Vol. 2 No. 6 (2026)

					View Vol. 2 No. 6 (2026)

All articles published in this issue have undergone a thorough peer review process, and stringent checks for repetition rates have been implemented to ensure the integrity of the content.

Total number of articles in this issue: 7
Total number of pages in this issue: 50

For inquiries regarding the content of specific articles, please feel free to contact the respective authors via their provided email addresses. For questions related to the journal itself, please reach out directly to SUAS Press.

Published: 2025-11-04

Articles

  • Authors: Yinlei Chen
    Resource Type: Article
    Disciplines: Artificial Intelligence and Intelligence | Subjects: Deep Learning
    Publication ID: v2n6a01
    Abstract: We propose a novel deep learning approach to asset pricing that predicts individual stock returns using daily data while integrating no-arbitrage constraints and capturing market dynamics. Our model combines Long Short-Term Memory (LSTM) networks,...
    1-10
    DOI Icon Abstract views: 21 | DOI Icon PDF downloads: 10 | DOI Icon references: 20
    DOI Icon DOI: 10.70393/6a6374616d.333235
    DOI Icon ARK: ark:/40704/JCTAM.v2n6a01
  • Authors: Zengyi Huang
    Resource Type: Article
    Disciplines: Software Technology | Subjects: Software Engineering
    Publication ID: v2n6a02
    Abstract: Artificial intelligence (AI) has taken a leading position in various fields, especially in the development of information solutions. This article presents a case study of mobile application user interface redesign to highlight the benefits and...
    11-14
    DOI Icon Abstract views: 45 | DOI Icon PDF downloads: 8 | DOI Icon references: 9
    DOI Icon DOI: 10.70393/6a6374616d.333236
    DOI Icon ARK: ark:/40704/JCTAM.v2n6a02
  • Authors: Sichong Huang
    Resource Type: Article
    Disciplines: Big Data Technology | Subjects: Data Analytics
    Publication ID: v2n6a03
    Abstract: Addressing the issue of insufficient accuracy in procurement demand forecasting under market volatility, this study investigates the Prophet model with exogenous variables. It outlines the comprehensive workflow encompassing data preprocessing,...
    15-20
    DOI Icon Abstract views: 25 | DOI Icon PDF downloads: 15 | DOI Icon references: 5
    DOI Icon DOI: 10.70393/6a6374616d.333237
    DOI Icon ARK: ark:/40704/JCTAM.v2n6a03
  • Authors: Sichong Huang
    Resource Type: Article
    Disciplines: Artificial Intelligence | Subjects: Deep Learning
    Publication ID: v2n6a04
    Abstract: Given the complex fluctuations and extended forecasting cycles inherent in retail inventory, this study investigates the application of LSTM deep learning models for inventory time series forecasting. It details the model architecture design,...
    21-25
    DOI Icon Abstract views: 18 | DOI Icon PDF downloads: 10 | DOI Icon references: 5
    DOI Icon DOI: 10.70393/6a6374616d.333238
    DOI Icon ARK: ark:/40704/JCTAM.v2n6a04
  • Authors: Xueyi Cheng
    Resource Type: Article
    Disciplines: Big Data Technology | Subjects: Data Analytics
    Publication ID: v2n6a05
    Abstract: Financial forecasting models tend to be based on past market action trends. While such methods are very good under steady-state conditions, financial markets tend to change abruptly due to a change in liquidity, macroeconomic news, or leverage...
    26-30
    DOI Icon Abstract views: 23 | DOI Icon PDF downloads: 8 | DOI Icon references: 10
    DOI Icon DOI: 10.70393/6a6374616d.333332
    DOI Icon ARK: ark:/40704/JCTAM.v2n6a05
  • Authors: Zan Li, Yida Zhu
    Resource Type: Article
    Disciplines: Artificial Intelligence and Intelligence | Subjects: Machine Learning
    Publication ID: v2n6a06
    Abstract: Culturally-responsive AI mentorship agents represent a substantial change in educational technology, addressing critical gaps between personalized learning systems and students' psychological needs for belonging. This research presents a...
    31-43
    DOI Icon Abstract views: 19 | DOI Icon PDF downloads: 10 | DOI Icon references: 45
    DOI Icon DOI: 10.70393/6a6374616d.333334
    DOI Icon ARK: ark:/40704/JCTAM.v2n6a06
  • Authors: Xiangmin Li
    Resource Type: Article
    Disciplines: Statistical Analysis | Subjects: Data Mining
    Publication ID: v2n6a07
    Abstract: This study proposes a framework for a dynamic decision-making model based on Customer Lifetime Value (CLV) to optimize sales resources. This model prioritizes profitability as a benchmark for customer performance, serving as a guide for effective...
    44-50
    DOI Icon Abstract views: 22 | DOI Icon PDF downloads: 12 | DOI Icon references: 14
    DOI Icon DOI: 10.70393/6a6374616d.333335
    DOI Icon ARK: ark:/40704/JCTAM.v2n6a07