Search Results - (( web organization learning algorithm ) OR ( java application sensor algorithm ))
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms : A review
Published 2023“…This review paper summarizes research on the hybrid of constraint-based models and machine learning algorithms in optimizing valuable metabolites. …”
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Design Of Robot Motion Planning Algorithm For Wall Following Robot
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Student resource exchange: a web-based system for sharing educational resources among students
Published 2025“…For content classification, the Google Gemini API with structured prompt engineering is applied to automatically organize materials into relevant academic courses. …”
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Human activity recognition via accelerometer and gyro sensors
Published 2023“…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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Data pre-processing of website browsing record: An initial step for web page classification
Published 2021“…A web page classification system is proposed to be constructed using a deep learning algorithm. …”
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New species orchid recognition system using convolutional neural network / Annisa Atikah Mohd Fadzil and Itaza Afiani Mohtar
Published 2021“…Transfer learning was also implemented in this project to skip the feature extraction phase that requires many computational resources in the CNN algorithm. …”
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Predictive analytics for the sentiment of malaysian place of interest using machine learning models
Published 2023“…Furthermore, this study also trains three machine learning algorithms to predict the sentiment of textual data. …”
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Undergraduates Project Papers -
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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Named entity recognition using a new fuzzy support vector machine.
Published 2008“…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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Software agent as an effective tool for managing the Internet of thing data complexity
Published 2017“…The current analysis tools and algorithms employed by the business organization were not designed to analyze the ever dynamic changes in taste and preferences of users when predicting the buying intent ion. …”
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Identifying suicidal ideation through twitter sentiment analysis using Naïve Bayes / Annasuha Atie Atirah Alias
Published 2023“…Thus, this project aims to design, develop, and evaluate web-based application utilizing sentiment analysis, specifically employing the Naïve Bayes algorithm, to identify and analyze suicidal ideation within Twitter posts. …”
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Phishing image spam classification research trends: Survey and open issues
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Design & Development of a Robotic System Using LEGO Mindstorm
Published 2006“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. Ultimately, the algorithm development program designed earlier is linked up directly to the robotic model for program implementation and verification. …”
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An early warning system for students at risk using supervised machine learning
Published 2024“…For that, this study will perform a study of the current issues, factors, and solutions in education student’s data, determine the supervised machine learning algorithms, compare which model is the best predict the students’ performances, develop an early warning system for the educators to make an early decision in order to assist and consult the at-risk students, and finally conduct testing and evaluation of the system. …”
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