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Several applications in numerical scientific computing process sparse matrices with either a regular or irregular structure. The very large size of these matrices requires to use compressing formats and target parallel/distributed architectures in order to reduce both space complexity and processing time. The optimal compression format (OCF) of such matrices may in fact vary according to both the...
This work focuses on Emirati speaker verification systems in neutral talking environments based on each of First-Order Hidden Markov Models (HMMls), Second-Order Hidden Markov Models (HMM2s), and Third-Order Hidden Markov Models (HMM3s) as classifiers. These systems have been evaluated on our collected Emirati speech database which is comprised of 25 male and 25 female Emirati speakers using Mel-Frequency...
In this paper, we study language models based on recurrent neural networks on three databases in two languages. We implement basic recurrent neural networks (RNN) and refined RNNs with long short-term memory (LSTM) cells. We use the corpora of Penn Tree Bank (PTB) and AMI in English, and the Academia Sinica Balanced Corpus (ASBC) in Chinese. On ASBC, we investigate word-based and character-based language...
It has been argued that recurrent neural network language models are better in capturing long-range dependency than n-gram language models. In this paper, we attempt to verify this claim by investigating the prediction accuracy and the perplexity of these language models as a function of word position, i.e., the position of a word in a sentence. It is expected that as word position increases, the...
Initialization and feature selection are crucial in supervised landmark detection. Mismatching caused by detector error and discrepant initialization is very common in these existing methods. To solve this problem, we proposed a new method, which includes a new initialize model and multitask feature learning, for the robust facial landmark localization. In our new method, firstly, a fast detection...
Modern software are object-oriented program systems. Almost all software has a database. Some databases are object-oriented. In this case, object-oriented software and databases shall be designed in a consistent manner. In this article, we describe a UML profile for the programming environment. It is an environment for support of object-oriented databases. The UML profile allows describing an application...
In this paper, a multi-objective approach to address the Full Model Selection (FMS) problem in temporal databases is presented. FMS problem is defined as a multi-objective problem where Cross Validation Error Rate (CVER) and the spent runtime (RT) of each candidate model are considered as objectives to be optimized through the well-known NSGA-II algorithm. The intuitive idea is to select competitive...
In this paper, we present a novel method for predicting gene functional interactions. We study the effectiveness of various raw and derived features from neural word embedding learned from biomedical literature. Our evaluation results demonstrate that the information captured in neural word embedding is very useful and our learned classification models are capable of predicting gene functional interactions...
In recent years, social networks developed in terms of diversities, capabilities and users. Therefore, researchers in different fields have been attracted to these kind of networks. Trust management between users in these kind of networks is one of the most important research topics. In this article a new model for evaluating trust between users in social networks based on subjective logic is presented...
The goal of this paper is to build a system that automatically creates synthetic data to enable data science endeavors. To achieve this, we present the Synthetic Data Vault (SDV), a system that builds generative models of relational databases. We are able to sample from the model and create synthetic data, hence the name SDV. When implementing the SDV, we also developed an algorithm that computes...
Virtual screening enables to search large small-molecule compound libraries for active molecules with respect to given macromolecular target. In ligand-based virtual screening, this goal is achieved by utilizing information about fragments or patterns present in existing known active compounds. Typically, the patterns are encoded as fingerprints which are used to screen a database of candidate compounds...
Traditional cognitive radio network is considerably constrained in the spectrum sensing and the access by its limited power, memory and computational capacity. Fortunately, the advent of cloud computing bring the potential to mitigate these constraints due to its vast storage and computational capacity. This paper focuses on the cloud-based cognitive radio spectrum access strategy and provides an...
Philipona & O’Regan (2006) [1] recently proposed a linear model of surface reflectance as it is sensed by the human eyes. In their model, the tristimulus response to reflected light is accurately approximated by a linear transformation of the tristimulus response to illumination, allowing the prediction of several perceptual characteristics of human vision. Later, Vazquez-Corral et al (2012) [2]...
We propose a novel inter-layer path control mechanism in a PCE-VNTM cooperative multi-layer networks (MLN). For this, we define a novel FA-LSP aware PCE which only reports and manages a forwarding adjacency-label switched path (FA-LSP) state. In our scheme, the FA-LSP can be distinguished from the pure higher-layer TE link more and accurately controlled with a network policy. We worked out the methodology...
The use of virtual patching tools to prevent attackers exploiting vulnerabilities of a web application is a widely adopted defensive approach. The constant evolution of applications, and thereby of attack techniques, requires a big maintenance and tuning effort to ensure that the remediation patches are working correctly. We put forward in this paper a tool supported process here security requirements...
Correct nuclide identification is critical for first responders. It is the final result of the complex chain occurring in a detector: a spectrum with poor statistics in a variable environment is recorded then analyzed. Industries are facing a complex challenge, as they have to design instruments that can identify materials that for the most part are difficult to obtain. Modelling a source is a viable...
Existing data modeling notations and methods of database development are dedicated to technicians. At the same time, there is a tendency to involve the end-user in the development process. This requires the creation of new modeling notations and development methods for databases area. These tools should be understandable both to end-users and to developers. Because of unified understanding, it is...
Data-driven research is increasingly ubiquitous and data itself is a defining asset for researchers, particularly in the computational social sciences and humanities. Entire careers and research communities are built around valuable, proprietary or sensitive datasets. However, many existing computation resources fail to support secure and cost-effective storage of data while also enabling secure and...
The popular i-vector model represents speakers as low-dimensional continuous vectors (i-vectors), and hence it is a way of continuous speaker embedding. In this paper, we investigate binary speaker embedding, which transforms i-vectors to binary vectors (codes) by a hash function. We start from locality sensitive hashing (LSH), a simple binarization approach where binary codes are derived from a set...
With the progressive development of information and communication technologies, we are now forming a new world called hyperworld that is composed by the cyber world and the physical world with various digital explosions including data, connectivity, service and intelligence. Therefore, Cyber-I has been proposed, which is a real individual's counterpart in cyberspace, and is to create a unique, digital,...
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