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The spike of a cereal plant is the grain-bearing organ whose physical properties are therefore critical components for plant yield. The ability to detect spikes from 2D images of cereals, such as wheat, provides vital information on tiller number and plants yield potential. We propose a novel spike detection method, which uses both RGB and fluorescence images. Firstly, an improved colour index method...
In order to extract the content information of Theme Web Pages more accurately, this paper proposes a self-learning method based on the tag information by calculating the information quantity of various tag indicators. This method predefines several tag information indexes and coefficients index to calculate a variety of tag information quantity of the web pages in turn, and then the candidate content...
In various domains, big data play crucial and related processes because of the latest developments in the digital planet. Such irrepressible data growth has led to bring clustering algorithms to segment the data into small sets to perform associated processes with them. However, the challenge continues in dealing with large data, because most of the algorithms are compatible only with small data....
The area of multi-label classification has rapidly developed in recent years. It has become widely known that the baseline binary relevance approach can easily be outperformed by methods which learn labels together. A number of methods have grown around the label power set approach, which models label combinations together as class values in a multi-class problem. We describe the label-power set-based...
Cloud infrastructures are prone to various anomalies due to their ever-growing complexity and dynamics. Monitoring behavior of dynamic resource management systems is necessary to guarantee cloud reliability. In this paper, we present AMAD, a system designed for detecting an abusive use of dynamic virtual machine migration, in the case of the abusive virtual machine migration attack. This attack is...
In this paper, we address the problem of recommending Point-of-Interests (POIs) to users in a location-based social network. To the best of our knowledge, we are the first to propose the ST (Social Topic) model capturing both the social and topic aspects of user check-ins. We conduct experiments on real life data sets from Foursquare and Yelp. We evaluate the effectiveness of ST by evaluating the...
Since link prediction helps improve our understandings about the structure, functions, and evolution of networks, it has drawn much attention from both computer science and physical communities. Among many mainstream proposed algorithms, the common-neighbor based ones show prominent efficiency but neglect the influence of community structure. Based on the assumption that in the same communities common...
Prior research in neutrally-inspired perceptron predictors and Geometric History Length-based TAGE predictors has shown significant improvements in branch prediction accuracy by exploiting correlations in long branch histories. However, not all branches in the long branch history provide useful context. Biased branches resolve as either taken or not-taken virtually every time. Including them in the...
Twitter data has been applied to address a wide range of applications (e.g., Political election prediction and disease tracking), however, no studies have been conducted to explore the interactions and potential relationships between twitter data and social events available from government entities. In this paper, we introduce a novel approach to investigate the spatio-temporal relationships between...
Partially constrained human recognition through periocular region has emerged as a new paradigm in biometric security. This article proposes Phase Intensive Global Pattern (PIGP): a novel global feature based on variation of intensity of a pixel-neighbours with respect to different phases. The feature thus extracted is claimed to be rotation invariant and hence useful to identify human from images...
In this paper, we describe a novel technique for the extraction of object shapes from Terahertz images using a 3D graph-cut segmentation scheme. This approach to segmentation includes images in temporal domain by creating nodes and edges between consecutive images in order to obtain improved segmentation results and compensate for the high levels of noise in the Terahertz images. The foreground and...
In this paper we discuss the design options for a language processing tool that supports humans in their task of classifying text excerpts according to CEFR levels of language proficiency. We describe the tool that we developed on the basis of these design options and provide an assessment of its functioning. This tool is suitable to be used by students taking courses of Portuguese as a second language,...
This paper presents and investigates two new numerical algorithms (i.e., E47 algorithm and 94LVI algorithm) for solving the quadratic programming (QP) problem subject to inequality and bound constraints. Such a constrained QP problem is firstly converted equivalently into a linear variational inequality (LVI), and then converted equivalently into a piecewise-linear projection equation (PLPE). The...
As the consistency prediction of data view in information systems and actual data, data quality is of vital importance to decision making and the development of banking industry. In this paper, we firstly analyze the influence of data quality on the banking industry, and make researches on the current situation of banking industry data quality automated management. Then five evaluation dimensions...
Molecular biometrics is an advancing field that involves the analysis of a person's unique biological markers at a molecular level to ascertain identity. Bacteria communities found on the skin of the human hand have shown to be highly diverse and to have a low percentage of similarity between individuals. The goal of this research effort is to see if a person's demographics, primarily ethnicity, share...
This paper describes utilization of surface electromyography (sEMG) identification for driving robotic hand. Therefore, this implementation will give other alternatives to the stroke survivors or paralysis patients in order to help their activities. This system detecs the movement of two fingers (thumb and index finger) by using threshold as pattern recognition algorithm. This pattern recognition...
A wireless local area network infrastructure, consisting of a couple of tens of access points exists in each office building, university or even block of flats. These can be used for indoor localization purposes without interfering with network activities. In this paper a correlation based method for indoor localization is presented. No specific infrastructure is needed except for the existing wireless...
In this paper we propose a cluster-based approach for the delineation of management zones in precision agriculture. The proposed approach was built following the steps of data mining for the clustering task, resulting in a computer application that generates maps of management zones and yield areas, allowing to compare them using known statistical indexes. The basis for this implementation was a model...
In this paper we introduce CrowdSource, a statistical natural language processing system designed to make rapid inferences about malware functionality based on printable character strings extracted from malware binaries. CrowdSource “learns” a mapping between low-level language and high-level software functionality by leveraging millions of web technical documents from StackExchange, a popular network...
Spectrum prediction is one key enabling method for cognitive radio to improve spectrum utilization. Different from the traditional methods which predict the spectrum state slot-by-slot, in this paper we investigate the issue of prediction analysis of channel state duration (CSD). Specifically, we first introduce the concept of Hurst index to characterize the predictability between different scales...
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