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International Conference on informatics and Computing (ICIC)

作者： Muhammad Subianto Alim Misbullah Razief Perucha Fauzie Afidh Essy Harnelly Muhammad Irfan Zulfan Department of Statistics & Study Program of Artificial Intelligence Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Banda Aceh Indonesia Department of Informatics Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Banda Aceh Indonesia Department of Biology Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Banda Aceh Indonesia

Indonesia is a country with a vast archipelago and rich biodiversity, particularly in the province of Aceh. However, challenges are often encountered when exploring biodiversity due to limited information access. Providing a comprehensive source of information in this context is therefore important. This study is aimed to design and develop the Aceh Biodiversity Application, which was designed for Android-based mobile devices. In our implementation, the waterfall model is used as development method to build the application which are consisted of two core elements including the back-end REST API and the front-end Android application. The application also uses three different roles to differentiate the access, those are contributors, testers, and administrators. Finally, the functionalities testing were applied using black-box testing after the development phase. In addition, the usability testing was performed using the Post Study Usability Questionnaire (PSSUQ) method. The PSSUQ results showed the efficiency of the application, with an average usability score of 5.85, signifying a high level of usability.

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Digitization and Gamification in Cultural Heritage: The portuguese context in the framework of national and international policies and some practical examples 16

Digitization and Gamification in Cultural Heritage: The port...

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16th Iberian Conference on Information Systems and Technologies, CISTI 2021

作者： Cordeiro, Patricia Alexandra Nunes Sousa, Joao Paulo Carvalho, Aida Dei Feup Digital Media Doctoral Program Porto Portugal Esact Ipb Department of Mathematics and Informatics Mirandela Portugal Esact Ipb Citur Departamento de Artes e Humanidades Mirandela Portugal

ISBN: (纸本)9789895465910

This article begins with an attempt to contextualize the use of digital media and computation in works related to cultural heritage, in Portugal, in the frame of the regulations and policies that have been developed internationally and nationally. It then develops on the contextualization of the implementation of digitalization strategies regarding museum's collections in Portugal and its struggles both to implement these strategies as well as to invest in the creation and implementation of applications of digital tools for audience's engagement. Following some examples that have been developed for different purposes such as preservation, cataloguing, education and teaching, in different fields of cultural heritage such as archeology, ethnology, natural and historical sites, the article will then focus on the contributions of the more recent uses of technology to enhance or create interactive heritage experiences in cultural heritage, such as, photogrammetry, 3D modelling, and movement analysis. Finally, the last part of this article explores a proposal of gamification of intangible cultural heritage, portraying the winter festivity Carnival of Podence inscribed, in the Representative List of Intangible Cultural Heritage of Humanity, in December 2019. © 2021 AISTI.

关键词： Digital storage

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Hamiltonian Cycles for Finite Weyl Groupoids

arXiv

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arXiv 2023年

作者： Inoue, Takato Yamane, Hiroyuki Mathematics and Informatics Program Graduate School of Science and Engineering University of Toyama 3190 Gofuku Toyama930-8555 Japan Faculty of Science Academic Assembly University of Toyama 3190 Gofuku Toyama930-8555 Japan

Let Γ(W) be the Cayley graph of a finite Weyl groupoid W. In this paper, we show an existence of a Hamitonian cycle of Γ(W) for any W. We exatctly draw a Hamiltonian cycle of Γ(W) for any (resp. some) irreducible W of rank three (resp. four). Moreover for the irreducible W of rank three, we give a second largest eigenvalue of the adjacency matrix of Γ(W), and know if Γ(W) is a bipartite Ramanujan graph or not. Copyright © 2023, The Authors. All rights reserved.

关键词： Hamiltonians

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Efficient Maximum Euclidean Distance Transform Computation in Component Trees Using the Differential Image Foresting Transform

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Journal of Mathematical Imaging and Vision 2025年第3期67卷 1-23页

作者： Silva, Dennis J. Miranda, Paulo A. V. Alves, Wonder A. L. Hashimoto, Ronaldo F. Kosinka, Jiří Roerdink, Jos B. T. M. Institute of Mathematics and Statistics University of São Paulo R. do Matão 1010 SP São Paulo05508-090 Brazil Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Nijenborgh 9 Groningen9747 AG Netherlands Informatics and Knowledge Management Graduate Program Nove de Julho University R. Vergueiro 235/249 SP São Paulo01525-000 Brazil

The distance transform is a crucial technique in binary image processing, assigning the distance to the nearest contour to each foreground pixel. In this extended version of our previous work, we enhance our method for computing the maximum distance transform (DT) value, now utilizing the optimized differential image foresting transform (DIFT) and improved contour extraction processes. These advancements enable more efficient computation of the maximum DT value across all connected components of a grayscale image, significantly reducing computational time by intelligently reusing DIFT trees rooted at contour points (DIFT seeds). Our optimized algorithm now achieves processing speeds that are twice as fast as our previous differential method. The proposed attribute, maximum distance, which measures the thickness of objects within the image, has proven pivotal in different image processing approaches. We showcase this through detailed illustrations of attribute opening, extinction value filters, watershed, and ultimate attribute openings. © The Author(s) 2025.

关键词： Binary images

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Investigating the Predictive Performance of Gaussian Process Machine Learning in Time Series Demographic Data Handling

Investigating the Predictive Performance of Gaussian Process...

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International Conference on Computer and Automation Engineering, ICCAE

作者： Shalini Nagaratnam Muhammad Naeim Mohd Aris Nuralea Natasya Amir Hamdan Department of Econometrics and Business Statistics School of Business Monash University Malaysia Bandar Sunway Malaysia Department of American Degree Transfer Program School of American Education Sunway University Bandar Sunway Malaysia College of Computing Informatics and Mathematics Universiti Teknologi MARA Malaysia

ISBN: (数字)9798350370058

ISBN: (纸本)9798350370164

Effective handling and modelling of time series data play a crucial role in enhancing the quality of derived information during the research process which includes addressing missing values. Meticulous attention to these data-related tasks is paramount, as the outcomes of the research are directly influenced by the quality and integrity of the processed data. This study employs a non-parametric Gaussian Process Regression (GPR) prediction algorithm in machine learning to investigate the predictive performance of Malaysian demographic data for 1960 to 2021. For robust results, the traditional parametric models were introduced for comparison. The reliability and efficiency of the algorithm are presented. The results show that the GPR with squared exponential covariance function can give the most accurate prediction on the data based on the low mean absolute deviation (MAD) and root mean squared error values (RMSE).

关键词： Interpolation Machine learning algorithms Computational modeling Biological system modeling Time series analysis Urban areas Gaussian processes

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Intelligent Traffic Management System using Internet of Things: A Systematic Literature Review

Intelligent Traffic Management System using Internet of Thin...

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International Conference on Computing, Engineering, and Design (ICCED)

作者： Hendra Marcos Rahmat Gernowo Isnaini Rosyida Oky Dwi Nurhayati Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Informatics Universitas Amikom Purwokerto Department of Mathematics Faculty of Mathematics and Natural Sciences Universitas Negeri Semarang Semarang Indonesia

ISBN: (纸本)9781665453905

The number of vehicles on the road will continue to expand as cities worldwide grow in population. This increases transportation congestion, especially in major cities and especially during rush hour. This phenomenon continuously pushes academics, city authorities, and urban planners to enhance traffic control systems for safety and efficiency. The application of Internet of Things (IoT) in the field of intelligent transportation systems is getting the attention of many parties. A well-controlled transportation management system can reduce congestion, especially at intersections and roads. This study was conducted to observe and study the development of research in transportation management, especially the use of IoT technology. There are 743 documents according to the keywords given related to IMS and ITS, the period 2012 until September 2021. Mapping of these articles, both in terms of publishers, the relationship between authors, and the methods used from keywords, abstracts, and titles, is expected to help the author determine research gaps and future research directions.

关键词： Systematics Roads Bibliographies Urban areas Sociology Transportation Traffic control

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Atmospheric dynamics and early warning system low level windshear for airport runway hazard mitigations 10

Atmospheric dynamics and early warning system low level wind...

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10th International Seminar on New Paradigm and Innovation of Natural Sciences and itsApplication, ISNPINSA 2020

作者： Gernowo, R. Subagio, A. Adi, K. Widodo, A.P. Widodo, C.E. Putranto, A.B. Department of Physics Faculty of Science and Mathematics Diponegoro University Indonesia Department of Informatics Faculty of Science and Mathematics Diponegoro University Indonesia Study Program of Automation Engineering Technology Vocational School Diponegoro University Jl. Prof. Soedarto SH. Tembalang Semarang50275 Indonesia

Natural disaster nowadays often occur in Indonesia due to climate change, especially those related to atmospheric dynamics anomalies. The statutory event of atmospheric turbulence statistically is quite significant in its improvement. This is an important issue to conduct research both in the analysis of atmospheric dynamics and early detection solutions for these events. The Windshear phenomenon is an atmospheric turbulence disaster that occurs below an altitude of 3000 feet, often known as low level windshear (LLWS), which is very dangerous for planes taking take-off or landing. Its effect on the aircraft will result in increased airflow on the wings, so this increased airflow will result in a sudden increase in aircraft speed. If the pilot is not aware of the indication of the windshear, he will instinctively throttle back to reduce/compensate for the aircraft's speed. However, once the plane passes through the wind shear zone, the wind suddenly turns into a downdraft. The design of windshear early detection devices have been developed to complement research on the dynamics of the atmosphere. The results obtained are anomalous changes in temperature and atmospheric pressure at this time, and the windshear sensor can detect it well. © Published under licence by IOP Publishing Ltd.

关键词： Aircraft

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Discoffery: A Coffee Types Detection Apps using an EfficienNet-Lite Architecture 7

Discoffery: A Coffee Types Detection Apps using an EfficienN...

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7th International Conference on Sustainable Information Engineering and Technology, SIET 2022

作者： Budiman, Satrio Arif Pramono, Andi Priyambadha, Bayu Putri, Annisa Maharani Arya Purnomo, Agung Nugroho, Ilham Setyo Information System Computer Science Faculty University of Brawijaya Malang65145 Indonesia Interior Design Department School of Design Bina Nusantara University Jakarta11480 Indonesia Department of Informatics Computer Science Faculty Brawijaya University Malang65145 Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences Brawijaya University Malang65145 Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781450397117

According to data from the World Food and Agriculture Organization (FAO), Indonesia produced the fourth-most coffee in the world in 2017 and 2018. Gayo, Robusta Dampit, and Toraja coffees are only a few well-known coffee varieties Indonesian growers produce. This research aims to create an app that can identify the type of coffee and serve as a coffee-related educational tool. A single case study was the research methodology used. By employing the EfficienNet-Lite architecture for transfer learning, a model for categorizing coffee beans is created. Users can get information through the photographs they submit with the help of the type of application development that uses deep learning to do categorization based on image data of coffee bean types. The coffee bean classification feature was built using transfer learning with the EfficientNet architecture. A training accuracy of 87% and a validation accuracy of 81% were achieved using the EfficientNet-Lite 0 architecture. © 2022 ACM.

关键词： Deep learning

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An Intelligent System Based on Evolutionary Algorithm for Scheduling University Course Timetable

SSRN

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SSRN 2022年

作者： Bimantara, I. Made Satria Yuhana, Umi Laili Supriana, I. Wayan Pardede, Eric Department of Informatics Institut Teknologi Sepuluh Nopember 60117 Indonesia Informatics Study Program Faculty of Mathematics and Natural Sciences Udayana University Indonesia Department of Computer Science and Information Technology La Trobe University BundooraVIC3086 Australia

University Course Timetabling (UCT) is a common problem in educational institutions. The preparation of the class schedule must pay attention to available resources without violating set constraints. This research applies Evolutionary Algorithm such as Genetic Algorithm into timetabling system, to replace human expertise in generating optimal lecture schedules. Genetic Algorithm (GA) uses chromosomes to represent the solution of the UCT. One chromosome represents a set of schedule solutions that AG generates. Genes and alleles become components of chromosomes that represent the value of each entity to be optimized. We modeled chromosomes into four gene types, each of which has three allele types, namely day, hour, and room alleles which will be optimized with GA. The N-point and cycle crossovers were implemented into the new chromosome encoding scheme and do not take place at the gene level, but at the allele level by grouping similar allele types before the crossover process is carried out. The success rate is measured by the percentage of the optimal number of schedules generated from the trials. The proposed method provides a success rate of 80 - 85% and can produce an optimal schedule with an average computation time of 8 minutes. GA can reduce human resources and save time in the process of preparing lecture schedules. © 2022, The Authors. All rights reserved.

关键词： Genetic algorithms

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Machine Learning for Prediction of Adverse Drug Reactions: Application to Neonatal Intensive Care Units

SSRN

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SSRN 2023年

作者： do Nascimento, Amanda Roseane Farias Greati, Victor Rodrigues Leopoldino, Ramon Weyler Duarte Martins, Rand Randall Barbosa, Euzebio Guimarães Graduate Program in Pharmaceutical Sciences Health Sciences Center Federal University of Rio Grande do Norte Rio Grande do Norte Natal Brazil Graduate Program in Systems and Computing Department of Informatics and Applied Mathematics Federal University of Rio Grande do Norte Rio Grande do Norte Natal Brazil

Introduction: The intensive care of neonates is associated with the entry of a large volume of data in their medical records. The treatment of this data can be done through Machine Learning: a tool capable of assisting in the detection and decision-making of a wide range of medical conditions, including adverse drug reactions (ADR). Objective: To train a prediction model to assist in the detection of adverse drug reactions in neonates admitted to an ICU. Methodology: observational study developed in the Neonatal Intensive Care Unit of a teaching hospital in Brazil. Clinical data were collected from daily pharmacotherapeutic follow-up, processed and analyzed by machine learning through libraries written in Python language. Results: Eight hundred and three neonates were included in the study, with a mean gestational age of 32.2 ± 4.2 weeks and mean birth weight of 1807.2 ± 936.6g. The incidence of ADR was 10.8%. Antimicrobials, especially aminoglycosides, were the most prescribed drugs for this population. An algorithm was trained and tested to predict ADR in the NICU, in which the metrics were precision (0.35) and recall (0.823), with specificity (80%) and sensitivity (67%). Conclusion: There is a high potential in the machine learning method to predict ADR in neonates admitted to an ICU. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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