Quantitative method for network security situation based on attack prediction by Hao HU, Run-guo YE, Hong-qi ZHANG, Ying-jie YANG, Yu-ling LIU

“…To predict the attack behaviors accurately and comprehensively as well as to quantify the threat of attack,a quantitative method for network security situation based on attack prediction was proposed.By fusing the situation factors of attacker,defender and network environment,the capability of attacker and the exploitability rate of vulnerability were evaluated utilizing the real-time detected attack events,and the expected time-cost for attack-defense were further calculated.Then an attack prediction algorithm based on the dynamic Bayesian attack graph was designed to infer the follow-up attack actions.At last,the attack threat was quantified as the security risk situation from two levels of the hosts and the overall network.Experimental analysis indicates that the proposed method is suitable for the real adversarial network environment,and is able to predict the occurrence time of attack accurately and quantify the attack threat reasonably.…”
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Quantitative method for network security situation based on attack prediction by Hao HU, Run-guo YE, Hong-qi ZHANG, Ying-jie YANG, Yu-ling LIU

“…To predict the attack behaviors accurately and comprehensively as well as to quantify the threat of attack,a quantitative method for network security situation based on attack prediction was proposed.By fusing the situation factors of attacker,defender and network environment,the capability of attacker and the exploitability rate of vulnerability were evaluated utilizing the real-time detected attack events,and the expected time-cost for attack-defense were further calculated.Then an attack prediction algorithm based on the dynamic Bayesian attack graph was designed to infer the follow-up attack actions.At last,the attack threat was quantified as the security risk situation from two levels of the hosts and the overall network.Experimental analysis indicates that the proposed method is suitable for the real adversarial network environment,and is able to predict the occurrence time of attack accurately and quantify the attack threat reasonably.…”
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Research on Oil and Gas-Bearing Zone Prediction and Identification Based on the SVD–K-Means Algorithm—A Case Study of the WZ6-1 Oil-Bearing Structure in the Beibu Gulf Basin, South China Sea by Zhilong Chen, Renyi Wang, Biao Xu, Jianghang Zhu

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An easy iris center detection method for eye gaze tracking system by Mingxin Yu, Yingzi Lin, Xiaoying Tang, Jing Xu, David Schmidt, Xiangzhou Wang, Yikang Guo

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Long short-term memory (LSTM) networks for precision prediction of Schottky barrier photodiode behavior at different illumination levels by Gökalp Tulum, Sajjad Nematzadeh, İlke Taşçıoğlu, Şemsettin Altındal, Fahrettin Yakuphanoğlu

“…Abstract This study has focused on modeling and predicting the electrical properties and parameters of CdZnO interlayered Al/p-Si Schottky Diodes (SDs) using the Long Short-Term Memory (LSTM) algorithm. …”
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Student behavior patterns in vocational education big data based on clustering algorithm by Jing Jin

Subjects: “…Vocational education…”
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A Systematic Review of Mind Maps, STEM Education, Algorithmic and Procedural Learning by Chrysovalantis Kefalis, Constantine Skordoulis, Athanasios Drigas

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The Evaluation of Online Education Course Performance Using Decision Tree Mining Algorithm by Yongxian Yang

“…The decision tree mining algorithm can classify the data, grasp the teaching process of the teacher, and analyze the overall performance of the students, so as to realize the dynamic management of the educational administration and help the educational administration personnel to make the right decision, with more reasonable allocation of resources. …”
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Improved Genetic Algorithm for English Information Education and Teaching Quality Impact Analysis by Yuanbo Li, Wanhe Song

“…Experimental results show that this algorithm has higher efficiency and quality than other algorithms with better performance, and the proposed teaching system can improve the teaching quality of English information education.…”
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Critical Algorithmic Mediation: Rethinking Cultural Transmission and Education in the Age of Artificial Intelligence by Fulgencio Sánchez-Vera

Subjects: “…algorithmic agency…”
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Development of an algorithm for managing an educational organization based on feedback and value-based management by Tikhonov Dmitriy

“…The purpose of this study is to develop an algorithm for managing an educational organization based on value management principles, taking into account the features of the digital transformation of higher education. …”
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Learning Path Analysis of Optimizing Educational Data Mining Based on Genetic Algorithm by Wu Yanhong

“…With the extensive use of educational data mining in the field of learning analysis, identifying an effective approach to maximize learning route analysis has become a research priority. …”
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Doctors Need Different Doctors to Treat Their Relatives: A Subject That Does Not Receive Enough Attention in Medical Education by Nazan Kaymaz, Şule Yıldırım, Fatih Battal, Hakan Aylanç

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A model for predicting academic performance on standardised tests for lagging regions based on machine learning and Shapley additive explanations by Mario Suaza-Medina, Rita Peñabaena-Niebles, Maria Jubiz-Diaz

“…Abstract Data are becoming more important in education since they allow for the analysis and prediction of future behaviour to improve academic performance and quality at educational institutions. …”
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Paradigm predictive analysis of two-phase Eyring–Powell fluid flow over a vertical stretching sheet with temperature-dependent viscosity by multilayer neural networks by Zahoor Shah, Hamza Iqbal, Waqar Azeem Khan, Taseer Muhammad, Muhammad Shoaib

“…Its consistently low MSE (mean square error) values (at the scale of E-09 to E-10) make it a good approximation for most scenarios; there is very little deviation and strong predictability. The results obtained validate the robustness of the DLNNs-LMA approach to solve complex fluid dynamics problems. …”
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Alzheimer’s Prediction Methods with Harris Hawks Optimization (HHO) and Deep Learning-Based Approach Using an MLP-LSTM Hybrid Network by Raheleh Ghadami, Javad Rahebi

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Research on Temperature Control Method of Rice Noodles Extruder Based on APSO-MPC by Mengyao Zhang, Yunren Yang, Guohua Gao, Zhenlong Li, Yakai He, Peigang Li, Huangzhen Lv

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Modelling and Predicting the Breaking Strength and Mass Irregularity of Cotton Rotor-Spun Yarns Containing Cotton Fiber Recovered from Ginning Process by Using Artificial Neural Network Algorithm by Mohsen Shanbeh, Hossein Hasani, Somayeh Akhavan Tabatabaei

“…The purpose of this study was to develop predictive models of breaking strength and mass irregularity (CV𝑚%) of cotton waste rotor-spun yarns containing cotton waste collected from ginning process by using the artificial neural network trained with backpropagation algorithm. …”
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Accuracy of cross-sectional imaging in predicting tumor viability using the LI-RADS treatment response algorithm after image-guided percutaneous ablation with radiologic-pathologic explant correlation by Anuradha S. Shenoy-Bhangle, M. Saad Malik, Aamir Ali, Nan Nancy Jiang, Syed Yasir Andrabi, Amit Singal, Michael P. Curry, Maria-Andreea Catana, Devin E. Eckhoff, Salomao Faintuch, Muneeb Ahmed, Imad Ahmad Nasser, Ammar Sarwar

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Development of an algorithm to improve on the National Early Warning Score 2 (NEWS2) system's accuracy in predicting critical outcomes using additional patient data and amendments to the scoring process by Lynsey Threlfall, Chris Plummer, Edward Meinert, Cen Cong, Madison Milne-Ives

“…Using these datasets, we will train and test an algorithm that optimises the variables and their weightings to predict the risk of key clinical outcomes, including mortality, intensive care unit admission, sepsis and cardiac arrest, to demonstrate a proof of concept for a modified scoring system. …”
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