Feature dependence graph based source code loophole detection method by Hongyu YANG, Haiyun YANG, Liang ZHANG, Xiang CHENG

“…Given the problem that the existing source code loophole detection methods did not explicitly maintain the semantic information related to the loophole in the source code, which led to the difficulty of feature extraction of loo-phole statements and the high false positive rate of loophole detection, a source code loophole detection method based on feature dependency graph was proposed.First, extracted the candidate loophole statements in the function slice, and gen-erated the feature dependency graph by analyzing the control dependency chain and data dependency chain of the candi-date loophole statements.Secondly, the word vector model was used to generate the initial node representation vector of the feature dependency graph.Finally, a loophole detection neural network oriented to feature dependence graph was constructed, in which the graph learning network learned the heterogeneous neighbor node information of the feature de-pendency graph and the detection network extracted global features and performed loophole detection.The experimental results show that the recall rate and F1 score of the proposed method are improved by 1.50%～22.32% and 1.86%～16.69% respectively, which is superior to the existing method.…”
Get full text

Feature dependence graph based source code loophole detection method by Hongyu YANG, Haiyun YANG, Liang ZHANG, Xiang CHENG

“…Given the problem that the existing source code loophole detection methods did not explicitly maintain the semantic information related to the loophole in the source code, which led to the difficulty of feature extraction of loo-phole statements and the high false positive rate of loophole detection, a source code loophole detection method based on feature dependency graph was proposed.First, extracted the candidate loophole statements in the function slice, and gen-erated the feature dependency graph by analyzing the control dependency chain and data dependency chain of the candi-date loophole statements.Secondly, the word vector model was used to generate the initial node representation vector of the feature dependency graph.Finally, a loophole detection neural network oriented to feature dependence graph was constructed, in which the graph learning network learned the heterogeneous neighbor node information of the feature de-pendency graph and the detection network extracted global features and performed loophole detection.The experimental results show that the recall rate and F1 score of the proposed method are improved by 1.50%～22.32% and 1.86%～16.69% respectively, which is superior to the existing method.…”
Get full text

Research on aircraft engine thrust estimation method incorporating attention mechanism by ZOU Yuhang, ZHAO Yongping

“…The study of thrust prediction under different conditions based on transfer learning methods indicates that Fine-tuning should be selected when there is limited target domain data，while the modified DANN method will yield a model with higher accuracy when there is sufficient target domain data.…”
Get full text

Perceived learning gaps in paediatric anaesthesia training: A cross-sectional survey by Vasudha Devi, Vinod Pallath, Balasubramaniam Gayathri, Shantanu S. Patil

Get full text

LOCAL LINEAR EMBEDDING ALGORITHM FOR PARAMETER MATRIX MEASUREMENT IN SYMMETRIC POSITIVE DEFINITE MANIFOLD (MT) by LIU QingQiang, HE HongKai, ZHENG ChangMin, SUN YanRu, LIU ZiXuan

“…First, in order to find a suitable measurement method on the symmetric positive definite manifold to improve the performance of the algorithm, an efficient Riemann space metric learning method is introduced. …”
Get full text

Integrasi Project-Based Learning dalam Pendidikan Agama Islam: Strategi, Tantangan, dan Efektivitas by Lutfi Rachman, Nurhanifansyah Nurhanifansyah

“…Education the current era increasingly recognizes Project-Based Learning (PBL) as an innovative approach to enhance student engagement and the relevance of learning. …”
Get full text

Analysis of 19.9 million publications from the PubMed/MEDLINE database using artificial intelligence methods: approaches to the generalizations of accumulated data and the phenomen... by I. Yu. Torshin, O. A. Gromova, L. V. Stakhovskaya, N. P. Vanchakova, A. N. Galustyan, Zh. D. Kobalava, T. R. Grishina, A. N. Gromov, I. A. Ilovaiskaya, V. M. Kodentsova, A. G. Kalacheva, O. A. Limanova, V. A. Maksimov, S. I. Malyavskaya, E. V. Mozgovaya, N. I. Tapilskaya, K. V. Rudakov, V. A. Semenov

Get full text

A Novel Online System Implementation to Enhance Team-Based Learning at a Medical School by Shaban S, Zafar I, Tariq MI, Magzoub ME

“…Sami Shaban, Imran Zafar, Mohammad Irfan Tariq, Mohi Eldin Magzoub Department of Medical Education, UAE University, Alain, United Arab EmiratesCorrespondence: Sami Shaban, Department of Medical Education, United Arab Emirates University, POBox 15551, Alain, United Arab Emirates, Tel +971 37137199, Email sami.shaban@uaeu.ac.aeIntroduction: Team-Based Learning (TBL) is an effective learning model utilized in education to address the concerns of student active learning, participation, critical thinking and teamwork. …”
Get full text

IMPLEMENTASI MODEL PEMBELAJARAN PROJECT-BASED LEARNING (PJBL) DALAM PENGEMBANGAN BERPIKIR KRITIS by Dinah Mardatillah, Dadan Setiawan

“…This study aims to analyse the effectiveness of Project-Based Learning (PjBL) learning model in improving critical thinking skills of elementary school students. …”
Get full text

Exploring the experiences of sonography students with simulation‐based learning: A perspective from South Africa by Geordean Schwartz, Kathleen Naidoo, Ferial Isaacs

“…Abstract Introduction Simulation‐based learning (SBL) is widely used in healthcare education to provide a safe environment for students to practice clinical scenarios without causing patient harm. …”
Get full text

An Efficient Mutual Authentication and Fractional Lyrebird Optimization With Deep Learning–Based SIP-Based DRDoS Attack Detection by V. Sreenivasulu, C. V. Ravikumar

“…In this article, a deep learning model fractional lyrebird optimization algorithm–deep stack autoencoder (FLOA-DSA) is developed for the detection of SIP-based distributed reflection denial-of-service (DRDoS) attacks in SIP network. …”
Get full text

Multi-Timescale Voltage Control Method Using Limited Measurable Information with Explainable Deep Reinforcement Learning by Fumiya Matsushima, Mutsumi Aoki, Yuta Nakamura, Suresh Chand Verma, Katsuhisa Ueda, Yusuke Imanishi

“…The approach estimates the voltage at each grid node using a Deep Neural Network (DNN) that processes measurable substation data. Based on these estimated voltages, the method determines optimal LRT tap positions and PCS reactive power outputs using Deep Reinforcement Learning (DRL). …”
Get full text

Development and Validation of the Pre-service Teacher Competency Scale in an Online Learning Environment Using the Scenario Method by Jiwon Baek, Jiwoo Kim, Hyeonseong Lee, Youn-Jeng Choi

“…This study aims to address this gap by developing and validating a scale to measure pre-service teacher competency in an online learning context using the scenario method. After a comprehensive literature review, seven competencies of pre-service teachers in an online learning environment were constructed: design/planning competency, social competency, instructive competency, technological competency, management competency, positive teacher attitude competency, and learning competency. …”
Get full text

Developing A Model For Improving The Business Performance Of Nanotechnology Knowledge-Based Companies Based On Technological Learning Modes by Hedayat Samadiansari, Mohammadreza Razavi, Parivash Jafari

“…The purpose of this research is to provide an integrated model for improving the business performance of knowledge-based nanotechnology companies based on technological learning modes. …”
Get full text

Trajectory-Driven Deep Learning for UAV Location Integrity Checks by Mincheol Shin, Sang-Yoon Chang, Jonghyun Kim, Kyungmin Park, Jinoh Kim

“…Our extensive experimental results support the feasibility of our trajectory-based analysis approach, showing up to 98.9% classification performance with negligible false positive rates (lower than 1%) for ensuring location consistency (even without referring to the GPS signal-specific information).…”
Get full text

The Effect of Audio Visual-Based Inquiry Learning Model on Elementary Student Learning Outcomes in Science and Technology Subjects in Class IV by Nelli Kristina Sianturi, Juliana, Patri Janson Silaban, Bogor Lumbanraja, Nova Florentina Ambarwati

“…Through the t-test, it can be concluded that there is a significant positive effect between the  audio-visual media-based inquiry learning model on class IV student learning outcomes in the science and technology subject UPT SD Negeri 068008 Medan Tuntungan in the academic year 2023/2024. …”
Get full text

An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration by Jingjing Yang, Lihong Wan, Junbing Qian, Zonglun Li, Zhijie Mao, Xueming Zhang, Junjie Lei

Get full text

Transformation of Student Science Achievement Through Project-Based Learning (PjBL): A Meta Analysis Study by Islamiani Safitri

“…This study aims to evaluate the effectiveness of Project-Based Learning (PjBL) in enhancing students' science achievements through meta-analysis study. …”
Get full text

Vision Target Tracker Based on Incremental Dictionary Learning and Global and Local Classification by Yang Yang, Ming Li, Fuzhong Nian, Huiya Zhao, Yongfeng He

Get full text

Influence of Ocean Current Features on the Performance of Machine Learning and Dynamic Tracking Methods in Predicting Marine Drifter Trajectories by Huan Lin, Weiye Yu, Zhan Lian

“…This study establishes a baseline for selecting machine learning methods for marine drifter prediction and highlights the limitations of AI-based predictions under data-scarce and resource-constrained conditions.…”
Get full text