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Journal articles on the topic 'Jet expanding machine'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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1

Brianti, Greta, Roberto Iuppa, and Marco Cristoforetti. "Pipeline for performance evaluation of flavour tagging dedicated Graph Neural Network algorithms." Journal of Instrumentation 19, no. 02 (2024): C02064. http://dx.doi.org/10.1088/1748-0221/19/02/c02064.

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Abstract Machine Learning is a rapidly expanding field with a wide range of applications in science. In the field of physics, the Large Hadron Collider, the world's largest particle accelerator, utilizes Neural Networks for various tasks, including flavour tagging. Flavour tagging is the process of identifying the flavour of the hadron that initiates a jet in a collision event, and it is an essential aspect of various Standard Model and Beyond the Standard Model studies. Graph Neural Networks are currently the primary machine-learning tool used for flavour tagging. Here, we present the AUTOGRA

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2

Vishal Gotarane. "Optimizing Energy-Efficient Machine Learning Algorithms for Real-Time Attack Detection in IoT Devices." Journal of Electrical Systems 20, no. 3 (2024): 6912–19. https://doi.org/10.52783/jes.7214.

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Energy efficiency is a critical challenge in the expanding domain of In-ternet of Things (IoT) networks, where resource-constrained devices must operate securely under strict energy limitations. This study explores the application of Levy-Based Moth-Flame Optimization (LB-MFO) to enhance intrusion detection in IoT systems. Using the CICIDS 2017 dataset, LB-MFO was evaluated against standard machine learning models, including Logistic Regression, Decision Trees, Random Forest, and Support Vector Machines. To further optimize energy usage, techniques such as pruning, quantization, and model comp

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Jasmine Sabeena. "Fault Detection and Diagnosis in Electric Vehicle Systems using IoT and Machine Learning: A Support Vector Machine Approach." Journal of Electrical Systems 20, no. 3s (2024): 990–99. http://dx.doi.org/10.52783/jes.1414.

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This research examines blame discovery and determination in electric vehicle (EV) frameworks utilizing Internet of Things (IoT) information and machine learning calculations, centring on a Support Vector Machine (SVM) approach. The study points to improving the unwavering quality and security of EV operations by precisely recognizing and diagnosing flaws in real time. The test comes about illustrates the adequacy of the SVM-based approach, with an exactness of 95%, accuracy of 94%, review of 96%, and F1-score of 95%. Comparative investigation with elective calculations such as k-Nearest Neighb

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Vijay Singh Sen. "Transcending Linguistic Boundaries: A Technical Exploration of The Evolution and Future Trajectory of Corpus-Based Machine Translation." Journal of Electrical Systems 20, no. 7s (2024): 2502–9. http://dx.doi.org/10.52783/jes.4073.

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This review paper presents a comprehensive examination of the evolution, current state, and future perspectives of machine translation (MT). The field of MT, encompassing the automatic translation of text from one language to another, has undergone significant transformations from rule-based methods to statistical models, and more recently, to neural network-based approaches. By synthesizing current research and technological progress, this paper aims to provide a detailed understanding of the dynamic landscape of machine translation and its future directions. In today's globalized world, lang

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Sumanta Chatterjee. "Next-Generation Helmet Detection: A Real-Time Approach with Cutting-Edge Vision Technique." Journal of Electrical Systems 20, no. 11s (2024): 1793–800. https://doi.org/10.52783/jes.7618.

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This research work addresses the critical need for improved road safety by developing a real-time motorcycle helmet detection system using advanced machine learning techniques. The system processes video feeds from surveillance cameras to detect helmet compliance and identify violators by detecting number plate information. Utilizing Convolutional Neural Networks (CNNs) like YOLO, the system ensures accurate detection. It is designed for real-time processing and scalability, seamlessly integrating with existing traffic monitoring infrastructures. Extensive testing on diverse datasets confirms

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Dovbysh, Anatolii, Vladyslav Piatachenko, Mykyta Myronenko, Mykyta Suprunenko, and Julius Simonovskiy. "Hierarchical Information-Extreme Machine Learning of Hand Prosthesis Control System Based on Decursive Data Structure." Journal of Engineering Sciences 11, no. 2 (2024): E1—E8. http://dx.doi.org/10.21272/jes.2024.11(2).e1.

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The article considers the machine learning method for a hand prosthesis control system that recognizes electromyographic signals with a non-invasive recording system. The method was developed within the information-extreme intelligent data analysis technology framework to maximize the system’s information capacity during machine learning. The method is based on adapting the input information description to maximize the probability of correct classification decisions, similar to artificial neural networks. However, unlike neural-like structures, the proposed method was developed within a functi

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Deng, Yanyao. "A Systematic Review of Application of Machine Learning in Curriculum Design Among Higher Education." Journal of Emerging Computer Technologies 4, no. 1 (2024): 15–24. http://dx.doi.org/10.57020/ject.1475566.

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Machine learning has become an increasingly popular area of research in the field of education, with potential applications in various aspects of higher education curriculum design. This study aims to review the current applications of AI in the curriculum design of higher education. We conducted an initial search for articles on the application of machine learning in curriculum design in higher education. This involved searching three core educational databases, including the Educational Research Resources Information Centre (ERIC), the British Education Index (BEI), and Education Research Co

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8

Huang, Ruixia. "Design and Implementation of English Writing Aids Based on Natural Language Processing." Journal of Electrical Systems 20, no. 6s (2024): 2178–87. http://dx.doi.org/10.52783/jes.3132.

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The design and implementation of English writing aids based on natural language processing (NLP) involve leveraging advanced algorithms and techniques to assist users in improving their writing skills. These aids can encompass various functionalities such as grammar and spell checking, style suggestions, vocabulary enhancement, and plagiarism detection. By analyzing the context, structure, and semantics of the text, NLP models can provide intelligent feedback and recommendations to help users express themselves more effectively. Additionally, interactive features such as real-time editing and

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V, Shwetha, Abinaya Selvarajan, Aarthi A, and Sneka R. "Quantum Speedup for Linear Systems: An Analysis of the HHL Algorithm Using IBM Qiskit." Journal of Electronics and Informatics 6, no. 4 (2025): 317–31. https://doi.org/10.36548/jei.2024.4.003.

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One of the most significant developments in quantum computing is the Harrow-Hassidim-Lloyd (HHL) method, which can solve linear equation systems at exponential speedup. Because linear systems are essential to many scientific fields, including physics, engineering, and machine learning, this approach has great potential to revolutionize computational paradigms. The HHL algorithm is thoroughly examined in this work, with particular attention paid to its theoretical framework, real-world application utilizing IBM's Qiskit platform, and the difficulties in simulating quantum algorithms on noisy in

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Bireshwar Ganguly,. "Navigating Industry 4.0 Frontiers: A Scalable and Resilient Next-Generation IoT Framework to Implement Future Advancements in Smart and Adaptive Industrial Systems." Journal of Electrical Systems 20, no. 1s (2024): 444–54. http://dx.doi.org/10.52783/jes.784.

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The emergence of Industry 4.0 signifies a paradigm shift in industrial systems, characterized by the amalgamation of digital technologies with tangible operations. The goal of this study is to present a state-of-the-art, scalable, and robust Internet of Things (IoT) framework that will enable future innovations in intelligent and adaptable industrial systems to be seamlessly integrated. Our framework gives scalability first priority in response to Industry 4.0's dynamic nature, which is marked by fast technical evolution and rising connection in order to handle the expanding ecosystem of netwo

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Rohit R Dixit. "Data-Driven Decision Support Systems for Drug Discovery and Development: A Case Study in Pharmaceutical Management." Journal of Electrical Systems 20, no. 3s (2024): 691–99. http://dx.doi.org/10.52783/jes.1360.

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This paper covers the use and influence of data-driven decision support systems (DSS) on drug management, particularly in the areas of drug exploration and production. The study, which employed a mixed-methods approach, involving literature review, qualitative interviews, quantitative assessments, and case study analysis, reveals the AI, machine learning and big data analytics ability to drive drug discovery and development processes revolution in the pharmaceutical industry. The study shows that handling of DSS allows sound decision making, consequently resulting in improved efficiency, decre

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Drakshayani Desai, Harsha Jitendra Sarode. "Customized Mechanism for Diabetic Risk Prediction: A Hybrid CNN–Autoencoder Approach with Emphasis on Retinal Imaging in the Elderly." Journal of Electrical Systems 20, no. 1s (2024): 190–99. http://dx.doi.org/10.52783/jes.764.

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Diabetes Mellitus presents a substantial health obstacle on a global scale, with a particular impact on the elderly demographic. Prompt identification is vital for efficient control and avoidance of complications. This study introduces a new Hybrid Convolutional Neural Network (CNN) and Autoencoder model specifically developed for accurately predicting the risk of diabetes at an early stage. The model is specifically designed to analyze retinal images in older individuals. The introduction of this paper presents a comprehensive analysis of the increasing incidence of diabetes in the elderly po

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Sutton, Steve G., Vicky Arnold, and Matthew Holt. "How Much Automation Is Too Much? Keeping the Human Relevant in Knowledge Work." Journal of Emerging Technologies in Accounting 15, no. 2 (2018): 15–25. http://dx.doi.org/10.2308/jeta-52311.

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ABSTRACT With the rapid advances in data analytics, machine learning, and continuous monitoring along with other related advances in artificial intelligence-based technologies, our solution as researchers to many of today's business problems increasingly becomes one of, “Can I fix the problem through automation?” However, as we find that artificial intelligence increasingly provides us with the power to replace knowledge workers with automated systems, rarely is the question asked, “Should we automate knowledge work?” There are a host of questions that should be addressed including (1) whether

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14

Kshirod Sarmah. "A State-of-arts Review of Deep Learning Techniques for Speech Emotion Recognition." Journal of Electrical Systems 20, no. 7s (2024): 1638–52. http://dx.doi.org/10.52783/jes.3745.

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In sophisticated Human-Computer Interfaces (HCI), the emotional state of the user is becoming a crucial component that is closely linked to emotional speech recognition. Spoken expressions, which can be a part of human-machine interaction, are an important source of emotional information. Speech emotion recognition (SER) in deep learning (DL) continues to be a hot topic, especially in the field of emotional computing. Current deep learning (DL) and neural network methods are applied in this highly active field of research. This is as a result of its expanding potential, advancements in algorit

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Praloy Biswas. "Review on Multi-lingual Sentiment Analysis in Health Care." Journal of Electrical Systems 20, no. 3 (2024): 3394–405. http://dx.doi.org/10.52783/jes.4975.

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Multilingual sentiment analysis in healthcare is rapidly expanding, utilizing machine learning methods to identify emotions and sentiments in material written in several languages. This multidisciplinary field integrates computational linguistics, natural language processing, and health informatics to help healthcare providers better comprehend patient attitudes. Sentiment analysis is particularly useful in the healthcare industry since it facilitates comprehension of patient feedback, responses to interventions, and general contentment. Moreover, in an increasingly interconnected society, it

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16

Engels, Andreas, Mike Thomas Hauschultz, Hannes Jacobs, and Andreas H. Foitzik. "High Volume 3D Printer and Developed of High-Volume Extruders for Gelatin and Liquids." Key Engineering Materials 964 (November 23, 2023): 143–49. http://dx.doi.org/10.4028/p-sufk67.

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Over the last decade, the development of 3D printing technology has led to both increased interest and availability of these machines. The steady growth and demand have made 3D printing an affordable and consumer-friendly craft. Due to the shrinking barrier-of-entry, the technology is increasingly integrated into wider areas of science and research, as well as the manufacturing industry in general. The demand for individualized medical solutions is continuously expanding in multiple fields, such as medical training and patient-specific surgical guides—exposing a need for further development of

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17

Bespalov, A. L., I. G. Svidrak, and O. O. Boiko. "Increase the functionality of vibration feeders with electromagnetic vibration." Scientific Messenger of LNU of Veterinary Medicine and Biotechnologies 23, no. 95 (2021): 33–37. http://dx.doi.org/10.32718/nvlvet-f9506.

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Under modern conditions vibrating hopper feeders with electromagnetic drive are irreplaceable when it comes to production processes in mechanical engineering and instrument making optimization processes. They are used to download small, medium or miniature details to automated technological equipment, such as automatic machines, automatic lines and automated complexes, or any other flexible automated production. The vibrating hopper loading devices are most commonly used in transportation and loading of details on working positions of assembly automatic machines and assembly automated complexe

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18

Al-Khadaar, Rana M., and Mahmood D. Ahmed. "Experimental and theoretical analysis of single-jet column and concrete column using double-jet grouting technique applied at Al-Rashdia site." Open Engineering 14, no. 1 (2024). http://dx.doi.org/10.1515/eng-2022-0596.

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Abstract Progress in jet grouting technology has been focused on the cutting-edge observer of jets, which aims to generate large columns of jet grouting and increase the activity of construction sites. Since jet grouting techniques vary from conventional grouting methods to modern techniques, they can be used in a variety of soil types and their application areas are expanding quickly. So, grouting methods have become very popular methods for subsoil strengthening. This article includes finding the physical and mechanical properties of the soil of the AL-Rashdia site, using a single-jet grouti

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19

Hou, Yanbei, Ming Gao, Jingwen Gao, et al. "3D Printed Conformal Strain and Humidity Sensors for Human Motion Prediction and Health Monitoring via Machine Learning." Advanced Science, November 8, 2023. http://dx.doi.org/10.1002/advs.202304132.

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AbstractWearable sensors have garnered considerable attention due to their flexibility and lightweight characteristics in the realm of healthcare applications. However, developing robust wearable sensors with facile fabrication and good conformity remains a challenge. In this study, a conductive graphene nanoplate‐carbon nanotube (GC) ink is synthesized for multi jet fusion (MJF) printing. The layer‐by‐layer fabrication process of MJF not only improves the mechanical and flame‐retardant properties of the printed GC sensor but also bolsters its robustness and sensitivity. The direction of senso

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20

Prasad, Ranjeet, Manish Oraon, and Vinay Sharma. "Exploring Advancements in Incremental Sheet Metal Forming: A Review." Engineering Research Express, January 20, 2025. https://doi.org/10.1088/2631-8695/adac2d.

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Abstract Incremental Sheet Metal Forming (ISMF), a gradually prominent technique in metal forming, facilitates the production of small batches and prototype products by utilising CNC machine-controlled tool motion. Metal forming is significant in diverse industries, including automotive, aerospace, manufacturing, and construction. Conventional metal forming methods encounter limitations in flexibility, cost-effectiveness, and productivity. The recent ISMF technology presents promising solutions to overcome these challenges. Lightweight alloys such as magnesium, titanium, and aluminium face for

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21

Litaudon, Xavier L., Hans-Stephan Bosch, Tomohiro Morisaki, et al. "Long plasma duration operation analyses with an international multi-machine (tokamaks and stellarators) database." Nuclear Fusion, October 23, 2023. http://dx.doi.org/10.1088/1741-4326/ad0606.

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Abstract Combined high-fusion performance and long-pulse operation is one of the key integration challenges for fusion energy development in magnetic devices. Addressing these challenges requires an integrated vision of physics and engineering aspects with the purpose of simultaneously increasing time duration and fusion performance. Significant progresses have been made in tokamaks and stellarators including very recent achievement in duration and/or performance. These progresses are reviewed by analyzing the experimental data provided by 10 tokamaks (ASDEX Upgrade, DIII-D, EAST, JET, JT60-U,

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22

Rami, Mohammad Abu Wadi. "Impact of Fintech on Performance of Banks: Empirical Evidence From Jordan." February 12, 2023. https://doi.org/10.5281/zenodo.7633680.

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<strong>Abstract:</strong> Today, technology is expanding over most aspects including financial issues. Financial technology is considered as a creative innovation that attracts more customers and enhances the performance of many banks. To accomplish this, this study made an attempt to assess the impact of implementing Fintech on performance of commercial banks in Jordan for the period 2012-2020 using the panel data. The research employed return on equity (ROE) as a proxy to measure the performance level in addition to three types of control variables applied in this study Gross Domestic Produ

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23

Pregowska, Agnieszka, Agata Roszkiewicz, Magdalena Osial, and Michael Giersig. "How scanning probe microscopy can be supported by artificial intelligence and quantum computing?" Microscopy Research and Technique, June 12, 2024. http://dx.doi.org/10.1002/jemt.24629.

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AbstractThe impact of Artificial Intelligence (AI) is rapidly expanding, revolutionizing both science and society. It is applied to practically all areas of life, science, and technology, including materials science, which continuously requires novel tools for effective materials characterization. One of the widely used techniques is scanning probe microscopy (SPM). SPM has fundamentally changed materials engineering, biology, and chemistry by providing tools for atomic‐precision surface mapping. Despite its many advantages, it also has some drawbacks, such as long scanning times or the possib

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Moore, Kyle. "Painting the Town Blue and Green: Curating Street Art through Urban Mobile Gaming." M/C Journal 18, no. 4 (2015). http://dx.doi.org/10.5204/mcj.1010.

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Released in 2012 as an Android only open-beta, Ingress is an alternate-reality game for mobile devices. Developed by Niantic Labs, a subsidiary of Google, Ingress now has 7 million users worldwide (Ingress) on both Android and Apple operating systems. Players are aligned to one of two opposing factions, the Resistance (Blue) and the Enlightened (Green). Working on behalf of their faction, individual players interact with “portals” in order to establish dominance over material environments. Portals are located at places of educational or historical value, public artworks, “hyper-local” location

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25

Beyer, Sue. "Metamodern Spell Casting." M/C Journal 26, no. 5 (2023). http://dx.doi.org/10.5204/mcj.2999.

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There are spells in the world: incantations that can transform reality through the power of procedural utterances. The marriage vow, the courtroom sentence, the shaman’s curse: these words are codes that change reality. (Finn 90) Introduction As a child, stories on magic were “opportunities to escape from reality” (Brugué and Llompart 1), or what Rosengren and Hickling describe as being part of a set of “causal belief systems” (77). As an adult, magic is typically seen as being “pure fantasy” (Rosengren and Hickling 75), while Bever argues that magic is something lost to time and materialism,

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