https://repositorio.ifpe.edu.br/xmlui/handle/123456789/494 Sun, 12 Apr 2026 07:14:38 GMT 2026-04-12T07:14:38Z https://repositorio.ifpe.edu.br/xmlui/handle/123456789/2056 ANS2JSON: uma API baseada em IA, para extração de Informações da avaliação neurológica de pacientes com hanseníase The Simplified Neurological Assessment (SNA) is a mandatory and essential tool for monitoring patients with leprosy in Brazil. However, its physical format and manual completion represent a significant obstacle, as they confine crucial clinical data to paper records and hinder longitudinal analyses, large-scale research, and evidence-based health policymaking. This study introduces ANS2JSON, an innovative application that overcomes this barrier through a hybrid Artificial Intelligence architecture for the complete and automatic digitization of SNA forms. The proposed solution addresses the challenge of interpreting a complex form that combines textual data with visual diagrams by employing a two-stage pipeline: (1) a computer vision model (YOLOv8 + Random Forest) to detect and anatomically map sensitivity assessment points, and (2) an Intelligent Document Processing model to extract textual fields. The approach demonstrated outstanding effectiveness, achieving 97.5% precision in visual data interpretation and over 95% accuracy in extracting key clinical indicators. ANS2JSON, publicly available via the web, provides a robust tool for converting a vast repository of unstructured data into ready-to-use digital information, unlocking the potential of years of clinical records to advance both leprosy treatment and research. The application is accessible at: https://ans2json.dotlabbrazil.com.br . Tue, 16 Sep 2025 00:00:00 GMT https://repositorio.ifpe.edu.br/xmlui/handle/123456789/2056 2025-09-16T00:00:00Z https://repositorio.ifpe.edu.br/xmlui/handle/123456789/1999 Monitoramento ambiental de recursos abióticos This report describes the supervised internship carried out at the Pernambuco State Environmental Agency (CPRH), within the Abiotic Resources Monitoring Unit (UMRA), between September 2021 and September 2023, with a workload of 20 hours per week. The objective was to experience professional practice in public environmental management, applying and expanding the knowledge acquired in the Technology in Environmental Management course at IFPE. The main activities focused on the environmental monitoring of abiotic resources (water, air, and solid waste), specifically: (i) the calculation and organization of data for the Water Quality Index (IQA), using software Microsoft® Excel spreadsheets based on the CETESB methodology and on CONAMA resolution nº 357/2005; (ii) the generation and dissemination of daily Air Quality Index (IQAr) bulletins, based on processing data from automatic pollutant monitoring stations and the application of CONAMA Resolution No. 506/2024; and (iii) the monitoring and processing of data from the Annual Declaration of Solid Waste (DARS), involving support to declarants via the SGRI/SILIA systems and email. The experience provided a direct integration between the theory from the curriculum of the Higher Technology Course in Environmental Management (mainly Water Resources Management, Atmospheric Pollution, Waste Management, and Environmental Legislation) and the operational practice of a state environmental agency, developing technical (software handling, data analysis, application of regulations), professional (ethics, proactivity, communication), and interpersonal skills. The evaluation of the experience is extremely positive, highlighting the qualified supervision, the relevance of the activities for professional training, and the institutional stance of CPRH in fostering learning, culminating in an effective contribution to public disclosure technical products. The internship confirmed the relevance of the academic training and the complexity of environmental management in the public sector. Mon, 26 Jan 2026 00:00:00 GMT https://repositorio.ifpe.edu.br/xmlui/handle/123456789/1999 2026-01-26T00:00:00Z https://repositorio.ifpe.edu.br/xmlui/handle/123456789/1997 Turismo pedagógico no IFPE campus Recife: uma análise do potencial formativo para o ensino médio a partir da valorização do sentimento de pertencimento à cidade do Recife a visão docente The following analysis aims to highlight teachers’ perspectives on pedagogical tourism, emphasizing its importance for students’ development as well as the challenges faced in its implementation. This study examined how pedagogical tourism is addressed in the Integrated High School at IFPE Campus Recife, reaffirming its relevance as an formative practice. The analysis provides a foundation for implementing strategies that enhance this approach in the school context, contributing to the strengthening of the teaching-learning process and the integral education of students. The research adopted a descriptive and qualitative approach, combining a literature review on public policies, educational projects, and pedagogical tourism practices in Recife with data collection through open-ended questions addressed to IFPE Campus Recife teachers. Eight questions were applied, allowing the understanding of teachers’ perceptions of the impact of pedagogical tourism on the teaching-learning process and on students’ appreciation of the city. The findings indicate that pedagogical tourism at IFPE Campus Recife has great potential as an formative strategy, capable of linking academic knowledge with cultural experiences, thus reinforcing both learning and students’ emotional connection with their environment. However, further articulation is still needed for the effective development of such activities. Tue, 09 Sep 2025 00:00:00 GMT https://repositorio.ifpe.edu.br/xmlui/handle/123456789/1997 2025-09-09T00:00:00Z https://repositorio.ifpe.edu.br/xmlui/handle/123456789/1988 Contagem automática de ovos de mosquitos Aedes em ovitrampas com visão computacional baseada em aprendizado de máquina The present study proposes the automation of egg counting for Aedes aegypti and Aedes albopictus mosquitoes, vectors of arboviruses, through computer vision based on machine learning. Using images from ovitraps provided by Fiocruz-PE, fine-tuning was applied to advanced models (YOLOv10, YOLOv11, and Faster R-CNN) to overcome challenges related to high variability and noise in the images. The solution reduces manual effort and analysis time, contributing to more effective strategies for controlling diseases such as dengue, zika, and chikungunya. Thu, 13 Nov 2025 00:00:00 GMT https://repositorio.ifpe.edu.br/xmlui/handle/123456789/1988 2025-11-13T00:00:00Z