Search Results - (( java implementation mining algorithm ) OR ( using mobile learning algorithm ))
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1
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
2
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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3
Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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4
Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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5
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Final Year Project / Dissertation / Thesis -
6
Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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7
GuitarApprentice: A Mobile Application for Acoustic Guitar Learning using Fast Fourier Transform algorithm
Published 2013“…The objective of the project is to create a learning-based mobile application for learning to play an acoustic guitar. …”
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Final Year Project -
8
Mobile machine vision for railway surveillance system using deep learning algorithm
Published 2021“…The detection model used in this paper is Single-Shot multibox Detection (SSD) MobileNet detection model. …”
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Proceedings -
9
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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10
Extreme learning machine for user location prediction in mobile environment
Published 2011“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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11
A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
12
Designing algorithm visualization on mobile platform: The proposed guidelines
Published 2017“…This paper entails an ongoing study about the design guidelines of algorithm visualization (AV) on mobile platform, helping students learning data structures and algorithm (DSA) subject effectively.Our previous review indicated that design guidelines of AV on mobile platform are still few.Mostly, previous guidelines of AV are developed for AV on desktop and website platform. …”
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13
Extreme learning machine for user location prediction in mobile environment
Published 2011“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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14
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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15
Algorithm visualization design guidelines for mobile leaning
Published 2018“…The guidelines are established through systematic activities: analytical review from various related fields. The guidelines are useful for AV designers in constructing AV mobile learning.…”
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16
A New Mobile Botnet Classification based on Permission and API Calls
Published 2024“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. …”
Proceedings Paper -
17
Automated feature selection using boruta algorithm to detect mobile malware
Published 2020“…Boruta algorithm is used to select features automatically for assisting the machine learning. …”
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18
Autonomous path planning robot using geographical information
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19
Review on ubiquitous education system with multi-agent synchronization on mobile learning application environment
Published 2012“…The sync agent (Multi-agent system) proposed algorithm is based on the use of mobile agents which runs from the host (sender) computer and then migrates to the receiving (receiver) mobile computer to continue the process of updating learning contents before coming back to the sender for completing the process. …”
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20
Solving the optimal path planning of a mobile robot using improved Q-learning
Published 2019“…Additionally, the effectiveness of the proposed algorithm is validated in a real-world experiment using a three-wheeled mobile robot.…”
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