Russian Text Author’s Gender Identification in Forensic Examination: Probability-and-Statistics Method

The article discusses intermediate research results in the development and improvement of a computerized model of Russian texts authorization, which is based on complex application of probabilistic-and-statistical methods. The study aims to describe the new capabilities of the created system in the aspect of its application to diagnostic examinations in text authorization for detection of the gender of the alleged author of the text. The work presents the next stage of fine-tuning and testing of the improved version of the computer program "CTA" (computerized text authorization), which at this stage was adapted for the task of determining and comparing stable relative frequencies of correlation coefficients (the ratio of specified linguistic phenomena of different levels of the language system) in the texts, the authors of which are men and women. The research material is the continuously updated primary bases of literary texts of the 19 th and 21 st centuries (4 bases, respectively). The work shows that for the texts written by men and women, significant differences can be noted in such correlation coefficients as average word length, average sentence length, objectivity coefficient, quality coefficient, activity coefficient, dynamism coefficient, connectivity coefficient, etc. Verification of the results obtained experimentally has demonstrated that the accuracy of gender determining at this stage of the study is approximately 65%. This indicator can be significantly exceeded with an increase in the volume and quality specification of databases and/or when using new models for calculating the correlation coefficients (Spearman's model, etc.).

USING ACTIVE LEARNING METHODOLOGIES IN AN INTRODUCTORY STATISTICS COURSE

In general, engineering students show little interest in the activities inherent in statistics subjects. This claim may be partly explained by the competition with other subjects in the first years of undergraduate courses, or by student perceived low attractiveness of the classes. In this context, several studies indicated that methodologies where the student is the protagonist of the learning process lead to greater engagement during the activities and better scores in the assessments. This work describes the use of active learning methodologies in an introductory probability and statistics course for Engineering classes at a Brazilian public institution. Two classes were monitored during one term: in the first one (control class) traditional lectures were used, in the second one (experimental class) three different active methodologies were applied, namely: Jigsaw, Peer Instruction and Think-Pair-Share. On the one hand, the results indicated slightly better performances in the experimental class, as well as an increase in attendance. On the other hand, dropout rates were similar in both classes. This study is part of a renewal proposal of the mathematics subjects, based on the use of active learning methodologies and the review of curricular content to meet current pedagogical demands. Abstract: Portuguese Em geral, os alunos de Engenharia demonstram pouco interesse nas atividades inerentes à disciplina de Estatística. Tal constatação pode ser em parte explicada pela concorrência com outras disciplinas do ciclo básico, ou ainda, pela pouca atratividade das aulas. Nesse contexto, diversos estudos apontam que metodologias onde o aluno é o protagonista do processo de aprendizagem acarretam maior engajamento durante as atividades e melhores escores nas avaliações. Este trabalho descreve o uso de metodologias de aprendizagem ativa em um curso introdutório de Probabilidade e Estatística para turmas de Engenharia, numa instituição pública brasileira. Duas turmas foram monitoradas ao longo de um semestre: na primeira, fez-se uso de aulas expositivas dialogadas (turma controle) e, na segunda, aulas com três metodologias ativas diferentes, a saber: Jigsaw, Peer Instruction e Think-Pair-Share (turma experimental). Os resultados indicam um desempenho acadêmico levemente melhor da turma experimental, assim como na frequência dessa turma. Por outro lado, a taxa de evasão manteve-se semelhante em ambas as turmas. Este estudo é parte de uma proposta de renovação para as disciplinas de cunho matemático da instituição, baseada no uso de metodologias de aprendizagem ativa e na revisão de conteúdos curriculares para atender às demandas pedagógicas atuais.

An Algorithm for Fitting Sphere Target of Terrestrial LiDAR

The sphere target played a vital role in terrestrial LiDAR applications, and solving its geometrical center based on point cloud was a widely concerned problem. In this study, we proposed a newly finite random search algorithm for sphere target fitting. Based on the point cloud data and the geometric characteristics of the sphere target, the algorithm realized the target sphere fitting from the perspective of probability and statistics with the help of parameter estimation. Firstly, an initial constraint space was constructed, and the initial center and radius were determined by finite random search. Then, the optimal spherical center and radius were determined gradually through continuous iterative optimization. We tested the algorithm with the simulated and realistic point cloud. Experimental results showed that the proposed algorithm could be effectively applied to all kinds of point cloud fitting. When the coverage rate was bigger than 30%, the fitting accuracy could reach within 0.01 mm for all kinds of point clouds. When the coverage rate was less than 20%, the fitting accuracy can reach ±1 mm, although it was reduced to a certain extent.

Machine Learning Fundamentals

This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely “from scratch” based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts.

Assessment of the Reliability of Different Components of Fuel Measurement Systems Used in Angola

The present work aims to assess the reliability of the different fuel measurement systems used at SNLD filling stations. As objectives, it is intended to propose a methodology for selecting the types and models of pumps to be used and when to replace them. The assessment of the risks in the replacement of a pump and the impact on the environment will also be examined. Although the discussion on pumps is not new in Angola, there are no published records on this subject, particularly in the selection of types and models of systems to be used and when to replace, using the different scientific tools. For the analysis of these equipments and their reliability, weibull distribution, ANOVA analysis and computational tools of probability and statistics with excel were used. The analysis by these two methods made it possible to certify the results obtained. A benchmarking was carried out at the filling stations of SNLD, Pumangol and Sonangalp to compare the quality of some services. The results achieved were discussed during the internship held at Petrotec. As a result, the components that have the most impact on the maintenance system of the different pumps, the causes of the faults and their respective costs were identified. The most vulnerable components identified are errors in the display, heating in the engine and malfunction of electrovalves.