Real-Time Stringing Detection for Additive Manufacturing by Oumaima Charia, Hayat Rajani, Inés Ferrer Real, Miquel Domingo-Espin, Nuno Gracias

“…To address data scarcity in training machine learning models, we also release a new dataset and improve upon the results achieved by the Obico server model, one of the most prominent tools for stringing detection. Our contributions aim to enhance process reliability, reduce material wastage, and optimize time efficiency in AM workflows.…”
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Pupil Detection Algorithm Based on ViM by Yu Zhang, Changyuan Wang, Pengbo Wang, Pengxiang Xue

“…This algorithm introduces weighted feature fusion, aiming to enable the model to adaptively learn the contribution of different feature patches to the pupil detection results; combines ViM with the MSA (multi-head self-attention) mechanism), aiming to integrate global features and improve the accuracy and robustness of pupil detection; and uses FFT (Fast Fourier Transform) to convert the time-domain vector outer product in MSA into a frequency–domain dot product, in order to reduce the computational complexity of the model and improve the detection efficiency of the model. …”
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A lightweight mechanism for vision-transformer-based object detection by Yanming Ye, Qiang Sun, Kailong Cheng, Xingfa Shen, Dongjing Wang

“…It struggles to extract fine-grained details of small and medium-sized objects from low-resolution features, and its computational complexity increases significantly with the input scale, thereby constraining real-time detection efficiency. …”
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Improved YOLOv10n model for enhanced cotton recognition in complex environments by Yutao Gong, Wenwen Ding, Nenghui Huang, Tao Li, Juntao Zhou

“…Currently, target detection models struggle with multi - category cotton recognition in complex farmland environments. …”
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Dataset for Single Character Detection in Dongba Manuscripts by Yuqi Ma, Yongbo Li, Guang Long, Ruiyuan Li, Fengyuan Hu, Chenjun Xu, Yueran Wang, Maoling Peng, Xiaoliang Li, Shanxiong Chen

“…Through automated Dongba script detection technology, experts can efficiently extract precise text data from many manuscripts, providing essential support for the subsequent translation of Dongba script and constructing a corpus. …”
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Using the model of closed-loop economy in certain branches of the agro-industrial complex by I. V. Petrunina, N. A. Gorbunova

“…The paper examines several aspects of using elements of closed-loop economy in certain branches of the agro-industrial complex, including the meat industry. A special attention in this work is given to the introduction of modern technologies and equipment for efficient processing of waste from crop husbandry, animal husbandry and meat production to include it into the economic turnover. …”
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ORD-YOLO: A Ripeness Recognition Method for Citrus Fruits in Complex Environments by Zhaobo Huang, Xianhui Li, Shitong Fan, Yang Liu, Huan Zou, Xiangchun He, Shuai Xu, Jianghua Zhao, Wenfeng Li

“…Furthermore, the model enables real-time, non-destructive detection. When deployed on harvesting robots, it can substantially increase picking efficiency and reduce post-maturity fruit rot due to delayed harvesting. …”
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Development of Model for Traffic Flows on Urban Street and Road Network by D. V. Kapskiy, D. V. Navoy, P. A. Pegin

“…The algorithm has been already implemented as part of the current automated traffic management system in the city of Minsk and it has shown its efficiency. However this efficiency can be increased if it is used together with an algorithm for searching maximum volume of motion in a cycle with a distributed intensity pulse. …”
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Research on the Tunable Optical Alignment Technology of Lidar Under Complex Working Conditions by Jianfeng Chen, Jie Ji, Chenbo Xie, Yingjian Wang

“…However, maintaining optical path stability in complex environments poses significant challenges, especially regarding adaptability and cost efficiency. …”
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Balancing Complexity and Performance in Convolutional Neural Network Models for QUIC Traffic Classification by Giovanni Pettorru, Matteo Flumini, Marco Martalò

“…This is particularly relevant in the Internet of Things (IoT), where resource-constrained platforms at the edge must manage tasks like traffic analysis and threat detection. In this context, balancing classification accuracy with computational efficiency is key to enabling practical, real-world deployments. …”
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Complex Dynamics and Intelligent Control: Advances, Challenges, and Applications in Mining and Industrial Processes by Luis Rojas, Víctor Yepes, José Garcia

“…Complex dynamics and nonlinear systems play a critical role in industrial processes, where complex interactions, high uncertainty, and external disturbances can significantly impact efficiency, stability, and safety. …”
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Research Progress and Prospect of Multi-robot Collaborative SLAM in Complex Agricultural Scenarios by MA Nan, CAO Shanshan, BAI Tao, KONG Fantao, SUN Wei

“…These capabilities are particularly valuable for completing complex tasks efficiently. However, deploying multi-robot SLAM in agricultural settings presents significant challenges. …”
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Parameter Adaptive LCD Screen Defect Detection Framework by LIU Wang, SHAO Huili, HE Yongjun, XIE Yining, CHEN Deyun

“…It is necessary to detect defects in the production process of LCD screens for quality improvements Manual detection brings a heavy workload and low accuracy Therefore, an efficient and accurate automatic detection method is urgently needed To this end, this paper proposes a new defect detection framework, which mainly includes screen area extraction, preprocessing, threshold segmentation and defect selection By adaptive adjustment of parameters, the detection method can adapt to various complex situations In order to eliminate the influence of illumination changes, the defect region is segmented by automatic parameter adjustment in the threshold segmentation First, the maximum grayscale value of the image is calculated, and then the fixed parameters and the coefficient of the defect image are determined according to the nodefect image, and finally the maximum value which was selected as the minimum threshold of the threshold segmentation from the fixed parameters and the product of the maximum grayscale value and the coefficient In addition, in order to solve the problem that the brightness difference of the images captured by lowresolution cameras is too small to detect defects in the saturation condition, selfadaptive adjustment of exposure parameters was used to collect images to process different parts of images with large difference in light and shade Experiments show that the method can achieve high performance and efficiency in detecting defects such as points, lines, Mura, saturation…”
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Cellular porosity in dentin exhibits complex network characteristics with spatio-temporal fluctuations. by Lucas Chatelain, Nicolas Tremblay, Elsa Vennat, Elisabeth Dursun, David Rousseau, Aurélien Gourrier

“…Residual errors were classified in 4 topological classes related to fluorescence staining and confocal detection efficiency, instrumental resolution and image processing. …”
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Optimizing of Universal DEA Model with Multi-Level Integration under Neutrosophic Environment by Hamiden Abd El- Wahed Khalifa, Loay Alkhalifa, Sultan S. Alodhaibi, Basma E. El- Demerdash

“…The proposed model seeks to identify inefficient organizations so as to improve specifically on those areas to have a much better outcome in overall efficiency. This provides decision-makers with very strong and versatile options for efficient measures, even in the context of heterogeneous and imprecise data. …”
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Linear viscoelastic models from creep and complex modulus testing in soil-emulsion by Paulo Mateus Barros Rodrigues, Silvrano Adonias Dantas Neto, Lucas Feitosa de Albuquerque Lima Babadopulos, Jorge Luiz Oliveira Lucas Júnior

“…Test samples were then exposed to air until a constant density loss was detected, followed by conducting complex modulus tests at thirty different temperature-frequency pairs. …”
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Accurate depth of anesthesia monitoring based on EEG signal complexity and frequency features by Tianning Li, Yi Huang, Peng Wen, Yan Li

“…A random forest regression model was employed to estimate anesthetic states, and an unsupervised learning method using the Hurst exponent algorithm and hierarchical clustering was introduced to detect transitions between anesthesia states. The method was tested on two independent datasets (UniSQ and VitalDB), achieving an average Pearson correlation coefficient of 0.86 and 0.82, respectively. …”
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A framework for complex signal processing via synthetic biological operational amplifiers by Wenjun Cao, Lili Liu, Qingxu Sun, Yang Shan, Ye Chen

“…Abstract Engineering genetic circuits to process complex biological signals remains a significant challenge due to non-orthogonal signal responses that limit precise control. …”
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Development of Impact Factors Reverse Analysis Method for Software Complexes’ Support Automation by Andrii Pukach, Vasyl Teslyuk, Nataliia Lysa, Liubomyr Sikora

“…This research represents a corresponding and developed specialized impact factors reverse analysis method for software complexes’ support automation; it is intended for the analysis of impact factors affecting the supported software’s (or processes of its comprehensive support) subjective perception results, as one of the constituent tasks of the more complex problem of software complexes’ support automation. …”
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Improved YOLO for long range detection of small drones by Sicheng Zhou, Lei Yang, Huiting Liu, Chongqin Zhou, Jiacheng Liu, Yang Wang, Shuai Zhao, Keyi Wang

“…The model demonstrates strong cross-dataset generalization, balancing accuracy and efficiency. These findings contribute to advancements in small drone target detection.…”
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