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160 articles for “State machine”
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FlexEdify: Adaptive Learning Platform
Abstract: FlexEdify is an innovative adaptive learning platform revolutionizing the educational experience by customizing content to meet the unique needs of each student. Utilizing state-of-the-art machine learning algorithms, the system promptly analyzes students' real-time errors, meticulously storing them in a centralized database. This database serves as the cornerstone for adaptive questioning, allowing the platform to dynamically adjust subsequent content based on individual weaknesses. The platform features a user-friendly interface, guaranteeing accessibility …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 20–24 Read article
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Smart Glasses Using Ultrasonic Sensor and AI for Blind Person
Abstract: Smart glasses has received considerable attention recently from people around the world. This research paper introduces a pioneering project, 'Smart Glasses Using AI and Ultrasonic Sensor,' aimed at revolutionizing the assistive technology landscape for visually impaired individuals. The project seamlessly integrates advanced hardware, including Raspberry Pi and Node MCU, with an array of sensors and state-of-the-art machine learning techniques, notably the YOLOv5 model. This paper presents a new paradigm in …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 2, 2024 · pp. 1–9 Read article
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Extraction of speech Emotion Features Using MLP Classifier
Abstract: Speech Emotion Recognition is a thriving research topic. Speech emotion recognition use MLP classifier to categorize the emotions from the speech. This Speech is also used as the medium, through which one can express their feelings and mind state in human to machine interaction. The case is very easy where two humans communicate along with their emotions as by nature, they can recognize each other’s emotions. But for computer, if …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 3, 2022 · pp. 11–19 Read article
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Novel Catalytic Strategies for Reducing Residual Stresses and Improving Surface Quality in Machined Ceramic Materials
Abstract: To prepare for material cutting and utilize utility-specific edges, it’s crucial to understand the inherent brittleness of ceramics. This brittleness limits the forming methods available and hinders achieving dimensional accuracy and precision through conventional machining techniques. The fabrication of composite materials is becoming increasingly significant, particularly in technical fields like the automotive industry, where they are used to manufacture engine connecting rods, propeller shafts, brake discs, and more. The machining …
Published in Journal of Catalyst & Catalysis · Vol. 11, Issue 2, 2024 · pp. 01–07 Read article
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Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article
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Photochemical Materials for Light-responsive Optical Switching: AI-optimized Design of Dynamic Visual Effects
Abstract: This paper presents an in-depth investigation into the design and behavior of photochemical materials that generate optical illusions and dynamic visual effects through light-induced molecular transformations. The study focuses on advanced photoresponsive compounds such as azobenzene and spiropyran derivatives, emphasizing their reversible optical transitions governed by photoisomerization, phase transitions, and photochromism in solid-state and polymeric matrices. Spectroscopic and kinetic analyses are employed to evaluate the influence of light wavelength, material …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 13–27 Read article
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Multivariant Disease Detection from Different Plant Leaves and Classification
Abstract: Agricultural growth is significant in Indian GDP which is based on yield of crops, quality of the plants and procedure of the plants taken. To maintain good quality of plant, the plant diseases should be identified and then given proper suggestions to farmers for specific fertilizers and pesticides to be used. The use of specific fertilizers or pesticides makes plant more health with good quality so that farmers can get …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 27–35 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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Human Powered Washing Machine
Abstract: AbstractThe power generated by pedaling is the transformation of energy which utilizes the human efforts to drive the wheel. It is a very common form of energy used in various types of applications like transportation for a long time ago. Altogether this form of energy can be utilized in various aspects. This study mainly focuses on the pedal-powered washing mechanism. The basics of this machine depend on the Principle of …
Published in Journal of Instrumentation Technology & Innovations · Vol. 10, Issue 2, 2020 · pp. 13–18 Read article
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Gob to pursue heat to mould – a study
Abstract: This article is the study of gob at hot state between molten glass pool and mould machine. The empirical description has modification from trial and error prosecution to suggest automated produce equipment. Feedback sensing loop from plunger feed at mould has data conversion ethic to shaped mass regulator equipment. Modification in the trajectory of flow line production has improved quality produce at minimized wear. Difference in composition-wise viscosity and heat …
Published in Journal of Thermal Engineering and Applications · Vol. 8, Issue 1, 2021 · pp. 47–53 Read article
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A Review on Implementation of Lean Manufacturing in Maize Grinding Mill Assembly Line
Abstract: At present scenario, lean manufacturing has become a worldwide phenomenon. It is quite successful in drawing the attention of companies of all sizes. A large number of organizations are following the lean technologies and experiencing vast improvements in quality, production, customer service and profitability. Lean manufacturing is a systematic approach to identify and eliminate the waste through continuous improvement. The manufacturing industry in India must also look to leverage its …
Published in Journal of Industrial Safety Engineering · Vol. 3, Issue 1, 2016 · pp. 10–14 Read article
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Machine Learning Approach to Detect and Analyze Attention-Deficit/Hyperactivity Disorder
Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by difficulties with attention, impulse control, behavioral regulation, and daily functioning that persist across childhood and adulthood. Clinical diagnosis is predominantly based on behavioral assessments and expert interpretation, which may result in subjectivity and delayed clinical decisions. To reduce reliance on subjective evaluation, this study introduces an automated ADHD identification framework that integrates resting-state functional Magnetic Resonance Imaging (rs-fMRI) with advanced machine …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 22–26 Read article
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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
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Minimization of Steady State Error of DC Motor Drive Using PID Controller
Abstract: As it is the time of advanced technology, machinery implementation is increasing very rapidly. Industries always work with the implemented technology which gives the fast and accurate response of the system. This paper includes the dc motor speed controlling using the PID controller. Close loop control system and electrical drives have the advantageous system for the technology. DC motor is used for getting best and easiest speed and torque control …
Published in Journal of Power Electronics and Power Systems · Vol. 8, Issue 2, 2018 · pp. 25–29 Read article
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Deploying Fuzzy Logic for Self-Tuning Regulator Design for Motion Control in Modern Electrical Machines
Abstract: Modern electrical machines require sophisticated motion control systems capable of adapting to varying operating conditions, load disturbances, and parameter uncertainties. Traditional self-tuning regulators (STR) based on classical control theory often struggle with nonlinearities, time-varying dynamics, and complex operational environments characteristic of contemporary electric drives. This article presents a comprehensive framework for deploying fuzzy logic in self-tuning regulator design to address these challenges in motion control applications. Fuzzy logic controllers leverage …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 11–21 Read article
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
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BY USING FLYWHEEL TO PRODUCE ELECTRICITY WITH POWER MULTIPLICATION
Abstract: Electricity production using conventional methods consume lot of energy, utilize from the fuels and which in turn converted from one source of energy to another. To produce free energy experiments conducted on the perpetual motion states that it is practically impossible to run a machine on the perpetual motion 100 percent . Instead of pursuing on perpetual motion, when we support the perpetual motion with slight energy boost just before …
Published in Journal of Catalyst & Catalysis · Vol. 5, Issue 3, 2018 · pp. 5–7 Read article
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Content-based Image Retrieval: Recent Trends and Techniques
Abstract: Due to the affordability of digital devices and the accessibility of internet technologies, a vast number of multimedia databases have been established for various applications. These image databases increase the need for efficient picture retrieval search strategies that meet user requirements. When compared to other systems, the content-based image retrieval (CBIR) system is one of the most widely used systems for retrieving images from enormous databases. Much work has been …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 01–32 Read article
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Review of Machine Technique for Prediction of Depression Using EEG Signal
Abstract: Depression is a prevalent mental health disorder that affects millions worldwide, often leading to significant personal and societal burdens. Traditional diagnostic methods for depression rely heavily on subjective assessments, which can be prone to bias and inconsistency. In recent years, there has been a growing interest in utilizing machine learning techniques to predict depression based onelectroencephalogram (EEG) signals, offering a promising avenue for more objective and reliable diagnosis. This review …
Published in Recent Trends in Electronics Communication Systems · Vol. 10, Issue 3, 2023 · pp. 23–29 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article