In this paper, a new algorithm based on ESPRIT is proposed for the estimation of central angle and angular extension of Incoherently Distributed (ID) sources. The central angles are estimated using TLS-ESPRIT. The covariance matrix is approximated using a finite Taylor series expansion which leads to the formulation of covariance matrix in terms of central moments of the angular power distribution. The extension widths are estimated using the central moments of distribution. The algorithm can be used for sources with different angular distributions and has low computational cost.

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Introduction: Myxomas are benign mesenchymal neoplasms which arise mainly in the heart. The laryngeal localization is very rare. We aim to describe the clinical, histological and therapeutic features of this condition. Case Report: We report two cases of laryngeal myxomas occurred in male and female patients, presenting with a history of prolonged hoarseness. Laryngoscopy revealed a polypoid mass on the true vocal folds. The lesions were excised with cold instruments. One patient presented a recurrence 4 years after the first surgery. Conclusions: Laryngeal myxoma should be considered in case of a benign looking vocal fold lesion, especially a vocal cord polyp. Histologic exam is the only tool to confirm the diagnosis. It is treated by surgical resection. In the literature, recurrence is rare in laryngeal site, but patients need to be kept on close follow-up.

In this paper, at first the philosophical concept of objectivity in scientific studies and analyses is described. Then, it's meaning in damage analysis and, especially, "strain localization analyses" is represented. After that, the most important solution for making an analysis objective i.e. using the nonlocal values of relevant variables is discussed. Then, the current idea on objective analysis based on the secant modulus, is represented and the authors suggestion for objective analysis, based on the tangent modulus, is represented. Finally, a sample problem is solved.

Background and Objectives: Signage is everywhere, and a robot should be able to take advantage of signs to help it localize (including Visual Place Recognition (VPR)) and map. Robust text detection & recognition in the wild is challenging due to pose, irregular text instances, illumination variations, viewpoint changes, and occlusion factors.Methods: This paper proposes an end-to-end scene text spotting model that simultaneously outputs the text string and bounding boxes. The proposed model leverages a pre-trained Vision Transformer based (ViT) architecture combined with a multi-task transformer-based text detector more suitable for the VPR task. Our central contribution is introducing an end-to-end scene text spotting framework to adequately capture the irregular and occluded text regions in different challenging places. We first equip the ViT backbone using a masked autoencoder (MAE) to capture partially occluded characters to address the occlusion problem. Then, we use a multi-task prediction head for the proposed model to handle arbitrary shapes of text instances with polygon bounding boxes.Results: The evaluation of the proposed architecture's performance for VPR involved conducting several experiments on the challenging Self-Collected Text Place (SCTP) benchmark dataset. The well-known evaluation metric, Precision-Recall, was employed to measure the performance of the proposed pipeline. The final model achieved the following performances, Recall = 0.93 and Precision = 0.8, upon testing on this benchmark.Conclusion: The initial experimental results show that the proposed model outperforms the state-of-the-art (SOTA) methods in comparison to the SCTP dataset, which confirms the robustness of the proposed end-to-end scene text detection and recognition model.

In this paper, the position of the leakage in a pressurized gas pipe is localized. As an experimental example, the leakage in a steel pipe is simulated by different orifices. To decrease the risk of explosion and environmental contamination during experiments, pressurized air was used instead of natural gas. Most of the published papers are based on using high sampling rate sensors placed on both sides of the leakage. In this study, a new method is extended due to leakage localization in a gas pipe. To achieve this goal, attenuation analysis is implementing by installing two sensors on one side of the pipe. In the proposed technique, the dominant frequency of recorded signals is used, to decrease the effect of background noises on final results. Experimental results reveal by increasing the pressure the leakage localization error is decreased. Finally, by implementing signal processing into the data the average value of leakage localization error is reported 13.77 cm.

Let R be a commutative ring with identity, M be a unital R-module and let L be a complete Heyting algebra. In this paper, among results on colon structures of L-neutrosophic submodules and L-neutrosophic ideals, we introduce and study the notion of primary (and prime) L-neutrosophic submodules and give connections with primary (prime) behavior of its t, i and f components. Then, for a multiplicatively closed subset S of R, we define the notion of localization formation for an L-neutrosophic submodule λ of M and study its behavior. Some types of L-neutrosophic quotients will also be investigated.