Yalin Yang
Biographic Data
| ID | 8308465 |
|---|---|
| NAME | Yalin Yang |
| GIVEN NAMES | Yalin |
| FAMILY NAME | Yang |
| SIGNATURE | YANG Y |
| AFFILIATIONS | Chengdu University of Technology |
| ORCID | 0000-0002-2561-0759 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Where Matters
Does where an incident happens affect how quickly first responders arrive? Timely emergency responses are important to urban safety. However, the combined influence of street-level environments, operational conditions, and neighborhood contexts on dispatch performance remains unclear. We examined such geographical complexity by modeling geographic predictors for whether emergency vehicles successfully arrived at incidents in the city of Dallas wi…
An Analysis of Factors Influencing Chatbots on College Students’ Programming Self-learning Ability
Against the backdrop of the deep integration of chatbots into education, this study, based on Self-Determination Theory (SDT) and the UTAUT model, constructed a model of factors influencing college students’ self-directed learning ability in programming. Through a review of existing literature, six key determinants were identified: learning expectancy, effort expectancy, facilitation conditions, teaching interaction, learning motivation, and lear…
What Local Environments Drive Opportunities for Social Events? A New Approach Based on Bayesian Modeling in Dallas, Texas, USA
In-person social events bring people to places, while people and places influence where and what social events occur. Knowing what people do and where they build social relationships gives insights into the distribution and availability of places for social functions. We developed a Bayesian Network model, integrating points of interest (POIs) and sociodemographic characteristics, to estimate the probabilistic effects of places and people on the …
Research on Deep Cooperation and Collaborative Development Between China and Indonesia Cross-Border E-commerce Based on Silk Road E-Commerce
With the rapid development of "Silk Road E-commerce", the cross-border e-commerce cooperation between China and countries along the "Belt and Road" is gradually deepening. As a major e-commerce country and the initiator of "Silk Road E-Commerce", China has rich experience and a good material foundation. As the largest economy of ASEAN and one of the partner countries of "Silk Road E-Commerce", Indonesia has a broad market and a huge consumer base…
Age-related differences of different components of working memory
摘要: 采用选择/无选范式, 借助工作记忆成套测验, 在两位数乘法估算问题中探讨了工作记忆系统各成分对不同年龄段个体算术策略运用的预测效应。结果显示:(1) 工作记忆的不同成分与年龄之间存在明显的相关。表现为, 除视空模板成分外, 其他各成分得分随着年龄增长而呈现上升趋势; (2) 估算策略运用中, 年龄与策略选择显著相关, 表现为随着年龄增长, 策略选择表现明显提高; (3) 估算策略运用中, 不同年龄个体的工作记忆不同成分和策略选择表现出不同的联系, 中央执行均显示出显著的预测效应, 语音环路和视空模板的预测效应均不显著。不同年龄个体的工作记忆不同成分对策略执行的预测效应均不显著。上述发现对于深刻理解工作记忆系统在算术认知策略运用中的作用机制具有重要理论含义
No prominent works on this page.
Age-related differences of different components of working memory
摘要: 采用选择/无选范式, 借助工作记忆成套测验, 在两位数乘法估算问题中探讨了工作记忆系统各成分对不同年龄段个体算术策略运用的预测效应。结果显示:(1) 工作记忆的不同成分与年龄之间存在明显的相关。表现为, 除视空模板成分外, 其他各成分得分随着年龄增长而呈现上升趋势; (2) 估算策略运用中, 年龄与策略选择显著相关, 表现为随着年龄增长, 策略选择表现明显提高; (3) 估算策略运用中, 不同年龄个体的工作记忆不同成分和策略选择表现出不同的联系, 中央执行均显示出显著的预测效应, 语音环路和视空模板的预测效应均不显著。不同年龄个体的工作记忆不同成分对策略执行的预测效应均不显著。上述发现对于深刻理解工作记忆系统在算术认知策略运用中的作用机制具有重要理论含义
Research on Deep Cooperation and Collaborative Development Between China and Indonesia Cross-Border E-commerce Based on Silk Road E-Commerce
With the rapid development of "Silk Road E-commerce", the cross-border e-commerce cooperation between China and countries along the "Belt and Road" is gradually deepening. As a major e-commerce country and the initiator of "Silk Road E-Commerce", China has rich experience and a good material foundation. As the largest economy of ASEAN and one of the partner countries of "Silk Road E-Commerce", Indonesia has a broad market and a huge consumer base…
What Local Environments Drive Opportunities for Social Events? A New Approach Based on Bayesian Modeling in Dallas, Texas, USA
In-person social events bring people to places, while people and places influence where and what social events occur. Knowing what people do and where they build social relationships gives insights into the distribution and availability of places for social functions. We developed a Bayesian Network model, integrating points of interest (POIs) and sociodemographic characteristics, to estimate the probabilistic effects of places and people on the …
An Analysis of Factors Influencing Chatbots on College Students’ Programming Self-learning Ability
Against the backdrop of the deep integration of chatbots into education, this study, based on Self-Determination Theory (SDT) and the UTAUT model, constructed a model of factors influencing college students’ self-directed learning ability in programming. Through a review of existing literature, six key determinants were identified: learning expectancy, effort expectancy, facilitation conditions, teaching interaction, learning motivation, and lear…
Where Matters
Does where an incident happens affect how quickly first responders arrive? Timely emergency responses are important to urban safety. However, the combined influence of street-level environments, operational conditions, and neighborhood contexts on dispatch performance remains unclear. We examined such geographical complexity by modeling geographic predictors for whether emergency vehicles successfully arrived at incidents in the city of Dallas wi…
Computer Science (2 works) · Arithmetic (1 work) · Artificial Intelligence (1 work) · Bayesian probability (1 work) · Business (1 work) · China (1 work) · Cognition (1 work) · Cognitive and developmental aspects of mathematical skills (1 work) · Cognitive psychology (1 work) · Commerce (1 work)