A method for data path synthesis using neural networks by Harmanani, H.

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Indexing Arabic texts using association rule data mining by Haraty, Ramzi A.

“…The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. Design/methodology/approach The proposed model uses an association rule algorithm for extracting frequent sets containing related items – to extract relationships between words in the texts to be indexed with words from texts that belong to the same category. …”
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Enhancing Personalized Learning Experiences through AI-driven Analysis of xAPI Data by ODEH, HANEEN

“…The Experience API (xAPI) provides a comprehensive mechanism to document all types of learning interactions, storing this stream of data into the Learning Record Store (LRS). …”
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Use of Data Mining Techniques to Detect Fraud in Procurement Sector by AL HAMMADI, SUMAYYA ABDULLA

“…The method used in this research is a classification of models and algorithms used in data mining. …”
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What are artificial intelligence literacy and competency? A comprehensive framework to support them by Thomas K.F., Chiu

“…We also identify five effective learning experiences to foster abilities and confidences, and suggest five future research directions: prompt engineering, data literacy, algorithmic literacy, self-reflective mindset, and empirical research.…”
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A Graph Heuristic Approach for the Data Path Allocation Problem by Makhoul, Racha

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The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review by Zainab Jan (17306614)

“…</p><h3>Objective</h3><p dir="ltr">This review aims to explore the machine learning algorithms used for the detection and diagnosis of bipolar disorder and its subtypes.…”

Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units by Shanableh, Tamer

“…The flags pertaining to 16x16 sub CUs are used as a cover for data embedding, where 6 or 4 message bits are embedded per CU. …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”

Auto-indexing Arabic texts based on association rule data mining. (c2015) by Rouba G. Nasrallah

“…Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. The model uses the Apriori Algorithm - an association rule algorithm for extracting frequent sets containing related items - to extract relations between words in the texts to be indexed with words from texts that belong to the same category. …”
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Using machine learning for disease detection. (c2013) by Jreij, Georges Antoun

“…Classification consists of predicting group membership for new data instances by learning from pre-classified data instances. …”
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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou (1887307)

“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”

Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining by Alqaryouti, Omar

“…Additionally, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is employed for modelling the two proposed clustering algorithms to identify transactional risks. …”
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

“…Featuring the capability of learning the correlations of time-series data, the proposed deep learning method is well-suited for extracting the valuable transient feature contained in the very beginning of the response curve. …”

Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur (712349)

“…It further aids in addressing challenges like data availability and geographical variations. It has been learned that image-processing techniques overwhelm the existing research and have the potential to integrate meteorological data. …”

An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems by Boukhari, Bahia

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Software defect prediction. (c2019) by Moussa, Rebecca

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Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

“…Furthermore, this paper demonstrates the advantages of the developed ADL algorithm approach and DSM prediction of the DT using vector autoregressive model for anomaly detection in utility gas turbines with data from an operational power plant.…”

Defining quantitative rules for identifying influential researchers: Insights from mathematics domain by Ghulam Mustafa (458105)

“…The rules were developed for each parameter category using the Decision Tree Algorithm, which achieved an average accuracy of 70 to 75 percent for identifying awardees in mathematics domains. …”