Professor Hongji Yang

(Selected from over 500)

1.     X. Zhao, Q. Duan, and H. Yang, “MPathRP : A Knowledge Graph Relationship Prediction Method Based on Cross-Modal Entity Representation Learning and Path Reasoning,” (IS) Information Sciences, p. 122786, 2026, doi: 10.1016/j.ins.2025.122786.

2.     X. Zhao, J. Bai, and H. Yang, “A scalable rule learning approach fusing multiple sources of information,” (CC) Cluster Computing, vol. 7, 2025, doi: 10.1007/s10586-024-04699-7.

3.     T. Liu, Z. Wang, Z. Feng, H. Yang, and L. Zou, “Using Big Data from Internet to Improve Land Use Transition Effects on Eco-Environment,” (JIT) JIT, 2025.

4.     Y. Zhang, H. Yang, C. Zeng, Y. Guo, and Y. Yao, “Simulating Emotion-Creativity Dynamics : A Default Mode Network Mediation Hypothesis Tested via Computational Approaches,” in (ISSSR), 2025, pp. 424–431. doi: 10.1109/ISSSR65654.2025.00063.

5.     P. Zhang, H. Yang, and Z. Zhou, “Increasing the Validity and Trustworthiness of Automated Facial Emotion Recognition Systems,” (ISSSR), pp. 386–395, 2025, doi: 10.1109/ISSSR65654.2025.00059.

6.     L. Zou, H. Yang, and M. Al-akaidi, “A Creative Computing Approach to Dimentionalising the DIKW Model : Bridging the Gap Between Concepts and Practice,” in (Book Chapter) Springer, no. February, 2025, pp. 1–16.

7.     S. O. Aliyu, H. Yang, and M. Sciences, “Quantum-Inspired Black and Turkey-Vulture Swarm Optimization : A Case Study in Network Routing,” in (QCE) QCE, 2025.

8.     D. Fennell and H. Yang, “Constitutive in flammation and epithelial- mesenchymal transition dictate sensitivity to nivolumab in CONFIRM : a placebo- controlled , randomised phase III trial,” (Nature Comm) Nature Communications, 2025.

9.     Z. Lu, H. Yang, C. Zeng, and Y. Guo, “A Translation Engine for Mapping User Intent to Design Artifacts via Aesthetic Rule Compilation,” in (QRS) IEEE International Conference on Software Quality, Reliability and Security Companion, 2025, pp. 426–433. doi: 10.1109/QRS-C65679.2025.00060.

10.  M. M. Abouzeid, H. Yang, and F. Wang, “Enhancing Reliability of Temporal Workflows through Artifact Anomaly Detection,” in (QRS) IEEE International Conference on Software Quality, Reliability and Security Companion, 2025, pp. 710–720. doi: 10.1109/QRS-C65679.2025.00091.

11.  X. Yue, Z. Lu, Y. Zhang, L. Zou, and H. Yang, “Generative AI vs Human Creativity: Comparative Study on Artistic Processes, Aesthetic Depth, and Value Orientation,” in (DSA) IEEE Dependable Systems and Their Applications, 2025.

12.  D. Pathak, R. Herrema, N. Heffer, and H. Yang, “A Framework for Brain-Based Digital Twins in Sport Motor Imagery,” in (DSA) IEEE Dependable Systems and Their Applications, 2025.

13.  K. Harianto, F.-J. Wang, P.-S. Huang, and H. Yang, “Incremental Dataflow Anomaly Detection During Deletion Activities,” in (DSA) IEEE Dependable Systems and Their Applications, 2025.

14.  S. Ji, Z. Zhou, H. Yang, L. Zhang, and M. Shi, “Exploiting Virtual Reality Visualisation Feature for Intangible Cultural Heritage in a Tourism Industrial Chain,” (JIT) Journal of Internet Technology, 2024.

15.  H. Zhang, X. Gao, H. Chen, Z. Lu, and H. Yang, “Establishing a Big Data Driver for Digital Transformation , Supplier Concentration and Total Factor Productivity in Enterprises,” (JIT) JIT, 2024.

16.  A. Mustafa, R. Millham, and H. Yang, “PRISMA Approach For Assessing Fingerprint Classification Models based on ASI,” in (ICMIMT) International Conference on Mechanical and Intelligent Manufacturing Technologies, 2024.

17.  V. Gupta and H. Yang, “Study protocol for factors influencing the adoption of ChatGPT technology by startups: Perceptions and attitudes of entrepreneurs,” (PlosOne) Plos One, vol. 19, no. 2 February, pp. 1–15, 2024, doi: 10.1371/journal.pone.0298427.

18.  X. Zhao, M. Yang, and H. Yang, “A knowledge graph embedding model based on multi-level analogical reasoning,” (CC) Cluster Computing, vol. 3, 2024, doi: 10.1007/s10586-024-04514-3.

19.  D. Wang, H. Yang, and H. Zhou, “Dynamic Spatial – Temporal Self-Attention Network for Traffic Flow Prediction,” (FI) Future Internet, pp. 1–20, 2024.

20.  C. Zeng, Y. Wu, Z. Zhou, Y. Yao, and H. Yang, “Computational Imagination in Three-Dimension Scene Synthesis,” in (ISCC) IEEE International Symposium on Creative Computing, 2024.

21.  C. Zeng et al., “Enhancing Digital Health Analysis with Gravitational Models : Creative Computing for Semantic 3D Visualisation,” in (ICDH) IEEE Service Computing, 2024.

22.  M. Zhang, H. Yang, and D. Fennell, “A gut microbiota rheostat forecasts responsiveness to PD-L1 and VEGF blockade in mesothelioma,” (Nature) Nature Communications, vol. 15:7187, pp. 1–14, 2024, doi: 10.1038/s41467-024-49842-5.

23.  D. Pathak, R. Herrema, N. Heffer, and H. Yang, “Building a Digital Twin Framework for EEG Neurofeedback in Cricket Batting Motor Imagery Using Simulated Data,” in (DT) Digital Twin, 2024.

24.  H. Yang, “Message from the Chairs,” in (QRS) IEEE International Conference on Software Quality, Reliability and Security Companion, 2024.

25.  Z. Zhou et al., “SIMULATING PERSUASIVE RESONANCE : A COMPUTATIONAL MODEL FOR,” in (MESM) International Middle Eastern Simulation and Modelling Conference, 2024.

26.  Z. Lu, M. Al-Akaidi, F. Zhou, and H. Yang, “THE DUALITY OF BEAUTY : INTEGRATING COMPUTATIONAL METHODS AND SUBJECTIVE EXPERIENCE IN AESTHETIC EVALAUTION,” in (MESM) International Middle Eastern Simulation and Modelling Conference, 2024.

27.  C. Zeng, Z. Zhou, Y. Zhang, Z. Lu, and H. Yang, “Deep-Deploying Imagination in Creative Computer for Dependent System Design,” in (DSA) IEEE Dependable Systems and Their Applications, 2024, pp. 409–416. doi: 10.1109/DSA63982.2024.00062.

28.  P. Zhang and H. Yang, “Introduction of a Time-Parameter for State Analysis in Affective Computing,” in (DSA) IEEE Dependable Systems and Their Applications, 2024, pp. 386–392. doi: 10.1109/DSA63982.2024.00059.

29.  H. Zhang and H. Yang, “Effects of big data analytics capability on Performance of Internet Enterprises : Chain Mediating Effects of Strategic Flexibility and Strategic Innovation,” (IJCAT) International Journal of Computer Applications in Technology, vol. 71, no. 1, 2023.

30.  A. Mustafa, R. Millham, and H. Yang, “Fingerprint Classification Models Based on Bio-inspired Optimization Algorithm: A Systematic Review,” in (ICDTA) ICDTA 2023, 2023.

31.  X. Zhao, F. Li, and H. Yang, “RDFS ( c ) Schema Inconsistency Checking based on a Key Instance and Its Query Rewriting,” (IEEE Access) IEEE Access, no. c, pp. 1–13, 2023.

32.  C. Li and H. Yang, “IRWoZ : Constructing An Industrial Robot,” (IEEE Access) IEEE Access, vol. 4, pp. 1–17, 2023.

33.  C. Li, D. Chrysostomou, and H. Yang, “A Speech-enabled Virtual Assistant for Efficient Human-Robot Interaction in Industrial Environments,” (JSS) Journal of Systems and Software, pp. 1–13, 2023.

34.  L. Zou, H. Yang, and J. Lin, “A Creative Computing Approach to Analysis of Speaker Intention Using the DIKCW Model,” in (QRS) IEEE International Conference on Software Quality, Reliability and Security Companion, 2023.

35.  L. Zou and H. Yang, “A Creative Computing Approach to Pragmatics Analysis involving UML Diagrams,” in (MESM) International Middle Eastern Simulation and Modelling Conference, 2023.

36.  J. Meng, G. Zhang, Z. Li, H. Yang, and M. Sciences, “An Evolutionary Mechanism of Social Preference for Knowledge Sharing in Crowdsourcing Communities,” (MAGS) Multiagent and Grid Systems, vol. 19, no. 3, pp. 253–269, 2023.

37.  Z. Lu, H. Yang, U. Kingdom, and L. Xiao, “Aesthetics , Headline Typeface in Fashion Typography and Creativity,” (Icac) Icac 2023, pp. 1–6, 2023, doi: 10.1109/ICAC57885.2023.10275295.

38.  Y. Wu, W. Mo, C. Author, and H. Yang, “A Creative Computing Approach to Creating Abstract Objects Conveying Artists ’ Perceptions in Contemporary Oil Painting,” (Icac) Icac 2023, pp. 1–7, 2023, doi: 10.1109/ICAC57885.2023.10275287.

39.  D. Zhang, Y. Dong, and H. Yang, “An adversarial defense algorithm based on robust U-net,” (MTA) Multimadi Tools and Applications, 2023, doi: 10.1007/s11042-023-17355-w.

40.  D. A. Fennell et al., “Efficacy, cellular and molecular determinants of PD-1 checkpoint inhibition in relapsed mesothelioma.,” (JCO) Journal of Clinical Oncology, vol. 41, no. 16_suppl, pp. 8506–8506, 2023, doi: 10.1200/jco.2023.41.16_suppl.8506.

41.  Y. Wang, S. Ma, L. Zou, and H. Yang, “An abstraction-based approach to eliciting wisdom in intangible cultural heritage utilisation,” (IJCAT) International Journal of Computer Applications in Technology, vol. 73, no. 3, 2023.

42.  Y. Liu and H. Yang, “A hexagonal grid geometry system for applications in 3D graphics,” (IJCAT) International Journal of Computer Applications in Technology, vol. 73, no. 3, 2023.

43.  H. Zhang, L. Wang, H. Yang, C. Yu, F. Xia, and X. Xue, “Effects of big data analytics capability on performance of internet enterprises: chain mediating effects of strategic flexibility and strategic innovation,” (IJCAT) International Journal of Computer Applications in Technology, vol. 71, no. 1, pp. 52–63, 2023, doi: 10.1504/IJCAT.2023.131062.

44.  J. Meng, G. Zhang, Z. Li, and H. Yang, “An evolutionary mechanism of social preference for knowledge sharing in crowdsourcing communities,” (MAGS) Multiagent and Grid Systems, vol. 19, no. 3, pp. 253–269, 2023, doi: 10.3233/MGS-221532.

45.  V. Gupta and H. Yang, “Generative Artificial Intelligence ( AI ) Technology Adoption Model for Entrepreneurs : Case of ChatGPT Generative Artificial Intelligence ( AI ) Technology Adoption Model for Entrepreneurs : Case of ChatGPT,” (IRSQ）Internet Reference Services Quarterly, vol. 0, no. 0, pp. 1–20, 2023, doi: 10.1080/10875301.2023.2300114.

46.  Y. Wang, S. Ma, L. Zou, and H. Yang, “An abstraction-based approach to eliciting wisdom in intangible cultural heritage utilisation,” International Journal of Computer Applications in Technology, vol. 73, no. 3, pp. 178–191, 2023, doi: 10.1504/IJCAT.2023.135540.

47.  X. Xu, C. Liu, and H. Yang, “Robust Inference Based On the Complementary Hamiltonian Monte Carlo,” (TR) IEEE Transactions on Reliability, vol. 71, no. 1, pp. 111–126, 2022, doi: 10.1109/TR.2021.3117189.

48.  X. Xu, C. Liu, H. Yang, and X. Zhang, “A Multi-Trajectory Monte Carlo Sampler,” (JIT) JIT, 2022.

49.  C. Zhao, X. Li, Z. Shao, and F. Wang, “Multi-Featured Spatial-Temporal and Dynamic Multi-Graph Convolutional Network for Metro Passenger Flow Prediction,” in (ConnectionScience) Connection Science, 2022, pp. 1252–1272. doi: 10.2139/ssrn.3989741.

50.  T. Liu, T. Yang, H. Yang, F. Languages, F. L. Teaching, and M. Sciences, “A Creative Computing Approach to Intelligent Second Class Management,” (IJEM) International Journal of Education and Management, 2022.

51.  Y. Wu and H. Yang, “CREATIVE COMPUTING-BASED MULTI-LEVEL VISUAL FEATURE,” in (MESM) International Middle Eastern Simulation and Modelling Conference, 2022, pp. 9–13.

52.  C. Li and H. Yang, “USING BREEZE FOR MODELLING SOFTWARE ARCHITECTURE OF COMPONENT-BASED SYSTEMS,” in (MESM) International Middle Eastern Simulation and Modelling Conference, 2022, pp. 192–195.

53.  H. Yang, Z. Lu, and A. Aesthetics, “Computerising Connections between Creativity and Aesthetics,” in (SOSE) SOSE, 2022.

54.  X. Xu, X. Zhang, H. Yang, and M. Sciences, “A Probability Parameter Estimation Tool in C ++,” in (DSA) DSA, 2022, pp. 518–523. doi: 10.1109/DSA56465.2022.00075.

55.  L. Liu and H. Yang, “Revisiting Hazard Analysis Requirements,” in (DSA) DSA, 2022, pp. 437–445. doi: 10.1109/DSA56465.2022.00064.

56.  C. Li, X. Zhang, and D. Chrysostomou, “ToD4IR : A Humanised Task-Oriented Dialogue System for Industrial Robots,” (IEEE Acess), vol. 14, no. 8, pp. 1–18, 2022.

57.  T. Liu, T. Yang, and H. Yang, “A Creative and Formal Approach to Humour Deconstruction for Computation,” (IJET) IJET, 2022.

58.  C. Xu, H. Ding, X. Zhang, C. Wang, and H. Yang, “A Data-Efficient Method of Deep Reinforcement Learning for Chinese Chess,” in (QRS), 2022.

59.  C. Li, D. Chrysostomou, and H. Yang, “A Natural Language-enabled Virtual Assistant for Human-Robot Interaction in Industrial Environments,” in (QRS), 2022.

60.  L. Zhu, L. Bai, X. Hao, and H. Yang, “A General Characterization of Representing Spatiotemporal Knowledge Graph based on OWL,” (QRS) IEEE 22nd International Conference on Software Quality, Reliability and Security Companion, QRS-C 2022, pp. 679–686, 2022, doi: 10.1109/QRS-C57518.2022.00108.

61.  C. Zeng, J. Zhou, and H. Yang, “Generation of Creativity with Inspiration from Synaesthesia,” in (NMDME) Proceedings of the 2nd International Conference on New Media Development and Modernized Education, 2022, pp. 560–570. doi: 10.5220/0011916000003613.

62.  E. Y. Baitei et al., “28P Epithelial mesenchymal transition confers resistance to dual PDL1-VEGF inhibition in relapsed mesothelioma,” (JIOT) Journal of Immuno-Oncology and Technology, vol. 16, p. 100133, 2022, doi: 10.1016/j.iotech.2022.100133.

63.  Y. Essa, H. Yang, and D. Fennell, “Clonal biallelic inactivation of NF2 is an evolutionary bottleneck that exposes a vulnerability to CDK7 inhibition in mesothelioma,” (CR) Cancer Research, vol. 82, 2022.

64.  T. Wang, X. Hu, and H. Yang, “A Distributed Design of Ripple-Spreading Algorithms for Path Optimization Problems Gong-Peng Zhang,” (IJCAT) International Journal of Computer Applications in Technology, vol. X, 2021.

65.  R. Millham, I. E. Agbehadji, and H. Yang, “Pattern Mining Algorithms,” in (Book Chapter) Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing, Springer Berlin Heidelberg, 2021, pp. 67–80. doi: 10.1007/978-981-15-6695-0_4.

66.  R. Millham, I. E. Agbehadji, and H. Yang, “Extracting Association Rules: Meta-Heuristic and Closeness Preference Approach,” in (Book Chapter) Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing, Springer Berlin Heidelberg, 2021, pp. 81–95. doi: 10.1007/978-981-15-6695-0_5.

67.  R. Millham, I. E. Agbehadji, and H. Yang, “Parameter Tuning onto Recurrent Neural Network and Long Short-Term Memory (RNN-LSTM) Network for Feature Selection in Classification of High-Dimensional Bioinformatics Datasets,” in (Book Chapter) Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing, Springer Berlin Heidelberg, 2021, pp. 21–42. doi: 10.1007/978-981-15-6695-0_2.

68.  R. Millham, I. E. Agbehadji, and H. Yang, “The Big Data Approach Using Bio-Inspired Algorithms: Data Imputation,” in (Book Chapter) Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing, Springer Berlin Heidelberg, 2021, pp. 1–19. doi: 10.1007/978-981-15-6695-0_1.

69.  I. E. Agbehadji and H. Yang, “Data Visualization Techniques and Algorithms,” in (Book Chapter) Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing, Springer Berlin Heidelberg, 2021, pp. 195–205. doi: 10.1007/978-981-15-6695-0_10.

70.  C. Zhao, L. Li, H. Sun, and H. Yang, “Multi-Scenario Evolutionary Game of Rumor-Affected Enterprises under Demand Disruption,” (Sustainability) Sustainability, vol. 13, no. 1, 2021.

71.  C. Zhao, Y. Song, and M. Zuo, “Performance Analysis for Green Food in Dual-Channel Supply Chain Considering Fairness Concern,” (IJPE) International Journal of Performability Engineering, vol. xx, no. x, pp. 563–570, 2021, doi: 10.1109/qrs-c51114.2020.00098.

72.  X. Zhao, F. Li, and H. Yang, “Extracting Satisfiability-preserving Modules from the OWL RL Ontology for Efficient Reasoning,” (IEEE Access) IEEE Access, pp. 1–1, 2021, doi: 10.1109/access.2021.3056556.

73.  M. Zhang et al., “Clonal architecture in mesothelioma is prognostic and shapes the tumour microenvironment,” (Nature) Nature Communications, pp. 1–12, 2021, doi: 10.1038/s41467-021-21798-w.

74.  H. Zhou, X.-B. Hu, J. Zhou, and H. Yang, “An Efficient Genetic Method for Multi-objective Location Optimization of Multiple City Air Terminals,” (IEEE Access) IEEE Access, vol. 9, pp. 108665–108674, 2021, doi: 10.1109/access.2021.3101279.

75.  C. Zhao, L. Liu, and H. Yang, “Multiscenario Analyses Between Front and Back End Investment in Software Reliability: An Evolutionary Game Perspective,” (TR) IEEE Transactions on Reliability, 2021, doi: 10.1109/TR.2021.3118884.

76.  H. Yang and Z. Lu, “Speculating on Research Trends in Emotions and Artificial Creativity,” (SOSE) 15th IEEE International Conference on Service-Oriented System Engineering, SOSE, pp. 28–32, 2021, doi: 10.1109/SOSE52839.2021.00008.

77.  I. Zhao, M. Zhang, and H. Yang, “Vertical Scaling of Resource for OpenMP Application,” in (ICSOC) LNCS 13121, Springer International Publishing, 2021, pp. 839–849. doi: 10.1007/978-3-030-91431-8_61.

78.  Y. Wu and H. Yang, “A Rule-Based Approach to Painting Technique Selection to Convey Latent Semantics,” in (NCS) National Computer Symposium, 2021.

79.  Z. Lu, J. Luo, and H. Yang, “Emotions Behind Divergent Thinking,” in (DSA) IEEE Dependable Systems and their Applications, 2021, pp. 566–571. doi: 10.1109/dsa52907.2021.00083.

80.  P.-S. Huang, F. Fahmi, F.-J. Wang, and H. Yang, “Constructing A Creative Service Software with Semantic Web,” in (DSA) IEEE Dependable Systems and their Applications, 2021, pp. 499–507. doi: 10.1109/dsa52907.2021.00074.

81.  S. Zheng, H. Liu, and H. Yang, “A Survey of Story-Generation Apps and Online Systems between 2017 and 2020,” in (DSA) IEEE Dependable Systems and their Applications, 2021, pp. 390–398. doi: 10.1109/dsa52907.2021.00059.

82.  F. Fahmi, P. S. Huang, F. J. Wang, and H. Yang, “Constructing a Creative Software with Services,” (SCC) IEEE International Conference on Services Computing, SCC 2021, pp. 134–144, 2021, doi: 10.1109/SCC53864.2021.00026.

83.  T. Liu, H. Yang, and T. Yang, “A Cognitive Humour Classification for Creative Generation,” (IJEM) International Journal of Education and Management, vol. 6, no. 4, pp. 74–76, 2021.

84.  Z. Lu and H. Yang, “An Emotion-Oriented System for Creativity Stimulation,” in (QRS) IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C), IEEE, 2021, pp. 184–191. doi: 10.1109/QRS-C55045.2021.00035.

85.  H. Yang and T. Liu, “The Influence of Handwriting and Wor-Processing on Creativity in the Fictions,” in (QRS) IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C), IEEE, 2021, pp. 1145–1152. doi: 10.1109/QRS-C55045.2021.00169.

86.  X. Zhang et al., “Stock Prediction with Stacked-LSTM Neural Networks,” in (QRS) IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C), IEEE, 2021, pp. 1119–1125. doi: 10.1109/QRS-C55045.2021.00166.

87.  F. Wang, F. Fahmi, and H. Yang, “A Research Agenda for Constructing an Environment to Help Develop a Creative Software,” in (QRS) IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C), IEEE, 2021, pp. 454–462. doi: 10.1109/QRS-C55045.2021.00073.

88.  H. Zhang and H. Yang, “Modelling influence of big data analytic capability on enterprise performance : mediating effect of strategic flexibility,” (IJMIC)), vol. x, no. x, 2021.

89.  C. Li and H. Yang, “Bot-X: An AI-based Virtual Assistant for Intelligent Manufacturing,” (MAGS) Multiagent and Grid Systems, vol. 17, pp. 1–14, 2021, doi: 10.3233/MGS-210340.

90.  T. C. Hsu, H. Yang, Y. C. Chung, and C. H. Hsu, “A Creative IoT agriculture platform for cloud fog computing,” (SCIS) Sustainable Computing: Informatics and Systems, 2020, doi: 10.1016/j.suscom.2018.10.006.

91.  F. Dai, Q. Mo, Z. Qiang, B. Huang, W. Kou, and H. Yang, “A Choreography Analysis Approach for Microservice Composition in Cyber-Physical-Social Systems,” IEEE Access, vol. 8, pp. 53215–53222, 2020, doi: 10.1109/ACCESS.2020.2980891.

92.  I. Gai, S. Zheng, H. Yu, and H. Yang, “Software defect prediction based on weighted extreme learning machine,” (MAGS) Multiagent and Grid Systems, vol. 16, no. 3, pp. 67–82, 2020, doi: 10.3233/mgs-200321.

93.  F. Dai, Q. Mo, Z. Qiang, B. Huang, W. Kou, and H. Yang, “A Choreography Analysis Approach for Microservice Composition in Cyber-Physical-Social Systems,” (IEEE Access) IEEE Access, vol. 8, pp. 53215–53222, 2020, doi: 10.1109/ACCESS.2020.2980891.

94.  Y. Tian, D. Jing, C. Yang, Y. Chen, and H. Yang, “An Ontological Approach for Architecture Design of a Smart Tourism System-of-Systems,” (IJPE) International Journal of Performability Engineering, vol. 16, no. 4, pp. 587–598, 2020, doi: 10.23940/ijpe.20.04.p10.587598.

95.  F. Dai and H. Yang, “Refactoring business process models with process fragments substitution,” (WN) Wireless Networks, vol. 3, 2020, doi: 10.1007/s11276-020-02367-3.

96.  L. Zou, H. Yang, and M. Al-Akaidi, “A Creative Computing Approach to Dimentionalising the Data-Information- Knowledge-Wisdom Model,” in (AUEIRC) AUEIRC, 2020.

97.  X. Bai, H. Zhou, and H. Yang, “An HVSM-based GRU Approach to Predict Cross-Version Software Defects,” (IJPE) International Journal of Performability Engineering, vol. 16, no. 6, pp. 979–990, 2020, doi: 10.23940/ijpe.20.06.p16.979990.

98.  D. Jing, Y. Tian, C. Zhang, C. Yang, and H. Yang, “Knowledge-based semantic reasoning for creativity,” (IJPE) International Journal of Performability Engineering, vol. 16, no. 5, pp. 800–810, 2020, doi: 10.23940/ijpe.20.05.p14.800810.

99.  H. Guan, C. Jia, and H. Yang, “Intelligent recognition of semantic relationships based on antonymy,” (MAGS) Multiagent and Grid Systems, vol. 16, no. 3, pp. 263–290, 2020, doi: 10.3233/MGS-200332.

100.         F. Ma and H. Yang, “An Intelligent Health Analysis Approach to Detecting Potential Threats with Health Data Reuse,” in (COMPSAC) Computer Software and Applications Conference, 2000. COMPSAC 2000, the 24th Annual International, 25-27 Oct. 2000 Pages: 223 - 227, 2020, pp. 1546–1551. doi: 10.1109/COMPSAC48688.2020.00-35.

101.         T. Ma, H. Liu, and H. Yang, “Interactive Narrative Generation of Aesthetics of Violence in Films,” in (ICCLC) 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C), 2020, pp. 656–661. doi: 10.1109/QRS-C51114.2020.00111.

102.         T. Liu, H. Yang, and F. Wang, “A Creative Approach to Humour Degree Calculation for Utterances,” in (ICCLC) 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C), 2020, pp. 649–655. doi: 10.1109/QRS-C51114.2020.00110.

103.         X. Bai, H. Zhou, H. Yang, and D. Wang, “Connecting historical changes for cross-version software defect prediction,” (IJCAT) International Journal of Computer Applications in Technology, vol. 63, no. 4, p. 371, 2020, doi: 10.1504/ijcat.2020.10032601.

104.         A. Balderas, J. Doder, and H. Yang, “End-User development challenges for creative computing,” (IxDA) Interactive design and Architecture Journal, pp. 177–179, 2020.

105.         Y. Wu, H. Yang, Z. Lu, Y. Liu, and C. Zeng, “Measuring Significance of Factors Influencing Effectiveness of Visual Elements in Advertisement and An Approach Proposal,” in (MESM) MESM20, 2020, pp. 1–13.

106.         H. Bi, H. Zhou, J. Yang, H. Yang, U. Kingdom, and Z. Liang, “A Survey on Blockchain : Architecture , Applications , Challenges , and Future Trends,” in (CPSCom) CPSCom, 2020.

107.         H. Xue, H. Zhou, B. Huang, H. Yang, U. Kingdom, and M. Qin, “Edge Computing for Internet of Things : A Survey,” in (CPSCom) CPSCom, 2020.

108.         W. Hou, Y. Xie, Z. Li, H. Yang, and Z. Hu, “Preliminary study on the multispectral measurement simulations of polarized scanning atmospheric corrector image,” in (SPIE) Proc. SPIE 11566, AOPC 2020: Optical Spectroscopy and Imaging; and Biomedical Optics, 2020.

I.      Du, Z. Liang, Y. Huang, Z. Guo, H. Yang, and S. Wang, “Performance Optimisation Method of PBFT Consensus for Supply Chain Integration SVM,” in (DSA) IEEE Dependable Systems and Their Applications, 2020. doi: 10.1109/DSA51864.2020.00002.

109.         Q. Liu, M. Al-Akaidi, and H. Yang, “A Machine Learning based Associating Degree Predicting Algorithms Applying in Tourism Areas,” (Mesm) Mesm20, 2020.

110.         Y. Wu, H. Yang, Z. Lu, Y. Liu, and C. Zeng, “Measuring Significance of Factors Influencing Effectiveness of Visual Elements in Advertisement and An Approach Proposal,” (Mesm) Mesm20, pp. 1–13, 2020.