On the use of common random numbers in activity-based travel demand modeling for scenario comparison

Activity-based travel demand models provide a high level of detail when modeling complex travel behavior. Since stochastic simulation is used, however, this high level may induce large random fluctuations in the output, necessitating many model reruns to produce reliable output. This may become prohibitive in terms of computation time when...

Sustainable mobility strategies and their impact: A case study using a multimodal activity based model

Nowadays, many cities are intending to reduce the use of private vehicles. Governments are incorporating new mobility services and are adapting their parking policies to promote a more sustainable mobility, as both strategies are believed to have the potential to reduce private vehicle use. To understand the effects of these strategies, one...

A tour-based multimodal mode choice model for impact assessment of new mobility concepts and mobility as a service

Mobility as a Service (MaaS) and new mobility concepts mutually inspire each other, provide alternatives for the private car-oriented transport system as we know it, and will offer more mobility choices in a single journey than ever. This multitude of mobility choices however poses challenges in modeling the travelers’ mode choices in travel...

Bayesian deep learning for system identification

Applying deep neural networks (DNNs) for system identification (SYSID) has attracted more andmore attention in recent years. The DNNs, which have universal approximation capabilities for any measurable function, have been successfully implemented in SYSID tasks with typical network structures, e.g., feed-forward neural networks and recurrent...

Sparse Bayesian deep learning for dynamic system identification

This paper proposes a sparse Bayesian treatment of deep neural networks (DNNs) for system identification. Although DNNs show impressive approximation ability in various fields, several challenges still exist for system identification problems. First, DNNs are known to be too complex that they can easily overfit the training data. Second, the...

Identify dominant dimensions of 3D hand shapes using statistical shape model and deep neural network

Hand anthropometry is one of the fundamentals of ergonomic research and product design. Many studies have been conducted to analyze the hand dimensions among different populations, however, the definitions and the numbers of those dimensions were usually selected based on the experience of the researchers and the available equipment. Few...

Hydrate slurry as cold energy storage and distribution medium: Enhancing the performance of refrigeration systems

The research presented in this thesis focuses on the use of hydrate slurries in the air conditioning and refrigeration areas. Both experimental and mathematical methods have been used. Hydrate slurries have been suggested as promising cold storage materials that can be used in air conditioning systems due to their high latent heat (193 kJ/kg and...

Effect of type-III Anti-Freeze Proteins (AFPs) on CO₂ hydrate formation rate

CO2 hydrate slurry is a favourable direct coolant of fresh products due to its large latent heat and phase change temperature around 7 °C. Continuous production of this slurry is, however, difficult to realise due to the high rate of hydrate formation. The use of additives is proposed with the purpose of decreasing the formation rate so that the...

Investigation of hydrate growth rate on the interface between liquid and solid film

Hydrate slurry has been reported to be a suitable secondary fluid for refrigeration and air-conditioning systems. The latent heat of CO2 hydrate is 387 kJ/kg under phase equilibrium condition of 7 °C and 30 bar. The utilization of CO2 hydrate slurry in air-conditioning systems is promising in improving the energy efficiency and shifting energy...

Flexible labor and innovation performance: Evidence from longitudinal firm-level data

Firms with high shares of workers on fixed-term contracts have significantly higher sales of imitative new products but perform significantly worse on sales of innovative new products (“first on the market”). High functional flexibility in “insider-outsider” labor markets enhances a firm’s new product sales, as do training efforts and highly...

Flexible labor and innovation performance: Evidence from longitudinal firm-level data

Firms with high shares of workers on fixed-term contracts have significantly higher sales of imitative new products but perform significantly worse on sales of innovative new products (“first on the market”). High functional flexibility in “insider-outsider” labor markets enhances a firm’s new product sales, as do training efforts and highly...