A Topic Representation Model for Online Social Networks Based on Hybrid Human–Artificial Intelligence

Han, Weihong; Tian, Zhihong; Zhu, Chunsheng; Huang, Zizhong; Jia, Yan; Guizani, Mohsen

doi:10.1109/tcss.2019.2959826

Cited by 14 publications

(2 citation statements)

References 22 publications

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“…The success of a learning process can be measured by the success of students who follow the subject (Han et al, 2021). This success can be seen from the level of understanding of concepts, mastery of material, and learning outcomes (Solis et al, 2021), students with a high level of understanding of concepts and mastery of material will have higher learning outcomes.…”

Section: Introductionmentioning

confidence: 99%

The Use of Wordwall in Vocabulary Selection in Narrative Texts of Students in Class VII-1 SMP Palangka Raya

Perdana,

Bungai,

Oscar

et al. 2023

J. Journal International Inspire Education Technology

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Learning media is one of the important factors that influence learning outcomes. The selection and use of appropriate and interesting media will have a good impact on student learning success. The use of technology-based learning media is still not widely done at SMPN 2 Palangka Raya. This study aims to apply Wordwall media as a medium for doing assignments and helping students in choosing the right vocabulary in the Imagination story. This research was conducted on students of class VII-I. Procedure for collecting data through observation, documentation, pre-test, post-test and interviews. Data were analyzed through data reduction, data presentation and drawing conclusions. The results showed that the application of Wordwall media can help students in working on the task of choosing Vocabulary in the Imagination story. It can be seen from the change in the score between the Pre Test and Post Test which has increased.

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Section: Introductionmentioning

confidence: 99%

The Use of Wordwall in Vocabulary Selection in Narrative Texts of Students in Class VII-1 SMP Palangka Raya

Perdana,

Bungai,

Oscar

et al. 2023

J. Journal International Inspire Education Technology

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show abstract

“…Face forgery often contains faked characters, events and voice information, such as fake news, Internet fraud, rumors, etc. [7][8][9], which can negatively impact our lives. Face forgery detection has become an important subject to be studied urgently because the abuse of face forgery technology has brought great threats to personal privacy and social security.…”

Section: Introductionmentioning

confidence: 99%

IR-Capsule: Two-Stream Network for Face Forgery Detection

Lin

Han

et al. 2022

Cogn Comput

Self Cite

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The rapid advancement of deepfake technologies raises significant concerns about the security of face recognition systems. While existing methods leverage the clues left by deepfake techniques for face forgery detection, malicious users may intentionally manipulate forged faces to obscure the traces of deepfake clues and thereby deceive detection tools. Meanwhile, attaining cross-domain robustness for data-based methods poses a challenge due to potential gaps in the training data, which may not encompass samples from all relevant domains. Therefore, in this paper, we introduce a solutiona Cross-Domain Robust Bias Expansion Network (BENet) -designed to enhance face forgery detection. BENet employs an auto-encoder to reconstruct input faces, maintaining the invariance of real faces while selectively enhancing the difference between reconstructed fake faces and their original counterparts. This enhanced bias forms a robust foundation upon which dependable forgery detection can be built. To optimize the reconstruction results in BENet, we employ a bias expansion loss infused with contrastive concepts to attain the aforementioned objective. In addition, to further heighten the amplification of forged clues, BENet incorporates a Latent-Space Attention (LSA) module. This LSA module effectively captures variances in latent features between the auto-encoder's encoder and decoder, placing emphasis on inconsistent forgery-related information. Furthermore, BENet incorporates a crossdomain detector with a threshold to determine whether the sample belongs to a known distribution. The correction of classification results through the cross-domain detector enables BENet to defend against unknown deepfake attacks from cross-domain.Extensive experiments demonstrate the superiority of BENet compared with state-ofthe-art methods in intra-database and cross-database evaluations.

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Attention-LSTM based prediction model for aircraft 4-D trajectory

Jia,

Chen,

Zhang

et al. 2022

Sci Rep

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Aviation activities are constantly increasing as a result of the growth of the global economic system. How to increase airspace capacity within the limited airspace resources while ensuring smooth and safe aircraft operations is a challenge for civil aviation today. Air traffic safety is supported by accurate trajectory prediction. The way-points are relatively sparse, and there are many uncertain factors in the flight, which greatly increases the difficulty of trajectory prediction. So, it is vital to enhance trajectory prediction accuracy. An attention-LSTM trajectory prediction model is proposed in this paper, which is split into two parts. The time-series features of the flight trajectory are extracted in the initial stage using the long-short-term memory neural network (LSTM). In the second part, the attention mechanism is employed to process the extracted sequence features. The impact of secondary elements is reduced while the influence of primary ones is increased according to the attention mechanism. We used the advanced models in trajectory prediction as the comparison models, such as LSTM, support vector machine (SVM), back propagation (BP) neural network, Hidden Markov Model (HMM), and convolutional long-term memory neural network (CNN-LSTM). The model we proposed is superior to the model above based on quantitative analysis and comparison.

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A Topic Representation Model for Online Social Networks Based on Hybrid Human–Artificial Intelligence

Cited by 14 publications

References 22 publications

The Use of Wordwall in Vocabulary Selection in Narrative Texts of Students in Class VII-1 SMP Palangka Raya

The Use of Wordwall in Vocabulary Selection in Narrative Texts of Students in Class VII-1 SMP Palangka Raya

IR-Capsule: Two-Stream Network for Face Forgery Detection

Attention-LSTM based prediction model for aircraft 4-D trajectory

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