bluuebunny/crossref_metadata_2025 huggingface dataset:
Qualidade da informação de mortalidade por causas externas em Fortaleza-CE (2017-2020): o uso do ananconda
Authors: De Moura Lydia Meneses , Macena Raimunda Hermelinda Maia , Mota Rosa Maria Salani , Florêncio Caroline Mary Gurgel Dias , Cronemberger Andréa da Nóbrega Cirino Nogueira , Da Silva Denise Maia Alves , De Araújo Ticiana Maria Lima Azevedo , Beserra Mabell Kallyne Melo
Published: June 2023

O registro dos óbitos por causas externas de uma população é a fonte essencial de base de informação de saúde e segurança. Entretanto, a qualidade das estatísticas sobre causas de morte tem sido questionada, visto que cerca de 400 mil óbitos/ano são registrados no SIM com causas classificadas como códigos garbage (CG). Portanto, este estudo visa analisar a qualidade dos dados das mortes de causa externa em Fortaleza-Ce no período de 2017-2020 utilizando o ANACONDA. Estudo ecológico, descritivo, de abordagem quantitativa com dados de informação de mortalidade por causas externas disponíveis no banco de dados do SIM (Sistema de Informação de Mortalidade) da Secretaria Municipal de Saúde (SMS). O projeto foi aprovado pelo CEP/UFC via parecer 5.772.791. Os achados evidenciaram que a qualidade da informação de mortalidade por causas externas em Fortaleza-CE, encontra-se deficiente, visto que ocorre um aumento do percentual de causas pouco úteis de 2017 a 2020, com nível de gravidade alto como mais prevalente, no decorrer dos anos (de 68% para 89,5%). Identificamos em praticamente todos os ranks, o código Y34.9 do CID-10 (refere-se a Fatos ou eventos não especificados e intenção não determinada), reforçando a necessidade de aprimorar a qualidade da informação reduzindo os CG.
Observação da prática docente: um olhar didático metodológico
Authors: Vermelho Dilmara dos Santos , Oliveira Ellen Lopes , Viana Luciene da Silva , Filho Gilson Silva
Published: June 2023

Diante dos avanços tecnológicos e mudanças culturais, ocorridas na contemporaneidade, as salas de aulas estão cada vez mais cheias de alunos do século XXI. Assim, de forma a acompanhar a demanda social para garantir uma educação significativa, surgiu a importância de promover uma pesquisa de campo de observação da prática docente, com o intuito de analisar, refletir e relacionar de forma crítica as práticas pedagógicas elaboradas pelos professores de hoje. O trabalho procedeu-se a partir de uma pesquisa exploratória com relato de experiência e observação não-participativa, bem como revisão de literatura. Relativo aos resultados, apesar da utilização de algumas estratégias favoráveis, percebeu-se a carência de planejamento e falta de mediação para a construção do conhecimento no que tange o conteúdo estudado. Por fim, foi possível refletir que realmente existe uma carência por parte de alguns professores para fazer o processo de ensino-aprendizagem de fato acontece, sendo preciso que educadores tenham em mente a necessidade de uma formação continuada.
Visita de estudios y actividades educativas en una escuela preescolar: estudio de caso
Authors: Da Cruz Fernando Manuel Rocha
Published: June 2023

Actualmente, la educación se basa en la pareja pedagógica profesor(a)/alumno(a) y se centra en el aula. Al mismo tiempo, la familia vio reducida su intervención en la Escuela limitándose a los contactos con el Director de la Clase o el Director de la Escuela. Las visitas de estudio también son esporádicas o inexistentes en muchas escuelas, que además de la pandemia por SARS-CoV-2 ha llegado a extremos. En este artículo buscamos cuestionar esta realidad a partir de un estudio de caso en una escuela preescolar. La investigación es cualitativa y se basó en el registro de actividades de una clase en Facebook, comentarios e entrevistas realizadas con padres/madres y profesora. Concluimos que la familia puede tener un papel activo en la docencia, participando en visitas de estudio junto a sus hijos e hijas, donde se desarrolla la práctica pedagógica sin inculcar en los alumnos la dicotomía entre familia y escuela, sino su asociación, continuidad o incluso complementariedad entre ellas.
Deep Learning Unveils Hidden Insights: Advancing Brain Tumor Diagnosis
Authors: Kaushik Priyanka
Published: June 2023

Timely detection and treatment are crucial in managing brain tumors, a severe medical condition. MRI is a commonly used diagnostic tool to detect brain tumors. However, because of the complex structure of the brain and the wide range of tumors sizes and forms, MRI scan interpretation can be time-consuming and error-prone. The automated detection and segmentation of brain tumors has shown encouraging results with to recent developments in DL techniques. We suggest a CNN-RNNs and GANs based DL technique for brain tumor identification in this paper. Transfer learning and data augmentation techniques are used in the suggested method to train the CNN on a sizable dataset of MRI images labelled with tumor areas. The suggested strategy, according to experimental findings, is more accurate than the most advanced techniques now available for finding brain tumors. The suggested strategy has the potential to help radiologists identify brain tumors quickly and reliably, improving patient outcomes.
English Language Teacher Education Programs at Turkish Universities: A Statistical Overview
Authors: ASMALI Mehmet
Published: June 2023

Considering the significant role of English Language Teacher Education (ELTE) programs on future English teachers’ teaching skills and eventually on the English proficiency of future generations, the present study investigated some statistics concerning the academics and students of these programs. All the statistics were gathered from YÖK Atlas, a website initiated by Council of Higher Education (CoHE) in Turkey. The data were analyzed to find out the differences between public and private universities’ ELTE programs, and to find out correlations among various elements of the ELTE programs regardless of the type of universities. The findings revealed the superiority of the ELTE programs at public universities over the ones at private universities on various aspects. However, students’ decreasing number of ELTE program preferences in recent years at both public and private universities were among the major findings of the present study. Moreover, some positive correlations among the variables were reported. The findings were discussed in the light of the related literature.
Biochemical and histopathological changes in livers of rats poisoned with aluminum phosphide and treated with carrot extract
Authors: Al-Safar Ali Husein Ali , Jawad Rafat A. Mohammed , Khayoon Hussein Ali , Alsaadawi Mohenned A. , Zenad Khalil Hassan , Saeed Zeayd Fadhil , Alkhaled Mansoor J.
Published: June 2023

The experimental studies of Aluminum Phosphide (AP) poisoning in rats revealed several clinical and pathological signs such as hemorrhage, sinusoidal dilatation, bile stasis, centrilobular necrosis, Kupffer cell hyperplasia, infiltration by mononuclear cells, and fatty infiltration in the liver tissues. This paper aimed to show the impact of carrots on the toxic effect of AP on the livers of adult rats (female). To investigate some biochemical and histopathological changes effects of AP in rats, sixty white female rats were equally divided into four groups, the first group (G1) was administered orally with 3mg/kg/ body weight of AP, the second group (G2) was orally treated with AP and 10% carrot extract at the same time. The third group (G3) administrated 10% carrot extract only. The fourth (G4) group was the negative control and was treated with distilled water only. The experiments continued for a month at the animal house of the Veterinary Medicine College of Baghdad University. The results revealed that high levels of liver enzymes and bilirubin were induced in G1 with decreasing total protein levels. The pathological examination revealed the presence of marked proliferation of Kupffer cells in G1 livers. However, the G2 group showed slight infiltration of lymphocytes in sinusoids. The pathological changes in the livers of G3 group showed slight cloudy swelling in hepatocytes compared with the normal texture of hepatocytes in G4. The data of this experiment showed that treatment with carrot extract significantly decreases the elevation in the level of liver function enzymes in animal poisoned with AP. In addition, treatment with carrot extract reduces the severe damage in the hepatic tissue that occurred in rats treated with AP only. In general, it could be concluded that treatment with carrot extract provides a remedial effect against the hepatotoxicity that is resulted from exposure to AP.
Quantitative analysis of qualitative data: using text mining techniques for the music therapy clinic
Authors: Pedrosa Frederico Gonçalves , Reis Jeniffer Soares dos
Published: June 2023

Text mining is a data mining process that aims to extract useful information from unstructured or semi-structured data sets, such as emails, HTML files, or transcripts. This study proposes the use of text mining techniques to evaluate verbal communication in music therapy sessions. To this end, sessions conducted by the project Effects of Music Therapy Interventions on the Quality of Life of Black Women were transcribed. The techniques of word cloud, topic modeling, and sentiment analysis were employed in this research. Topic modeling identified four clusters of words named "Black Women", "Reflections", "Music Therapy" and "Pain". In turn, sentiment analysis identified a broad distribution of sentiments, with a predominance of neutral or positive sentences, strongly skewed to the right and concentrated around the mean, with few extremely negative or positive sentences. These data suggest that the sessions addressed sentimental issues related to the Black women participants and promoted well-being for this population. According to the participants' reports in response to a questionnaire at the end of the music therapy sessions, the results of the text mining are in line with the participants' perceptions. In this sense, text mining is a promising technique for understanding verbal communication in music therapy sessions, and can be used in future research to investigate, with more evidence, these and other possibilities for music therapy clinical practice.
Sport initiation in VivaVôlei Project: a systematic review
Authors: Benedita Silva Joice , Helena da Silva Tamires , Macedo Furtado Chaves Julia , Pereira dos Santos Silva Valesca , Luiz dos Santos Coelho Dione , de Castro Teixeira Marcelo
Published: June 2023

VivaVôlei is a social project created by the Brazilian Volleyball Confederation (CBV), which covers more than twelve regions of Brazil, and its goal is the insertion of volleyball for children and adolescents in need, through the mini-volleyball methodology. The objective of this study was to verify, through a systematic review produced by means of articles published between the years 2003 and 2022, the quantity of publications about the project and whether they allude to its benefits for the target audience. Six scientific papers were found, five of them in Google Scholar in the form of articles published in journals, and one in the form of a book chapter found on the Capes platform. Satisfactory results were observed in the analyses, such as: socialization and happiness with the practice of sports, improvement in interpersonal relationships, progress in motor coordination, flexibility, and muscle strengthening. However, new studies about the program still need to be published
The influence of the brazilian public school math olympiad on the basic education development index: an analysis in the municipality of Coruripe-Alagoas
Authors: José da Silva Jailson , Izidorio Rodrigues Vagno , De Oliveira Nascimento César , Saturnino de Oliveira Júnior Jalon
Published: June 2023

This article aims to analyze the influence of the Brazilian Mathematics Olympiad for Public and Private Schools (OBMEP) on the Basic Education Index (IDEB) in a municipality of Alagoas in the period from 2007 to 2017. It was developed from the collection and analysis of data through interviews and semi-structured questionnaires prepared by the proponents themselves, and directed to the coordinators of the aforementioned municipality, in order to analyze the influence of the Brazilian Mathematics Olympiad for Public Schools on the IDEB results. Based on the data obtained, it was clear that since the insertion of programs aimed at improving student performance in the OBMEP, the results of the IDEB of the municipality were also improved, reaching 6.3 points in 2017, which means an increase of 1.9 points compared to 2015.
On project pedagogy: experience leading the individual to theory
Authors: Rodrigues De Souza Sérgio , Dau Sandro Dau , Da Silva Santos Vinícius , Rosalino Pereira Cleidimar , Pacheco Ferreira Ketlyn
Published: June 2023

This article-essay is about the pedagogy of projects: the experience leading the individual to theory. The proposal is to clarify that learning happens through empirical contact with reality and with the phenomena that happen in nature. Its scientific relevance lies in the fact that it presents a technical discussion about a study methodology that allows a direct, reciprocal, and simultaneous relationship between practice and theory. Its social relevance lies in making available to society a mechanism that exponentially increases students' learning gains, allowing them a pragmatic view of the syllabus with which they have academic contact. The methodology used for this research was the bibliographic one, added to the pedagogical and didactic practice of the authors in teaching. We tried to present a deep and wide discussion, in which the supremacy of experience over theory is advocated, in which the former leads the latter, expressing and communicating the acquired knowledge. Project Pedagogy arose from the need to develop a pedagogical work methodology that aimed at valuing the participation of the student and the educator in the learning- teaching process, considering that learning takes precedence over teaching. By proposing Project Pedagogy as a teaching methodology, this means ending the monopoly of the traditional teacher who decides and defines himself the content and the tasks to be developed and which truths should be considered and/or denied, valuing, within strict academic-scientific principles, what the students already know and respecting what they want to learn at that moment, aware that the
problem-situation raised is the leitmotiv of the experience to be put in evidence, culminating in learning. When we talk about project-based learning we are necessarily referring to the formulation of questions by the author of the project, by the individual who will build knowledge from a problem situation.
Angles and areas in plane geometry with emphasis on history and everyday applications
Authors: Augusto Valente da Cunha Luis , Francisco da Silva Costa José , Antônio Farias Nonato José , Carvalho Lobato Marinaldo , Eduardo Pastana Silva José , das Graças Carvalho Almeida Raimundo
Published: June 2023

This work has as general objective to understand the historical aspect of plane geometry, calculation of plane areas and applications. For a better approach to the theme, it develops a study on the primitive ideas between straight and plane points, opening a gap to introduce essential elements for a better understanding of the content. Methodology is developed in a bibliographical study based on some authors such as Gelson Iessi, Osvaldo Dulce, Geovane, etc. which contributes to a better solid construction of the exposed content. In terms of specific objectives, it brings as main goals to show that the study of plane geometry is widely used in practice, mainly in house constructions where its relevance is observed in the inherent geometric figures of regular polygons, perimeters and areas that, routinely, are observed and that requires knowledge of plane geometry to consolidate a solid approach to content; Check that plane geometry has the advantage of helping professionals with problems encountered in everyday life, since they need this knowledge to carry out certain measurements that are essential for correct calculations of areas of polygons, such as areas of plane figures.; Analyze the relevance of mathematical formalism for a better understanding of the theory and subsequent practical application. The research concludes considering that plane geometry is commonly found in practice and it is essential to know how to apply mathematical knowledge in everyday situations. Therefore, it is justifiable that the essence of this content is of fundamental practical and theoretical importance.
The Importance of Islamic Regal Leadership in Zakat Delivery to Its Recipients in Perlis
Authors:   Department of Shariah and Law, Academy of Islamic Studies, University of Malaya, Kuala Lumpur, Malaysia, Akashah Khalil Lailatul Shahreen , Buang Ahmad Hidayat ,   Professor, Department of Shariah and Law, Academy of Islamic Studies, University of Malaya, Kuala Lumpur, Malaysia.
Published: June 2023

The purpose of this article is to justify that Islamic regal leadership in Perlis plays a very important role in the delivery of zakat to its recipients with a goal to alleviate poverty. This study argues that Islamic regal leadership benefits the recipients in Perlis by adopting effective Islamic governance based on the principle of al-siyāsah al-sharʿiyyah and adab through the reflections of wisdom and justice in Islam derived from the the Holy Quran. Accordingly, this article discusses how His Royal Highness the Crown Prince of Perlis, as the ulū al-amr (Islamic leader), adopts Islamic values and virtues while expressing benevolence (i.e., kindness) by personally hand delivering the zakat to its recipients. The primary data collected were from interviews with selected respondents representing interested parties such as policy makers and zakat contributors. About 30 zakat recipients were chosen to take part in a faceto-face interview. The data collected were analysed through qualitative methods using Atlas.ti 8 and triangulated with the literature to show that virtuous traits, beneficence (i.e., being charitable) and righteousness in Islamic regal leadership in Perlis have benefitted the recipients by transitioning them out of poverty through three positive interdependent factors, namely the important existence of Islamic regal leadership traits in His Royal Highness, the fulfilment of the zakat recipients’ needs and the opportunities for the zakat recipients to set up businesses. The findings of this study are useful to those concerned about Islamic regal leadership and to those responsible for zakat delivery to its recipients. This is a pioneer study, presenting new observations and knowledge pertaining to Perlis.
Secondary School Students Self-Regulated Learning Skill as Predictor of Mathematics Achievement in Imo State Nigeria: Focus on Gender
Authors: Duru Darlington C. , Mba David O. , Ike Iheanacho C.
Published: June 2023

Mathematics as an abstract subject, requires the application of cognitive strategies such as self-regulated learning skill to predict students’ achievement. This paper was designed to investigate the secondary school students self-regulated learning skill as a predictor of mathematics achievement with respect to gender. A correlational survey research design was employed. The sample size consisted of 882 senior secondary students class two (SSII) randomly selected from 14 out of 124 public senior secondary schools in Owerri Education Zone of Imo State. Two different instruments were used for data collection. They are Questionnaire on Self-Regulated Learning (QSRL) and Mathematics Achievement Proforma (MAP). Three experts validated the instrument. The Cronbach Alpha calculated yielded a reliability coefficient of 0.89 for QSRL. The data collected were analyzed using Pearson Product-moment correlation coefficient and regression analysis with the aid of Statistical Package for Social Sciences (SPSS) version 20. The findings revealed that self-regulated learning skills significantly predict male students’ achievement in mathematics. The findings also showed that self-regulated learning skill does not significantly predict female students’ achievement in mathematics. It was recommended among others that secondary school students should regulate their learning to increase their mathematics achievement.
How Racial Diversity and Gender Diversity in Job Positions Affect the Economy?
Authors: Li Zheng
Published: June 2023

Gender and racial discrimination at work have gradually gained more attention from the public in the recent years. With social movements such as #MeToo and #BlackLivesMatter, people start to reach the consensus that there should be more equality in society; more perspectives from different genders and different races are beneficial to society. This paper focuses on employment in the general workforce and studies how race and gender diversity in different job positions affect the economy. This paper explores to empirically explain why race and gender diversity in the workforce can have an impact on the economy. Using data from the U.S. Equal Employment Opportunity Commission and from the Federal Reserve for the years of 1996 - 2018, this paper finds that race and gender diversity at work are positively associated with the economy. Also, this dataset supports the conjecture that race and gender diversity increases total employment, which further increases the economy. This dataset also supports the possibility that race and gender diversity may increase the capacity of different perspectives, which further increases the economy. Moreover, race and gender diversity both increased during these years: from 11.783% to 23.339% and from 31.683% to 38.735% in the executive and managerial positions. This study has significant contributions to current research and practice.
Assessment of Agricultural Sustainability: Case Study of Baltic States
Authors: Streimikiene Dalia , Mikalauskiene Asta
Published: June 2023

The agri-food sector is the world’s largest economic sector having the biggest impact on environment. According to the Food and Agriculture Organization of the United Nations (FAO), sustainable agriculture must meet the needs of present and future generations while ensuring profitability, environmental health and social and economic equity. Therefore, agricultural systems need transition to become more sustainable. The use of renewables in agriculture allows to reduce energy costs and GHG emissions and implement cyclic economy principles. Sustainability assessment of agriculture can be done by applying various sets of indicators. The sustainability assessment of agriculture can be performed on country and micro level. The paper presents assessment of agricultural sustainability of Baltic States based on indicators framework and applies MCDA tool for ranking of Baltic States in terms of agriculture sustainability.
Premenstrual Syndrome and Mindfulness: The Mediating Effect of Perceived Social Support and Health-Related Quality of Life Among Deaf/Hard-of-Hearing Women
Authors: Alkahtani Mohammed Ali , Alqahtani Hanadi Hussain , Zaien Sahar Ziedan , Melhem Tameem , Alanazi Abdullah Naif
Published: June 2023

The purpose of this study is to explore the relationship between premenstrual syndrome (PMS) and mindfulness as well as the mediating role of perceived social support (PSS) and health-related quality of life (HRQoL) among deaf/hard-of-hearing women. This is a cross-sectional study. An overall sample of 202 participants was selected. Path analysis was used. As indicated by the results obtained, PMS correlated significantly with mindfulness, PSS, and HRQoL. Moreover, mindfulness correlated significantly and positively with PSS and HRQoL. Besides, there is a significant negative relationship between PSS and HRQoL. PMS has direct effects on PSS and HRQoL. In addition, both PSS and HRQoL have immediate impacts on mindfulness. To conclude, this study examined and confirmed the relationship between PMS and mindfulness as mediated by PSS and HRQoL among deaf/hard-of-hearing women.
Civic Life in the Digital Space of Pre-Service Teachers
Authors: Abril Mary Ann C.
Published: June 2023

This research investigates the profile and perceptions of respondents towards widely accessible social media platforms to identify key considerations in transforming online engagement into actual civic action. Quantitative in design, the survey of the descriptive method of research is used adopting the developed questions for the study of the United Nations Development Programme on young activists in 2021 to assess the digital engagement of 118 pre-service teachers randomly selected through the multistage sampling method. Utilizing descriptive statistics, social media platforms providing greater opportunities for self-expression such as Facebook and Tiktok are found frequently used for creating and sharing content related to education, and health. Respondents concurred on widespread disinformation online and the complementary nature of civic engagement. Despite the manifested lack of trust and reservations due to the risk of data surveillance and breach, the respondents consider social media platforms as enabling venues for civic engagement. Corresponding policies and programs that institute gender-inclusive, safe, and participatory venues in both digital and traditional forms are necessary means for supporting the youth as key players in nation-building.
SteamBR: a dataset for game reviews and evaluation of a state-of-the-art method for helpfulness prediction
Authors: Jorge Germano A. Z. , Pardo Thiago A. S.
Published: June 2023

The digital revolution has led to exponential growth in user-generated content, including ratings and reviews, across numerous online platforms. One such platform is Steam, a multifaceted digital distribution network primarily for video games, that also functions as an active social network. Like many e-commerce, travel, and restaurant platforms, Steam users rely heavily on reviews to inform their purchasing decisions. However, the vast amount of data and varying quality of reviews may hinder the utility of such reviews. Furthermore, there is a significant challenge in assessing the helpfulness of recent or less-voted reviews. This study proposes a method for automating review helpfulness evaluation, focusing particularly on Brazilian Portuguese game reviews. The research involved the collection of a large dataset, including 2,789,893 reviews from over 12,000 games, creating a novel dataset for game reviews. Using feature extraction techniques, we were able to capture the metadata, semantic elements, and distributional characteristics present in the reviews. Subsequently, Machine Learning algorithms were employed to perform classification and regression tasks, with the objective of discerning helpful from unhelpful reviews. The achieved results demonstrated that the method was highly effective in predicting review helpfulness.
Analyzing Character Networks in Portuguese-language Literary Works
Authors: Silva Mariana O. , Oliveira Gabriel P. , Moro Mirella M.
Published: June 2023

Literary works are complex narratives with multifaceted character relationships. Studying these relationships can reveal important insights into the story’s structure and each character’s contribution to the plot development. This research investigates character networks in Portuguese-language literature using two main analytical approaches: structural network analysis and character importance metrics. Our analyses emphasize the significance of character networks in understanding the narrative structure of literary works and reveal the intricate interplay between characters in Portuguese-language literature. These findings deepen our comprehension of literary works’ fundamental structure and the characters’ pivotal role in shaping the story.
Some results on irregular decomposition of graphs
Authors: Lintzmayer Carla N. , Mota Guilherme O. , Rocha Lucas S. da , Sambinelli Maycon
Published: June 2023

A graph is locally irregular if any pair of adjacent vertices have distinct degrees. A locally irregular decomposition of a graph G is a decomposition of G into subgraphs that are locally irregular. We prove that any graph G can be decomposed into at most 2∆(G) − 1 locally irregular graphs, improving on the previous upper bound of 3∆(G)−2. We also show some results on subcubic and non-decomposable graphs.
PTAS para Problema do Empacotamento de Soma Mínima com Quadrados
Authors: Saraiva Rachel V. , Schouery Rafael C. S.
Published: June 2023

O trabalho trata do problema do empacotamento de soma mínima com itens quadrados, em que uma lista de itens quadrados deve ser empacotada em recipientes 1 × 1, e o custo de empacotar cada item é igual ao índice do recipiente em que é empacotado. O problema tem aplicações na minimização do tempo médio de operações logísticas como corte e entrega de produtos. Nesse trabalho apresentamos um esquema de aproximação (PTAS) para o problema.
Bounds on Identifying Codes in the Cartesian Product of a Star and a Path Graph
Authors: Felix Juliana P. , Cappelle Márcia R.
Published: June 2023

In a graph, an identifying code (or ID code, for short) is a dominating set with the property that the closed neighborhood of each vertex in the graph has a distinct intersection with the set. Thus every vertex can be uniquely identified by this intersection. The ID code number of a graph G is the minimum cardinality of an ID code of G and is denoted by γID(G). We present lower and upper bounds for γID in the Cartesian product of star and path graphs.
MIP-Heuristics for the Capacitated Lot-Sizing with Hybrid Flow Shop Integration
Authors: Silva Diego Mello da , Mateus Geraldo Robson
Published: June 2023

Este artigo propõe uma abordagem em duas fases para resolver o problema integrado de lot-sizing capacitado (CLSP) com flow shop híbrido (HFS). Constrói-se uma solução inicial explorando três heurísticas: relax-and-fix, LP-and-fix e gulosa. Em seguida, aprimora-se a solução inicial usando a heurística fix-and-optimize, que decompõe o MIP original em subproblemas menores, um por período. Experimentos numéricos mostram que combinar uma heurística gulosa com fix-and-optimize pode superar as alternativas, obtendo gaps menores para a maioria dos casos, mesmo para instâncias de grande porte.
Estratégias Vencedoras e Complexidade de Jogos de Convexidade em Grafos
Authors: Araújo Samuel N. , Folz Raquel , Freitas Rosiane de , Brito João Marcos , Sampaio Rudini
Published: June 2023

Segundo Duchet (1987), o primeiro artigo de convexidade em grafos gerais é o artigo de 1981 “Convexity in graphs”. Um dos autores, Frank Harary, introduziu em 1984 os primeiros jogos de convexidade em grafos, na convexidade geodésica, investigados numa sequência de 5 artigos que terminou em 2003. Neste artigo, estendemos esses jogos para outras convexidades e obtemos estratégias vencedoras para geometrias convexas gerais, bem como os primeiros resultados de complexidade PSPACE em jogos de convexidade.
What is the Profile of American Inmate Misconduct Perpetrators? A Machine Learning Analysis
Authors: de Oliveira F. M. , Balbino M. de S. , Zárate L. E. , Nobre C. N.
Published: June 2023

Correctional institutions often develop rehabilitation programs to reduce the likelihood of inmates committing internal offenses and criminal recidivism after release. Therefore, it is necessary to identify the profile of each offender, both for the appropriate indication of a rehabilitation program and the level of internal security to which he must be submitted. In this context, this work aims to discover, from Machine Learning methods and the SHAP approach, which are the most significant characteristics in the prediction of misconduct by prisoners. For this, a database produced in 2004 through the Survey of Inmates in State and Federal Correctional Facilities in the United States of America, which provides nationally representative data on prisoners in state and federal facilities, was used. The predictive model based on Random Forest had the best performance; therefore, SHAP was applied to it to interpret the results. In addition, the attributes related to the type of crime committed, age at first arrest, drug use, mental or emotional health problems, having children, and being abused before arrest are more relevant in predicting internal misconduct. Thus, it is expected to contribute to the prior classification of an inmate, on time, use of programs and practices that aim to improve the lives of offenders, their reintegration into society, and, consequently, the reduction of criminal recidivism.
A Textual Representation Based on Bag-of-Concepts and Thesaurus for Legal Information Retrieval
Authors: Costa Wagner M. , Pedrosa Glauco V.
Published: June 2023

The retrieval of similar textual documents is a challenging task for the legal area due to its peculiar language with unique characteristics. This paper presents a new approach, called BoC-Th, proposed to represent legal documents based on the Bag-of-Concept (BoC) approach, which generates concept through clustering word vectors generated from a basic neural network model, and compute the frequencies of these concept clusters to represent document vectors. The novel contribution of the BoC-Th is to generate weighted histograms of concepts defined from the distance of the word to its respective similar term within a thesaurus. The idea is to emphasize those words that have more significance for the context, thus generating more discriminative vectors. Experimental evaluations were performed by comparing the proposed approach with the traditional BoW and BoC approaches, both popular techniques for document representation. The proposed method obtained the best result among the evaluated techniques for retrieving judgments and jurisprudence documents. The BoC-Th increased the mAP (mean Average Precision) in 51% compared to the traditional BoC approach, while being up to 3.4 times faster than the traditional BoW representation.
Value Estimation of Properties Administered by the Brazilian Army Using Machine Learning and Spatial Components
Authors: Alves de Sousa Neto José Nilo , Ladeira Marcelo
Published: June 2023

The valuation of an institution’s patrimony represents a necessary condition for an efficient management of its assets. The execution and analysis of real estate appraisal reports are essential to the achievement of some strategic objectives of the Brazilian Army, but they are also quite costly in terms of time, labor and financial resources. Sometimes, great effort is required for the aforementioned steps to take place and the market value finally obtained is inconsistent with what was initially imagined by the authorities, causing the technical study carried out to not be effectively used in negotiations by the organization. This work proposes the development of predictive models capable of building estimates of real estate values, so that the formal requests of the managers that imply the stages of execution and analysis of appraisal reports can occur with this information as an initial input. Counting on linear and nonlinear approaches and on machine learning techniques, the models have a reasonable level of assertiveness and national geographic coverage when generate estimated market values of Union real estate assets. Intrinsic and extrinsic variables to the properties were considered, including tests of aggregation of spatial components on some of them. As the interpretability of the proposed solution is an important requirement in both linear and nonlinear approaches, the Shapley value was adopted as a tool to support the guarantee of explainability and a PLS-SEM conceptual model was built to select attributes in a reasoned manner. These two considerations associated with modeling of real estate prices at a national level represent an innovation of this work in relation to the scientific literature analyzed.
Genetic Programming-based AutoML for EEG Signal Classification - A Comparative Study
Authors: Miranda I. M. , Aranha C. , de Carvalho A. P. L. , Garcia L. P. F.
Published: June 2023

End-to-end Machine Learning (ML) applications using complex data often need to investigate several alternatives for the data modeling pipeline before a good solution is found. This process, which is time-consuming and subjective, can benefit from an automated solution design by using Automated Machine Learning (AutoML). End-toend AutoML allows automated data preparation, modeling, and evaluation of ML pipelines, increasing the chances of arriving at a good solution. AutoML can implement this optimization with different strategies. Among them, Genetic Programming (GP) stands out for its ability to create pipelines of arbitrary format, allowing high interpretability and the customization of information from the data context. This paper proposes and compares two approaches of end-to-end AutoML optimized with GP for a time series classification problem, the classification of Electroencephalogram (EEG) signals. We selected this dataset because of the signals’ high complexity, spatial and temporal co-variance, and nonstationarity. For the AutoML experiments, four different domain-based data characterization measures are evaluated. The analysis of the data characterization measures shows that using only spectral or time-domain features does not lead to pipelines with good predictive performance. Our experimental results also reveal how AutoML can generate more accurate and interpretable solutions than the literature’s complex and ad hoc models. The proposed approach makes it easier to analyze dimensional reduction through fitness convergence, tree depth, and extracted features.
Automatic identification of similar judicial precedents
Authors: Stemler Igor , Ladeira Marcelo , Faleiros Thiago de Paulo
Published: June 2023

Brazilian Code of Civil Procedure has been reformulated in 2015 and created new institutes of judicial precedents to allow the Courts of Appeal to decide about similar cases based on one main case, which is considered the paradigm for similar cases that remain suspended. This mechanism aims to avoid legal uncertainty in the lower courts, but, uncertainty can be taken to the Courts of Appeal, since different courts can judge similar legal matter in the opposite way. The identification of similar judicial cases is hard because Courts of Appeal work independently and the number of cases is high. We propose the use of computational intelligence techniques to automatically identify similar judicial precedents. Our hypothesis is that algorithms based on semantic approaches, such as Latent Semantic Indexing and Latent Dirichlet Allocation, perform better than those that use only syntactic approach, as (Okapi) BM25 ranking function. The best-performing model is extended with named entities to verify if its performance increases. The performance of the models is evaluated using similarity metrics and with the assistance of a specialist. We test this approach with the database of judicial precedent of the National Council of Justice. Our approach correctly grouped more than 90% of judicial precedents and found similar precedents with divergent decisions or precedents that should be suspended due to the existence of appeals into superior courts of same subject matter. Models based on syntactic approach presented the best results, as it required lower computational cost and fewer parameter tuning compared to the others.
On the use of Query by Committee for Human-in-the-Loop Named Entity Recognition
Authors: Corvino Gabriel , Oliveira Vitor Vasconcelos , Mendes da Silva Angelo C. , Marcacini Ricardo Marcondes
Published: June 2023

Named Entity Recognition is a relevant task for extracting information from textual data. Traditional methods for training NER models assume that humans annotate entities manually, identifying entities in predefined categories. This strategy presents a great human effort, mainly in more specific application domains. To address these challenges, we consider Human in the Loop (HITL), which can be understood as a set of strategies to incorporate human knowledge and experience into machine learning, while accelerating model training. In this paper, we investigate a classic method called Query by Committee (QBC), which helps to select informative instances for data labeling. Traditionally, QBC selects instances with a high level of disagreement between different models of a committee. We present heuristics for QBC relaxation to also consider some level of agreement. We showed that taking advantage of some committee agreement for pre-labeling of instances is promising to speed up human feedback and increase the training set. Experimental results showed that our method is able to preserve the performance of models compared to traditional QBC, while reducing human labeling effort.
Meta-Learning Approach for Noise Filter Algorithm Recommendation
Authors: B. Pio P. , Garcia L. P. F. , Rivolli A.
Published: June 2023

Preprocessing techniques can increase the quality or even enable Machine Learning algorithms. However, it is not simple to identify the preprocessing algorithms we should apply. This work proposes a methodology to recommend a noise filtering algorithm based on Meta-Learning, predicting which algorithm should be chosen based on a set of features calculated from a dataset. From synthetics datasets, we created the meta-data from an extracted set of meta-features and the f1-score performance metric calculated from the DT, KNN, and RF classifiers. To perform the suggestion, we used a meta-ranker that returns the rank of the best algorithms. We selected three noise filtering algorithms, HARF, GE, and ORBoost. To predict the f1-score, we used the PCT, RF, and KNN algorithms as meta-rankers. Our results indicate that the proposed solution acquired over 60% and 80% accuracy when considering a top-1 and top-2 approach. It also shows that the meta-rankers, when compared with a random choice and single algorithms as a baseline, provided an overall performance gain for the Machine Learning algorithm.
Differentiable Planning with Indefinite Horizon
Authors: Dias Daniel B. , N. de Barros Leliane , V. Delgado Karina , Mauá Denis D.
Published: June 2023

With the recent advances in automated planning based on deep-learning techniques, Deep Reactive Policies (DRPs) have been shown as a powerful framework to solve Markov Decision Processes (MDPs) with a certain degree of complexity, like MDPs with continuous action-state spaces and exogenous events. Some differentiable planning algorithms can learn these policies through policy-gradient techniques considering a finite horizon MDP. However, for certain domains, we do not know the ideal size of the horizon needed to find an optimal solution, even when we have a planning goal description, that can either be a simple reachability goal or a complex goal involving path optimization. This work aims to solve a continuous MDP through differentiable planning, considering the problem horizon as a hyperparameter that can be adjusted for a DRP training process. This preliminary investigation show that it is possible to find better policies by choosing a horizon that encompasses the planning goal.
Condução de experimentos para o treinamento de modelos de Rede Neurais Artificiais em tarefas de inferência de expressões faciais em um ambiente Testbed
Authors: Melo Ítalo J. da S. , C. Filho Edson M. da , Medeiros Alana M. , Pires Yomara P. , Costa Saulo W. da S. , Seruffo Marcos C. da R.
Published: June 2023

Os avanços da área de Inteligência Artificial (IA) nos últimos tempos, têm permitido o desenvolvimento de tecnologias e pesquisas presentes em nosso cotidiano, a exemplo a área de computação afetiva no reconhecimento de expressões faciais. No entanto, a realização de experimentos nesta área, requer alocação de recursos e um ambiente de testes controlável para treinamento dos modelos neurais capazes de realizar a inferência de emoções. Este artigo relata o uso de Testbeds para o treinamento de um modelo de Redes Neurais Artificiais (RNA) para tarefas de inferência de emoções através do reconhecimento de expressões faciais. Para tal, foi utilizada a ferramenta Teachable Machine para composição do modelo de rede neural. O ambiente de testes utilizado foi Testbeds da Rede Nacional de Ensino e Pesquisa (RNP). Os resultados obtidos indicam que o uso Teachable Machine em um TestBeds possibilita a criação de modelos de reconhecimento facial precisos e eficientes.
A Study on the Optimization of 3D Printing Additive Manufacturing by Direct Energy Deposition Method Using High Speed Steel Material
Authors: Kwon Yongjae , Shin SeongSeon , Joo SangEun , Lee JongHoon , Hwang JunHo , Kim HyunDeok
Published: June 2023

In this study, an additive manufacturing (AM) optimization process experiment was conducted using high-hardness metal powders (AISI M4) that can be used for mold repairs. The process variables applied in the experiment were the laser power, laser head moving speed, and powder feed rate, and the manufacture cross section was analyzed through one-pass manufacturing. The AM efficiency was evaluated for each process with respect to the layer height, dilution ratio, and global energy density. In the case of the layer height, the AM efficiency was good under the condition of the laser output of 500 W. In the case of the dilution ratio, the AM efficiency was good under the conditions of a powder feed rate of 6 g/min and laser head moving speed of 500 mm/min. Finally, the GED values of the process variables applied in this experiment were calculated, and the AM efficiency was excellent at values between 60 and 108 J/mm2.
e-Pharmacophore modeling and in silico study of CD147 receptor against SARS-CoV-2 drugs
Authors: Pandit Nisha Kumari , Mann Simranjeet Singh , Mohanty Anee , Meena Sumer Singh
Published: June 2023

Coronavirus has left severe health impacts on the human population, globally. Still a significant number of cases are reported daily as no specific medications are available for its effective treatment. The presence of the CD147 receptor (human basigin) on the host cell facilitates the severe acute respiratory disease coronavirus 2 (SARS-CoV-2) infection. Therefore, the drugs that efficiently alter the formation of CD147 and spike protein complex could be the right drug candidate to inhibit the replication of SARS-CoV-2. Hence, an e-Pharmacophore model was developed based on the receptor-ligand cavity of CD147 protein which was further mapped against pre-existing drugs of coronavirus disease treatment. A total of seven drugs were found to be suited as pharmacophores out of 11 drugs screened which was further docked with CD147 protein using CDOCKER of Biovia discovery studio. The active site sphere of the prepared protein was 101.44, 87.84, and 97.17 along with the radius being 15.33 and the root-mean-square deviation value obtained was 0.73 Å. The protein minimization energy was calculated to be –30,328.81547 kcal/mol. The docking results showed ritonavir as the best fit as it demonstrated a higher CDOCKER energy (–57.30) with correspond to CDOCKER interaction energy (–53.38). However, authors further suggest in vitro studies to understand the potential activity of the ritonavir.