Sunshine duration measurements and predictions in Saharan Algeria region: an improved ensemble learning approach

El-kenawy, El-Sayed M.; Ibrahim, Abdelhameed; Bailek, Nadjem; Bouchouicha, Kada; Hassan, Muhammed A.; Jamei, Mehdi; Al‐Ansari, Nadhir

doi:10.1007/s00704-021-03843-2

Cited by 40 publications

(23 citation statements)

References 46 publications

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“…To train the 256 batch experiments, we utilized 4 NVIDIA Tesla V100 32 GB GPUs in parallel; otherwise, we used 1 NVIDIA Tesla V100 32GB GPU. also, many artificial intelligence applications can be used in real-world problem [46][47][48][49][50].…”

Section: Experimental Settingsmentioning

confidence: 99%

Using BlazePose on Spatial Temporal Graph Convolutional Networks for Action Recognition

Alsawadi¹,

El-kenawy²,

Rio³

2023

Computers, Materials &Amp; Continua

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The ever-growing available visual data (i.e., uploaded videos and pictures by internet users) has attracted the research community's attention in the computer vision field. Therefore, finding efficient solutions to extract knowledge from these sources is imperative. Recently, the BlazePose system has been released for skeleton extraction from images oriented to mobile devices. With this skeleton graph representation in place, a Spatial-Temporal Graph Convolutional Network can be implemented to predict the action. We hypothesize that just by changing the skeleton input data for a different set of joints that offers more information about the action of interest, it is possible to increase the performance of the Spatial-Temporal Graph Convolutional Network for HAR tasks. Hence, in this study, we present the first implementation of the BlazePose skeleton topology upon this architecture for action recognition. Moreover, we propose the Enhanced-BlazePose topology that can achieve better results than its predecessor. Additionally, we propose different skeleton detection thresholds that can improve the accuracy performance even further. We reached a top-1 accuracy performance of 40.1% on the Kinetics dataset. For the NTU-RGB+D dataset, we achieved 87.59% and 92.1% accuracy for Cross-Subject and Cross-View evaluation criteria, respectively.

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Section: Experimental Settingsmentioning

confidence: 99%

Using BlazePose on Spatial Temporal Graph Convolutional Networks for Action Recognition

Alsawadi¹,

El-kenawy²,

Rio³

2023

Computers, Materials &Amp; Continua

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“…It reroutes traffic and drops all packets as it passes through itself. As a result, this type of black-hole attack exclusively targets a network's architecture rather than introducing more fake routing signals into the network [24][25][26][27][28][29][30]. By receiving an instantaneous Route Reply Packet (RREP) packet, the malicious node persuades the entire adjacent node to submit their packets early in active black-hole attacks.…”

Section: Proposed Approachmentioning

confidence: 99%

Dipper Throated Optimization for Detecting Black-Hole Attacks in MANETs

Alkanhel¹,

El-kenawy²,

Abdelhamid³

et al. 2023

Computers, Materials &Amp; Continua

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In terms of security and privacy, mobile ad-hoc network (MANET) continues to be in demand for additional debate and development. As more MANET applications become data-oriented, implementing a secure and reliable data transfer protocol becomes a major concern in the architecture. However, MANET's lack of infrastructure, unpredictable topology, and restricted resources, as well as the lack of a previously permitted trust relationship among connected nodes, contribute to the attack detection burden. A novel detection approach is presented in this paper to classify passive and active black-hole attacks. The proposed approach is based on the dipper throated optimization (DTO) algorithm, which presents a plausible path out of multiple paths for statistics transmission to boost MANETs' quality of service. A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron (DTO-MLP), and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical (LEACH) clustering technique. MLP is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights of minor features. This hybrid method is primarily designed to combat active black-hole assaults. Using the LEACH clustering phase, however, can also detect passive black-hole attacks. The effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested approach. For diverse mobility situations, the results demonstrate 1906 CMC, 2023, vol.74, no.1 up to 97% detection accuracy and faster execution time. Furthermore, the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

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“…Different techniques may be resolved, organized, and called to optimize the problems involving continuous functions [10], [11]. The information about the objective function utilized and used throughout the optimization process depends on one technique of optimization classification.…”

Section: Introductionmentioning

confidence: 99%

Novel Meta-Heuristic Algorithm for Feature Selection, Unconstrained Functions and Engineering Problems

et al. 2022

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This paper proposes a Sine Cosine hybrid optimization algorithm with Modified Whale Optimization Algorithm (SCMWOA). The goal is to leverage the strengths of WOA and SCA to solve problems with continuous and binary decision variables. The SCMWOA algorithm is first tested on nineteen datasets from the UCI Machine Learning Repository with different number attributes, instances, and classes for feature selection. It is then employed to solve several benchmark functions and classical engineering case studies. The SCMWOA algorithm is applied for solving constrained optimization problems. The two tested examples are the welded beam design and the tension/compression spring design. The results emphasize that the SCMWOA algorithm outperforms several comparative optimization algorithms and provides better accuracy compared to other algorithms. The statistical analysis tests, including one-way analysis of variance (ANOVA) and Wilcoxon's rank-sum, confirm that the SCMWOA algorithm performs better.

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Sunshine duration measurements and predictions in Saharan Algeria region: an improved ensemble learning approach

Cited by 40 publications

References 46 publications

Using BlazePose on Spatial Temporal Graph Convolutional Networks for Action Recognition

Using BlazePose on Spatial Temporal Graph Convolutional Networks for Action Recognition

Dipper Throated Optimization for Detecting Black-Hole Attacks in MANETs

Novel Meta-Heuristic Algorithm for Feature Selection, Unconstrained Functions and Engineering Problems

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