Rethinking 'Method' in Early Childhood Writing Education by Carina Hermansson, Tomas Saar, Christina Olin-­Scheller

“…The article also discusses how methods on the one hand has an explicit and formalized side, possible to articulate and predict. …”
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A Regularization Method for Landslide Thickness Estimation by Lisa Borgatti, Davide Donati, Liwei Hu, Germana Landi, Fabiana Zama

“…These reconstructions showed good agreement with existing geological interpretations, validating the method’s effectiveness in real-world scenarios.…”
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Synthetic Dataset Generation Method for Object Detection by Ningning Zhou, Tong Li

“…Finally, computer graphics methods are applied to automatically annotate target objects in the synthetic images. …”
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Research on Calibration Method of Laser Camera Sensor by LIU Shiwang, HU Yunqing, LIN Jun

“…Comprehensive analysis of the two sets of data shows that mean square error of the L-M algorithm based on maximum likelihood estimation is reduced by 0.221 4 mm and 0.212 3 mm respectively, and the calibration accuracy of this method is improved effectively.…”
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Optical Cryptanalysis Method Using Wavefront Shaping by Meihua Liao, Dajiang Lu, Wenqi He, Xiang Peng

“…In this paper, a practical optical cryptanalysis method using wavefront shaping is proposed. Considering that the confusion and diffusion of information in the optical cryptosystem are actually caused by scattering effect of random phase mask(s), the proposed method employs a point source function and the feedback-based optimization algorithm, which can obtain an equivalent key of the optical cryptosystem. …”
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Efficient Data Collection Method in Sensor Networks by Keyan Cao, Haoli Liu, Yefan Liu, Gongjie Meng, Si Ji, Gui Li

“…The algorithm is improved on the basis of the random node selection algorithm. This method can effectively avoid the failure of random path node selection and improve the node selection of random path in wireless sensor networks. …”
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Adoption of the Creative Process According to the Immersive Method by Sonja Vuk, Tonka Tacol, Janez Vogrinc

“…The immersive method is a new concept of visual education that is better suited to the needs of students in contemporary post-industrial society. …”
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Separation Method for Installation Eccentricity Error of Workpiece by Guanyao Qiao, Chunyu Zhao, Huihui Miao, Ye Chen

“…Then, numerical simulations were used to verify the effectiveness and reliability of the proposed method, producing a calculation error of less than 0.07% and high consistency (<i>R</i>² > 0.97). …”
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Method for Assessing Numbness and Discomfort in Cyclists’ Hands by Flavia Marrone, Nicole Sanna, Giacomo Zanoni, Neil J. Mansfield, Marco Tarabini

“…This study demonstrates the effectiveness of the proposed method for assessing hand numbness and discomfort in cyclists.…”
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Chromium nanostructured coatings formed by the PVD method by Saydakhmedov Ravshan, Saidakhmedova Gulirano

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Deep Learning Method for Bearing Fault Diagnosis by LIU Xiu, MA Shan-tao, XIE Yi-ning, HE Yong-jun

“…In recent years, deep learning technology has shown great potential in bearing fault diagnosis based on vibration signals.However, in the fault diagnosis method based on deep learning, the traditional single network topology feature extraction has weak discrimination and low noise robustness, and the accuracy of fault diagnosis is not high.In addition, most of the current research methods have a low fault recognition rate in a variable load environment.In response to the above problems, this paper proposes an improved neural network end-to-end fault diagnosis model.The model combines convolutional neural networks (CNN) and the attention long short-term memory (ALSTM) based on the attention mechanism, and uses ALSTM to capture long-distance correlations in time series data , Effectively suppress the high frequency noise in the input signal.At the same time, a multi-scale and attention mechanism is introduced to broaden the range of the convolution kernel to capture high and low frequency features, and highlight the key features of the fault. …”
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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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An Unsupervised Learning Method for Radio Interferometry Deconvolution by Lei Yu, Bin Liu, Cheng-Jin Jin, Ru-Rong Chen, Hong-Wei Xi, Bo Peng

“…Building on this insight, we develop a deep dictionary (realized through a convolutional neural network), which is designed to be multiresolution and overcomplete, to achieve sparse representation and integrate it within the CS framework. The resulting method is a novel, fully interpretable unsupervised learning approach that combines the mathematical rigor of CS with the expressive power of deep neural networks, effectively bridging the gap between deep learning and classical dictionary methods. …”
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Correction Method for Initial Conditions of Underwater Explosion by Zeyu Jin, Wentao Xu, Caiyu Yin, Zhiyang Lei, Xiangshao Kong

“…The results demonstrate that the proposed correction method effectively compensates for load discrepancies caused by inaccuracies in the JWL equation of state parameters. …”
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Visual explanation method for reversible neural networks by Xinying MU, Bingbing SONG, Fanxiao LI, Yisen ZHENG, Wei ZHOU, Yunyun DONG

“…The issue of model explainability has gained significant attention in understanding the vulnerabilities and anonymous decision-making processes inherent in deep neural networks (DNN).While there has been considerable research on explainability for traditional DNN, there is a lack of exploration on the operation mechanism and explainability of reversible neural networks (RevNN).Additionally, the existing explanation methods for traditional DNN are not suitable for RevNN and suffer from issues such as excessive noise and gradient saturation.To address these limitations, a visual explanation method called visual explanation method for reversible neural network (VERN) was proposed for RevNN.VERN leverages the reversible property of RevNN and is based on the class-activation mapping mechanism.The correspondence between the feature map and the input image was explored by VERN, allowing for the mapping of classification weights of regional feature maps to the corresponding regions of the input image.The importance of each region for model decision-making was revealed through this process, which generates a basis for model decision-making.Experimental comparisons with other explanation methods on generalized datasets demonstrate that VERN achieves a more focused visual effect, surpassing suboptimal methods with up to 7.80% improvement in average drop (AD) metrics and up to 6.05% improvement in average increase (AI) metrics in recognition tasks.VERN also exhibits an 82.00% level of localization for the maximum point of the heat value.Furthermore, VERN can be applied to explain traditional DNN and exhibits good scalability, improving the performance of other methods in explaining RevNN.Furthermore, through adversarial attack analysis experiments, it is observed that adversarial attacks alter the decision basis of the model.This is reflected in the misalignment of the model’s attention regions, thereby aiding in the exploration of the operation mechanism of adversarial attacks.…”
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Adaptive channel decoding method for polar codes by YE Maolin, TAN Xiaoqing, XU Liqing, LÜ Shanxiang

“…The successive cancellation list (SCL) decoding algorithm is the most commonly used decoding method for polar codes, but it has high memory and time complexity. …”
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THE METHOD OF TREATMENT OF GENERALIZED CYTOMEGALOVIRUS INFECTION IN INFANTS by S. S. Kochkina, E. P. Sitnikova

“…Evaluation of the effectiveness of treatment of generalized cytomegalovirus infection (CMVI) in infants with a combination of ganciclovir and VIFERON®.Materials and methods. 52 children of the first months of life were treated with generalized CMV. …”
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Index Method of Evaluating the Performance of Economic Activities by A. Sh. Kamaletdinov, A. A. Ksenofontov

“…Economic and statistical methods, system analysis, as well as general scientific methods of comparison were used. …”
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On the Lanczos Method for Computing Some Matrix Functions by Ying Gu, Hari Mohan Srivastava, Xiaolan Liu

“…Numerical results illustrate the effectiveness of our theoretical results.…”
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Method of calculating the pressure on the soil of wheeled tractors by V. Yu. Revenko, A. N. Nazarov, V. I. Skorlyakov

“…Nevertheless, the customer should have access to information about the basic consumer properties and the degree of effectiveness of a particular machine unit. The article provides a computational method for evaluating one of the most important functional indicators of tractors, namely, the level of impact of its wheels on the soil, using limited initial information: technical characteristics and operational documentation of the manufacturer. …”
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