The wealth of networks: How social production transforms markets and freedom

A vida dos seres humanos e marcada pela globalizacao, impondo uma interdependencia planetaria, provocando impactos, por vezes nocivos, para a humanidade como um todo. A perspectiva de superacao das situacoes de dominacao, de exclusao, de desumanizacao, esta na educacao alicercada em principios da solidariedade, da etica, da justica, tendo a democracia como principio norteador na gestao e efetivacao de um projeto de cooperacao internacional. Urge conciliar, vincular desenvolvimento economico e desenvolvimento humano, almejando a construcao de uma sociedade sustentavel.

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Educação: um tesouro a descobrir

Network Functions Virtualization (NFV) and Software-Defined Networking (SDN) are new paradigms in the move towards open software and network hardware. While NFV aims to virtualize network functions and deploy them into general purpose hardware, SDN makes networks programmable by separating the control and data planes. NFV and SDN are complementary technologies capable of providing one network solution. SDN can provide connectivity between Virtual Network Functions (VNFs) in a flexible and automated way, whereas NFV can use SDN as part of a service function chain. There are many studies designing NFV/SDN architectures in different environments. Researchers have been trying to address reliability, performance, and scalability problems using different architectural designs. This Systematic Literature Review (SLR) focuses on integrated NFV/SDN architectures, with the following goals: i) to investigate and provide an in-depth review of the state-of-the-art of NFV/SDN architectures, ii) to synthesize their architectural designs, and iii) to identify areas for further improvements. Broadly, this SLR will encourage researchers to advance the current stage of development (i.e., the state-of-the-practice) of integrated NFV/SDN architectures, and shed some light on future research efforts and the challenges faced.

Integrated NFV/SDN Architectures: A Systematic Literature Review

ContextCrime rates are increasing more and more, especially residential burglaries. This thesis includes a study of the Kernel Density Estimation algorithm, and how to use this algorithm for mapping crime patterns based on geographical data. By visualizing patterns as spatial hotspots, law-enforcements can get a better understanding of how criminals think and act. ObjectivesThe thesis focuses on two experiments, including measuring the accuracy and performance of the KDE algorithm, as well as the analysis of the amount of crime data needed to compute accurate and reliable results. MethodsA Prediction Accuracy Index is used to effectively measure the accuracy of the algorithm. The development of a Python test program, which is used for extracting and evaluating the results is also included in the study. ResultsThe data from three geographical areas in Sweden, including Stockholm, Gothenburg and Malmoe are analyzed and evaluated over a time period of one year. ConclusionsThe study conclude that the usage of the KDE algorithm to map residential burglaries performs well overall when having access to enough crimes. The minimum number of crimes for creating a trustworthy hotspot are presented in the result and conclusion chapters. The results further shows that KDE performs well in terms of execution time and scalability. Finally the study concludes that the amount of data that was available for the study was not enough for producing highly reliable hotspots.

Crime hotspots: An evaluation of the KDE spatial mapping technique : Spatial analysis

Recent advances in data science have made available many URL-analysis–based detection and machine learning algorithms, which are being leveraged for phishing detection. It is necessary to measure t...

Exquisite Analysis of Popular Machine Learning–Based Phishing Detection Techniques for Cyber Systems

Current infrastructures in modern cities are highly dependent on complex software-intensive systems, which are composed of many elements, including software, sensors, actuators, and processes. Citizens and managers are also important stakeholders in these systems, as they provide data, provide and retrieve information and also manage the many systems that control the city infrastructures’. UML has been often considered for designing these types of systems, mostly with focus only on designing the software elements of the system. However, these infrastructures systems are composed of many more elements than software, including processes, constraints, sensors, networks, laws and further documents. SysML is a UML profile that has gained attention in past years, as SysML also models systems elements that are not software. In this paper, the main idea is to describe a SysML profile for modeling smart cities applications, which is useful as it specifies common elements of a city as native elements of system design. The profile, named SmartCitySysML, extended from SysML Requirements, Sequence and Block Definition diagrams in order to model system and software elements for smart cities. Design of a road traffic control system regarding a group of intersections is used as a case study. As a result, SmartCitySysML facilitates the use of common elements in smart city infrastructures and provides a visual representation to assess quality of diagrams from a practical point of view.

SmartCitySysML: A SysML Profile for Smart Cities Applications

Context: Crime is a prevalent social problem, then, government and society, in general, have had enormous problems caused by this phenomenon. However, with the increasing ability to collect and sto...

Applied Intelligent Data Analysis to Government Data Related to Criminal Incident: A Systematic Review

Digital innovation focuses on using digital technologies to orchestrate new products, services, platforms, or even new business models in a given context. Design science research has the potential to contribute to digital innovation as it focuses on the development of innovative IT artifacts. However, existing literature still lacks an understanding of how these two disciplines would converge. This article conducts a literature review that examines this issue intending to obtain an overview of the current state of the art, which leads to a research agenda. We employ a systematic approach to mapping in first-line journals, and well-known IS conferences. The results of the study revealed that most studies are focused on providing two types of contributions (Model and Method). They also showed, as well as the need to employ design science for developing innovative artifacts in new emerging application domains such as disaster management or urban mobility.

Design Science in Digital Innovation: A Literature Review

In this paper, we aimed to analyze the application and contribution of the use of Test-Driven Development (TDD) and Behavior-Oriented Development (BDD) in Software Engineering teaching. As empirical research, we presented an experiment conducted in the Software Engineering Laboratory (LES) course of a Private University (Tiradentes University) in the Bachelor of Computer Science and Information Systems courses. This experiment demonstrated the fundamentals in verifying the learning difficulties of students. Collected data were subjected not only to quantitative analysis but also to appropriate statistical analysis. The results showed a reduction in student absences, higher student satisfaction rate and higher grades in the courses. Furthermore, our approach allowed students to deliver a product in a short period, representing a possibility of adoption of BDD due to their successful learning experience.

Agile Teaching Practices: Using TDD and BDD in Software Development Teaching

A demonstration of the application and contribution of Test-Driven Development (TDD) and Behavior-Driven Development (BDD) in the student learning experience in the context of a Software Engineering course. Background: Software testing is an activity for ensuring software quality. Although teaching testing rigorously to students is a priority in academia, undergraduate students often encounter difficulties performing testing tasks effectively. Intended Outcomes: To increase satisfaction rate and course grades, and reduce delivery time. Application Design: We experimented with the Software Engineering Laboratory (LES) course of a Private University in the Bachelor of Computer Science and Information Systems courses. This experiment corroborated the learning difficulties of students. Collected data were assessed both quantitatively and qualitatively. Findings: Backed up with statistical tests, the results showed a reduction in student absences, higher student satisfaction rate, and higher grades in the courses. Furthermore, our approach allowed students to deliver a product in a short period, representing a possibility of adoption of BDD due to their successful learning experience. Finally, we aim to foster a discussion of appropriate teaching methods of software testing.

Layse Santos Souza

Papers

SmartCitySysML: A SysML Profile for Smart Cities Applications

Applied Intelligent Data Analysis to Government Data Related to Criminal Incident: A Systematic Review

Design Science in Digital Innovation: A Literature Review

Agile Teaching Practices: Using TDD and BDD in Software Development Teaching

Enhancing the Student Learning Experience by Adopting TDD and BDD in Course Projects