Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks by Daou, Leonardo

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An Introduction to the Special Issue “Protein Glycation in Food, Nutrition, Health and Disease” by Naila Rabbani (291722)

“…The keynote speaker was Lasker Laureate Professor Kazutoshi Mori, speaking on the unfolded protein response, and there were sessions on: glycation in obesity, diabetes, and diabetic complications; glycation in food; glycation through the life course—from maternal bonding to aging; glycation in plants—physiology, function, and food security; glycation in the COVID-19 response; glycation analytics and chemistry; glycation in kidney disease, cancer, and mental health; glycation-related imaging, diagnostic algorithms, and therapeutics; and methods and models in glycation research. …”

Artificial intelligence in respiratory care by Manjush Karthika (18384907)

“…Despite barriers, the current decade is witnessing an increased utility of AI into diverse specialities of the medical field to enhance precision medicine, predict diagnosis, therapeutic results, and prognosis; this includes respiratory medicine, critical care, and in their allied specialties. AI algorithms are widely studied in areas like mechanical ventilation, sleep medicine, lung ultrasound, and pulmonary function diagnostics and the results are found to be promising. …”

Traffic Offloading with Channel Allocation in Cache-Enabled Ultra-Dense Wireless Networks by Abbas, Nadine

“…We generate results as a function of a wide range of system parameters, and demonstrate that the proposed algorithms achieve near-optimal performance with notably low time complexity.…”
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Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization by Hafez, Ishaq

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Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates by Ratiba F. Ghachi (14152455)

“…The thin plate and the zigzag cutouts are modelled using the finite element method, and the optimal location and optimal tip mass of the zigzag cutouts are obtained using genetic algorithms through iterative simulations. Two case studies are considered, and the fitness function used in the optimization problem is the plate’s root mean square of vibration in a specific low-frequency range. …”

Software defect prediction. (c2019) by Moussa, Rebecca

“…This is normally measured at the level of a module. A module is a class in the object-oriented design or a function in the procedural design. …”
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Assessing Factors Influencing Customers’ Adoption of AI-Based Voice Assistants by Surbhi Choudhary (21633701)

“…To examine the hypothesized relationship, a quantitative approach employing PLS-SEM was utilized to evaluate a representative sample of 1189 Indian consumers and examining the psychological and functional constructs leading to adoption intention for voice assistants. …”

LNCRI: Long Non-Coding RNA Identifier in Multiple Species by Saleh Musleh (15279190)

“…</p> <p> </p> <h2>Other Information</h2> <p>Published in: Pathogens<br> License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br> See article on publisher's website: <a href="https://doi.org/10.1109/access.2021.3131846" target="_blank"><u>https://doi.org/10.1109/access.2021.3131846</u></a></p>…”

Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodolog... by Mutasim Baba, Fuad

“…This paper aims to develop long-term adaptation strategies for the existing Canadian school buildings under extreme current and future climates using a developed methodology based on global and local sensitivity analysis and Multi-Objective Optimization Genetic Algorithm. …”
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Analyzing Partial Shading in PV Systems Using Wavelet Packet Transform and Empirical Mode Decomposition Techniques by Kais Abdulmawjood (17947784)

“…In the first stage, the WPT is used to split the PV voltage and string currents into specific sub-band frequencies, and then EMD is used to decompose the selected frequency bands into a number of intrinsic mode functions (IMFs) and a residual. …”

StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features by Muhammad Arif (769250)

“…Thus, the shortcomings of wet lab experiments are leveraged by computational methods to accurately predict the functional types of DPs. In this paper, we aim to propose a novel multi-class ensemble-based prediction model called StackDPPred for identifying the properties of DPs. …”

Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle by Reza Jafari (3494018)

“…., linear quadratic regulator with the sequential quadratic programming (LSQP) and sliding mode control with SQP (SSQP). A tailored multi-term reward function is structured to penalize excessive yaw rate error, sideslip angle, tire slip deviations beyond peak grip regions, and power losses based on a realistic electric machine efficiency map. …”

Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches by Mohammad, Areej Osama

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Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …”

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. …”

Condenser capacity and hyperbolic perimeterImage 1 by Mohamed M.S., Nasser

“…Especially, we apply domain functionals to study the capacities of condensers (G,E) where G is a simply connected domain in the complex plane and E is a compact subset of G. …”
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H.264/AVC to HEVC Video Transcoder Based on Dynamic Thresholding and Content Modeling by Peixoto, Eduardo

“…Then, two types of mode mapping algorithms are proposed. In the first solution, a single H.264/AVC coding parameter is used to determine the outgoing HEVC partitions using dynamic thresholding. …”
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Condenser capacity and hyperbolic perimeter by Mohamed M.S. Nasser (16931772)

“…Especially, we apply domain functionals to study the capacities of condensers (,) where is a simply connected domain in the complex plane and is a compact subset of . …”

Deploying model obfuscation: towards the privacy of decision-making models on shared platforms by Sadhukhan, Payel

“…Privacy and security of data and models are fundamental necessities that must be satisfied for this protocol's proper functioning. To this end, we propose a conceptual and algorithmic framework of a model obfuscation scheme. …”
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