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Empowering Responsible Digital Citizenship Through an Augmented Reality Educational Game 1

3rd International Conference on Novel and Intelligent Digital Systems, NiDS 2023

作者： Iakovidis, Marios Papakostas, Christos Troussas, Christos Sgouropoulou, Cleo Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (数字)9783031441462

ISBN: (纸本)9783031441455

As big data analytics becomes increasingly prevalent, fostering a comprehensive understanding of digital information ownership and responsibility is crucial. This paper presents an educational game that uses mobile augmented reality and a server backend to promote responsible digital citizenship among students. The mobile app uses ArUco markers to locate virtual characters, which represent digital citizens and are role-played by the participants. In the game, students can assign keywords to their characters and create text based on the keywords of nearby characters. The server backend facilitates communication between the characters and sets the interaction range for collecting keywords. The paper details the system’s architecture and a proposed use-case as an educational scenario that employs the game. This educational game holds the potential to equip students with the skills to become conscientious digital citizens and seeks to enhance understanding of data ethics, digital information ownership, and responsible data practices. An initial evaluation of the developed prototype has been performed, yielding encouraging results. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Students

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Mental Health Sentiment Analysis on Social Media TikTok with the Naïve Bayes Algorithm 6

Mental Health Sentiment Analysis on Social Media TikTok with...

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6th International Conference on computer and informatics engineering, IC2IE 2023

作者： Lase, Yuyun Yusnida Lubis, Arif Ridho Elyza, Fauziah Syafli, Sekar Arini Politeknik Negeri Medan Department of Computer Engineering and Informatics Medan Indonesia

ISBN: (纸本)9798350345162

Mental health disorders can affect a person's emotions and behavior and can impact their health and daily activities. The most serious consequence of poor mental health is death by suicide. The problem in this research is about mental health which can be analyzed using the field of natural language processing with the science of sentiment analysis on the developing TikTok platform. Content contained on the TikTok platform will have comments made by fellow users, then these comments are collected for sentiment analysis. This study utilizes a classification algorithm, namely naïve Bayes. The dataset obtained is preprocessed by text first, then the process from TF-IDF will be used to be able to see the appearance of words in the data. The data used in this study is 6300 data. The results of this study are accuracy as measured by a metric evaluation which produces 80.95%. The sentiment in this study focuses on positive and negative sentiments. With visualization, words that often appear are tired, sick, tired, and hurt in negative comments. Meanwhile, the words that often appear in positive comments are able, passionate, strong, and happy. © 2023 IEEE.

关键词： mental health naïve bayes social media tiktok

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Exploring the Use of Augmented Reality in Teaching History to Students with Attention-Deficit Hyperactivity Disorder 3rd

Exploring the Use of Augmented Reality in Teaching History t...

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3rd International Conference on Novel and Intelligent Digital Systems, NiDS 2023

作者： Fraggista, Chrysa Krouska, Akrivi Troussas, Christos Sgouropoulou, Cleo Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (纸本)9783031440960

Augmented reality is an emerging technology that aims to enrich the elements of the real world with virtual information through the use of appropriate devices. These new technological devices, namely smart mobile devices such as smartphones and tablets, can serve as a link between augmented reality and the user. Augmented reality technology has not left the education industry unscathed, attracting the interest of many teachers and researchers, since it is seen as an important, cutting-edge learning and educational tool. Augmented reality provides students with unique learning experiences by supplementing the sensory stimuli of sight and hearing with three-dimensional images, sounds, videos, etc. The purpose of this study is to investigate the effectiveness of augmented reality in high school history classrooms for the teaching of students with attention-deficit hyperactivity disorder (ADHD). The evaluation was conducted with semi-structured interviews with students who have been diagnosed with ADHD, using a questionnaire at the end of the procedure. Qualitative analysis was mainly used to conclude. The method used to carry out this work is the case study. Research findings show that augmented reality technology can make a positive contribution to the learning process. Through the answers of most students, it seemed that they accepted augmented reality and considered it essential for learning better. Furthermore, student behaviors such as attention, engagement and learning motivation showed an improvement. Finally, the educational objectives of this didactic intervention were achieved to a satisfactory degree according to the results of the test. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Augmented reality

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UMUX and UMUX-Lite as Usability Assessment for Smart Door Lock Systems

UMUX and UMUX-Lite as Usability Assessment for Smart Door Lo...

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2023 International Conference on Information Technology and Computing, ICITCOM 2023

作者： Hermawan, Indra Nalawati, Rizki Elisa Oktivasari, Prihatin Iswara, Ratna Widya Politeknik Negeri Jakarta Informatics and Computer Engineering Department Depok Indonesia

ISBN: (纸本)9798350359633

Smart Door Lock System is used to protect priceless and prevent unwanted access to a room. A usability evaluation is required to raise the system's usability level because it will help to decide how acceptable the system is. UMUX, UMUX-Lite, and SUS comparative ratings are used to gauge the usability level. The System Usability Score (SUS) has more questions than the UMUX and UMUX-Lite approaches. The general degree of acceptance of this system was deemed to be acceptable during the system's evaluation period. With an average UMUX score of 68,1, which is in the marginal category, the UMUX-LITe score is 77.3, which is categorized as acceptable, and the SUS comparison score is 73.0, which is categorized as acceptable. © 2023 IEEE.

关键词： Locks (fasteners)

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Multi-type Vehicle Detection and Classification Using YOLOV5

Multi-type Vehicle Detection and Classification Using YOLOV5

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2023 International Conference on informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Liliana, Dewi Yanti Nalawati, Rizki Elisa Iswara, Ratna Widya Pradito, Reza Nova Heryana, Aldy Mochamad Andayani, Gresia Politeknik Negeri Jakarta Department of Computer and Informatics Engineering Depok Indonesia

ISBN: (纸本)9798350307306

In the modern era marked by technological advancement, vehicle recognition using computer vision has become increasingly important. The ability to accurately identify and classify vehicles has far-reaching implications, from efficient traffic management to better road safety. Some research on vehicle classification have been performed, but for multi-type vehicles still needs to be carried out due to the limited efforts on it, especially in vehicles variation, not only on specific vehicle such as cars, but also for two-wheeled and more. The problems of automated vehicle recognition are the variety of vehicle types on the roads;the ability to recognize many vehicles in real-time;as well as the accuracy of classifying vehicles where many obstacles and occlusions appears in the real-world. Hence, this research develops a web-based application that can recognize multi-type vehicles in real-time. The YOLOv5 method is used because of its advantages in fast recognition time and high accuracy, especially for surveillance data. Testing on dataset of multi-type vehicles including cars, trucks, motorcycles, and bicycles gave results with the accuracy rate of 93.23% and F1 score of 0.93. This research contributes to produce a web-based application for fast detecting and classifying multiple types of vehicles with the superior accuracy rate. © 2023 IEEE.

关键词： computer vision

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Blockchain Application in the Waste Trading 7

Blockchain Application in the Waste Trading

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7th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2023

作者： Dana, Ian Rachman Hidayati, Anita Ismail, Iklima Ermis Politeknik Negeri Jakarta Department of Computer and Informatics Engineering Depok Indonesia

ISBN: (纸本)9798350342154

Waste is a complex and severe problem with detrimental environmental impacts if not appropriately managed. The process of buying and selling waste is essential in waste management. With its smart contracts, blockchain allows transactions to be carried out automatically without involving third parties, thereby speeding up the process and increasing efficiency and security. This research applies blockchain to record waste buying and selling transactions. We selected Binance Smart Chain (BSC) as a blockchain platform and Solidity 0.8.0 to build smart contracts containing structures, events, and functions that manage transactions. Autotask connected to the relayer records transactions on the blockchain network without requiring direct intervention from the user. We set up credentials from apiKey and apiSecret to connect to OpenZeppelin Defender, then enter the contract address deployed to the BSC network. After that, we create a variable to accommodate the deployed smart contract's Application Binary Interface (ABI). System testing uses the black box and System Usability Scale (SUS). Of the ten test scenarios in the black box, everything ran smoothly. System testing using SUS resulted in a score of 76 and a Net Promoter Score (NPS) value of 70%. This score indicates that the system is deemed acceptable and included in the good category. This system can guarantee transparency in the waste buying and selling system, hoping to increase accountability and trust in the community. © 2023 IEEE.

关键词： Smart contract

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A Two-Pronged Approach to Security of Discrete-Event Systems

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Journal of Systems Science & Complexity 2025年第1期38卷 178-209页

作者： MATSUI Shoma RUDIE Karen CAI Kai Department of Electrical and Computer Engineering&the Ingenuity Labs Research Institute Queen's UniversityKingston K7L 3N6Canada Department of Core Informatics Osaka Metropolitan UniversityOsaka 545-0051Japan

This paper investigates a security problem of simultaneously addressing two types of attacks:Eavesdropping and *** authors model the target system as a discrete-event system(DES)with subsets of concealable events and protectable events,in order to make the proposed methodology applicable to various practical systems and employ two existing works of DES security:Degree of opacity and state ***,the authors consider that all protectable events are observable,and some observable events are *** addition,protectable events cannot be protected once they are *** such a constraint,the goal is to figure out which events to conceal and which transitions to protect so that the prescribed requirements of degree of opacity and state protection are *** this work the authors decide which events to conceal as all transitions of a given event label are concealed or not *** proposed problem formulation also requires a solution to only involve absolutely necessary protectable events in order for the system to avoid superfluous protection *** authors first examine a general version of our security problem with an intuitive algorithm to compute acceptable solutions,and then present a special version which results in a reduced computation time compared to the general version.

关键词： Degree of opacity discrete-event systems security state protection

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Improving Indonesian Informal to Formal Style Transfer via Pre-Training Unlabelled Augmented Data 6

Improving Indonesian Informal to Formal Style Transfer via P...

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6th International Conference on computer and informatics engineering, IC2IE 2023

作者： Irnawan, Bassamtiano Renaufalgi Adi, Rizky Politeknik Negeri Jakarta Department of Computer and Informatics Engineering Depok Indonesia

ISBN: (纸本)9798350345162

Neural Machine Translation is already used for Indonesian informal to formal style transfer. It works by translating the input language to the target language. In Indonesian informal-to-formal style transfer task, informal sentence work as an input language, and formal sentence is the target the model needs to translate to. Currently, the STIF parallel dataset is the only manually labelled informal-to-formal dataset. We need sufficient data to achieve a good model for style transfer performance. In contrast, the current Indonesian informal to formal dataset is insufficient. We adopted the pre-train augmentation architecture introduced by work done in GEC tasks to elevate the Low-Resource data. We create the augmented dataset with a simpler word replacement approach. We benchmark several transformer-based pre-trained model architectures, including BART, GPT2, and BERT Encoder Decoder. We train the augmented dataset to all models as a pre-trained model and fine-tune it with the STIF dataset. We perform the sacreBLEU benchmarking techniques to find which approach with better style transfer quality. The result is the BART model that was pre-trained with an augmented dataset and fine-tuned with the STIF dataset with a score of sacreBLEU 53,19. © 2023 IEEE.

关键词： Indonesia machine translation natural language processing pre-train semi-supervised style-transfer

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Comparative Analysis of Brain Waves for EEG-Based Depression Detection in the Prefrontal Cortex Lobe using LSTM 7

Comparative Analysis of Brain Waves for EEG-Based Depression...

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7th International Conference on New Media Studies, CONMEDIA 2023

作者： Pratiwi, Monica Universitas Multimedia Nusantara Faculty of Engineering and Informatics Department of Computer Engineering Tangerang Indonesia

ISBN: (纸本)9798350307504

Global anxiety and depression have become 25% more prevalent, with teenagers and women being the most affected. Approximately 280 million people suffer from depression. Doctors and psychologists are able to diagnose depressive disorders through counselling sessions and ask relevant questions to the subject, despite being vulnerable to mistakes due to the examiner's lack of experience. Therefore, automated depression detection development is necessary to validate doctor and psychiatrist assessment. Electroencephalography (EEG) is considered to be a popular option for the detection and investigation of various mental disorders. In this study, a comparison and analysis of each existing brain wave is carried out, namely Alpha (8-12Hz), Beta (13-30Hz), Theta (4-8 Hz), Delta (0.5-4 Hz) and Gamma (30-50Hz). From each wave, an accuracy testing is carried out for three groups of features: linear features, nonlinear features, and a combination of linear and nonlinear features. The given results demonstrate that the combination of linear and nonlinear data consistently yields the highest accuracy outcomes across all waves. Also, the combination of theta waves and linear nonlinear features contributed the highest accuracy (84%) using LSTM as the classifier. © 2023 IEEE.

关键词： Electroencephalography

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Deep Learning Quantitative Susceptibility Mapping With Reduced Training Time Based on Local Field Transformation

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IEEE Transactions on Emerging Topics in Computational Intelligence 2025年第2期9卷 1527-1538页

作者： Wu, Ming-Long Huang, De-Rong Cheng, Jhih-Shan National Cheng Kung University Department of Computer Science and Information Engineering Tainan701 Taiwan National Cheng Kung University Institute of Medical Informatics Tainan701 Taiwan

A quantitative susceptibility mapping (QSM) approach using single-orientation imaging data is proposed in this study. The proposed method generates local field maps at five predefined orientations via deep learning from single-orientation local field maps, followed by physical dipole inversion using the analytical Calculation of Susceptibility through Multiple Orientation Sampling (COSMOS) algorithm. We termed the method pseudo COSMOS (pCOSMOS). By isolating the physical dipole inversion process from deep learning, training of the neural network model becomes greatly accelerated. Brain imaging data from 10 healthy subjects (7 training and 3 testing) acquired at 3T with five different orientations relative to the main magnetic field were included to evaluate the reconstruction quality. Results compared against two iterative (Morphology Enabled Dipole Inversion or MEDI, and Structural Feature-based Collaborative Reconstruction or SFCR) and two deep learning QSM approaches (QSMnet and Learned Proximal Convolutional Neural Network or LPCNN) using COSMOS as the reference standard revealed that the susceptibility maps obtained from pCOSMOS yielded global quantitative performance comparable to QSMnet and LPCNN, while being prominently superior to MEDI and SFCR. Estimation errors in magnetic susceptibility were between 0.01 and 0.02 ppm voxel-wise, and 0.006 ± 0.004 ppm for five selected gray matter areas. Visual inspection further suggested better preserved tissue boundaries in pCOSMOS than QSMnet and LPCNN. Training time was reduced from 2 days for LPCNN and 12 hours for QSMnet to 3.2 hours for pCOSMOS. It is concluded that the proposed pCOSMOS method is an alternative deep learning QSM approach when computational efficiency is essential. © 2017 IEEE.

关键词： Brain mapping

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