METHOD AND ALGORITHMS OF CALCULATION OF PARAMETERS OF RELIABILITY IN ACCORDANCE WITH MULTIVARIATE DATA by E. M. Farhadzadeh, A. Z. Muradaliyev, T. K. Rafiyeva, S. A. Abdullayeva

“…The methods function with the aid of calculations of indicators of reliability. …”
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IMPLEMENTATION OF THE CASE STUDY METHOD IN DISTANCE LEARNING OF ENTREPRENEURSHIP FUNDAMENTALS by O. R. Chepyuk, A. I. Gorylev

“…The research and experience of application of cases in distance training of entrepreneurship fundamentals have showed the universality and efficiency of this method.…”
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Measurement and Calculation of Leakage Gamma Energy Deposition Spectra from Fe Samples after Interaction of D-T Neutrons by XU Kuozhi1, NIE Yangbo1, 2, , ZHANG Shiyu2, PAN Xinyi1, ZHAO Qi1, DING Yanyan1, REN Jie1, CHEN Hongtao1, SUN Qi1, RUAN Xichao1, 2

“…Therefore, conducting integral experiments on natural iron (natFe) samples is an important research topic. …”
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Malware classification method based on static multiple-feature fusion by Bo-wen SUN, Yan-yi HUANG, Qiao-kun WEN, Bin TIAN, Peng WU, Qi LI

“…In recent years,the amount of the malwares has tended to rise explosively.New malicious samples emerge as variability and polymorphism.By means of polymorphism,shelling and confusion,traditional ways of detecting can be avoided.On the basis of massive malicious samples,a safe and efficient method was designed to classify the mal-wares.Extracting three static features including file byte features,assembly features and PE features,as well as im-proving generalization of the model through feature fusion and ensemble learning,which realized the complementarity between the features and the classifier.The experiments show that the sample achieve a stable F1-socre (93.56%).…”
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Experimental evaluation of nanoclay assisted water based EOR method by Hamid Mohammad Soleimani, Mohammad Taghi Sadeghi

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Multiple Channel Integration Quality Assessment Method Using NARX by Xiaolei Wang, Yingzhao He

“…Through the GRA method and the NARX model, the comprehensive gray relational degree between the test sample and the ideal sample is obtained, and the results are quantified. …”
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Method of anti-confusion texture feature descriptor for malware images by Yashu LIU, Zhihai WANG, Hanbing YAN, Yueran HOU, Yukun LAI

“…It is a new method that uses image processing and machine learning algorithms to classify malware samples in malware visualization field.The texture feature description method has great influence on the result.To solve this problem,a new method was presented that joints global feature of GIST with local features of LBP or dense SIFT in order to construct combinative descriptors of malware gray-scale images.Using those descriptors,the malware classification performance was greatly improved in contrast to traditional method,especially for those samples have higher similarity in the different families,or those have lower similarity in the same family.A lot of experiments show that new method is much more effective and general than traditional method.On the confusing dataset,the accuracy rate of classification has been greatly improved.…”
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Research on unsupervised domain adaptive bearing fault diagnosis method by WU ShengKai, SHAO Xing, WANG CuiXiang, GAO Jun

“…Aiming at the problem that the bearing fault diagnosis algorithm based on deep learning has poor diagnosis performance when the fault samples are lack of labels in different working conditions and real environmentsly, an unsupervised domain adaptive bearing fault diagnosis method was proposed to realize the unsupervised fault diagnosis of bearings under different working conditions. …”
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Soil remediation at coastal plains with the help of DC Resistivity Method by Emin Ulugergerli, Öznur Karaca, Buse Özentürk

“…The electrokinetic remediation method was employed to reduce the salinity level in the soil samples in laboratory conditions. …”
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Evidence Prediction Method Based on Sentence Selection for Legal Documents by Huijie Bai

“…In order to solve the problem that it is difficult to find evidence from a large number of legal document statements and the irrelevant statements in a large number of document sample data will cause a great interference to the prediction results and further improve the accuracy of evidence prediction, this paper puts forward an intelligent evidence criterion prediction method for legal documents based on the comprehensive consideration of legal problems, the nature of statements, and the characteristics of answers. …”
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Semi-Automated PCR Method for Quantitating MDR1 Expression by S. Zhao, U. Consoli, R. Arceci, J. Pfeifer, W.S. Dalton, M. Andreeff

“…There were significant differences between the samples with high and medium P-gp levels comparing the two methods. …”
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New Method for Differentiation between Irradiated and non-Irradiated Potatoes by Mohammed M. Mohammed Rushdy, Hameed O. Abed, Ali M. Merie, Alaa K. Ismaeel, Mustafa G. Farhan, Hassen A. Abed

“…Our laboratory experiments were able to develop a new method for differentiation; this method depends on (volume, viscosity, and color intensity) measurements of potatoes water extract, together with the value of reduced pressure measurements during filtration of the water extract. …”
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Encrypted traffic classification method based on convolutional neural network by Rongna XIE, Zhuhong MA, Zongyu LI, Ye TIAN

“…Aiming at the problems of low accuracy, weak generality, and easy privacy violation of traditional encrypted network traffic classification methods, an encrypted traffic classification method based on convolutional neural network was proposed, which avoided relying on original traffic data and prevented overfitting of specific byte structure of the application.According to the data packet size and arrival time information of network traffic, a method to convert the original traffic into a two-dimensional picture was designed.Each cell in the histogram represented the number of packets with corresponding size that arrive at the corresponding time interval, avoiding reliance on packet payloads and privacy violations.The LeNet-5 convolutional neural network model was optimized to improve the classification accuracy.The inception module was embedded for multi-dimensional feature extraction and feature fusion.And the 1*1 convolution was used to control the feature dimension of the output.Besides, the average pooling layer and the convolutional layer were used to replace the fully connected layer to increase the calculation speed and avoid overfitting.The sliding window method was used in the object detection task, and each network unidirectional flow was divided into equal-sized blocks, ensuring that the blocks in the training set and the blocks in the test set in a single session do not overlap and expanding the dataset samples.The classification experiment results on the ISCX dataset show that for the application traffic classification task, the average accuracy rate reaches more than 95%.The comparative experimental results show that the traditional classification method has a significant decrease in accuracy or even fails when the types of training set and test set are different.However, the accuracy rate of the proposed method still reaches 89.2%, which proves that the method is universally suitable for encrypted traffic and non-encrypted traffic.All experiments are based on imbalanced datasets, and the experimental results may be further improved if balanced processing is performed.…”
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Auto-Probabilistic Mining Method for Siamese Neural Network Training by Arseniy Mokin, Alexander Sheshkus, Vladimir L. Arlazarov

“…Firstly, this paper presents an auto-probabilistic mining method designed to automatically select the most informative training samples for Siamese neural networks. …”
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Multi-adversarial domain adaptation method based on feature correction by Yong ZHANG, Haoshuang LIU, Qi ZHANG, Wenzhe LIU

“…Domain adaptation can transfer labeled source domain information to an unlabeled but related target domain by aligning the distribution of source domain and target domain.However, most existing methods only align the low-level feature distributions of the source and target domains, failing to capture fine-grained information within the samples.To address this limitation, a feature correction-based multi-adversarial domain adaptation method was proposed.An attention mechanism to highlight transferable regions was introduced in this method and a feature correction module was deployed to align the high-level feature distributions between the two domains, further reducing domain discrepancies.Additionally, to prevent individual classifiers from overfitting their own noisy pseudo-labels,dual classifier co-training was proposed and the feature aggregation property of graph neural networks was utilized to generate more accurate source domain labels.Extensive experiments on three benchmark datasets for transfer learning demonstrate the effectiveness of the proposed method.…”
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Modeling of Asphalt Concrete While Using Discrete Element Method by V. V. Alekseenko, K. Yu. Vabishchevich, E. V. Verkhoturova

“…The paper considers a mathematical model which is used to study a composite material similar in structure to asphalt concrete and it takes into account presence of solid particles of different sizes and a soft and plastic binder. The twodimensional method of discrete elements has been applied to investigate destruction of asphalt-concrete samples under uniaxial compression, tension during splitting and compression by the Marshall method. …”
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An Iterative Adaptive Polarization Calibration Method Independent of Corner Reflectors by Bowen Chi, Jixian Zhang, Guoman Huang, Lijun Lu, Shucheng Yang

“…The experiments demonstrated that the proposed method not only ensured convergence but also improved the accuracy and stability of PolCal methods without CRs.…”
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Contrastive learning method for leak detection in water distribution networks by Rongsheng Liu, Tarek Zayed, Rui Xiao

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An Intelligent Weed Recognition Method Based on Optical Patrol Image by Guoliang YUE, Yanqiao LU, Hao CHANG, Cuiying SUN

“…Based on the feature of weeds in the optical images, and combined with the convolutional neural network method, the problem of weed recognition near the power equipment in optical patrol images is solved. …”
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The Post-Method Teacher in the AI Age: Adapting, Collaborating, Evolving by Rosa Cecibel Varas Giler, Karina Fernanda Sotomayor

“…Post-method teachers can create dynamic and personalized learning experiences that prepare students for success This research was applied as a sample to 25 English professors from the Technical State University of Quevedo-Ecuador. …”
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