Idio, Emmanuel E.
Department Of Geography And Natural Resources Management,university Of Uyo
Aggregating Species Distribution In Distorted Mangrove Communities Of Coastal Nigeria
The study assessed the effects of land use drivers on vegetation diversity, and projected the. To achieve these objectives, the study used remotely sensed image data and direct field observation. Landsat imageries of 1986, 2003 and 2022 were utilized for pre-processing of data, employing unsupervised classification. A total of 400 copies of questionnaire were used to determine the drivers of

Dr Y. M. Malgwi
Faculty Of Computing, Department Of Computer Science, Modibbo Adama University, Yola, Nigeria
From Rules To Transformers: A Review Of Spam Detection Techniques, Research Gaps And The Promise Of Bert-ensemble Frameworks
Spam has grown from a minor nuisance into one of the most persistent threats in digital communication, yet existing detection systems continue to struggle with balancing accuracy and computational efficiency. This paper reviews the evolution of spam detection approaches from early rule-based filters and traditional machine learning classifiers to deep learning models and transformer-based architectures with particular attention to the

Dr Y. M. Malgwi
Faculty Of Computing, Department Of Computer Science, Modibbo Adama University, Yola
A Review Of Deep Learning Approaches To Real-time Financial Fraud Detection, Research Gaps And The Path Forward
Financial fraud costs the global economy over $40 billion annually, yet existing detection systems continue to struggle at the intersection of accuracy, latency, interpretability, and fairness. This paper reviews the evolution of fraud detection methods from early rule-based systems and classical machine learning through recurrent and convolutional deep learning architectures, to transformer models, graph neural networks, and federated learning with

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