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1281 articles for “machines”
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Sentiment Analysis of X (Formerly Twitter) Using Machine Learning
Abstract: Sentiment analysis is a methodology to determine the nature and behavior of each and every user for the content posted on the social media platform in the form of post and feed. Consumers of the online platform are encouraged to post reviews of the product that they purchase. Little attempt is created by Amazon to confine or limit the content of these reviews. The number of reviews for various merchandise …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 2, 2024 · pp. 28–37 Read article
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House Price Prediction Using Linear Regression In Machine Learning
Abstract: In the modern world, real estate is among the most important investments, particularly in a city like Chennai, which is where many people aspire to work and settle down. Due to people's high purchasing power, this will cause property prices to rise daily. When purchasing a home, buyers will consider whether or not it will yield a healthy profit margin. Hence, before spending your hard-earned money on any property, it …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 92–100 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Identifying and Implementing a Machine Learning Model Suitable for Processing Visually Evoked Potential
Abstract: A Brain-Computer Interface (BCI) is a system that translates brain activity patterns into computer commands, bypassing physical movement. Electroencephalography (EEG) is commonly used to acquire signals in BCI research. Visual evoked potentials (VEPs) are brain responses in the visual cortex to visual stimuli. Recent studies show that exposing individuals to flickering at a consistent frequency generates EEG signals synchronized with the stimulation. Efficient extraction of VEP signals begins with preprocessing …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Bank Locker Security System Using Machine Learning
Abstract: The Bank Locker Security System integrates cutting-edge technology solutions to strengthen the security of bank locker facilities. This system uses biometric identification techniques, such as facial recognition and fingerprint scanning, to confirm users' identities before granting them access to the lockers. Furthermore, access control techniques based on RFID technology are employed to augment security protocols. The locker area is equipped with real-time monitoring and alerting tools that enable fast detection …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 16–20 Read article
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Utilizing Machine Learning for Waste Analysis
Abstract: The Internet of Things can be expanded to include any physical object with an IP address that allows data to be transmitted over a network by installing electronic devices such as networking hardware, sensors, and software. The Internet of Things (IoT) offers enhanced connectivity for an array of devices, services, protocols, and applications. It is further defined by its diverse nature. Not just in houses and smart cities has IoT …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Automating Compiler Optimization: A Machine Learning Approach
Abstract: This study reports on an ML-based approach to compiler optimization, complementing traditional optimization methods that rely strongly on hand-tuned settings. Compiler optimization plays a key role in performance-speedup and energy optimization of complex contemporary software systems. However, the traditional approach to optimizer settings involves laborious, error-prone, and scale-insensitive human-in-the-loop intervention, especially in the complex and high-demand environments in which today's computing application thrives. By integrating RL and GA, we can …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 12–16 Read article
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Textual Clues to Stress: A Machine Learning Approach
Abstract: Nowadays, numerous individuals utilize social media platforms to share tweets about their daily lives, which often reflect their mental well-being. Recognizing and managing stress is essential before it becomes a serious issue. Each day, a significant volume of informal messages is posted on discussion forums, blogs, and social networking sites. This study introduces a method for detecting stress using information gathered from social media, with a focus on Twitter. The …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 72–76 Read article
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Pothole Detection utilising Machine Learning: A Review
Abstract: Potholes must be found and fixed quickly in order to maintain infrastructure, maximize transportation systems, and guarantee road safety. Using the Sequential API and the Keras library, this study presents a neural network model for pothole detection. Convolutional layers with ReLU activation, global average pooling, dense layers with dropout, and softmax activation for binary classification make up the model architecture. Image loading, resizing, array conversion, labeling, shuffling, normalization, and one-hot …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 35–43 Read article
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Cloud Enabled Machine Learning Framework for Medicine System
Abstract: The Medicine Generic App is a cutting-edge mobile application designed to empower users with information about generic medications. Given the rising expenses of healthcare and prescription medications, this app acts as a useful resource for consumers to make informed decisions regarding their medication options. The Medicine Generic App aims to promote generic drug usage, reduce healthcare costs, and improve medication management for users. By providing detailed information and price transparency, …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 1, 2025 · pp. 1–6 Read article
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Blood Cell Saver Machine
Abstract: Intraoperative Cell Salvage (ICS) is a crucial technique in modern surgical practice aimed at minimizing the need for allogeneic blood transfusions. By collecting, filtering, washing, and re-infusing a patient’s own blood lost during surgery, ICS provides a safer and cost-effective alternative to donor transfusion, reducing the risk of transfusion-related infections and immunologic reactions. Initially conceptualized in the early 19th century, ICS technology evolved significantly with the introduction of the Cell …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 15, Issue 2, 2025 · pp. 51–59 Read article
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Smart Environmental Noise Monitoring System Using IoT and Machine Learning for Urban Pollution Control
Abstract: Human race has steadily evolved over past centuries. Development of new technology, vigorous research, consistent efforts, indomitable will to find solutions for the problems, are the key factors to shape our future in way that everyone gets safe, secure and satisfactory life. Construction industries provides basic but most valuable service or product or we can say that construction industries fulfill the basic needs of individual and group of people by …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 Read article
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Defect Diagnosis and Modelling for A Rotating Machine Running at A Steady Pace
Abstract: Rotary equipment, such as gears, shafts, pumps, and bearings, are widely used across various rotary machine in industries, often operating under different loading conditions. The fluctuations in loading can lead to fatigue failures in rotating components, significantly affecting machinery performance. To investigate the behavior of such rotating equipment under diverse operational scenarios, a numerical model has been created. This approach can replace costly and often challenging experimental methods. However, it …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 154–164 Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article
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Machinability and Reliability Analysis of Al6063–Al2O3 Metal Matrix Composites Using Image-Based Flank Wear Evaluation
Abstract: This study explores the machinability and reliability characteristics of Al6063–Al2O3 metal matrix composites (MMCs) as analogues for polymer–metal hybrid composite systems, focusing on their potential use in lightweight structural and metal matrix composite-integrated applications. The composite specimens were fabricated through stir casting with 3% and 9% Al2O3 reinforcements, followed by mechanical characterization that confirmed significant enhancements in hardness and strength compared to unreinforced Al6063. Machining experiments were performed using a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 264–290 Read article
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The Role of Artificial Intelligence and Machine Learning in Redefining Global Healthcare Systems and Advancing Medical Innovation
Abstract: Health Services are being revolutionized with AI and ML through improved accuracy, efficiency and accessibility in the delivery of health care. With AI and ML, it is now possible for health care professionals to assess varying amounts of complex clinical data in a relatively short amount of time, therefore, creating opportunities for early detection of disease, increasing the odds of accurate diagnosis, and improving the ability to make informed clinical …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 14–19 Read article
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Record Linkage in Knowledge Discovery Process Using Angle Based Machine Learning
Abstract: Record linkage is a critical data cleansing step in the knowledge discovery process, aimed at identifying and resolving inconsistencies across datasets. This study proposes an enhanced record linkage framework tailored for uncertain and large-scale data using a combination of distance measurement, probabilistic modeling, and semantic reasoning. A novel angle-based distance measurement technique is introduced to optimize matching between candidate records. To further boost match accuracy, a Finite Mixture Model (FMM) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1157–1170 Read article
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Machine Learning Based House Price Forecasting
Abstract: This research endeavours to craft a predictive model leveraging machine learning to estimate the market value of houses in Delhi. By integrating Python and its powerful libraries, pandas for data processing, Plot for interactive visualizations, scikit-learn for implementing machine learning algorithms, XGBoost for boosting the model's prediction accuracy, and to evaluate the model's performance cross-validation techniques are used. An interactive user interface is created using a Flask web application to …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 5–11 Read article
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Fluidic Engineering: Investigating Cutting Fluids’ Effect on Machined Surface Roughness
Abstract: The primary goal of this experimental study project is to determine the optimal cutting fluid by experimenting with two distinct oil kinds and compositions. Thirty-six compositions of cutting oil are obtained by mixing three distinct oil compositions, such as mineral oil and paraffin oil, with six different additive and anti-foaming agent compositions. Then, using a trial-and-error methodology, we employed these 36 cutting oil compositions for drilling operations with constant pressure …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 27–42 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article