A method to convert non-numeric characters into numerical values in dynamic time warping for string matching

Dynamic time warping (DTW) is one of the well-known algorithms for measuring similarity between two temporal sequences, and it can be used for character matching. It uses a distance of two character strings. However, since the characters are non-numeric, it must be assigned to numerical values to calculate a distance between two character strings. Therefore, in this paper, we propose a method to convert non-numeric characters into numerical values in dynamic time warping for string matching. The proposed method uses normalized correlation coefficient, and it makes DTW gives more accurate results. Experimental results show that the proposed method gives excellent results

Continuity of the Explosive Percolation Transition

The explosive percolation problem on the complete graph is investigated via extensive numerical simulations. We obtain the cluster-size distribution at the moment when the cluster size heterogeneity becomes maximum. The distribution is found to be well described by the power-law form with the decay exponent $\tau = 2.06(2)$, followed by a hump. We then use the finite-size scaling method to make all the distributions at various system sizes up to $N=2^{37}$ collapse perfectly onto a scaling curve characterized solely by the single exponent $\tau$. We also observe that the instant of that collapse converges to a well-defined percolation threshold from below as $N\rightarrow\infty$. Based on these observations, we show that the explosive percolation transition in the model should be continuous, contrary to the widely-spread belief of its discontinuity.Comment: Some corrections during the revie

Estimation of object location probability for object detection using brightness feature only

Most existing object detection methods use features such as color, shape, and contour. If there are no consistent features can be used, we need a new object detection method. Therefore, in this paper, we propose a new method for estimating the probability that an object can be located for object detection and generating an object location probability map using only brightness in a gray image. To evaluate the performance of the proposed method, we applied it to gallbladder detection. Experimental results showed 98.02% success rate for gallbladder detection in ultrasonogram. Therefore, the proposed method accurately estimates the object location probability and effectively detected gallbladder

Determinants of Competitive Advantage for Sport Firms: Using Public Big Data in Korea

This study examines the determinants of competitive advantage with respect to economic performance of sport firms. Logit regressions estimated dependent variables of economic performance measures based on sales per capita of firms. Determinants of competitive advantage were estimated by efficiency indicators, organization characteristic indicators, and industry classification indicators. Increase in efficiency was a significant determinant of competitive advantage as well as organizational type, size of human resource, diversification of products, and sales growth rate. Operationalizing competitive advantage as outperforming the market average and better than the top 10%, the logit regression model provides means for sport firms to analyze industry data to evaluate their own performance. In particular, including efficiency estimates showed practical significance for market analysis

Vision-based Crack Identification on the Concrete Slab Surface using Fuzzy Reasoning Rules and Self-Organizing

Identifying cracks on the surface of concrete slab structure is important for structure stability maintenance. In order to avoid subjective visual inspection, it is necessary to develop an automated identification and measuring system by vision based method. Although there have been some intelligent computerized inspection methods, they are sensitive to noise due to the brightness contrast and objects such as forms and joints of certain size often falsely classified as cracks. In this paper, we propose a new fuzzy logic based image processing method that extracts cracks from concrete slab structure including small cracks that were often neglected as noise. We extract candidate crack areas by applying fuzzy method with three color channel values of concrete slab structure. Then further refinement processes are performed with Self Organizing Map algorithm and density based noise removal process to obtain basic crack characteristic attributes for further analysis. Experimental result verifies that the proposed method is sufficiently identified cracks with various sizes with high accuracy (97.3%) among 1319 ground truth cracks from 30 images

Automatic Segmentation of Brachial Artery based on Fuzzy C-Means Pixel Clustering from Ultrasound Images

Automatic extraction of brachial artery and measuring associated indices such as flow-mediated dilatation and Intima-media thickness are important for early detection of cardiovascular disease and other vascular endothelial malfunctions. In this paper, we propose the basic but important component of such decision-assisting medical software development – noise tolerant fully automatic segmentation of brachial artery from ultrasound images. Pixel clustering with Fuzzy C-Means algorithm in the quantization process is the key component of that segmentation with various image processing algorithms involved. This algorithm could be an alternative choice of segmentation process that can replace speckle noise-suffering edge detection procedures in this application domain