5 citations · 9 across the 11 of their papers we have counts for
12 papers
Resource-Aware Model Selection for Scalable Indoor Localization on HPC Platforms
Fukuharu Tanaka, Hamada Rizk, Moustafa Youssef +1
Large-scale indoor localization is increasingly needed in campuses, smart buildings, factories, and digital-twin infrastructures, where wireless conditions, access-point deployment…
Optimizing Nursing Care Taxi Dispatch Leveraging Integer Linear Programming Solvers and Machine Learning
Riku Nakao, Akihito Hiromori, Hamada Rizk +1
In this paper, we formulate a new vehicle dispatch optimization problem, called Nursing Care Taxi Dispatch, as a variant of the Vehicle Routing Problem, considering constraints rel…
Human-Flow Digital Twin for Predicting the Effects of Mobility Introduction on Visitor Circulation
Chiharu Shima, Haruki Yonekura, Fukuharu Tanaka +2
We propose a framework for predicting the effects of mobility introduction measures using a human-flow digital twin. This digital twin incorporates a multi-agent simulator that can…
Learning Displacement-Robust Representations for Landslide Early Warning under Rainfall Forecast Uncertainty
Ren Ozeki, Hamada Rizk, Hirozumi Yamaguchi
Rainfall-induced landslides pose a growing risk worldwide as climate change intensifies extreme rainfall events. To provide sufficient evacuation time, landslide early warning syst…
Pedestrian-Aware LLM-Driven Behavioral Planning for Autonomous Vehicles
Aidana Baimbetova, Haruki Yonekura, Hamada Rizk +1
Autonomous Vehicles (AVs) must make reliable decisions in dense urban environments where pedestrian behavior is variable, sometimes abnormal, and often unseen during training. Rein…
Energy-Free Sensing and Context Recognition Using Photovoltaic Cells
Kaede Shintani, Hamada Rizk, Hirozumi Yamaguchi
The field of energy-free sensing and context recognition has recently gained significant attention as it allows operating systems without external power sources. Photovoltaic cells…
Restoring Super-High Resolution GPS Mobility Data
Haruki Yonekura, Ren Ozeki, Hamada Rizk +1
This paper presents a novel system for reconstructing high-resolution GPS trajectory data from truncated or synthetic low-resolution inputs, addressing the critical challenge of ba…
TimeSense: Multi-Person Device-free Indoor Localization via RTT
Mohamed Mohsen, Hamada Rizk, Hirozumi Yamaguch +1
Locating the persons moving through an environment without the necessity of them being equipped with special devices has become vital for many applications including security, IoT,…
Privacy-Preserved Taxi Demand Prediction System Utilizing Distributed Data
Ren Ozeki, Haruki Yonekura, Hamada Rizk +1
Accurate taxi-demand prediction is essential for optimizing taxi operations and enhancing urban transportation services. However, using customers' data in these systems raises sign…
CROSS-Net: Region-Agnostic Taxi-Demand Prediction Using Feature Disentanglement
Ren Ozeki, Haruki Yonekura, Aidana Baimbetova +2
The growing demand for ride-hailing services has led to an increasing need for accurate taxi demand prediction. Existing systems are limited to specific regions, lacking generality…
Eco-Friendly Sensing for Human Activity Recognition
Kaede Shintani, Hamada Rizk, Hirozumi Yamaguchi
With the increasing number of IoT devices, there is a growing demand for energy-free sensors. Human activity recognition holds immense value in numerous daily healthcare applicatio…
Privacy-Preserving Taxi-Demand Prediction Using Federated Learning
Yumeki Goto, Tomoya Matsumoto, Hamada Rizk +2
Taxi-demand prediction is an important application of machine learning that enables taxi-providing facilities to optimize their operations and city planners to improve transportati…