Search
816 articles for “machining time”
-
A Review on Lung Cancer Prediction Using Machine Learning
Abstract: Lung cancer continues to be a major contributor to cancer-related mortality across the globe. Timely diagnosis and reliable prediction models play a crucial role in enhancing treatment outcomes and survival rates for patients. The present study focuses on the utilization of machine learning (ML) methods for the prediction of lung cancer. Using datasets that incorporate clinical records, imaging modalities, and genetic profiles, the research assesses the predictive capabilities of multiple …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–11 Read article
-
Physically Challenged People Health Monitoring System Using Blynk Server
Abstract: Because of the fast pace of modern life, keeping an eye on persons who are physically challenged is a challenging task. Examining the medical histories of persons who are physically challenged who live in their homes is a challenging endeavor. In this paper, a proposal was made to maintain a continuous health monitoring system for intelligent people who are physically challenged. The system would use sensors to monitor the health …
Published in Trends in Opto-electro & Optical Communication · Vol. 12, Issue 3, 2022 · pp. 11–18 Read article
-
Smart-Waste-Management-System
Abstract: The rapid urbanization and increasing waste generation pose significant challenges to traditional waste management systems, necessitating innovative solutions that integrate economic principles and management strategies. In order to enhance trash transportation and recycling procedures, this paper investigates the deployment of a Smart trash Management System that makes use of Internet of Things (IoT) components and machine learning algorithms. By applying economic principles such as cost-benefit analysis and resource allocation, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 18–27 Read article
-
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
-
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
-
Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
-
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
-
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
-
Plc Hmi base testing machine data loger with usb excel data export
Abstract: The PLC-HMI-based testing machine data logger is designed to acquire, process, and log real-time sensor data using a PLC analog input card. This system is developed for industrial applications requiring accurate measurement, monitoring, and data storage. The setup integrates an HMI (Human-Machine Interface) for visualization and control, while a USB-based Excel data export feature ensures efficient data management. The system incorporates four key transducers: 1. Water Flow Sensor – Measures …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 47–54 Read article
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
Pharma Guard: Smart Medication Management System
Abstract: Pharma Guard Smart Medication Management System presenting a comprehensive overview of an innovative technology designed to revolutionize medication management in healthcare settings. In an era of advancing digital solutions, the Pharma Guard system offers a sophisticated approach to ensuring medication safety and adherence. Through the integration of smart technology, including internet of things (IoT) devices and machine learning algorithms, Pharma Guard enables real-time monitoring, tracking, and management of medication consumption …
Published in International Journal of Mobile Computing Technology · Vol. 2, Issue 1, 2024 · pp. 30–37 Read article
-
Revolutionizing Motorcycle Safety: A Deep Learning Approach for Helmet and Triple Riding Detection using Computer Vision Technology and Machine Learning Model
Abstract: Introducing a revolutionary paradigm in road safety, our project unveils the Intelligent Traffic Surveillance System (ITSS), a groundbreaking initiative poised to transform urban traffic management. In an era where road safety is paramount, ITSS emerges as a beacon of innovation, harnessing the prowess of computer vision and machine learning to tackle two of the most pressing concerns plaguing our roads: helmet non-compliance and triple riding among motorcyclists. At its core, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 28–36 Read article
-
Employee Well-Being: Deep Learning Approaches to Stress Detection
Abstract: Stress has become a major concern for employee health, productivity, and overall well-being in today's fast-paced work environment. It is a growing global issue, affecting both individual employees and the productivity of organizations. Work-related stress occurs when the demands of a job surpass an individual's ability to manage, whether because of long hours, overwhelming responsibilities, or other pressures. Factors such as conflicts with coworkers or supervisors, constant changes, and job …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 52–58 Read article
-
Recent Advances and Future Prospects in Digital Twin Technology for Battery Management Systems of Electric Vehicles
Abstract: Digital twin technology in battery management systems (BMS) for electric cars (EVs) represents a major development in the automotive industry. Digital twins provide predictive maintenance, modelling, and real-time monitoring by creating virtual copies of real-time monitoring, actual battery systems. This paper describes the functional components, architecture, and design of Digital Twin technology along with how it may be included into BMS. Emphasizing how consistent data flow from sensors improves battery …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 2, 2025 Read article