High-impedance faults (HIFs) are linked to enduring unaddressed knowledge gaps due their diverse and complex behavior, despite being extensively researched disturbances. Vegetation HIFs, for instance, a particular type of fault that can lead great fire hazards life risks. They have unique signatures should receive special attention if risk mitigation is desired. This paper focuses on the detection these distinct, very small current faults. As main correlational features, proposed methodology...

The COVID-19 pandemic has triggered an urgent need to contribute the fight against immense threat human population. Computer Vision, as a subfield of Artificial Intelligence, enjoyed recent success in solvingvarious complex problems health care and potential controlling COVID-19. In response this call, computer vision researchers are putting their knowledge base at work devise effective ways counter challenge serve global community. New contributions being shared with everypassing day. It...

The COVID-19 pandemic has triggered an urgent call to contribute the fight against immense threat human population. Computer Vision, as a subfield of artificial intelligence, enjoyed recent success in solving various complex problems health care and potential controlling COVID-19. In response this call, computer vision researchers are putting their knowledge base at test devise effective ways counter challenge serve global community. New contributions being shared with every passing day. It...

High Impedance Faults (HIFs) are recurring events in electrical Distribution Systems (DSs) and occur by the contact between energized conductors high impedance surfaces. HIFs may pose hazards to living beings cause bushfires. However, HIF protection has not been completely solved due small fault current varying impedance, inhibiting traditional techniques from functioning correctly. In literature, researchers have mainly focused on detection techniques. Thus, development of Location Methods...

Quantitative assessment of the abdominal region from CT scans requires accurate delineation organs. Therefore, automatic image segmentation has been subject intensive research for past two decades. Recently, deep learning-based methods have resulted in state-of-the-art performance 3D segmentation. However, complex characterization organs with weak boundaries prevents learning Specifically, voxels on boundary are more vulnerable to misprediction due highly-varying intensities. This paper...

This study aims to ensure the observability of voltage sags in entire distribution system (DS) for any short‐circuit manifested by optimal allocation monitors focusing on power quality. After determining a sag matrix each type (balanced or unbalanced), resulting binary is determined which simultaneously observes all types faults. Later, proposal made reduce this decrease computational effort large DS. Furthermore, vulnerability node analysed establish monitors’ installation priority. The...

High Impedance Faults (HIFs) are disturbances that can lead to bush fires. This work presents physical and electrical phenomena associated with ph-to-ph faults for a range of tree species. Physical ignition branch under fault scenario analysed identify stages ignition. A methodology, based on the rate change RMS current zero-crossings in averaged current, has been applied 96.12% accuracy stages. The key contribution is proposed volatility detector detecting during HIF event. concept relative...

This letter exhibits the presence of High-Frequency (HF) current signatures arcing in Vegetation High Impedance Fault (VeHIF) events. Zero-crossing discontinuities are shown to have varying widths causing different levels HF noise bursts depending on how aggressively 50-Hz waveform gets distorted. The work has identified that temporal growth disturbances often occurs quicker than those linked third harmonic or entire Low-Frequency (LF) spectrum. In 59.2% a dataset 125 phase-to-earth...

Lung cancer is the leading cause of death and morbidity worldwide. Many studies have shown machine learning models to be effective in detecting lung nodules from chest X-ray images. However, these techniques yet embraced by medical community due several practical, ethical, regulatory constraints stemming "black-box" nature deep models. Additionally, most visible on X-rays are benign; therefore, narrow task computer vision-based nodule detection cannot equated automated detection. Addressing...

High-impedance faults are a challenging problem in power distribution systems. They often do not trigger protection devices and can result serious hazards such as igniting fires when contact with vegetation. The current research field dedicated to studying these is extensive but suffers from constraining bottleneck of lack real experimental data. Many works set detect localize rely on high-impedance fault low-fidelity models, the public data sets makes it impractical have objective...

High Impedance Faults (HIFs) are extensively addressed in the literature due to their safety hazards and fire risks. The consequent small amplitude of fault currents makes it a challenging disturbance be detected. Vegetation faults special case since even very low brief can result igniting embers. Such relevance led creation 'Vegetation Ignition Testing Program', experiment program funded by Victorian Government response series fires created faulty electric assets Australia. This paper aims...

High-impedance faults in power distribution systems is a lasting problem with decades of steady investigation. Due to the complexity problem, field can also be challenging navigate. Although there exist surveys literature, it not easy find comprehensive contextualization how and when developments unfolded. This paper presents historical narrative progress based on most cited papers since inception field. The accounts are limited archaic obsolete works. They all contextualized from seminal...

This paper presents an original methodology for extracting semantic features from X-rays images that correlate to severity a data set with patient ICU admission labels through interpretable models. The validation is partially performed by proposed method correlates the extracted separate larger does not contain ICU-outcome labels. analysis points out few explain most of variance between patients admitted in ICUs or not. methods herein can be viewed as statistical approach highlighting...

High-impedance faults (HIFs) behavior in power distribution systems depends on multiple factors, making it a challenging disturbance to model. Factors, such as network characteristics and impedance surface, can change the phenomena so intensely that insights about their may not translate well between with different parameters. Signal processing techniques help reveal patterns from specific types of fault, given availability sampled data real faults. The methodology described this article...

High Impedance Faults (HIFs) are disturbances with a potential to ignite bush fires. This work focuses on presenting physical and electrical phenomena associated earth faults for range of species. Phase analyzed in terms the fault current limit speed/nature current's development. HIFs that lead fires shown differ conduction continuity from those do not result ignition. Three stages ignition development investigated governing species under HIF scenario. The change Δ averaged RMS is yield...

The behavior of High-Impedance Faults (HIFs) in power distribution systems depends on multiple factors, making it a challenging disturbance to model. If enough data from real staged faults is provided, signal processing techniques can help reveal patterns specific type fault. Such task implemented herein by employing the Shift-Invariant Sparse Coding (SISC) technique set vegetation high-impedance faults. facilitates uncoupling shifted and convoluted present recorded signals fault tests....

Plant phenotyping tasks such as leaf segmentation and counting are fundamental to the study of phenotypic traits. Since it is well-suited for these tasks, deep supervised learning has been prevalent in recent works proposing better performing models at segmenting leaves. Despite good efforts from research groups, one main challenges methods still limitation labelled data availability. The field seem be augmenting existing limited sets, some aspects modelling process have under-discussed....

Plant phenotyping concerns the study of plant traits resulted from their interaction with environment. Computer vision (CV) techniques represent promising, noninvasive approaches for related tasks such as leaf counting, defining area, and tracking growth. Between potential CV techniques, deep learning has been prevalent in last couple years. Such an increase interest happened mainly due to release a data set containing rosette plants that defined objective metrics benchmark solutions. This...

The COVID-19 pandemic has triggered an urgent need to contribute the fight against immense threat human population. Computer Vision, as a subfield of Artificial Intelligence, enjoyed recent success in solving various complex problems health care and potential controlling COVID-19. In response this call, computer vision researchers are putting their knowledge base at work devise effective ways counter challenge serve global community. New contributions being shared with every passing day. It...

X-ray images may present non-trivial features with predictive information of patients that develop severe symptoms COVID-19. If true, this hypothesis have practical value in allocating resources to particular while using a relatively inexpensive imaging technique. The difficulty testing such comes from the need for large sets labelled data, which be well-annotated and should contemplate post-imaging severity outcome. This paper presents an original methodology extracting semantic correlate...