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In this paper, we report the experience of a mathematics teacher educator, who is a mathematician, while teaching the Euclidean Division Algorithm Theorem in a Number Theory course for prospective mathematics teachers. Considering that the knowledge of a Mathematics teacher is specialized, from the perspective of the Mathematics Teachers' Specialised Knowledge model, we intended to identify which knowledge is mobilized when the teacher educator addresses this algebraic result. Some activities were conducted by the professor in an attempt to understand how the prospective teachers performed the division of integers before, during, and after knowing the theorem; our analysis focuses on these different moments. Regarding the prospective teachers' knowledge, it was possible to observe, primarily, knowledge related to procedures involving the algorithm. However, throughout the conducted activities, they were able to establish different connections concerning the Euclidean Division Algorithm Theorem. About the teacher educator, we emphasize that his mathematical and pedagogical knowledge, combined with the goal of effectively prepare future Mathematics teachers, has the potential to promote specialized knowledge in the prospective teachers regarding the subject matter. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has become increasingly present in human life, pointing to an integrated future with the real and the virtual walking side by side. Inserted as an AI field, Machine Leaning operates with a set of tools, called algorithms, that allow performing activities in almost every area of knowledge, whether in Biology, Math and Science or Humanities. An application of the algorithms is in the area of credit card fraud detection, which causes financial institutions and society to lose billions of dollars every year. In this sense, this work aimed to identify how Machine Learning has contributed to this financial and social problem. For this proposal, it was used the Systematic Bibliographic Review, from which it was obtained primary diagnoses on the areas of Machine Learning, Fraud and Credit Card Fraud, in order to arrive at a thorough portrait of the subject. As a source of research, it was used in the Web of Science portal, with searches centered on the period from 2008 to 2018. The results show that, both in the subject of Machine Learning and fraud, most of the works refer to areas of Medicine & Biomedicine. In the integration between “Machine Learning” and credit card fraud, five papers were found that, when fully evaluated, proved to have good fraud detection power. There is, however, a way to go that allows comparing the methods employed from a common database. [ABSTRACT FROM AUTHOR]

This paper presents an exploratory study of image banks, specifically Getty Images and Shutterstock, analyzing whether their tagging processes reveal algorithmic forms of reproducing colonial mentalities about black women. From Patricia Hill Collins' concept of "controlling images," Jezebel, Mammy, and Sapphire images were examined, understanding that these stereotypes of black female subjectivity underscore narratives of subordination, exploitation, and animalization in the service of coloniality. While the results show specificities, primarily due to the COVID-19 pandemic, we found that algorithmic coloniality becomes apparent in these banks, which frequently tag the images of black women under colonial representation standards of labor, sexuality, and aggressiveness. [ABSTRACT FROM AUTHOR]

In this theoretical articulation based on bibliographic research, the culture of intolerance, driven by the political context of hyperneoliberalism, is linked to the imaginary present on algorithmic platforms, where a fundamental mode of governance is practiced today. While not ignoring past manifestations of intolerance on the Internet, this paper intends to demonstrate how these platforms are environments even more favorable for such manifestations, given the peculiarities of their technology and their business model. To this end, certain aspects of their operation, classified as arena of attention, uneven omnimediation, calibrated exposure and flexible veridiction, are related to dispositions that Lacan associates with the imaginary and aggressiveness - respectively, narcissism, narcissistic identification with leaders, segregation and paranoia. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the relationship between data practice and algorithmic actions on digital platforms. For this purpose, we do a descriptive analysis of Instagram documents that are addressed to its users, identifying what suggests action and practical consequence of digital materialities in terms of production, sharing and collection. Through them we identify the centrality of experience in this kind of informational construct developed in relation to datafication processes - which we call algorithmic experience. From a pragmatist and neomaterialist perspective, we suggest following this experience to understand the practical differences produced in the use of digital platforms and identifying relevant interactions in situated practices. [ABSTRACT FROM AUTHOR]

Algorithms have become the focus of discussions on technology whether involving the role of social networks in our everyday life or the promise of a generalized coding of various occupations. This paper intends to unravel the importance of algorithms for capitalism from the advent of the Third Industrial Revolution in three functions: (1) to expand the everyday life colonization by the market and by the State, a task formerly exercised only by the cultural industry, (2) increase the limits of the subsumption of labor by capital, and (3) improving existing forms of precarious work. Finally, we present possible solutions for working class organization of the working in the contemporary scenario of precariousness and withdrawal of labor rights. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for extracting road seeds (segments) from digital aerial images, these images often have variations, which involves complex analysis and characterizes a challenging problem in this area. This work consists in implementing techniques for detecting possible road seed. This paper presents a methodology in eliminating invalid points of the roads using the application of Modified Canny Algorithm. In the segmentation of valid points for seed construction was applied the Douglas-Peucker algorithm. In the road extraction, problems were found in relation to valid and invalid seed and in images that have rural roads. Experiments were performed with aerial images of roads to prove the proposed methodology. [ABSTRACT FROM AUTHOR]

A problem in mass balance resolution in mineral processing plants is the circulation load in closed-circuits. A family of methods which can be used to solve the circulating load is the iterative methods. This paper shows a low complexity algorithm to calculate the circulation load in closed circuits which allows the construction of mass, metallurgic and water reliable balances. The proposed algorithm was validated against results from Caspeo BILCO software and real industrial data for two different closed-circuits types. The obtained results are satisfactory with respect to the calculated result, processing speed, solution convergence and number of iterations needed to evaluate the circulation load. [ABSTRACT FROM AUTHOR]

This paper presents a method for building a three dimensional model of the lower leg bone (tibia) from a human, from X-ray images. The methodology adopted to obtain the 3D object is deforming the model until it corresponds to X-ray images (front and left and right sides) of the tibia. We used the following algorithms for X-ray images segmentation and three-dimensional modeling: Canny, Border Following, Free Form Deformation (FFD) and deformation algorithm developed in this work. The viewing application defined and implemented shows the three-dimensional image of the bone of the tibia resulting from deformation of the 3D object. The experimental results demonstrate the possibility of representing the real human bone obtained from X-ray images into a 3D model, however, a great difficulty for this activity was the number of images available for the project. [ABSTRACT FROM AUTHOR]

In underground mining, daily a fleet of LHDs must be allocated to a haulage network of drifts for extracting ore according to a plan-driven strategy. This plan is hierarchically decided by a higher management level and it contains the number of ore bucketfuls to be extracted from each drawpoint within a drift for each working shift. In this paper, an integer programming (IP) model for minimizing the makespan of drift workload is formulated and a polynomial time optimal algorithm for its resolution is proposed. Next, a set of decision rules obtained from the algorithm above is integrated into the decision-making process (DMP). This DMP is simple to execute for LHD operators, determines the optimal makespan, and whether or not it can be carried out in the working shift. Finally, a comparative analysis between the DMP proposed and the DMP used in El Teniente copper underground Chilean mine is studied. The results show that the cumulative operators experience has converged to solutions near to optimal makespan. [ABSTRACT FROM AUTHOR]

Costreduction is a permanent target, pursued in all steel production phases. Production processes that use high volumes of raw materials and big amounts of inputs present excellent opportunities in terms of cost reduction. In this context, the aim of the present paper I to analyse the steps to automatize ferroalloys and deoxidizers calculations for the processes of steel tapping - Ladle Metallurgy -, and secondary refining - Argon Bubbling Stations -, in order to minimize specific cost of these materials and standardize operational procedures, focusing on operation flexibility and options of ferroalloys available in the market. It is developed a mathematical algorithm, updated in real time by the process events, which assess the best materials options, that fulfill all quality requirements of final product, and minimize production costs. As final result, the implementation of this project has allowed the use of low cost ferroalloys, without any risks of operation deviations, resulting in a reduction of CSN's production costs around R$ 4 million per year. [ABSTRACT FROM AUTHOR]

Introduction. The significance of information retrieval has been increased as a result of the increasing frequency with which digital files are created and used. One of the many strategies for processing texts for the indexing of their contents in information retrieval systems is called stemming, which consists in the reduction of similar words to the same unvarying representation. Stemming relies on the morphological structure of the language with which it is intended to work. Aim. This paper aims at defining the concept of stemming, presenting the algorithms available for Portuguese and commenting on several topics related to the use of this type of algorithms. Method. Literature review on stemming for Portuguese known to the authors. Results. To this day, there are only three algorithms published which deal with stemming in Portuguese: Porter's, Orengo's and Gonzalez's. Conclusion. Today,improvement in terms of stemming for the Portuguese language cannot be achieved successfully, since there is little research being done in this area. [ABSTRACT FROM AUTHOR]