METHOD OF BUILDING THE SEMANTIC NETWORK OF DISTRIBUTED SEARCH IN E-LEARNING by Nina Kuchuk, Roman Artiukh, Artem Nechausov

“…Determining intensions and extensions allowed stratified semantic networks to be used for searching. Conclusions. The method of synthesizing a decision tree and a stratified semantic network is suggested; this method enables considering them as closely interrelated ones in the context of distributed search in e-learning. …”
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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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Optical fiber eavesdropping detection method based on machine learning by Xiaolian CHEN, Yi QIN, Jie ZHANG, Yajie LI, Haokun SONG, Huibin ZHANG

“…Optical fiber eavesdropping is one of the major hidden dangers of power grid information security,but detection is difficult due to its high concealment.Aiming at the eavesdropping problems faced by communication networks,an optical fiber eavesdropping detection method based on machine learning was proposed.Firstly,seven-dimensions feature vector extraction method was designed based on the influence of eavesdropping on the physical layer of transmission.Then eavesdropping was simulated and experimental feature vectors were collected.Finally,two machine learning algorithms were used for classification detection and model optimization.Experiments show that the performance of the neural network classification is better than the K-nearest neighbor classification,and it can achieve 98.1% eavesdropping recognition rate in 10% splitting ratio eavesdropping.…”
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A Graph Representation Learning-Based Method for Event Prediction by Xi Zeng, Guangchun Luo, Ke Qin, Pengyi Zheng

“…This paper proposes a novel event prediction method based on graph representation learning, aiming to improve the accuracy of event prediction while reducing the time cost. …”
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Implementation of the Drill Method in Learning Arabic with a Communicative Approach by Muhammad Zikran Adam, Laily Fitriani

Subjects: “…drill method…”
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Implementation of Inquiry Learning Method in Maharah al-Qiro'ah by Siti Shalihah, Ummi Nisa, Achmad Yani

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Backdoor defense method in federated learning based on contrastive training by Jiale ZHANG, Chengcheng ZHU, Xiang CHENG, Xiaobing SUN, Bing CHEN

“…In response to the inadequacy of existing defense methods for backdoor attacks in federated learning to effectively remove embedded backdoor features from models, while simultaneously reducing the accuracy of the primary task, a federated learning backdoor defense method called ContraFL was proposed, which utilized contrastive training to disrupt the clustering process of backdoor samples in the feature space, thereby rendering the global model classifications in federated learning independent of the backdoor trigger features.Specifically, on the server side, a trigger generation algorithm was developed to construct a generator pool to restore potential backdoor triggers in the training samples of the global model.Consequently, the trigger generator pool was distributed to the participants by the server, where each participant added the generated backdoor triggers to their local samples to achieve backdoor data augmentation.Experimental results demonstrate that ContraFL effectively defends against various backdoor attacks in federated learning, outperforming existing defense methods.…”
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Method of accelerating deep learning with optimized distributed cache in containers by Kai ZHANG, Yang CHE

“…When using GPU to train deep learning models with large-scale dataset, the data loading and preprocessing stages often decrease overall performance notably.Lots of GPU computing resources are wasted on waiting for loading data from remote storage.Firstly, the methods of accelerating deep learning training with container and distributed cache were introduced.The architecture and initial optimization of such training system, which was implemented with Alluxio and Kubernetes, were introduced as well.Secondly, the task and data co-located scheduling (TDCS) and the colocated scheduling policy were elaborated.Thirdly, TDCS was implemented in Kubernetes cluster, which made the acceleration result more extensible.Finally, the result of training ResNet50 image classification model on 128 NVIDIAV100 GPU devices demonstrates that the proposed methods can bring 2 to 3 times speed up comparing with load data from remote storage directly.…”
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A Transfer Learning Method to Generate Synthetic Synoptic Magnetograms by Xiaoyue Li, Valliappan Senthamizh Pavai, Daria Shukhobodskaia, Mark D. Butala, Luciano Rodriguez, Jasmina Magdalenic, Véronique Delouille

“…Toward this goal, we develop a method called Transfer‐Solar‐GAN which combines a conditional generative adversarial network with a transfer learning approach to overcome training data set limitations. …”
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The Effect of The Mind Map Method on The Students’ Memory in Thematic Learning by Dea Amelia Harits, Mizaniya Mizaniya

“…The purpose of this study was to find out the influence of mind map method on the memory of learners in thematic learning in class IV MI Ma'arif NU 02 Tamansari. …”
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Helium Speech Recognition Method Based on Spectrogram with Deep Learning by Yonghong Chen, Shibing Zhang, Dongmei Li

“…This study introduces deep learning into helium speech recognition and proposes a spectrogram-based dual-model helium speech recognition method. …”
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Research on Apple Recognition and Localization Method Based on Deep Learning by Zhipeng Zhao, Chengkai Yin, Ziliang Guo, Jian Zhang, Qing Chen, Ziyuan Gu

“…This study proposes a fusion recognition method based on improved YOLOv7 for apple growth morphology classification and fruit position. …”
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Deep Learning Method for Classifying Items into Categories for Dutch Auctions by Janusz Bobulski, Sabina Szymoniak

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Clothing classification method based on attention mechanism and transfer learning by CHEN Jinguang, HUANG Xiaoju, MA Lili

“…Aimed the low efficiency and low accuracy of clothing image classification, a clothing image classification method based on attention mechanism and transfer learning was proposed. …”
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FLWD:A Webshell detection method based on federated learning by ZENG Qingpeng, CHAI Jiangli, WU Shuixiu

“…To address these challenges, a Webshell detection method based on federated learning was proposed. The method integrated the abstract syntax tree node value sequence features, code structure features, text obfuscation features, and cybersecurity expertise and experience features of Webshells. …”
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A Survey of Grapheme-to-Phoneme Conversion Methods by Shiyang Cheng, Pengcheng Zhu, Jueting Liu, Zehua Wang

“…This paper provides a systematical overview of the G2P conversion from different perspectives. The conversion methods are first presented in the paper; detailed discussions are conducted on methods based on deep learning technology. …”
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METHODOLOGICAL BASES OF BLENDED LEARNING IN THE HIGHER EDUCATION by Olga Korotun

Subjects: “…blended learning; traditional learning; distance learning; methodological bases; principles…”
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Modern vs Traditional: Comparative Study of Efficacious Arabic Language Learning Methods by Budi Pratama, Haerani Kadar, Busyro Husaini, Muslih Abdul Aziz, Dimas Adi Saputra

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Review of pedestrian trajectory prediction methods by Linhui LI, Bin ZHOU, Weiwei REN, Jing LIAN

“…With the breakthrough of deep learning technology and the proposal of large data sets, the accuracy of pedestrian trajectory prediction has become one of the research hotspots in the field of artificial intelligence.The technical classification and research status of pedestrian trajectory prediction were mainly reviewed.According to the different modeling methods, the existing methods were divided into shallow learning and deep learning based trajectory prediction algorithms, the advantages and disadvantages of representative algorithms in each type of method were analyzed and introduced.Then, the current mainstream public data sets were summarized, and the performance of mainstream trajectory prediction methods based on the data sets was compared.Finally, the challenges faced by the trajectory prediction technology and the development direction of future work were prospected.…”
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Comparing the effect of lecture method and cooperative teaching method on the learning, communication skills, and attitudes of students: a quasi-experimental study by Amin Beigzadeh, Hadi Bazyar, Hadi Bazyar, Mozhdeh Delzendeh, Mohammad Hassan Razmi, Nafiseh Sharifi

“…The objective of this study was to evaluate the effectiveness of the lecture method in comparison to the cooperative learning method, specifically focusing on students’ learning outcomes, communication skills, and attitudes.MethodsThis quasi-experimental interventional study was conducted at Sirjan School of Medical Sciences, Sirjan, Iran in 2023 involving a sample of 30 third-semester students. …”
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