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The paper discusses a non-deterministic model for data association tasks in visual surveillance of crowds. Using detection and tracking of crowd components (i.e., individuals and groups) as baseline tools, we propose a simple algebraic framework for maintaining data association (continuity of labels assigned to crowd components) between subsequent video-frames in spite of possible disruptions and inaccuracies in tracking/detection algorithms. Formally, two alternative schemes (which, in practice, can be jointly used) are introduced, depending on whether individuals or groups can be prospectively better tracked in the current scenario. In the first scheme, only individuals are tracked, and the continuity of group labels is inferred without explicitly tracking the groups. In the second scheme, only group tracking is performed, and associations between individuals are inferred from group tracking. The associations are built upon non-deterministic estimates of memberships (individuals in groups) and estimates obtained directly from the baseline detection and tracking algorithms. The framework can incorporate any detectors and trackers (both classical or DL-based) as long as they can provide some geometric outlines (e.g., bounding boxes) of the crowd components. The formal analysis is supported by experiments in exemplary scenarios, where the framework provides meaningful performance improvements in various crowd analysis tasks.

This article has been retracted. A retraction notice can be found at . [ABSTRACT FROM AUTHOR]

Introduction: The availability of proactive techniques for health monitoring is essential to reducing fetal mortality and avoiding complications in fetal wellbeing. In harsh circumstances such as pandemics, earthquakes, and lowresource settings, the incompetence of many healthcare systems worldwide in providing essential services, especially for pregnant women, is critical. Being able to continuously monitor the fetus in hospitals and homes in a direct and fast manner is very important in such conditions. Methods: Monitoring the health of the baby can potentially be accomplished through the computation of vital bio-signal measures using a clear fetal electrocardiogram (ECG) signal. The aim of this study is to develop a framework to detect and identify the R-peaks of the fetal ECG directly from a 12 channel abdominal composite signal. Thus, signals were recorded noninvasively from 70 pregnant (healthy and with health conditions) women with no records of fetal abnormalities. The proposed model employs a recurrent neural network architecture to robustly detect the fetal ECG R-peaks. Results: To test the proposed framework, we performed both subjectdependent (5-fold cross-validation) and independent (leave-one-subjectout) tests. The proposed framework achieved average accuracy values of 94.2% and 88.8%, respectively. More specifically, the leave-one-subject-out test accuracy was 86.7% during the challenging period of vernix caseosa layer formation. Furthermore, we computed the fetal heart rate from the detected R-peaks, and the demonstrated results highlight the robustness of the proposed framework. Discussion: This work has the potential to cater to the critical industry of maternal and fetal healthcare as well as advance related applications. [ABSTRACT FROM AUTHOR]

This paper presents the impact of temperature variations and alterations in transistor channel dimensions on CMOS (Complementary Metal-Oxide-Semiconductor) circuit technology. To facilitate this investigation, we first identified critical parameters characterizing the device's performance, which could exhibit susceptibility to these influences. The analysis encompassed critical metrics such as the transfer characteristic, drain current, logic levels, inflection points, and truncation points. These parameters enabled us to validate the results obtained from the PSPICE simulator, which demonstrated unequivocal effectiveness. Notably, our simulation results unveiled significant effects resulting from a wide temperature range spanning from -100°C to 270°C, offering valuable in-sights into thermal-induced failures. Additionally, the influence of channel dimension changes on factors like drain current and transfer characteristics, as well as temporal parameters including signal propagation delay and rise and fall times, were meticulously examined and appreciated.

The presence of barriers in point-plane oil gaps has an important role on the insulating oil dielectric strength. This latter closely related to the nature (material), the thickness and the diameter of the barrier, its relative position, the distance between electrodes and theirs interactions. The present work is devoted to estimate the dielectric strength of the transformer oil, the Borak 22 under 50 Hz AC voltage, in presence of Bakelite and Pressboard barriers of 2 and 4 mm thicknesses. To achieve this goal, proposal mathematical models have been built via Central Composite Face method (CCF) which is a robust tool introduced by FISHER. It allowed us to estimate the dielectric strength through a mathematical model. For each barrier, the formulation and the verification of the established models are carried out for several inter-electrodes distance (d=4, 6, 8 10 and 12cm) and relative positions of the barrier (a/d=20, 40, 60, 80 and 100%; a being the point-barrier distance). For each configuration, the corresponding model is verified using graphical and statistical analyses. It is validated as long as the relative mean error between the estimated dielectric strength values and the experimental ones. [ABSTRACT FROM AUTHOR]