Abstract
There is no doubt that tourism benefits Portugal's economy. The area should be able to better target the market for its travel and tourist products and increase its performance with the use of a marketing strategy, especially in a field where global competition is always increasing. This digital marketing plan seeks to analyze the strengths and limitations of the Portuguese region in its target markets, as well as the most current advancements in the global travel and tourism sector. In this work, it is conducted an analysis of both micro and macro environments of Casa Pereirinha. In addition, it was created a marketing mix based on the 7P's. Furthermore, the work provides the prospective avenues for product growth and marketing following the markets' stated growth objectives. This project comprises creating a comprehensive digital marketing strategy for Casa Pereirinha as a significant example of the region's tourism business, and the primary purpose is to conserve its past, while developing a new strategy.

Abstract
The key question that will be addressed in this research is whether advertising narratives feature initiatives within the ESG - Environment, Social and Governance - framework. Investors increasingly value companies that promote sustainable impact actions, something that the promoting companies report in detail in their ESG reports directed at corporate stakeholders. To identify and understand how brands present such initiatives to the consumer market, we checked campaigns awarded with the Golden Lion of Advertising at Cannes 2022. The methodological cut involved three award categories, being analyzed 19 campaigns from 10 different countries. Besides the bibliographical survey on discourse analysis and content analysis, this exploratory qualitative and quantitative research had the inductive method to direct the individual analysis of each campaign. As a result, we identified that more than half of the campaigns address aspects related to ESG initiatives, being the social scope addressed by most of the campaigns. A result that provokes new hypotheses and possibilities of research continuity.

Abstract
Following the lack of existing studies about the applications development and use in the event industry, this research aims to analyze the use of applications as a tool to improve event communication. The methodology used includes an exploratory method. This research methodology is based on a review of the literature, a semi-structured interview with the CEO of the company and a case study with participant observation of the French start-up Invent App which provides event applications. The study demonstrate that the event app use allows to ease the event organization, to improve the event communication but also the interactivity and the participant engagement. All of this, increasing the customer experience but also having a part in the customer digital experience improvement. Event applications could be thus considered as amarketing and event communication tool. The research has the limitation to its application within a single company in France. Furthermore, the point of viewadopted is the one of the event organizers and not the event participant one. This research helped to better understand the role that event applications can have in the event industry and particularly in the communication around an event. In addition, this made it possible to understand the perception of market requirements and the characteristics expected of an event application.

Abstract
The world of video games has more and more users, and today it is considered as an alternative to the existing reality. Online games like Second Life have independent economies with independent businesses and there is a growing interest to create rich experiences with high levels of presence, to create an alternative to reality, where you can work, be with friends, socialize and much more. With this new era that could be true virtual reality, and with advertising agents always trying to innovate the way they convey their advertising messages, it will be necessary to keep up with the medium to also reach new consumers. This integration of advertising in video games is not recent, however, and the practice itself has become increasingly popular in sports games, car racing games and many others that already have the presence of brands and advertising messages. This study intends to work as an introductory study to the theme, proposing some questions regarding the influence of the way advertising is inserted in the game. In this sense, an initial descriptive investigation of acquired data was developed, using a game created on the Unity platform, specifically for this research. The game was developed in 3 different versions, in which each one integrates advertising messages in a distinct way. Subsequently, a questionnaire survey was conducted to assess the respondents' opinion about the game, the effectiveness of advertising and the players' opinion regarding the practice of inserting advertising in video games. The influence and effectiveness of in-game advertising was also analyzed in order and to acquire their opinion regarding the practice used. The descriptive research indicates preliminarily that the way advertising is integrated may influence the effectiveness of in-game advertising. It was also possible to perceive that although the opinion is generally neutral, the respondents that have as a habitual leisure activity the consumption of videogames have a higher retention to in-game advertising when compared with non-gamers. At the end of this study, proposals and recommendations for future research involving this theme are presented. © ICWI 2023.All rights reserved.

Abstract

Abstract
Recently, deep learning has proven to be a successful technique especially in medical image analysis. This paper aims to highlight the importance of deep learning architectures in lung disease diagnosis using CXR images. Related articles were identified through searches of electronic resources, including IEEE, Springer, Elsevier, PubMed, Nature and, Hindawi digital library. The inclusion of articles was based on high-performance artificial intelligence models, developed for the classification of possible findings in CXR images published from 2018 to 2023.After the quality assessment of papers, 129 articles were included according to PRISMA guidelines. Papers were studied by types of lung disease, data source, algorithm type, and outcome metrics. Three main categories of computer-aided lung disease detection were covered: traditional machine learning, deep learning-based methods, and combination of aforementioned methods for all lung diseases.The results showed that various pre-trained networks including ResNet, VGG, and DenseNet, are the most frequently used CNN architectures and would result in a notable increase in sensitivity and accuracy. Recent research suggests that utilizing a combination of deep networks with a robust machine learning classifier can outperform deep learning approaches that rely solely on fully connected neural networks as their classifier. Finally, the limitations of the existing literature and potential future research opportunities in possible findings in CXR images using deep learning architectures are discussed in this systematic review.