Abstract
Currently, business organizations are struggling with the increasing demand for learning needs to address their knowledge gaps. They must have a structure that can reach all employees in terms of training and extract all the important data which is collected by Learning Management Systems during the instruction or learning process. This data will be of extreme importance for better business decisions. In this paper, it is presented a Systematic Literature Review with their respective phases duly explained and framed in the topic. It allowed us to understand the benefits, challenges, enablers, and inhibitors of the deployment and usage of a specified Teaching-Learning Analytics Framework. Finally, it is concluded, that the development of a reference model, could fulfill this gap in knowledge and help business organizations to allocate resources better and improve the decision-making process as well as an instructional and learning process. To achieve the final goal of this research, future work about the development of a Survey Research methodology will be started to fulfill this gap of knowledge.

Abstract
E-Learning has been widely implemented in educational institutions to improve the learning process and meet the new challenges imposed by technology in the 21st century. The implementation and use of learning management systems (LMS) in organizations have grown exponentially in recent years and have strongly impacted education, especially in higher education. The present systematic review aims to identify studies and research topics that are being addressed to improve the learning process in the e-Learning context in higher education institutions and map the studies on the implementation and use of LMS. The review process examined 30 articles that met the inclusion and exclusion criteria on the topic over the past five years, adopting Kitchenham's systematic review design methodology. The results showed that technology alone would not be enough for e-Learning to become a dominant teaching standard. The digital literacy of the stakeholders is crucial in this process.

Abstract
Managing company knowledge and using it effectively is more than ever a strong competitive advantage in the business world. The scientific area of knowledge management and knowledge management systems have been intensively studied in the last years; however, we still see the unstructured implementation of knowledge management systems in organizations, the misalignment of knowledge management systems from the business model and the frustration non-use, lack of systems integration and/or non-return on investment made either in technology or spent on heavy implementation processes. The state-of-the-art conducted during this study, showed that most knowledge management systems alignment models in the business context have a strong focus on the organizational dimension, e.g., culture, organizational processes, organizational structure, and leadership, having been identified only three models that also cover, simultaneous, the technological and strategic dimension. Our final objective in this study is, following the research survey methodology, to develop a proposed framework for the strategic alignment of knowledge management systems that can support company managers in their decision-making, and to contribute to the development of scientific knowledge in this area.

Abstract
In the digital age, the training in companies can be facilitated through a proper system to the company's demand. A learning platform personalized to the profile of employees can facilitate the selection of training that tailored to their roles. This research aims to investigate the existence of adaptation and personalization of learning management systems (LMS) in enterprise context, that facilitate the selection of learning's content suited for employees' roles. This study focuses on literature reviewto understand the importance of a personalizedLMSin company, especially in selection of content that adequate to role of each employee.

Abstract
The Internet of Things (IoT) emerged to describe a network of connected things on a large scale to offer services to a large number of applications in different environments and domains. Middleware is software that seeks to facilitate the management and communication of all these things, providing the necessary functionalities to manage things, to discover, to compose services, and perform communication. For this reason, several proposals for middleware solutions for IoT have been developed. In this article, we conducted a systematic review of the literature to bring together middleware solutions for IoT, identifying the requirements and communication protocols used. In addition, we present some gaps and directions for future research in the development of IoT middleware.

Abstract
Despite being one of the most cost-effective methods, email marketing remains challenging due to the low rate of opened emails and the high percentage of unsubscribed campaigns. Since the sender and the subject line are the only information that the recipient sees at first when receiving an email, the decision to open an email critically depends on these two factors, which should stand out and catch the recipient's attention. Therefore, the motivation behind this study is to support email campaign editors in choosing a subject line based on its potential quality. We propose and compare several models to measure the quality of a subject line, considering its potential to promote the email opening. The subject lines' structure and content are explored together with different machine learning techniques (Random Forest, Decision Trees, Neural Networks, Naive Bayes, Support Vector Machines, and Gradient Boosting). To validate the proposed model, a data set of 140,000 emails' subject lines was used. The results revealed that the models proposed are very promising to support the definition of the email marketing subject lines and show that the combination of data regarding the structure, the content of the subject lines, and senders characteristics leads to more accurate classifications of the potential of the subject line.