagnostic value for CRC with a moderate level of overall diagnostic accuracy. Hence, it could be used as auxiliary means for the initial screening of CRC and avoid unnecessary colonoscopy, which is an invasive and expensive procedure.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.2
• /
• pp.81-88
• /
• 2018

Spectrum sensing, the key technology of the cognitive radio networks, is used by a secondary user to determine the frequency state of a primary user. The energy detection in the spectrum sensing determines the presence or absence of a primary user according to the intensity of the allocated channel signal. Since this technique simply uses the strength of the signal for spectrum sensing, it is difficult to detect the signal of a primary user in the low SNR band. In this paper, we propose a way to combine spectrum sensing and support vector machine using wavelet packet decomposition to overcome performance degradation in low SNR band. In our proposed scheme, the sensing signals were extracted by wavelet packet decomposition and then used as training data and test data for support vector machine. The simulation results of the proposed scheme are compared with the energy detection using the AUC of the ROC curve and the accuracy according to the SNR band. With simulation results, we demonstrate that the proposed scheme show better determining performance than one of energy detection in the low SNR band.

• KSBB Journal
• /
• v.17 no.2
• /
• pp.158-161
• /
• 2002

In this study, a prototype fiber-optic biosensor was fabricated using the inhibition of enzyme reaction by organophosphorus compounds to detect organophosphorus compounds, which is nervous toxic material an? is used as chemical weapon and pesticide. Enzyme, substrate, and inhibitor for enzyme reaction were acetylcholinesterase (key enzyme in nervous cell), acetylthiocholine iodide, and paraoxon (a kind of organophosphorus compounds), respectively. The detection principle of sensor is the detection of enzyme reaction inhibited by organophosphorus compounds by the quantitative measurement of acetic acid, which was achieved by absorbance measurement using litmus solution that maximum absorbance band is changed by pH. To fabricate prototype fiber-optic biosensor, high bright LED and photodiode was used as light source and light intensity detector, respectively. From the experimental results using a prototype biosensor, the linear change of sensor signal was obtained in a range of 0-2 ppm inhibitor concentrations. From these results, it was verified that the quantitative measurement of organophosphorus compounds could be achieved fast (within 2 minutes) and accurately by a prototype fiber-optic biosensor.