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1048 articles for “time machine”
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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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A Review of Statistical Project Control Tool for Construction Industry
Abstract: AbstractProject management at construction industry is a complex task which involves qualitative and quantitative analysis of the activities. Various statistical models have been developed and suggested by the researchers which aim at making the process of managing construction projects more systematic and to access any shortcoming at the proper time, before it leads to the failure of the project. This paper presents and overview of such methods and discusses theirimportance …
Published in Journal of Structural Engineering and Management · Vol. 5, Issue 1, 2018 · pp. 18–21 Read article
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A Review on Process Parameters Optimization of WEDM for Metal Matrix Composites
Abstract: Wire electrical discharge machining (WEDM) is a thermal spark erosion type cutting process used for precisely machining parts with intricate shapes and sharp edges that are difficult to machine by the conventional machining processes. The WEDM process is derived from conventional EDM sparking phenomena utilizing the noncontact type technique for material removal. From the time of introduction of the process, WEDM has emerged as alternative for production of micro-scale parts …
Published in Journal of Experimental & Applied Mechanics · Vol. 7, Issue 1, 2016 · pp. 1–6 Read article
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A Review on Parametric Optimization of WEDM Technique for OHNS Steel
Abstract: In this study, the Wire Electrical Discharge Machining (WEDM) process for OHNS (Oil Hardened Non-Shrinking) steel, a high-performance material frequently used in the production of dies, punches, and precision tooling components, is optimized parametrically and validated experimentally. A continuously moving wire electrode and a sequence of electrical discharges are used in WEDM, a non-traditional machining method, to erode material and produce intricate and precise profiles, particularly in materials that are …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 29–35 Read article
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AI-Powered Solutions for Sustainable Waste Management in Construction Projects
Abstract: The construction industry is a significant contributor to global waste, posing challenges to sustainability and environmental health. This research explores AI-powered solutions for sustainable waste management in construction projects, focusing on optimizing waste reduction, recycling, and resource efficiency. By integrating machine learning algorithms and IoT-enabled sensors, real-time monitoring of waste generation and segregation can be achieved. Predictive analytics and AI-driven decision-making tools are employed to enhance material reuse and minimize …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 1–5 Read article
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Early Autism Diagnosis: Machine Learning Models and Their Effectiveness
Abstract: Diagnosis is of utmost importance for timely intervention and support. However, traditional diagnosis methods, which are based on subjective assessment, are delayed. This project explores the role that machine learning techniques might play in enhancing the accuracy and effectiveness of ASD detection. Several state-of-the-art classification algorithms were benchmarked using a dataset from Kaggle. Logistic Regression, XG Boost, Random Forest, Decision Tree, and Gradient Boosting were taken into consideration. Other performance …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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IoT-Based Battery Health Monitoring for Electric Vehicles Using Machine Learning
Abstract: With increasing utilization of the Electric Vehicles (EV)s in global scale, battery health management becomes a critical factor which has great impact on vehicle performance, safety and longevity. Battery materials, such as NMC LFP lithium-ion batteries and lithium-ion batteries, degrade over time from charging behaviour, heat stress, discharging voltage profiles and environmental limits. Conventional BMS only offer threshold based health diagnostics and cannot perform accurate degradation prediction. This work presents …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 8–12 Read article
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IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction
Abstract: Manufacturing, transportation, and energy systems rely largely on industrial electric motors, and their untimely failure can result in expensive downtime, safety hazards, and decreased operational efficiency. The majority of traditional motor maintenance procedures rely on reactive methods or routine inspections, which frequently miss early-stage problems and lead to needless maintenance or unexpected breakdowns. This project offers an Intelligent Motor Health Monitoring and Predictive Maintenance System that combines Internet of Things …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 28–37 Read article
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Optimization of Robotic Path Planning Algorithms for Autonomous Material Handling Systems
Abstract: For autonomous systems for handling materials (AMHS) to operate as efficiently as possible in industrial and logistical settings, robotic route planning is essential. This study examines many robotic route planning algorithms, emphasizing their use, ways of optimization, and difficulties in material handling systems. To improve the effectiveness, precision, and computational viability of these algorithms, the study also examines a number of optimization strategies, including machine learning, parallelization, heuristic search, and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 2, 2024 · pp. 15–20 Read article
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Parametric Optimization of Aluminum Alloy 6061 Using Wire-EDM for Automotive Applications: A Taguchi-Based Approach
Abstract: Machining hard materials with complex geometries presents numerous challenges, often requiring the use of non-traditional methods such as wire Electric Discharge Machining (EDM). However, wire EDM machines operate at slow speeds, and increasing the speed can negatively impact surface finish, making it a difficult task. The ongoing research investigates the machinability study of Aluminum Alloy 6061 using wire EDM, emphasizing the optimization of process parameters to enhance machining performance and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 293–302 Read article
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Current Updates On Employability Of Artificial Intelligence In Healthcare Science & Research
Abstract: Over the centuries, tools have been developed to increase refinement to manipulate different tools in many ways to use human digital computers. It can perform the same types of numerical and symbolic operations that can be done by ordinary people, but faster and more reliable. Artificial intelligence algorithms applied to computer applications and software. Include knowledge-based systems. AI is the science that mimics the mental skills of humans in computers. …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 72–77 Read article
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All-in-One Focus image using Guided Filters
Abstract: Machine Vision System plays a vital role in manufacturing industries for the automatic inspection of quality of the finished product. The success of machine vision system for real time application is purely depends on the response of the hardware system in capturing the image of the object and the image processing algorithm which is used to extract the features of the object from the captured image. For the extraction of …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 2, 2022 · pp. 46–53 Read article
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Efficient Automation Solutions: Building a Budget-friendly Cylindrical Robotic Arm for Component Handling
Abstract: Design and Development of Automation of Loading and Unloading to machine fixture” This Setup involves the use of automation solution to reduce operator fatigue and increase efficiency. Industries in the recent day concentrating on CNC machineries for mass production by replacing conventional lathes to improve productivity but loading and unloading of job carried over by manual, However Present work, machine tool manufacturer are coming with solutions including automatic loading and …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 1, 2023 · pp. 6–15 Read article
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Design of Gear Tooth Rounding and Chamfering Machine
Abstract: All movable gears which mesh with another gear require either rounding or chamfering. The operation is generally applied to the teeth of spur gears for use in sliding gear transmission of automotive vehicles and machine tool Gear boxes where the gears are moved on their longitudinal axes meshing with another spur gear. In current scenario the mechanically operated machines require lot of settings, which is time consuming and requires one …
Published in Trends in Machine design · Vol. 4, Issue 3, 2017 · pp. 38–44 Read article
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Survey on Progress in Agricultural Yield Prediction-from Machine Learning to Deep Learning
Abstract: Machine learning has offered new prospects for data-intensive study in the multidisciplinary field of Agri-technology, especially with the rise of big data systems and advanced computers. Machine learning is a powerful decision-making tool for predicting crop yields, as well as determining which crops to plant and what activities to engage in during the crop's growing season. To facilitate the study of the prediction of the agricultural yield many techniques of …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 12, Issue 1, 2022 · pp. 6–16 Read article
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Leafguard: Smart Plant Health Detection
Abstract: Machine learning techniques, including traditional (shallow) ML, deep learning (DL), and augmented learning (AL), are being increasingly utilized for leaf disease classification. These methods involve feature extraction, data augmentation, and transfer learning to enhance model effectiveness and reduce the need for labeled data. The success of machine learning approaches in this domain hinges on the quality and quantity of data available. LeafGuard is a cutting-edge device with intelligent sensing systems …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 32–39 Read article
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Disease Prediction Using Machine Learning (ML)
Abstract: A technique called Machine Learning Disease Prediction uses symptoms reported by users or patients to forecast disease. The user-provided symptoms are entered into the system, and it outputs the disease probability. In disease forecasting, various popular supervised machine learning methods are known to be utilized. These algorithm estimates the likelihood of a disease occurrence. Precise analysis of medical information will support timely disease detection and management of patients based on …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 12, Issue 2, 2024 · pp. 40–48 Read article
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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
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Farmer’s Pal
Abstract: Precision agriculture, characterized by data-driven decision-making, has transformed contemporary farming practices. To increase agricultural sustainability and efficiency, this abstract investigates the combination of sensor monitoring, machine learning, and picture processing. A network of sensors continuously collects vital environmental data, including temperature, humidity, rainfall, sunshine, soil moisture, and conductivity, for precision agriculture. By providing real-time insights, these sensors enable farmers to make informed choices about pest control, fertilization, and irrigation. This …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–31 Read article