Adaptive temporal compression for reduction of computational complexity in human behavior recognition by Haixin Huang, Yuyao Wang, Mingqi Cai, Ruipeng Wang, Feng Wen, Xiaojie Hu

“…With the advancement of deep learning algorithms and computer hardware, the conventional two-dimensional convolution technique for training video models has been replaced by three-dimensional convolution, which enables the extraction of spatio-temporal features. …”
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Spatial–Spectral Hierarchical Multiscale Transformer-Based Masked Autoencoder for Hyperspectral Image Classification by Haipeng Liu, Zhen Ye, Wen-Shuai Hu, Zhan Cao, Wei Li

“…First, after the spatial–spectral feature embedding with a spatial–spectral feature extraction module, to solve the increased computational complexity caused by filling invisible patches in traditional masked autoencoder (MAE), the grouped window attention module is introduced to process only the visible patches of HSIs during spatial–spectral reconstruction, avoiding unnecessary computations for masked ones. …”
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ENHANCING NETWORK INTRUSION DETECTION USING MACHINE LEARNING AND META-MODELLING FOR IMPROVED CYBER SECURITY PERFORMANCE by Sunita, Pankaj Verma, Nitika, Jaspreet Kaur, Vijay Rana

“…Common parameters such as accuracy, precision, recall, and F1-score were computed on each model to allow for a comparative evaluation. …”
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The algorithnt software program for cakulating the mechanical parameters of multilayer rod by Vytautas Kleiza, Rita Laurikietytė

“…The program is developed for training purposes, so the algorithm used is idealized and not sophisticated but preserving the main features of multilayer structural elements calculation. …”
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Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application by Andrei Velichko, Mehmet Tahir Huyut, Maksim Belyaev, Yuriy Izotov, Dmitry Korzun

“…We propose to use these 11 features and their binary combinations as important biomarkers for ML sensors in the diagnosis of the disease, supporting edge computing on Arduino and cloud IoT service.…”
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2D affine transform parameters by Gaussian elimination with pivoting by Tariq N. Ataiwe, Israa Hatem, Hisham M. Jawad Al Sharaa

“…Geometric transformation is a technique used to define the properties of common features between different images using the same coordinates basis, This method can be effectively used in image processing and computer vision to facilitate the computation process throughout eliminating the need for solving the inverse of the matrix.…”
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Efficient hybrid heuristic adopted deep learning framework for diagnosing breast cancer using thermography images by Ahmad Y. A. Bani Ahmad, Jafar A. Alzubi, Manimaran Vasanthan, Suresh Babu Kondaveeti, J. Shreyas, Thella Preethi Priyanka

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Mathematical modelling with computational fractional order for the unfolding dynamics of the communicable diseases by Mati ur Rahman, Yeliz Karaca, Ravi P. Agarwal, Sergio Adriani David

“…Mathematical models based on computational fractional orders, employed for accurate modelling of complex dynamic systems, can ensure the implementation of various analytical, numerical and computing methods encompassing their applications to emerging and ever-varying real-world problems. …”
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High-Resolution Computed Tomography of Single Breast Cancer Microcalcifications in Vivo by Kazumasa Inoue, Fangbing Liu, Jack Hoppin, Elaine P. Lunsford, Christian Lackas, Jacob Hesterman, Robert E. Lenkinski, Hirofumi Fujii, John V. Frangioni

“…Microcalcification is a hallmark of breast cancer and a key diagnostic feature for mammography. We recently described the first robust animal model of breast cancer microcalcification. …”
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Testing of Technical Indicators of Accumulators by Means of Complex Computer Model of EV by Fedotovs Jurijs, Bunina Inna, Zhiravetska Anastasia, Andrianova Svetlava

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Modeling and Simulations of Retina-Like Three-Dimensional Computational Ghost Imaging by Kaiyu Zhang, Jie Cao, Qun Hao, Fanghua Zhang, Yongchao Feng, Yang Cheng

“…R-3DCGI models are developed, and corresponding simulations are conducted to verify and evaluate the accuracy and features of the R-3DCGI. Results show that the models obtain rotation and scaling invariances and compress redundant information, thereby improving imaging efficiency over the traditional computational ghost imaging. …”
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A Space-Time Plume Algorithm to Represent and Compute Dynamic Places by Brent Dell, May Yuan

“…Point clustering analysis commonly assumes events occur in an empty space and therefore ignores geospatial features where events take place. This research introduces relational density, a novel concept redefining density as relative to the spatial structure of geospatial features rather than an absolute measure. …”
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Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed Tomography by Alexander Hertel, Mustafa Kuru, Johann S. Rink, Florian Haag, Abhinay Vellala, Theano Papavassiliu, Matthias F. Froelich, Stefan O. Schoenberg, Isabelle Ayx

“…<b>Conclusions</b>: Radiomics texture features of the left ventricular myocardium outperformed conventional parameters like EAT density and thickness in differentiating age groups, offering a potential imaging biomarker for myocardial aging. …”
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A Novel SHiP Vector Machine for Network Intrusion Detection by Sowmya T., E. A. Mary Anita

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Edge computing privacy protection method based on blockchain and federated learning by Chen FANG, Yuanbo GUO, Yifeng WANG, Yongjin HU, Jiali MA, Han ZHANG, Yangyang HU

“…Aiming at the needs of edge computing for data privacy, the correctness of calculation results and the auditability of data processing, a privacy protection method for edge computing based on blockchain and federated learning was proposed, which can realize collaborative training with multiple devices at the edge of the network without a trusted environment and special hardware facilities.The blockchain was used to endow the edge computing with features such as tamper-proof and resistance to single-point-of-failure attacks, and the gradient verification and incentive mechanism were incorporated into the consensus protocol to encourage more local devices to honestly contribute computing power and data to the federated learning.For the potential privacy leakage problems caused by sharing model parameters, an adaptive differential privacy mechanism was designed to protect parameter privacy while reducing the impact of noise on the model accuracy, and moments accountant was used to accurately track the privacy loss during the training process.Experimental results show that the proposed method can resist 30% of poisoning attacks, and can achieve privacy protection with high model accuracy, and is suitable for edge computing scenarios that require high level of security and accuracy.…”
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Data-driven discovery and parameter estimation of mathematical models in biological pattern formation. by Hidekazu Hishinuma, Hisako Takigawa-Imamura, Takashi Miura

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Evaluation of the volume and function of the right atrial appendage using computed tomography by Yang Liu, Tong Pan, Xin Tian, Cai-Ying Li

“…Abstract Objective To assess the volume and function of the right atrial appendage (RAA) in patients with sinus rhythm using 256-slice spiral computed tomography (CT) angiography. Methods A total of 60 patients with normal cardiac CT imaging features were enrolled in this retrospective study. …”
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Development and application of distributed computing system in inverse problems of fracture mechanics by Arkady N. Soloviev, Pavel V. Vasiliev, Lyubov A. Podkolzina

“…This simplifies the process of the system deployment, and increases the productivity of the computing process. A finite element model with a large set of parameters is calculated. …”
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Computer Multimedia Art Pattern Creation Based on P-Filling Algorithm by Wenli Lian

“…Experimental results show that, through this production model, users can produce a large number of computer multimedia art patterns with hand-drawn style features through very little interaction and parameter control.…”
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A malware detection method with function parameters encoding and function dependency modeling by Ronghao Hou, Dongjie Liu, Xiaobo Jin, Jian Weng, Guanggang Geng

“…Specifically, we first design a parameter encoder to convert various types of function parameters into feature vectors, and then discretize various parameter features through clustering methods to enhance the representation of API encoding. …”
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