Security protocol code analysis method combining model learning and symbolic execution by Xieli ZHANG, Yuefei ZHU, Chunxiang GU, Xi CHEN

“…Symbolic execution can comprehensively analyze program execution space in theory, but it is not feasible in practice for large programs like security protocols, due to the explosion of path space and the limitation of difficulty in solving path constraints.According to the characteristics of security protocol program, a method to guide the symbolic execution of security protocol code by using protocol state machine information obtained from model learning was proposed.At the same time, by separating cryptographic logic from protocol interaction logic, the problem that path constraints cannot be solved caused by the complexity of cryptographic logic is avoided.The feasibility of the method is demonstrated by the practice on the SSH open source project Dropbear.Compared with Dropbear's test suite, the proposed method has advantages in code coverage and error point discovery.…”
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Predictive Technology Assessment by Means of a Structure-Based Method of Machine Learning by Manja Mai-Ly PFAFF, Uwe FRIEß, Andreas OTTO, Matthias PUTZ

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Sharing Method of Online Teaching Resources of Spoken English Based on Deep Learning by Wei Cai, Yan Peng

“…Finally, this paper analyzes the sharing methods of online teaching resources of spoken English in combination with deep learning methods and constructs a corresponding intelligent teaching resource sharing system. …”
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The Imbalanced Target Classification Method Based on Mixed Learning of Virtual and Real Data by Fengyu Yang, Peng Wang, Wutao Qin, Zhangze Liao

“…In the unbalanced subdomain clipart dataset of DomainNet, using the proposed method, the accuracy of the trained model is as high as 65.1%. …”
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Automatic Detection Method for Surface Diseases of Shield Tunnel Based on Deep Learning by WANG Baokun, WANG Rulu, CHEN Jinjian, PAN Yue, WANG Lujie

“…Finally, the proposed method is trained, verified, and tested on a dataset, and applied to practical engineering detection, achieving high-precision pixel-level diseases semantic segmentation. …”
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A Machine Learning Method for Predicting Driving Range of Battery Electric Vehicles by Shuai Sun, Jun Zhang, Jun Bi, Yongxing Wang

“…The study is innovative in its application of machine learning method, the gradient boosting decision tree algorithm, on the driving range prediction which includes a very large number of factors that cannot be considered by conventional regression methods. …”
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Deep Learning Method for Wetland Segmentation in Unmanned Aerial Vehicle Multispectral Imagery by Pakezhamu Nuradili, Ji Zhou, Guiyun Zhou, Farid Melgani

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Substructure correlation adaptation transfer learning method based on K-means clustering by Haoshuang LIU, Yong ZHANG, Yingbo CAO

“…Domain drifts severely affect the performance of traditional machine learning methods, and existing domain adaptive methods are mainly represented by adaptive adjustment cross-domain through global, class-level, or sample-level distribution adaptation.However, too coarse global matching and class-level matching can lead to insufficient adaptation, and sample-level adaptation to noise can lead to excessive adaptation.A substructure correlation adaptation (SCOAD) transfer learning algorithm based on K-means clustering was proposed.Firstly, multiple subdomains of the source domain and the target domain were obtained by K-means clustering.Then, the matching of the second-order statistics of the subdomain center was sought.Finally, the target domain samples were classified by using the subdomain structure.The proposed method approach further improves the performance of knowledge transfer between the source and target domains on top of the traditional approach.Experimental results on common transfer learning datasets show the effectiveness of the proposed method.…”
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Deep Reinforcement Learning Method for Wireless Video Transmission Based on Large Deviations by Yongxiao Xie, Shian Song

“…In scalable video transmission research, the video transmission process is commonly modeled as a Markov decision process, where deep reinforcement learning (DRL) methods are employed to optimize the wireless transmission of scalable videos. …”
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A trajectory planning and tracking method based on deep hierarchical reinforcement learning by Jiajie Zhang, Bao-Lin Ye, Xin Wang, Lingxi Li, Bo Song

“…To improve the driving efficiency of unmanned vehicles in a complex urban traffic flow environment and the safety and passenger comfort of vehicles when changing lanes, we propose a hierarchical reinforcement learning (HRL)-based vehicle trajectory planning and tracking method. …”
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Research on Automatic Classification Method of Ethnic Music Emotion Based on Machine Learning by Zijin Wu

“…The classification model used in this article is mainly after determining the use of Support Vector Machine (SVM) classification method, a variety of attempts have been made to feature extraction, and good results have been achieved. …”
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A lightweight deep learning method to identify different types of cervical cancer by Md. Humaion Kabir Mehedi, Moumita Khandaker, Shaneen Ara, Md. Ashraful Alam, M. F. Mridha, Zeyar Aung

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EFL learners’ perception of the project-based learning method in extensive reading course by Harini

“…The lack of English reading ability in Indonesian students is a common problem, and many times the teacher uses the Project-Based Learning (PBL) method to help students improve their English reading ability. …”
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Method based on contrastive incremental learning for fine-grained malicious traffic classification by Yifeng WANG, Yuanbo GUO, Qingli CHEN, Chen FANG, Renhao LIN, Yongliang ZHOU, Jiali MA

“…In order to protect against continuously emerging unknown threats, a new method based on contrastive incremental learning for fine-grained malicious traffic classification was proposed.The proposed method was based on variational auto-encoder (VAE) and extreme value theory (EVT), and the high accuracy could be achieved in known, few-shot and unknown malicious classes and new classes were also identified without using a large number of old task samples, which met the demand of storage and time cost in incremental learning scenarios.Specifically, the contrastive learning was integrated into the encoder of VAE, and the A-Softmax was used for known and few-shot malicious traffic classification, EVT and the decoder of VAE were used for unknown malicious traffic recognition, all classes could be recognized without a lot of old samples when learning new tasks by using VAE reconstruction and knowledge distillation methods.Experimental results indicate that the proposed method is efficient in known, few-shot and unknown malicious classes, and has greatly reduced the forgetting speed of old knowledge in incremental learning scenarios.…”
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Automation of the complex ecological monitoring of the territory of the airport using the method of machine learning by V. N. Ekzarian, V. V. Rukavitsyn, M. V. Zyulyaeva

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Class Action Research: Application of the Sociodrama Method in Increasing Student Learning Motivation by Abdul Rahman Tanjung, Muhammad Rasyid Ridho

Subjects: “…sociodrama method…”
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Presenting an Innovative Method Based on Ensemble Learning for a Credit Approval System by Eshonkulov Uchkun, Elmurodov Tulkin, Ravshanov Zavqiddin, Каramanov Asqar

“…Notably, the major innovation of this work lies in the exceptional accuracy and computational efficiency demonstrated by the proposed method, which significantly enhances the performance of data classification processes within credit approval systems by enabling faster decision-making and more reliable credit risk assessments.…”
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Explainable Two-Layer Mode Machine Learning Method for Hyperspectral Image Classification by Wenjia Chen, Junwei Cheng, Song Yang, Li Sun

“…Explainable machine learning methods with a specific mathematical model provide insights into how the model works. …”
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Multi energy dynamic soaring trajectory optimization method based on reinforcement learning by ZHANG Yunfei, WANG Honglun, ZHANG Menghua, GONG Yinan

Subjects: “…gaussian pseudospectral method…”
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Exploring the Informal Learning Resources Used by Dental Students: A Mixed Method by Maha Akkari, Mayssoon Dashash, Issam Jamous

“…Background Informal learning resources can be considered supportive to formal learning resources in shaping future professional identity. …”
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