An efficient and lightweight detection method for stranded elastic needle defects in complex industrial environments using VEE-YOLO by Qiaoqiao Xiong, Qipeng Chen, Saihong Tang, Yiting Li

“…Finally, EIoU Loss replaced CIoU Loss to address bounding box aspect ratio variability and sample imbalance challenges, significantly improving overall detection task performance. The algorithm’s performance was evaluated using a dataset to detect stranded elastic needle defects. …”
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Energy Efficiency of Kernel and User Space Level VPN Solutions in AIoT Networks by ALEKSANDAR JEVREMOVIC, Zona Kostic, Ivan Chorbev, Dragan Perakovic, Andrii Shalaginov, Ivan Cvitic

“…The ability to process data locally using complex algorithms is becoming increasingly important in Internet of Things (IoT) contexts. …”
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A Particle Swarm Optimization Variant with an Inner Variable Learning Strategy by Guohua Wu, Witold Pedrycz, Manhao Ma, Dishan Qiu, Haifeng Li, Jin Liu

“…The resulting novel PSO algorithm with an inner variable learning strategy (PSO-IVL) is particularly efficient for optimizing functions with symmetric variables. …”
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Using Electrocardiogram Signal Features and Heart Rate Variability to Predict Epileptic Attacks by Ying Jiang, Yuan Feng, Danni Lu, Lin Yang, Qun Zhang, Haiyan Yang, Ning Li

“…From a practical point of view, due to the ease of obtaining the heart rate variability signal, the proposed algorithm is more promising than the algorithms that use brain signal processing to predict epilepsy.…”
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Exploring Many-Core Design Templates for FPGAs and ASICs by Ilia Lebedev, Christopher Fletcher, Shaoyi Cheng, James Martin, Austin Doupnik, Daniel Burke, Mingjie Lin, John Wawrzynek

“…The key benefits of this approach are that it (i) allows programmers to express parallelism through an API defined in a high-level programming language, (ii) supports coarse-grained multithreading and fine-grained threading while permitting bit-level resource control, and (iii) reduces the effort required to repurpose the system for different algorithms or different applications. We compare template-driven design to both full-custom and programmable approaches by studying implementations of a compute-bound data-parallel Bayesian graph inference algorithm across several candidate platforms. …”
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Behavior modeling for a new flexure-based mechanism by Hunger Game Search and physics-guided artificial neural network by Hieu Giang Le, Thanh-Phong Dao, Minh Phung Dang, Thao Nguyen-Trang

“…In the field of compliant mechanism modeling, there has been no research interested in applying meta-heuristics optimization algorithms to optimize the weights and biases of the neural network globally. …”
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Tool wear prediction based on XGBoost feature selection combined with PSO-BP network by Zhangwen Lin, Yankun Fan, Jinling Tan, Zhen Li, Peng Yang, Hua Wang, Weiwei Duan

“…Experimental results show that PSO outperforms other algorithms in training the tool wear prediction model, with XGBoost feature selection reducing model construction time by 57.4% and increasing accuracy by 63.57%, demonstrating superior feature selection capabilities over Decision Tree, Random Fores, Adaboost and Extra Trees. …”
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Detection of GRBs and OTs by All-Sky Optical and SID Monitors by R. Hudec, M. Spurny, M. Krizek, P. Pata, R. Slosiar, M. Rerabek, M. Klima

“…The processing and measuring of image data is complicated, and sophisticated deconvolution algorithms are used for image restoration. The second method is the GRB detection based on their ionospheric response.…”
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Soft computing paradigm for climate change adaptation and mitigation in Iran, Pakistan, and Turkey: A systematic review by Muhammad Talha, A. Pouyan Nejadhashemi, Kieron Moller

“…Although some articles utilized multiple techniques, classical ML methods appeared in approximately 37.3 % of the studies, neural network paradigms in about 57.5 %, and optimization or meta-heuristic algorithms in around 5.0 %. Regarding thematic focus, about 33.3 % of the articles addressed water resource management, 22.2 % focused on climate prediction, 11.1 % on land and agriculture, 9 % on ecosystem modeling, and 24.2 % on natural disaster preparedness and response. …”
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Computational Approaches to Facilitate Epitope-Based HLA Matching in Solid Organ Transplantation by Kirsten Geneugelijk, Jeroen Wissing, Dirk Koppenaal, Matthias Niemann, Eric Spierings

“…For these algorithms, high-resolution HLA genotype data of both donor and recipient is required. …”
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A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game Theory by Haigen Min, Yukun Fang, Runmin Wang, Xiaochi Li, Zhigang Xu, Xiangmo Zhao

“…Connected and automated vehicles (CAVs) have attracted much attention of researchers because of its potential to improve both transportation network efficiency and safety through control algorithms and reduce fuel consumption. However, vehicle merging at intersection is one of the main factors that lead to congestion and extra fuel consumption. …”
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Inclined Aerial Image and Satellite Image Matching Based on Edge Curve Direction Angle Features by Hao Wang, Chongyang Liu, Yalin Ding, Chao Sun, Guoqin Yuan, Hongwen Zhang

“…Experiments run on a variety of remote sensing datasets including forests, hills, farmland, and lake scenes demonstrate that the effectiveness of the proposed algorithm shows a great improvement over existing state-of-the-art algorithms.…”
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Coherent Signal DOA Estimation Method Based on Space–Time–Coding Metasurface by Guanchao Chen, Xiaolong Su, Lida He, Dongfang Guan, Zhen Liu

“…Compared to the traditional algorithms, the performance of the proposed algorithm can achieve more accurate DOA estimation under a low SNR.…”
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Solving the fully fuzzy multi-choice linear programming model by Zahra Arami, Maryam Arabameri, Hassan Mishmast Nehi

“…In general, the resulting algorithms are simple and very inexpensive to implement, and they are more efficient than those of previous studies.Originality/Value: In this article, all parameters and coefficients of the problem are triangular fuzzy numbers, and the right side of the problem's constraints are the fuzzy multi-choice parameters. …”
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Description of route dependencies for computer-based railway signalling systems by Michał Grzybowski, Jakub Młyńczak, Lucyna Sokołowska

“…In addition, during research algorithms for automatic verification of conflicting route exclusion correctness have been designed, which allows for reduction of effort required for verification of conflicting route exclusion function. …”
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3D convolutional deep learning for nonlinear estimation of body composition from whole body morphology by Isaac Y. Tian, Jason Liu, Michael C. Wong, Nisa N. Kelly, Yong E. Liu, Andrea K. Garber, Steven B. Heymsfield, Brian Curless, John A. Shepherd

“…Abstract Body composition prediction from 3D optical imagery has previously been studied with linear algorithms. In this study, we present a novel application of deep 3D convolutional graph networks and nonlinear Gaussian process regression for human body shape parameterization and body composition estimation. …”
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Application of edge computing technology in smart grid data security by Zhuo Cheng, Jiangxin Li, Jianjun Zhang, Chen Wang, Hui Wang, Juyin Wu

“…The experimental results indicate that: The total running time required for executing proxy authorization and verification, proxy key generation, signature and decryption algorithms in this scheme is 5.617 ms, with a ciphertext length of 80 Bytes. …”
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Predicting the hub interactome of COVID-19 and oral squamous cell carcinoma: uncovering ALDH-mediated Wnt/β-catenin pathway activation via salivary inflammatory proteins by Pradeep Kumar Yadalam, Deepavalli Arumuganainar, Prabhu Manickam Natarajan, Carlos M. Ardila

“…Hub proteins were identified using Cytoscape and Cytohubba, and machine learning algorithms including naïve Bayes, neural networks, gradient boosting, and random forest were used to predict hub genes. …”
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A High Efficiency Discontinuous Galerkin Method for 3D Ground-Penetrating Radar Simulation by Shuyang Xue, Changchun Yin, Jing Li, Jiao Zhu, Wuyang Liu

“…Numerous numerical simulation algorithms have been developed to improve the computational efficiency of GPR simulations, enabling the modeling of complex structures. …”
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Tracking solid electrolyte interphase dynamics using operando fibre-optic infra-red spectroscopy and multivariate curve regression by Cédric Leau, Yu Wang, Charlotte Gervillié-Mouravieff, Steven T Boles, Xiang-Hua Zhang, Simon Coudray, Catherine Boussard-Plédel, Jean-Marie Tarascon

“…This work employs chalcogenide fibres embedded in negative electrode materials for operando Infra-red Fibre-optic Evanescent Wave Spectroscopy (IR-FEWS), combined with Multivariate Curve Resolution by Alternating Least Squares (MCR-ALS) algorithms for spectra analysis. By establishing molecular fingerprints that can be used to identify reaction products, IR-FEWS combined with MCR-ALS enables improved understanding of SEI evolution during cell formation with notable differences stemming from electrolyte or anode material. …”
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