TCC - Bacharelado em Sistemas da Informação (Sede)
URI permanente para esta coleçãohttps://arandu.ufrpe.br/handle/123456789/427
Navegar
104 resultados
Resultados da Pesquisa
Item Análise de performance de algoritmos estocásticos aplicados ao problema do caixeiro viajante(2024-10-09) Lima, Lucas Gabriel Oliveira Sales; Monteiro, Cleviton Vinícius Fonsêca; http://lattes.cnpq.br/9362573782715504; http://lattes.cnpq.br/7636465842833021Optimization algorithms are increasingly relevant tools in modern companies because they are capable of optimizing processes and resources, ensuring more efficient results and timely processing for decision making. Comparing these algorithms is a common process during their adoption studies. However, the use of complex methodologies can often lead to the choice of an imprecise algorithm, since its result may not reflect the reality of a company seeking to implement applications with limited resources. In view of this problem, the need arises to evaluate these algorithms from a new perspective. The main objective of this work is to propose a reflection on the way experiments in algorithms are conducted. The present study carried out experiments with optimization algorithms using computational resources similar to those found in most companies, comparing them with another work in which optimizations and tunings were used in these same algorithms. For the experiment, the traveling salesman problem was used, through 15 benchmarking divided into 3 categories, according to the size of each article. Finally, statistical metrics were obtained for the performance of each algorithm, which, when compared to the reference article, showed shorter execution times without compromising the accuracy of the results. Probabilistic algorithms are of great financial importance to companies that need to manage resources quickly, such as airports and shipyards. Therefore, the appropriate choice of parameters provides a more accurate view of reality.Item Sistema integrado para registro de aulas e análise de frequência dos alunos do Projeto Conecta Vidas do Centro Tecnológico da Associação Conexão Social(2024-10-09) Santos, Djair Batista dos; Albuquerque Júnior, Gabriel Alves de; http://lattes.cnpq.br/1399502815770584The Social Connection Association (ACS), founded in 2005 in Lagoa de Itaenga, Pernambuco, has the mission of guaranteeing the rights of people in situations of social vulnerability through education and inclusion. The Conecta Vidas Project aims to promote digital literacy and physical activities for the elderly, contributing to their active aging and strengthening community bonds. However, the registration of attendance and the documentation of activities face significant challenges, such as the logistics of real-time records and the security of sensitive beneficiary data. This report presents a proposal for a responsive Integrated System for Class Registration and Attendance Analysis, developed with React, Node.js and MySQL technologies. The proposed solution seeks to optimize attendance registration, facilitate the secure storage of photos and simplify the flow of information for coordination. This is intended to improve the efficiency of educators, ensure data protection, and provide detailed and accurate reporting to funders. The system aims not only at the continuity and success of the project, but also at the promotion of a more transparent and effective management, enhancing the benefits offered by ACS.Item Minha UBS: aplicativo para facilitar o acesso a serviços disponibilizados em Unidades Básicas de Saúde(2024-10-09) Lira, Emerson Leonardo Oliveira de; Monteiro, Cleviton Vinicius Fonsêca; http://lattes.cnpq.br/9362573782715504The Unified Health System is the system that guarantees the Brazilian population access to health services free of charge through the public network. The main way of accessing these services is from basic health units, popularly known as "postinhos", Those responsible in these units for facilitating this access for residents are community, health and endemic diseases, agents who act as bridges between residents and health units. With tools to help plan strategies to operate in the region and facilitate communication with residents, Minha UBS proposes, through an application, to reduce barriers between the population and public health services.Item Aprendizagem de máquina para a identificação de clientes propensos à compra em Inbound marketing(2019-07-12) Silva, Bruno Roberto Florentino da; Monteiro, Cleviton Vinicius Fonsêca; Soares, Rodrigo Gabriel Ferreira; http://lattes.cnpq.br/2526739219416964; http://lattes.cnpq.br/9362573782715504The most important point for a company should always be the customer and getting new customers is not always an easy strategy. Digital marketing techniques study how to attract new customers to businesses using digital platforms. By virtue of the popularization of these means, the strategies had to be shaped to the new possibilities. With just one click you can reach thousands of individuals, which means many new leads for the company. However, filtering out which of these individuals are really interested in the product or service offered by the company demands a lot of effort from the sales team. This overhead is detrimental in the sense that the company can lose revenue by not targeting the real opportunities. With the aim to minimize this problem, the present work offers a proposal whose objective is the automatic identification of the client achieved through digital marketing strategies. It is proposed the usage of Machine Learning techniques, in particular supervised classification algorithms, namely Decision Tree and Naive Bayes. It was used the Scikit-learn library available for the Python programming language. In addition, it was necessary to apply the SMOTE oversampling algorithm, due to the unbalance of the dataset. In addition, in order to optimize the classification, we used the techniques of attribute selection and model selection with hyperparameters adjustment. Finally, to evaluate the results, we used the confusion matrix, the precision and coverage metrics, and the accuracy and coverage curve. Due to the imbalance of the data, the precision metric did not report good indexes results, with averages of 5.5% of correctness. In addition, the coverage was around 83%. Even with such divergent results among the applied metrics, the present work reached its goal, identifying most of the real opportunities and reporting that using this approach, it would be possible to obtain a reduction of up to 85% in the effort applied by the sales team if they had to call for all the leads. As a consequence, the company may have a cost reduction with the resources applied to obtain new customers, allowing the sales team to find new customers with greater efficiency.Item Implementação de um sistema mobile colaborativo para acompanhamento do quadro de pacientes com esclerose múltipla por meio de análise de sentimento(2024-10-02) Araujo, Paula Priscila da Cruz; Gouveia, Roberta Macêdo Marques; Tschá, Elizabeth Regina; http://lattes.cnpq.br/9598413463162759; http://lattes.cnpq.br/2024317361355224; http://lattes.cnpq.br/0280090820230057The study aims to develop a mobile system to facilitate the monitoring of patients with Multiple Sclerosis (MS), based on the Human-Centered Design (HCD) Toolkit to meet patient needs. The app allows patients to record and track emotions, symptoms, and treatments, offering monthly reports and personalized alerts. For sentiment analysis, the machine learning algorithms XGBoost and Naive Bayes were used, with XGBoost showing better performance, achieving 87.56% accuracy and an F1-Score of 0.876, while Naive Bayes obtained 62.25% accuracy and an F1-Score of 0.524. The results indicate the tool’s effectiveness in emotional and medical monitoring, contributing to an improved quality of life.Item Técnicas preditivas para auxílio no diagnóstico de melanomas via imagens(2024-10-02) Silva Júnior, José Carlos Monte; Soares, Rodrigo Gabriel Ferreira; http://lattes.cnpq.br/2526739219416964Skin cancer is the most common type of cancer worldwide, divided into two main types: melanoma and non-melanoma. Although rarer, melanoma is the most lethal due to its potential to cause metastasis. Non-invasive methods, such as dermoscopy and the ABCDE rule, have been used to avoid unnecessary surgical procedures and have helped in the identification of lesions, contributing to faster diagnoses. With advances in technology, Artificial Intelligence (AI) has gained prominence, proving to be a promising solution for medical data analysis, especially with the use of Convolutional Neural Networks (CNNs), which can recognize patterns in dermoscopic images and help classify lesions as melanoma or non-melanoma in an automated manner. This project proposes an ensemble of classifiers based on Convolutional Neural Networks to classify dermoscopic images as melanoma or non-melanoma, comparing its performance with validated architectures, such as AlexNet and VGG-16, using Transfer Learning techniques The analyses of Precision, Recall, and F1 Score showed that the ensemble of Convolutional Neural Networks outperformed the models using Transfer Learning techniques, with AlexNet showing better performance than VGG-16. The ensemble of Convolutional Neural Networks demonstrated a greater generalization capability, proving to be promising in capturing relevant features from the images, revealing potential for medical applications, although it still needs refinement to meet clinical standards.Item Análise de sentimentos em reviews de jogos digitais da Plataforma Steam(2024-09-26) Albuquerque, Júlia de Melo; Albuquerque Júnior, Gabriel Alves de; http://lattes.cnpq.br/1399502815770584Sentiment analysis is an area that investigates the emotional expressions of human language, aiming to understand the underlying needs and opinions expressed in texts. Its complexity lies in the ability to discern not only the textual content but also the implicit emotional matrices. With technological advancements, the ease of publicly expressing opinions is disseminated through various means, with online gaming being a sector that attracts numerous player posts about various available titles. However, this diversity of audiences and topics makes it challenging to understand the expressed sentiment that pervades this universe. The aim of this study is to apply sentiment analysis techniques to digital game reviews, adopting an approach focused on supervised machine learning algorithms and pre-polarized libraries, in order to identify the best classification path capable of discerning the sentiments expressed by users in the reviews. This operation considers an approach with all opinions and another focused on each game’s specific genre. This analysis was conducted by exploring data from an online game distribution company (Steam), followed by data preparation due to the peculiarities present in the records. The results reveal that machine learning models outperform traditional approaches, such as using the VADER library, showing a higher precision by approximately 10% in captures. A difference of 20% more was observed in metrics such as recall and F1-score. This study represents an analytical contribution to the field of sentiment analysis, highlighting the model’s ability to deal with the complexity of human language.Item Análise comparativa de ferramentas de testes automatizados de ponta a ponta em ambientes de aplicações web(2024-03-11) Farias, Guilherme Carneiro de; Monteiro, Cleviton Vinicius Fonsêca; http://lattes.cnpq.br/9362573782715504In a context where software occupies an increasingly relevant and complex space in society, it is extremely important to enable means for it to be developed with quality. One of these means is automated testing, and in the current scenario, we observe the emergence of a variety of tools in this area, each with its own nuances and unique functionalities. Faced with this diversity of options, this research compares the main end-to-end testing automation tools in web application environments, aiming to facilitate the choice of the most suitable for each project. The theoretical foundation includes concepts of Software Quality, Software Testing, and Architecture and Automation Testing Tools. Three tools were identified and evaluated: Selenium WebDriver, Cypress, and Playwright. The research method is exploratory and descriptive, combining qualitative and quantitative approaches. The results indicate that Playwright presents the best combination of features for end-to-end automated testing in web applications.Item Como o uso de Play Feature Delivery no Android pode ajudar na sustentabilidade digital(2023-09) Claudino, Yasmmin Maria Monteiro; Albuquerque Júnior, Gabriel Alves de; http://lattes.cnpq.br/1399502815770584; http://lattes.cnpq.br/0549149216731460With the increasing access to the internet via mobile devices among the less privileged classes in Brazil, digital sustainability becomes of growing importance. The aim of this study is to assess the impact of the Play Feature Delivery technology on mobile data consumption on Android devices. A parametric t-test was applied to evaluate significant differences between the averages of data amounts spent in Megabytes when downloading two applications. The result corresponded to a t-value of approximately 65.55 and the rejection of the null hypothesis. This finding not only underscores the technical importance for Android developers but also highlights its relevance in showing an improvement in mobile data usage, especially in an era where the democratization of access to information is vital. The research reinforces the idea that society should adapt to digital resources, optimizing data usage. To reach these conclusions, two mobile applications focused on first aid guidelines were developed and analyzed. The main advantage observed was the reduction in mobile data consumption, validating the efficacy of Play Feature Delivery compared to conventional applications.Item Construção de pipelines de dados sobre obras públicas em Pernambuco: abordagem prática com o Apache Airflow(2023-09-21) Silva, Henrique César José da; Albuquerque Júnior, Gabriel Alves de; http://lattes.cnpq.br/1399502815770584This study presents a practical approach to building data pipelines focused on collecting, transforming, and storing information related to public works in the state of Pernambuco. The central objective is to develop efficient and automated workflows for extracting data from public transparency portals and subsequently consolidating this information. Based on Data Engineering technologies, the Apache Airflow framework was chosen to orchestrate the processes, enabling the scheduling and monitoring of these workflows.