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Big data approach to sentiment analysis in machine learning-based microblogs: Perspectives of religious moderation public policy in Indonesia by Mhd., Furqan, Ahmad Fakhri, Ab Nasir

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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Benchmarking Robust Machine Learning Models Under Data Imperfections in Real-World Data Science Scenarios by Marlindawati, ., Mohammad, Azhar, Esha, Sabir

“…Multiple classical machine learning algorithms and deep learning models were assessed across diverse benchmark datasets. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging by Norhasmira, Mohammad, Anuar Mikdad, Muad, Rohana, Ahmad, Mohd Yusmiaidil, Putera Mohd Yusof

“…Background: This study aims to propose the combinations of image processing and machine learning model to segment the maturity development of the mandibular premolars using a Keras-based deep learning convolutional neural networks (DCNN) model. …”
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GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms by Tella, A., Balogun, A.-L.

“…Nevertheless, the two algorithms with the best performance (XGBoost and RF) indicate that a high percentage of the air quality is moderate. …”
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Fuzzy Evaluation and Benchmarking Framework for Robust Machine Learning Model in Real-Time Autism Triage Applications by Shayea G.G., Zabil M.H.M., Albahri A.S., Joudar S.S., Hamid R.A., Albahri O.S., Alamoodi A.H., Zahid I.A., Sharaf I.M.

“…These patients were categorized into one of three triage labels: urgent, moderate, or minor. We employ principal component analysis (PCA) and two algorithms to fuse a large number of dataset features. …”

Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate by Nadimalla, Altamashuddinkhan, Masjuki, Siti Aliyyah, Gubbi, Abdullah, Khan, Anjum, Mokashi, Imran

“…Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. …”
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Development of Deep Learning Classification Model for Diabetic Retinopathy Detection and Grading by Nurul Mirza Afiqah, Tajudin

“…The rapid growth of technologies and AI has led to the development of Deep Learning (DL), in which its algorithms are stacked in a hierarchy of increasing complexity and abstraction. …”
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A cluster analysis of population based cancer registry in Brunei Darussalam : an exploratory study by Lai, Daphne Teck Ching, Owais A. Malik

“…Machine learning techniques have been mostly applied in gene expression cancer data. …”
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Developing Android Application To Guide Lean Six Sigma PDCA Project by Ong, Sin Joo

“…Some recommendations were suggested for future development.…”
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Sentiment analysis of customer review for Tina Arena Beauty by Amri, Nur Najwa Shahirah

“…While the model provided valuable insights, limitations include its moderate accuracy and the lack of real-time updates. …”
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Unveiling sarcastic intent: web-based detection of sarcasm in news / Mohd Nazzim Lahaji, Tajul Rosli Razak and Mohammad Hafiz Ismail by Lahaji, Mohd Nazzim, Razak, Tajul Rosli, Ismail, Mohammad Hafiz

“…The results demonstrate the superiority of the developed model in sarcasm detection for news headlines. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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Hybrid neural network in medicolegal degree of injury determination based on Visum et Repertum by Wardhana, Mohammad Hadyan

“…GA is aimed to increase the accuracy and minimize the error in the learning stages of NN. The development phase accomplished with testing stages by employing VeR dataset. …”
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Penggunaan penggugusan subtraktif bagi menjana peraturan kabur by Agus Priyono, Muhammad Ridwan, Ahmad Jais Alias, Riza Atiq O. K. Rahmat, Azmi Hassan, Mohd. Alauddin Mohd. Ali

“…Many methodologies to develop fuzzy logic rules have been previously studied. …”
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Deep learning-based vehicular engine health monitoring system utilising a hybrid convolutional neural network/bidirectional gated recurrent unit by Rahim, Md. Abdur, Rahman, Md Mustafizur, Islam, Md. Shofiqul, Md. Muzahid, Abu Jafar, Rahman, Md. Arafatur, D., Ramasamy

“…This model monitors a vehicle’s engine health in real-time and classifies its status as good, critical, moderate, or minor condition. Several advanced and hybrid deep learning algorithms were applied to monitor engine health and categorise its status by integrating sensor data with evaluated vulnerability information from an infrastructure vulnerability assessment model. …”
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Predictive modeling of land surface temperature (LST) based on Landsat-8 satellite data and machine learning models for sustainable development by Pande C.B., Egbueri J.C., Costache R., Sidek L.M., Wang Q., Alshehri F., Din N.M., Gautam V.K., Chandra Pal S.

Classification of Mental Health Level of Students Using SMOTE and Soft Voting Ensemble Classifier and the DASS-21 Profile by Muhammad Imron, Rosadi, Khoirun, Nisa, Nanik, Kholifah

“…These findings support the use of ensemble learning and SMOTE for developing effective college student mental health screening systems, ultimately enabling timely intervention and support…”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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