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In this paper, we examine the possibility to utilize the well-known approximations of Jaccard metric in order to reduce computational complexity of Edit Distance metric estimation. The scope of our analytical results is the representing strings rather than the original (raw) textual data, still in practice we obtained a solid indication that the results can be applied to (raw) strings that have low...
Deep learning (deep structured learning, hierarchical learning or deep machine learning) is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using multiple processing layers with complex structures or otherwise composed of multiple non-linear transformations. In this paper, we present the results of testing neural networks architectures...
Vehicular communication plays a key role in nearfuture automotive transport, promising features like increased traffic safety or wireless software updates. However, vehicular communication can expose driver locations and thus poses important privacy risks. Many schemes have been proposed to protect privacy in vehicular communication, and their effectiveness is usually shown using privacy metrics....
The aim of the article is application of entropy defined in combinatorics on words for finite words; entropy function will be applied for solving classification and clusterisation problems.
Emotion recognition system using electrocardiogram (ECG) has received considerable attention recently in the area of human computer interaction (HCI). Our work in this paper is an attempt towards developing an emotion recognition system that would classify emotions effectively into four emotional states: joy, anger, sadness and pleasure. The contributions of this paper is summarized in three fold:...
Trust management systems provide a means for trustworthy interactions in cloud environments. However, trust establishment could be compromised when malicious cloud users intentionally provide unfair feedbacks to decrease the reputation of some cloud providers or to benefit others. In this paper, we define "Feedback Entropy" as a newmetric to detect unfair rating attacks. As such, we propose...
Fuzzy rough technique is a mathematical tool to deal with fuzzy and rough knowledge, which could reduce the redundant objects and attributes by keeping the information invariant. In the existing researches on fuzzy rough sets, all the attributes are assumed to have the same weights for the decision. Actually different attributes may play different roles on the decision. As a result, we introduce weights...
We present a new distance measure between sequences that can tackle local temporal distortion and periodic sequences with arbitrary starting points. Through viewing the instances of sequences as empirical samples of an unknown distribution, we cast the calculation of the distance between sequences as the optimal transport problem. To preserve the inherent temporal relationships of the instances in...
the task of full-focused digital images construction relates to computational photography and is a process of increasing the information capacity of images obtained via photo- and video-fixation devices with limited optical depth of field. Additional to this task is the question of automatic evaluation of the quality of the images. The most popular non-reference metrics for comparing the quality of...
Complexity is a term that is currently used not only in research articles but also in the methodologies and standards used to manage information and projects. The complexity can represent the size of a system, process, program or project, the number of functions and the cost of their acquisition, operation and maintenance. Within the context of this work, the complexity is a variable that represents...
First-person videos (FPVs) in daily living help us to memorize our life experience and information systems to process daily activities. Summarizing FPVs into key frames that represent the entire data would allow us to remember our memory in the past and computers to efficiently process the data. However, most video summarization approaches only use visual information, even though our daily activities...
Most of the existing population behavior studies are about the analysis of the population dynamic behavior of genetic algorithm, while there is little analysis of the population dynamic behavior of particle swarm optimization (PSO). Therefore, there is an urgent need for a new method to characterize the population dynamic behavior of PSO in the search process. In this paper, we propose some metrics...
Stereoscopic vision is a complex system which receives and integrates perceptual information from both monocular and binocular cues. In this paper, a novel reduced-reference stereoscopic image quality assessment scheme is proposed, based on the visual perceptual information measured by entropy of classified primitives (EoCP) and mutual information of classified primitives (MIoCP), named as DCprimary,...
The relation between fetal heart rate and the value of umbilical cord artery pH is not something new for the scientific community. However, the problem has not been investigated sufficiently. One reason for that is the lack of open databases with a large number of recordings. Such a database is used here, recently publicly available, with cardiotocographic data recorded approximately two hours before...
Nowadays, the challenge of learning from large scale and imbalanced data set have attracted a great deal of attention from both industry and academia, which is also deemed to be an important task for fraud detection in telecommunication, finance, online commerce. In general, it's almost impossible to train a classification model on the complete data set, especially in the era of big data, due to the...
Consider a data source comprised of a graph with marks on its edges and vertices. Examples of such data sources are social networks, biological data, web graphs, etc. Our goal is to design schemes that can efficiently compress and store such data. We aim for universal compression, i.e. without making assumptions about the stochastic properties of the data. To make sense of this, we employ the framework...
In this paper, we consider a scalar Gaussian Channel with minimum amplitude constraint, and investigate when the capacity-achieving input is binary. First, we study the case that the input satisfies both minimum and peak amplitude constraints and find that the optimal input is discrete. Then, for a given minimum amplitude, we find sufficient conditions that the peak amplitude constraint must satisfy...
Estimation of functions of d variables is considered using ridge combinations of the form Σmk=1 c1, kφ(Σdj=1c0, j, kxj-bk) where the activation function φ is a function with bounded value and derivative. These include single-hidden layer neural networks, polynomials, and sinusoidal models. From a sample of size n of possibly noisy values at random sites X ∊ B = [−1, 1]d, the minimax mean square error...
The problem of publishing privacy-guaranteed data for hypothesis testing is studied using the maximal leakage (ML) as a metric for privacy and the type-II error exponent as the utility metric. The optimal mechanism (random mapping) that maximizes utility for a bounded leakage guarantee is determined for the entire leakage range for binary datasets. For non-binary datasets, approximations in the high...
Scale-free can be seemed as one of the most impacting discoveries in complex networks theory and has already been successfully proved to be highly effective in constructing error-tolerant topology structures of wireless sensor networks (WSNs). As in scale-free WSNs, a few key nodes possess most connections, requiring them to take excessive message-relay tasks. Due to this reason, the energy of these...
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