Search Results - (( parameters variation method algorithm ) OR ( waste detection sensor algorithm ))

An Embedded Machine Learning-Based Spoiled Leftover Food Detection Device for Multiclass Classification by Wan Azman,, Wan Nur Fadhlina Syamimi, Ku Azir, Ku Nurul Fazira, Mohd Khairuddin, Adam

“…Several studies have examined the factors influencing food waste behaviour and management. This work was motivated by the lack of previous research on machine learning and electronic noses to detect contamination from leftover cooked food. …”
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Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system by Ali, Hazem I.

“…These algorithms are designed to achieve the robustness over a wide range of system parameters change and disturbances. …”
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Hybrid Control of A Quadrotor System Carrying Suspended Payload With Parameter Variations by Amalin Aisya binti Mohd Awi

Automation of plastic waste sorting through robotic technology by Chong, Yoong Kiat

“…A YOLOv8 deep learning model, trained on a custom dataset of waste images, was integrated with the ByteTrack algorithm to provide real-time object detection and tracking. …”
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IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management by Eugine Teh, Yin Jie, Chee Soon, Chong, Rozaimi, Ghazali, Hazriq Izzuan, Jaafar, Muhamad Fadli, Ghani, Howe Cheng, Teng, Nur Farhanah, Zulkipli, Siaw Hong, Liew

“…A Convolutional Neural Network (CNN) trained on a dataset of aluminium cans and plastic bottles is deployed for waste identification. Real-time monitoring is enabled by IoT sensors and machine vision algorithms, facilitating precise detection of waste levels and material types. …”
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Smart waste management system with IoT monitoring by Kalitazan, Sachein, Muniswaran, Suvarshan, Velan, Sheshan, Muniswaran, Suvathithan, Shah, Dhanesh

“…Through advanced data analytics and machine learning algorithms, the platform predicts waste accumulation patterns, optimizes collection routes, schedules pickups based on fill-level data, and detects any abnormal conditions. …”
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Voltage Variation Analysis By Using Gabor Transform by Abdullah, Abdul Rahim, Tee, Wei Hown, Yusoff, Mohd Rahimi

“…The parameters extracted can detect the voltage variation signals successfully. …”
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Comparison of several improved versions of particle swarm optimizer algorithm for parameter estimation of squirrel-cage induction motors / Mohammad Yazdani-Asrami, Mehran Taghipour... by Gorjikolaie, Mehran Taghipour, Gholamian, S. Asghar

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Model-based hybrid variational level set method applied to lung cancer detection by Jing, Wang, Liew, Siau-Chuin, Azian, Abd Aziz

“…This paper presents a novel model-based hybrid variational level set method (VLSM) tailored for lung cancer detection. …”
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A reliable algorithm of fourth–order boundary value problems using modified variational iteration method by Rangkuti, Yulita Molliq, Mohd Salmi, Mohd Noorani, Prof. Dr., Rokiah @ Rozita, Ahmad, Dr.

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Energy-Aware Clustering Routing for Mobile Ad-Hoc Sensor Networks (MASNETS) by Amanda, Hendrick

“…There are many potential applications of MASNETs such as military sensor networks to detect and gather information about enemy movements and some sensor nodes are also mounted on animals or other moving objects, which can sense and collect information such as body temperature. …”
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Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz by Abdul Aziz, Mohd Azri

“…However, the use of moment of inertia and other parameters of DC motor are mostly to complete the transfer function and no specific analysis was done on the effects of their variations to the control method. …”
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Performance evaluation of smoothed functional algorithm based methods for sigmoid-PID control optimization in MIMO twin-rotor systems by Mok, Ren Hao, Mohd Ashraf, Ahmad

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Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz by Abdul Aziz, Mohd Azri

“…However, the use of moment of inertia and other parameters of DC motor are mostly to complete the transfer function and no specific analysis was done on the effects of their variations to the control method. …”
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A review: Use of evolutionary algorithm for optimisation of machining parameters by Zolpakar, N. A., Mohd Fuad, Yasak, Pathak, Sunil

“…Lately, evolutionary algorithm, statistical approaches such as genetic algorithm (GA), particle swarm optimisation (PSO), and cuckoo search algorithm (CSA) have been utilised in simultaneous optimisation of the parameters of the desired outputs and its great potential in optimising machining processes is recognisable.…”
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Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm by Alhamdawee, Ehsan Mohsin Obaid

“…MPPT algorithms can be categorized into classical methods and artificial intelligence-based methods. …”
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Development Of An Algorithm To Reduce The Topographical Effects In Reflected Radiance by Yeap, Eng Choo

“…Many researchers have tried to reduce the effect of topography in the past with success; however, most of these methods are complicated and require many parameters. …”
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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Arbitrary Lagrangian-Eulerian form of flowfield dependent variation (ALE-ADV) method for moving boundary problems by Zulkafli, Mohd Fadhli

“…Flowfield Dependent Variation (FDV) method is a mixed explicit-implicit numerical scheme that was originally developed to solve complex flow problems through the use of so-called implicitness parameters. …”
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Model-based hybrid variational level set method applied to object detection in grey scale images by Wang, Jing

“…This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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