This paper presents a comprehensive review of static transfer switch (STS) applications in AC power systems, with a focus on enhancing reliability and fault tolerance. The review outlines the fundamental requirements for effective STS deployment, including the necessity of two truly independent and nominally synchronized AC power sources, optimal placement of the STS near protected loads, and proper grounding practices to minimize single points of failure. The analysis synthesizes recent literature on STS topologies, control mechanisms, and integration with uninterruptible power supplies (UPS), highlighting the importance of redundancy and the persistent challenges of achieving source independence and synchronization. Empirical studies and case analyses are discussed to demonstrate the impact of STS design and deployment on minimizing risks to sensitive loads. The paper concludes by providing practical recommendations and identifying future research directions for further improving STS solutions in resilient AC power systems.
Electrical engineering. Electronics. Nuclear engineering, Information technology
Metwally Rashad, Doaa M. Alebiary, Mohammed Aldawsari
et al.
The expressions on human faces reveal the emotions we are experiencing internally. Emotion recognition based on facial expression is one of the subfields of social signal processing. It has several applications in different areas, specifically in the interaction between humans and computers. This study presents a simple CCNN-SVM automated model as a viable approach for FER. The model combines a Convolutional Neural Network for feature extraction, certain image preprocessing techniques, and Support Vector Machine (SVM) for classification. Firstly, the input image is preprocessed using face detection, histogram equalization, gamma correction, and resizing techniques. Secondly, the images go through custom single Deep Convolutional Neural Networks (CCNN) to extract deep features. Finally, SVM uses the generated features to perform the classification. The suggested model was trained and tested on four datasets, CK+, JAFFE, KDEF, and FER. These datasets consist of seven primary emotional categories, which encompass anger, disgust, fear, happiness, sadness, surprise, and neutrality for CK+, and include contempt for JAFFE. The model put forward demonstrates commendable performance in comparison to existing facial expression recognition techniques. It achieves an impressive accuracy of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>99.3</mn><mo>%</mo></mrow></semantics></math></inline-formula> on the CK+ dataset, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>98.4</mn><mo>%</mo></mrow></semantics></math></inline-formula> on the JAFFE dataset, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>87.18</mn><mo>%</mo></mrow></semantics></math></inline-formula> on the KDEF dataset, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>88.7</mn><mo>%</mo></mrow></semantics></math></inline-formula> on the FER.
Abstract Selecting greener solvents during experiment design is imperative for greener chemistry. While many solvent selection guides are currently used in the pharmaceutical industry, these are often paper-based guides which can make it difficult to identify and compare specific solvents. This work presents a stand-alone version of the solvent flashcards that were developed as part of the AI4Green electronic laboratory notebook. The functionality is an intuitive and interactive interface for the visualisation of data from CHEM21, a pharmaceutical solvent selection guide that categorises solvents according to “greenness”. This open-source software is written in Python, JavaScript, HTML and CSS and allows users to directly contrast and compare specific solvents by generating colour-coded flashcards. It can be installed locally using pip, or alternatively the source code is available on GitHub: https://github.com/AI4Green/solvent_flashcards . The documentation can also be found on GitHub or on the corresponding Python Package Index webpage: https://pypi.org/project/solvent-guide/ . Scientific Contribution This simple and easy-to-use digital tool provides a visualisation of solvent greenness data through a novel intuitive interface and encourages green chemistry. It offers numerous advantages over traditional solvent selection guides, allowing users to directly customise the solvent list and generate side-by-side comparisons of only the most important solvents. The release as a standalone package will maximise the benefit of this software. Graphical Abstract
At present, the frequency of non-geostationary orbit(NGSO) mobile satellite service is becoming more and more tense.Aimed at the complicated problem of frequency coordination of mobile direct connection to NGSO satellite service, firstly, an analysis was conducted on the current frequency usage status and trends of mobile direct connection to NGSO satellite service.Secondly, the frequency coordination scheme between mobile direct connection to NGSO satellite service and other same frequency space services in extended L-band was analyzed and studied.By analyzed the frequency coordination of mobile direct connection to NGSO satellite service in extended L-band, the space services that need to carry out frequency coordination work with mobile direct connection to NGSO satellite service were determined.The basic frequency coordination scheme of mobile direct connection to NGSO satellite service with each space service was studied and the coordination scheme suggestions were given, at the same time, the interference analysis and calculation involved in the specific coordination scheme were listed for example.The above research can be used as reference for the research of frequency coordination of mobile direct connection to NGSO satellite service system, as well as for the next step research of key technologies related to mobile direct connection to NGSO satellite service.
Hydrocarbons are one of the subclasses of organic compounds that comprise exactly of hydrogen and carbon. Alkanes are one of the types of hydrocarbons that have chemical formula CnH2n+2. Isomers are molecules with identical chemical formula but different structural arrangements, leading to variations in their spectral properties as their corresponding molecular graphs also differ in structure. This exploration is motivated by the understanding that variations in structural configurations manifest as differences in spectral properties, as evidenced by alterations in their respective molecular graphs. Alkanes with ten carbon atoms are called decanes. Our study employs a multifaceted approach, encompassing the determination of spectral properties and the calculation of eigenvalue-based entropy for the C10H22 decane isomers. This analysis is undertaken with the goal of unravelling the intricate relationships between structural variations and corresponding spectral bounds. Notably, our investigation extends beyond the realm of molecular structures to draw connections with physico-chemical properties. Through meticulous comparison of the obtained spectral data with the known characteristics of C10H22 isomers, we unveil interesting correlations among the characteristics. We establish that the spectral gap, a key parameter in our study, intriguingly exhibits a maximal correlation with the refractive index of the isomers. This finding not only enhances our understanding of the spectral intricacies of decane isomers but also underscores the practical implications of such research. The correlation between spectral gap and refractive index opens avenues for predicting and manipulating the optical properties of hydrocarbons, offering potential applications in diverse fields, from materials science to optics. In essence, this study bridges the gap between molecular structure and macroscopic properties, shedding light on the intricate interplay between isomeric variations and their consequential effects on spectral characteristics.