Intelligent intrusion detection system based on crowd search optimization for attack classification in network security by Chetan Gupta, Amit Kumar, Neelesh Kumar Jain

“…In this study, the various performance matrix parameters have been evaluated in terms of all classifiers along with the proposed model. …”
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Optimized Time-domain Feature Extraction for Early Onset Diagnosis of Parkinson Disease From EEG Signals by Delshad Ghavami, Moein Radman, Ali Chaibakhsh

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Analysis of Leakage Inductance Effect and Loss Calculation of DAB Using Single-Phase Shift Modulation Scheme by T. Deepti, K. Deepa, Albert Alexander Stonier, Geno Peter, A. Anoop, D. Ferlin Deva Shahila, Vivekananda Ganji, Arya Jha

“…This paper introduces an analytical methodology for evaluating power losses and energy efficiency in a single-phase DAB. …”
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Predicting retracted research: a dataset and machine learning approaches by Aaron H. A. Fletcher, Mark Stevenson

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ChaMTeC: CHAnnel Mixing and TEmporal Convolution Network for Time-Series Anomaly Detection by Ibrahim Delibasoglu, Deniz Balta, Musa Balta

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TVGeAN: Tensor Visibility Graph-Enhanced Attention Network for Versatile Multivariant Time Series Learning Tasks by Mohammed Baz

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Copper Oxide-Nickel oxide nanocomposites synthesized via Allium cepa peel extract for photocatalytic degradation of methylene blue by Gamachu Mulatu Mamo, Shibiru Yadeta Ejeta

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Photoprotective Properties of Natural Pulvinic Acid Derivatives toward Ultraviolet-Induced Damages by Mehmet Varol

“…Due to the lack of literature about photo-protective features of pulvinic acid derivatives, their cosmetic potentials for skin protection were evaluated in silico, for the first time. Computational chemistry, biology and pharmacology platforms such as Gaussian, GAMESS, PASS, PaDEL-DDPredictor and VEGA QSAR platforms were employed to determine the activities of pulvinic acid derivatives. …”
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An analytical study of active earth pressure in cohesive soil considering interlayer shear stress. by Qizhuo Liu, Tianci Zhong, Daocai Li, Yuanyuan Duan

“…The efficacy of this solution was evaluated by comparing it with the Rankine solution, other existing analytical solutions, and outcomes from standard model tests. …”
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A novel approach for predicting microbe-disease associations by bi-random walk on the heterogeneous network. by Shuai Zou, Jingpu Zhang, Zuping Zhang

“…In conclusion, our method can be considered as an effective computational model for predicting novel microbe-disease associations.…”
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Simulating X-ray beam energy and detector signal processing of an industrial CT using implicit neural representations by Edwin Blum, Moritz Burmeister, Florian Stamer, Gisela Lanza

“…Current simulation approaches, often referred to as virtual computed tomography (vCT), predominantly rely on analytical models. …”
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Simple Calibration of Three-Axis Accelerometers with Freely Rotating Vertical Bench by Federico Pedersini

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Equivalence of Informations Characterizes Bregman Divergences by Philip S. Chodrow

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A new low-rank adaptation method for brain structure and metastasis segmentation via decoupled principal weight direction and magnitude by Hancan Zhu, Hongxia Yang, Yaqing Wang, Keli Hu, Guanghua He, Jia Zhou, Zhong Li, Alzheimer’s Disease Neuroimaging Initiative

“…PDoRA minimizes the reliance on extensive data annotation and computational resources by decomposing model weights into principal and residual weights. …”
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Enhancing Road Scene Segmentation With an Optimized DeepLabV3+ by Zhe Ren, Libao Wang, Tianming Song, Yihang Li, Jian Zhang, Fengfeng Zhao

“…Finally, a Shuffle Attention mechanism is incorporated to improve the handling of small objects and fine details, such as distant pedestrians or items held by them, enhancing segmentation precision without excessive computational overhead. The method was trained and evaluated on the Cityscapes and CamVid datasets, achieving 84.3% mPA and 41.8 FPS on Cityscapes, and 78.1% mPA and 30.2 FPS on CamVid. …”
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X-FASNet: cross-scale feature-aware with self-attention network for cognitive decline assessment in Alzheimer's disease by Wenhui Chen, Shunwu Xu, Yiran Peng, Yiran Peng, Hong Zhang, Jian Zhang, Huaihao Zheng, Hao Yan, Zhaowen Chen, Zhaowen Chen

“…The progressive nature of cognitive decline requires precise computational methods to detect subtle neuroanatomical changes in prodromal stages. …”
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Data-driven models for significant wave height forecasting: Comparative analysis of machine learning techniques by Ahmet Durap

“…Traditional numerical models for wave prediction are computationally intensive and often lack accuracy, prompting a shift towards data-driven methods. …”
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Colony-YOLO: A Lightweight Micro-Colony Detection Network Based on Improved YOLOv8n by Meihua Wang, Junhui Luo, Kai Lin, Yuankai Chen, Xinpeng Huang, Jiping Liu, Anbang Wang, Deqin Xiao

“…To overcome the problem of inaccurate small-target detection and high computational consumption in mulberry bacterial blight colony detection task, a mulberry bacterial blight colony dataset (MBCD) consisting of 310 images and 23,524 colonies is presented. …”
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Tradeoffs When Building and Running Cohort and Patient-Level Markov Simulation Models by Balázs Nagy, Ahmad Nader Fasseeh, Jonathan D. Campbell, Zoltán Kaló, Kareem Ahmed El-Fass, Rok Hren, Bertalan Németh

“…The choice of health care modeling approaches is driven by trade-offs between various modeling techniques. This study evaluates cohort (CH) versus patient-level (PL) Markov modeling techniques within a cost-effectiveness analysis framework to understand the practical decisions analysts face. …”
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Design, development, and testing of a cassava storage root-cutting robot utilizing a Stewart platform and mask R-CNN for precision agriculture by Thanaporn Singhpoo, Seree Wongpichet, Jetsada Posom, Kanda Runapongsa Saikaew, Arthit Phuphaphud, Poramate Banterng, Mahisorn Wongphati, Khwantri Saengprachatanarug

“…In the third step, the robot was integrated with computer vision technology. The integration achieved a remarkable success rate of 100 %. …”
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