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43 articles for “data splitting”
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Predicting Employees Performance using Data Mining Techniques
Abstract: Human resources management (HRM) has become one of the essential interests of managers and 4decision-makers in almost all types of businesses to adopt plans for correctly discovering highly qualified employees. In this research, data mining techniques were utilized to build a classification model for predicting the performance of employees using a real dataset. For this, we are using different methods such as support vector machine, Logistic Regression and Neural Network. …
Published in Recent Trends in Parallel Computing · Vol. 8, Issue 1, 2021 · pp. 4–13 Read article
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Transformative Breakthroughs: Revolutionizing Potato Disease Detection Through Machine Learning
Abstract: Advancements in agricultural technology and the integration of artificial intelligence for diagnosing plant and leaf diseases are crucial for sustainable agricultural development. Conditions like early blight and late blight exert a notable influence on both the quality and quantity of potato harvests. Identifying these leaf diseases manually demands significant labor and a considerable level of expertise. Therefore, efficient, and automated methods for disease detection are essential to improve potato production. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 54–62 Read article
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Automated Microstructure Classification with Class-Specific Segmentation for Titanium Based Composite Materials
Abstract: In engineering, characterisation of microstructure is required to determine and forecast behaviour of titanium alloys. Our proposal in this work has been a deep-learning-based framework in the automatic classification and segmentation of Titanium Based Composite Material. The framework then uses EfficientNetB0 backbone, where we have chosen the backbone to scale the performance of classification and the computational efficiency with the assistance of the transfer learning and the compound scaling. In …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 424–433 Read article
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Developing an AI-Based Novel Forecasting Framework for Surface Irregularity in Metal Matrix Materials
Abstract: Surface irregularity in metal matrix materials (MMM) signifies the deviations from smoothness, influencing structural integrity and performance frequently arising from the manufacturing process along with intrinsic material characteristics that influence effectiveness. Limitations in data, model interpretability and complexity are the difficulties that impede artificial intelligence (AI) based surface irregularity in MMM. In this study, we suggested a novel framework of Gaussian regression fused multi-strategy adaptive boosting classifier (GR-MABC) for the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 48–56 Read article
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IoT Based SCADA for Electrical Measurements and Control
Abstract: The suggested system's primary goal is to shield electrical equipment against malfunctions. Thesystem consists of various sensors that deployed strategically on electrical equipment. The data of theequipment is collected and transmitted to cloud platform through Node MCU ESP8266. The data issimultaneously displayed using LCD display. The collected data is splitted into train and test data.Train the machine learning model by using different algorithms. The best algorithm is chosen bycalculating their …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 2, 2023 · pp. 38–47 Read article
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Analyzing Potential Leads Data to Improve Marketing Strategies
Abstract: To develop a lead scoring model using multiple machine learning models and create a user-friendly web application, the first step is to clearly define the problem and collect relevant data from various sources such as CRM, website, social media, email campaigns, etc. After cleaning and pre-processing the data, identify the essential features that can affect the lead score and split the data into training and testing sets. Next, select a …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 18–25 Read article
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Human Retention using Data Science
Abstract: Employees are the backbone of any successful organization and hence employee retention is of utmost importance. Using Data Science, this research work seeks to assist HR and Project Managers in improving the retention rate of valued workers in an organization, thus lowering the company's employee turnover expense. Following extensive research into how to choose the most desirable employee and the application of methodological assumptions, performance was created using conditional logic …
Published in Journal of Advances in Shell Programming · Vol. 8, Issue 1, 2021 · pp. 18–24 Read article
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Ligand Efficiency in Relation to 3D Physicochemical Characters of Novel HIV-1 Vif Antagonist: An Approach in The Optimization of HIV Drugs
Abstract: AbstractLigand efficiency is a design framework commonly used in drug discovery. Thirty-six (36) newly discovered 1,2,3-triazole analogues as potent new inhibitors of HIV-1 Vif were subjected to quantitative structure-property relationship (QSPR) modeling to predict their ligand efficiencies (LE) in an attempt to improve/optimize it by using some numerical data of HIV-1 Vif inhibitors based on their physical and chemical properties (descriptors). Various 3D physicochemical properties or descriptors were calculated from …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 9, Issue 3, 2022 · pp. 50–59 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
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Real-time Criminal Detection Using Face Recognition
Abstract: The objective of this project is to create a criminal face detection system that utilizes machine learning algorithms like TensorFlow and Scikit-learn, implemented in the Python programming language. To handle image processing, OpenCV will be utilized, while SQL will manage the current criminal database. The high-resolution pictures in the database will be split into various components and utilized for training the model, which can identify specific features to recognize the …
Published in Journal Of Network security · Vol. 11, Issue 1, 2023 · pp. 1–7 Read article
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A Study on Diverse Routing Protocols for Mobile Sink in Wireless Sensor Network
Abstract: Wireless sensor networks are distinct ad hoc networks in which nodes are offered to analyze the physical word through abundant modest, economical and smart sensor nodes scattered in require field of intrigue. These sensor nodes are uninhibitedly suit to detect strategy and wirelessly stretch out climate conditions to a base station. Leach is a clustering based protocol that characterizes an entire WSN in type of various clusters. Clustering is the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 5, Issue 2, 2018 · pp. 1–7 Read article
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Timely Diabetes Possibility Prediction Using AI Techniques
Abstract: The fastest chronic life-threatening disease affecting more than 422 million people globally is diabetes. The primary causes of type 2 diabetes are lifestyle choices and environmental factors. It is a slowgrowing disease which starts to develop metabolic factors long before they evolve into a disease and is formally diagnosed by a fasting sugar test. There are records of indications related to diabetes from 520 patients in the dataset that was …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 37–47 Read article
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Brain Tumor Detection Using RestNet50 Architecture
Abstract: This paper presents a novel deep learning model for brain tumor diagnosis from MRI scans on the basis of ResNet50 with some modifications. Optimizing the modified layers and pre-trained ResNet50 for improved diagnostic accuracy and reliability in real-world clinical settings is one of the key contributions of this paper. The model was trained on an extremely well-balanced data of 2,577 MRI scans, which were split equally among the tumor and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 1–13 Read article
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Decrement of Spin-orbit Splitting Near Calcium Region
Abstract: Explanation of the observed decrement of splitting of spin-orbit partners near shell closure, has been sought through an introduction of tensor interaction in a mean field type of calculation. The strength of the tensor interaction used in the Skyrme Hartree Fock theory has been optimized by the reproduction of the experimentally determined splitting of 1d, 1f and 2d shell model states (both neutron and proton) of the isotopes of Calcium …
Published in Journal of Nuclear Engineering & Technology · Vol. 13, Issue 1, 2023 · pp. 11–22 Read article
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Feasibility of Using Nondestructive Testing (NDT) in Roller Compacted Concrete Quality Assessment
Abstract: Roller compacted concrete is a no slump, heavy duty concrete usually used in pavement constructed of roadway, parking lots, in areas of frozen environment or aired region where there is shortage of water for curing, and when other paving alternatives do not satisfy the pavement design requirements regarding heavy loading, and nonstandard wheel configuration. The traditional testing e slab samples have been prepared in the laboratory using two types of …
Published in Trends in Transport Engineering and Applications · Vol. 2, Issue 3, 2015 · pp. 30–39 Read article
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A Study to Assess the Effectiveness of Information Booklet Regarding DOTS Therapy among the Tuberculosis Clients in a Selected Primary Health Centre
Abstract: The purpose of the study was to assess the effectiveness of information booklet regarding DOTS therapy among the tuberculosis clients in a selected primary health centre. The design used for this study was quasi experimental one group pre-test without control group with evaluative approach. Simple random sampling technique was used to select the sample for the study. The data were collected by using structured questionnaire from 60 tuberculosis clients before …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 4, Issue 3, 2017 · pp. 29–33 Read article
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Research on Numerical Simulation of Fluids Based on BIM Boundary Conditions in the Lower Fazi River in Taichung
Abstract: Building Information Model (BIM) application in Taiwan, After sorting out the literature, it is found that the water conservancy field is less used, Computer processing technology is becoming more and more mature, Engineering fluid simulation software has various parameter control and high precision, Simulation channel analysis can be controlled by establishing the edge model to control the water conservancy factor, In this study, BIM was introduced into the river section …
Published in Journal of Water Resource Engineering and Management · Vol. 8, Issue 3, 2021 · pp. 1–18 Read article
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A IoT-Enabled Predictive Intelligence for Real-Time Failure and Damage Evolution Monitoring of Polymer Composites
Abstract: Damage assessment of carbon-fibre-reinforced polymer composites is still challenging since the damage occurs as a combination of matrix cracking, interfacial debonding, delamination and fibre fracture. The present work proposes a framework for predictive-intelligence based on IoT for multiaxial fatigue and compression-after-impact (CAI) CFRP experiments, employing publicly available acoustic-emission (AE) datasets. A causal CNN–GRU attention model is developed by integrating time-domain, spectral, wavelet, loading-history and trend features to estimate the damage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Topic Detection in Tweets using Hashtags
Abstract: Data clustering is a common technique used for topic detection and identification in text. In this paper we propose tokenizing of hashtags as an effective and efficient way of generating bags of words for tweets (text messages on Twitter). The document- term matrix generated using these terms is smaller and more relevant compared to the full text tokenization. Tweets from the 2018 Oscars event tagged with #oscars hashtag were collected …
Published in Recent Trends in Programming languages · Vol. 5, Issue 2, 2018 · pp. 6–14 Read article
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A Study to Assess the Knowledge and Practice Regarding Prevention of TB Among Staff Nurses Working in a Selected TB Hospital at Jodhpur
Abstract: Tuberculosis (TB) remains a major global public health concern, causing significant morbidity and mortality, particularly among healthcare workers. Staff nurses are at heightened risk due to repeated exposure to patients with active TB, making knowledge and adherence to preventive practices critical. The present study was conducted to evaluate the knowledge and practices of staff nurses concerning tuberculosis (TB) prevention at Kamla Nehru TB and Chest Hospital, Jodhpur. A descriptive and …
Published in International Journal of Community Health Nursing And Practices · Vol. 4, Issue 1, 2026 · pp. 7–33 Read article