TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

“…By using a comprehensive dataset with multiple attack types, a well-trained model can be created to improve the anomaly detection performance. …”

Automated Detection of Colorectal Polyp Utilizing Deep Learning Methods With Explainable AI by Md. Faysal Ahamed (21842396)

“…These polyps cause severe conditions in the colon or rectum, presenting a significant diagnostic challenge. Traditional manual detection through medical imaging is not only bulky and prone to errors but also incurs substantial costs, requiring expert endoscopist. …”

An efficient artificial intelligence approach for early detection of cross-site scripting attacks by Younas, Faizan

“…Cross-Site Scripting (XSS) attacks continue to pose a significant threat to web applications, compromising the security and integrity of user data. …”
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Bridging Innovation and Security: Advancing Cyber-Threat Detection in Sustainable Smart Infrastructure by Duaa Shoukat (20961200)

“…This significant improvement over existing models underscores the efficacy of our approach in mitigating cyber-threats in smart infrastructure environments.…”

Diabetic Foot Ulcer Detection: Combining Deep Learning Models for Improved Localization by Rusab Sarmun (17632269)

“…Our WBF-based approach combining YOLOv8m and FRCNN-ResNet101 achieves a mean average precision (mAP) score of 86.4% at the IoU threshold of 0.5 on the DFUC2020 dataset, significantly outperforming the former benchmark by 12.4%. …”

Toward Adaptive Intrusion Detection Systems for UAVs Using Cyber-Physical Image Analysis by Hanane Amirat (23126110)

“…Despite the growing body of research on intrusion detection systems (IDS) for UAVs, many existing solutions exhibit significant limitations, including a reliance on synthetic datasets and binary classification frameworks. …”

Effect of Intravenous Mannitol on Intraocular Pressure Changes in Vitrectomized and Non-Vitrectomized Eyes: A Systematic Review and Meta-Analysis by HASHEM ABU SERHAN (19737499)

“…No significant changes were observed on IOP with mannitol administration when comparing vitrectomized versus non- vitrectomized eyes.…”

Hybrid Model for Detection of Cervical Cancer Using Causal Analysis and Machine Learning Techniques by Umesh Kumar Lilhore (17727684)

“…This research proposed an efficient feature selection and prediction model for cervical cancer datasets using Boruta analysis and SVM method to deal with this challenge. …”

A Novel Versatile Framework for Enabling Early Detection of Evolving Network-based Cyberattacks by THOMAS, RAJESH

“…Histogram of Oriented Gradients (HOG), entropy byte histogram, byte-based feature learning, and representation learning from bytes, were used to demonstrate the applicability of the FPAC framework for early attack detection. Experiments were performed to validate the FPAC approach using the CTU botnet and the UTSA 2021 LDoS datasets. …”
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Fourier Transform Infrared Imaging—A Novel Approach to Monitor Bio Molecular Changes in Subacute Mild Traumatic Brain Injury by Fazle Rakib (5768069)

“…Significant decrease in methyl content and a significant increase in olefinic content were observed in Co and CC regions of mTBI rat brain tissues. …”

Enhanced coronary artery segmentation and stenosis detection: Leveraging novel deep learning techniques by Abu Jaffor Morshedul Abedin (22803884)

A FeedForward–Convolutional Neural Network to Detect Low-Rate DoS in IoT by Harun Surej Ilango (17545728)

“…The Canadian Institute of Cybersecurity Denial of Service 2017 (CIC DoS 2017) dataset is used for the study. An iterative wrapper-based feature selection using Support Vector Machine (SVM) is used to derive the significant features required for detection. …”

A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

PermGuard: A Scalable Framework for Android Malware Detection Using Permission-to-Exploitation Mapping by Arvind Prasad (19997799)

“…This paper introduces PermGuard, a scalable framework for Android malware detection that maps permissions into exploitation techniques and employs incremental learning to detect malicious apps. …”

Crowd behavior detection: leveraging video swin transformer for crowd size and violence level analysis by Marwa Qaraqe (10135172)

“…<p dir="ltr">In recent years, crowd behavior detection has posed significant challenges in the realm of public safety and security, even with the advancements in surveillance technologies. …”

A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

“…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. …”

Enhancing waste sorting and recycling efficiency: robust deep learning-based approach for classification and detection by Faizul Rakib Sayem (21399890)

“…Additionally, we introduced the GELAN-E (generalized efficient layer aggregation network) model for waste object detection tasks, obtaining a mean average precision (mAP50) of 63%, surpassing other state-of-the-art detection models. …”

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

“…Following, insights about current research trends are discussed to widen the applications and effectiveness of the anomaly detection technology before deriving future directions attracting significant attention. …”

Dynamic Change in Insulin Resistance Induced by Free Fatty Acids Is Unchanged Though Insulin Sensitivity Improves Following Endurance Exercise in PCOS by Myint Myint Aye (6404327)

Assessing the Built Environment’s Reflectivity, Flexibility, Resourcefulness, and Rapidity Resilience Qualities against Climate Change Impacts from the Perspective of Different Sta... by Mohammed M. Al-Humaiqani (18325554)

“…<p dir="ltr">The frequency and severity of climate change are projected to increase, leading to more disasters, increased built environment system (BES) vulnerability, and decreased coping capacity. …”