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  1. 1

    Detection of statistically significant network changes in complex biological networks by Raghvendra Mall (581171)

    Published 2017
    “…It can happen that due to gene mutations, as for example when cancer progresses, the gene expression network undergoes some amount of localized re-wiring. The ability to detect statistical relevant changes in the interaction patterns induced by the progression of the disease can lead to the discovery of novel relevant signatures. …”
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    Land Use/Land Cover Changes Impact on Groundwater Level and Quality in the Northern Part of the United Arab Emirates by Elmahdy, Samy

    Published 2020
    “…Each pair of enhanced LULC maps (1990–2000, 2000–2010, 2010–2018, and 1990–2018) were used as input data for an image difference algorithm to monitor LULC changes. Maps of change detection were then imported into a GIS environment and spatially correlated against the spatiotemporal maps of groundwater level and groundwater quality. …”
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    Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

    Published 2022
    “…The research work carried out, in relation to attack detection ensemble learning, mainly aims to increase the performance of machine learning algorithms by combining their results. …”
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    Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

    Published 2023
    “…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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    Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

    Published 2023
    “…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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    Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques by Amith Khandakar (14151981)

    Published 2022
    “…Plantar foot thermogram images acquired using an infrared camera have been shown to detect changes in temperature distribution associated with a higher risk of foot ulceration. …”
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    Digital-Twin-Based Diagnosis and Tolerant Control of T-Type Three-Level Rectifiers by Ali Sharida (17947847)

    Published 2023
    “…Then, the DT is used for the diagnosis and tolerance of open-switch faults (OSFs) and faults related to voltage and current sensors or for sensorless control. The OSF detection and localization algorithm is implemented based on the dynamic response difference between the physical system and its DT. …”
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    A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study by Masurkar, Faeez

    Published 2022
    “…Further, As the quality of received signals differs at different sensing points as a result of the surface conditions of the specimen, the Self Adaptive Smart Algorithm (SASA) method was adopted to filter out the noise and accurately pinpoint the defect reflected wave packet which ultimately aids in better detection and localization. …”
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    Image Local Features Description Through Polynomial Approximation by Fawad - (17018015)

    Published 2019
    “…The rotation invariance is achieved by aligning the local patch around the Harris corner through the dominant orientation shift algorithm. Weighted threshold histogram equalization (WTHE) is employed to make the descriptor in-sensitive to illumination changes. …”
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    Optimizing ADWIN for Steady Streams by Moharram, Hassan

    Published 2022
    “…Over time, several drift detection approaches have been proposed. A prominent approach is adaptive windowing (ADWIN) which can detect changes in features data distribution without explicit feedback on the correctness of the prediction. …”
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    Benchmarking Concept Drift Detectors for Online Machine Learning by Mahgoub, Mahmoud

    Published 2022
    “…The main task is to detect changes in data distribution that might cause changes in the decision bound aries for a classification algorithm. …”
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    Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura, Habiba

    Published 2023
    “…However, traditional IDS often follows rule-based detection where the rules can be changed and exposed to the attacker and becomes weak over time. …”
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    Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura Habiba (17808302)

    Published 2023
    “…However, traditional IDS often follows rule-based detection where the rules can be changed and exposed to the attacker and becomes weak over time. …”
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    CEAP by Abdel Wahab, Omar

    Published 2016
    “…We propose as well a propagation algorithm that disseminates only the final decisions (instead of the whole dataset) among clusters with the aim of reducing the overhead of either exchanging results between each set of vehicles or repeating the detection steps for the already detected malicious vehicles. …”
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    A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity by Abdullah Al Siam (22304047)

    Published 2025
    “…We examine cutting-edge AI methodologies and principal models across many domains, including machine learning algorithms, deep learning architectures, natural language processing techniques, and anomaly detection algorithms, emphasizing their distinct contributions to enhancing security. …”
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    Evolutionary support vector regression for monitoring Poisson profiles by Ali Yeganeh (16624998)

    Published 2023
    “…This paper aims to monitor Poisson profile monitoring problem in Phase II and develops a new robust control chart using support vector regression by incorporating some novel input features and evolutionary training algorithm. The new method is quicker in detecting out-of-control signals as compared to conventional statistical methods. …”
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