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Based on the method of latent semantic analysis (LSA), a text matching algorithm was proposed in this paper for constructing an automated scoring system of Chinese test papers. Firstly, by fully considering the correlation between terms, texts of examinee's answers and standard answers were represented in lower-dimensional space and the model was improved using the way of singular value decomposition...
In this paper, a fast forward motion estimation (FFME) algorithm based on motion compensated frame rate up-conversion (MC-FRUC) with reduced time complexity is proposed. The proposed algorithm exploits the spatial correlation of the displacement vectors of the neighboring blocks in a frame. The algorithm achieves a reduction in the computational complexity by 85% compared to the existing single frame...
In this article, an effort has been made to investigate the nonlinear and chaotic nature of daily CME linear speed time series data collected from the Solar and Heliospheric Observatory for solar cycle 23 over the period of February 1999 to December 2007. To explore the nonlinear characteristic of the CME linear speed signal delay vector variance algorithm is used whereas 0–1 test, information entropy...
The classification recognition performance is a hot study in the field of remote sensing image. In this paper, texture feature, shape feature, radiation intensity of remote sensing image information were used to initial terrain classification. Then an improved fuzzy c-means algorithm was applied on classification, and it included optimization of determine clustering center, got the number of clustering...
Because of the volatility of memory, nodes in in-memory storage system crashing down would lead to data lost. One solution to this problem is backing data up. However, if we backup data to a node which is about to fail down, the data should be recopied again. That would lead to a large amount of backup data, and in turn reduce the system reliability. We first establish a correlated failure model with...
This paper proposes an approach of recommending micro-learning path based on improved ant colony optimization algorithm. Micro-learning is a new learning style, which can be used to support learning in short time because of its micro-learning units. Each micro-learning unit consists of a small knowledge unit that can be learned at fragmented time. Meanwhile, micro-learning is more flexible than other...
We extend earlier work by Essick et al. [1,2] with a study of similarities among sky localization maps corresponding to gravitational-wave transients. Earlier in 2016, the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) announced the first direct observation of gravitational waves from binary black holes [3,4]. Motivated by the fact that multiple detection and localization algorithms...
Document layout segmentation and recognition is an important task in the creation of digitized documents collections, especially when dealing with historical documents. This paper presents an hybrid approach to layout segmentation as well as a strategy to classify document regions, which is applied to the process of digitization of an historical encyclopedia. Our layout analysis method merges a classic...
Tonic is one of the integral part of Indian music. It is base pitch for entire rag or melody. In this paper, we have discussed tonic extraction method for analysis of Indian music. The literature witnesses several computationally complex and slightly sluggish algorithms for tonic extraction. We have used Harmonic Product Spectrum (HPS) method to exploit the harmonic nature of music for pitch extraction...
The search for Trendsetters in social networks turned to be a complex research topic that has gained much attention. The work here presented uses big data analytics to find who better spreads the word in a social network and is innovative in their choices. The analysis on the Yelp platform can be divided in three parts: first, we justify the use of Tips frequency as a variable to profile business...
Sampling through crawling is an important research topic in social network analysis. However there is very little existing work on sampling through crawling in directed networks. In this paper we present a new method of sampling a directed network, with the objective of maximizing the node coverage. Our proposed method, Predicted Max Degree (PMD) Sampling, works by predicting which k open nodes are...
The proposed paper presents a novel scheme that can perform a precise extraction of knowledge from the complex and massive streaming of live data of the scene from the crowded place. The prime contribution of the proposed system is to perform enough processing over the raw and unstructured distributed data from multiple locations so that processing over distributed storage and mining can be done with...
Solar power penetration has made the site-specific energy ratings an essential necessity for utilities, independent systems operators and regional transmission organizations. Since, it leads to the reliable and efficient energy production with the increased levels of solar power integration. This study concentrates on the partitional clustering analysis of monthly average insolation period data for...
Multi-label data with high dimensionality arise frequently in data mining and machine learning. It is not only time consuming but also computationally unreliable when we use high-dimensional data directly. Supervised dimensionality reduction approaches are based on the assumption that there are large amounts of labeled data. It is infeasible to label a large number of training samples in practice...
In this paper we present a self-avoiding walk-jump (SAWJ) algorithm for finding a maximum degree node on a large assortative graph. We offer two contributions: i) we use the theory of absorbing Markov chains to effectively approximate the required search time as a function of the number of nodes, the edge density, and the assortativity, and ii) we measure the performance of our algorithm against competing...
Elliptic curve cryptosystems are built on an underlying additive group, with an addition operation defined as the group operation. The aim of the elliptic curve addition operation is to render an elliptic curve point on the underlying elliptic curve when two ECC points are taken as inputs. However ECC addition formula may not be complete in nature, and may contain exceptional points, for which the...
Demand side management (DSM) is a key mechanism to make smart grids cost efficient using electricity price forecasting issue. Price forecasting method takes the big price data into account, and gives estimates of the future electricity price. However, most of existing price forecasting methods cannot avoid redundancy at feature selection and lack of an integrated framework that coordinates the steps...
Given a set of events of two different types (e.g. locations of crime incidents/road accidents) in geographic space and minimum density and area thresholds, spatial regions of high correlation discovery (RHC) aims to determine rectangular-shaped areas of high correlation between two event types. RHC discovery is important to many fields like transportation engineering, criminology, and epidemiology...
Football training periodization is widely acknowledged as crucial to obtain the best performance throughout matches and to reduce the risk of injuries. Thus, the aim of this study is to detect the in-season short-term training cycles in an Italian elite football team. 80 trainings of 26 elite football players were monitored during 23 in-season weeks by a global position system (GPS). Machine learning...
Blind signal search is a technique used in many different types of systems, ranging from cognitive radio to broadcasting applications such as television and radio. A well-known approach used for this, is the Cyclostationary Feature Detection algorithm, which can estimate the baud rate of a detected signal, but is not capable of identifying its position in the spectrum, nor properly analyse spans with...
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