CFD Simulations of Basic Stepped-Hull Configurations in Planing Regime Using Star-CCM+ Software by Konstantin I. Matveev

“…Due to the large number of possible geometrical variations for stepped hulls, numerical simulations can potentially make the process of designing such hulls more effective. In this study, the computational fluid dynamics software Star-CCM+ (version 15.04.008) is applied to comparing the numerical results with the experimental hydrodynamic data available for prismatic hulls with one and two steps. …”
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Parallel Cross-section Recognition of Geometrical Features for Selected Machine Parts by Marcin Gołaszewski, Marcin Królikowski, Bartosz Powałka

“…The proposed algorithms are optimized to increase efficiency of the process. Initial identification parameters are selected with respect to defined criteria, e.g. identification accuracy, computing power and scanning accuracy. …”
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Tailhook Recognition for Carrier-Based Aircraft Based on YOLO with Bi-Level Routing Attention by Aiguo Lu, Pandi Liu, Jie Yang, Zhe Li, Ke Wang

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Critical biomarkers for responsive deep brain stimulation and responsive focal cortex stimulation in epilepsy field by Zhikai Yu, Binghao Yang, Penghu Wei, Hang Xu, Yongzhi Shan, Xiaotong Fan, Huaqiang Zhang, Changming Wang, Jingjing Wang, Shan Yu, Guoguang Zhao

“…The Linear Discriminant Analysis model demonstrates the highest accuracy among the three basic machine learning models, whereas the Naive Bayesian model necessitates the least amount of computational and storage space. The set of DFA exponents is employed as an intermediary variable in the machine learning process. …”
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Cooperative inference analysis based on DNN convolutional kernel partitioning by Jialin ZHI, Yinglei TENG, Xinyang ZHANG, Tao NIU, Mei SONG

“…With the popularity of intelligent chip in the application of edge terminal devices, a large number of AI applications will be deployed on the edge of networks closer to data sources in the future.The method based on DNN partition can realize deep learning model training and deployment on resource-constrained terminal devices, and solve the bottleneck problem of edge AI computing ability.Thekernel based partition method (KPM) was proposed as a new scheme on the basis of traditional workload based partition method (WPM).The quantitative analysis of inference performance was carried out from three aspects of computation FLOPS, memory consumption and communication cost respectively, and the qualitative analysis of the above two schemes was carried out from the perspective of flexibility, robustness and privacy of inference process.Finally, a software and hardware experimental platform was built, and AlexNet and VGG11 networks were implemented using PyTorch to further verify the performance advantages of the proposed scheme in terms of delay and energy consumption.It was concluded that, compared with the WPM scheme, the KPM scheme had better DNN reasoning acceleration effect in large-scale computing scenarios.And it has lower memory usage and energy consumption.…”
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Cooperative inference analysis based on DNN convolutional kernel partitioning by Jialin ZHI, Yinglei TENG, Xinyang ZHANG, Tao NIU, Mei SONG

“…With the popularity of intelligent chip in the application of edge terminal devices, a large number of AI applications will be deployed on the edge of networks closer to data sources in the future.The method based on DNN partition can realize deep learning model training and deployment on resource-constrained terminal devices, and solve the bottleneck problem of edge AI computing ability.Thekernel based partition method (KPM) was proposed as a new scheme on the basis of traditional workload based partition method (WPM).The quantitative analysis of inference performance was carried out from three aspects of computation FLOPS, memory consumption and communication cost respectively, and the qualitative analysis of the above two schemes was carried out from the perspective of flexibility, robustness and privacy of inference process.Finally, a software and hardware experimental platform was built, and AlexNet and VGG11 networks were implemented using PyTorch to further verify the performance advantages of the proposed scheme in terms of delay and energy consumption.It was concluded that, compared with the WPM scheme, the KPM scheme had better DNN reasoning acceleration effect in large-scale computing scenarios.And it has lower memory usage and energy consumption.…”
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On Risk Assessment for Out-of-Distribution Detection by Anton Vasiliuk

“…Finally, an analysis of popular computer vision benchmarks reveals that ID errors often dominate overall risk, highlighting the importance of strong ID performance as a foundation for effective OOD detection. …”
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METHODS OF RADIOLOGICAL IMAGING IN THE DIAGNOSIS OF SPACE-OCCUPYING LESIONS OF THE ADRENAL GLANDS (LITERATURE REVIEW) by Liliya A. Shingareeva, Denis A. Baikov

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Internal flow characteristics of axial flow absorbers by WANG Hao-yu, LIU Ying-shu, WU Yi-min, ZHENG Xin-gang

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Towards an Effective Use of Audio Conferencing in Distance Language Courses by Regine Hampel, Mirjam Hauck

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A Sizer model for cell differentiation in Arabidopsis thaliana root growth by Irina Pavelescu, Josep Vilarrasa‐Blasi, Ainoa Planas‐Riverola, Mary‐Paz González‐García, Ana I Caño‐Delgado, Marta Ibañes

“…Abstract Plant roots grow due to cell division in the meristem and subsequent cell elongation and differentiation, a tightly coordinated process that ensures growth and adaptation to the changing environment. …”
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A Method for Automatically Locating Defects in CCTV Inspection Data of Sewer Pipes by Jun Tang, Jisheng Xia, Zhiqiang Xie, Zhaoyong Li, Yuting Zhang

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TOLD LIKE IT IS! AN EVALUATION OF AN INTEGRATED ORAL DEVELOPMENT PILOT PROJECT by David Barr, Jonathan Leakey, Alexandre Ranchoux

“…Much established pedagogical and CALL (computer-assisted language learning) research advocates an integrated constructivist approach to the use of technology in language learning. …”
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Gripping Success Metric for Robotic Fruit Harvesting by Dasom Seo, Il-Seok Oh

“…Recently, computer vision methods have been widely applied to agricultural tasks, such as robotic harvesting. …”
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Lightweight image super-resolution network based on muti-domain information enhancement by KOU Qiqi, LIU Gui, JIANG He, CHEN Liangliang, CHENG Deqiang

“…Aiming to solve the problems that the reconstruction capability of single-domain features was limited and deep convolutional neural networks used in existing single-image super-resolution reconstruction tasks were difficult to deploy on mobile terminals due to the large number of parameters and high computational requirements, a lightweight image super-resolution network based on multi-domain information enhancement was proposed. …”
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Toward Annotation, Visualization, and Reproducible Archiving of Human–Human Dialog Video Recording Applications by Verena Schreyer, Marco Xaver Bornschlegl, Matthias Hemmje

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Semi-Automatic 3D Modeling of Rooftop Types from Aerial Photos by Arsa Fa'iz Nursyahrial, Hanif Ilmawan

“…This semi-automatic method used Computer Generated Architecture (CGA) rules that contained commands to create objects based on their input. …”
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From text to traits: exploring the role of large language models in plant breeding by Mohsen Yoosefzadeh-Najafabadi

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A Novel Framework for Whole-Slide Pathological Image Classification Based on the Cascaded Attention Mechanism by Dehua Liu, Bin Hu

“…Deep learning, particularly in computer vision, offers significant potential to mitigate these challenges. …”
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Infrared Detection of Substation Objects Using the Visible Light Spectrum by Andreas Anael Pereira Gomes, Leandra Ulbricht, Francisco Ganacim, Leonardo Göbel Fernandes, Anselmo Pombeiro, Nara Bobko, Eduardo Félix Ribeiro Romaneli

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