Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) by Bitar, Mandy

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Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

“…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”

Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context by SALIM, MAHA JAWDAT

“…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
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Towards Multimedia Fragmentation by Saad, Samir

“…Database fragmentation is a process for reducing irrelevant data accesses by grouping data frequently accessed together in dedicated segments. …”
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Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review by Arfan Ahmed (17541309)

“…WDs coupled with artificial intelligence (AI) algorithms show promise to help understand and conclude meaningful information from the gathered data and provide advanced and clinically meaningful analytics.…”

CAD TOOL FOR THE AUTOMATIC-GENERATION OF MICROPROGRAMS by Sait, Sadiq M.

“…Since the UAHPL model is directly related to hardware, this approach is better than those based on ordinary high-level languages or special microprogram languages. …”
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Artificial Intelligence for Skin Cancer Detection: Scoping Review by Abdulrahman Takiddin (14153181)

“…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.…”

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

“…LR DoS attacks are difficult to detect as their attack signature is similar to benign network traffic. The existing AI-based detection algorithms in the literature are signature-based, and their efficacy in detecting unknown LR DoS attacks was not explored. …”

Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images by Rehan Raza (17019105)

“…Lung-EffNet is built based on the architecture of EfficientNet and further modified by adding top layers in the classification head of the model. …”

Combinatorial method for bandwidth selection in wind speed kernel density estimation by El Dakkak, Omar

“…This goal calls for devising probabilistic models with adaptive algorithms that accurately fit wind speed distributions. …”
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Fuzzy controllers design using space-filling curves by Elshafei-Ahmed, M.

“…We then propose a SFC fuzzy inference model based on clustering the object space. The SFC fuzzy model is then used to design a fuzzy controller. …”
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Fuzzy Controllers Design Using Space-Filling Curves by Elshafei-Ahmed, M

“…We then propose a SFC fuzzy inference model based on clustering the object space. The SFC fuzzy model is then used to design a fuzzy controller. …”
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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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A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…We present a structured taxonomy covering value-based, policy-based, actor-critic, model-based, and advanced multi-agent and multi-objective approaches, and link algorithms to tasks such as dispatch, microgrid coordination, real-time pricing, load balancing, and demand–response. …”

Single-channel speech denoising by masking the colored spectrograms by Sania Gul (18272227)

“…With a slightly reduced PESQ score (by 0.58 points), the proposed model offers an improvement of 2 % in STOI, and 4375 and 1135 times reduction respectively in the required number of training epochs and network parameters when compared to a GAN-based model augmented by WavLM; a large-scale self-supervised learning model. …”

Accelerating Blockchain Transaction Verification With Parallel Computing by Zhou, Huangjin

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Identification of phantom movements with an ensemble learning approach by Akhan Akbulut (17380285)

“…Our study demonstrated that the ensemble learning-based models resulted in higher accuracy in the detection of phantom movements. …”

Efficient XML Structural Similarity Detection using Sub-tree Commonalities by Tekli, Joe

“…Various algorithms for comparing hierarchically structured data, e.g. …”
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Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes by Radhakrishnan Vishnubalaji (3563306)

“…In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER⁺), HER2⁺, ER⁺HER2⁺, and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells’ publicly available transcriptomic data derived from 26 BC patients. …”

Prototype project management tool (PPMT) with cocomo calibration. (c1998) by Haddad, Ibrahim F.

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