• Journal of Korea Society of Industrial Information Systems
• /
• v.6 no.3
• /
• pp.115-122
• /
• 2001

A scene change detection is an important step for video indexing and retrieval. This paper proposes an algorithm by a phased algorithm for fast and accurate detection of abrupt scene changes in an MPEG compressed domain with minimal decoding requirements and computational effort. The proposed method compares two successive I-frames for locating a scene change occurring within the GOP and uses macroblock-coded type information contained in B-frames to detect the exact frame where the scene change occurred. The algorithm has the advantage of speed, simplicity and accuracy. In addition, it requires less amount of storage. The experiment results demonstrate that the proposed algorithm has better detection performance, such as precision and recall rate, than the existing method using all DC images.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2000.04a
• /
• pp.235-241
• /
• 2000

This article suggests integrated neural network models for the interest rate forecasting using change point detection. The basic concept of proposed model is to obtain intervals divided by change point, to identify them as change-point groups, and to involve them in interest rate forecasting. the proposed models consist of three stages. The first stage is to detect successive change points in interest rate dataset. The second stage is to forecast change-point group with data mining classifiers. The final stage is to forecast the desired output with BPN. Based on this structure, we propose three integrated neural network models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported neural network model, (2) case based reasoning (CBR)-supported neural network model and (3) backpropagation neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. This article is then to examine the predictability of integrated neural network models for interest rate forecasting using change-point detection.

• The Journal of Korean Physical Therapy
• /
• v.22 no.4
• /
• pp.65-71
• /
• 2010

Purpose: The aim of this study was to describe the effects of conservative treatment intervention for individual with scoliosis. Methods: Studies were selected through a search of computerized databases of the literature (KERIS, 2000-2010) using "early detection", "conservative treatment", "exercise", "physical therapy", "manipulation", "chiropractic", "therapy", "taping" and "orthosis" as keywords. Selected articles were classified by research design and statistical methods. Results: Application of the search strategy to the KERIS databases resulted in 132 articles. Based on titles and abstracts, 17 studies were selected, excluding articles of overlapping study, surgery, pharmacologic therapy and no correcting aim under conservative treatment. Among the 17 selected studies, the majorityof study design consisted of one group pretest-posttest design and additionally most of these studies were paired (or independent) t-test. The most frequently used intervention was exercise therapy. Conclusion: All articles showed that interventions were effective. Thus, early detection of scoliosis may be connected participation of early conservative treatment. It is important to reduce prevalence of scoliosis in adolescents using regular evaluation as an effective measure.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.7
• /
• pp.4369-4371
• /
• 2013

Objective: To evaluate the association of a diagnosis of lung cancer and combined detection of serum carcinoembryonic antigen (CEA), carbohydrateantigen 19-9 (CA19-9), neuron specific enolase (NSE) as well as the cytokeratin 19 fragment (CYFRA21-1). Methods: Serum CEA, CA19-9, NSE and CYFRA21-1 were assessed in 150 patients with lung cancer, 100 patients with benign lung disease and 100 normal control subjects, and differences of expression were compared in each group, and joint effects of these tumor markers in the diagnosis of lung cancer were analyzed. Results: Serum CEA, CA19-9, NSE and CYFRA21-1 in patients with lung cancer were significantly higher than those with benign lung disease and normal controls (p<0.01). It is suggested that these four tumor markers combined together could produce a positive detection rate of 90.2%, significantly higher than that of any single test. Conclusion: Combination detection of CEA, CA19-9, NSE and CYFRA21-1 could significantly improve the sensitivity and specificity in diagnosis of lung cancer, and could be important in early detection.

• ETRI Journal
• /
• v.41 no.6
• /
• pp.797-810
• /
• 2019

Image saliency detection is the basis of perceptual image processing, which is significant to subsequent image processing methods. Most saliency detection methods can detect only a single object with a high-contrast background, but they have no effect on the extraction of a salient object from images with complex low-contrast backgrounds. With the prior knowledge, this paper proposes a method for detecting salient objects by combining the boundary contrast map and the geodesics-like maps. This method can highlight the foreground uniformly and extract the salient objects efficiently in images with low-contrast backgrounds. The classical receiver operating characteristics (ROC) curve, which compares the salient map with the ground truth map, does not reflect the human perception. An ROC curve with distance (distance receiver operating characteristic, DROC) is proposed in this paper, which takes the ROC curve closer to the human subjective perception. Experiments on three benchmark datasets and three low-contrast image datasets, with four evaluation methods including DROC, show that on comparing the eight state-of-the-art approaches, the proposed approach performs well.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.5
• /
• pp.423-428
• /
• 2005

This paper proposes a new edge detection method using a $3{\times}3$ ideal binary pattern and lookup table (LUT) for the mobile robot localization without any parameter adjustments. We take the mean of the pixels within the $3{\times}3$ block as a threshold by which the pixels are divided into two groups. The edge magnitude and orientation are calculated by taking the difference of average intensities of the two groups and by searching directional code in the LUT, respectively. And also the input image is not only partitioned into multiple groups according to their intensity similarities by the histogram, but also the threshold of each group is determined by fuzzy reasoning automatically. Finally, the edges are determined through non-maximum suppression using edge confidence measure and edge linking. Applying this edge detection method to the mobile robot localization using projective invariance of the cross ratio. we demonstrate the robustness of the proposed method to the illumination changes in a corridor environment.

• Journal of Magnetics
• /
• v.21 no.2
• /
• pp.173-178
• /
• 2016

Six-step commutation control widely used in brushless DC (BLDC) motor can be applied to consequent pole permanent magnet (CPPM) belt starter generator (BSG) with trapezoidal back electromotive force (EMF) in the starter state. However, rotor position detection with three Hall sensors in BLDC motor can hardly be employed in CPPM BSG due to asymmetric flux distribution in each pole side of CPPM BSG. This paper presents a low-cost rotor position detection method for CPPM BSG in which six Hall sensors are proposed to be used based on the analysis of flux distribution by 3D FEA. In the method, the six Hall sensors are divided into three groups and two signals in each group are combined through performing logic operations. In addition, offset angle between back EMF and the related Hall signal can be compensated by moving the Hall sensors. Experiments of a 2 kW CPPM BSG prototype have also been performed to verify the proposed method.

• Journal of the Institute of Convergence Signal Processing
• /
• v.5 no.3
• /
• pp.223-229
• /
• 2004

Recently, OFDM and STC techniques have been considered to be candidate to support multimedia services in the next generation mobile radio communications and have been developed the many communications systems in order to achieve the high data rates. In this paper, we propose the Trellis-Coded Differential Space Time Modulation-OFDM system with multiple symbol detection. The Trellis-code performs the set partition with unitary group codes. The Viterbi decoder containing new branch metrics is introduced in order to improve the bit error rate (BER) in the differential detection of the unitary differential space time modulation. Also, we describe the Viterbi algorithm in order to use this branch metrics. Our study shows that such a Viterbl decoder improves BER performance without sacrificing bandwidth and power efficiency.

• Journal of Dairy Science and Biotechnology
• /
• v.29 no.2
• /
• pp.43-49
• /
• 2011

The increasing number of analytes in concern and the alarming health and environmental consequences have required effective means of monitoring for safety control. Biosensors offer advantages as alternatives to conventional analytical methods because of their inherent specificity, simplicity, and quick response. Colorimetric biosensor, one of biosensor group, is one of the easiest and the most convenient methods because detection can be done using naked eye. Recently, a novel method for rapid detection and read-out of specific immunoassays with naked eye using polydiacetylene (PDA) was developed. Polydiacetylene has recently been in the limelight as a transducing materials because of its special features that allow optical transduction of sensory signals and inherent simplicity and ease of use in supramolecular chemistry. Various forms of PDA are used as a sensor platform for detection of various biological analytes such as viruses, DNA, proteins, bacteria and hazardous molecules.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.17 no.6
• /
• pp.41-56
• /
• 2007

In this paper, we propose a specification-based intrusion detection system for WIPI(Wireless Internet Platform for Interoperability). In proposing the system, we focused on providing lightweight code, supporting multiple languages and hardware independence. The proposed system is based on an algorithm which detects an intrusion to main API of WIPI-HAL(Handset Adaptation Layer) and defines the prototype of mIDS(mobile IDS) API group that it can be added on the HAL. Moreover, we prove apply possibility through a WIPI emulator using java library.