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1087 articles for “time machine”
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Machine Learning for Finding Materials for Membranes
Abstract: Traditionally, finding and improving membrane materials has depended on trial-and-error experiments, which can take a long time, cost a lot of money, and only cover a small area. Recent improvements in machine learning (ML) have the potential to change the way membrane materials are designed by making it possible to make predictions about performance, selectivity, and stability based on data. ML algorithms can find hidden links between the structure, composition, …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
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A Study on Time Optimization of Recoat Calender in Tyre Manufacturing Process
Abstract: Seven components are produced by the recoat calender in this plant. The machine cannot satisfy the current requirements of the company. Utilization planning of the 36 inch recoat calender. Optimize the production time and introduce a compound slitter.
Published in Journal of Automobile Engineering and Applications · Vol. 2, Issue 2, 2015 · pp. 1–4 Read article
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Real-time Facial Recognition with Convolutional Neural Networks for Personalized Music Therapy
Abstract: In this project, a web-based application has been developed that integrates computer vision-based facial recognition, multiple algorithms, and machine learning approaches. The given system obtains a user’s emotions in the real-time frame by analyzing facial expressions such as eyes, mouth, the forehead, and so on. It detects emotions like happiness, sadness, that is neutrality, or rock. For a given detected emotion, language, and a user’s chosen artist, the system recommends …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 67–76 Read article
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Integrating Digital Twins, Smart Materials, and Human Machine Collaboration for Sustainable Smart Manufacturing: Smart CNC & Industry 4.0 Applications
Abstract: The rapid evolution of Industry 4.0 and the emerging transition toward Industry 5.0 have been catalyzed by the convergence of intelligent digital technologies such as digital twins, cyber–physical systems (CPS), artificial intelligence (AI), the Internet of Things (IoT), and human-in-the-loop (HITL) frameworks. These technologies have transformed traditional manufacturing into adaptive, data-centric ecosystems capable of real-time optimization and predictive decision-making. In recent years, the fusion of computer numerical control (CNC) machines, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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Integrating Digital Twins, Smart Materials, and Human Machine Collaboration for Sustainable Smart Manufacturing: Smart CNC & Industry 4.0 Applications
Abstract: The rapid evolution of Industry 4.0 and the emerging transition toward Industry 5.0 have been catalyzed by the convergence of intelligent digital technologies such as digital twins, cyber–physical systems (CPS), artificial intelligence (AI), the Internet of Things (IoT), and human-in-the-loop (HITL) frameworks. These technologies have transformed traditional manufacturing into adaptive, data-centric ecosystems capable of real-time optimization and predictive decision-making. In recent years, the fusion of computer numerical control (CNC) machines, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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Integrating Digital Twins, Smart Materials, and Human Machine Collaboration for Sustainable Smart Manufacturing: Smart CNC & Industry 4.0 Applications
Abstract: The rapid evolution of Industry 4.0 and the emerging transition toward Industry 5.0 have been catalyzed by the convergence of intelligent digital technologies such as digital twins, cyber–physical systems (CPS), artificial intelligence (AI), the Internet of Things (IoT), and human-in-the-loop (HITL) frameworks. These technologies have transformed traditional manufacturing into adaptive, data-centric ecosystems capable of real-time optimization and predictive decision-making. In recent years, the fusion of computer numerical control (CNC) machines, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Parameters Optimization of EDM of AISI 316 Stainless Steel Material using RSM
Abstract: In this paper, cutting of SS316 material using electro discharge machining (EDM) with a copper electrode using RSM technique is discussed. Electrical discharge machining (EDM) is one of the earliest non-traditional machining processes [1]. These methodologies are used to analyze the effect of each parameter on the machining characteristics and to predict the optimal choice for each EDM parameter such as peak current, gap voltage and pulse on time. It …
Published in Journal of Industrial Safety Engineering · Vol. 3, Issue 2, 2016 · pp. 23–29 Read article
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A Machine learning approach to asses carbon emission, utility to produce biomaterial
Abstract: The transportation sector, and the automotive industry in particular, has grown significantly over the last ten years. However, these quick advancements have also brought about important problems that require workable answers. The problem of carbon emission is responsible for global warming due to greenhouse gas emission. The present work is focused on CO2 emission from public and personal transport within Agra city on a real-time basis. In the context of …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 22–30 Read article
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Random Forrest Based Man-in-the-Middle Attack Detection in Advanced Metering Infrastructure
Abstract: Advanced metering infrastructure (AMI) plays a central role in the operation of modern smart grid (SG) systems by enabling continuous, two-way communication between utility providers and consumers. Through this communication, AMI supports real-time monitoring, dynamic pricing, and efficient energy management. However, the same connectivity that makes AMI effective also increases its exposure to cyber threats. One of the most critical threats is the man-in-the-middle (MITM) attack, in which an attacker …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 1–8 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Implementation of Renewable Energy Resource in 5-In-1 Agro-Machine
Abstract: Since agriculture is the backbone of Indian economy and above 70% of Indian people are depending on agriculture, the development of agriculture process takes a vital role. From few decades, even though improved agricultural machineries have been invented, they have not been reached. Agri-process is the most important endeavor in the world as it imparts about 8.4% to the total gross domestic product and provides employment to over 60 of …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 10, Issue 2, 2019 · pp. 35–39 Read article
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Identification of Moisture Content in Paper Industry Using PID Auto-Tuning
Abstract: The maintenance of removal of moisture content in pulp is one of the major challenges in paper manufacturing process. In some paper industries, the above process is carried out using open loop method. This method uses more labor to monitor and control the process parameters such as moisture and temperature. Also the accurate maintenance is not possible and it takes more time for tuning the process parameter. So the closed …
Published in Journal of Industrial Safety Engineering · Vol. 3, Issue 1, 2016 · pp. 15–25 Read article
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Smart Education through Machine Learning: A Review of Trends, Benefits, and Risks
Abstract: Machine learning (ML) is transforming the contemporary education by transforming it into smarter, data-driven and personalised learning. This review examines the key tendencies, advantages, and possible threats of applying ML in intelligent education. ML promotes adaptive learning, automatization of assessments, and student engagement, which is highly beneficial both to learners and educators. Nonetheless, issues like data privacy, algorithmic bias or unequal access are also a significant concern. The article emphasises …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 24–28 Read article
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Utilizing Machine Learning to Combat Plant Disease
Abstract: Plant diseases are a significant source of lost income and time for the agricultural industry. Accurately diagnosing an illness requires a high level of experience and dedication. Symptoms of plant diseases, such as spots or streaks of a different colour, are sometimes visible on the leaves of infected plants. Many fungal, bacterial, and viral organisms may also cause illness in plants. The indications and symptoms of a plant disease are …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 20–28 Read article
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Automatic Cloth Cutting Machine Using Programmable Logic Controller
Abstract: AbstractDuring the past few decades, the automation industry has shown a great progress in automatic control of different systems. The manual handling of any system results in less accuracy as compared to automatic control system. This project basically gives an initial theme that how an approach to a cloth cutting can be done using PLC. So, design of automatic cloth cutting machine has been made which gives more accuracy, reduces …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 7, Issue 2, 2019 · pp. 1–3 Read article
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Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction
Abstract: The integration of machine learning algorithms in healthcare has revolutionized the way we approach disease prediction and diagnosis. An attempt to employ machine learning techniques to forecast numerous diseases is presented in this study. A diverse dataset containing patient records, medical history, and relevant features for various diseases was used to develop predictive models. Feature selection and normalization were among the preprocessing methods used to clean and prepare the data. …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 1, 2025 · pp. 1–6 Read article
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Recent Advances in Quality Control and Quality Assurance: Enhancing Pharmaceutical Product Integrity and Compliance
Abstract: The pharmaceutical industry is undergoing a paradigm shift driven by stringent regulatory expectations and the demand for high-quality, safe, and efficacious drug products. Quality Control (QC) and Quality Assurance (QA) serve as the two foundational pillars that ensure pharmaceutical integrity from raw material acquisition through to product release. Traditional QC and QA practices, while effective, have been challenged by complex formulations, biologics, and personalized medicine, requiring innovative methodologies and technologies. …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 54–62 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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Machine Learning Approaches for Intelligent Network Traffic Management in 6G
Abstract: The increasing adoption of smart devices, Internet of Things (IoT) technologies, cloud-based services, autonomous applications, and multimedia platforms has greatly enhanced the demands and complexity of modern wireless communication networks. To meet these evolving requirements, upcoming sixth-generation (6G) communication systems are anticipated to deliver extremely high data transmission speeds, support a vast number of connected devices, ensure minimal communication delays, enable intelligent network management, and provide seamless real-time connectivity for …
Published in Journal of Communication Engineering & Systems · Vol. 16, Issue 2, 2026 · pp. 19–32 Read article