Yajing Huang
Biographic Data
| ID | 9699018 |
|---|---|
| NAME | Yajing Huang |
| GIVEN NAMES | Yajing |
| FAMILY NAME | Huang |
| SIGNATURE | HUANG Y |
| AFFILIATIONS | Guizhou Normal University |
| ORCID | 0009-0009-0318-5462 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Cora-Tdppo
The advancements in deep learning and edge computing have driven artificial intelligence (AI) applications to the edge. However, challenges such as heterogeneous, resource-constrained edge devices, inference congestion, and dynamic environments hinder the development of edge intelligence (EI). To maximize the average quality of service (QoS) for EI, we formulate an optimization problem that aims to balance inference latency and accuracy while con…
The dynamics of personality, risk, and choice
Adventure tourism has grown rapidly, attracting individuals with diverse personality profiles and risk preferences. This study investigates how the Big Five Personality Traits, specifically extraversion, openness, and neuroticism, influence adventure tourism choices and how psychological risk preference moderates these relationships. Using stratified random sampling, 650 questionnaires were distributed, and 617 were collected. After excluding inc…
No prominent works on this page.
The dynamics of personality, risk, and choice
Adventure tourism has grown rapidly, attracting individuals with diverse personality profiles and risk preferences. This study investigates how the Big Five Personality Traits, specifically extraversion, openness, and neuroticism, influence adventure tourism choices and how psychological risk preference moderates these relationships. Using stratified random sampling, 650 questionnaires were distributed, and 617 were collected. After excluding inc…
Cora-Tdppo
The advancements in deep learning and edge computing have driven artificial intelligence (AI) applications to the edge. However, challenges such as heterogeneous, resource-constrained edge devices, inference congestion, and dynamic environments hinder the development of edge intelligence (EI). To maximize the average quality of service (QoS) for EI, we formulate an optimization problem that aims to balance inference latency and accuracy while con…
Adventure (1 work) · Adventure Sports and Sensation Seeking (1 work) · Advertising (1 work) · Business (1 work) · Computer Science (1 work) · Decomposition (1 work) · Edge computing (1 work) · Enhanced Data Rates for GSM Evolution (1 work) · Ferroelectric and Negative Capacitance Devices (1 work) · Geography (1 work)