Full bibliography

Zuev, D. (2023). Coral empire: underwater oceans, colonial tropics, visual modernity: by Ann Elias Durham: Duke University Press, 2019, 296 pages ISBN: 9781478003182 (hbk) 99.95 USD, 9781478003823 (pbk) 26.95 USD, 9781478004462 (ebook) 26.95 USD. Visual Studies, 38(1), 152–153. https://doi.org/10.1080/1472586X.2022.2042372

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Olga Ng Ka Man, S. (Ed.) (with Gerald, E.). (2023). (Un)directed Reading: Selected Students’ Work Directed Reading 2020/21 University of Saint Joseph, Macao, China. University of Saint Joseph.

Li, W., Yang, Q., & Du, W. (2022). Tourist Sentiment Mining Based on Deep Learning. In C. Thomas (Ed.), Artificial Intelligence (Vol. 8). IntechOpen. https://doi.org/10.5772/intechopen.98836

Mining the sentiment of the user on the internet via the context plays a significant role in uncovering the human emotion and in determining the exactness of the underlying emotion in the context. An increasingly enormous number of user-generated content (UGC) in social media and online travel platforms lead to development of data-driven sentiment analysis (SA), and most extant SA in the domain of tourism is conducted using document-based SA (DBSA). However, DBSA cannot be used to examine what specific aspects need to be improved or disclose the unknown dimensions that affect the overall sentiment like aspect-based SA (ABSA). ABSA requires accurate identification of the aspects and sentiment orientation in the UGC. In this book chapter, we illustrate the contribution of data mining based on deep learning in sentiment and emotion detection.

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Li, N., Yang, X., Du, W., Ogihara, A., Zhou, S., Ma, X., Wang, Y., Li, S., & Li, K. (2022). Exploratory Research on Key Technology of Human-Computer Interactive 2.5-Minute Fast Digital Early Warning for Mild Cognitive Impairment. Computational Intelligence and Neuroscience, 2022, 1–15. https://doi.org/10.1155/2022/2495330

Objective. As the preclinical stage of Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI) is characterized by hidden onset, which is difficult to detect early. Traditional neuropsychological scales are main tools used for assessing MCI. However, due to its strong subjectivity and the influence of many factors such as subjects’ educational background, language and hearing ability, and time cost, its accuracy as the standard of early screening is low. Therefore, the purpose of this paper is to propose a new key technology of fast digital early warning for MCI based on eye movement objective data analysis. Methodology. Firstly, four exploratory indexes (test durations, correlation degree, lengths of gaze trajectory, and drift rate) of MCI early warning are determined based on the relevant literature research and semistructured expert interview; secondly, the eye movement state is captured based on the eye tracker to realize the data extraction of four exploratory indexes. On this basis, the human-computer interactive 2.5-minute fast digital early warning paradigm for MCI is designed; thirdly, the rationality of the four early warning indexes proposed in this paper and their early warning effectiveness on MCI are verified. Results. Through the small sample test of human-computer interactive 2.5 fast digital early warning paradigm for MCI conducted by 32 elderly people aged 70–90 in a medical institution in Hangzhou, the two indexes of “correlation degree” and “drift rate” with statistical differences are selected. The experiment results show that AUC of this MCI early warning paradigm is 0.824. Conclusion. The key technology of human-computer interactive 2.5 fast digital early warning for MCI proposed in this paper overcomes the limitations of the existing MCI early warning tools, such as low objectification level, high dependence on professional doctors, long test time, requiring high educational level, and so on. The experiment results show that the early warning technology, as a new generation of objective and effective digital early warning tool, can realize 2.5-minute fast and high-precision preliminary screening and early warning for MCI in the elderly.

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Ma, X., Chen, Y., Li, S., Du, W., Tan, Z., Li, Q., Ma, Y., & Deng, H. (2021). Quality Detection Method for Controller Process Based on Mask R-CNN Network Model. 2021 8th International Conference on Computational Science/Intelligence and Applied Informatics (CSII), 18–22. https://doi.org/10.1109/CSII54342.2021.00012

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Han, W., Shasha, L., Shaobin, L., Wencai, D., Qinggu, L., & Bo, W. (2021). Research on Quality Control of Intelligent Injection Molding System Based on Process Monitoring. 2021 8th International Conference on Computational Science/Intelligence and Applied Informatics (CSII), 1–6. https://doi.org/10.1109/CSII54342.2021.00013

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Barzinji, A. O., Ma, C., Du, W., & Ma, J. (2021). A Machine Learning Approach to Predict the Trend of Obesity Prevalence at a Global Level. 2021 IEEE/ACIS 6th International Conference on Big Data, Cloud Computing, and Data Science (BCD), 25–30. https://doi.org/10.1109/BCD51206.2021.9581579

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Wang, H., Yang, J., Wu, Y., Du, W., Fong, S., Duan, Y., Yao, X., Zhou, X., Li, Q., Lin, C., Liu, J., Huang, L., & Wu, F. (2021). A Fast Lightweight Based Deep Fusion Learning for Detecting Macula Fovea Using Ultra-Widefield Fundus Images [Preprint]. MATHEMATICS & COMPUTER SCIENCE. https://doi.org/10.20944/preprints202108.0469.v2

Macula fovea detection is a crucial prerequisite towards screening and diagnosing macular diseases. Without early detection and proper treatment, any abnormality involving the macula may lead to blindness. However, with the ophthalmologist shortage and time-consuming artificial evaluation, neither accuracy nor effectiveness of the diagnose process could be guaranteed. In this project, we proposed a deep learning approach on ultra-widefield fundus (UWF) images for macula fovea detection. This study collected 2300 ultra-widefield fundus images from Shenzhen Aier Eye Hospital in China. Methods based on U-shape network (Unet) and Fully Convolutional Networks (FCN) are implemented on 1800 (before amplifying process) training fundus images, 400 (before amplifying process) validation images and 100 test images. Three professional ophthalmologists were invited to mark the fovea. A method from the anatomy perspective is investigated. This approach is derived&ensp;from the spatial relationship between macula fovea and optic disc center in UWF. A set of parameters of this method is set based on the experience of ophthalmologists and verified to be effective. Results are measured by calculating the Euclidean distance between proposed approaches and the accurate grounded standard, which is detected by Ultra-widefield swept-source optical coherence tomograph (UWF-OCT) approach. Through a comparation of proposed methods, we conclude that, deep learning approach of Unet outperformed other methods on macula fovea detection tasks, by which outcomes obtained are comparable to grounded standard method.

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Gois, F. N. B., Marques, J. A. L., De Oliveira Dantas, A. B., Santos, M. C., Neto, J. V. S., De Macêdo, J. A. F., Du, W., & Li, Y. (2023). Malaria Blood Smears Object Detection Based on Convolutional DCGAN and CNN Deep Learning Architectures. In R. Lee (Ed.), Computer and Information Science (Vol. 1055, pp. 197–212). Springer International Publishing. https://doi.org/10.1007/978-3-031-12127-2_14

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Ma, H., Ma, J., Liang, S., & Du, W. (2022). A Model of Integrating Bert and BiGRU+ Attention Dual-channel Mechanism for Investor Sentiment Analysis of Stock Price Forecast. 2022 IEEE/ACIS 23rd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 126–131. https://doi.org/10.1109/SNPD54884.2022.10051779

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Caldas, W. L., Do Vale Madeiro, J. P., Pedrosa, R. C., Gomes, J. P. P., Du, W., & Marques, J. A. L. (2023). Noise Detection and Classification in Chagasic ECG Signals Based on One-Dimensional Convolutional Neural Networks. In R. Lee (Ed.), Computer and Information Science (Vol. 1055, pp. 117–129). Springer International Publishing. https://doi.org/10.1007/978-3-031-12127-2_8

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Wu, W., Jing, X., Du, W., & Chen, G. (2021). Learning dynamics of kernel-based deep neural networks in manifolds. Science China Information Sciences, 64(11), 212103. https://doi.org/10.1007/s11432-020-3022-3

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Liang, S., Jin, J., Ren, J., Du, W., & Qu, S. (2023). An Improved Dual-Channel Deep Q-Network Model for Tourism Recommendation. Big Data, big.2021.0353. https://doi.org/10.1089/big.2021.0353

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Castro, M. G., Palinhos, J., Ribas, D., & Caires, C. S. (2017). Editorial. Journal of Science and Technology of the Arts, 9(2), 1–2. https://doi.org/10.7559/citarj.v9i2.363

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Caires, C., Cardoso, J. C., Lipovka, A., Bidarra, J., & Pimentel, L. (Eds.). (2017). ARTECH2017: Proceedings of the 8th International Conference on Digital Arts. Association for Computing Machinery. https://dl.acm.org/doi/proceedings/10.1145/3106548

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Caires, C. S., Barbosa, A., & Hanyou, W. (2020). Design for Classroom Units: A Collaborative Multicultural Studio Development with Chinese Students. International Journal of Educational and Pedagogical Sciences, 14(5), 376–383. https://publications.waset.org/10011207/design-for-classroom-units-a-collaborative-multicultural-studio-development-with-chinese-students

Design for Classroom Units: A Collaborative Multicultural Studio Development with Chinese Students

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Caires, C. S. (2021). Towards an Approach to the Interactive Filmic Narrative. In M. J. Baltazar, T. Quadros, J. Staal, & R. Amaral (Eds.), Image in the post-millennium: mediation, process and critical tension. Onomatopee.

Lau, C. M., & Caires, C. S. (2022). An Attempt to Examine Digital Native and Digital Immigrant Macau Graphic Designers’ Perceptions of Adopting Generative Design. International Journal of Creative Interfaces and Computer Graphics (IJCICG), 13(1), 1–16. https://doi.org/10.4018/IJCICG.311424

The manifestation of generating digital visuals through an algorithm is gaining worldwide attention in the graphic design industry. It is a new form of computing that visualizes data input by the designer or collected in the physical environment and turns them into artwork. The generative design of...

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Marcos, A., Caires, C., Estadieu, G., Mendes, D., & Rodrigues, N. (2023). Editorial Preface. International Journal of Creative Interfaces and Computer Graphics, 13(1). https://doi.org/10.4018/IJCICG

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Martins de Abreu, F., & Barbosa, A. (2018). Cyberculture and Multimodal Digital Games in Learning Environments: Fostering Creativity in Macau’s Educational System [Conference]. LISBON CONSORTIUM - VIII Lisbon Summer School for the Study of Culture “Cyber+Cipher+Culture".