Search Results - (( developing fire learning algorithm ) OR ( java implementation modified algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…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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Development of IoT-based automated dynamic emergency response system against fire incidents in academic building by Al-Hady, Syed Mohammed Zakaria, Islam, Md Rafiqul, Rashid, Muhammad Mahbubur

“…The proposed system leverages IoT technology, wireless and bluetooth sensor networks to gather real-time data from various sensors and devices installed in the site and uses machine learning algorithms to predict and prevent potential fire incidents. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”

Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Hybrid Intelligent Warning System for Boiler tube Leak Trips by Singh D., Ismail F.B., Shakir Nasif M.

Density based subspace clustering: a case study on perception of the required skill by Rahmat Widia, Sembiring

“…This research aims to develop an improved model for subspace clustering based on density connection. …”
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Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

“…This research aims to develop an improved model for subspace clustering based on density connection. …”
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Development of a smart edge device for fire detection by Ng, Wei Yuan

“…This project proposes a smart edge fire detection system that overcomes the limitations of conventional fire warning systems by utilizing deep learning models and edge computing. …”
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CFD modeling on coal properties towards the burnout efficiency by Nabil Asyraf Abd Halim

Development and application of an enhanced ART-Based neural network by Keem, Siah Yap, Chee, Peng Lim, W.M Lee, Eric, Junita, Mohamed Saleh

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Multi sensor network system for early detection and prediction of forest fires in southeast asia by Kadir, Evizal Abdul, Alomainy, Akram H., Hanita, Daud, Maharani, Warih, Noryanti, Muhammad, Syafitri, Nesi

“…The collected data is then processed and analyzed using machine learning algorithms to identify fire patterns and predict the likelihood of fire outbreaks. …”
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The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques by Mohammad Syawaludin Syafiq, Hassan

“…In this study, a tracking algorithm is developed by means of image processing technique in detecting ambulance. …”
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Development of spike train algorithms for physiotherapy assessment using deep learning approaches by Nor Rashid, Fadilla' Atyka

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ReSTiNet: An efficient deep learning approach to improve human detection accuracy by Shahriar Shakir, Sumi, Dayang Rohaya, Awang Rambli, Mirjalili, Seyedali, Miah, M. Saef Ullah, Muhammad Mudassir, Ejaz

“…ReSTiNet is a novel small convolutional neural network that overcomes the problems of network size, detection speed, and accuracy. The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy by Sumit, S.S., Rambli, D.R.A., Mirjalili, S., Miah, M.S.U., Ejaz, M.M.

“…ReSTiNet is a novel small convolutional neural network that overcomes the problems of network size, detection speed, and accuracy. The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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ReSTiNet : An efficient deep learning approach to improve human detection accuracy by Sumit, Shahriar Shakir, Dayang Rohaya, Awang Rambli, Seyedali, Mirjalili, Miah, Md Saef Ullah, Muhammad Mudassir, Ejaz

“…ReSTiNet is a novel small convolutional neural network that overcomes the problems of network size, detection speed, and accuracy. The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Hybrid Intelligent Warning System for Boiler tube Leak Trips by Singh, D., Ismail, F.B., Shakir Nasif, M.

“…The Extreme Learning Machine (ELM) methodology was also adopted in IWS-1 and compared with traditional training algorithms. …”
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Prediction of oil and gas pipeline failures through machine learning approaches: A systematic review by Al-Sabaeei, A.M., Alhussian, H., Abdulkadir, S.J., Jagadeesh, A.

“…The rapid progress of machine learning (ML) technologies provides an advantageous opportunity to develop predictive models that can effectively tackle these challenges. …”
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