Efficient Approach for Brain Tumor Detection and Classification Using Fuzzy Thresholding and Deep Learning Algorithms by Nashaat M. Hussain Hassan, Wadii Boulila

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BED-YOLO: An Enhanced YOLOv10n-Based Tomato Leaf Disease Detection Algorithm by Qing Wang, Ning Yan, Yasen Qin, Xuedong Zhang, Xu Li

“…The experimental results demonstrated that the improved BED-YOLO model achieved significant performance improvements compared to the original model. …”
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Research on anomaly detection algorithm based on sparse variational autoencoder using spike and slab prior by Huahua CHEN, Zhe CHEN

“…Anomaly detection remains to be an essential and extensive research branch in data mining due to its widespread use in a wide range of applications.It helps researchers to obtain vital information and make better decisions about data by detecting abnormal data.Considering that sparse coding can get more powerful features and improve the performance of other tasks, an anomaly detection model based on sparse variational autoencoder was proposed.Firstly, the discrete mixed modelspike and slab distribution was used as the prior of variational autoencoder, simulated the sparsity of the space where the hidden variables were located, and obtained the sparse representation of data characteristics.Secondly, combined with the deep support vector network, the feature space was compressed, and the optimal hypersphere was found to discriminate normal data and abnormal data.And then, the abnormal fraction of the data was measured by the Euclidean distance from the data feature to the center of the hypersphere, and then the abnormal detection was carried out.Finally, the algorithm was evaluated on the benchmark datasets MNIST and Fashion-MNIST, and the experimental results show that the proposed algorithm achieves better effects than the state-of-the-art methods.…”
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Research on anomaly detection algorithm based on sparse variational autoencoder using spike and slab prior by Huahua CHEN, Zhe CHEN

“…Anomaly detection remains to be an essential and extensive research branch in data mining due to its widespread use in a wide range of applications.It helps researchers to obtain vital information and make better decisions about data by detecting abnormal data.Considering that sparse coding can get more powerful features and improve the performance of other tasks, an anomaly detection model based on sparse variational autoencoder was proposed.Firstly, the discrete mixed modelspike and slab distribution was used as the prior of variational autoencoder, simulated the sparsity of the space where the hidden variables were located, and obtained the sparse representation of data characteristics.Secondly, combined with the deep support vector network, the feature space was compressed, and the optimal hypersphere was found to discriminate normal data and abnormal data.And then, the abnormal fraction of the data was measured by the Euclidean distance from the data feature to the center of the hypersphere, and then the abnormal detection was carried out.Finally, the algorithm was evaluated on the benchmark datasets MNIST and Fashion-MNIST, and the experimental results show that the proposed algorithm achieves better effects than the state-of-the-art methods.…”
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Identification of Low‐Value Defects in Infrared Images of Porcelain Insulators Based on STCE‐YOLO Algorithm by Shaotong Pei, Weiqi Wang, Chenlong Hu, Keyu Li, Haichao Sun, Mianxiao Wu, Bo Lan

“…To solve the above problems, this paper optimizes the small target and complex environment problems in the low‐value defect recognition of insulator infrared images, and proposes the STCE‐YOLO algorithm: based on YOLOv8, the deformable large kernel attention is used to improve the detection ability of small targets; then the cross‐modal contextual feature module is applied to Integrate the features of different scales to reduce the computation of the model. …”
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A Heuristic Optical Flow Scheduling Algorithm for Low-Delay Vehicular Visible Light Communication by Zhengying Cai, Shumeng Lei, Jingyi Li, Chen Yu, Junyu Liu, Guoqiang Gong

“…In response to this problem, we propose a heuristic optical flow scheduling algorithm. First, the optical flow scheduling problem of VVLC is built as a multi-objective optimization model considering the makespan, delay, schedulable ratio, and bandwidth utilization with non-conflict constraints. …”
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LG-YOLOv8: A Lightweight Safety Helmet Detection Algorithm Combined with Feature Enhancement by Zhipeng Fan, Yayun Wu, Wei Liu, Ming Chen, Zeguo Qiu

“…Evaluations on the SWHD dataset confirm the effectiveness of the LG-YOLOv8 algorithm. Compared to the original YOLOv8-n algorithm, our approach achieves a mean Average Precision (mAP) of 94.1%, a 59.8% reduction in parameters, a 54.3% decrease in FLOPs, a 44.2% increase in FPS, and a 2.7 MB compression of the model size. …”
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Improving the System of Mandatory Requirements to Business under the Digital Transformation of Economy by S. A. Minich

“…Objective: to elaborate scientifically substantiated proposals for improving the system of mandatory requirements in the sphere of business and other economic activity under formation of digital economy, taking into account the foreign experience of eliminating barriers for business and the available practice of legislation optimization in this sphere.Methods: the research methodological basis consists of traditional general and specific methods of scientific cognition: dialectical, formal-logical, historical-comparative, systematic, terminological, general logic methods (analysis, synthesis, generalization, induction, deduction, etc.), as well as special methods: historical-legal, formal-legal, and method of comparative jurisprudence.Results: the author investigated and systematized theoretical approaches and experience of improving the system of mandatory requirements in foreign countries and the Russian Federation; the possibilities of introducing the most successful innovative legal instruments and practices to improve the regulation of economic relations were considered. …”
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Mechanism of Immune System Based Multipath Fault Tolerant Routing Algorithm for Wireless Sensor Networks by Hongbing Li, Qingyu Xiong, Weiren Shi, Liwan Chen, Xin Shi, Qiang Chen

“…Mechanism of immune system is applied to do the variation on the initial antibody population, namely, the multiple disjoint paths, to establish the final optimal transmission paths. Mathematical model is established to do the theoretical analysis on the performance of the algorithm. …”
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Mobile Robot Path Planning Based on Fused Multi-Strategy White Shark Optimisation Algorithm by Dazhang You, Junjie Yu, Zhiyuan Jia, Yepeng Zhang, Zhiyuan Yang

“…A novel multi-strategy fusion white shark optimization algorithm is proposed, focusing on actual scenario requirements, to provide optimal solutions for mobile robot path planning. …”
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Set-Based Differential Evolution Algorithm Based on Guided Local Exploration for Automated Process Discovery by Si-Yuan Jing

“…Thirdly, a fine-grained evaluation technique is designed to assign score to each node in a process model, which is employed to guide the local exploration and improve the efficiency of the algorithm. …”
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Post-Quantum Cryptographic Frameworks for Internet of Things (IoT) and Internet of Medical Things (IoMT) Authentication Systems by Thomas L Barna, Samson Isaac, Christopher Habu, Saratu Habu, Abimbola A Joseph

“…This work contributes three key advancements: (1) an optimized NTRU implementation for medical IoT devices, (2) a novel integration of metaheuristic optimization with post-quantum cryptography, and (3) comprehensive validation across IoMT device classes. …”
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Investigating the Performance of Open-Vocabulary Classification Algorithms for Pathway and Surface Material Detection in Urban Environments by Kauê de Moraes Vestena, Silvana Phillipi Camboim, Maria Antonia Brovelli, Daniel Rodrigues dos Santos

“…Our approach uses large language models (LLMs) to improve the accuracy of classifying different pavement types. …”
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A cooperative dynamic target search approach for multi-UAV systems utilizing the MAPPO algorithm by Peiyan Zhang, Guodong Li

“…In response to these issues, this study proposes an improved multi-agent proximal policy optimization algorithm (AS-MAPPO). …”
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Stability Analysis and Construction Parameter Optimization of Tunnels in the Fractured Zone of Faults by Banma Huang, Haibo Chen, Chenglong Duan, Wenhu Li

“…Finally, the actual blasting effect of tunnel construction is tested and the optimization algorithm model of tunnel fault drilling and blasting parameters is established. …”
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A self-learning method with domain knowledge integration for intelligent welding sequence planning by Weidong Shen, Xuewen Wang, Juanli Li, Yong Wang, Xiaojun Qiao

“…To improve the interpretability of the results, domain knowledge was integrated into the construction and training processes of a self-learning model. …”
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Wood Panel Defect Detection Based on Improved YOLOv8n by Rui Li, Shilu Zhong, Xuemei Yang

“…However, the accuracy and convergence speed of existing defect detection techniques still require improvement. In this paper, an improved algorithm based on YOLOv8n was designed for accurate detection of wood panel defects. …”
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Efficient Optical Spatial First-Order Differentiator Based on Graphene-Based Metalines and Evolutionary Algorithms by Tian Zhang, Jia'nan Xie, Yihang Dan, Shuai Yu, Xu Han, Jian Dai, Kun Xu

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Location privacy protection method based on lightweight K-anonymity incremental nearest neighbor algorithm by Saite CHEN, Weihai LI, Yuanzhi YAO, Nenghai YU

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Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings. by Ioana Duta, Symon M Kariuki, Anthony K Ngugi, Angelina Kakooza Mwesige, Honorati Masanja, Daniel M Mwanga, Seth Owusu-Agyei, Ryan Wagner, J Helen Cross, Josemir W Sander, Charles R Newton, Arjune Sen, Gabriel Davis Jones

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