Search Results - (( waste detection method algorithm ) OR ( based optimization isotherm algorithm ))

Medical Waste Detection and Classification Through YOLO Algorithms by Moktar M.H.B., Hajjaj S.S.H., Mohamed H.

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

“…In conclusion, the work demonstrates a novel method for using machine learning algorithms to classify, identify, and predict the contamination level of leftover cooked food, contributing to reducing food waste generated primarily by Malaysians…”
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RGB and RGNIR image dataset for machine learning in plastic waste detection by Owen Tamin, Ervin Gubin Moung, Jamal Ahmad Dargham, Samsul Ariffin Abdul Karim, Ashraf Osman Ibrahim Elsayed, Nada Adam, Hadia Abdelgader Osman

“…The increasing volume of plastic waste is an environmental issue that demands effective sorting methods for different types of plastic. …”
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A gauss-newton approach for nonlinear optimal control problem with model-reality differences by Sie, Long Kek, Jiao, Li, Leong, Wah June, Abd Aziz, Mohd Ismail

“…Here, the linear model-based optimal control model is considered, so as the optimal control law is constructed. …”
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Recyclable waste classification using YOLO-based Convolutional Neural Network (CNN) / Shaharil Armin Sharizal by Sharizal, Shaharil Armin

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Fault detection and diagnosis for gas density monitoring using multivariate statistical process control by Norul Shahida, Che Din, Noor Asma Fazli, Abdul Samad, Chin, Sim Yee

“…Therefore, an efficient fault detection and diagnosis algorithm needs to be developed to detect faults that are present in a process and pinpoint the cause of these detected faults. …”
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PCB defect detection system using run-length encoding by Zakaria, Muhammad Anif

“…The secondary objective is to design run-length encoding algorithm able to detect and classify the defect of printed circuit board (PCB). …”
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Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Temitope T., Dele-Afolabi, Masoud, Ahmadipour, Mohamed Ariff, Azmah Hanim, A.A., Oyekanmi, M.N.M., Ansari, Sikiru, Surajudeen, Kumar, Niraj

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An approach of classifying waste using transfer learning method by Amin, Zian Md Afique, Khan, Nasik Sami, Hassan, Raini

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Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Dele-Afolabi T.T., Ahmadipour M., Azmah Hanim M.A., Oyekanmi A.A., Ansari M.N.M., Sikiru S., Kumar N.

Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption by Zamani, Seyed Ali

“…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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Snort-based smart and swift intrusion detection system by Olanrewaju, Rashidah Funke, Khan, Burhan Ul Islam, Najeeb, Athaur Rahman, Ku zahir, Ku Nor Afiza, Hussain, Sabahat

“…Methods/Statistical Analysis: The features are extracted using back-propagation algorithm. …”
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Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan T., Manan T.S.B., Isa M.H., Ghanim A.A.J., Beddu S., Jusoh H., Iqbal M.S., Ayele G.T., Jami M.S.

Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques by Chong, Xiao Wei

“…By employing the state-of-the-art You Only Look Once (YOLO) v7 object detection algorithm, the project aims to develop a system capable of accurately detecting and classifying prawns based on their growth stages. …”
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Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan, T., Manan, T.S.B., Isa, M.H., Ghanim, A.A.J., Beddu, S., Jusoh, H., Iqbal, M.S., Ayele, G.T., Jami, M.S.

“…The Fletcher-Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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Modelling and simulation of hollow profile aluminium extruded product by Sulaiman, Shamsuddin, Baharudin, B. T. Hang Tuah, Mohd Ariffin, Mohd Khairol Anuar, Magid, Hani Mizhir

“…This process is an isothermal process with an extrusion ratio of 3.3. Subsequently, the optimized algorithm for these extrusion parameters was suggested based on the simulation results. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

“…The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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Modeling of cu(ii) adsorption from an aqueous solution using an artificial neural network (ann) by Khan, Taimur, Abd Manan, Teh Sabariah, Hasnain Isa, Mohamed, A. J. Ghanim, Abdulnoor, Beddu, Salmia, Jusoh, Hisyam, Iqbal, Muhammad Shahid, Ayele, Gebiaw T, Jami, Mohammed Saedi

“…The Fletcher–Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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Evaluation of diagnostic performance of rK28 ELISA using urine for diagnosis of visceral leishmaniasis by Ghosh, Prakash, Bhaskar, Khondaker R. H., Hossain, Faria, Khan, Md Anik Ashfaq, Vallur, Aarthy C., Duthie, Malcolm S., Hamano, Shinjiro, Huda, M. Mamun, Salam, Md. Abdus, Khan, Md Gulam Musawwir, Coler, Rhea N., Reed, Steven G., Mondal, Dinesh

“…Although simple, these tests still require blood collection and their use in remote settings can be limited due to the need of collection devices, serum fractionation instrument and generation of biohazardous waste. The development of an accurate and non-invasive diagnostic algorithm for VL, such as could be achieved with urine, is desirable. …”
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Correlation of Retinal Blood Vessel Tortuosity and Chronic Kidney Disease by Amirul Asyraf bin Mustapha Kamel