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Postsurgery classification of best-corrected visual acuity changes based on Pterygium Characteristics using the Machine Learning Technique by Jais, Fatin Nabihah, Che Azemin, Mohd Zulfaezal, Hilmi, Mohd Radzi, Mohd Tamrin, Mohd Izzuddin, Mohd. Kamal, Khairidzan

“…Conclusion. Machine learning algorithms can produce a highly accurate postsurgery classification model of BCVA changes using pterygium characteristics.…”
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Change vulnerability forecasting using deep learning algorithm for Southeast Asia by Amelia Ritahani, Ismail, Nur ‘Atikah, Mohd Ali, Junaida, Sulaiman

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A Multi-tier Model and Filtering Approach to Detect Fake News Using Machine Learning Algorithms by Yu, Chiung Chang, A Hamid, Isredza Rahmi, Abdullah, Zubaile, Kipli, Kuryati, Amnur, Hidra

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An adaptive HMM based approach for improving e-Learning methods by Deeb B., Hassan Z., Beseiso M.

“…These users may have varying Visual, Auditory and Kinesthetic (VAK) oriented learning curves based on their mental abilities and these individual curves may also change during the course of education. …”

Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms by Nurellezia, Suleiman

“…The transformed data is then modelled using machine learning algorithms such as Naïve Bayes classifier and Support Vector Machine to predict the overall sentiment of tweets, in which the finding depicted an overall positive sentiment surrounding the issue. …”
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Neural Network Based Pattern Recognition in Visual Inspection System for Intergrated Circuit Mark Inspection by Sevamalai, Venantius Kumar

“…These algorithms could not compensate for the change or variation on the inspected parts dynamically. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

“…We applied a deep extreme learning machine approach to predict the user parameters. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…Furthermore, the efficacy of different models based on heuristic hyperparameter tuning is evaluated in which the different kernel function for Support Vector Machine, various distance metrics of k-Nearest Neighbors. The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Critical review of object detection techniques for traffic light detection in intelligent transportation systems by Muhammad Adhwa, Mohd Salemi, Muhammad Arif, Mohamad

“…Despite progress in deep learning and optimization algorithms, traffic light detection still faces persistent challenges under varying conditions such as illumination changes, occlusions, and visual clutter. …”
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Short lead time standard precipitation index forecasting: Extreme learning machine and variational mode decomposition by Ladouali S., Katipo?lu O.M., Bahrami M., Kartal V., Sakaa B., Elshaboury N., Keblouti M., Chaffai H., Ali S., Pande C.B., Elbeltagi A.

“…Study focus: This study focused on creating a novel hybrid VMD-ELM approach, established by combining the Variational Mode Decomposition (VMD) technique and the Extreme Learning Machine (ELM) algorithm as a preprocessing technique for predicting future droughts. …”

A Stepper Motor Design Optimization Using by Wong, Chin Wei

“…In this project, the program that has been developed is run to get the optimization result with Microsoft Visual C++. In order to obtain better results from the program, some of the parameters have to be changed. …”
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Comprehensive review of retinal blood vessel segmentation and classification techniques: intelligent solutions for green computing in medical images, current challenges, open issue... by Abdulsahib A.A., Mahmoud M.A., Mohammed M.A., Rasheed H.H., Mostafa S.A., Maashi M.S.

An early warning system for students at risk using supervised machine learning by Yam, Zheng Hong, Mohd Norshahriel, Abd Rani, Nabilah Filzah, Mohd Radzuan, Lim, Huay Yen, Sarasvathi, Nagalingam

“…As a result, significant changes have occurred in education, in which teaching is done remotely. …”
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Development of graphical interface software for solar flare monitoring system by Mohamad Zulfahmi Mohamad Izham, Gan, Kok Beng, Mardina Abdullah, Siti Aminah Bahari, Sabirin Abdullah

“…The developed Graphical Interface software showed a visualized sunrise and sunset patterns which is in agreement with the previous study. …”
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Development of river water level estimation from surveillance cameras for flood monitoring system using deep learning techniques by Muhadi, Nur 'Atirah

“…The findings demonstrated that these methods are handcrafted and the algorithms need to be changed when applying to different images, which is not practical to be used during flood disasters. …”
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Network intrusion detection and alert system by To, Jin Yi

“…Signature-based detection compares network traffic packets with a real-time updated database of known attack patterns, while anomaly-based detection algorithms learn normal behavior patterns and identify deviations. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

“…The IncFRNN algorithm is able to control the size of training pool using predefined window size threshold. …”
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In silico approaches for unearthing bacterial quorum-sensing inhibitors against pathogenic bacteria by Pawar, Shrikant, Bramha Chari, P. V., Lahiri, Chandrajit *

“…Thus, certain group of researchers also developed machine learning tools based on support vector machine (SVM) and hidden Markov models (HMM) for the identification of novel and effective biofilm inhibitory peptides (BIPs), while others used in silico approaches for predicting and designing of antibiofilm peptides usingbidirectional recursive neural network (BRNN) and Random Forest (RF) algorithms. …”
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