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This study develops a typology of coopetition in value networks, wherein a distinction is made based on two factors. Firstly, whether coopetition takes place inside a particular value network (i.e., intra-value network coopetition) or between value network ...
Under-resourced speech recognizers may benefit from data in languages other than the target language. In this paper, we boost the performance of an Afrikaans speech recognizer by using already available data from other languages. To successfully exploit av ...
Smartphones have the capability of recording various kinds of data from built-in sensors such as GPS in a non-intrusive, systematic way. In transportation studies, such as route choice modeling, the discrete sequences of GPS data need to be associated with ...
Proximity information is a valuable source for social network analysis. Smartphone based sensors, like GPS, Bluetooth and ANT+, can be used to obtain proximity information between individuals within a group. However, in real-life scenarios, different peopl ...
Real-time coordinated traffic management strategies that benefit from parsimonious models with aggregated network dynamics, provide a new generation of smart hierarchical strategies to improve network capacity and performance. However, this raises the ques ...
Pedestrian modeling is a tool for designing and optimizing infrastructures. In particular, walking in transportation hubs such as railway stations and airports is the key for an efficient multimodal transport systems. Data collections are needed in estimat ...
Synthetic social contact networks play a central role in the study of epidemics and methods to control them. In this paper we propose a new methodology that combines subjective surveys and data obtained using digital devices to synthesize detailed social n ...
In this thesis, we develop methods for modeling route choice behavior using smartphone data. The developing global positioning system (GPS) technology and the popularity of smartphones have revolutionized the revealed preference route choice data collectio ...
Until now, most efforts to improve monosaccharide production from biomass through pretreatment and enzymatic hydrolysis have used empirical optimization rather than employing a rational design process guided by a theory-based modeling framework. For such a ...
Efficiently querying data collected from Large-area Communitydriven Sensor Networks (LCSNs) is a new and challenging problem. In our previous works, we proposed adaptive techniques for learning models (e.g., statistical, non-parametric, etc.) from such dat ...