Abstract
The industry faces more and more the challenge of deploying and taking advantage of evidence-based strategic decisions to enhance profit gain. In this research, the possibility of having a fully integrated system composed by a simulator and an IoT platform with the capability of collecting real-time data from the shop floor and returning performance indicators to support decision making is evaluated. The suggested approach involves a Manufacturing Executing System (MES) producing a production schedule, an IoT Platform composed by a message broker and a real-time database, a Simulator including simulation software and a wrapper, and a user application serving as an interface between the user and the IoT Platform and Simulator integrated system. A detailed analysis of the functionalities and integration of the Simulator and the IoT Platform will also be explored. To evaluate the approach, one use case of a production line in the automotive industry is used. The application of the integrated IoT Simulation system permits its validation and consequent future work. © 2019, IEOM Society International.

Abstract
The continuous shift from TSO connected generation to DSO connection generation is presenting new challenges to DSOs and TSOs. Keeping the system up and running in the future requires a more collaborative approach to the issue of DSO/TSO cooperation that has existed so far in the vertically integrated network paradigm. It is possible to use IT tools to make sure both system operators have the relevant information they require to fulfil their mission.TDX-Assist’s Portuguese demo helps addressing these issues by:focusing on the provision of reactive power services by the DSO to the TSO. A new version of the Interval Constrained Power Flow (ICPF) tool, which takes into account disjoint flexibility areas as a result of the combination of discrete control variables, will be used to evaluate the range of operation points at the primary substations (Figure 1). With this information, the TSO can then select an operation point that will cause minimum impact on the transmission network.designing and implementing the information exchange needed to support other dimensions such as operational planning through nodal forecast at nodal level and exchange of maintenance plans in a defined observability area of both system operators

Abstract
The architectural pattern of micro-services is being increasingly adopted by developers, facilitating the maintenance and scalability of the systems’ code. The adoption and consumption of these micro-services are often seen on the front-end code of the Web applications. Nevertheless, this adoption obliges web designers/developers to know where to look for those web services, to read their documentation and to write the request/response code as well to control the corresponding UI rendering. This whole process is time-consuming and error-prone. This article introduces SeCoGen as an interactive code generator for Web service parsing and consumption. The generator benefits from an HTTP request template, a query normalizer and dynamic UI templates. In order, to validate the generator feasibility and usefulness, a REST API to search for countries is used.

Abstract
In our previous editorial, we positioned our perspective and introduced the acronym “ROTRUS” to characterise the science of managing for innovation as – Real world, Observable, Testable, Replicable, Uncertain and Social. Specifically, we argued that methods that draw on point-in-time beliefs, perceptions and de-humanised data in a complex and evolving social setting of innovation management pose a challenge for replicability. We warned innovation researchers to avoid the pitfalls that might foster pseudoscience and generalised assumptions from information that is still in the proto-science stage. Drawing on longstanding understanding in psychology of the whole human, we discussed the need to explore methods that capture brain, mind and behaviour aspects in innovation management, spanning the analysis from individual to group and societal levels. In this editorial, we move the discussions forward by focusing on one plausible methodological approach to advance the science of managing for innovation – behavioural experiments. In the following sections, we explain our methodological stance or in other words our world view followed by a brief review of behavioural experiments and their relevance to innovation research. We conclude with a foreword on our final editorial in the series titled the science of managing for innovation. (...)

Abstract
Innovation capabilities are important for firms to compete in the market. However, the literature has rarely examined how exploitative and exploratory innovation influences the export performance of small and medium-sized firms (SMEs). As exploitative and exploratory innovation plays different roles in sustaining SMEs' competitive advantages, this article presents an analysis of how four specific firms' innovation capabilities (i.e. marketing, strategy, research and development and manufacturing capabilities) impact these SMEs' export performance. Moreover, this study analysed how exploitative and exploratory innovation capabilities mediate the relationship of the four firms' internal innovation capabilities and export performance. The results indicate that exploitative innovation positively influences SMEs' export performance, but exploratory innovation does not. Another interesting finding is that strategy and manufacturing capabilities are important antecedents of both exploratory and exploitative innovation. Furthermore, the results reveal that only manufacturing capabilities have a direct impact on export performance, whereas strategy and manufacturing capabilities are the antecedents that most influence exploitative innovation and export performance.

Abstract
Atmospheric profiling is a requirement for controlling wide-field adaptive optics (AO) instruments, analysing the AO performance with respect to the observing conditions and predicting the point spread function (PSF) spatial variations. We present PEPITO, a new concept for profiling atmospheric turbulence from post facto tip-tilt (TT) corrected shortexposure images. PEPITO utilizes the anisokinetism effect in the images between several stars separated from a reference star, and then produces the profile estimation using a model-fitting methodology, by fitting to the long-exposure TT-corrected PSF. PEPITO has a high sensitivity to bothC2 n(h) and L0(h) by relying on the full telescope aperture and a large field of view(FOV). It then obtains a high vertical resolution (1-400 m) configurable by the camera pixel scale, taking advantage of fast statistical convergence (of the order of tens of seconds). With only a short-exposure capable large format detector and a numerical complexity independent of the telescope diameter, PEPITO perfectly suits accurate profiling for night optical turbulence site characterization or AO instruments operations. We demonstrate, in simulation, that the C2 n(h) and L0(h) can be estimated to better than 1 per cent accuracy, from fitted PSFs of magnitude V = 11 on a D = 0.5m telescope with a 10 arcmin FOV.