Vol. 4 No. 1 (2026)

Research Article

• EXPERIENCE ECONOMY–DRIVEN INNOVATION IN FIVE-STAR HOTELS: SOMATOSENSORY INTERACTION AND PARENT–CHILD EXPERIENCE SPACES

  XiaoQing Wang^*

  Published: 2026-03-09 | DOI: https://doi.org/10.61784/wjit3084

  64-70

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• THE CONSTRUCTION, EVALUATION, AND APPLICATION OF AN INTELLIGENT ADMISSIONS Q&A SYSTEM BASED ON RETRIEVAL-AUGMENTED GENERATION (RAG)

  JiaXin Wang , ZiHan Qi , JingJing Li , XuanEr Chen , Yuan Lin^*

  Published: 2026-03-09 | DOI: https://doi.org/10.61784/wjit3083

  53-63

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• PREDICTING OLYMPIC MEDAL DISTRIBUTION FOR LA 2028 BASED ON K-MEANS CLUSTERING AND AN XGBOOST-BOOTSTRAP ENSEMBLE

  YiMing Feng^* , HaoShuai Yu , LinYu Zhuo

  Published: 2026-03-09 | DOI: https://doi.org/10.61784/wjit3082

  48-52

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• U-NET MEDICAL IMAGE SEGMENTATION STUDY BASED ON CBAM ATTENTION MECHANISM

  MengYuan Cao^* , WenXuan Hong , XinRui Li , JiaLu Zhao

  Published: 2026-03-05 | DOI: https://doi.org/10.61784/wjit3081

  41-47

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• DESIGNING AN EFFICIENT RESEARCH OUTPUT MANAGEMENT SYSTEM FOR TECHNOLOGY TRANSFER

  Jun Wang^* , Xiang Wei , JiaLei Mo , Fan Wang , MingYuan Liu

  Published: 2026-03-02 | DOI: https://doi.org/10.61784/wjit3080

  33-40

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• PREDICTING FOLLOWER GROWTH FOR SOCIAL MEDIA BLOGGERS AND MODELING USER FOLLOWING BEHAVIOR USING XGBOOST AND RANDOM FOREST ENSEMBLE LEARNING

  ZhiYang Chen^* , JiaXin Wu

  Published: 2026-02-10 | DOI: https://doi.org/10.61784/wjit3079

  25-32

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• PARTIAL NONLINEAR FUNCTIONAL REGRESSION MODEL: AN APPROACH VIA REPRODUCING KERNEL AND ENSEMBLE LEARNING

  JiaYi Wang^* , Yuan Chen , YanRan Liu , HaoDi Lv

  Published: 2026-01-20 | DOI: https://doi.org/10.61784/wjit3078

  19-24

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• PREDICTING DRUG TOXICITY ON TOX21 WITH A MULTI-TASK GNN-TRANSFORMER MODEL

  YuHui Li^*

  Published: 2026-01-20 | DOI: https://doi.org/10.61784/wjit3077

  13-18

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• EVALUATION OF THE IMPLEMENTATION EFFECT OF INTELLECTUAL PROPERTY POLICY BASED ON NAIVE BAYES ALGORITHM

  ShuTong Wei^*

  Published: 2026-01-19 | DOI: https://doi.org/10.61784/wjit3076

  8-12

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• MULTI-FEATURE INTEGRATED INTELLIGENT DIAGNOSIS MODEL FOR NON-INVASIVE PRENATAL TESTING BASED ON ENSEMBLE LEARNING

  KangYong Wang^*

  Published: 2026-01-04 | DOI: https://doi.org/10.61784/wjit3075

  1-7

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