Abstract

Abstract
Simulation modeling is a well-known and recurrent approach to study the performance of urban systems. Taking into account the recent and continuous transformations within increasingly complex and multidimensional cities, the use of simulation tools is, in many cases, the only feasible and reliable approach to analyze such dynamic systems. However, simulation models can become very time consuming when detailed input-space exploration is needed. To tackle this problem, simulation metamodels are often used to approximate the simulators' results. In this paper, we propose an active learning algorithm based on the Gaussian process (CP) framework that gathers the most informative simulation data points in batches, according to both their predictive variances and to the relative distance between them. This allows us to explore the simulators' input space with fewer data points and in parallel, and thus in a more efficient way, while avoiding computationally expensive simulation runs in the process. We take advantage of the closeness notion encoded into the GP to select batches of points in such a way that they do not belong to the same highvariance neighborhoods. In addition, we also suggest two simple and practical user-defined stopping criteria so that the iterative learning procedure can be fully automated. We illustrate this methodology using three experimental settings. The results show that the proposed methodology is able to improve the exploration efficiency of the simulation input space in comparison with non-restricted batch-mode active learning procedures.

Abstract
In this work, an alternative method of coupling light into microstructured polymer fibers is presented. The solution consists in using a fiber taper fabricated with a CO2 laser. The connection is formed by inserting a tapered silica tip into the holes of a microstructured polymer fiber. This alternative method is duly characterized and the feasibility of such fiber connection to enable the polymer fiber as a displacement sensor is also demonstrated. © 2018 by the authors.

Abstract

Abstract
Electric vehicles (EVs) are to play an important role in electricity markets, since their energy storage capability can be beneficial to power systems operation. Electric vehicle aggregators will consequently develop adequate offering strategies to participate in energy and reserve markets, accounting for the market rules and operational capabilities of EVs aggregators (e.g., fleet of EVs). In this paper, we propose an offering strategy model for an EV aggregator to participate in the frequency-controlled normal operation reserve service (FCR-N) in Eastern Denmark. The aim is to maximize the expected revenue of the aggregator, accounting for potential penalties for missing the provision of both upward and downward reserves. The methodology has been modeled and tested under the scope of the PARKER project, which considers a case study based on real data from a small fleet of electric vehicles. An important conclusion relates to the availability patterns of the EVs that significantly changes the strategical participation of the EV aggregator in the service.

Abstract
In an increasingly competitive and dynamic world where globalization, information and technology are commonly accepted as influential and determining factors of organizational culture and performance, it becomes imperative for organizations to stand out and gain an advantage over their competitors. This scenario transformation created a greater and more exquisite demand as concerns the average customer and it is now understood that a competitive advantage gained does not necessarily prevail over time. Therefore, organizations must be flexible and learn to adapt easily and rapidly to changes in order to create a sustainable position. Furthermore, the ability to be different, to be innovative, and to create unique products, services, experiences, or a combination of all three, may be viewed as a booster of competitive advantages. In this context: 1. When does innovation begin or should it begin? 2. Is innovation an organizational goal or a philosophy? 3. What makes an organization innovative? This study focuses on innovation as a precursor and defining agent in the development of a business model. First, a brainstorming session was conducted as an exploratory qualitative research effort, with eighteen participants studying innovation and technology management in Portugal (the participants were probed for their views on the three questions above). Additionally, a questionnaire was administered to Portuguese millennials (171 valid responses), with the goal of perceiving potential changes in the national culture that could impact the national innovation mindset. The results were quite surprising and reveal a significant change since the original questionnaire (led by Hofstede) was administered in Portugal.