Date: May 26, 2023
Time: 2pm
Speaker: João Bachiega Junior (PhD)
Advisor: Prof. Aletéia Patrícia Favacho
Title: Computational Resource Allocation in Fog Computing
Abstract: Fog computing is a paradigm that allows the provisioning of computational resources and services at the edge of the network, closer to the end devices and users, complementing cloud computing. The heterogeneity and large number of devices are challenges to obtaining optimized resource allocation in this environment. This presentation brings a systematic literature review with a focus on resource allocation for fog computing. For this, 108 publications were selected, from 2012 to 2022. They were analyzed and the main techniques and metrics they adopted, the most common evaluation tools, the most used virtualization methods, the architectural layout, and the most common domains of use were collected , highlighting the main challenges and open research questions.
Time: 2:20 pm
Speaker: James Taylor Faria Chaves (PhD)
Advisor: Prof. Edna Canedo
Title: Documentation Debt in Requirements Engineering for Agile Software Development
Abstract: Agile Software Development (ASD) is a lightweight software development process widely adopted in the industry and studied by academia that always embraces changes in requirements and allows developers to rapidly deliver value to the client in the form of system pieces. In ASD, Requirements Engineering (RE) plays one of the most critical roles, as RE is the beginning of the software development lifecycle. However, the traditional way of doing RE is an expensive and time-consuming task for ASD parameters. ASD mainly focuses on human interaction over large plans and comprehensive documentation. Although it is one of its strengths and gives it some advantages over traditional ways of software development, this property can cause some problems in ASD that prevent it from being fully exploited. Issues may arise in this context (eg, incomplete or hidden requirements, lack of stakeholder cooperation, multiple interests, prioritization of needs, change management, and traceability). Some of these issues could be due to the Documentation Debt, that is, the need for more comprehensive documentation. However, simply increasing the documentation may not be the solution, as it can corrupt the ASD process. According to recent research, using Artificial Intelligence (AI) techniques in Software Engineering (SE), including in RE for ASD, is a current trend. In this context, my work will investigate the use of Machine Learning (ML) and Natural Language Processing (NLP), both AI techniques, to address the Documentation Debt in RE for ASD. The thesis will try to answer the question: Can the Requirements Engineering (RE) for Agile Software Development (ASD) benefit from augmented documentation to solve the Documentation Debt problem without corrupting the ASD values?
Time: 2:40 pm
Speaker: Henrique Costa Jung (PhD)
Advisor: Prof Bruno Macchiavello
Title: Detection of Atheromas in Panoramic Radiographs using Neural Networks
Summary: An atheroma is a calcification of the carotid vein, and is a strong indicator of circulatory problems in patients. When present, it appears on panoramic x-rays, which are routine examinations performed by dentists. However, dentists are not trained to identify atheromas, and ignore their presence. The idea of this work is to develop a neural network for object detection with a focus on atheromas. A yolo architecture is currently being used, but other architectures will be used in the future for comparison
Time: 3pm
Speaker: Ítalo Barbosa Brasileiro (PhD)
Advisor: Prof André Drummond
Title: Sparse Core Switching in SDM-EON
Abstract: The use of spatial multiplexed networks has become one of the main references to supply the fast increase in internet traffic. However, the current literature related to core-switching in spatial division multiplexed elastic optical networks is polarized between two groups. In the first one, scenarios with full core-switching capacity are considered, and in the second, scenarios with restricted switching are presented, in which the circuit must be kept in the same spatial lane. In order to balance the core-switching capabilities and the cost applied on the network to enable it, the sparse core-switching allocation is presented. We concluded that the strategic distribution of core-switching ports can bring great benefits to the deployment of SDM-EON, both in terms of blocking and cost.
Time: 3:20 pm
Speaker: Anderson Jefferson Cerqueira (PhD)
Advisor: Prof. Edna Canedo
Title: Software Requirements Engineering Ethics Implementation Maturity Model for Artificial Intelligence Systems
Summary: Although there are several initiatives and guidelines that address ethics in AI, many organizations still struggle to implement these ethical considerations into their Software Requirement Engineering (SRE) processes. The lack of a maturity model to evaluate the implementation of ethics in SRE for AI systems is one of the reasons why implementing ethics in SRE for AI systems is challenging. Therefore, the objective of this research is to develop a maturity model that allows organizations to assess the level of implementation of ethical considerations in their SRE processes and identify areas for improvement that can help organizations improve their SRE processes to ensure development responsible of AI systems and prevent harm to society.
Time: 3:40 pm
Speaker: Igor da Silva Bonomo (PhD)
Advisor: Prof Eduardo Alchieri
Title: Use of Nilcatenation Graphs in Identification of Transactions for Pruning in Blockchains
Summary: Blockchain technology has consolidated itself with its use in various areas of knowledge, with its greatest use in cryptocurrencies. However, there are still limitations to its wide use in various applications. A relevant limitation is the growing size of blockchains, which causes both storage problems and an increasing need for node synchronization time. In this context, this article studies a solution for pruning in blockchains. This technique consists of removing transactions from the network without harming the consistency of the blockchain. The proposed solution is based on nilcatenation graphs, whose objective is to identify a subgraph that can be removed without compromising the consistency of the network. Experimental results show that the proposed solution can more accurately identify transactions that can be removed (reaching a reduction of up to 20% of transactions), when compared to current techniques (managed to provide up to 5% reduction) that seek to find cycles of transactions in these graphs that can be removed.
Location: Teams- Team PPGI0095 Seminar, Channel 1-2023
Prof. Célia Ghedini Ralha ( This email address is being protected from spambots. You need JavaScript enabled to view it. )
Coordinator Postgraduate Seminars in Informatics 1-2023