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FOSS4G 2021 - Academic Track

作者： Camara, Gabriele Silveira Camboim, Silvana Philippi Bravo, João Vitor Meza Graduate Program in Geodetic Science Federal University of Parana Brazil Institute of Geography Graduate Program in Geography and Graduate Program in Agriculture and Geospatial Information Federal University of Uberlandia Brazil

This article presents two applications developed using Jupyter Notebook in the Google Colab, combining several Python libraries that enable an interactive environment to query, manipulate, analyse, and visualise spatial data. The first application is from an educational context within the MAPFOR project, aiming to elaborate an interactive map of the spatial distributions of teachers with higher education degrees or pedagogical complementation per vacancies in higher education courses. The Jupyter solutions were applied in MAPFOR to better communicate within the research team, mainly in the development area. The second application is a framework to analyse and visualise collaborative emotional mapping data in urban mobility, where the emotions were collected and represented through emojis. The computational notebook was applied in this emotional mapping to enable the interaction of users, without a SQL background, with spatial data stored in a database through widgets to analyse and visualise emotional spatial data. We developed these different contexts in a Jupyter Notebook to practice the FAIR principles, promote the Open science movement, and Open Geospatial Resources. Finally, we aim to demonstrate the potential of using a mix of open geospatial technologies for generating solutions that disseminate geographic information. Copyright © 2021 G. S. Camara et al.

关键词： Python

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A Hybrid Inference Engine to Predict Uncertain Sugar Content for Sugar Industry

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Procedia computer science 2024年 245卷 480-489页

作者： Muhammad Asrol Napthaleni Ditdit Nugeraha Utama Suharjito Christian Harito Muhammad Syafrudin Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Department of Artificial Intelligence and Data Science Sejong University Seoul 05006 South Korea

The sugar industry is facing challenges in increasing productivity to meet consumer demand. One opportunity for productivity improvement lies in ensuring sugar content. This study proposes a hybrid model to predict sugar content by considering uncertainty factors. A hybrid model combining fuzzy subtractive clustering, and a fuzzy inference system is proposed to predict sugar content. The clustering results using silhouette and fuzzy subtractive clustering successfully identified 6 cluster centres from 2225 datasets collected in a sugar industry in East Java Province. The hybrid inference engine model is designed with fuzzy rules derived from the clustered data. Two inference models are developed: triangular and Gaussian fuzzy numbers. The testing results indicate that the hybrid model with triangular fuzzy numbers shows the smallest error with an R2 value of 0.95. This model is possible to applied in the sugar industry for decision makers in improving productivity with taking attention into uncertain factors influencing sugar content.

关键词： Clustering Fuzzy Hybrid model Inference System Prediction Sugarcane

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An Accuracy Assessment for Active Data Physicalization

An Accuracy Assessment for Active Data Physicalization

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International Conference on Information Visualisation (IV)

作者： Cleyton Luiz Ramos Barbosa Thiago Augusto Soares de Sousa Walbert Cunha Monteiro Diego Hortencio Dos Santos Tiago Davi Oliveira de Araujo Bianchi Serique Meiguins Computer Science Graduate Program Federal University of Para Belem Para Brazil IEETA DETI University of Aveiro Aveiro Portugal

Recent literature reviews point out that active data physicalizations still lack evaluation scenarios. These evaluations mainly focus on the perception of visual and physical characteristics of physicalizations and users' performance of analysis tasks. This paper addresses a proposed accuracy assessment of data physicalization for data representation. The data physicalization used is a physical and dynamic bar chart using 3D printed models (3D bars) and LED strips inside the bars, both controlled by microcontrollers (Arduino), being possible to represent different datasets. The accuracy assessment of this physicalization is based on the height and color of the 3D bars. For this, distance sensors measure the actual height values of the bars, and a computer vision camera/algorithm collects and estimates the RGB value of the bars. From original and measured values datasets, bar charts images are built to perform a similarity comparison between the images. The similarity metric is used as an accuracy metric of the bar heights to represent data and obtained as initial results value higher than 96%. Furthermore, an evaluation scenario of the distance between the reference and measured colors 2000) classifies most of them as having proper perception. Additionally, the accuracy loss was evaluated on data physicalization in a scenario of continuous use (ten configurations without any calibration), and the variation of errors was around 2%.

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An IoT-Driven Fuzzy Decision Model for Determining Room Comfort

An IoT-Driven Fuzzy Decision Model for Determining Room Comf...

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Informatics International Conference (BTS-I2C), Beyond Technology Summit on

作者： Ditdit Nugeraha Utama John Reigton Hartono Johan Muliadi Kerta Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia Bina Nusantara University School of Computer Science Computer Science Bandung Indonesia

ISBN: (数字)9798331508579

ISBN: (纸本)9798331508586

The use of the Internet of Things (IoT) has been widely adopted for a lot of purposes. Business process automation is one type of implementation that has been carried out. In addition, the data successfully captured by the IoT ecosystem can be utilized for various computer modeling needs, including the decision model construction in assessing room quality. The decision model itself is a computer model supporting the decision maker in decision making process. This research, via four simple research stages, aims to develop an IoT-based decision model to evaluate room quality based on two parameters: temperature and humidity. The design of the IoT environment and the implementation of temperature and humidity data readings in a room are used as input data for a decision model to assess the comfort level of the room. In this study, the primary method used to design the model is object-oriented, while fuzzy logic is employed to build the model. The developed decision model can simulate data captured from the designed IoT ecosystem, successfully assessing the comfort level of a room. From the simulation results using 18 data points (from 9 days of data capturing) captured by temperature and humidity sensors, the average comfort level of the room was found to be 19.7873.

关键词： Temperature sensors Fuzzy logic Temperature distribution Object oriented modeling Computational modeling Simulation Ecosystems Humidity Data models Internet of Things

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Trends of Digital Transformation in the Property Management Industry: A Systematic Literature Review

Trends of Digital Transformation in the Property Management ...

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2023 IEEE International Conference on Smart Information Systems and Technologies, SIST 2023

作者： Saputra, Prasetya Cahya Prabowo, Harjanto Ramadhan, Arief Madyatmadja, Evaristus Didik Binus University Binus Graduate Program-Computer Science Computer Science Department Jakarta Indonesia Binus Business School Doctor of Research in Management Binus University Management Department Jakarta Indonesia Telkom University Bandung Indonesia School of Information System Binus University Jakarta Indonesia

ISBN: (纸本)9798350335040

After the Covid 19 pandemic, the property management industry is slowly starting to revive. Even though the occupancy rate has not returned to normal like the Covid19 pandemic, its growth is starting to move in a positive direction. The Covid19 pandemic has provided many lessons for all stakeholders in the property management industry. Digital transformation has become a part that has received important attention in the property management industry worldwide. With digital transformation in the property management industry, all stakeholders are expected to receive various benefits, directly or indirectly. The implementation of digital transformation will involve 6 components, namely: Strategy, Organization, Culture, Customer, People, and Technology. The implementation of digital transformation in the property management industry will require support from many parties, not only internal parties but also external parties. Technological developments, IoT, and demands from residents and property owners are challenges that must be answered by property managers. This systematic literature review will examine articles that have been published in the Scopus database regarding the development of digital transformation in the property management industry from various countries. The purpose of this SLR is to be able to see how the digital transformation trend and the application of its components are in the current property management industry. © 2023 IEEE.

关键词： Apartment Property Management Systematic Literature Review Transformation Digital

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Evaluation of REAL-ESRGAN Using Different Types of Image Degradation

Evaluation of REAL-ESRGAN Using Different Types of Image Deg...

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International Conference on ICT For Smart Society (ICISS)

作者： Kus Andriadi Muhammad Zarlis Yaya Heryadi Andry Chowanda Computer Science Department Binus Graduate Program Bina Nusantara University Jakarta Indonesia Information System Management Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science BINUS University Jakarta Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

This study evaluates the performance of the REAL-ESRGAN [1] model on images with varying levels of degradation using the DIV2K dataset [2], such as the Wild, the Mild, the Difficult, and the x8 subsets. REAL-ESRGAN was created to solve super-resolution problems and aims to produce high-resolution images from low-resolution images. Experiments were conducted at scales of x2 and x4, and performance was measured using Full-Reference metrics (LPIPS, PSNR, SSIM) and No-Reference metrics (NIQE, MANIQA, CLIPIQA, and PI). The Results were good, especially with the x2 scale; it has higher PSNR and SSIM scores, lower LPIPS and NIQE values, and enhanced visual and perceptual quality. The model faced more significant challenges with the wild and the difficult datasets because they have more complex degradations and compression artifacts; it can be seen with unstable results of Full-Reference and No-Reference metrics. On the contrary, the Mild and x8 datasets yielded better results in both metrics; not only that, even the computational cost for Mild and x8 outperforms the rest of the dataset. This study shows the strengths and limitations of REAL-ESRGAN in handling different levels of image degradation. For future research, the model needs enhancement to tackle the degradation format of the wild and the difficult dataset. It would be good if the REAL-ESRGAN improvement could also maintain the computational cost.

关键词： Degradation Measurement Visualization Computational modeling Superresolution Computational efficiency Image reconstruction

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Exploring Transfer Learning Approach for Environmental Sound Classification: A Comparative Analysis

Exploring Transfer Learning Approach for Environmental Sound...

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Smart Computing, IoT and Machine Learning (SIML), International Conference on

作者： Theresia Herlina Rochadiani Yulyani Arifin Derwin Suhartono Widodo Budiharto Computer Science Department Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350364101

ISBN: (纸本)9798350364118

The expansion of deep learning techniques, as well as the availability of large audio/sound datasets, have fueled tremendous breakthroughs in audio/sound classification during the last several years. The transfer learning approach has emerged as one of the primary approaches for improving the accuracy and durability of classification systems. This study conducts a comprehensive comparative analysis to determine the effectiveness and performance of this method in environment sound classification. This current investigation focuses on environmental sound classification using VGGish and YAMNet pre-trained models with the ESC-50 and BDLib2 datasets. In the ESC-50 dataset, VGGish improves accuracy to 372.22%, while YAMNet improves accuracy to 383.33% when compared to baseline models. Similarly, in the BDLib2 dataset, accuracy increases significantly to 221.43% with VGGish and 246.43% with YAMNet. Transfer learning exhibits remarkable effectiveness in enhancing model performance, with significant accuracy boosts observed in both datasets. YAMNet, designed specifically for sound classification tasks, surpasses VGGish in improving environmental sound classification performance, potentially due to its architecture’s adaptability and diverse training on environmental sounds.

关键词： Training Deep learning Adaptation models Analytical models Accuracy Computational modeling Transfer learning

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A Comparative Analysis of User Experience and Educational Outcomes in Math Memory Games

A Comparative Analysis of User Experience and Educational Ou...

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International Conference on computer Engineering, Network and Intelligent Multimedia (CENIM)

作者： Nicholas Martin Raffel Nathanael Doni Jeriyanto Eric Savero Hermawan Janshen Fung Francisco Maruli Panggabean Computer Science Department Game Application & Technology Program School of Computer Science Bina Nusantara University Jakart Indonesia Master of Computer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350368802

ISBN: (纸本)9798350368819

This research explores multiple varieties of effective and child-friendly learning approaches for mathematics and memorization among young children in today's increasingly digital age considering their specific developmental needs. This type of approach includes in-person teaching, engaging online videos, interactive textbooks, and innovative educational games. This research employs a detailed comparative analysis, considering both ‘User Experience’ and measurable learning outcome factors, and spans a range of age groups from preschoolers to elementary school children. Through highlighting the strengths and weaknesses of each method, this research aims to inspire the adoption of efficient, child-centric, and novel teaching techniques by educators and institutions, thereby advancing the quality of education in Indonesia. The results show that using serious game in education presents high usefulness score alongside positive user experience, suggesting its viability for educational purposes.

关键词： Measurement Video games Education Games Educational technology Information age User experience Mathematics Usability Systematic literature review

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The Age and Updating Stability for a Communication Context in VANET

The Age and Updating Stability for a Communication Context i...

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Brazilian Symposium on Computing System Engineering (SBESC)

作者： Margarete De Sá Sérgio Gorender Distributed Systems Laboratory (LaSiD) Graduate Program in Mechatronics (PPGM) Computer Science Institute (IC) and Polytechnic School (EP) Federal University of Bahia (UFBA)

ISBN: (数字)9798331509002

ISBN: (纸本)9798331532857

VANETs make it possible to execute specific vehicular applications, in particular those with the aim of turning traffic safe and avoiding congestion. However, it is difficult to maintain communication between vehicles when these vehicles move dynamically at high speeds. Context-aware systems have been studied as a way to monitor context information from sensors, which can be used by systems to adapt to changes in their environment or in application requirements. This concept is used by VANET protocols and applications in different ways. Quality of Context (QoC) metrics are used to qualify the context information considering different characteristics of sensors and of the information, being a base for systems to decide if it is safe and interesting to use specific information. In this paper, we propose QoC metrics related to the stability of the updating process for a vehicular communication context. In addition, we also analyze the Age QoC metric and show how to calculate it for distinct context information. We simulate scenarios to verify the QoC metrics behavior. The results showed that the proposed QoC metrics can properly qualify the vehicular communication context.

关键词： Measurement Roads Vehicular ad hoc networks Sensor phenomena and characterization Turning Systems engineering and theory Stability analysis Sensor systems Reliability Monitoring

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Resilient Software Defined Satellite Networks: Combining Clustering Techniques with Efficient Routing Protocols

Resilient Software Defined Satellite Networks: Combining Clu...

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International Conference on Software Defined Systems (SDS)

作者： Juliano Antonio da Silva Paulo Mendes Edison Pignaton de Freitas Graduate Program in Computer Science Federal University of Rio Grande do Sul Porto Alegre Brazil Central Research and Technology Airbus Munich Germany

ISBN: (数字)9798331518325

ISBN: (纸本)9798331518332

Low Earth Orbit satellite constellations are highly mobile and thus have time-varying network topologies. Such time-varying networks face various challenges due to intermittently available links and devices. Consequently, many routing algorithms that work well on the terrestrial Internet may not be suitable for Low Earth Orbit (LEO) constellations. This paper provides an analysis of the impact that different types of routing algorithms may have on the performance of LEO constellations. The provided study analyses not only link-state routing algorithms, as used in well-known routing protocols for LEO constellations such as Contact Graph Routing (CGR), which follows a Software Defined Networking (SDN) approach, but also distance-vector algorithms, as well as the potential combination of link-state and distance-vector algorithms when network clusters are used in a LEO constellation.

关键词： Satellites Heuristic algorithms Software algorithms Clustering algorithms Low earth orbit satellites Routing Software Routing protocols Vectors Software defined networking

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