Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. A novel MH optimization algorithm, called arithmetic optimization algorithm (AOA), was proposed to address complex optimization tasks. …”

Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control by Abu Zitar, Raed

“…The proposed algorithm (Ls-AOA) was tested against unimodal and multimodal benchmark functions and demonstrated better capability comparatively using other efficient metaheuristic algorithms reported in the literature. …”

Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images by Abu Zitar, Raed

“…The leading mathematical arithmetic operators' distributional nature is used by the AOA method. The picture histogram was used to construct the candidate solutions in the modified algorithms, which were then updated according to the algorithm's features. …”
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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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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. …”

Vibration suppression in a cantilever beam using a string-type vibration absorber by Issa, Jimmy S.

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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)! …”

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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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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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. …”