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This paper describes an FPGA-based system capable of computing the distance of objects in a scene to two stereo cameras, and use that information to isolate objects in the foreground. For this purpose, four disparity maps are generated in real time, according to different similarity metrics and sweep directions, and then merged into a single foreground-versus-background bitmap. Our main contribution...
An Unattended Detection method for monitoring the CO2 concentration in soil respiration is described. It is based on the gas pump and gas extraction with a dynamic air chamber assay, and the study of the relationship between data collected from on-line measurement of carbon dioxide and time, as well as the resistance to interfering. This method uses proposed utility line peak extraction method to...
With high compression ratio performance, fractal image compression technology becomes a hot topic of research of image compression techniques. However, the encoding time of traditional fractal compression technique is too long to achieve real-time image compression, so it cannot be widely used. Based on the theory of fractal image compression; this paper raised an improved algorithm form the aspect...
As a means of continuous improvement for the existing process, 6σ is more and more popular to enterprises. The purpose and the main implementing methods in all phases of DMAIC model of 6σ are introduced. The difference between the process capability index and the process performance index is analyzed. The significance of the application of process capability analysis in measurement phase is discussed...
This article focuses on the performance measurement of non-for-profit organizations. Most of the existing researches just copy the method for the for-profit organizations performance measurement and apply to the non-for-profit organizations. In this article, I find out that there no core performance measures in the non-for-profit organizations which make the core-measurement, the method of for-profit...
Poor quality data is a growing problem that affects many enterprises across all aspects of their business ranging from operational efficiency to revenue protection. Moreover, this problem is costly to fix because significant effort and resources are required to identify a comprehensive set of rules that can detect (and correct) data defects along various data quality dimensions such as consistency,...
Image registration is the process of overlaying two or more images of the same scene taken at different times, from different viewpoints, and/or by different sensors. It geometrically aligns two images the reference and floating images. Medical image registration concentrates on aligning two or more images that represent the same anatomy from different angles and are obtained at different times. In...
In this paper we introduce an ant-based algorithm on continuous domains used to create procedural animations. We focus our approach on finding movement sequences that satisfy both the physical constraints as well as animator requirements. The proposed method is very flexible and can be easily adapted to different situations and characters' morphologies. Our simulations show that the proposed technique...
In this paper we show how the complexity of performing nearest neighbor (NNS) search on a metric space is related to the expansion of the metric space. Given a metric space we look at the graph obtained by connecting every pair of points within a certain distance r. We then look at various notions of expansion in this graph relating them to the cell probe complexity of NNS for randomized and deterministic,...
In the field of geoscience and atmospheric science, raw data should be interpolated by appropriate times due to the temporal and spatial resolution limitation or the length of initial data at the given observation time for the follow-up process. But this type of data have universal and special nonlinear characteristics, such as chaotic and fractal feature, these nonlinear time series are sensitive...
Instance-based learning algorithms typically suffer influences of dissimilarity functions. The problem is frequently related to the Nearest Neighbor rules of these algorithms. This paper will introduce a new dissimilarity measure, called Heterogeneous Centered Difference Measure, which is tested over many known databases. The results are compared with other distance functions.
Quality of Service (QoS) routing is known to be an NP-hard problem in case of two or more additive constraints and several exact algorithms and heuristics have been proposed to address this issue. In this work, we consider a particular two-Constrained Quality of Service Routing Problem where one constraint is superlative and the other is comparative. We consider the superlative constraint to represent...
This paper presents a hybrid intelligent method to design Morphological-Rank-Linear (MRL) perceptrons to solve the Software Development Cost Estimation (SDCE) problem. The proposed method uses a modified genetic algorithm (MGA) to determine the best particular features to improve the MRL perceptron performance, as well as its initial parameters. Furthermore, for each individual of MGA, a gradient...
Edited video recordings, such as talk-shows and sitcoms, often include Audio-Visual clusters: frequent repetitions of closely related acoustic and visual content. For example during a political debate, every time that a given participant holds the conversational floor, her/his voice tends to co-occur with camera views (i.e. shots) showing her/his portrait. Differently from the previous Audio-Visual...
In multi-instance multi-label learning (i.e. MIML), each example is not only represented by multiple instances but also associated with multiple labels. Most existing algorithms solve MIML problem via the intuitive way of identifying its equivalence in degenerated version of MIML. However, this identification process may lose useful information encoded in training examples and therefore be harmful...
As an emerging area in information retrieval, question answering aims at retrieving answers to user-posted questions from a given sentence collection or text corpus. In question answering, the queries are usually submitted in the form of short sentences which are unable to represent user intentions sufficiently. In this study, we present a novel framework which improves question answering through...
We discuss a new algorithm for traversing possible worlds in games of imperfect information based on the enumerablity of permutations by means of Sims tables. The resulting anytime capabilities of the algorithm are demonstrated by applying it to the card game Schnapsen, popular in Central Europe.
Recent work in the field of machine translation (MT) evaluation suggests that sentence level evaluation based on machine learning (ML) can outperform the standard metrics such as BLEU, ROUGE and METEOR. We conducted a comprehensive empirical study on support vector methods for ML-based MT evaluation involving multi-class support vector machines (SVM) and support vector regression (SVR) with different...
The notion of vertex sparsification (in particular cut-sparsification) is introduced in, where it was shown that for any graph G = (V, E) and any subset of k terminals K ⊂ V, there is a polynomial time algorithm to construct a graph H = (K, EH) on just the terminal set so that simultaneously for all cuts (A,K-A), the value of the minimum cut in G separating A from K-A is approximately the same as...
A great number of techniques were already applied to the non-adversarial variation of the multiagent patrolling problem. Experiments suggest that, for general graphs, all those approaches are inferior to a strategy based on the travelling salesman problem (TSP), in which agents are distributed equidistantly along the TSP-cycle. This approach, however, is neither optimal nor scalable. In this article,...
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