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6th international conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Pratama, Galih Dea Soeparno, Haryono Arifin, Yulyani Gaol, Ford Lumban Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798331539603

Mental health is one of the states of well-being which enables people to cope with various things in everyday life. Despite that, mental health is often overlooked, driving the emergence of numerous mental disorders on people. Along the presence of technological advancements, there is serious game which is utilized to entertain and achieve non-game goals related to real-life issues. Due to that, serious game can be leveraged as a media put into health sectors, particularly in presenting fun therapy to people diagnosed with mental disorders. this research presents systematic literature review on publications discussing the utilization of serious game in providing fun therapy for people with mental disorders, focusing on matters like the mental disorders emphasized within, the game elements presented in each publication, and ways to evaluate the serious game. the result indicates overall well-received responses regarding the usage of serious game in serving the purpose, albeit with different ways on evaluation process based on the mental disorders each publication addressed for. © 2024 IEEE.

关键词： Serious games

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Enhancing Electronic Document Security with Lightweight Digital Signature 6

Enhancing Electronic Document Security with Lightweight Digi...

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6th IEEE international conference on Artificial Intelligence in Engineering and Technology, IICAIET 2024

作者： fun, Tan Soo Ahmad Zulkifli, Nur Sufia Binti Sia, Florence Hung, Lai Po Universiti Malaysia Sabah Cybersecurity Research Lab Faculty of Computing and Informatics Sabah Kota Kinabalu Malaysia Universiti Malaysia Sabah Creative Advanced Machine Intelligence Research Centre Faculty of Computing and Informatics Sabah Kota Kinabalu Malaysia

ISBN: (纸本)9798350389692

the heightened frequency and ferocity of recent security breaches and electronic document falsification pose significant concerns globally. these incidents underscore the critical need for robust security measures to protect sensitive documents from unauthorized access and tampering. While digital signatures are essential for ensuring the authenticity and integrity of electronic documents, traditional digital signature algorithms can be computationally intensive, making them unsuitable for resource-constrained environments such as IoT devices and mobile applications. this paper explores lightweight digital signature algorithms that offer robust security with minimal resource consumption. We investigate, implement, and evaluate the performance evaluation of lightweight digital signatures, highlighting their efficiency in both signature generation and verification processes. Our findings demonstrate that these algorithms can significantly enhance the security of electronic documents without compromising performance. © 2024 IEEE.

关键词： Electronic document identification systems

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User Authentication with Keystroke Dynamics: Performance Evaluation in Neural Network 6

User Authentication with Keystroke Dynamics: Performance Eva...

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6th IEEE international conference on Artificial Intelligence in Engineering and Technology, IICAIET 2024

作者： Kek, Xin-Jin Leau, Yu-Beng Tan, Soo fun Cybersecurity Research Lab Faculty of Computing and Informatics Universiti Malaysia Sabah Sabah Malaysia Creative Advanced Machine Intelligence Research Centre Faculty of Computing and Informatics Universiti Malaysia Sabah Sabah Malaysia

ISBN: (纸本)9798350389692

In the current context of research, it investigates user authentication through keystroke dynamics using the neural network model which focuses on Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU) and Long Short-Term (LSTM). As of above, four distinct experiments were conducted: (1) evaluating 3 different algorithms, (2) layering configuration for CNN and GRU fusion, (3) number of filters and neurons as hyperparameters, (4) assessing combinations of events counts and classes. In justification, the final outcome demonstrates an achieved accuracy of 87%. Based on the experiments that were carried out, optimal hyperparameters were identified: window size of 40, 256 for the number of filters and neurons and 2500 as the optimal number of events with 30 as the number of classes. these findings underscore a significance of considering diverse combinations of a number of events and classes by providing insights into the determination of optimal hyperparameters for keystroke dynamics in performance evaluation. © 2024 IEEE.

关键词： Convolutional neural networks

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the Pedagogy Gamification Design for fun Engagement 6

The Pedagogy Gamification Design for Fun Engagement

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6th international conference on Information Technology, InCIT 2022

作者： Inchamnan, Wilawan Yampray, Karuna Niranatlamphong, Winyu Imsombut, Aurawan Dhurakij Pundit University College of Creative Design and Entertainment Technology Bangkok Thailand Kasetsart University Faculty of Science Bangkok Thailand

ISBN: (纸本)9781665489126

this study aims to develop an educational gamification design method. It focuses on how gamification elements can influence student engagement to improve learning processes. Pedagogy is the design of the processes of learning activities as 'knowledge processes': experiencing, conceptualizing, analyzing, and applying. the design of pedagogical activities is based on fun theory. fun theory analyzes the learner's path, skills, and feelings in learning. the results show the relationship between gamification elements and fun activities in the classroom. © 2022 IEEE.

关键词： Design

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Optimized Convolutional Neural Network Using Genetic Algorithm for Music Genre Classification 6

Optimized Convolutional Neural Network Using Genetic Algorit...

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6th IEEE international conference on Artificial Intelligence in Engineering and Technology, IICAIET 2024

作者： Yumil, Hana Magdelina Sia, Florence fun, Tan Soo Hung, Lai Po Creative Advanced Machine Intelligence Research Center Faculty of Computing and Informatic Universiti Malaysia Sabah Malaysia

ISBN: (纸本)9798350389692

Music genre classification plays an important role in identifying and classifying music tracks into genre. Due to the enormous number of genres available nowadays, music genre classification has been automated through analyzing the features of audio files of music by using machine learning specifically the Convolutional Neural Network (CNN) method. However, the hyperparameter values of CNN has not yet been optimized to ensure accurate classification. It has been found that the classification effectiveness of CNN can be further enhanced with the right setting of hyperparameter in many different domains. Hence, this paper proposes to optimize the hyperparameter setting of CNN by using Genetic Algorithm (GA) for music genre classification. the hyperparameter includes learning rate, batch size, and number of epoch. Experiments have been conducted to assess the effectiveness of the optimized CNN algorithm by comparing it to a baseline CNN method on music genre dataset. the results show that the optimized CNN can classify music genre well. © 2024 IEEE.

关键词： Convolutional neural networks

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Enhanced Authentication Protocol for Securing Internet of Medical things with Lightweight Post-Quantum Cryptography 6

Enhanced Authentication Protocol for Securing Internet of Me...

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6th IEEE international conference on Artificial Intelligence in Engineering and Technology, IICAIET 2024

作者： Man Lo, Chris Ka Tan, Soo fun Chung, Gwo Chin Universiti Malaysia Sabah Cybersecurity Research Lab Faculty of Computing and Informatics Sabah Kota Kinabalu Malaysia Universiti Malaysia Sabah Creative Advanced Machine Intelligence Research Centre Faculty of Computing and Informatics Sabah Kota Kinabalu Malaysia Multimedia University Faculty of Enginerering Cyberjaya Malaysia

ISBN: (纸本)9798350389692

As the healthcare sector transitions to the Internet of Medical things (IoMT), it promises significant improvements in productivity by streamlining processes, reducing administrative burdens, and automating routine tasks. However, the current authentication methods are vulnerable due to reliance on simple passwords and a lack of additional protective layers, posing a heightened risk of data breaches. Given the significant value of medical data, security measures for medical devices remain inadequate, especially in safeguarding user and device identities against future quantum computing threats. this paper proposes an enhanced authentication protocol aimed at ensuring the confidentiality and integrity of medical data. the protocol validates user and device identities while incorporating post-quantum cryptography to address upcoming challenges posed by quantum technology. © 2024 IEEE.

关键词： Quantum computers

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fun with fun 11

Fun with FUN

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11th international conference on fun with algorithms, fun 2022

作者： Mathieu, Fabien Tixeuil, Sébastien Swapcard Paris France Sorbonne Université CNRS LIP6 Paris France

ISBN: (纸本)9783959772327

the notions of scientific community and research field are central elements for researchers and the articles they publish. We propose to explore the evolution of the fun conference community since its creation from the articles listed in DBLP, authors, program committees, and advertised themes, by means of a novel symmetric embedding, and carefully crafted software tools. Our results make it possible on the one hand to better understand the evolution of the community, and on the other hand to easily integrate new themes or researchers during future editions. © Fabien Mathieu and Sébastien Tixeuil.

关键词： Natural language processing systems

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Planning and Optimization of Indoor Climbing Routes 6

Planning and Optimization of Indoor Climbing Routes

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6th international conference on Information Technologies and Electrical Engineering, ICITEE 2023

作者： Chao, Hucheng School of International Education Wuhan University of Technology Wuhan China

ISBN: (纸本)9798400708299

Indoor rock climbing, as a challenging and fun sport, has become more and more popular among sports enthusiasts in recent years, and in order to successfully complete the climb, it is necessary to select suitable routes and evaluate the difficulty of the routes. this study focuses on rock climbing route planning, evaluation and optimization. Canny edge detection is used to preprocess the image to obtain the coordinates of the rock point locations, K-means clustering is used to classify the rock points based on the rock point location-based model, DFS algorithm is used for data analysis, and multiple linear regression modelling is used to optimize the climbing routes using the A∗algorithm by taking into account a number of key variables, including the weather, the temperature, and the density of the rock points, and to determine the best climbing route profile.. © 2023 ACM.

关键词： Multiple linear regression

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Superficial Wound Classification Using CNN Image Classifier for Initial Wound Care 6

Superficial Wound Classification Using CNN Image Classifier ...

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6th IEEE international conference on Artificial Intelligence in Engineering and Technology, IICAIET 2024

作者： Ambo'miri, Sitti Wan Fazirah Hung, Lai Po Sze, Florence Sia Fui fun, Tan Soo Universiti Malaysia Sabah Faculty of Computing and Informatics Sabah Malaysia

ISBN: (纸本)9798350389692

Proper diagnosis of the types of wounds is the first step in effective wound management. Healthcare quality can be improved with the use of artificial intelligence technology. In this project, convolutional neural network (CNN) models are employed for superficial wound image classification. the goal of this project is to implement carefully selected CNN models with fine-tuned parameters (batch sizes, augmentation parameters and epoch size) to categorize superficial wounds of abrasion, bruise and superficial skin burns. the library and functions from TensorFlow, Keras, MatplotLib and OpenCv will be used alongside the Python programming language to create this project in a Google Colaboratory notebook, also widely known as Colab. this work evaluates the CNN models of VGG-16, InceptionV3 and ResNet-50 to find out which best classifies the dataset of non-fatal superficial wounds. these models have significant differences especially in their number of layers and concepts of capturing the features of images input. By utilizing these models, the accuracy rate of more than 40% is observed after models being trained and validated on 90% of the dataset (80% for training and 20 for validation), then tested and prediction with the remaining 10% of the dataset for classification report and confusion matrix generation. Out of 3 CNN models used in this study, it is observed that InceptionV3 model's highest accuracy is 44% while both ResNet50 and VGG-16 model achieved 45% accuracy against the superficial wound database (non-fatal wound). © 2024 IEEE.

关键词： Convolutional neural networks

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the Documentation of the 6th Progressive and fun Education international conference

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AIP conference Proceedings 2021年第1期2438卷

the Documentation of the 6th Progressive and fun Education international conference, AIP conference Proceedings, Volume 2438, Issue 1, 27 October 2021, 010002,

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