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Frontiers in Education (FIE) Conference

作者： Pablo Schoeffel Raul Sidnei Wazlawick Vinicius Faria Culmant Ramos Adilson Vahldick Marcelo de Souza Graduate Program in Computer Science Federal University of Santa Catarina Florianópolis Brazil Department of Informatics and Statistics Federal University of Santa Catarina Florianópolis Brazil Department of Information and Communication Technologies Federal University of Santa Catarina Araranguá Brazil Departament of Software Engineering University of Santa Catarina State Ibirama Brazil

ISBN: (纸本)9781538611753;9781538611746

This Research to Practice Paper presents the results of the evaluation of pre-university factors that impact the initial motivation of undergraduate students in computing. Although there are studies in the literature that have investigated some previous factors, this paper replicates a previous work that aims to consolidate several pre-university factors and, as the main differential, uses the AMS (Academic Motivation Scale), a scale already consolidated in the literature to measure students' initial motivation, and evaluate the relation between motivation and candidate factors. We applied a questionnaire to 159 students from different computing programs in ten universities, which evaluates 20 factors divided into 4 groups: personal and demographic data, taste and knowledge of the program and area, computing experience, and school performance. To evaluate the correlation between factors and motivation, we used Spearman's coefficient, t-student test, and ANOVA to evaluate the correlation between factors and motivation. As main results, we found significant variation in the initial motivation according to following factors: taste for programming and technology, knowledge about the undergraduate program content, correct perception about computing professionals, knowledge and experience in computer programming, and general school performance.

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Validation of MRI-VLFF for the non-invasive measurement of steatosis in children

GastroHep

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GastroHep 2020年第4期2卷

作者： Miriam B. Vos Eduardo Castillo-Leon Jack Knight-Scott Rebecca Cleeton Alvin Jay Freeman Jennifer K. Frediani Albert Hernandez Stephen F. Simoneaux Jun Kong Alton Brad Farris Michael J House Tim St. Pierre Division of Gastroenterology Hepatology and Nutrition Department of Pediatrics Emory University Atlanta GA USA Children's Healthcare of Atlanta Atlanta GA USA Nutrition and Health Sciences Program Laney Graduate School Emory University Atlanta GA USA Department of Radiology Children's Healthcare of Atlanta Atlanta GA USA Department of Computer Science and Biomedical Informatics Emory University Atlanta GA USA Department of Mathematics and Statistics and Computer Science Georgia State University Atlanta GA USA Department of Pathology and Laboratory Medicine Emory University Atlanta GA USA School of Physics Mathematics and Computing The University of Western Australia Crawley WA Australia Resonance Health Ltd Claremont WA Australia

Background & Aims Magnetic resonance-based steatosis measurement of the liver has become the non-invasive gold standard; however very few diagnostic thresholds have been independently validated and none in children. This study was designed to validate diagnostic thresholds, assess repeatability and the relationship to histology of a proprietary MRI volumetric liver fat fraction (VLFF) method (HepaFat-Scan ® ) and magnetic resonance spectroscopy (MRS) proton density fat fraction (PDFF) method. Methods This cross-sectional study assesses the diagnostic accuracy of MRI-VLFF and MRS-PDFF of 50 children who had a clinically indicated liver biopsy. Twenty-five children were randomly selected for intra-examination repeatability. The positive pixel count (PPC) algorithm was used to quantify the area of fat vesicles in the histology. The area under the receiver operating characteristic curve (AUROC) was used to assess the diagnostic accuracy. Bland-Altman plots were used to compare the methods and examine the repeatability. Results The MRI-VLFF ranged from 0.3% to 35.4% and the MRS-PDFF ranged from 0.5% to 36.9%. Based on histopathological analysis, the diagnostic accuracy of MRI-VLFF for steatosis detection (grade 0 vs 1-3) showed an AUROC of 0.95 (95% confidence interval [CI]: 0.89-1.00), whereas MRI-PDFF classified grade 0 vs 1-3 showed an AUROC of 0.96 (95% CI: 0.91-1.00). The repeatability coefficients were 1.8 (±0.5) % for MRI-VLFF and 2.1 (±0.6) % for MRS-PDFF. There was no bias between MRI-VLFF and PPC steatosis. To allow direct comparison, MRS-PDFF was converted to MRS-VLFF. Small, but significant biases were measured between PPC steatosis and MRS-VLFF (−1.38%) and between MRI-VLFF and MRS-VLFF (−1.39%). Conclusions Both MRI-VLFF and MRS-PDFF accurately estimated hepatic steatosis in children with excellent agreement with the histological assessment.

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The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2

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Cell 2025年第12期188卷 3167-3183.e18页

作者： Pekar, Jonathan E. Lytras, Spyros Ghafari, Mahan Magee, Andrew F. Parker, Edyth Wang, Yu Ji, Xiang Havens, Jennifer L. Katzourakis, Aris Vasylyeva, Tetyana I. Suchard, Marc A. Hughes, Alice C. Hughes, Joseph Rambaut, Andrew Robertson, David L. Dellicour, Simon Worobey, Michael Wertheim, Joel O. Lemey, Philippe Institute of Ecology and Evolution University of Edinburgh Edinburgh United Kingdom Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla 92093 CA United States Department of Biomedical Informatics University of California San Diego La Jolla 92093 CA United States Department of Medicine University of California San Diego La Jolla 92093 CA United States Division of Systems Virology Department of Microbiology and Immunology The Institute of Medical Science The University of Tokyo Tokyo Japan Medical Research Council University of Glasgow Centre for Virus Research Glasgow United Kingdom Department of Biology University of Oxford Oxford United Kingdom Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles 90095 CA United States Department of Immunology and Microbiology The Scripps Research Institute La Jolla 92037 CA United States Institute of Genomics and Global Health Redeemer's University Osun State Ede Nigeria Department of Computer Science and Engineering University of California San Diego La Jolla 92093 CA United States Department of Mathematics School of Science and Engineering Tulane University New Orleans LA United States Department of Population Health and Disease Prevention University of California Irvine Irvine 92617 CA United States Department of Biostatistics Fielding School of Public Health University of California Los Angeles Los Angeles 90095 CA United States Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles 90095 CA United States School of Biological Sciences University of Hong Kong Hong Kong Hong Kong China Biodiversity Green Development Foundation Beijing China Spatial Epidemiology Lab (SpELL) Université Libre de Bruxelles CP160/12 50 av. FD Roosevelt Bruxelles 1050 Belgium Department of Microbiology Immunology and Transplantation Rega Institute

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 led to increased sampling of sarbecoviruses circulating in horseshoe bats. Employing phylogenetic inference while accounting for recombination of bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed less than a decade prior to their emergence in humans. Phylogeographic analyses show bat sarbecoviruses traveled at rates approximating their horseshoe bat hosts and circulated in Asia for millennia. We find that the direct ancestors of SARS-CoV and SARS-CoV-2 are unlikely to have reached their respective sites of emergence via dispersal in the bat reservoir alone, supporting interactions with intermediate hosts through wildlife trade playing a role in zoonotic spillover. These results can guide future sampling efforts and demonstrate that viral genomic regions extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses. © 2025 The Authors

关键词： molecular epidemiology phylogeography sarbecoviruses virus evolution

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Retracted: Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method

Retracted: Design of Decision Support System Determination o...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, computer science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Iqbal, Muhammad Abdullah, Dahlan Hartono, H. Erliana, Cut Ita Sriadhi, S. Nurmawati, N. Prasnowo, M Adhi Hasibuan, Abdurrozzaq Iskandar, Akbar Saddhono, Kundharu Abdussakir, A. Musa, Hastuti Setiawan, Muhammad Ikhsan Sagala, Youmeni Siahaan, Rumiris Sinaga, Eka Mayastika Syahputri, Anggraini Milanie, Feby Aspan, Henry Khaddafi, Muammar Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Department of Industrial Engineering Universitas Maarif Hasyim Latif Sidoarjo Indonesia Faculty of Engineering Universitas Islam Sumatera UtaraMedan Indonesia Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Department of Mathematics Universitas Muhammadiyah Parepare Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia STIE Bina Karya Tebing Tinggi Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

The development of information and communication technology at this time has touched all sides of life. Almost no side of human life is not touched by this information technology, which is more synonymous with the world of computerization. No exception also with the computerization that is popular in the corporate environment and government agencies. If in ancient times everything was still done manually. However, at this time all leaders and management have realized the importance of this information technology products that can facilitate them in carrying out the day-to-day corporate functions. Decision Making System of goods purchasing is one of the determinants of the accumulation of goods. If the decision is taken right then stockpiling of goods can be avoided. In this thesis the authors designed a web-based system that helps Management in making the decision of the purchase amount of goods. the system was developed by using Microsoft Visual Studio 2010 and using SQL Server database processing applications. The end result of system design is expected to help minimize the accumulation of goods. © Published under licence by IOP Publishing Ltd.

关键词： Decision support systems

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Autonomous Exploration Guided by Optimisation Metaheuristic

Autonomous Exploration Guided by Optimisation Metaheuristic

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International Conference on Control, Automation, Robotics and Vision

作者： Raphael Gomes Santos Edison Pignaton de Freitas Sen Cheng Paulo Rogerio de Almeida Ribeiro Alexandre Cesar Muniz de Oliveira Federal University of Maranhão São Luís MA Brazil Graduate Program on Computer Science Federal University of Rio Grande do Sul Porto Alegre Brazil Computational Neuroscience Ruhr University Bochum Bochum Germany Department of Computer Engineering Federal University of Maranhão São Luís Maranhão Department of Informatics Federal University of Maranhão São Luís Maranhão

Autonomous exploration aims to develop mechanisms that enable a robot to navigate through an unknown environment, seeking to collect information that is relevant to its objective, with minimal or no human intervention. This article presents an autonomous exploration strategy based on a multimodal continuous utility function and optimization metaheuristic. The problem of autonomous exploration of mobile robots is formulated as an optimization problem, providing data for a Firefly-based algorithm that is able to search for points in the solution space, representing cells on the map being constructed, that best meet the exploration objectives. Simulations in a Robot Operating System environment showed that the proposed approach is able to guide robot through good trajectories, leading to full mapping, without any human intervention.

关键词： Linear programming Optimization Heuristic algorithms Robot kinematics Navigation Mobile robots

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Stream Learning and Anomaly-based Intrusion Detection in the Adversarial Settings

Stream Learning and Anomaly-based Intrusion Detection in the...

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IEEE Symposium on computers and Communications

作者： Eduardo Viegas Altair Santin Vilmar Abreu Luiz S. Oliveira Graduate Program in Computer Science Pontifical Catholic University of Parana Curitiba Parana Brazil Informatics Department Federal University of Parana Curitiba Parana Brazil

Despite existing many anomaly-based intrusion detection studies in the literature, they are not frequently adopted by the industry in production environments (products). Such a usage gap occurs mainly due to the difficulty to maintain the detection rate in acceptable level, given the occurrence of false alarms. In general, the literature does not consider the adversarial settings, when an opponent attempt to evade the detection system, thus possibly rendering the system unreliable over time. In this paper, we propose and evaluate a new approach to reliably perform real time stream learning for anomaly-based intrusion detection. We employ a class-specific stream outlier detector to automatically update the intrusion detection engine over the time, and a rejection mechanism, which makes it possible to obtain indications that an evasion attempt might being happening. Furthermore, the proposal is resilient to causative attacks, providing a secure intrusion detection mechanism even when the attacker can inject misclassified instances in the training dataset. The evaluation tests show that the proposed approach is resilient to exploratory attacks, allowing the system administrator to know when an evasion attempt might be occurring.

关键词： Adversarial Settings Outlier Detection Stream Learning Intrusion Detection

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The prediction of scholarship recipients in higher education using k-Nearest neighbor algorithm

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IOP Conference Series: Materials science and Engineering 2018年第1期434卷

作者： D Kurniadi E Abdurachman H L H S Warnars W Suparta Department of Informatics Sekolah Tinggi Teknologi Garut Jalan Mayor Syamsu 1 Garut 44151 Indonesia Department of Computer Science Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

This article aims to implement the algorithm model of k-Nearest Neighbor (k-NN) in analyzing, predicting, and classifying students who have potentials to get scholarships in universities. The k-NN algorithm works by making a prediction based on the closest data points between the old data history as training data and the new data as testing data. The data collected totals 1018 students with 24 scholarship receiver candidate students are used as the dataset for the test purposes. The attributes used in the prediction process are a semester, parents' income, number of family dependents, and Cumulative Grade Point Average. The distance calculation of the value from testing attribute to each training attribute uses Euclidean Distance equation, while the test of the model accuracy value is calculated using Confusion Matrix. The results of the simulation of the prediction model show that the determining factor of training data from both the number and the variation of different values can improve the performance of the k-NN algorithm with the best accuracy rate of 95.83 percent in predicting students who have the greatest chance of getting the scholarship.

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Using simplified chords sequences to classify songs genres

Using simplified chords sequences to classify songs genres

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Rodolfo Miranda Pereira Carlos N. Silla Informatics Department State University of Maringa (UEM) Maringa PR Brazil Computer Music Technology Laboratory — Graduate Program in Computer Science (PPGIa) Pontifical Catholic University of Paraná (PUCPR) Curitiba PR Brazil

ISBN: (纸本)9781509060689

Music Genre Recognition (MGR) is one of the most important forms of music organization and has been an important research subject. Most MGR methods consider the audio content itself instead of the songs meta-data, such as its chords. However, the audio is not always available due to copyright issues, which makes the use of meta-data for MGR an important task. The main objective of this paper is to propose a new method for MGR using simplified chords sequences. We also propose a new public dataset with 8,994 songs containing audio and chords features from six different genres in order to evaluate our method. The experimental results reached an accuracy rate of 56.13% using only the chords sequence feature with the Random Forest classifier, and 78.40% combining audio and chords features with the SVM classifier.

关键词： Feature extraction Support vector machines Frequency modulation Databases Rhythm Histograms Radio frequency

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Applying the MVC EA-IRPM to reporting-guidelines in medicine: A strategy that is a web system 4

Applying the MVC EA-IRPM to reporting-guidelines in medicine...

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4th IEEE EMBS International Conference on Biomedical and Health informatics, BHI 2017

作者： Letouze, Patrick De Souza, J.I.M. Silva, Valeria Martins Climaco, Glaubos Chagas, F.B. Ishihara, Joao Y. Graduate Program of Computational Modeling of Systems Universidade Federal Do Tocantins Quadra 109 Norte Avenida NS-15 Palmas77001-090 Brazil Graduate Program of Systems' Engineering and Computation - PESC Universidade Federal Do Rio de Janeiro Rio de Janeiro Brazil Department of Informatics at the Universidade Federal Do Maranh/ Ao - UFMA Brazil Faculty of Computer Science Faculdade Pitagoras Imperatriz Imperatriz Brazil Faculty of Electrical Engineering Universidade de Brasília Brasília Brazil

ISBN: (纸本)9781509041794

Reporting-Guidelines in Medicine play an important role in promoting the quality of reports in health-related research. For instance, a poorly reported research may induce misinterpretation and inappropriate clinical settings. Basically, three major issues regarding Reporting-Guidelines in Medicine has to be addressed: (1) the existence of lots of reporting guidelines covering a broad spectrum of medical research increases the difficulties when reporting a medical research because it may not be clear which guidelines are applicable, or if all related guidelines are considered;(2) most guideline developers have not described how their guidance was developed, consequently tracking guidelines and features for evaluation, or even for correcting, may be not possible;(3) few guideline developers have evaluated the effectiveness of their guidance, then the real value that the guideline brings to reporting the research is not assured. Hence, we propose a solution to these three issues based on the Model-View-Controller Evolutionary Acquisition Interdisciplinary Research Project Management (MVC EA-IRPM) that is simultaneously a strategy and a web system for the development and management of reporting guidelines. © 2017 IEEE.

关键词： Clinical research

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An Investigation of the Hoeffding Adaptive Tree for the Problem of Network Intrusion Detection

An Investigation of the Hoeffding Adaptive Tree for the Prob...

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International Joint Conference on Neural Networks

作者： Diego Guarnieri Corrêa Fabrício Enembreck Carlos N. Silla Graduate Program in Informatics (PPGI) - Federal University of Technology of Paraná (UTFPR) Cornélio Procópio PR Brazil 86300-000 Graduate Program in Computer Science (PPGIa) - Pontifical Catholic University of Paraná (PUCPR) Curitiba PR Brazil 80215-901

ISBN: (纸本)9781509061839

Intrusion detection in computer networks is a important topic in information security. Due to numerous cases of security breaches that caused economic and social losses in recent years, this topic has been the subject of several studies in order to mitigate problems related to network intrusion and computer attacks. Information security systems have been using different techniques for network intrusion detection. However, with the development of communication mechanisms and consequently with the increase in data traffic, some techniques used for intrusion detection lost their information processing capability. The emergence of new forms of attacks on computer systems also contribute to the depreciation of some of the existing tools. In this scenario, new techniques capable of processing large amounts of information and that perform proactive discovery of new attack vectors are necessary. This paper presents a study on the use of a data stream mining technique known as Hoeffding Adaptive Tree to create a predictive model for network intrusion detection. The experiments performed in this work show the effectiveness of this technique when applied to a database of computer network attacks.

关键词： Intrusion detection Data mining Tools computers Databases Prediction algorithms Adaptation models

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