Random vector functional link network: Recent developments, applications, and future directions by A.K. Malik (16003193)

“…<p>Neural networks have been successfully employed in various domains such as classification, regression and clustering, etc. Generally, the back propagation (BP) based iterative approaches are used to train the neural networks, however, it results in the issues of local minima, sensitivity to learning rate and slow convergence. …”

Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

“…In the event of a violation in internet security, an attacker was able to interfere with the system's functions, which might result in catastrophic consequences. …”
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Particle swarm optimization based algorithm for protein structure prediction in the 3D HP model. (c2008) by Kanj, Fatima Hassan

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A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models by Osama Bassam J. Rabie (21323741)

“…<p dir="ltr">The Internet of Things (IoT) is extensively used in modern-day life, such as in smart homes, intelligent transportation, etc. However, the present security measures cannot fully protect the IoT due to its vulnerability to malicious assaults. …”

A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

“…<p dir="ltr">Due to the rapid growth in IT technology, digital data have increased availability, creating novel security threats that need immediate attention. …”

IMPROVING BER PERFORMANCE OF LDPC CODES BASED ON INTERMEDIATE DECODING RESULTS by Alghonaim, Esa

“…The behavior of the BP algorithm is first investigated as a function of number of decoder iterations, and it is shown that typical uncorrected error patterns can be classified into 3 categories: oscillating, nearly-constant, or random-like, with a predominance of oscillating patterns at high Signal-to-Noise (SNR) values. …”
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Energy-Efficient Computation Offloading in Vehicular Edge Cloud Computing by Xin Li (51274)

“…Finally, we propose a low-complexity heuristic resource allocation algorithm based on this novel theoretical discovery. …”

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. …”

Entire hypergeometric approximants for the ground state energy perturbation series of the quartic, sextic and octic anharmonic oscillators by I.S. Elkamash (16810689)

“…In this work, we use appropriate hypergeometric functions to approximate a divergent series ( n! large order growth factor) and strongly-divergent series ( (2n)! …”

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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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. …”

Critical exponents from the weak-coupling, strong-coupling and large-order parametrization of the hypergeometric (k+1Fk) approximants by Abouzeid M. Shalaby (16810695)

“…The algorithm with the new parametrization has been tested using two quantum mechanical problems where one can incorporate the weak-coupling, strong-coupling and large-order information. …”

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

“…Differential expression and gene set enrichment analysis in TNBC revealed enrichment in the cycle and mitosis functional categories in FDPShigh, while ENO1high was associated with numerous functional categories, including cell cycle, glycolysis, and ATP metabolic processes. …”