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ABSTRACT In this study, performances of Multiple Linear Regression and Automatic Linear Modelling are compared for different sample sizes and number of predictors. A comprehensive Monte Carlo simulation study was carried out for this purpose. Random numbers generated from multivariate normal distribution by using RNMVN function of IMSL library of Microsoft FORTRAN Developer Studio composed the material of this study. Results of the simulation study showed that the sample size and the number of predictors are the main factors that lead to produce different results. Although both methods gave very similar results especially when studied with large sample sizes (n≥100), the Automatic linear modelling is preferred for analyzing data sets due to its simplicity in analyzing data and interpreting the results, ability to present results visually and providing more detailed information especially studying large complex data sets. It will be beneficial to use the Automatic linear modelling especially in analyzing massive and complex data sets for the purposes of investigating the relationships between one continuous dependent and 10 or more predictors and determine the factors that affect the response or target variable. At the same time, it will also be possible to evaluate the effect of each predictor with a more detailed response.

Surface Reconstruction from raw Pointclouds generates polygonal meshes characterised by typical local issues that need to be addressed by a global reorganisation of mesh connectivity during the Remeshing process. While in the applications for which remeshing algorithms have historically been developed, the problem can be addressed without affecting the mesh polycount, for the authoring of 3D assets intended for Real-Time Rendering applications, maintaining a low polycount is mandatory. However, there is a trade-off between the number of polygons and accuracy. Hence, in cases where accuracy is a primary concern, such as with Digital Cultural Heritage Objects, the topology of the mesh that ensures this reduction becomes crucial since, to an even polycount, the dimensional discrepancy between the original and different simplified meshes can vary significantly.Therefore, it is vital to evaluate the characteristic quality obtainable from different remeshing algorithms with simplification, but despite the importance of the matter, there is a lack of metrics to perform such comparative benchmarks. This study aims to address this gap by defining and testing a Shape Complexity Index on real-world case studies, which is applicable uniformly and consistently to geometric shapes of generic complexity. Such index allows for pre-determine a target polycount and subsequently normalising signed distance computations among different test simplified meshes, posing the basis for both quantitative and qualitative analysis of accuracy achievable by any automatic remeshing tool. Additionally, the proposed workflow is employable as an instrument for planning, monitoring, and reporting a digitisation campaign of objects belonging to the Cultural Heritage.DOI: https://doi.org/10.20365/disegnarecon.32.2024.10

The use of automatic item generation (AIG) methods offers potential for assessing clinical reasoning (CR) skills in medical education, a critical skill combining intuitive and analytical thinking. In preclinical education, these skills are commonly evaluated through written exams and case-based multiple-choice questions (MCQs), which are widely used due to the high number of students, ease of standardization, and quick evaluation. This research generated CR-focused questions for medical exams using two primary AIG methods: template-based and non-template-based (using AI tools like ChatGPT for a flexible approach). A total of 18 questions were produced on ordering radiologic investigations for abdominal emergencies, alongside faculty-developed questions used in medical exams for comparison. Experienced radiologists evaluated the questions based on clarity, clinical relevance, and effectiveness in measuring CR skills. Results showed that ChatGPT-generated questions measured CR skills with an 84.52% success rate, faculty-developed questions with 82.14%, and template-based questions with 78.57%, indicating that both AIG methods are effective in CR assessment, with ChatGPT performing slightly better. Both AIG methods received high ratings for clarity and clinical suitability, showing promise in producing effective CR-assessing questions comparable to, and in some cases surpassing, faculty-developed questions. While template-based AIG is effective, it requires more time and effort, suggesting that both methods may offer time-saving potential in exam preparation for educators.

Gross motor skills such as sitting, jumping, and running are activities that involve the large muscles of the human body. The Test of Gross Motor Development, or TGMD, is widely used by researchers, pediatricians, physiotherapists, and educators from different countries to assess these skills in children aged 3 to 11 years. An important part of the test is that the movement, performed by the children, needs to be recorded and assessed by two or more professionals. The assessment process is laborious and takes time, and its automation is one of the main points to be developed. In recent years, methods have been proposed to automate the assessment according to the TGMD. The hypothesis investigated in this work is that it is possible to induce a machine learning model to identify whether the movement executed by the child is correct, considering only the first criterion of the TGMD-3 jumping skill. The skeleton of the children was extracted using PoseNet. A dataset of 350 images of Brazilian children between 3 and 11 years old performing the preparatory movement for the jump was used. The experimental results show an accuracy of 84%.

In a cluster of news texts on the same event, two sentences from different documents might express different multi-document phenomena (redundancy, complementarity, and contradiction). Cross-Document Structure Theory (CST) provides labels to explicitly represent these phenomena. The automatic identification of the multi-document phenomena and their correspondent CST relations is definitely handy for Automatic Multi-Document Summarization since it helps computers understand text meaning. In this paper, we evaluated a typology of (textual) signals for the automatic detection of the CST relations of complementarity (i.e., Historical background, Follow-up and Elaboration) in a multi-document corpus of news texts in Brazilian Portuguese. Using algorithms from different machine-learning paradigms, we obtained classifiers that achieved high general accuracy (higher than 90%), indicating the potential of the signals.

ABSTRACT This study was carried out for two purposes: comparing performances of Regression Tree and Automatic Linear Modeling and determining optimum sample size for these methods under different experimental conditions. A comprehensive Monte Carlo Simulation Study was designed for these purposes. Results of simulation study showed that percentage of explained variation estimates of both Regression Tree and Automatic Linear Modeling was influenced by sample size, number of variables, and structure of variance-covariance matrix. Automatic Linear Modeling had higher performance than Regression Tree under all experimental conditions. It was concluded that the Regression Tree required much larger samples to make stable estimates when comparing to Automatic Linear Modeling.

This article aims to problematize the relationship between automatic writing and the marvelous. To do so, we start from the interest of young André Breton in creative processes beyond the literary sphere, in a context where, in addition to Freud's recent discoveries about the unconscious, various experiences intersect: a poetic production that experiments with the decentralization of the creating subject, scientific investigations in the field of neurology and psychiatry on automatic psychic phenomena, and belief in the manifestation of life after death. All these experiences point to the same issue: the manifestation of thought, free from the coercion of morality, taste, and reason. Although there is something universal in this issue, perhaps inherent to the poetic experience itself, we recognize that surrealist automatism is an original "war machine" against reflection and language, the literary institution, the notion of reality, and the foundations of modernity. Despite all the controversies surrounding surrealist automatic writing, it makes a difference because it is all difference; by freeing language from its communicative function, it does not express the freedom of man, it is freedom in action, revealing the unknown and opening the doors to the marvelous. [ABSTRACT FROM AUTHOR]

Abstract: Automatic summaries commonly present diverse linguistic problems that affect textual quality and thus their understanding by users. Few studies have tried to characterize such problems and their relation with the performance of the summarization systems. In this paper, we investigated the problems in multi-document extracts (i.e., summaries produced by concatenating several sentences taken exactly as they appear in the source texts) generated by systems for Brazilian Portuguese that have different approaches (i.e., superficial and deep) and performances (i.e., baseline and state-of-the art methods). For that, we first reviewed the main characterization studies, resulting in a typology of linguistic problems more suitable for multi-document summarization. Then, we manually annotated a corpus of automatic multi-document extracts in Portuguese based on the typology, which showed that some of linguistic problems are significantly more recurrent than others. Thus, this corpus annotation may support research on linguistic problems detection and correction for summary improvement, allowing the production of automatic summaries that are not only informative (i.e., they convey the content of the source material), but also linguistically well structured. Keywords: automatic summarization; multi-document summary; linguistic problem; corpus annotation. Resumo: Sumários automáticos geralmente apresentam vários problemas linguísticos que afetam a sua qualidade textual e, consequentemente, sua compreensão pelos usuários. Alguns trabalhos caracterizam tais problemas e os relacionam ao desempenho dos sistemas de sumarização. Neste artigo, investigaram-se os problemas em extratos (isto é, sumários produzidos pela concatenação de sentenças extraídas na íntegra dos textos-fonte) multidocumento em Português do Brasil gerados por sistemas que apresentam diferentes abordagens (isto é, superficial e profunda) e desempenho (isto é, métodos baseline e do estado-da-arte). Para tanto, as principais caracterizações dos problemas linguísticos em sumários automáticos foram investigadas, resultando em uma tipologia mais adequada à sumarização multidocumento. Em seguida, anotou-se manualmente um corpus de extratos com base na tipologia, evidenciando que alguns tipos de problemas são significativamente mais recorrentes que outros. Assim, essa anotação gera subsídios para as tarefas automáticas de detecção e correção de problemas linguísticos com vistas à produção de sumários automáticos não só mais informativos (isto é, que cobrem o conteúdo do material de origem), como também linguisticamente bem-estruturados. Palavras-chave: sumarização automática; sumário multidocumento; problema linguístico; anotação de corpus.

Purpose – The purpose of this study is to identify arrangements of fully funded defined contribution (FF-DC) pension plans associated with the continuity of retirement savings. Design/methodology/approach – The authors adopted an experimental design composed of a control group and two treatment groups. In all groups, individuals made decisions throughout nine periods: five during the working period and four at the postretirement stage. The authors asked participants if they wanted to join a pension plan, and which plan. The authors offered three plans with different risk profiles: plan 1 (high risk), plan 2 (moderate) and plan 3 (low risk) and one risk-free plan, plan 4. In treatment groups 1 and 2, there was an automatic enrollment of the participants in the default plan (moderate risk), and in the following periods they had to decide whether to continue contributing, and in this case, to which plan, with a defined percentage. Findings – In treatment scenarios, participants chose the riskiest plan in all periods of the experiment, and most of them chose the risk-free plan in period 5. These findings suggest that pension plans with automatic enrollment, employer matching and low risk foster the continuation of retirement savings. Research limitations/implications – The research has as limitation the fact that the sample is not representative of the population and therefore does not allow generalizations. This is because the authors use social media ads to prospect respondents. Practical implications – The research's findings can be relevant for the design of public policies for private pension plans, suggesting that compulsory automatic enrollment can be used as default in plans offered by the employers. The results encourage the inclusion of behavioral elements in the design of the pension system, paying attention to the nudges. In this sense, it is possible to increase participation in the pension plan and develop low cost programs to increase the amount accumulated by people before retirement. Social implications – Decision-making architecture, such as automatic enrollment, can improve individuals' retirement decisions, affecting savings and welfare in the long run. Originality/value – Although the effect of pension plan designs is widely studied in other countries, such as the United States and United Kingdom, the authors are unaware of a national empirical research that seeks to understand how different arrangements affect an individual choice through an experiment.

This paper presents a reflection on two technologies - automatic speech recognition (ASR) and Text-to-Speech (TTS) - to improve learners’ pronunciation, aiming for successful spoken communication. It sheds some light on the practical usage of these technologies, demonstrating their effectiveness, qualities, and limitations to assist teachers in deciding the most efficient digital resources applied to their students’ needs. A review of literature on previous empirical studies was carried out, with quantitative and/or qualitative studies conducted by researchers in the field, investigating teachers’ and learners' perceptions and the use of ASR and TTS as a pedagogical tool for pronunciation practice. As a result, it was concluded that a) the presented resources seem to have the potential to enhance pronunciation practice, both in terms of perception and production; b) technology can result in considerable benefits to learners, mainly as a supplement to pronunciation teaching; and c) the use of these digital resources is a way of giving learners the opportunity to focus on their specific difficulties and receive personalized feedback while becoming more autonomous in their learning process.

ABSTRACT Objective: To develop a well-detailed and reproducible tooth segmentation method, when quantifying tooth volumetric measurements is needed. Material and Methods: This was an in vitro study in which lower incisors and canines of five patients were 3D reconstructed by means of an automatic segmentation with manual refinements process. All the images were obtained using a 0.3-mm voxel size CBCT imaging. The software utilized was the ITK-SNAP®. The primary outcomes were the intra-rater and inter-rater reliabilities and the respective measurement errors. Results: The intra-rater reliability was excellent, with a mean measurement error of 4.16%. The inter-rater reliability was good, with a mean measurement error of 7.11%. Accuracy assessment was not possible, as the assessed teeth were not extracted. Conclusions: Although the described method is reliable, tooth volumetric error measurements may become significant, depending on the assessed situation.

Copyright of Perspectivas em Ciência da Informaçao is the property of Nova Economia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Resumen La tecnología puede facilitar el aprendizaje de la gramática de una lengua, por ejemplo, a través de la revisión automática de los textos. El objetivo principal de este artículo es describir el desarrollo de una herramienta de ayuda a la redacción de textos en español que contribuye al aprendizaje de los conectores discursivos. La herramienta dispone de funcionalidades a nivel discursivo, que se basan en la clasificación de los conectores a partir de la relación discursiva que vehiculan (Antítesis, Causa, Concesión, etc.). Estas funcionalidades también tienen en cuenta dos tipos de conectores: intraoracionales e interoracionales. Así, la herramienta proporciona recomendaciones a los usuarios en relación con: a) la revisión de oraciones largas, b) la división de estas en otras más breves mediante conectores y c) la variación en el uso de los mismos. Abstract Technology can make it easier to learn the grammar of a language, for example, through the automatic review of texts. The main goal of this article is to describe the development of an automatic tool that helps to write texts in Spanish and contributes to the learning of discourse connectors. The tool includes discourse-level functionalities. They are based on a connectors’ classification that takes discourse relations into account (Antithesis, Cause, Concession, etc.). In addition, these functionalities comprise two types of connectors: intrasentence and intersentence connectors. Thus, the tool provides users with recommendations in relation to several aspects, such as: a) revision of long sentences, b) segmentation of long sentences into shorter ones by means of connectors and c) variation in the use of connectors.

Copyright of Nativa is the property of Revista Nativa and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Brachytherapy is the use of radiotherapy with insertion of radiation sources close to the site that needs treatment. It has become an extremely sought-after option by research fields for its impressive efficiency and practicality. In addition to being a fast-paced procedure, it allows patients to leave hospital care very soon after it is done, without pain or with minor discomfort, which can be considered an advantage. The brachytherapy procedure is divided into two stages, obtaining images of the region where seed implantation will take place and the application itself. The images are obtained by ultrasonography, which will guide the insertion of the needle into the patient's body. During the injection, the patient is anesthetized and immobilized, so that movements that compromise the accuracy of the needle, which, by the current manual method, are already subject to oscillations are avoided. Currently the application of radioactive seeds is done manually by a clinician who uses needles and monitors their positions through the images generated by ultrasound equipment. Thus, the main objective of this project was to improve the prototype of the Prostate Seed Implantation System (SISP), developed by the Nuclear Engineering Department of the UFMG (Nuclear Engineering Department). Thus, the device allows automated scanning on x, y and z axes, facilitating the application of radioactive seeds in prostate brachytherapy treatments, which in current treatments are done manually by the clinician. And the possibility of controlling this movement via BLUETOOTH technology.

Copyright of Boletim de Geografia is the property of Universidade Estadual de Maringa and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study analyzes the constitutionality of §3° of article 496 from Brazilian Procedure Code (Federal law number 13.105/2015), considering rules of collective interest, material equality, federalism, financial autonomy and legislative powers of Federal Government, States, Federal District and municipalities. Additionally, it presents legislative propositions to optimize the automatic appeal and its exemptions.

The purpose of this study is to develop a predictive model that increases the accuracy of business operational planning using data from a small business. By using Machine Learning (ML) techniques feature expansion, resampling, and combination techniques, it was possible to address several existing limitations in the available research. Then, the use of the novel technique of feature engineering allowed us to increase the accuracy of the model by finding 10 new features derived from the original ones and constructed automatically through the nonlinear relationships found between them. Finally, we built a rule-based classifier to predict the store's revenue with high accuracy. The results show the proposed approach open new possibilities for ML research applied to small and medium businesses.

ABSTRACT This paper presents an algorithm capable of calculating the optimal route for pipelines that traverse terrain with or without additional displacement constraints to the difference in ground elevations and head losses to be overcome by pumping. The criterion used to determine the pipeline diameter and calculate feasible routes was minimizing the annual cost, which results from the sum of (i) annualized costs related to the acquisition of the pipeline and (ii) costs of payment for electric power to operate the system throughout its useful life. The geometry of the shortest routes in the multidimensional search space is calculated by the proposed algorithm, called BAGDA (Busca pelo Ajuste Geométrico da Despesa Anual, in Portuguese, or Search for the Annual Cost of Geometric Tuning, in English), thus obtaining the optimal combination of length and manometric head of the pipeline. The performed applications show the efficiency of the algorithm in providing subjectivity-free routes sensitive to the most important variables considered in the design of piping systems.

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

ABSTRACT With the increasing scale of farms and the correspondingly higher number of laying hens, it is increasingly difficult for farmers to monitor their animals in a traditional way. Early warning of abnormal animal activities is helpful for farmers’ fast response to the negative impact on animal health, animal welfare and daily management. This study introduces an automatic and non-invasive method for detecting abnormal poultry activities using a 3D depth camera. A typical region including eighteen Hy-line brown laying hens was continuously monitored by a top-view Kinect during 49 continuous days. A mean prediction model (MPM), based on the frame difference algorithm, was built to monitor animal activities and occupation zones. As a result, this method reported abnormal activities with an average accuracy of 84.2% and a rate of misclassifying abnormal events of 15.8% (PFPR). Additionally, it was found that the flock showed a diurnal change pattern in the activity and occupation quantified index. They also presented a similar changing pattern each week.

An important piece of information for planning public transportation is the number of passengers using the system. Several initiatives have started to explore the Wi-Fi packets generated by passengers’ smartphones as means to obtain this information. A sensing device located inside the bus can intercept and collect these packets. By applying filters, e.g., verifying if the signal strength is higher than a threshold, the sensor can infer passengers' presence/absence. However, such limits are set arbitrarily, leading to errors, for example, when close to bus stops. To address this issue, this article proposes a method (UAI-FI) based on an artificial intelligence technique (Support Vector Machine) to classify the origin of packets as inside or outside the bus. To validate UAI-FI, we applied and compared our approach to other methods in a bus line in Goiânia/Brazil. The results suggest that UAI-FI outperformed existing methods. Furthermore, it successfully classified the packet’s origin, obtaining 83.3% and 88.5% of the total number of passengers boarding and alighting the line. Despite the overall similarity, we highlight that UAI-FI’s counting curve presented a delay compared to the manual count indicating that the frequency that Wi-Fi packets are sent can cause the presence/absence of passengers to be perceived at different stops.

Abstract: The objective of this work was to evaluate the growth performance of common snook (Centropomus undecimalis) subjected to different feeding rates and frequencies using automatic feeders. Two experiments of 60 days each were carried out. In the first one, 20 fishes per tank were distributed in three feeding rates of: 5, 10, and 15% body weight per day. In the second experiment, 20 fishes per tank were distributed in nine tanks, in three feeding frequency: once a day, three times a day, and six times a day. Water parameters were maintained at the recommended level for the species. Final weight, body weight gain, specific growth rate, and feed conversion rate did not differ significantly between the 10 and 15% feeding rates. However, both rates differed from the 5% one. The feeding frequency of six times a day resulted in better values for final weight, final biomass, body weight gain, and specific growth rate. Therefore, common snook fingerlings should be fed at the feeding rate of 10% body weight per day, six times a day, in order to achieve the best growth performance.

This work presents the development of an automatic radioactive seed implantation system (PSIS). PSIS may assist the testing permanent implants procedure in the prostate. These tests will be important in measurements of absorbed doses in the pelvic structures, involving the organs and tissues at risk to improve planning, seed positioning and dosimetry. The automated Prostate Seed Implant System (PSIS) has been designed to meet operational needs, which offers the freedom when positioning the brachytherapy needle inside the treatment area ensuring repeatability and fidelity to the planned treatment. Both the ultrasound probe and the seed implant needle are driven by stepper motors, ATMEGA microcontroller, bearings, aluminum shafts and a GUI (Graphical User Interface). Movement of both the probe and the needle holder was performed by fixed spindle on a threaded rod going through a stepper motors by a coupling. These engines were chosen due to the necessity of movements precision that these types of motors provide. The project was developed and the PSIS prototype was assembled. The prototype presented acceptable operating characteristics for prostate implants. The advantage of this system is that the automation of the application provides an accurate positioning and movement of both probe and seed application. In addition to this study, seeds implantation tests will be performed, and such tests will be essential in protocol validation processes.

Abstract: Automatic geocoding methods have become popular in recent years, facilitating the study of the association between health outcomes and the place of living. However, rather few studies have evaluated geocoding quality, with most of them being performed in the US and Europe. This article aims to compare the quality of three automatic online geocoding tools against a reference method. A subsample of 300 handwritten addresses from hospital records was geocoded using Bing, Google Earth, and Google Maps. Match rates were higher (> 80%) for Google Maps and Google Earth compared with Bing. However, the accuracy of the addresses was better for Bing with a larger proportion (> 70%) of addresses with positional errors below 20m. Generally, performance did not vary for each method for different socioeconomic status. Overall, the methods showed an acceptable, but heterogeneous performance, which may be a warning against the use of automatic methods without assessing quality in other municipalities, particularly in Chile and Latin America.

The present article was developed in the field of Natural Language Processing and Language Studies based on a corpus compiled by computational tools. This study is based on the assumption that it is helpful to trace a close relationship between corpus generation/annotation and the assessment of the constitutive elements of the text genre source. It aims to demonstrate, through specific studies of structured data from the text genre ‘scientific article’, alternatives to automatic text processing techniques. In order to reach the intended goal, the authors created a computational model for the compilation of a linguistic, specialized Corpus, representative of the genre Scientific Article - CorpACE. The object of study includes the constitutive elements of scientific articles, marked in XML, extracted and collected from the SciELO-Scientific Electronic Library On-line database. The final product was a database obtained with information extracted and structured in XML format, which designates and identifies the markups of the genre being analyzed and is available for many tools and applications. The results demonstrate how the representation of constitutive elements of the genre can condense available information with hierarchical and dynamic processes built during the compilation. At the end of the study, it is believed that more research will be required for bringing Language Science and Computer Science closer with emphasis on NLP in the attempt to represent and manipulate linguistic knowledge in its many levels – morphological, syntactic, semantic and discursive – in order to improve implementation and manipulation of automatic text processing.

ABSTRACT The aim of the current study is to develop an electronic system capable of automatically replacing hydraulic spray nozzles, based on psychrometric air conditions such as temperature and relative air humidity, in order to help improving the efficiency of application technologies. The system comprised one microcontroller, two solenoid valves, one temperature and relative humidity sensor, and a control algorithm. The system was installed in a hydropneumatic sprayer adapted with two semi-arcs. One semi-arc was equipped with JA-2 and other semi-arc with CVIA-015 hydraulic nozzles. After the algorithm interpreted the momentary psychrometric air conditions, it activated the JA-2 (when VPD < 20 hPa) or the CVIA-015 nozzle (when VPD > 20 hPa). The system was evaluated based on technical spraying parameters and on the response time to replace the hydraulic nozzle. Based on the results, the smallest-diameter droplets were the most influenced by psychrometric air conditions. VPD > 20 hPa tended to increase the VMD values and to reduce droplet density, although it did not change the SPAN index. The necessary mean time to switch from the JA-2 to the CVIA-015 nozzle was 0.742 s, whereas the necessary mean time to switch from the CVIA-015 to the JA-2 nozzle was 0.684 s.

In recent years, several studies have indicated interpreters resist adopting new technologies. Yet, such technologies have enabled the development of several tools to help those professionals. In this paper, using bibliographical and documental research, we briefly analyse the tools cited by several authors to identify which ones remain up to date and available on the market. Following that, we present concepts about automation, and observe the usage of automatic speech recognition (ASR), while analysing its potential benefits and the current level of maturity of such an approach, especially regarding Computer-Assisted Interpreting (CAI) tools. The goal of this paper is to present the community of interpreters and researchers with a view of the state of the art in technology for interpreting as well as some future perspectives for this area.

The literature has vastly explored Automatic Essay Scoring (AES) in the last few years. The critical motivation is the possibility of reducing the human effort in scoring a large number of essays in a short period. In literature, most of the work concentrates on the English language; there is still a need for progress in Brazilian Portuguese. Thus, this works provides a Systematic Mapping Study aiming to identify Artificial Intelligence methods that support Automatic Essay Correction in Brazilian Portuguese. Furthermore, the main facts this paper brings are: (i) the methods focus on feature engineering methods instead of deep learning models; (ii) there is a prevalence of traditional metrics such as precision, coverage, and f-measure to evaluate the results; (iii) feedbacks provided by the tools have low-level of details; and (iv) there is no practical evaluation of the advancement in real-world applications. [ABSTRACT FROM AUTHOR]

The understanding of travel pattern dynamics in the urban environment is essential for the transportation systems planning and operation. Recently, the increasing availability of massive traffic data from traffic monitoring systems, including automatic number plate recognition systems (TMS-ANPR), can allow an understanding of the day-to-day variability of traffic flows in large urban network systems. However, to enhance the data quality for analysis, it is essential to carry out a previous data treatment. This work presents a method for treatment of TMS-ANPR data. The main product of this data treatment are the day-to-day time series of traffic volumes and OD flows for different periods of a typical day, allowing the analysis of the multiday dynamic of travel behavior and of the model assumptions stated in the literature about such dynamic behavior. The proposed method, which can be applied to any type of TMS-ANPR, was applied to generate time series data from the TMS-ANPR of Fortaleza city, contributing to identify suspicious and atypical data, to define representative patterns of vehicular traffic and to estimate series of OD flows.

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Water management is a key field to support life and economic activity nowadays. The greatly increased mechanization of agriculture, mainly through center pivot irrigation systems, represents a big challenge to control this resource. Irrigated agriculture makes up the large majority of consumptive water use, therefore it is important to identify and quantify these systems. Currently, with 6.95x10⁶ ha, Brazil is among the 10 largest countries in irrigation areas in the world. In this study, a combined Computer Vision and Machine Learning approach is proposed for the identification of center pivots in remote sensing images. The methodology is based on Circular Hough Transform (CHT) and Balanced Random Forest (BRF) classifier using vegetation indices NDVI/SAVI generated from Landsat 8 images and Land Use and Land Cover (LULC) data provided by project MapBiomas. The candidate's circles of pivots identified on images are filtered based on vegetation behavior and shape characteristics of these areas. Our approach was able to detect 7358 pivots, reaching 83.86% of Recall for 52 scenes analyzed overall Brazil compared with mapping done by the Brazilian National Water and Sanitation Agency (ANA). In some scenes, the Recall reaches up to 100%.

Copyright of Informacao & Sociedade: Estudos is the property of Universidade Federal de Campina Grande, Centro de Humanidades and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The following is the introduction to the first volume of Bernard Stiegler’s most recent work, La Société automatique, 1. L’Avenir du travail, published by Fayard in 2015. The second volume, subtitled L’Avenir du savoir, is forthcoming. This translation is published with the generous permission of the author.

Copyright of Saúde Coletiva is the property of MPM Comunicacao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Social bots are automated users who use social networks and messaging applications to interact with real users. These bots can be used for sharing important news such as weather information or in emergency situations. However, they can also be used for malicious purposes, such as spreading fake news. This paper presents a case study on bot penetration in electoral discussions during the second round of the 2018 Brazilian presidential elections. It was found that the number of bots participating in the electoral discussions may have exceeded 10% of the total users. The use of general user account characteristics proved to be very specic in identifying humans (it is estimated that over 97% of human users were correctly classified as humans), but bot recalls did not exceed 52.3%.

Translation memory systems have been promoting definitive changes in the development and contracting criteria of translations of texts in electronic format. With the purpose of examining the influence of the use of these tools in the production of translators in training, this paper presents a study proposing a reflective approach for the analysis of translations by students in academic training. For this purpose, eight participants attending the third year of an undergraduate program in Translation were invited to translate three contracts from English into Brazilian Portuguese with and without the assistance of Wordfast Classic (version 6.0). The results of the analysis of the students’ translations suggest that those who used the tool produced more uniform translations, with high similarity index between them, which may be indicative of the influence of the memory in the translation work. In view of the scarce research focused on the analysis of the way translators interact with the tools employed in their work and how they are affected by them, this study aims to contribute to a better understanding of the possible implications involved in the association between the translator and translation memory systems in the work of translation.

RESUMO: O transtorno do pânico (TP) é caracterizado por ataques de pânico, os quais surgem acompanhados por uma série de pensamentos inadequados ao contexto. Objetivo: identificar e sistematizar a distorção cognitiva e os tipos de pensamentos negativos automáticos (PNA) presentes em pacientes com TP. Participantes: 20 indivíduos na faixa etária de 32 anos e com diagnóstico de TP. Instrumentos: Anamnese e entrevista semi-estruturada, Inventário Beck de Ansiedade e Escala para Pânico e Agorafobia. Resultados: os dados apontaram níveis de ansiedade significativos, corroborando o diagnóstico de transtorno do pânico nos sujeitos. Já os PNA - como «Estou com dor de cabeça. Será que é uma crise?» - e os padrões de distorções cognitivas identificados, incluindo suposição, catastrofização, generalização e subestimação/ superestimação, estão em acordo com a literatura apresentada e são condizentes com a prática clínica. ABSTARCT: Panic disorder (PD) is characterized by attacks of panic, which are accompanied by a series of thoughts, inappropriate to the context. Objective: to identify and systematize the cognitive distortion and the types of automatic negative thoughts (ANT) present in patients with (PD). Participants: 20 individuals in the age of 32 years and with a diagnosis of PD. Instruments: Anamnesis and semi-structured interview, Beck anxiety inventory and scale of panic and agoraphobia. Results: data showed significant levels of anxiety, corroborating the diagnosis of disorders of panic in the subjects. Already the ANT - as «I have a headache. Is it a crisis?» - and the standards identified cognitive distortions, including assumptions, pessimism, generalization and under-estimation / over-estimation, they are subject to the presented literature and they are suitable for clinical practice.