12 citations · 12 across the 12 of their papers we have counts for
14 papers
Extending FAIR Principles with Observability for Trustworthy Federated Learning
Hangli Ge, Noboru Koshizuka
Federated learning (FL) keeps data at its source, but locality alone does not make a federation trustworthy. Without sufficient observability, an aggregator cannot determine whethe…
Anomaly Detection and Localization for the Pantograph-Catenary System
Francesco Vitale, Hangli Ge, Francesco Flammini
Monitoring the Pantograph-Catenary System (PCS) provides insight into the health conditions of the pantograph and the railway infrastructure. Recent industrial solutions trace the…
Cyberspace Search Intentions as Leading Indicators for Proactive Traffic Hotspot Detection
Hangli Ge, Dizhi Huang, Takeshi Kawasaki +1
This study proposes a cyber-physical data-driven framework for proactive detection of highway traffic hotspots and hot regions. The proposed framework bridges users' online search…
Place with Intention: An Empirical Attendance Predictive Study of Expo 2025 Osaka, Kansai, Japan
Xiaojie Yang, Dizhi Huang, Hangli Ge +4
Accurate forecasting of daily attendance is vital for managing transportation, crowd flows, and services at large-scale international events such as Expo 2025 Osaka, Kansai, Japan.…
Realizing Space-oriented Control in Smart Buildings via Word Embeddings
Hangli Ge, Hiroaki Mori, Yasuhira Chiba +1
This paper presents a novel framework for implementing space-oriented control systems in smart buildings. In contrast to conventional device-oriented approaches, which often suffer…
Deep Unfolding for MIMO Signal Detection
Hangli Ge, Noboru Koshizuka
In this paper, we propose a deep unfolding neural network-based MIMO detector that incorporates complex-valued computations using Wirtinger calculus. The method, referred as Dynami…
Simulation of Emergency Evacuation in Large Scale Metropolitan Railway Systems for Urban Resilience
Hangli Ge, Xiaojie Yang, Zipei Fan +2
This paper presents a simulation for traffic evacuation during railway disruptions to enhance urban resilience. The research focuses on large-scale railway networks and provides fl…
Origin-Destination Extraction from Large-Scale Route Search Records for Tourism Trend Analysis
Hangli Ge, Dizhi Huang, Xiaojie Yang +4
This paper presents a novel method for transforming large-scale historical expressway route search records into a three-dimensional (3D) Origin-Destination (OD) map, enabling data…
Causality-Aware Next Location Prediction Framework based on Human Mobility Stratification
Xiaojie Yang, Zipei Fan, Hangli Ge +3
Human mobility data are fused with multiple travel patterns and hidden spatiotemporal patterns are extracted by integrating user, location, and time information to improve next loc…
A Traffic Evacuation Model for Enhancing Resilience During Railway Disruption
Hangli Ge, Xiaojie Yang, Jinyu Chen +2
This paper introduces a traffic evacuation model for railway disruptions to improve resilience. The research focuses on the problem of failure of several nodes or lines on the rail…
CausalMob: Causal Human Mobility Prediction with LLMs-derived Human Intentions toward Public Events
Xiaojie Yang, Hangli Ge, Jiawei Wang +4
Large-scale human mobility exhibits spatial and temporal patterns that can assist policymakers in decision making. Although traditional prediction models attempt to capture these p…
Time-Probability Dependent Knowledge Extraction in IoT-enabled Smart Building
Hangli Ge, Hirotsugu Seike, Noboru Koshizuka
Smart buildings incorporate various emerging Internet of Things (IoT) applications for comprehensive management of energy efficiency, human comfort, automation, and security. Howev…
FRTP: Federating Route Search Records to Enhance Long-term Traffic Prediction
Hangli Ge, Xiaojie Yang, Itsuki Matsunaga +2
Accurate traffic prediction, especially predicting traffic conditions several days in advance is essential for intelligent transportation systems (ITS). Such predictions enable mid…
Efficient Compressed Ratio Estimation Using Online Sequential Learning for Edge Computing
Hiroki Oikawa, Hangli Ge, Noboru Koshizuka
Owing to the widespread adoption of the Internet of Things, a vast amount of sensor information is being acquired in real time. Accordingly, the communication cost of data from edg…