A novel network-based SIS framework for improved GA performance by Tohme, Rawane

“…To address these challenges, this work introduces SIS-NGA which integrates the Susceptible-Infected-Susceptible (SIS) epidemic model and Genetic Algorithms within a scale-free network topology, to guide the search for optimal solutions. …”
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Design and Optimization of a Planar Cable Robot by Kassem, Mohamad Hassan

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Autonomous 3D Deployment of Aerial Base Stations in Wireless Networks with User Mobility by Islambouli, Rania

“…We present performance results for the algorithm as a function of various system parameters assuming a random walk mobility model. …”
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Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition by Abboud, Ralph

“…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …”
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A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance by Krishnamoorthy Natarajan (22047464)

“…<p dir="ltr">A disease is a distinct abnormal state that significantly affects the functioning of all or part of an individual and is not caused by external harm. …”

ELISSAR. (c1997) by Nasreddine, Diana M.

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Fragment based protein structure prediction. (c2013) by Terzian, Meghrig Ohanes

“…The results, evaluated on three proteins, show that the algorithm produces tertiary structures with promising root mean square deviations, within reasonable times.…”
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Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation by Hariprasath Manoharan (14157966)

“…Additionally, a clustering algorithm with a fuzzy membership function is implemented, allowing the robots to advance in accordance with predefined clusters and arrive at their starting place within a predetermined amount of time. …”

CFD Based Airfoil Shape Optimization for Aerodynamic Drag Reduction by Khot, Mohammed Taha Shafiq

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Blood Glucose Regulation Modelling and Intelligent Control by Nasar, Nabeel

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Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling by Armin, Amindari

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Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network by Fares Almomani (12585685)

“…An ANN model consists of three layers, 15 neutrons and 260 <i>epochs</i> accurately predict the CMP with 99.1% of data within ±10% deviation of the mean experimental value. …”

Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling by Amindari, Armin

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DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications by Danya A. Saifaldeen (19498705)

“…The system comprises four VLC access points with light fixtures, reinforced by a mirror array sheet, and a mmWave access point with antennas, supported by a reflecting unit sheet. Within the system, both sheets function as IRS. The aim is to enhance the secrecy capacity (SC) of the system by optimizing the beamforming weights at the VLC fixtures, the beamforming weights at the mmWave AP, the mirror array configurations, and the phase shift vector while meeting specific power constraints. …”

Label dependency modeling in Multi-Label Naïve Bayes through input space expansion by PKA Chitra (21749216)

“…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. …”

Defense against adversarial attacks: robust and efficient compressed optimized neural networks by Insaf Kraidia (19198012)

“…First, introducing a pioneering batch-cumulative approach, the exponential particle swarm optimization (ExPSO) algorithm was developed for meticulous parameter fine-tuning within each batch. …”

Cohen syndrome and early-onset epileptic encephalopathy in male triplets: two disease-causing mutations in VPS13B and NAPB by Alice AbdelAleem (17753799)

“…Sanger sequencing verified the segregation of the two recessive gene variants with the phenotype in family members. The prediction algorithms support the pathogenicity of these variants. …”

Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes by Radhakrishnan Vishnubalaji (3563306)

“…., immune cells and stromal cells) within the tumor microenvironment. 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. …”

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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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…Unlike standard machine learning approaches such as PCA, LDA, SVM, RF, GBM etc, DeepRaman functions independently, requiring no human interaction, and can be used to much smaller datasets than traditional CNNs. …”
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