Detection of Pear Quality Using Hyperspectral Imaging Technology and Machine Learning Analysis by Zishen Zhang, Hong Cheng, Meiyu Chen, Lixin Zhang, Yudou Cheng, Wenjuan Geng, Junfeng Guan

“…In summary, the combination of HSI and machine learning models enabled an efficient, rapid, and non-destructive detection of pear quality and provided a practical value for quality control and the commercial processing of pears.…”
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Image-Based Malicious Network Traffic Detection Framework: Data-Centric Approach by Doo-Seop Choi, Taeguen Kim, Boojoong Kang, Eul Gyu Im

“…This often leads to increased computational overhead and heightened complexity in detection models, potentially degrading overall system performance and efficiency. …”
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Effects of Ageing and Sex on Complexity in the Human Sleep EEG: A Comparison of Three Symbolic Dynamic Analysis Methods by Pinar Deniz Tosun, Derk-Jan Dijk, Raphaelle Winsky-Sommerer, Daniel Abasolo

“…All three SDA techniques distinguished the vigilance states (i.e., wakefulness, REM sleep, NREM sleep, and its sub-stages: stage 1, stage 2, and slow wave sleep). Complexity of the sleep EEG increased with ageing. Sex on the other hand did not affect the complexity values assessed with any of these three SDA methods, even though FFT detected sex differences. …”
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AN ITERATIVE ALGORITHM OF OBJECT DETECTION IN VIDEO SEQUENCE BASED ON HISTOGRAM SPATIAL MEASURES by I. A. Baryskievic

“…The parameters of algorithm are defined in terms of detection efficiency and computational complexity.…”
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Experimental Demonstration of 16-QAM DD-SEFDM With Cascaded BPSK Iterative Detection by Jun Huang, Qi Sui, Zhaohui Li, Fei Ji

“…To simplify the complexity of a spectrally efficient frequency-division multiplexing (SEFDM) system, cascaded binary-phase-shift-keying iterative detection (CBID) is proposed for square <inline-formula> <tex-math notation="LaTeX">$M$</tex-math></inline-formula>-ary quadrature-amplitude-modulation (M-QAM) SEFDM as the first decoding stage, in conjunction with a fixed sphere decoder (FSD). …”
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Automatic detection of foreign object intrusion along railway tracks based on MACENet. by Xichun Chen, Yu Tian, Ming Li, Bin Lv, Shuo Zhang, Zixian Qu, Jianqing Wu, Shiya Cheng

“…Ensuring high accuracy and efficiency in foreign object intrusion detection along railway lines is critical for guaranteeing railway operational safety under limited resource conditions. …”
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Redundancy and conflict detection method for label-based data flow control policy by Rongna XIE, Xiaonan FAN, Suzhe LI, Yuxin HUANG, Guozhen SHI

“…To address the challenge of redundancy and conflict detection in the label-based data flow control mechanism, a label description method based on atomic operations has been proposed.When the label is changed, there is unavoidable redundancy or conflict between the new label and the existing label.How to carry out redundancy and conflict detection is an urgent problem in the label-based data flow control mechanism.To address the above problem, a label description method was proposed based on atomic operation.The object label was generated by the logical combination of multiple atomic tags, and the atomic tag was used to describe the minimum security requirement.The above label description method realized the simplicity and richness of label description.To enhance the detection efficiency and reduce the difficulty of redundancy and conflict detection, a method based on the correlation of sets in labels was introduced.Moreover, based on the detection results of atomic tags and their logical relationships, redundancy and conflict detection of object labels was carried out, further improving the overall detection efficiency.Redundancy and conflict detection of atomic tags was based on the relationships between the operations contained in different atomic tags.If different atomic tags contained the same operation, the detection was performed by analyzing the relationship between subject attributes, environmental attributes, and rule types in the atomic tags.On the other hand, if different atomic tags contained different operations without any relationship between them, there was no redundancy or conflict.If there was a partial order relationship between the operations in the atomic tags, the detection was performed by analyzing the partial order relationship of different operations, and the relationship between subject attribute, environment attribute, and rule types in different atomic tags.The performance of the redundancy and conflict detection algorithm proposed is analyzed theoretically and experimentally, and the influence of the number and complexity of atomic tags on the detection performance is verified through experiments.…”
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An Anomaly Detection Method for Industrial System Cybersecurity Based on GGL-WAVE-CNN by Bing Zou, Ke jun Zhang, Xin Ying Yu, Yu han Jin, Jun Wang, Ling yu Liu

“…Current approaches often struggle to handle complex, unknown topological time series data, thereby necessitating improved anomaly detection accuracy. …”
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Integrating ANN and ANFIS for effective fault detection and location in modern power grid by Yadav Goutam Kumar, Kirar Mukesh Kumar, Gupta S.C., Rajender Jatoth

“…The increasing complexity and demand for reliability in modern power systems necessitate advanced techniques for fault detection, classification, and location. …”
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Intelligent Casting Quality Inspection Method Integrating Anomaly Detection and Semantic Segmentation by Min-Chieh Chen, Shih-Yu Yen, Yue-Feng Lin, Ming-Yi Tsai, Ting-Hsueh Chuang

“…Customized optical path design is often required, especially when conducting internal and external defect inspections, which increases overall operational complexity and reduces inspection efficiency. We developed an automated optical inspection (AOI) system to address these challenges. …”
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Deformation, fracture characteristics and damage constitutive model of soft coal under true triaxial complex stress paths. by Chongyang Jiang, Lianguo Wang, Jiaxing Guo, Shuai Wang

“…Furthermore, based on the experimental results, a damage constitutive model for soft coal is developed that integrates damage mechanics, Weibull statistical distribution theory, and the Mogi-Coulomb criterion to effectively measure microelement strength under true triaxial complex stress paths. Comparing the theoretical model with the experimental curves demonstrates that the proposed damage constitutive model can effectively reflect the deformation strength characteristics of soft coal under true triaxial complex stress paths. …”
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Research on Defect Detection in Lightweight Photovoltaic Cells Using YOLOv8-FSD by Chao Chen, Zhuo Chen, Hao Li, Yawen Wang, Guangzhou Lei, Lingling Wu

“…Given the high computational complexity and poor real-time performance of current photovoltaic cell surface defect detection methods, this study proposes a lightweight model, YOLOv8-FSD, based on YOLOv8. …”
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ITD-YOLO: An Improved YOLO Model for Impurities in Premium Green Tea Detection by Zezhong Ding, Yanfang Li, Bin Hu, Zhiwei Chen, Houzhen Jia, Yali Shi, Xingmin Zhang, Xuesong Zhu, Wenjie Feng, Chunwang Dong

“…To solve this technical problem in the industry, this article proposes a lightweight algorithm for detecting and sorting impurities in premium green tea in order to improve sorting efficiency and reduce labor intensity. …”
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Outlier detection algorithm based on fast density peak clustering outlier factor by Zhongping ZHANG, Sen LI, Weixiong LIU, Shuxia LIU

“…For the problem that peak density clustering algorithm requires human set parameters and high time complexity, an outlier detection algorithm based on fast density peak clustering outlier factor was proposed.Firstly, k nearest neighbors algorithm was used to replace the density peak of density estimate, which adopted the KD-Tree index data structure calculation of k close neighbors of data objects, and then the way of the product of density and distance was adopted to automatic selection of clustering centers.In addition, the centripetal relative distance and fast density peak clustering outliers were defined to describe the degree of outliers of data objects.Experiments on artificial data sets and real data sets were carried out to verify the algorithm, and compared with some classical and novel algorithms.The validity and time efficiency of the proposed algorithm are verified.…”
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Outlier detection algorithm based on fast density peak clustering outlier factor by Zhongping ZHANG, Sen LI, Weixiong LIU, Shuxia LIU

“…For the problem that peak density clustering algorithm requires human set parameters and high time complexity, an outlier detection algorithm based on fast density peak clustering outlier factor was proposed.Firstly, k nearest neighbors algorithm was used to replace the density peak of density estimate, which adopted the KD-Tree index data structure calculation of k close neighbors of data objects, and then the way of the product of density and distance was adopted to automatic selection of clustering centers.In addition, the centripetal relative distance and fast density peak clustering outliers were defined to describe the degree of outliers of data objects.Experiments on artificial data sets and real data sets were carried out to verify the algorithm, and compared with some classical and novel algorithms.The validity and time efficiency of the proposed algorithm are verified.…”
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Multi-Scale Construction Site Fire Detection Algorithm with Integrated Attention Mechanism by Haipeng Sun, Tao Yao

“…To address the issues of large target-scale variations and frequent false detections in construction site fire monitoring, we propose a fire detection algorithm based on an improved YOLOv8 model, achieving real-time and efficient detection of fires on construction sites. …”
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Attachment as a Primary Mechanism in Physician Cognition and Bias During Complex Medical Cases: A Narrative Review by Rein C

“…Carrie Rein Department of Clinical Research and Leadership, the George Washington University School of Medicine and Health Sciences, Washington, DC, USACorrespondence: Carrie Rein, Email crein15@gwmail.gwu.eduIntroduction: In recent decades, improvements in diagnostic accuracy in medical cases have been minimal despite rapid advancements in technology. Moreover, in complex cases, diagnostic accuracy remains a significant challenge, often reflecting practices from the 18th and 19th centuries. …”
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Forecast of the morphology and occurrence conditions of complex chromite ore bodies (on example of Labogeyskoe-2 site, Polar Urals) by T. P. Morozova, E. V. Karelina, V. E. Markov

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Dynamic Aerial Small Target Detection Algorithm Based on Compound Zoom Scaling by Jiang Yuan, Zhu Gaofeng, Zhu Fenghua, Xiong Gang

“…Experiments conducted on the VisDrone2019 UAV aerial ima-gery dataset demonstrate that the proposed algorithm improves mAP by 2.1%, reduces FLOPs by 32.5%, and decreases computational complexity, resulting in superior detection performance.…”
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Towards real-time interest point detection and description for mobile and robotic devices by Patrick Rowsome, Muhammad Adil Raja, R. Muhammad Atif Azad

“…This paper demonstrates how techniques, developed for other CNN use cases, can be integrated into interest point detection and description systems to compress their network size and reduce the computational complexity; this reduces the barrier to their uptake in computationally challenged environments. …”
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