Blood-Based Proteomic Profiling Identifies Potential Biomarker Candidates and Pathogenic Pathways in Dementia by Hanan Ehtewish (17149825)

“…We used a high-throughput proximity extension immunoassay to quantify 1090 proteins in 122 participants (22 with dementia, 64 with mild cognitive impairment (MCI), and 36 controls with normal cognitive function). …”

Nouveaux points de coupure et primitives pour les préoccupations de renforcement de sécurité by Mourad, Azzam

“…The two proposed primitives are called exportParameter and importParameter and are used to pass parameters between two pointcuts. They allow to analyze a program’s call graph in order to determine how to change function signatures for the passing of parameters associated with a given security hardening. …”
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Joint distributed synchronization and positioning in UWB ad hoc networks using TOA by Denis, B.

“…Finally, the proposed distributed maximum log-likelihood algorithm proves to preserve a reasonable level of complexity in each node by approximating asynchronously the positive gradient direction of the log-likelihood function. …”
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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. …”

Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

“…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …”
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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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Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP by Abdelhafez, Nada

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Robust tuning of power system stabilizers in multimachine powersystems by Abdel-Magid, Y.L.

“…The problem of selecting the stabilizer parameters is converted to a simple optimization problem with an eigenvalue-based objective function, which is solved by a tabu search algorithm. …”
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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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Adaptive cooperative control of nonlinear multi-agent systems with uncertain time-varying control directions and dead-zone nonlinearity by Maryam Shahriari-kahkeshi (17269051)

“…The dead-zone nonlinearity is described by an uncertain nonlinear function of the control input which can represent a wide class of practical input nonlinearities. …”

Fragment-based computational protein structure prediction by Mansour, Nashat

“…The method is based on a two-phase Scatter Search algorithm that minimizes the energy function. …”
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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…BackgroundBacterial endotoxin, a lipopolysaccharide exuded by bacteria during their growth and infection process, serves as a valuable biomarker for bacterial identification. …”
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Economic Production Lot-Sizing For An Unreliable Machine Under Imperfect Age-Based Maintenance Policy by El-Ferik, S

“…Numerical results are provided to illustrate both the use of the algorithm in the study of the optimal cost function and the latter's sensitivity to different changes in cost factors. …”
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Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

“…The learned system can apply sensor allocation online, works in real-time, and selects one radar and one camera at a time without having to reevaluate a cost function at every time step. …”
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Weak-coupling, strong-coupling and large-order parametrization of the hypergeometric-Meijer approximants by Abouzeid M. Shalaby (16810695)

“…<p dir="ltr">Without Borel or Padé techniques, we show that for a divergent series with n! large-order growth factor, the set of hypergeometric series _pF_p -2 represents suitable approximants. …”

FoGMatch by Arisdakessian, Sarhad

“…Our solution consists of (1) two optimization problems, one for the IoT devices and one for the fog nodes, (2) preference functions for both the IoT and fog layers to help them rank each other on the basis of several criteria such latency and resource utilization, and (3) centralized and distributed intelligent scheduling algorithms that consider the preferences of both the fog and IoT layers to improve the performance of the overall IoT ecosystem. …”
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GENETIC SCHEDULING OF TASK GRAPHS by Benten, M. S.

“…A genetic algorithm for scheduling computational task graphs is presented. …”
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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series by Lasfer, Assia

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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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