Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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VEGAWES: variational segmentation on whole exome sequencing for copy number detection by Samreen Anjum (19651882)

“…We tested this algorithm on synthetic data and 100 Glioblastoma Multiforme primary tumor samples. …”

Growing hierarchical self-organizing map for filtering intrusion detection alarms by Mansour, Nashat

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Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning by ALFALASI, FARIS Jr

“…Pre-processing is a vital part of the data preparation process for cyberbullying detection. …”
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Efficient XML Structural Similarity Detection using Sub-tree Commonalities by Tekli, Joe

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PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits by Hind Almerekhi (7434776)

“…Implications are that toxicity trigger detection algorithms can leverage generic approaches but must also tailor detections to specific communities.…”

NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY by JINESH, PADIKKAPPARAMBIL

“…This study's dataset was sourced from the Kaggle machine learning repository, and it refers to data gathering from wearable IoT devices. The experimental outcomes demonstrate the proposed MCFS, NCA, and NSCP algorithms work more effectively than previous feature selection, clustering and classification algorithms, respectively, in terms of accuracy, sensitivity, specificity, precision, recall, f-measure and execution time. …”
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Predicting the Impact of Data Poisoning Attacks in Blockchain-Enabled Supply Chain Networks by Javed Butt , Usman

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BioNetApp: An interactive visual data analysis platform for molecular expressions by Ali M. Roumani (18615124)

“…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”

ADD. (c2002) by Varjabedian, Ralph A.

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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

Generic metadata representation framework for social-based event detection, description, and linkage by Abebe, Minale A.

“…Various methods have been put forward to perform automatic social-based event detection and description. Yet, most of them do not capture the semantic meaning embedded in online social media data, which are usually highly heterogeneous and unstructured, and do not identify event relationships (e.g., car accident temporally occurs after storm, and geographically occurs near soccer match). …”
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Enhancing Personalized Learning Experiences through AI-driven Analysis of xAPI Data by ODEH, HANEEN

“…There is a gap of research in utilizing xAPI and AI integration in addressing learning objectives and understanding learners cognitive state and the utilization of data in actionable manner. This paper recommends a competency-aware framework for integrating xAPI and AI that predicts the pass/fail status of every student and provides personalized actionable feedback in an autonomous manner and in human-friendly language. …”
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Efficient Test Compaction for Combinational Circuits Based on Fault Detection Count-Directed Clustering by El-Maleh, Aiman H.

“…Test compaction is an effective technique for reducing test data volume and test application time. In this paper, we present a new static test compaction algorithm based on test vector decomposition and clustering. …”
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Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks by Daou, Leonardo

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Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression by Alaa Abd-Alrazaq (17430900)

“…<p dir="ltr">Given the limitations of traditional approaches, wearable artificial intelligence (AI) is one of the technologies that have been exploited to detect or predict depression. The current review aimed at examining the performance of wearable AI in detecting and predicting depression. …”

Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives by Yassine Himeur (14158821)

“…If leveraged properly, that data could assist end-users, energy producers and utility companies in detecting anomalous power consumption and understanding the causes of each anomaly. …”

Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems by Tarek Berghout (16905132)

Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights by Malekloo, Arman

“…In the age of the smart city, Internet of Things (IoT), and big data analytics, the complex nature of data-driven civil infrastructures monitoring frameworks has not been fully matured. …”
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