bluuebunny/crossref_metadata_2025 huggingface dataset:
EVALUASI KEBIJAKAN REVITALISASI PASAR TRADISIONAL DALAM MEWUJUDKAN PENGEMBANGAN EKONOMI LOKAL DI PASAR PETIR KABUPATEN SERANG
Authors: Laili Neli Nur , Riswanda Riswanda , Yulianti Rina
Published: October 2022

ABSTRAK
Revitalisasi Pasar Tradisional Petir merupakan program yang dilakukan oleh pemerintah Kabupaten Serang melalui Dinas Koperasi, Perindustrian dan Perdagangan bertujuan untuk meningkatkan pendapatan asli daerah dan peningkatan ekonomi masyarakat sekitar pasar. Namun dalam  penerapannnya,  di pasar tersebut masih ada beberapa masalah pada sisi fasilitas prasarana penunjang dan minimnya sosialisasi.  Penelitian ini dilakukan dari bulan Januari hingga Juni tahun 2021 dengan pendekatan kualitatif deskriptif dan data diperoleh melalui purposive sampling. Teknik pengumpulan data dilakukan dengan wawancara, observasi, dan studi dokumentasi. Hasil penelitian menunjukkan bahwa program revitalisasi Pasar Petir belum optimal terbukti dengan: belum terpeliharanya ketertiban pasar Petir, tidak semua fasilitas yang tersedia seperti kios/los diisi oleh pedagang, sumber daya aparatur dan tenaga pengelola pasar yang masih kurang, semberdaya prasarana penunjang tidak terpelihara dengan baik, minimnya sosialisasi dan penegakan mekanisme pemanfaatan fasilitas pasar kepada pedagang. Sebagai saran dari hasil penelitian adalah perlu adanya peningkatan evaluasi dan monitoring secara rutin oleh pejabat terkait dalam rangka mengetahui dan memantau aktivitas pasar baik dari segi fisik, manajemen, ekonomi dan sosial budaya, serta perlunya penambahan staf pengelola Pasar Petir Serang.
Kata Kunci : Ekonomi lokal, kebijakan revitalisasi, pasar tradisional
EVALUASI PENERAPAN STANDAR PELAYANAN MINIMAL (SPM) PENDIDIKAN MENENGAH DI PROVINSI BANTEN
Authors: Subki Subki , Sjafari Agus , Arenawati Arenawati
Published: October 2022

Penerapan Standar Pelayanan Minimal (SPM) pendidikan menengah menjadi fokus Pemerintah Provinsi Banten sebagai upaya implementasi penyelenggaraan urusan wajib pelayanan dasar. Penelitian ini membahas mengenai  evaluasi penerapan SPM Pendidikan Menengah yang dilakukan Dinas Pendidikan dan Kebudayaan Provinsi Banten dengan pendekatan teori evaluasi kebijakan publik CIPP (Context, Input, Process, Product). Penelitian ini diharapkan dapat memberikan saran masukan bagi Pemerintah Provinsi Banten dalam Penerapan SPM. Metode penelitian yang digunakan adalah metode deskriptif dengan pendekatan kualitatif. Berdasarkan hasil penelitian, penerapan SPM Pendidikan Menengah di Provinsi Banten belum optimal. Pada dimensi Context menunjukan Pemerintah Provinsi Banten telah mengintegrasikan muatan ke dalam dokumen RPJMD Provinsi Banten Tahun 2017-2022, diperlukan strategi untuk mendorong dan memberikan fasilitasi kepada satuan pendidikan dalam peningkatan Standar Nasional Pendidikan (SNP) dan upaya  strategis percepatan sertifikasi pendidik dan pemetaan dan penambahan guru agar rasio guru dan siswa pada jenjang SMA dan SMK di Provinsi Banten. Pada dimensi Input, aspek sumber daya manuasia dan alokasi anggaran sudah cukup memadai, namun perlu dibentuk tim SPM Pendidikan Menengah tingkat Dinas untuk peningkatan pemahaman dan percepatan pemenuhan SPM pendidikan menengah. Pada dimensi Process, capaian indikator kinerja persentase guru SMA dan SMK bersertifikat pada Program Peningkatan Mutu Pendidik dan Tenaga Kependidikan di bawah 50 persen dengan katagori sangat rendah, yang dihadapkan pada permasalahan terbatasnya kuota peserta program Pendidikan Profesi Guru (PPG) dari Pemerintah Pusat. Pada Product, cakupan pemenuhan SPM Pendidikan Menengah di Provinsi Banten belum semuanya terpenuhi.  
Kata kunci: Evaluasi,  Standar Pelayanan Minimal (SPM), pendidikan menengah, kebijakan publik.
Átélni, megismerni, tudni
Authors: Szabó Zsófia
Published: October 2022

A 2018/2019-es tanévben a 100 esztendős Bauhaus módszereinek nyomába eredtünk a kaposvári művészeti intézetben: kutattuk, tanulmányoztuk, majd teszteltük a Bauhaus pedagógiájának, művészeti szemléletének és stílusának jelenkori érvényességét, lehetőségeit. Az átélés – megismerés – tudás egységét a Bauhaus legendás tanára, Johannes Itten a játék, ünnep és munka mottójával kapcsolta össze. Ez a tanulmány az elmélettől a gyakorlatig vezető utat mutatja be: mi így dolgoztunk, játszottunk és ünnepeltük együtt a Bauhaust Kaposváron.
Effects of Feed Additives Garlic and Onion on Growth of Mrigal (Cirrhinus Mirgala) Fingerlings
Authors: ARIANA ALI  , ISRAR MAQBOOL  , MUHAMMAD ASHRAF  , TASLEEM KAUSAR  , FAISAL JAMEE  , MALJA IMAN YOUSAF  , SAIMA TALIB  , ALIA HUSSAIN
Published: October 2022

The purpose of this study was to see how dietary garlic and onion powder effected on Cirrhinus mrigala. Feed additives such as garlic and onion are used. Cirrhinus mrigala was fed garlic and onion supplementary meals containing 2.5 percent of their body weight for a total of 60 days. The initial body weight and length of Cirrhinus mrigala fingerlings were respectively 18.48±0.139g and 10.17±0.123cm. When garlic and onion were fed together, the effect of garlic and onion on Cirrhinus mrigala growth performance was examined. Final weight was 29.37±0.071 and final length was 13.2±0.022cm, indicating that feed consumption was enhanced based on growth performance. The current findings showed that dietary garlic or onion powder, given alone or in combination, might increase mrigal (Cirrhinus mrigala) survival, growth, and feed consumption. Based on the findings, it can be concluded that feeding a food supplement (onion and garlic) to fish, either alone or in combination, enhanced their growth performance.
Biodiversity and Distribution of Fish Fauna in Dera Ghazi Khan Canal
Authors: BUSHRA RASHEED  , MUHAMMAD IMRAN BIRMANI  , ROMANA ARSHAD
Published: October 2022

The DG Khan canal is a vast canal starting from Taunsa Barrage and flowing through different areas of the DG Khan District. In some places, its water is restricted and has many fish species. The present study was intended to examine the fish fauna of DG Khan district from the Taunsa dam at DG Canal to the boundary line of DG Khan District with Rajanpur District. During the study, 16 species including Gudusia chapra (Hamilton, 1822), Notopterus notopterus (Pallas, 1769), Labeo gonius (Hamilton, 1822), Labeo rohita (Hamilton, 1822), Cirrhinus mrigala (Bloch, 1795) , Catla catla (Hamilton, 1822), Puntius ticto (Hamilton, 1822), Puntius sophore (Hamilton, 1822), Securicula gora (Hamilton, 1822), Cyprinus carpio (Linnaeus, 1758), Mystus cavasius (Hamilton, 1822), Mystus bleekeri (Day, 1877), Wallago attu (Day, 1878), Channa marulia (Hamilton, 1822), Oreochromis niloticus (Linnaeus, 1758), Mastacembelus armatus (Lacepède, 1800), were recorded in the DG canal of DG khan district. Taunsa barrage was also explored in which fishes Chitala chitala (Hamilton, 1822), Catla catla (Hamilton, 1822), Labeo gonius (Hamilton, 1822), Labeo rohita (Hamilton, 1822), Cirrhinus mrigala (Bloch, 1795), Labeo calbasu, Labeo bogga (Hamilton, 1822), Labeo dyocheilus (McClelland, 1839), Cirrhinus reba (Hamilton, 1822), Labeo boggut (Sykes, 1839), Hypophthalmichthys molitrix (Valenciennes, 1844), Ctenopharyngodon Idella (Valenciennes, 1844), Cyprinus carpio (Linnaeus, 1758), Oreochromis mossambicus (Peters, 1852), Oreochromis aureus (Steindachner, 1864), Oreochromis niloticus (Linnaeus, 1758), Channa punctata (Bloch, 1793), Channa striata (Bloch, 1793), Channa marulius (Hamilton, 1822), Macrognathus pancalus (Hamilton, 1822), Mastacembelus armatus (Lacepède, 1800), Ompok bimaculatus (Bloch, 1794) , Wallago attu (Day, 1878), Sperata seenghala (Sykes, 1839), Eutropiicthys vacha (Hamilton, 1822), Bagarius bagarius (Hamilton, 1822), Rita rita (Hamilton, 1822), Goanolisa manminus and Rita macracanthus (Ng, 2004) were recorded.
Proactivité et réactivité: deux orientations pour concevoir des dispositifs visant le développement de la sécurité industrielle par la formation
Authors: Flandin Simon , Poizat Germain , Perinet Romuald
Published: October 2022

In a world exposed to uncertainty and upsets, the development of organizational resilience is often proposed to improve performance. Intended as a complement – but also sometimes as a counterpoint – to management approaches based on anticipation and preparedness, resilience-based approaches aim to improve the ability of professionals to react in an opportune manner to extraordinary and unexpected situations. Despite increasing interest for this change in paradigm, few concrete case studies have been documented. The work presented in this document explores the possibilities offered by new training modalities, for and using resilience, which aim to improve the ability of professionals to produce safety in work situations. The work is part of a research project called FOResilience, led by Simon Flandin and Germain Poizat at the University of Geneva, which was partially funded by the FonCSI. Three characteristics of the authors’ approach are worth emphasizing: - They adopt a broad definition of “training”, which includes professional development activities and organizational interventions, with a particular interest for methods that differ from classical classroom-based training, such as crisis exercises, discussion forums, coaching, and collective analysis of work situations. - They are more interested in activities and methods that develop professionals’ ability to interpret ambiguous situations and to act and cooperate in unexpected or critical situations, than in activities that promote a quasi-mechanical execution of a procedure or deployment of a pre-established plan. - They see safety as resulting as much from the daily work activities that develop professionals’ ability to act in appropriate ways in a constantly evolving context, as from the initial safe system design and careful implementation of operating procedures that cover all possible situations. Two families of training/intervention methods are analyzed: - Methods that develop proactivity in routine situations, the daily activities that create conditions which are favourable to safe operations. These include different forms of discussion between professionals that aim to improve the shared understanding of goal conflicts, of the decisions and compromises made, the difficulties encountered (such as procedures that are inappropriate in certain situations) and improvement opportunities. - Methods that encourage reactivity in extraordinary or critical situations and the ability to bounce back after a critical organizational upset. These include various simulation-based methods, such as crisis exercises, though designed to improve the ability of professionals to make sense of and react in appropriate ways to unexpected events, rather than the classical objective of exercises to check correct execution of a predefined plan.
FeatSet+: Visual Features Extracted from Public Image Datasets
Authors: T. Cazzolato Mirela , C. Scabora Lucas , F. Zabot Guilherme , A. Gutierrez Marco , Traina Jr. Caetano , J. M. Traina Agma
Published: October 2022

Real-world applications generate large amounts of images every day. With the generalized use of social media, users frequently share images acquired by smartphones. Also, hospitals, clinics, exhibits, factories, and other facilities generate images with potential use for many applications. Processing the generated images usually requires feature extraction, which can be time-consuming and laborious. In this paper, we present FeatSet+, a compilation of color, texture and shape visual features extracted from 17 open image datasets reported in the literature. FeatSet+ provides a collection of 11 distinct visual features, extracted by well-known Feature Extraction Methods (FEMs) such as LBP, Haralick, and Color Layout. We organized the available features in a standard collection, including the metadata and labels, when available. Eleven of the datasets also contain classes, which aid the evaluation of supervised methods such as classifiers and clustering tasks. FeatSet+ is available for download in a public repository as sql scripts and csv files. Additionally, FeatSet+ provides a description of the domain of each dataset, including the reference to the original work and link. We show the potential applicability of FeatSet+ in four computational tasks: multi-attribute analysis and retrieval, visual analysis using Multidimensional Scaling (MDS) and Principal Components Analysis (PCA), global feature classification, and dimensionality reduction. FeatSet+ can be employed to evaluate supervised and non-supervised learning tasks, also widely supporting Content-Based Image Retrieval (CBIR) applications and complex data indexing using Metric Access Methods (MAMs).
Using Musical and Statistical Analysis of the Predominant Melody of the Voice to Create datasets from a Database of Popular Brazilian Hit Songs
Authors: A. Bertoni André , P. Lemos Rodrigo
Published: October 2022

This work deals with the creation and optimization of a large set of features extracted from a database of 882 popular brazilian hit songs and non-hit songs, from 2014 to May 2019. From this database of songs, we created four datasets of musical features. The first comprises 3215 statistical features, while the second, third and fourth are completely new, as they were formed from the predominant melody of the Voice and previously there were no similar databases available for study. The second set of data represents the graph of the time-frequency spectrogram of the singer’s voice during the first 90 seconds of each song. The third dataset results from a statistical analysis carried out on the predominant melody of the voice. The fourth is the most peculiar of all, as it results from the musical semantic analysis of the predominant melody of the voice, which allowed the construction of a table with the most frequent melodic sequences of each song. Our datasets use only Brazilian songs and focus their data on a limited and contemporary period. The idea behind these datasets is to encourage the study of Machine Learning techniques that require musical information. The extracted features can help develop new studies in Music and Computer Science in the future.
BovDB: a data set of stock prices of all companies in B3 from 1995 to 2020
Authors: Corrêa Cardoso Fabian , Valverde Malska Juan Andrey , Ramiro Paulo Junior , Lucca Giancarlo , Nunes Borges Eduardo , Leite Dias de Mattos Viviane , Alceste Berri Rafael
Published: October 2022

Stock markets are responsible for the movement of vast amounts of financial resources worldwide. This market generates a high volume of transaction data, which after being analyzed are very useful for many applications. In this article, we present BovDB, a data set that was built considering a source of the Brazilian Stock Exchange (B3) with information related to the years between 1995 and 2020. We have approached the events’ impact on the stocks byapplying a cumulative factor to correct prices. The results were compared with public data from InfoMoney and BR Investing, showing that our methods, are valid and follow the market standards, based on the proposed factor. BovDBdata set can be used as a benchmark for different applications and it is available in open access for any researcher on GitHub.
Musical Success in the United States and Brazil: Novel Datasets and Temporal Analyses
Authors: P. Oliveira Gabriel , R. G. Barbosa Gabriel , C. Melo Bruna , E. Botelho Juliana , O. Silva Mariana , B. Seufitelli Danilo , M. Moro Mirella
Published: October 2022

Music is not only a worldwide essential cultural industry but also one of the most dynamic. The increasing volume of complex music-related data defines new challenges and opportunities for extracting knowledge, benefiting not only different music segments but also the Music Information Retrieval research field. In this article, we assess musical success in the United States and Brazil, two of the biggest music markets in the world. We first introduce MUHSIC and MUHSIC-BR, two novel datasets with enhanced success information that combine chart-related data with acoustic metadata to describe the temporal evolution of musical careers. Then, we use such enriched and curated data to cluster artists according to their success level by considering their high-impact periods (hot streaks). Our results reveal three groups with distinct success behavior over time. Furthermore, Brazil and the US present specific music success patterns regarding artists and genres, reflecting the importance of analyzing regional markets individually.
A Comprehensive Dataset of Brazilian Fact-Checking Stories
Authors: Marques Igor , Salles Isadora , M. M. Couto João , C. Pimenta Breno , Assis Samuel , C. S. Reis Julio , C. da Silva Ana Paula , M. de Almeida Jussara , Benevenuto Fabrício
Published: October 2022

In recent years, digital platforms have become a powerful means for large scale information diffusion world-wide, particularly in Brazil. Understanding key aspects driving the misinformation diffusion process is of paramountimportance to the design and implementation of new tools to automatically detect misinformation content. In this scenario, fact-checking performed by high credibility agencies provide rich labeled data, which is fundamental to build tools capable of detecting and mitigating the effects of misinformation. This paper opens a novel dataset, referred to as FactCenter, to the research community, containing fact-check instances collected from 6 different Brazilian fact-checking agencies. This dataset has 11 647 fact-check instances, covering several topics and domains. We present an initial analysis of the data collected, enriched by data from Facebook, which demonstrates the potential of our repository for future studies.
CandiDATA: an enhanced dataset for data analysis of elections in Brazil from 1945 to 2020
Authors: F. Vasconcelos Felipe , Tavares João V. S. , Oliveira Matheus G. S. , J. Coutinho Fabio , Clarindo João Paulo
Published: October 2022

The Brazilian Superior Electoral Court (TSE) keeps data on elections that have taken place in Brazil since 1933. These data constitute an important collection serving as a reference for works in several research areas. However, this collection is not fully exploited due to some problems, such as missing and non-standard data, making analysis and integration with external databases difficult. Previous works built limited datasets and tools because of these problems as they only include data since the 1998 election, disregarding the election years from 1945 and 1996. This work discusses the steps to create CandiDATA – a standardized and enhanced dataset from TSE data, including a toolkit of webscrapping and data visualization. CandiDATA is available in open format and covers the election period between 1945 and 2020.
A Framework to Compute Entity Relatedness in Large RDF Knowledge Bases
Authors: Guillot Jiménez Javier , P. Paes Leme Luiz André , Torres Izquierdo Yenier , Neves Angelo Batista , Casanova Marco A.
Published: October 2022

The entity relatedness problem refers to the question of exploring a knowledge base, represented as an RDF graph, to discover and understand how two entities are connected. This article addresses such problem by combining distributed RDF path search and ranking strategies in a framework called DCoEPinKB, which helps reduce the overall execution time in large RDF graphs and yet maintains adequate ranking accuracy. The framework allows the implementation of different strategies and enables their comparison. The article also reports experiments with data from DBpedia, which provide insights into the performance of different strategies.
Sketch+ for Visual and Correlation-Based Exploratory Data Analysis: A Case Study with COVID-19 Databases
Authors: Cazzolato Mirela T. , S. Rodrigues Lucas , X. Ribeiro Marcela , A. Gutierrez Marco , Traina Jr. Caetano , M. Traina Agma J.
Published: October 2022

The amount of data daily generated by different sources grows exponentially and brings new challenges to the information technology experts. The recorded data usually include heterogeneous attribute types, such as the traditional date, numerical, textual, and categorical information, as well as complex ones, such as images, videos, and multidimensional data. Simply posing similarity queries over such records can underestimate the semantics and potential usefulness of particular attributes. In this context, the Exploratory Data Analysis (EDA) technology is well-suited to understand data and perform knowledge extraction and visualization of existing patterns. In this paper, we propose Sketch+ , a technique and a corresponding supporting tool to compare electronic health records (provided by hospitals) by similarity, supporting correlation-based exploratory analysis over attributes of different types and allowing data preprocessing tasks for visualization and knowledge extraction. Sketch+ computes partial and overall data correlation considering distance spaces induced by the attributes. It employs both ANOVA and association rules with lift correlations to study relationships between variables, allowing extensive data analysis. Among the tools provided, a pixel-oriented one drives the analysts to observe visual correlations among dates, categorical and numerical attributes. As a running case study, we employed three open databases of COVID-19 cases, showing that specialists can benefit from the inference modules of Sketch+ to analyze electronic records. The study highlights how Sketch+ can be employed to spot strong correlations among tuples and attributes, with statistically significant results. The exploratory analysis has been shown to be an essential complement for similarity search tasks, identifying and evaluating patterns from heterogeneous attributes.
A Scalable Data Integration Architecture for Smart Cities: Implementation and Evaluation
Authors: B. Ribeiro Murilo , R. Braghetto Kelly
Published: October 2022

The collection, processing, and analysis of data generated by varied sources can help us better understand the functioning and demands of the cities. However, developing efficient solutions to explore urban data is challenging due to the large volume, heterogeneity, and lack of accessibility and integration of this kind of data. In this work, we identify the main requirements of a data integration system to support decision-making in cities, focusing on its challenges. We analyze some existing data integration solutions, to uncover their features and limitations. Based on these results, we propose a new microservice architecture to support the development of software platforms for integrating smart cities’ heterogeneous data and a guideline to assess their performance. We also present details of a proof-of-concept implementation of the proposed architecture and its performance evaluation. The results demonstrate that the platform can scale horizontally to handle the highly dynamic demands of a smart city while maintaining low response times.
ACERPI-Block: Applying Blocking Techniques to the ACERPI Approach
Authors: Schmitz Christian , Martins Jonathan , K. Mbaye Serigne , Manica Edimar , Galante Renata
Published: October 2022

Ordinances are documents issued by federal institutions that contain, among others, information regarding their staff. These documents are accessible through public repositories that usually do not allow any filter or advanced search on documents’ contents. This paper extends ACERPI (an approach to collect documents, extract information and resolve entities from institutional ordinances), which identifies the people mentioned in ordinances from institutions to help users find the documents of interest. ACERPI-Block focuses on the Entity Resolution step of the approach, developing blocking strategies that allow scalability to hundreds of thousands of records being resolved. Experiments show a reduction of 93.3% in the number of comparisons of similarity between records if compared to the solution without blocking, with no decrease in efficacy.
Investigation of the performance of driver mutation identification methods using biological networks and enriched biological networks
Authors: Souza Alfredo Guilherme da Silva , Simao Adenilso
Published: October 2022

Several computational methods allow identifying genes related to cancer (driver mutation) through patient mutation data and biological networks. Usually, networks are not built focusing on biological activities associated with cancer because they are designed for general use. In this study, we investigate the performance of methods for identifying driver mutations using biological networks and enriched biological networks, applying a gene prioritization method to classify genes associated with cancer understudy in the biological network. The results indicated that employing the enrichment method helped identify different driver genes in all cases.
Avaliação do Uso de IA para Auxiliar no Diagnóstico de Casos de COVID-19 para Diferentes Surtos
Authors: Ulrichsen Felipe C. , Sena Alexandre C. , Pôrto Luís C. M. S. , Figueiredo Karla
Published: October 2022

A experiência vivida com a COVID-19 indicou que, em situações de grande demanda ou em regiões remotas e/ou carentes, pode haver falta de testes RT-PCR, considerado padrão para diagnóstico de COVID-19. Nesse contexto, este trabalho investiga algoritmos baseados em Machine Learning (ML) para diagnóstico de COVID-19, a partir de sinais e sintomas. Para além do diagnóstico, este trabalho também incluiu estudos sobre alterações nos sinais e sintomas, considerando as ondas de surtos e a qualidade dos resultados obtidos com RT-PCR e Teste Rápido. Os resultados apontam que o modelo selecionado, baseado em Redes Neurais MLP, possui resultado bem mais preciso (70%, no caso de 1ª onda) do que o indicado pelo Ministério da Saúde para o Teste Rápido (em torno de 25%), além de apontar as mudanças nos sinais e sintomas ao longo da evolução da pandemia.
Provendo um modelo automático de detecção de quedas baseado em rede adversária generativa para assistência de idosos
Authors: Santos Allan Costa N. dos , Seixas Flávio Luiz , Fernandes Natalia Castro
Published: October 2022

As quedas são um grave problema de saúde pública e as pessoas com mais de 65 anos estão entre as mais vulneráveis a lesões graves decorrentes de uma queda. Este artigo propõe e avalia um modelo de arquitetura de rede neural, chamada de CNN Video Stream Combination (CVSC), para melhorar o monitoramento e a segurança de idosos. É proposto o uso de uma rede neural generativa para calcular a pontuação de anomalia. Propõe-se um modelo capaz de trabalhar simultaneamente com câmeras RGB e infravermelho, pois as quedas de idosos frequentemente ocorrem em ambientes com pouca luz. O CVSC utilizando câmera RGB apresentou 97,00% de sensibilidade e com câmera infravermelho obteve 94,00% de sensibilidade.
Explorando Redes Neurais de Grafos para Classificação de Arritmias
Authors: Oliveira Rafael F. , Freitas Vander L. S. , Moreira Gladston J. P. , Luz Eduardo J. S.
Published: October 2022

Arritmia cardíaca é uma condição de risco e seu diagnóstico precoce é de fundamental importância. Por isso, a automação do processo de identificação de arritmia é desejável. Neste contexto, um modelo de classificação automática de arritmias em sinais de eletrocardiograma (ECG) é proposto baseado em Graph Neural Network (GNN) e o batimento cardíaco representado por meio de um grafo via algoritmo Visibility Graph (VG). São avaliados três modelos de redes GNN: uma rede convolutional de grafos com duas camadas (GCN-2L), outra com três camadas (GCN-3L) e GraphSAGE (GraphSAGE-4L). Sob o paradigma interpatient, o modelo GraphSAGE-4L apresentou o melhor desempenho, obtendo F1-score médio de 0,86 para as classes N, S e V.
Otimização de Hiperparâmetros de Redes Neurais Profundas para Detecção de Cardiomegalia em radiografias do tórax
Authors: Fernandes Saulo Enock Rodrigues , Marques Ricardo Costa da Silva , Almeida João Dallyson Sousa de , Paiva Anselmo Cardoso de , Braz Júnior Geraldo
Published: October 2022

A radiografia do tórax é um dos exames mais comumente utilizados para o diagnóstico de doenças torácicas. Devido à complexidade das doenças torácicas, existe a demanda de médicos experientes e habilidosos na área para mitigar as chances de erros no diagnóstico de tais patologias. Diversas pesquisas utilizando Redes Neurais foram elaboradas para auxiliar especialistas na detecção de doenças da região do tórax como, por exemplo, a opacidade pulmonar e a pneumonia. Este trabalho apresenta uma metodologia que pretende fornecer auxílio aos profissionais da saúde no diagnóstico de doenças da região do tórax. É proposta uma abordagem baseada no balanceamento de quantidades de imagens e otimização de hiperparâmetros do modelo. Os testes foram focados na classificação da cardiomegalia e os resultados obtidos se provaram promissores alcançando 0,919 de AUC, 0,873 de acurácia, 0,842 de precisão, 0,876 de F1-Score, 0,913 de sensibilidade e 0,790 de especificidade, aproximando-se das melhores métricas presentes na literatura.
Um Modelo de Aprendizado Profundo Multimodal para Classificação de Estresse Utilizando Sinais Obtidos por Dispositivos Vestíveis de Pulso
Authors: Medeiros Vinícius P. , Cunha Fagner , Santos Eulanda M. dos , Souto Eduardo
Published: October 2022

A recente proliferação dos dispositivos vestíveis (e.g. smartphones e smartwatches) e sua capacidade de medir vários sinais fisiológicos criam uma oportunidade de monitoramento contínuo e discreto do estado de estresse de um indivíduo. Tendo isso em vista, este trabalho propõe um novo modelo para classificação de estresse baseado em uma rede de convolução usando dados coletados por dispositivos de pulso. Os resultados obtidos, utilizando a validação leave-one-subject-out (LOSO), alcançaram a taxa média de 95,67% de acurácia, sendo um valor superior à maioria dos trabalhos já existentes na literatura.
Integração de Dados Abertos em Saúde com o modelo OBDA: Um Estudo de Caso na Área de Cirurgia Bariátrica
Authors: Bispo Samuel L. B. , Fukace Vinícius K. , Mazur Ana Heloísa B. , Penteado Raqueline R. M. , Teixeira Heloise M. P.
Published: October 2022

Com a crescente disponibilização de dados abertos em saúde no portal do DATASUS, surgem várias oportunidades de estudos no sentido de gerar informações para subsidiar a tomada de decisão e elaboração de ações em saúde. Um desafio para sistemas computacionais é executar consultas em diferentes fontes de dados, sendo necessária a implementação de uma solução capaz de tratar as diferenças semânticas dos dados. Esta pesquisa descreve um estudo de caso de integração dados abertos em saúde por meio de ferramentas OBDA (Ontology Based Data Access), utilizando uma ontologia no domínio da cirurgia bariátrica como camada conceitual sobre os dados. A principal contribuição da pesquisa é apresentar e discutir o uso de ferramentas OBDA por meio de um experimento prático de integração de dados do DATASUS.
Avaliação de modelos para extração de dados não estruturados de um sistema EHR para atender a estrutura final de uma ontologia
Authors: Silva Diego Pinheiro da , Mello Blanda Helena de , Fröhlich William da Rosa , Rigo Sandro José , Schwertner Marco Antonio , Costa Cristiano André da
Published: October 2022

Há um aumento significativo no número de Electronic Health Records (EHRs) que acomodam dados não estruturados em linguagem natural. A análise manual destes dados é inviável devido ao grande volume existente, cuja tendência é continuar a aumentar. Há uma necessidade de abordagens que permitam a estruturação destas informações para que possam auxiliar os profissionais de saúde na análise dos dados, indicação de tratamento, diagnóstico de doenças, entre outros. Esta pesquisa tem como objetivo desenvolver um modelo para processamento de dados não estruturados de EHRs observando o objetivo de representá-los em estruturas de ontologias. Experimentos preliminares foram realizados e indicaram resultados promissores para o modelo.
Aumentando a Eficiência do Cache Proativo com Algoritmos de Mochilas para PoPs e Hashes para Servidores
Authors: Mendes Paulo Renato C. , Rodrigues Lenise M. V. , Soares João L. da S. Guio , Serra Arthur , Coelho Yago , Turatti Nedimar , Rocha Antonio A. de A. , Menasché Daniel Sadoc
Published: October 2022

Caches são elementos fundamentais para reduzir a carga nos servidores e o atraso dos usuários nas redes de entrega de conteúdo (CDNs). Este trabalho apresenta e avalia estratégias de cache proativo para aumentar a eficiência do cache em uma CDN distribuída geograficamente, com dois algoritmos para selecionar mídias a serem armazenadas em cache. O primeiro se aproveita do clássico problema das mochilas (knapsack), e acopla todos os servidores de cada PoP ao determinar como preencher cada mochila. O segundo preestabelece os servidores candidatos a servir cada mídia, por meio do uso de hashes e, então, aplica o problema da mochila em cada servidor alvo. As duas soluções foram testadas na infraestrutura da Globo, na qual foi possível aumentar o número de visualizações dos vídeos servidos em cache em 80,1%.
HPyC-FPGA - Integração de Aceleradores em FPGA de Alto Desempenho com Python para Jupyter Notebooks
Authors: Silva Lucas B. da , Penha Jeronimo Costa , Ribeiro Dener V. , Silva Alysson , Nacif José Augusto M. , Ferreira Ricardo
Published: October 2022

O desenvolvimento de aceleradores em FPGAs (Field Programmable Gates Arrays) ainda é um desafio. Recentemente, o ambiente PYNQ da Xilinx possibilitou a integração de código Python com aceleradores em FPGA. A maioria dos exemplos está voltada para placas de prototipação utilizadas no desenvolvimento de aplicações embarcadas. Este artigo apresenta o algoritmo K-means de aprendizado de máquina não supervisionado como estudo de caso. A principal contribuição deste trabalho é o encapsulamento de 3 aceleradores acoplados com PYNQ usando o ambiente Jupyter Notebook. A avaliação foi realizada em uma máquina de alto desempenho utilizando um FPGA Alveo U55C com memória HBM (High Bandwidth Memory). Os resultados são promissores, além de mostrar as facilidades de uso do FPGA de forma encapsulada, o ganho de desempenho foi de uma a duas ordens de grandezas em comparação a um sistema com dois processadores Xeon(R) Silver 4210R com 10 núcleos cada, executando a etapa de classificação do algoritmo K-means.
Vitamin D and Zinc are Interlinked But Affected by Different Growth Factors in Iranian Children and Adolescents: Vitamin D and Zinc in Iranian Children and Adolescents
Authors: Habib Ashkan , Molayemat Mohadeseh , Habib Asadollah , Hejrati Zinatosadat , Kheirandish Zahra
Published: October 2022

Background: Zinc and vitamin D are essential factors required for growth. Recently, studies have shown a possible link between serum zinc and vitamin D levels. Objectives: This study was designed to evaluate this link and its possible affecting growth factors in children and adolescents in Iran. Methods: This cross-sectional study was performed on the data obtained from children aged 2 to 18 years old referring to a growth assessment clinic for routine growth follow-ups in the city of Shiraz from April to August 2019. A total of 454 children who were checked for 25-hydroxyvitamin D and zinc simultaneously were included. Results: Vitamin D was negatively correlated with body mass index (BMI) z-scores, while zinc was positively correlated with vitamin D and height z-scores. Subjects with vitamin D levels ≤ 8.6 ng/mL were 2.081 times as likely to have a zinc deficiency. Vitamin D insufficiency was significantly higher in overweight and obese children. Mean vitamin D and zinc levels were significantly lower, and vitamin D insufficiency was significantly higher in boys than girls. While mean zinc levels were significantly lower in short children, the prevalence of zinc deficiency was not statistically different between short and normal height statures. Conclusions: Very low vitamin D levels are likely to be accompanied by zinc deficiency, possibly caused by malnutrition and the modulatory effect of serum vitamin D on zinc absorption. Unlike zinc deficiency, vitamin D insufficiency is much more prevalent in Iranian children than in children from other countries. Vitamin D and zinc are associated with BMI and height z-scores, respectively.
Not Just a Trick: A survey study exploring how ‘exposing’ exhibition visitors to science of magic concepts impacts their appreciation of magic Magic and exposure
Authors: Medeiros Gabriel , Tompkins Mathew , Bagienski Steve , Kuhn Gustav
Published: October 2022

Deception, secrecy, and mystery are inexorably intertwined with the idea of performance magic. Magicians traditionally do not reveal their secret methods to non-magicians. The recent rise in scientific research on magic raises important issues about the impact that the dissemination of magic knowledge has on people’s appreciation of magic.  This study used a survey to assess how people’s appreciation of magic was impacted by a magic exhibition designed to highlight and reveal the psychological mechanisms that underpin magic. Visitors to the exhibition were asked to rate the impact of the exhibition on a range of measures assessing people’s interest and appreciation for magic. The results revealed a significantly positive change in all dimensions. The qualitative analysis reports on things that people like and dislike about magic as well as the impact that magic has on people’s appreciation for magic.  Despite magicians’ traditional fear that revelations related to magic secretes might rob magic audiences of their sense of wonder, our results indicate that an engaging exhibition about the science that underpins some magical experiences can actually enhance peoples’ stated appreciation for magic. 
Design and construct unit to control fluid entering solar collectors during efficiency tests
Authors: Mezaal Jawad , Alameri Thamer
Published: October 2022

This paper describes the development of an apparatus to control the fluids that enter a solar collector in experimental tests with respect to the Australian and New Zealand Standard AS/NZS 2535.1.2007. This standard explains the testing procedure, indicating that the inlet fluid should have specified temperature and flow rate uncertainties. The hardware components were constructed in the lab. A new sophisticated data acquisition system with an NI CompactDAQ was added to control the unit, and a new software application in LabVIEW was developed. The unit was operated in an open-loop to understand its behaviour as a multiple-inputs and multiple-outputs system (MIMO). A rule of thumb tuning method was used to design the proportional-integral PI controller for the heating system. Moreover, a custom decoupler with a PI controller was developed to reduce the interactions in the MIMO. The measured steady-state responses were analysed to determine the flow rate and temperature compared with the limited boundaries. The final results show that the system could supply water to the solar collector within the accuracy requirements. Achieving the fluid's absolute temperature and flow rate within the required constraints of the published standard has proven that the developed unit can be adapted to perform solar collector testing. However, additional steps are suggested for further work to enable the unit to provide field testing.
Security Segmentation in a Small Manufacturing Environment
Authors: Powell Michael , Hoyt John , Sherule Aslam , Wilcox Lynette
Published: October 2022

Manufacturers are increasingly targeted in cyber-attacks. Small manufacturers are particularly vulnerable due to limitations in staff and resources to operate facilities and manage cybersecurity. Security segmentation is a cost-effective and efficient security design approach for protecting cyber assets by grouping them based on both their communication and security requirements. This paper outlines a six-step approach that manufacturers can follow to implement security segmentation and mitigate cyber vulnerabilities in their manufacturing environments. The security architecture resulting from the security segmentation design activities is a foundational preparation step for additional security strategies like Zero Trust.
COMPARATIVE ASSESSMENT OF MACROECONOMIC INDICATORS GROWTH PERFORMANCE BETWEEN INDIA AND NIGERIA
Authors: SADIQ Sanusi
Published: October 2022

India and Nigeria were colonized by the British empire, got their independence within a given time range, and are among the largest growing economies among developing nations; they were ranked 1st and 3rd most populous among the common wealth countries respectively and both the countries houses significant population of malnourished, poor and food insecure people. The paper comparatively assessed the macroeconomic growth performance between the two countries using time series data that spanned from 1990-2020. Compound growth rate model was fitted to the data to confirm the trend of acceleration, deceleration or stagnation during the period. The results of the study revealed that mean values of GDP and GNI in US dollars at constant prices for India were higher than that of Nigeria by almost 7 times, while Nigeria`s per capita GDP was higher than that of India under the reference period. With respect to the GDP and per capita GDP growth rates, India recorded lower growth but more stable than Nigeria. Further, both the countries recorded highest GDP contributions from Service sector (46 per cent in India and 35 per cent in Nigeria). But the growth rate shows stability in Indian Service sector in contrast to the highest instability in agricultural sector. In Nigeria, on the other hand, agricultural sector got the highest growth contribution to GDP growth-though stagnant and instable, while service sector’s growth contribution to GDP growth was the lowest among other variables. It is recommended that increase budget share to agriculture through proper funding of research, credit support and extension service would help to repositioned agriculture back to its higher (of about 50 per cent) GDP contribution and compete vigorously with other economic sectors in income generation, employment opportunities and poverty reduction in both India and Nigeria.
The Effect of Slope, Rootstock and Cluster Thinning on Berry Properties
Authors: KORKUTAL İlknur , BAHAR Elman , KOSKOSOĞLU Batuhan
Published: October 2022

Vineyard was established 13 years ago by Kalpak Tarım Ürünleri Ltd. Şti. in Şarköy/Tekirdağ, for two years (2019/2020 and 2020/2021). The vineyard altitude is 309-327 m and grapevine stem height is 70 cm where Cabernet Franc/Fercal and Cabernet Franc/140Ru graft combinations were used, and the spacing is 2.1 m and 1.0 m. The vines planted in the North-South direction were cultivated in the form of Cordon Royat trellising system. Purpose of the research is to determine the cluster thinning applications effects on the vines, which was grafted onto two different rootstocks, and also their locations on the slope, affects the grape berry. As a result, low values were obtained from Fercal rootstock in terms of berry fresh and dry weight, berry volume, berry density and berry skin area on the other hand, berry width, berry length, % dry weight and berry skin area / berry volume from 140Ru rootstock. When the location on the slope is examined; the Top position reduced the criteria other than berry density and berry skin area / berry volume. Since the average yield of two years in the vineyard is between 700-800 kg da-1, it was determined that it would be more appropriate no cluster thinning (0% S).
Comparison of outcomes between children ventilated in a non‐paediatric intensive care and a paediatric intensive care unit: A retrospective analysis
Authors: Jingxi X L , Tinarwo P , Masekela R , Archary M
Published: October 2022

Background. Lack of paediatric intensive care infrastructure, human resources and expertise in low- and middle-income countries (LMICs) often results in critically ill children being managed in non-intensive-care unit (ICU) settings.Objectives. To compare the mortality between critically ill patients who required ventilation for more than 24 hours in a non-paediatric ICU (PICU) setting v. those admitted directly to a PICU.
Methods. Participants were enrolled if they were between one month and 13 years of age and were ventilated in a non-PICU ward in a regional hospital and a PICU ward in a tertiary/quaternary hospital during the study period of January 2015 - December 2017 in KwaZulu- Natal, South Africa. Descriptive statistics, chi-square test, Wilcoxon test and binary logistic regression were used for data analysis. Ethics approval was obtained (approval number BE568/18 BREC) from the Biostatistics Research Council of the University of KwaZulu-Natal.
Results. Of the 904 admissions, 25.1% (n=227) were admitted to non-PICU and 74.9% (n=677) to a PICU. A significantly higher proportion of non-PICU patients were malnourished than PICU patients (26.4% v. 13.3%, p<0.001). Patients ventilated in a PICU were 76% less likely to die (p<0.001), while patients who required inotropes were 15.08 (9.68 - 24.34) times more likely to die (p<0.001). There was a statistically significant association between admission setting and survival outcome, with higher mortality in the non-PICU setting than in the PICU setting (46.3% v. 19.5%, p<0.001).
Conclusion. Critically ill children ventilated in a non-PICU setting in KwaZulu-Natal are more likely to be malnourished, require inotropes and have higher mortality. Although increasing access to PICU bed availability is a long-term goal, the high mortality in the non-PICU setting highlights the need to optimise the availability of resources in these non-PICU wards, optimise and train the staff, and improve primary healthcare services.