Browsing by Type "journal-article"

We present a systematic search for periodic X-ray sources in ten Galactic globular clusters (GCs) using deep archival Chandra observations. By applying the Gregory–Loredo algorithm, we detect 28 periodic signals from 27 independent X-ray sources across six GCs, including 21 newly discovered X-ray periodic sources. The remaining four GCs show no periodic X-ray sources, primarily due to lower data sensitivity. Based on X-ray timing and spectral analyses, complemented by available optical and ultraviolet data, 21 of these periodic sources are identified as cataclysmic variables (CVs). Combined with 11 previously identified periodic CVs in 47 Tuc, this work constitutes the most comprehensive sample to date of GC CVs with probable orbital periods. The observed scarcity of old, short-period CVs in GCs compared to the Galactic inner bulge and solar neighbourhood is likely due to both selection effects favoring younger, dynamically formed systems and the suppression of primordial CV formation by stellar dynamical interactions typical of GC environments. Furthermore, a significant fraction of GC CVs—most with orbital periods below or within the CV period gap—are identified as probable magnetic CVs, while luminous intermediate polars appear underrepresented compared to the solar neighbourhood.

Although walking methodologies (WMs) and machine learning (ML) have been objects of interest for urban scholars, it is difficult to find research that integrates both. We propose a ‘cyborg walk’ method and apply it to studying litter in public spaces. Walking routes are created based on an unsupervised learning algorithm (k-means) to classify public spaces. Then, a deep learning model (YOLOv5) is used to collect data from geotagged photos taken by an automatic Insta360 X3 camera worn by human walkers. Results from image recognition have an accuracy between 83.7% and 95%, which is similar to what is validated by the literature. The data collected by the machine are automatically georeferenced thanks to the metadata generated by a GPS attached to the camera. WMs could benefit from the introduction of ML for informative route optimisation and georeferenced visual data quantification. The links between these findings and the existing WM literature are discussed, reflecting on the parallels between this ‘cyborg walk’ experiment and the seminal cyborg metaphor proposed by Donna Haraway.

A new high gain control law is proposed for stably invertible linear systems. The continuous-time case is first studied to set ideas. The extension to the sampled-data case is made difficult by the presence of sampling zeros. For continuous-time systems having relative degree greater than or equal to two, these zeros converge, as the sampling rate approaches zero, to either marginally stable or unstable locations. A methodology which specifically addresses the sampling zero issue is developed. The methodology uses an approximate model which includes, when appropriate, the asymptotic sampling zeros. The core idea is supported by simulation studies. Also, a preliminary theoretical analysis is provided for degree two, showing that the design based on the approximate model stabilizes the true system for the continuous and sampled-data cases