Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

“…Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
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Degradation of cephalexin toxicity in non-clinical environment using zinc oxide nanoparticles synthesized in Momordica charantia extract; Numerical prediction models and deep learn... by Adel Ali Al-Gheethi, Adel Ali Al-Gheethi, Rubashini A.P. Alagamalai, Rubashini A.P. Alagamalai, Efaq Ali Noman, Efaq Ali Noman, Radin Mohamed, Radin Maya Saphira, Ravi Naidu, Ravi Naidu

“…MCZnO NPs have a white colour, spherical shape, non-agglomerated, smooth surface and size-wise they ranged from 50 to 100 nm. The ANN results indicated that 88.87% of CFX was degraded using 50 mg/L of MCZnO NP, 40 mg/L of CFX, at pH 9, and after 180 min. …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Muhamad Aiman Raziq, Muhamad Aiman Raziq, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

“…Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, MuhamadAiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

“…Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
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Degradation of cephalexin toxicity in non-clinical environment using zinc oxide nanoparticles synthesized in Momordica charantia extract; Numerical prediction models and deep learn... by Adel Ali Al-Gheethi, Adel Ali Al-Gheethi, Rubashini A.P. Alagamalai, Rubashini A.P. Alagamalai, Efaq Ali Noman, Efaq Ali Noman, Radin Mohamed, Radin Maya Saphira, Ravi Naidu, Ravi Naidu

“…MCZnO NPs have a white colour, spherical shape, non-agglomerated, smooth surface and size-wise they ranged from 50 to 100 nm. The ANN results indicated that 88.87% of CFX was degraded using 50 mg/L of MCZnO NP, 40 mg/L of CFX, at pH 9, and after 180 min. …”
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Irish perspectives on British education: a national conference by Irish in Britain Representation Group, IBRG

“…Seminar speakers included: Catríona Ní Scannláin, Brian Foster, Ann Rossiter, Irish Youth, Brigid Loughran, Maude Casey, Alan Clinton, and Siobhán Ui Néill.…”
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Debating their beliefs to victory by Abdul Latiff, Muhamad Farid

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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by SuhailaAbd Halim, SuhailaAbd Halim, Yupiter H. P. Manurung, Yupiter H. P. Manurung, MuhamadAiman Raziq, MuhamadAiman Raziq, ChengYee Low, ChengYee Low, Muhammad Saufy Rohmad, Muhammad Saufy Rohmad, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

“…Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by SuhailaAbd Halim, SuhailaAbd Halim, Yupiter H. P. Manurung, Yupiter H. P. Manurung, MuhamadAiman Raziq, MuhamadAiman Raziq, ChengYee Low, ChengYee Low, Muhammad Saufy Rohmad, Muhammad Saufy Rohmad, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

“…Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. …”
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Recognition of dengue disease patterns using artificial neural networks by Cetiner, Beytullah Gultekin, Sari, Murat, Aburas, Hani M.

“…This research aimed at the recognition of the patterns for dengue disease patterns using Artificial Neural Networks (ANN’s). Real data was provided by Singaporean National Environment Agency (NEA), for academic purposes only. …”
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Development of an intelligent multimodal biometric system for household appliances control by Abiodun musa, Aibinu

“…To this effect, a novel skin segmentation algorithm using artificial neural network (ANN) technique was developed and this was deployed to segment the palmprint and face images from the background. …”
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Textile wastewater treatment using magnetic powder activated carbon biogranules by Omar@Omri, Ahmad Hanis

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Machine learning applications for the topology prediction of transmembrane beta-barrel proteins by Grimaldi, Cédric Maxime

“…This research presents and evaluates approaches such as ANN (Artificial Neural Networks), KNN (K-Nearest Neighbors, SVM (Support Vector Machines), and a novel approach to TMB topology prediction with the use of a cascading classifier. …”
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Ammonical nitrogen effluent prediction using artificial neural network by Mujeli, Mustapha, Jami, Mohammed Saedi, Kabbashi, Nassereldeen Ahmed

“…Therefore, the study explores the robust capability of artificial neural network (ANN) in solving complex problems, as such similar to physical, chemical and biological environment of wastewater treatment plant. …”
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The impact of COVID-19 on tourism sector in India by Jaipuria, Sanjita, Parida, Ratri, Ray, Pritee

“…As there has been a substantial decline in the arrivals of overseas tourists in India in 2020, the paper aims to predict foreign tourists’ arrival in India and FEE using artificial neural networks (ANN). Furthermore, we analyse the impact of COVID-19 based on four scenarios considering with and without lockdown in terms of loss and gain in FEE. …”
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Diagnosis, classification and prognosis of rotating machine using artificial intelligence by Mahamad, Abd Kadir

“…For fault prognosis systems, the acoustic emission and vibration signals were used as input signals. Furthermore, ANN was used as prognosis systems of rotating machinery failure. …”
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الخصائص العامة للشعر العربي في ولايتي هوسا ويوربا: نظرات مقارنة = General characteristics of Arabic poetry in the Provinces of Hausa and Yoruba: Some comparative considerations =... by Ahmad H.Osman, Rahmah, Mohammad Jamiu, Abdullahi

“…Thanks to the strong dedication of Muslims in both provinces to the Arabic language, the splendor of Arabic poetry has continued to shine and cope with the waves of life without stopping or stumbling. …”
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An efficient method for fetal electrocardiogram extraction from the abdominal electrocardiogram signal by Hasan, Muhammad Asfarul, Ibrahimy, Muhammad Ibn, Reaz, Mamun Ibn

“…A new methodology by combining the Artificial Neural Network (ANN) and Correlation (ANNC) approach had been proposed in this study. …”
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Thermal conductivity prediction of foods by Neural Network and Fuzzy (ANFIS) modeling techniques by Rahman, Muhammad Shafiur, Rashid, Muhammad Mahbubur, Hussain, Mohamed Azlan

“…However the adaptive neuro-fuzzy model (ANFIS) was able to predict conductivity values which closely matched the experimental values by providing lowest mean square error compared to multivariable regression and conventional artificial neural network (ANN) models. This method also alleviates the problem of determining the hidden structure of the neural network layer by trial and error…”
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Arabtalk, an implementation for Arabic TTS by Abdulhalim, Yasser Hifny, Qurany, Shady, Hamid, Salah, Rashwan, Muhsen, Atiyya, Muhammad, Ahmed Mahmoud, Ahmed Ragheb, Khallaaf, Galaal

“…The system employs Artificial Neural Networks (ANN) statistical prosody based models for duration, energy, and global pitch contour prediction. …”
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