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895 articles for “Accuracy”
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Effect of WEDM Machining Parameter on the MMC: A Review
Abstract: Recent area of manufacturing is highly focus on good accuracy and a complex shapes are mechanized by the advanced machining operation. The wire electrical discharge machining (WEDM) have the ability to produce the complex shapes with having high accuracy. The WEDM is non-contact type machining operation and is used for metal materials as well as Metal Matrix Composites (MMCs), ceramics composites those have many application in vast areas such as …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 1, Issue 1, 2023 · pp. 1–7 Read article
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Tracking Subsystem in Satellite
Abstract: The central nervous system and operating system of all satellite and spacecraft missions is called Satellite Telemetry, Tracking and Control (STT&C). Ground controllers can keep an eye on and manage the spacecraft's position, velocity, and location thanks to the tracking subsystem of the satellite. A key component of satellite TV for PC operations is tracking, which makes sure that satellites maintain their precise orbits and the right attitude to complete …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 36–42 Read article
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Development and Validation of a Robust RP-HPLC Method for Rufinamide Quantification in Pharmaceutical Dosage Forms
Abstract: The creation and validation of a simple, precise, and targeted reverse phase high-performance liquid chromatographic (RP-HPLC) approach allowed for the quantification of rufinamide in pharmaceutical dosage forms. With a mobile phase of methanol and water (50:50, v/v), the technique used a gradient mode Symmetry Qualisil gold C18 column (4.6 x 150mm, 5 μm). For the detection method, a flow rate of 1 mL/min was employed at 220 nm. During a …
Published in Emerging Trends in Personalized Medicines · Vol. 1, Issue 1, 2024 · pp. 25–32 Read article
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Detectiverse: Advancing Supply Chain Efficiency with AI-Enhanced Screw Counting
Abstract: Accurate screw counting is essential in the manufacturing sector to ensure efficient inventory management and maintain quality control standards. The current manual counting method is prone to errors and lacks the ability to identify the source of missing screws. To address this challenge, we propose implementing an automated screw counting system at Indo Metal Tech in Ambattur, Chennai. This system would utilize advanced image processing and machine learning algorithms to …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 21–26 Read article
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Interest Level Prediction in Rental Properties Using Data Science
Abstract: A key component of forecasting home prices and rental patterns is real estate market analysis. Data science, data mining methodologies, and statistical models are some of the strategies that have been created in recent years to solve this problem. A few problems are still required to be resolved, such as the obstacles caused by the availability and quality of the data; the presence of outliers, missing values, and inconsistent formats …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 28–34 Read article
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An Automation Detection for Sign Language Using AI
Abstract: Sign language recognition has attracted considerable interest because of its ability to facilitate communication between the deaf community and the public, thereby bridging communication divides. Traditional approaches to sign language recognition often face challenges in accurately interpreting the complex and nuanced gestures inherent in sign languages. However, recent advancements in deep learning techniques have shown promising results in improving the accuracy and robustness of sign language recognition systems. This study …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 1–14 Read article
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Using AIML to Enhance Demand Forecasting in Business
Abstract: Artificial intelligence machine learning (AIML) can play a significant role in enhancing demand forecasting in business. AIML is a programming language designed for creating chatbots and conversational agents, but its application extends beyond simple interactions. In the context of demand forecasting, AIML can be utilized to analyze historical data, customer interactions, and market trends. By implementing AIML algorithms, businesses can create intelligent models that learn from past demand patterns, customer …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 35–40 Read article
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A Comprehensive Exploration of Method Validation and Development in Pharmaceutical Analysis: Focus on Vortioxetine Analysis
Abstract: The pharmaceutical industry relies on rigorous method validation to ensure the accuracy, precision, and reliability of analytical techniques employed in drug testing and quality control. This comprehensive exploration delves into the validation parameters and guidelines essential for method validation, emphasizing accuracy, precision, linearity, detection and quantitation limits, specificity, range, robustness, and ruggedness. Validation plays a pivotal role in guaranteeing high-quality products, adhering to good manufacturing practices (GMP), and optimizing manufacturing …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 1, 2024 · pp. 46–52 Read article
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Comparison of K-nearest Neighbor and Artificial Neural Network Classifiers for the Detection of Breast Cancer
Abstract: Breast cancer is the most common type of cancer seen in women in the present day, which is also considered a life-threatening disease. If this cancer can be detected in its early stage it can be a lifesaver for many people around the world. Machine Learning techniques have become one of the hotspots for predicting the early diagnosis of breast cancer. This research work experiments with the two most popularly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 78–83 Read article
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Developing a Comprehensive Framework for User and Entity Behavior Analytics (UEBA): Integrating Advanced Machine Learning and Contextual Insights
Abstract: User and Entity Behavior Analytics (UEBA) has emerged as a crucial approach in modern cybersecurity for detecting and mitigating insider threats, compromised accounts, and other malicious activities within organizational networks. However, existing UEBA frameworks often face challenges in scalability, detection accuracy, and response effectiveness. This research work proposes a novel framework for UEBA that aims to address these limitations and enhance threat detection and response capabilities. The framework integrates advanced …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 20–32 Read article
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Identification of Papaya Fruit Ripening Process Using AI
Abstract: Identifying the ripening process of papaya fruit using artificial intelligence involves employing machine learning algorithms to analyze various features such as color changes, texture alterations and chemical compositions. This model is capable of analyzing visual cues to determine the stage of ripeness. The dataset compares images of papaya at various ripening stages, and our AI model demonstrated high accuracy in classifying these stages. Employing machine learning algorithms and image processing …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 2, 2024 · pp. 23–30 Read article
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A Supervised Learning Approach for Toxic Comment Detection on Social Media Platforms
Abstract: Nowadays everyone uses social media platforms like X (formerly Twitter), Instagram, Facebook, etc. for various purposes. With the help of this, we share our opinions, ideas, and feelings. Generally, the datasets obtained from the internet are constructive; however, there is a significant proportion of toxic ones. The datasets are filtered to remove noise, and noise is removed in post-processing. The study initiates with the upload and preprocessing of a toxic …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 7–14 Read article
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Botnet Beacon: Unveiling Covert Networks with Advanced AI Detection Strategies
Abstract: Securing information technology systems is paramount in today's interconnected world, where the reliability and security of networks and applications are of utmost importance. In this context, the development of a Botnet Detection System (BDS) that harnesses the power of AI classification algorithms becomes a critical endeavor. The primary objective of this work is to construct a comprehensive framework for a BDS that can efficiently gather network data and subject it …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 2, 2024 · pp. 26–32 Read article
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Advancements in Handwriting Recognition: A Deep Learning Approach
Abstract: This article provides detailed information about handwriting text recognition. Some human characteristics are unique to the individual. Writing is one of the scientifically proven habits that is different for everyone. Handwriting Text Recognition (HTR) is responsible for identifying written characters and converting them into digital text. HTR is an intensively researched area, but improvements can still be made in accuracy and efficiency. Digitization of manuscripts is very useful in today's …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 28–34 Read article
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Customer Churn Prediction Using ML Algorithms
Abstract: Comprehending customer churn is essential for businesses aiming to enhance and sustain customer relationships. This study introduces a machine learning approach aimed at forecasting customer churn by leveraging demographic and behavioral data. Our research involved developing predictive models using support vector machines (SVM), random forests, and decision trees, evaluating their efficacy using real-world data from the telecom industry. Our findings underscore that random forests consistently outperform SVM and decision trees …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 70–75 Read article
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Enhancing Profanity Detection in Dravidian Languages: Leveraging Language Models for Optimization and Improvement
Abstract: Detecting and documenting instances of abusive behaviour can significantly improve the quality of virtual environments. Given the vast amount of content published daily on social media, it is impractical for human annotators to manually identify potentially harmful content. Recent algorithmic initiatives, especially on platforms like Twitter, have advanced in abuse detection. However, for Dravidian texts, there remains a need to understand the context better and build robust language models for …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 17–23 Read article
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Vehicle Black Box Systems: Evolution, Implementation, and Impact on Road Safety
Abstract: The main goal is to create a Black Box System for Vehicle that can be used to enhance road safety. To record accident data, as well as the location of the accident, an SOS message, the temperature of the car, and an automatically administered breathalyzer test for the driver, we are developing a black box in this project. The Black Box for Vehicle can aid in making automobiles safer, gather …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 2, 2024 · pp. 38–46 Read article
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Fluid-Structure Interaction Simulation of Parachute by Eulerian-Lagrangian penalty method
Abstract: In general, modeling and simulation of a model consisting of fluid and solid combinations has been considered difficult, and it has become impossible in terms of computer dependencies and accuracy to be analyzed by Fluent or other programs. The parachute evaluation process, which is historically based on a large amount of experimental data, necessitates many falling experiments. These tests can be costly and time-consuming, and they don't always allow for …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
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Sentinels of Safety: A Robotic Revolution in Autonomous Landmine Detection for Humanitarian Resilience
Abstract: Landmine Detection Robotic Vehicle Project is to create an autonomous robotic system that can identify landmines in dangerous locations. The rover navigates through a variety of terrains by using modern sensor technology, such as metal detectors and infrared photography, to detect buried landmines. The rover can distinguish between potentially dangerous items and harmless ones. The principal aim of the project is to optimise the efficacy and security of landmine removal …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 28–34 Read article
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Enhancing Crop Health: A Review of Image Processing Methods for Leaf Disease Identification
Abstract: This research presents an overview of different image processing techniques for the identification of leaf disease. Many algorithms can be used to identify and categorize leaf diseases in plants, and digital image processing provides a quick, dependable, and accurate method of disease detection. This paper presents various techniques used on multiple crops and the achieved accuracy for each model. Leaf disease detection is a critical task in agriculture to ensure …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 10–14 Read article