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In the scenario of multiple access communication, the spectral sidelobes and peak-to-average power radio (PAPR) problems of orthogonal frequency division multiplexing (OFDM) must not be ignored. This paper proposes a novel precoding scheme that ahead of inverse discrete Fourier transformation (IDFT) is presented to jointly suppress the in-band-out-of-subband (IBOSB) radiation and high PAPR in orthogonal...
Commercial seaports are a key component in the transport chain and particularly in the supply chain and in the production process. Port performance is a recurring question as each change in ports affects their performance level. These changes occur at different levels: international (technological advances), national (division of traffic between different regions) and local (land use planning). This...
The human brain is organized into functionally specialized subnetworks, referred to as modules. Many methods have been employed to detect modules in the brain network, e.g. Newman's modularity and the Louvain method for community detection. However, these methods suffer from a resolution limit, and the detected number of modules is often inaccurate. In this work, we adopt Eigen Value Decomposition...
We propose computationally efficient carrier frequency offset estimators for multicarrier underwater acoustic communication using identical pilot tones equi-spaced in the frequency domain. The first estimator uses the phase of the maximal eigenvector of a channel-dependent correlation matrix. Next, the phase of the minimal eigenvector of a channel-independent correlation matrix is combined with the...
We formulate and analyze a graphical model selection method for inferring the conditional independence graph of a high-dimensional nonstationary Gaussian random process (time series) from a finite-length observation. The observed process samples are assumed uncorrelated over time but having a time-varying marginal distribution. The selection method is based on testing conditional variances obtained...
This paper deals with the problem of single-channel noise reduction. Thanks to the eigenvalue decomposition, we arrange the eigenvalues of the speech correlation matrix in such a way that all the spectral mode signal-to-noise ratios (SNRs) of the noisy speech are ordered in a descending manner. By maintaining no speech distortion in the spectral modes with high input SNRs while allowing some degree...
In this paper, we extend the recent definition of graph stationarity into a definition of local stationarity. Doing so, we present a metric to assess local stationarity using projections on localized atoms on the graph. Energy of these projections defines the local power spectrum of the signal. We use this local power spectrum to characterize local stationarity and identify sources of non-stationarity...
At high SNR, strong correlations in the elements of the MIMO channel can lead to a decrease in channel capacity. In this paper we propose a new methodology to estimate these spatial correlations based on the analysis of the most significant eigenvalues of transmit and receive covariance matrices of the MIMO channel. Our study is based on measurements performed in a university campus with the following...
Two different solutions for the characteristic modes (CMs) of lossy structures were previously developed using induced volume currents. The first solution diagonalizes the scattering and perturbation matrices, guaranteeing far-field orthogonality at the cost of imaginary eigenvalues and eigencurrents. The second solution does not perfectly diagonalize these matrices, but maintains real-valued eigenvalues...
This paper review an important of the student loan consideration criteria by using factor analysis method. The processes include five steps determining factors that influence the consideration; Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Bartlet's test of sphericity, Principal components analysis (PCA), rotation, evaluation, and interpretation. The dataset is a historical data of student loan...
Every educational institute feels proud when its admission closes with expected number of students. The prospective student enters the campus with lots of hopes, dreams and expectations. When their expectations are not met or if they undergo for critical circumstances and makes them drop from their registered program. Predicting undergraduate student dropouts are a major challenge in educational system...
In this paper, we present a novel thermodynamic framework for graphs that can be used to analyze time evolving networks, relating the thermodynamics variables to macroscopic changes in network topology, and linking major structural transition to phase changes in the thermodynamic picture. We start from a recent quantum-mechanical characterization of the structure of a network relating the graph Laplacian...
In this paper, two methods are showed to identify the seismic source using an array signal processing technique. One method is applicable when there are multiple sources, and it identifies the directions of the sources, and the other one estimates the distance and angular position of a single seismic source. Both the methods uses MUltiple SIgnal Classifier (MUSIC) for array signal processing. In case...
We consider a reduced dimensionality representation based on multiple views of the same underlying process. These multiple views can be obtained, for example, using several different modalities, measured with different instrumentation or generated based on different methods of feature extractions. Our framework is based on a cross-view random walk process which is restrained to hop between the different...
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...
Customer satisfaction is an important factor governing adoption and retention of multimedia products and services, such as Over-The-Top(OTT) video transmission. Quality of Experience involves user-centric evaluation of various services. However, users differ in terms of their ratings of service quality. Some rating differences are due to unreliability (outlier users who are not motivated, or are not...
Cyber-physical systems are critical infrastructures that are crucial both to the reliable delivery of resources such as energy, and to the stable functioning of automatic and control architectures. These systems are composed of interdependent physical, control and communications networks described by disparate mathematical models creating scientific challenges that go well beyond the modeling and...
Because a huge number of base stations are deployed due to the recent development of mobile access services, network monitoring in mobile networks becomes more challenging. In this paper, we propose a novel change-point detection scheme to efficiently detect a time instant (change-point) when the spatial distribution of mobile terminals connecting to base stations is changed dramatically. In the proposed...
A better understanding of the composition of rumen microbial communities and the association between host genetic and microbial activities has important applications and implication in bioscience. Being capable of revealing the full extent of microbial gene diversity, metagenomics-based approaches hold great promises in this endeavor. This study investigates the rumen microbial community in cattle...
Kernel and Multiple Kernel Canonical Correlation Analysis (CCA) are employed to classify schizophrenic and healthy patients based on their SNPs, DNA Methylation and fMRI data. Kernel and Multiple Kernel CCA are popular methods for finding nonlinear correlations between high-dimensional datasets. Data was gathered from 183 patients, 79 with schizophrenia and 104 healthy controls. Kernel and Multiple...
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