Machine Learning Techniques for Pharmaceutical Bioinformatics by SULTAN, AHMED ATTA AHMED

“…In this matrix, each drug is represented by a vector of attributes from all other drugs. A predictive model is developed to predict drug indication as well as to predict new DDIs using multiple machine learning algorithms. …”
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Optimal Planning of Distributed Generators and Shunt Capacitors in Isolated Microgrids With Nonlinear Loads by Yazdavar, Ameen H.

“…The intermittent natures of loads and renewable DGs are modelled probabilistically. The effectiveness of the proposed planning approach has been validated using the PG&E 69-bus system, and the followings are observed: 1) the significance of applying suitable fundamental-power-flow and harmonic-power-flow algorithms for isolated microgrids, and 2) the possibility of avoiding a severe voltage distortion by utilizing an appropriate planning method and only small increase in the cost.…”
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Transformations for Variants of the Travelling Salesman Problem and Applications by Assaf, Mustafa Jamil

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Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective by Zhitao Xu (2426023)

“…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. …”

Artificial Intelligence for Assessing the Correlation Between Sleep Apnoea and Comorbidities by Ramesh, Jayroop

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Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach by Mohammad Taghi Dabiri (16904658)

“…We then formulate the problem for UAV trajectory to minimize the maximum outage probability (OP) of directional THz links. Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …”

Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters by Farhan, Abid

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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

“…Given the complexity of the LDTP solution for managing online requests, we propose a real-time, lightweight solution using multi-agent meta-reinforcement learning. Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. …”

Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study by Alaa Abd-alrazaq (17058018)

“…Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.…”

Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review by Arfan Ahmed (17541309)

“…Wearable devices (WDs) make use of sensors historically reserved for hospital settings. …”

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

“…The algorithms used in the process of translation from UAHPL description to microprograms are also discussed. …”
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Depthwise Separable Convolutions and Variational Dropout within the context of YOLOv3 by Chakar, Joseph

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Data Endowment as a Digital Waqf: An Islamic Ethical Framework for AI Development by Abdulqadir J. Nashwan (11659453)

“…<p dir="ltr">In the era of artificial intelligence (AI), data is often called the new oil—an essential asset for training algorithms and fueling intelligent systems. However, the ethical considerations surrounding this data’s ownership, use, and benefits remain contentious. …”

SemIndex: Semantic-Aware Inverted Index by Chbeir, Richard

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A family of minimum curvature variable-methods for unconstrained optimization. (c1998) by Obeid, Samir Y.

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Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces by Uzair Sajjad (19646296)

“…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …”

Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures by Iryna Haponchyk (19691701)

“…Most interestingly, we show that such functions can be (i) automatically learned also from controversial but commonly accepted coreference measures, e.g., MELA, and (ii) successfully used in learning algorithms. The accurate model comparison on the standard CoNLL-2012 setting shows the benefit of more expressive loss functions.…”

Data redundancy management for leaf-edges in connected environments by Mansour, Elio

“…Major advances in the fields of Internet and Communication Technology (ICT), data modeling/processing, and sensing technology have rendered traditional environments (e.g., cities, buildings) more connected. …”
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A Cyber-Physical System and Graph-Based Approach for Transportation Management in Smart Cities by Muhammad Mazhar Rathore (17051745)

“…Traditional graph algorithms with efficient implementation technologies are employed to respond to commuters’ and authorities’ needs in order to achieve a smart and optimum transportation system. …”

Energy-Efficient VoI-Aware UAV-Assisted Data Collection in Wireless Sensor Networks by Kalash, Saeddin

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