Widely Linear vs. Conventional Subspace-Based Estimation of SIMO Flat-Fading Channels: Mean-Squared Error Analysis

We analyze the mean-squared error (MSE) performance of widely linear (WL) and conventional subspace-based channel estimation for single-input multiple-output (SIMO) flat-fading channels employing binary phase-shift-keying (BPSK) modulation when the covariance matrix is estimated using a finite number of samples. The conventional estimator suffers from a phase ambiguity that reduces to a sign ambiguity for the WL estimator. We derive closed-form expressions for the MSE of the two estimators under four different ambiguity resolution scenarios. The first scenario is optimal resolution, which minimizes the Euclidean distance between the channel estimate and the actual channel. The second scenario assumes that a randomly chosen coefficient of the actual channel is known and the third assumes that the one with the largest magnitude is known. The fourth scenario is the more realistic case where pilot symbols are used to resolve the ambiguities. Our work demonstrates that there is a strong relationship between the accuracy of ambiguity resolution and the relative performance of WL and conventional subspace-based estimators, and shows that the less information available about the actual channel for ambiguity resolution, or the lower the accuracy of this information, the higher the performance gap in favor of the WL estimator.Comment: 20 pages, 7 figure

Learning Representations from Persian Handwriting for Offline Signature Verification, a Deep Transfer Learning Approach

Offline Signature Verification (OSV) is a challenging pattern recognition task, especially when it is expected to generalize well on the skilled forgeries that are not available during the training. Its challenges also include small training sample and large intra-class variations. Considering the limitations, we suggest a novel transfer learning approach from Persian handwriting domain to multi-language OSV domain. We train two Residual CNNs on the source domain separately based on two different tasks of word classification and writer identification. Since identifying a person signature resembles identifying ones handwriting, it seems perfectly convenient to use handwriting for the feature learning phase. The learned representation on the more varied and plentiful handwriting dataset can compensate for the lack of training data in the original task, i.e. OSV, without sacrificing the generalizability. Our proposed OSV system includes two steps: learning representation and verification of the input signature. For the first step, the signature images are fed into the trained Residual CNNs. The output representations are then used to train SVMs for the verification. We test our OSV system on three different signature datasets, including MCYT (a Spanish signature dataset), UTSig (a Persian one) and GPDS-Synthetic (an artificial dataset). On UT-SIG, we achieved 9.80% Equal Error Rate (EER) which showed substantial improvement over the best EER in the literature, 17.45%. Our proposed method surpassed state-of-the-arts by 6% on GPDS-Synthetic, achieving 6.81%. On MCYT, EER of 3.98% was obtained which is comparable to the best previously reported results

Impact of Toxic Leadership, Marginalization, Favouritism, Ergonomics, and Servant Leadership on Human Capital Sustainability

The issue of toxic leadership, marginalization, and favoritism-(nepotism-cronyism) one of the important issues that represent risky phenomena and real problem that impact and results in many negative effects on the sustainability of human capital. But the question remains, which of these managerial and psychological variables affects the sustainability of human capital most? Is toxic leadership or marginalization or favoritism or ergonomics or servant leadership are the most or least impact on the sustainability of human capital? The research focused on a puzzling subject in managerial thought philosophy and studied six variables: toxic leadership, marginalization, favouritism- (nepotism-cronyism), ergonomics, and servant leadership and their impact on the sustainability of human capital. a sample of (371) Cairo international airport (CIA) employees. Finally, the study measured and determined the six most important variables that impacted the sustainability of human capital and tested the ten research hypotheses. Additionally, suggested some recommendations and implementation mechanisms that raise the efficiency of the airline sector and contribute to moderating the effects of toxic leadership, favoritism-(nepotism-cronyism) (FNC), and marginalization on employee performance and enhancing the role of servant leadership (SL), providing and improving ergonomics (workplace conditions and environment), which contributes to the sustainability of human capital (SHC)

Coupled THM analysis of long-term anisotropic convergence in the full-scale micro tunnel excavated in the Callovo-Oxfordian argillite

The main purpose of this paper is to analyse the convergence measurements of the ALC1604 in situ heating test carried out in the Callovo-Oxfordian claystone formation (COx) in the Meuse/Haute-Marne underground research laboratory (MHM URL). The concept of the test consists of horizontal micro-tunnel, equipped with a steel casing. The micro-tunnel is excavated in the direction of the horizontal principal major stress (sH). In situ observations showed anisotropic convergence with the maximum and minimum values in the horizontal and vertical directions, respectively. Coupled THM numerical analyses have been carried out to provide a structured framework for interpretation, and to enhance understanding of THM behaviour of Callovo-Oxfordian claystone. However, a special mechanical constitutive law is adopted for the description of the time-dependent anisotropic behaviour of the COx. The simulation of the test using this enhanced model provides a satisfactory reproduction of the THM long-term anisotropic convergence results. It also provides a better understanding of the observed test response.Postprint (published version