7 citations · 16 across the 13 of their papers we have counts for
14 papers
Toward Practical Decentralized Proof-of-Location via Physical Witnessing Zones
Tamor Tomson, Eduardo Brito, Amnir Hadachi +1
Digital services increasingly rely on claims that a person, device, or asset was in a specific place at a specific time. Today, those claims often depend on self-reported location…
Beyond Dark Knowledge: Mixup-Based Distillation for Reliable Predictions
José Medina, Paul Honeine, Abdelaziz Bensrhair +1
Knowledge Distillation (KD) and mixup have proven effective at inducing smoothness in class boundaries; KD captures inherent class relationships in probability distributions, and m…
Decentralized Proof-of-Location for Content Provenance: Towards Capture-Time Authenticity
Eduardo Brito, Fernando Castillo, Amnir Hadachi +2
Reliable use of real-world data requires confidence that recorded evidence reflects what actually occurred at the moment of capture. In adversarial or incentive-misaligned cyber-ph…
A Taxonomy and Methodology for Proof-of-Location Systems
Eduardo Brito, Fernando Castillo, Liina Kamm +2
Digital societies increasingly rely on trustworthy proofs of physical presence for services such as supply-chain tracking, e-voting, ride-sharing, and location-based rewards. Yet,…
Mamba base PKD for efficient knowledge compression
José Medina, Amnir Hadachi, Paul Honeine +1
Deep neural networks (DNNs) have remarkably succeeded in various image processing tasks. However, their large size and computational complexity present significant challenges for d…
Knowledge Distillation Neural Network for Predicting Car-following Behaviour of Human-driven and Autonomous Vehicles
Ayobami Adewale, Chris Lee, Amnir Hadachi +1
As we move towards a mixed-traffic scenario of Autonomous vehicles (AVs) and Human-driven vehicles (HDVs), understanding the car-following behaviour is important to improve traffic…
A Random Walk Approach for Simulation-Based Continuous Dynamic Traffic Assignment
Kaveh Khoshkhah, Mozhgan Pourmoradnasseri, Sadok Ben Yahia +1
This paper presents a new simulation-based approach to address the stochastic Dynamic Traffic Assignment (DTA) problem, focusing on large congested networks and dynamic settings. T…
Exploring Machine Learning Techniques to Identify Important Factors Leading to Injury in Curve Related Crashes
Mehdi Moeinaddini, Mozhgan Pourmoradnasseri, Amnir Hadachi +1
Different factors have effects on traffic crashes and crash-related injuries. These factors include segment characteristics, crash-level characteristics, occupant level characteris…
Real-Time Calibration of Disaggregated Traffic Demand
Mozhgan Pourmoradnasseri, Kaveh Khoshkhah, Amnir Hadachi
This paper presents a simulation-based optimization framework for city-scale real-time estimation and calibration of dynamic demand models by focusing on disaggregated microsimulat…
CDR Based Trajectories: Tentative for Filtering Ping-pong Handover
Joonas Lõmps, Artjom Lind, Amnir Hadachi
Call Detail Records (CDRs) coupled with the coverage area locations provide the operator with an incredible amount of information on its customers' whereabouts and movement. Due to…
Evaluation of the Robustness of Visual SLAM Methods in Different Environments
Joonas Lomps, Artjom Lind, Amnir Hadachi
Determining the position and orientation of a sensor vis-a-vis its surrounding, while simultaneously mapping the environment around that sensor or simultaneous localization and map…
Neural Networks Model for Travel Time Prediction Based on ODTravel Time Matrix
Ayobami E. Adewale, Amnir Hadachi
Public transportation system commuters are often interested in getting accurate travel time information to plan their daily activities. However, this information is often difficult…
Exploring a New Model for Mobile Positioning Based on CDR Data of The Cellular Networks
Amnir Hadachi, Artjom Lind
The emerging technologies related to mobile data especially CDR data has great potential for mobility and transportation applications. However, it presents some challenges due to i…
Adaptive Edge Process Migration for IoT in Heterogeneous Cloud-Fog-Edge Computing Environment
Chii Chang, Amnir Hadachi, Satish Srirama
The latency issue of the cloud-centric IoT management system has motivated Fog and Edge Computing (FEC) architecture, which distributes the tasks from the cloud to the edge resourc…