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PatternIQ Mining (PIQM)

Published by Sahara Digital Publication  •  eISSN: 3006-8894

Current Issue

Volume 3, Issue 1 - 2026

Original Research
Self-Supervised Vision Transformer with Swarm Intelligence for Pattern-Aware Crop Stress Detection in Smart Farming Environments

Authors Details: Fatima Al Nuaimi and Noor Aisyah Rahman

Abstract: The following limitations exist in the traditional crop stress detection techniques in the background of smart farming applications: low detection accuracy, inefficient feature extraction, poor adaptability to the environment, and high computational complexity. Stress detection using traditional mac more...

101 71
DOI: 10.70023/piqm311
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Original Research
Robust Acoustic Pattern Recognition for Low Resource Automatic Speech Recognition System

Authors Details: Hassan Al Tamimi and Sara Hosseini

Abstract: ASR systems have been highly successful in high-resource languages yet less effective in low-resource languages due to limited labeled speech data, speaker variability, background noise, and variable acoustic conditions. The significant barrier to accessing and deploying speech-enabled technologies more...

87 65
DOI: 10.70023/piqm312
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Original Research
Adaptive Pattern Computation with Swarm Optimization and Deep Learning for Efficient Traffic Flow Prediction in Intelligent Transportation

Authors Details: Reza Mohammadi and Maryam Al Balushi

Abstract: The current conventional traffic flow prediction methods adopted in Intelligent Traffic Systems (ITS) are severely frustrated by their static model architectures, fixed hyperparameter values, and restricted spatiotemporal learning capabilities, which are unable to model the nonlinear traffic dynamic more...

92 86
DOI: 10.70023/piqm313
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Original Research
Fast Pattern Discovery in Big Data Mining Using Incremental Mining for Social Media Analysis

Authors Details: Nasser Al Riyami and Amal Al Hinai

Abstract: Social media websites generate high-volume, high-velocity data streams that are hard to deal with using traditional data-mining techniques. Most methods for mining frequent and sequential patterns of data currently in use require the whole data set to be reprocessed each time a new post is added to more...

81 85
DOI: 10.70023/piqm314
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Original Research
Explainable Quantum-Driven Pattern Recognition for Multimodal Brain Tumor Classification Using Hybrid Deep Learning Networks

Authors Details: Lim Wei Jian and Huda Al Kaabi

Abstract: The classification of brain tumors with traditional deep learning methods is challenging due to its lack of interpretability, computational complexity and its limited classification ability for multimodal medical image data. The influence of clinical diagnosis can impede early detection of tumors more...

81 68
DOI: 10.70023/piqm315
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Original Research
Deep Pattern Recognition Framework for Early Tumor Detection in Multimodal Medical Imaging

Authors Details: Nasser Al Riyami and Huda Al Kaabi

Abstract: In medical imaging, there are many challenges associated with diagnostic systems to detect tumors earlier: the integration of different imaging modalities. Due to the multifactorial nature of tumors, the lack of representation of features and the high proportion of false positives, the reliability o more...

86 83
DOI: 10.70023/piqm316
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Original Research
Advanced Pattern Computation Using Reinforcement Learning and Metaheuristic Optimization for Energy Consumption Forecasting in Smart Grid Networks

Authors Details: Yousif Al Suwaidi

Abstract: The energy consumption is one of the significant challenges of smart grid networks, since it has nonlinear and changing trends, high computational complexity of the conventional forecasting systems, and uncertainty in the data. The existing machine learning and statistical forecasting methods do n more...

69 66
DOI: 10.70023/piqm317
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Original Research
Seeker Optimized Deep Neural Model for Pattern Mining in Smart Grid Energy

Authors Details: Kaveh Rostami and Mahsa Karimi

Abstract: Smart grids collect a tremendous amount of energy-use data in various formats from smart meters, distributed sensors, renewable energy systems, and IoT monitoring systems. However, existing pattern mining techniques using deep neural networks are complex, and feature optimization and predictive p more...

80 69
DOI: 10.70023/piqm318
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Original Research
Intelligent Pattern Computation with Deep Learning and Swarm Optimization for Personalized Learning Analytics in Smart Education Systems

Authors Details: Salim Mahrouqi and Azreen Ismail

Abstract: The fast pace of the evolution of smart education platforms, it is possible to leverage the interaction data of the learner to create more advanced personalized learning analytics. Current approaches to prediction of student performance and the adaptivity of learning systems are not optimal in featu more...

87 115
DOI: 10.70023/piqm319
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Original Research
Federated Graph Neural Pattern Learning Framework for Adaptive Intrusion Detection in Large-Scale IoT Networks

Authors Details: Shamsi Lawati and Zainab Mahmood Al Obaidi

Abstract: Internet of Things (IoT) systems are a major source of vulnerability for large networks, leaving them particularly susceptible to distributed denial of service (DDoS) attacks, botnet growth, spoofing and zero-day attacks. The existing centralized intrusion detection systems (IDSs) are linked to h more...

99 59
DOI: 10.70023/piqm3110
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