Search Results - (( risk mitigation methods algorithm ) OR ( panel detection method algorithm ))
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Risk assessment for safety and health algorithm for building construction in Oman
Published 2015“…The RASH algorithm is defined by overall risk, which is equivalent to the sum of Risk Safety Safety, Risk Safety Health, Risk Health Safety, and Risk Health Health. …”
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Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…Not much research has been done on method of detecting HLPs for panel data. Hence, we have proposed Robust Diagnostic-F (RDF) to remedy the problem of masking and swamping in detecting HLPs. …”
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A real-time integrated fire detection and alarm (FDA) system for network based building automation
Published 2017“…This work proposes an improved framework for FDA system to ensure a robust, intelligent network of FDA control panels in real-time. Methods/Analysis: In this work, the shortest path algorithm was chosen for series of buildings connected by a fiber-optic network. …”
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Network-based real-time integrated Fire Detection and Alarm (FDA) system with building automation
Published 2017“…This work proposes an improved framework for FDA system to ensure a robust intelligent network of FDA control panels in real-time. A shortest path algorithmic was chosen for series of buildings connected by fiber optic network. …”
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Proceeding Paper -
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Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…The process of classifying individuals or households that may be at risk of poverty can be time consuming and less accurate in relation to traditional methods like Poverty Line Income (PLI). …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…This performance is validated through rigorous comparative assessments against various classification algorithms and state-of-the-art methods, revealing notable advantages in terms of predictive precision, computational efficiency, and adaptability to real-world clinical scenarios. …”
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Simulation and Design of an Intelligent Mobile Robot for Fire Fighting
Published 2003“…More comprehensive study in behaviour coordination will be the major focus to ensure smoother robot navigation and more effective fire detection capability. Keywords: (Fuzzy logic control, mobile robot, part recognition algorithms)…”
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Modeling Earthquake Bond Prices with Correlated Dual Trigger Indices and the Approximate Solution Using the Monte Carlo Algorithm
Published 2025journal::journal article -
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Rockfall hazard assessment based on airborne laser scanning data and GIS in tropical region
Published 2016“…The result shows the barrier in suggested location can effectively aid in rockfall hazard mitigation. The outcomes of this study prove the ability of the proposed and applied methods to make valid detection and prediction for rockfall phenomena. …”
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Fault-tolerant power extraction strategy for photovoltaic energy systems
Published 2018“…Fault detection and identification (FDI) techniques methods have been proposed to detect the presence of faults and isolate them. …”
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Assessment of the beach profile at Terengganu coastline / Emran Zaki Abdul Halim
Published 2024“…The method for determining the beach profile in this study involves using Google Earth Pro to extract beach profile conditions, while a coastal slope estimation algorithm will be employed for detailed in-situ analysis. …”
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Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique
Published 2024“…In this study, an attempt via metaheuristic algorithms, namely the Harris Hawks Optimisation (HHO) Algorithm and the Opposite Based Learning of HHO (OBL-HHO) are made to minimise the water deficit as well as mitigate floods at downstream of the Klang Gate Dam (KGD). …”
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Panel regression method to analyse the stock market returns due to Covid-19 / Nur Mardziah Aziz Jaafar and Noraini Noordin
Published 2021“…This study aimed to determine the aftereffects of COVID-19 pandemic outbreaks on stock markets by measuring the correlation between market returns and daily growth of total new and death cases of COVID-19. Panel regression methods, namely pooled ordinary least square and fixed-effect methods were used in this study where the dependent variable is stock market returns and independent variables were i) daily growth new death cases COVID-19 ii) natural algorithm market capitalisation iii) Brent Crude Oil Price from January 2, 2020, until March 31, 2020. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…By proposing an alternative method to detect in-car-abandoned children's sounds with high accuracy, this research can assist authorities, including the Ministry of Transportation, in implementing effective measures to mitigate the risks associated with this pressing issue. …”
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Student Project -
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Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation
Published 2016“…The classification combines the analysis of defect intensity features, the application of unsupervised k-mean clustering and multi-class SVM algorithms. The methods have been applied for detecting, clustering and classification polycrystalline solar wafer images, corresponding to defects such as micro cracks, stain, and fingerprints. …”
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Water level prediction using various machine learning algorithms: a case study of Durian Tunggal river, Malaysia
Published 2023“…A reliable model to predict the changes in the water levels in a river is crucial for better planning to mitigate any risk associated with flooding. In this study, six different Machine Learning (ML) algorithms were developed to predict the river�s water level, on a daily basis based on collected data from 1990 to 2019 which were used to train and test the proposed models. …”
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XAIRF-WFP: a novel XAI-based random forest classifier for advanced email spam detection
Published 2024“…However, these algorithms often suffer from the "black box" dilemma, a lack of transparency that hinders their applicability in security contexts where understanding the reasoning behind classifications is essential for effective risk assessment and mitigation strategies. …”
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