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Frontiers in Education (FIE) Conference

作者： Joethe Moraes de Carvalho José Francisco de Magalhães Netto Post-Graduate Program in Informatics (PPGI) Institute of Computing (ICOMP) Federal University of Amazonas (UFAM) CMC-Federal Institute of Amazonas (IFAM) Manaus AM Brazil Post-Graduate Program in Informatics (PPGI) Institute of Computing (ICOMP) Federal University of Amazonas (UFAM) Manaus AM Brazil

This Research Full Paper presents a pedagogical approach to evaluate a virtual platform for teaching robotics at a distance. The virtual environment was developed using the principles of Collaborative Learning. This virtual platform, called groupware, should facilitate interaction between those involved in the teaching and learning process, whether the student or the teacher. In this research, we will use Educational Robotics as a mediating tool in the teaching and learning process, because it has become a powerful tool that has stimulated the acquisition of knowledge in computing. In the groupware used in this research, Multi-Agent Systems were used to collaborate with teachers in the management of activities. The purpose of this study was to evaluate the functionality and usability of this virtual environment. A qualitative, exploratory research was used and to assess the usability of this virtual environment, the usability evaluation techniques were used with the Syetem Usabily Scale metric, and the technique of evaluation of feelings through EmoCards. Ten computer teachers participated in this research, with training and specializations in the areas of computing. Collaborative Learning was used as a focus for solving the tasks proposed for this research. The results showed that the participants evaluated the groupware with great potential to collaborate in robotics teaching and with content appropriate to the students' initial level of learning. The teachers' perceptions regarding the usability of the evaluated groupware revealed that it is favorable in the teaching of robotics and allowed an analysis of the importance of collaborative learning in the educational environment, directly impacting their ways of conducting learning.

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2nd International Conference on Computer Science and Engineering, IC2SE 2021

作者： Hartanto, Anggit Dwi Pristyanto, Yoga Saputra, Andy Universitas Amikom Department of Information System Yogyakarta Indonesia Universitas Amikom Master Program of Informatics Yogyakarta Indonesia

ISBN: (纸本)9781665400459

Plagiarism action often occurs in the world of education. One example of plagiarism in education, especially in the university environment, is the frequent occurrence of similarities between theses made by students. One solution is to develop an application that can detect similarities in thesis documents that can be used by all groups, especially to facilitate students. Natural Language Processing (NLP) is one of the fields that can be a solution in developing document similarity detection applications. In this study, testing focused on Indonesian documents. In addition, this study aims to build a system or application to detect the similarity of Indonesian documents using the Rabin-Karp algorithm with the Cosine Similarity method as a Distance-Based Similarity Measure and using the Stemming technique. The experiment results using 15 documents of scientific publications in Indonesian show that the Rabin-Karp algorithm with Cosine Similarity can be used to detect the similarity of published manuscripts, especially in Indonesian. With the fastest processing time of seconds and the longest around. seconds, this algorithm quickly detects document similarities, especially in documents. Further research is recommended to optimize from the algorithm side so that the processing time is faster with a much larger number of words. © 2021 IEEE.

关键词： Students

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Event-driven Sentiment Drift Analysis in Text Streams: An Application in a Soccer Match

Event-driven Sentiment Drift Analysis in Text Streams: An Ap...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Cristiano Mesquita Garcia Alceu de Souza Britto Jean Paul Barddal Graduate Program in Informatics (PPGIa) Pontifícia Universidade Católica do Paraná (PUCPR) Instituto Federal de Santa Catarina - Caçador Curitiba Brazil Graduate Program in Informatics (PPGIa) Pontifícia Universidade Católica do Paraná (PUCPR) Curitiba Brazil

Social media has been a data source for various applications, given its characteristic of working as a social sensor. Many applications in several areas, such as brand reputation and online opinion monitoring, use this valuable resource to understand the users of services and products. This paper describes an application in the soccer domain, considering data collected from a social media textual data stream. The goal is to detect possible sentiment drifts related to actual events in a soccer match. This task is challenging as we resort to short texts made available during a short time (match length). We evaluated four drift detectors using four metrics: false alarms, delay (considering the number of posts), delay, and missing drifts. Our results show that ADWIN had a stable performance in sentiment drift detection compared to other methods in timely detecting the flagged drifts, raising a small number of false alarms. Given the drifts detected, we used Incremental Word-Vectors to monitor words of interest and check their relatedness to actual events in the match. We empirically assert that the closest words trace back to the sentiment drift generator events.

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Achievement of green campus indications based on assessment indicators on H-BAT program Universitas Negeri Semarang 9

Achievement of green campus indications based on assessment ...

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9th Engineering International Conference, EIC 2020

作者： Prihanto, T. Fathoni, K. Prasetiyo, B. Study Program of Architecture Faculty of Engineering Universitas Negeri Semarang Indonesia Study Program of Electrical Engineering Faculty of Engineering Universitas Negeri Semarang Indonesia Study Program of Informatics Universitas Negeri Semarang Indonesia

Universitas Negeri Semarang (UNNES) has a spirit to become a Conservation and International Reputation University is realized through strategic missions. One of the conservation-oriented implementation programs is H-BAT (Green, Clean and Healthy) program. In its implementation, there is a problem, namely the achievement of H-BAT program has not been maximized during the last 3 years in assessment. The objectives of this research are: (1) to identify of the potential and character of environmental support in the work units;(2) to determine the achievement of the indication of a green campus based on the assessment indicators on H-BAT program. This research was carried out in four stages: (1) Data collection;(2) Spatial data processing;(3) Non Spatial data processing;(4) Analysis (ecological, technical standards);The results achieved in June 2020 are as follows: FT got 87,50%, FE got 85,87%, FMIPA got 81,52%, BUHK got79,49%, FIP got 73,91%, LP3 got 69,23%, LP2M got 63,46%, FIS got 60,33%,PPS got 57,07%, FIK got 56,52%, FH got 52,72%, FBS got 49,46%, TIK got 40,38%, BPB got 34,62%, Library got 30,13%, Archive got 17,31%. From these results, it can be seen that there is a lack of maximum achievement due to, among others, the lack of guidance and technical assistance in the management of the unit. So it is necessary to complete governance guidelines and technical assistance that are more intensive in unit governance to achieve the goals of UNNES as a green campus. © Published under licence by IOP Publishing Ltd.

关键词： Data handling

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An Introduction to the Three-Body Problem Optimization Algorithm: A Novel Swarm-Based Optimization Method 3

An Introduction to the Three-Body Problem Optimization Algor...

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3rd International Conference on Disruptive Technologies, ICDT 2025

作者： Sudirman, Ivan Diryana Herwanto, Patah Binus Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Bandung40181 Indonesia Stmik Im Informatics Engineering Department Bandung40113 Indonesia

ISBN: (纸本)9798331519582

The Three-Body Problem Optimization Algorithm (3BPOA) is a metaheuristic method inspired by how gravity interacts if there are three bodies, a classical physics problem. 3BPOA uses 3 best agents or leaders where these 3 best agents will interact with each other and also influence the movement of the swarm. The interaction of these 3 best bodies or agents is also influenced by the distance between the three. In this study, 3BPOA was tested on the Rastrigrin mathematical function using various scenarios from 5 dimensions to 100 dimensions, also using various population sizes. The test results show that the 3BPOA algorithm has good performance in low dimensions and quite good in medium dimensions. In high dimensions, if using a large population, 3BPOA has good potential. © 2025 IEEE.

关键词： Particle swarm optimization (PSO)

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Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer 24

Predicting Microsatellite Instability from Histology Images ...

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24th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2024

作者： Chen, Yun-Chi Chao, Tung Phandita, Wimaya Nitya Sun, Tzu-Yu Wang, Huai-Zhi Hsieh, Yi-Hsien Hsu, Le-Yin Lin, Che Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan NTU Data Science Degree Program Taipei Taiwan NTU Department of Electrical Engineering Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan NTU Smart Medicine and Health Informatics Program Taipei Taiwan

ISBN: (纸本)9798331518622

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients. © 2024 IEEE.

关键词： Diseases

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Superimposition of 3D Dynamic Objects on a Static Environment for Driver Assistance System 10

Superimposition of 3D Dynamic Objects on a Static Environmen...

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10th IEEE Global Conference on Consumer Electronics, GCCE 2021

作者： Zhang, Haihan Shishido, Hidehiko Kitahara, Itaru Empowerment Informatics Program University of Tsukuba Ibaraki Japan Center For Computational Sciences University of Tsukuba Ibaraki Japan

ISBN: (纸本)9781665436762

With the development of sensor accuracy and optimization algorithms, Advanced Driver Assistance System (ADAS) has been widely used on vehicles to achieve level 3 of automatic driving. Vision-based dense mapping is one of the most essential solutions in ADAS to help vehicles sensing surroundings. However, traditional methods could only reconstruct a 3D map of a static environment because the occlusion of dynamic objects on the environment map. Moreover, dynamic environment is hard to be 3D modeled in real-time because of the limitation of computing power and algorithm complexity. To make the dynamic scene visible in a 3D point cloud, this paper proposes a system that superimposes dynamic objects on a static environment in real-time. The static environment is reconstructed by aerial multi-view images from the unmanned aerial vehicle (UAV) in advance to reduce the required computing power. Dynamic objects point cloud is generated from disparity maps generated by a consumer stereo-camera frame by frame. To superimpose the dynamic objects on the global 3D static map, a plane segmentation method is applied to reduce the mismatching for global point cloud registration. The result shows that the registration fitness reaches 79.8%, which is applied for the fusion of multiple measuring methods. © 2021 IEEE.

关键词： Advanced driver assistance systems

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Impact of Filter-Based Feature Selection on Prediction Model Performance for Early Detection of Stunting

Impact of Filter-Based Feature Selection on Prediction Model...

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International Conference on informatics and Computing (ICIC)

作者： Sri Handani Widiastuti Purwanto Adi Wibowo Ratih Wirapuspita Wisnuwardani Informatics Engineering Study Program Sekolah Tinggi Teknologi Bontang Indonesia Doctoral Program of Information System School of Postgraduate Studies Diponegoro Univercity Indonesia Department of Chemical Engineering Faculty of Engineering Diponegoro Univercity Semarang Indonesia Department of Informatics Faculty of Science and Mathematics Diponegoro Univercity Semarang Indonesia Faculty of Public Health Mulawarman Univercity Samarinda Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

This study investigates the impact of feature selection results using the filter method on the performance of predictive models for the nutritional status of children aged 0-23 months. This study aimed to understand how correlation-based feature selection methods affect the efficiency and accuracy of predictive models. The dataset comes from the Basic Health Research survey, which consists of 84 variables and around 130,000 data, including anthropometric, family, socioeconomic, and environmental information. In this study, various filter-based feature selection methods were applied to evaluate and identify features that have significant relationships with children’s nutritional status, both linearly and non-linearly. The mutual information method was used to identify complex relationships between features and target variables, while the Pearson Correlation Coefficient and information gain were used to assess the relevance of numerical and categorical features. Of the 84 variables in the dataset, 37 features were selected after the selection process. The model performance evaluation was carried out using the Random Forest (RF) and Gradient Boosting (GB) algorithms, by comparing the results between the dataset that had been selected and without feature selection. The RF model without feature selection produces accuracy: 0,84600, precision: 0,83958, recall: 0,84600, F1-score: 0,78962, and a computation time of 9 seconds. The GB model without feature selection produces accuracy: 0,86330, precision: 0,84722, recall: 0,86330, F1-score: 0,84925, and a computation time of 2 minutes 50 seconds. After feature selection and cross-validation, the RF model shows accuracy: 0,85701, precision: 0,83599, recall: 0,85701, and F1 score: 0,83484. The GB model shows accuracy at 0,86124, precision at 0,84226, recall at 0,86130, and F1 score at 0,84120.

关键词： Radio frequency Pediatrics Accuracy Correlation Computational modeling Predictive models Aging Feature extraction Prediction algorithms Numerical models

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Reversible data hiding based on pixel segmentation and prediction for improving hiding capacity

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Signal, Image and Video Processing 2024年第6-7期18卷 5043-5059页

作者： Huang, Cheng-Ta Weng, Chi-Yao Zheng, Guo-Ting Weng, Hao-Yu International Bachelor Program in Informatics Yuan Ze University Taoyuan320315 Taiwan Department of Information Management Yuan Ze University Taoyuan320315 Taiwan Department of Computer Science and Information Engineering National Chiayi University Chiayi City600355 Taiwan Department of Computer Science and Artificial Intelligence National Pingtung University Pingtung900391 Taiwan Department of Computer Science and Information Engineering National Central University Taoyuan City320317 Taiwan

The idea of the traditional histogram shifting technique is to hide a message within the cover-image pixel distribution. However, the embedding capacity is limited by the peak point occurrences. To solve this problem, many reversible data hiding (RDH) techniques are developed to combine pixel prediction and histogram shifting to increase the embedding payload. In this paper, a RDH scheme based on chessboard prediction and pixel partitioning is proposed for enhancing the hiding payload. Pixel partitioning is used to separate a pixel into two parts: most significant bit and least significant bit. Then, the chessboard predictor is adopted to generate prediction errors and separate the pixels. Thereafter, histogram shifting is applied to embed the secret messages into prediction errors. Due to the high similarity of adjacent pixels in an image, the generated prediction errors are highly close to zero, resulting in a large embedding space. The experimental results indicate that the proposed method has superior performance in embedding capacity with acceptable image visual quality compared to existing schemes since it adopts the adaptive adjustment strategy to achieve this improved balance. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Pixels

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Current practices, challenges, and opportunities for lifestyle-based market segmentation of older consumers in Thailand

Current practices, challenges, and opportunities for lifesty...

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2023 International Conference on Cyber Management and Engineering, CyMaEn 2023

作者： Yamprayaml, Karuna Choemprayong, Songphan Taiphapoon, Tatri Chulalongkorn University Technopreneurship and Innovation Management Program Bangkok Thailand Chulalongkorn University Faculty of Arts Behavioral Research and Informatics in Social Science Unit Sasin School of Management Department of Library Science Bangkok Thailand Chulalongkorn University Faculty of Communication Arts Bangkok Thailand

ISBN: (纸本)9781665493291

Older consumers' consumption patterns differ from those of other customer groups, affecting many business factors and practices, including product development and service delivery. Acquiring, monitoring, and processing lifestyle and other behavior-oriented data become key activities to gain in-sights about older consumers. While lifestyle patterns have been observed in marketing research for several decades, observing older consumers' lifestyles is still a challenging task and needs further exploration. This study investigates the current practices of marketing researchers and professionals in Thailand in conducting lifestyle-based market segmentation (LMS) as well as related challenges and opportunities. A qualitative in-depth interview approach was employed, with eighteen marketers who have at least ten years of experience. The verbatim data were analyzed by using deductive thematic analysis. As a result, Thai marketers frequently use self-reported questionnaires in offline and online formats, face-to-face interviews with older consumers, telephone surveys, and questionnaires posted on social media sites to collect data for LMS. From the marketers' perspectives, the LMS of older consumers requires abundant resources. It is still perplexing to access data that directly lead to customer insights into the current practices. Additionally, there is a lack of data collection tools tailored to LMS for the older population. Nevertheless, these issues shed some light on specific opportunities to develop more robust and tailored tools and techniques to conduct LMS faster and more efficiently (i.e., getting valid and reliable data while using fewer resources than the current ones). © 2023 IEEE.

关键词： Data acquisition

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