Abstract
With the continued growth of wind power penetration into conventional power grid systems, wind power forecasting plays an increasingly competitive role in organizing and deploying electrical and energy systems. The wind power time series, though, often present non-linear and non-stationary characteristics, allowing them quite challenging to estimate precisely. The aim of this paper is in proposing a novel hybrid model named EvolCNN in order to predict the short-term wind power at 10-min interval up to 3-hr based on deep convolutional neural network (CNN) and evolutionary search optimizer. Specifically, we develop an improved version of Grey Wolf Optimization (GWO) algorithm by incorporating two effective modifications in its original structure. The proposed GWO algorithm is more effective than the original version due to performing in a faster way and the ability to escape from local optima. The proposed GWO algorithm is utilized to find the optimal values of hyperparameters for deep CNN model. Moreover, the optimal CNN model is employed to predict wind power time series. The main advantage of the proposed Evol-CNN model is to enhance the capability of time series forecasting models in obtaining more accurate predictions. Several forecasting benchmarks are compared with the Evol-CNN model to address its effectiveness. The simulation results indicate that the Evol-CNN has a significant advantage over the competitive benchmarks and also, has the minimum error regarding of 10-min, 1-hr and 3-hr ahead forecasting.

Abstract
Immersive technologies, such as virtual reality, could be effective marketing tools for destination marketing, namely in creating place attachment prior experience the destination. Place attachment plays a significant role in behavioural intentions to visit and to recommend a destination. However, place attachment research is relatively new in the tourism context. This study seeks to empirically examine the effectiveness of Virtual Reality in creating place attachment to destinations exploring the changes in the place attachment after two moments. First, after watching a video and after having an experience in the Virtual Reality environment. Second, after the experience in the Virtual Reality environment and after the 'real' visit to a representative viewpoint in Douro region. Students belonging to Gen Z were sampled. Findings reflect that Virtual Reality has potentialities for marketing destinations.

Abstract
Digital presence, especially using websites, is currently one of the pillars for effective communication in the field of marketing. However, it appears that many organizations, despite making high investments in development, even if they present a visually attractive website, face difficulties in attracting visitors. In the case of the tourism sector, in which competition takes place on a global level, it is even more pressing for technologies to reach potential stakeholders, first attracting visitors, then seducing them and converting them into customers. In this context, digital marketing techniques, and more specifically, website optimization techniques to improve their visibility by search engines (Search Engine Optimization) are the key to leveraging the potential for visits to any website. In this article, digital marketing concepts and the technological aspects that affect the indexing made by search engines will be explored. The case study presented intends to demonstrate, in a simplified way, the importance and applicability of these concepts and techniques, proposing a set of improvements that should be implemented to improve the positioning of the Termas de Chaves web site in the search engine page results.

Abstract
5G has become increasingly popular nowadays, mainly due to its characteristics which enable high data rates and low latency. At the same time, mobile robotic platforms, such as drones and robots, appeared as suitable platforms to carry radio stations, enabling the on-demand placement of 5G communications cells. The main contribution of this paper is an obstacle-aware on-demand 5G network. The proposed solution consists of a 5G radio station (gNB) carried by a mobile robotic platform capable of providing obstacle-aware wireless connectivity to 5G User Equipments (UEs), leveraged by a novel virtual network function - On-Demand Mobility Management Function (ODMMF). ODMMF is designed to integrate the 5G Core network and it allows to monitor the radio conditions provided to the served UEs, while enabling the positioning of the mobile robotic platform remotely by taking advantage of the visual information provided by on-board video cameras. The proposed solution was validated using an experimental prototype, under a representative networking scenario.

Abstract
To enhance the economic viability and address the labour shortage in the forestry industry, alternative solutions using robotization and automation are emerging. However, due to technological barriers and lack of solid business models, successful commercialization in the forestry sector is yet to be challenging. As an initial market analysis for developing a business model for new forestry machineries, this study was conducted to reveal clusters of EU countries to seek the potential market opportunities outside of Portugal. To identify similar market conditions and restrictions, EU countries were clustered using a hierarchical clustering algorithm and selection of variables while considering the geographic, economic, and social conditions of each country. Preliminary results showed that Austria and Poland had similar social capital and geographic conditions.

Abstract