Search Results - (( structures machine learning algorithm ) OR ( java applications interface algorithm ))

Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

“…In addition, the system also utilises JavaFx and jFugue for its graphical user interface and music programming respectively. …”
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Application-Programming Interface (API) for Song Recognition Systems by Murtadha Arif Sahbudin, Chakib Chaouch, Salvatore Serrano

“…In addition the implementation is done by algorithm using Java’s programming language, executed through an application developed in the Android operating system. …”

A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification by Madanan M., Gunasekaran S.S., Mahmoud M.A.

Classification of JPEG files by using extreme learning machine by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

“…This paper proposes an Extreme Learning Machine (ELM) algorithm to assign a class label of JPEG or Non-JPEG image for files in a continuous series of data clusters. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

“…To overcome these limitations, this research has proposed five machine learning algorithms namely Linear Regression, Lasso, Ridge, Random Forest and Decision Tree. …”
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Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms by Shaikh, Abdul Aabid, Raheman, Md Abdul, Hrairi, Meftah, Baig, Muneer

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Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Mohammed, Waheed Yasin, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

“…In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. The proposed approaches take the advantages of structured peer-to-peer systems where the contents of peers’ caches are shared using Distributed Hash Table (DHT) in order to enhance the performance of the web caching policy. …”
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Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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A review of machine vision pose measurement by Xiaoxiao, Wang, Beng, Ng Seng, O. K. Rahmat, Rahmita Wirza, Sulaima, Puteri Suhaiza

“…It also suggests that the integration of machine learning techniques may improve the performance of machine vision pose measurement algorithms. …”
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A review of machine vision pose measurement by Xiaoxiao, Wang, Beng, Ng Seng, O. K. Rahmat, Rahmita Wirza, Sulaima, Puteri Suhaiza

“…It also suggests that the integration of machine learning techniques may improve the performance of machine vision pose measurement algorithms. …”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…Results of studying color segmentation using machine-learning algorithm and color space analysis is presented in this thesis. …”
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Prediction of Ground Surface Deformation Induced by Earthquake on Urban Area Using Machine Learning by Usman F., Nanda, Sumantyo J.T.S.

“…Earthquakes can inflict significant damage to structures and infrastructures. This paper presents a machine learning model to predict ground surface deformation (GDS) induced by earthquake events. …”

Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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Exploring brain structure differences and male/female classification: a machine learning study on Huffaz and non-Huffaz by Sapuan, Abdul Halim, Abdul Majid, Zafri Azran, Mohd Tamrin, Mohd Izzuddin, Che Azemin, Mohd Zulfaezal

“…This study investigates the potential of machine learning (ML) to classify sex based on brain structural features, incorporating the unique perspective of cognitive training through Quran memorization. …”
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms by Ziyad Sami B.H., Ziyad Sami B.F., Kumar P., Ahmed A.N., Amieghemen G.E., Sherif M.M., El-Shafie A.

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Detection on ambiguous software requirements specification written in malay using machine learning by Zahrin, Mohd Firdaus

“…Four (4) algorithms have been evaluated to find the suitable classification algorithm for this purpose. …”
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Machine learning methods for multi-rotor UAV structural damage detection based on MEMS sensor by Ma, Y., Mustapha, F., Ishak, M.R., Abdul Rahim, S., Mustapha, M.

“…An independent data acquisition device with a Micro Electro Mechanical Systems (MEMS) sensor is designed and fixed onto the multi-rotor UAVs to acquire the vibration data. Four machine learning algorithms, namely Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Decision Tree, and Random Forest, are employed for damage detection. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Design of efficient blue phosphorescent bottom emitting light emitting diodes by machine learning approach by Janai, Muhammad Asyraf, Woon, Kai Lin, Chan, Chee Seng

“…This study demonstrates the applicability of machine learning algorithm in extracting underlying complex correlations in blue PhOLEDs.…”
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Feature selection and prediction of heart disease using machine learning approaches by Molla, M. M.Imran, Islam, Md Sakirul, Shafi, A. S.M., Alam, Mohammad Khurshed, Islam, Md Tarequl, Jui, Julakha Jahan

“…In this paper, it is capable of recognizing and classifying the heart disease patient from healthy people by using three standard machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). …”
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