https://tede.unioeste.br/handle/tede/507 Tue, 03 Feb 2026 19:09:54 GMT 2026-02-03T19:09:54Z https://tede.unioeste.br/handle/tede/8206 Title: Pós-edição humana apoiada por anotações de erro: um estudo de caso para textos científicos de português brasileiro para inglês Autor: Nürmberg, Rodrigo Schmidt Primeiro orientador: Spanhol, Fabio Alexandre Abstract: The internet and globalization have boosted the demand for translation services. In this scenario, the automated translation of texts, by means of computer programs, aims to meet part of this demand and improve the productivity of translators. However, problems with the quality of automated translation are accentuated in specific contexts, due to the characteristics of the domain, such as the translation of scientific texts, an area in which more than 80% of all world publications are in English. The improvement in the fluency of automated translations makes it difficult to identify such errors, demanding additional attention from proofreaders. A case study was conducted to investigate whether error annotations, generated by quality estimation models of automated translations, can support translators in the post-editing of scientific texts, translated from Brazilian Portuguese into English, with a view to increasing the productivity and quality of translations. No evidence of increased productivity was found, associated exclusively with the presence of highlights. The quality assessments are still under analysis and their results will be communicated in due course. Although translators in the highlighted modalities corrected 1.5 times more critical errors than those in the No highlighted modality, no significant differences were found in quality averages between the modalities. In terms of usability, participants acknowledged the influence of highlights on post-editing, but their perception of its usefulness was mixed. Keywords: machine translation; scholarly communication; quality estimation; Publisher: Universidade Estadual do Oeste do Paraná Tipo do documento: Dissertação Fri, 12 Sep 2025 00:00:00 GMT https://tede.unioeste.br/handle/tede/8206 2025-09-12T00:00:00Z https://tede.unioeste.br/handle/tede/8205 Title: Uma aplicação de visão computacional para detecção automática de defeitos em pavimentação asfáltica urbana no Brasil Autor: Borges, Marcos Augusto Primeiro orientador: Spanhol, Fabio Alexandre Abstract: Road infrastructure maintenance is a cornerstone of well-functioning cities, as it directly influences urban mobility, traffic safety, and the efficiency of transporting people and goods. However, the natural deterioration of pavements—compounded by increasing traffic and the lack of adequate preventive maintenance—leads to recurrent damage that affects both users and public management. In this context, efficient monitoring methods are indispensable to ensure roadway quality and to reduce costs associated with emergency interventions. This work aims to develop an automated system for detecting damage in asphalt pavements using computer vision and deep learning techniques. Among the principal challenges addressed are the accurate identification and classification of different defect types: fissures (cracks), deformations, ravelling (surface wear), potholes, and patches. We present a publicly available dataset of high-resolution digital images of urban pavements, structured in accordance with Brazilian standards and accompanied by per-image annotations curated by a technical committee. The study also proposes an efficient methodology for automated roadway condition assessment based on images collected with a smartphone mounted on the bumper of a passenger vehicle. The model trained with YOLOv5 achieved an mAP@50 of 84.4%. These results are intended to support public administrations in making decisions about maintenance and interventions, leading to improvements in the quality and safety of road infrastructure. Publisher: Universidade Estadual do Oeste do Paraná Tipo do documento: Dissertação Fri, 03 Oct 2025 00:00:00 GMT https://tede.unioeste.br/handle/tede/8205 2025-10-03T00:00:00Z https://tede.unioeste.br/handle/tede/8184 Title: Monitoramento da irrigação por gotejamento com bombeamento fotovoltaico autônomo e direto Autor: Goés, Naila Cristina Kepp de Primeiro orientador: Boas, Marcio Antonio Vilas Abstract: Autonomous direct photovoltaic pumping is a sustainable technological solution that directly uses solar energy to power water pumps, without the need for batteries or electronic controllers. This system operates intermittently, following the variation in solar irradiance throughout the day, which makes its design and management a challenge. Therefore, the objective of this research was to monitor the uniformity of water application in a drip irrigation system powered by autonomous direct photovoltaic pumping. Three irrigation systems with hoses of different wall thicknesses and emitters from different manufacturers were analyzed. The experiment was conducted at the UNIOESTE Irrigation and Fertigation Laboratory, using a 10-meter irrigation bench. The photovoltaic system consisted of a 150 Wp module connected directly to a submersible pump, without the use of batteries. Twenty-five trials were carried out per treatment, with flow rate measurements taken every 45 minutes between 9 a.m. and 5 p.m. under different irradiance conditions. The variables calculated included flow rate, pressure, irradiance, and hydraulic power, and the data were analyzed using Shewhart control charts and the Coefficient of Uniformity of Distribution (CUD). The results showed that the Aries (Netafim) and Irritec 1.1 L/h emitters showed excellent uniformity, with mean CUD values above 95%, even under average irradiance of 360 W·m⁻², while the Irritec 2.1 L/h model obtained lower uniformity (87%). It was found that hoses with greater wall thickness provided greater stability in relation to the system’s fluctuating pressure, improving application uniformity. Despite the greater hydraulic power observed in higher flow emitters, the choice of emitter should also take into account uniformity parameters and cost effectiveness, especially in autonomous systems without a controller. Publisher: Universidade Estadual do Oeste do Paraná Tipo do documento: Tese Mon, 04 Aug 2025 00:00:00 GMT https://tede.unioeste.br/handle/tede/8184 2025-08-04T00:00:00Z https://tede.unioeste.br/handle/tede/8181 Title: Codigestão anaeróbia de lixiviado de aterro sanitário com lodo flotado de agroindústria para produção de biogás Autor: Dechechi, Fernanda Gomes Primeiro orientador: Gotardo, Jackeline Tatiane Abstract: Sanitary landfill leachate, commonly known as “leachate”, exhibits high diversity and complexity in its pollutant load, making it difficult to apply a single treatment method. To prevent environmental impacts associated with its discharge into water bodies or soil, leachate must undergo complete treatment. In turn, centrifuged floated sludge, an effluent generated in agro industrial wastewater treatment, poses the challenge of being produced in large volumes, resulting in significant costs for disposal and transport to licensed facilities. Due to these characteristics, both effluents motivated the investigation of anaerobic co-digestion for biogas production, fostering the development of sustainable alternatives for treatment and clean energy generation. The objective of this study was to assess the efficiency of organic matter removal and biogas production from sanitary landfill leachate co-digested with centrifuged floated sludge from an agro-industrial complex in batch reactors, aiming at energy recovery. The research was divided into three phases: Phase 1: batch reactor using the Ritter fermentation system; Phase 2: batch reactor in BOD bottles; and Phase 3: batch reactor in a shaker. In all phases, the residues were collected and their physicochemical characteristics analyzed, as well as the mixtures of each reactor before incubation and at the end of the predetermined period. An experimental design was developed for Phases 1 and 2. Eleven reactors were incubated at 37ºC for approximately 60 days or until accumulated biogas production fell below 1%. The pH was adjusted before incubation, according to the central composite rotational design (CCRD), along with the proportions of the studied residues. Statistical analyses were applied to the results, and in Phase 2 it was possible to optimize the model. To validate the optimal point, the parameters obtained were applied to batch reactors operated on a shaker (Phase 3). Phase 1 showed that the test reactor containing centrifuged floated sludge performed better than the reactor with non-centrifuged floated sludge for the response variable (COD removal). Thus, centrifuged floated sludge was selected as the essential co-substrate for the experimental design in Phase 2. In Phase 2, among all reactors in the experimental design, Reactor 6 achieved the highest COD removal (73.73% for centrifuged COD and 84.38% for filtered COD), operating with 95% leachate and pH 7.5. For methane production, the central points of the design showed the highest values, approximately 7.5 L CH₄/L reactor, with parameters of 97.5% leachate and pH 7.5. The reactor containing only leachate (Reactor 5) and the test reactors with only centrifuged floated sludge or distilled water (Reactors 19 and 20) did not show significant results, confirming the advantage of co digestion over mono-digestion. Model optimization indicated 96.3% landfill leachate and pH 7.7 as the optimal independent variables, predicting 6.76 L CH₄/L reactor. After operating the Phase 3 reactor, methane production exceeded expectations, reaching 10.01 L CH₄/L reactor. In conclusion, the co-digestion of sanitary landfill leachate with centrifuged floated sludge from poultry processing contributes to advances in clean and renewable energy research, supporting energy autonomy through biogas production. Finally, for real-scale application, obtaining seasonal operational data from a pilot-scale reactor is recommended to generate a robust database and increase confidence in system design Publisher: Universidade Estadual do Oeste do Paraná Tipo do documento: Dissertação Mon, 25 Aug 2025 00:00:00 GMT https://tede.unioeste.br/handle/tede/8181 2025-08-25T00:00:00Z