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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Susanto, Ajib Sari, Christy Atika Mulyono, Ibnu Utomo Wahyu Rachmawanto, Eko Hari Setiadi, De Rosal Ignatius Moses Ali, Rabei Raad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia Northern Technical University Department of Computer Engineering Technology Mosul Iraq

ISBN: (纸本)9798350339215

This study examines the decline in the usage of the Javanese language, which has experienced a decrease in the number of speakers from approximately 82 million in 2007 to 68.2 million in 2015. The convergence of the Javanese script and Optical Character Recognition (OCR) technology is proposed as a solution, allowing for the preservation and accessibility of the Javanese script in the digital age. The integration of Convolutional Neural Networks (CNNs) in Javanese script classification achieved a high accuracy rate of 92.95% in identifying positive and negative cases. The dataset used for training consisted of 8440 sample images, which were divided into 20 subfolders for training and testing. The results presented in Table IV demonstrate the successful implementation of the classification model, achieving a 98.87% sensitivity, 100% precision, and 98.88% specificity. This research contributes to the preservation and understanding of the culturally significant Javanese script while addressing the decline in its usage. © 2023 IEEE.

关键词： Convolutional neural networks

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Exact Solution of the Full RMSA Problem in Elastic Optical Networks

IEEE Networking Letters

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IEEE Networking Letters 2024年第1期6卷 55-59页

作者： David, Fabio Rezende, Jose F. De Barbosa, Valmir C. Federal University of Rio de Janeiro Informatics and Computer Science Department Rio de Janeiro21941-914 Brazil Federal University of Rio de Janeiro Systems Engineering and Computer Science Program Centro de Tecnologia Rio de Janeiro21941-914 Brazil

Exact solutions of the Routing, Modulation, and Spectrum Allocation (RMSA) problem in Elastic Optical Networks (EONs), so that the number of admitted demands is maximized while those of regenerators and frequency slots used are minimized, require a complex ILP formulation taking into account frequency-slot continuity and contiguity. We introduce the first such formulation, ending a hiatus of some years since the last ILP formulation for a much simpler RMSA variation was introduced. By exploiting a number of problem and solver specificities, we use the NSFNET topology to illustrate the practicality and importance of obtaining exact solutions. © 2019 IEEE.

关键词： Topology

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Actively Learning Ontologies from LLMs: First Results (Extended Abstract) 37

Actively Learning Ontologies from LLMs: First Results (Exten...

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37th International Workshop on Description Logics, DL 2024

作者： Magnini, Matteo Ozaki, Ana Squarcialupi, Riccardo Department of Computer Science and Engineering University of Bologna Via dell’Università 50 Cesena Italy Department of Informatics University of Oslo Gaustadalléen 23B Oslo Norway Department of Informatics University of Bergen Thormøhlensgate 55 Bergen Norway

In active learning a learner attempts to acquire some kind of knowledge by posing questions to a teacher. Here we consider that the teacher is a language model and study the case in which the knowledge is expressed as an ontology. To evaluate the approach, we present first results testing logical consistency and the performance of GPT and other language models when answering whether concept inclusions from existing EL ontologies are ‘true’ or ‘false’. © 2024 Copyright for this paper by its authors.

关键词： Active learning

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Implementing a Robust and Scalable Detect-and-Avoid Algorithm for UAV Navigation in ROS 15

Implementing a Robust and Scalable Detect-and-Avoid Algorith...

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15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Meimetis, Dimitrios Daramouskas, Ioannis Lappas, Vaios Perikos, Isidoros Kapoulas, Vaggelis Paraskevas, Michael Nkua Department of Aerospace Science & Technology Athens Greece Computer Technology Institute and Press 'Diophantus' Patras Greece UoP Applied Mechanics Lab Patras Greece UoP Computer Engineering and Informatics Department Patras Greece Computer Technology Institute and Press 'Diophantus' University of Peloponnese Electrical and Computer Engineering Dept. Patras Greece

ISBN: (纸本)9798350368833

Unmanned aerial vehicles (UAVs) have garnered significant attention from the research community during the last decade, due to their diverse capabilities and potential applications. One of the most critical functions that drones must execute efficiently is navigation in real-world environments. This paper presents a decentralized approach for enabling unmanned aerial vehicles (UAVs) to navigate safely in unknown environments and avoid obstacles. Leveraging the Optimal Reciprocal Collision Avoidance (ORCA) algorithm, implemented in the Robot Operating System (ROS), our method facilitates conflict detection and resolution in 2D environments. Through simulations using ROS, Gazebo, and Iris drones, we validate the effectiveness of our approach in scenarios with initial trajectory conflicts. Our work addresses the pressing need for UAVs to autonomously plan and execute safe flights, laying the groundwork for enhanced UAV capabilities in various real-world applications. The simulation results demonstrate the efficiency and robustness of our approach. © 2024 IEEE.

关键词： Drones

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Gestures detection and device control in AAL environments using machine learning and BLEs 12

Gestures detection and device control in AAL environments us...

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12th Mediterranean Conference on Embedded Computing, MECO 2023

作者： Spournias, Alexandros Faliagka, Evanthia Skandamis, Theodoros Antonopoulos, Christos Voros, Nikolaos S. Keramidas, Georgios University of the Peloponnese Electrical & Computer Engineering Department Patra Greece School of Informatics Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (纸本)9798350322910

This paper presents a system for detecting gestures and controlling devices in Ambient Assisted Living (AAL) environments using machine learning and Bluetooth Low Energy (BLE) technology. The system consists of two main components: a device equipped with a set of sensors to detect hand gestures via IMU sensor and a BLE-enabled hub that receives the gesture data and controls the lighting of the house. The hub uses machine learning algorithms to recognize hand gestures and transmit the corresponding commands to the devices. The hub, in turn, uses wifi to communicate with the devices and execute the appropriate actions based on the received commands. The proposed system's performance evaluation was carried out through a series of experiments in a AAL environment. The results demonstrate that the system is capable of accurately detecting hand gestures and controlling various devices such as lights, where the model's performance yields successful predictions with an accuracy rate of 90%. The proposed system provides a user-friendly and intuitive way for elderly or people with disabilities to control their environment without the need for complex interfaces or physical buttons. Furthermore, the system can be easily extended to support more gestures and devices, making it a flexible and scalable solution for AAL environments. © 2023 IEEE.

关键词： Gesture recognition

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Supervised Machine Learning Algorithms for the Analysis of Ship Engine Data 16th

Supervised Machine Learning Algorithms for the Analysis of S...

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16th EAI International Conference on Wireless Internet, WiCON 2023

作者： Dimitriou, Theodoros Skondras, Emmanouil Hitiris, Christos Gkola, Cleopatra Papapanagiotou, Ioannis S. Vergados, Dimitrios J. Papapanagiotou, Stavros I. Koumantakis, Stratos Michalas, Angelos Vergados, Dimitrios D. Department of Informatics University of Piraeus Piraeus Greece Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Department of Informatics University of Western Macedonia Kastoria Greece Internet Business Hellas Athens Greece MAS S.A. Athens Greece

ISBN: (纸本)9783031580529

Supervised Machine Learning (ML) algorithms are used for making predictions or decisions based on labeled data. In this paper, an overview about existing supervised ML algorithms is performed. In particular, the algorithms that are studied comprehend the Linear Regression (LR), the Ridge Regression (RR), the Decision Tree (DT), as well as Ensemble algorithms. Subsequently, a comparative analysis of the algorithms is performed using a dataset containing data about ship engines. Effective management of ship engines is important for their robust operation, which can then bring significant economic and environmental benefits. Inferences about the condition of engines and predictions about their performance could prove crucial for specifying optimal cruise parameters, early fault detection and timely service planning. The analysis demonstrates the strength and the weaknesses of each algorithm in terms of predicting decay factors of the ship engine by taking into consideration the data included to the aforementioned dataset. © ICST Institute for computer Sciences, Social informatics and Telecommunications engineering 2024.

关键词： Forecasting

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Evaluating the Utilization of Grammatical Structures of Arabic Language in Hiding Bits

Evaluating the Utilization of Grammatical Structures of Arab...

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2024 Advances in Science and engineering Technology International Conferences, ASET 2024

作者： Rihan, Yazen Altaweel, Ala Khattab, Khattab Kamel, Ibrahim University of Sharjah College of Computing and Informatics Department of Computer Engineering Sharjah United Arab Emirates Ondokuz Mayis University Faculty of Ilahiyat Samsun Turkey

ISBN: (纸本)9798350344134

Nowadays, there is massive volume of data transmitted constantly through digital mediums. This data faces the risks of various cyber-attacks like eavesdropping, traffic analysis, packet injection, and packet dropping. There has been several security mechanisms to secure sensitive data and ensure their confidentiality, integrity, and availability. Indeed, Encryption, which is the process of converting the plain-text data into a non-understandable form known as the cipher-text, can secure the sensitive data. However, Encryption techniques are costly in terms of computational resources. Steganography, on the other hand, attempts to exploit the redundancy in data representation and structure to hide secret information within the data. Text steganography refers to the art of hiding secret information inside long passages of text. This paper proposes a new text steganography technique that exploits grammatical structures of Arabic language. Specifically, the paper exploits the redundancy in the language structure of Arabic grammar. The paper also presents the results of applying the proposed technique on a large dataset of articles from different categories such as politics, sports, and religion. The conducted experiments measure the number of secret bits that can be hidden in 1000 words for each category. The results show that some steganography rules can perform differently when annlied to different categories of text. © 2024 IEEE.

关键词： Data integrity

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Framing Theory on Music Streaming Platforms: How Vocabulary Influences Music Playlist Decision-Making and Expectations

Framing Theory on Music Streaming Platforms: How Vocabulary ...

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2024 ACM International Conference on Intelligent User Interfaces Workshops, IUI-WS 2024

作者： van Bree, Lotte Graus, Mark Ferwerda, Bruce Department of Computer Science and Informatics School of Engineering Jönköping University Jönköping Sweden Human-Centric SARL Paris France

To improve decision-making and prevent information overload, music streaming services try to offer users personalized content. Vocabulary can be an important component in achieving personalization, in addition to recommender systems that ensure users are given access to their musical preferences. One way to apply personalization through vocabulary is to use personal pronouns. However, it is still unclear how the use of vocabulary personalization affects users’ decisions and expectations when it comes to music streaming services. This study aims to explore how vocabulary framing in playlist titles influences decision-making and the content expectations of the music playlist. Despite challenges in making informed vocabulary choices, our results show a substantial impact of personalized vocabulary in playlist titles on user choice and overall expectations. Users distinctly favor playlists with personalized vocabulary, emphasizing their crucial role in enhancing the music streaming experience. © 2024 Copyright for this paper by its authors.

关键词： Decision making

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A Comprehensive Framework for Cold Start Problem in Hybrid Recommendation Systems Extending the Efficient Multi-Mode Approach 27

A Comprehensive Framework for Cold Start Problem in Hybrid R...

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27th International computer Science and engineering Conference, ICSEC 2023

作者： Badriyah, Tessy Ramadhan, Yunaz Gilang Syarif, Iwan Informatics and Computer Engineering Department Kampus PENS JL. Arief Rahman Hakim Sukolilo Surabaya60111 Indonesia

ISBN: (纸本)9798350342109

E-Commerce is a prominent application of information technology in business, offering convenience in transactions. However, as more products and users join the platform, the complexity of E-Commerce systems increases. This necessitates the implementation of a recommendation system to enhance the user experience and address individual preferences. E-Commerce platforms often face the challenge of the cold start problem, where new products are introduced to the platform or when there is limited information available about new users. In such cases, traditional recommendation systems struggle to provide accurate recommendations due to the lack of historical data or user preferences. In this research, a comprehensive framework for an efficient multi-mode Hybrid Recommendation System is proposed, focusing on addressing the cold start problem. The system leverages user behavior tracking, specifically search history and product visit history, to capture user preferences effectively. Through experimental evaluation, the system demonstrates its adaptability to different dataset conditions, achieving a high precision rate of 90%. This research addresses the challenges of data sparsity and the cold start problem in recommendation systems, particularly in the E-Commerce context. The flexibility of the recommendation system ensures optimal recommendations in various scenarios, with potential applications beyond E-Commerce. © 2023 IEEE.

关键词： Recommender systems

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Comparing the Effectiveness of Machine Learning and Deep Learning Techniques for Feature Envy Detection in Software Systems 1

Comparing the Effectiveness of Machine Learning and Deep Lea...

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1st International Conference of Intelligent Methods, Systems and Applications, IMSA 2023

作者： Menshawy, Rana S. Yousef, Ahmed H. Salem, Ashraf Faculty of Engineering Computer and System Department Ain Shams University Cairo Egypt Egypt University of Informatics Cairo Egypt

ISBN: (纸本)9798350335569

Code smells are common in poorly designed software that can hinder code maintainability. Automatic detection of design flaws assists developers in identifying code smells in theirsoftware programs to avoid low-quality delivery. However, the interpretation of code smells is subjective, and existing machine learning-based detection tools are limited in their ability to capture complex semantic relationships in textual code. To address this limitation, the paper proposes a detection system that exploits machine learning and deep learning techniques and compares their effectiveness in identifying the feature envy code smell. The study applies six deep learning techniques based on code semantics features extracted from abstract syntax trees, and eleven machine learning techniques based on code structural features. The results show that both approaches are effective in detecting code smells, with Random Forest achieving exceptional performance among the machine learning classifiers. © 2023 IEEE.

关键词： Deep learning

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