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3rd International Conference on Creative Communication and Innovative Technology, ICCIT 2024

作者： Padeli Lukita, Chandra Fahrurroji Purnama, Suryari Rizky, Agung Fazri, Muhammad Faizal University of Raharja Department of Computer Science Tangerang Indonesia University of Catur Insan Cendekia Department of Management Cirebon Indonesia University of Bina Bangsa Department of Informatics Engineering Serang Indonesia University of Esa Unggul Department of Management Jakarta Indonesia Pandawan Sejahtera Indonesia Department of Informatics Engineering Tangerang Indonesia Bosindo Department of Business Intelligence Tangerang Indonesia

ISBN: (纸本)9798350367492

Gamification, the implementation of game mechanics in non-game settings, is the primary approach driving current advancements in education. Educational gamification has arisen as a possible way to address the issues posed by traditional learning methods, which are generally seen as incompatible with contemporary human features and behavior. Concurrently, blockchain technology has emerged as a highly popular subject and has experienced significant growth in recent years. Blockchain, which has its origins in diverse global communities and companies, serves as an infrastructure technology that is gaining prominence in several industries, such as industry and education. An inherent benefit of blockchain technology is its capacity to function autonomously, eliminating the necessity for third-party involvement and ensuring a heightened level of security, transparency, and integrity. Regrettably, the current body of research on the integration of blockchain technology in the realm of educational gamification remains scarce. Hence, this article seeks to analyze and address the primary challenges associated with education by utilizing educational gamification facilitated by the blockchain system. A mixed-methods approach was employed, involving quantitative surveys and qualitative interviews with 500 participants and 20 key informants. Findings indicate enhanced user engagement and motivation, with increased satisfaction and active participation. The study provides a first gamification model using blockchain, serving as a foundation for future research and development in this field. © 2024 IEEE.

关键词： Decentralized finance

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The Effects of Weather Conditions on Data Transmission in Free Space for Wireless Sensor Networks 3rd

The Effects of Weather Conditions on Data Transmission in Fr...

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3rd International Conference on Computing and Communication Networks, ICCCN 2023

作者： Kadhim, Aqeel A. Naif, Jolan R. Salman, Muna M. Hoomod, Haider K. Computer Techniques Engineering Department Imam AlKadhim University College Baghdad Iraq Informatics Institute for Postgraduate Studies Iraqi Commission for Computers and Informatics Baghdad Iraq Information Technology Directorate Ministry of Science and Technology Baghdad Iraq College of Education Computer Science Department Al-Mustansiriya University Baghdad Iraq

ISBN: (纸本)9789819708918

It is necessary to collect data measured in open lands, whether for example for monitoring purposes or for border protection. The process of data transmission from active nodes and its next level to the cluster head (CH), followed by follow-up to arrive at the base station (BS), with safety and acceptability, are the main objectives of wireless sensor networks (WSNs). The key benefits of wireless systems are low-cost system installation and loss-free data transfer. Weather conditions in the spacious area affect wireless data transmission that is done between sensor nodes in free space. This study attempted to ascertain the influence of atmospheric and meteorological conditions on the loss of data when utilizing the wireless data transmission systems in a wireless sensor network. For this reason, the volume of data transfer losses that happen in free space because of three types of weather conditions is the main discussion point. The meteorological criteria that can be considered in this research are temperature, clear weather, dust, and rain as the weather elements that affect the Iraqi climate. The correlation analysis's outcomes show that the amount of precipitation and the size of raindrops have a main effect on the losses of data transmission. From a practical point of view, there is no confirmed statistical evidence of the amount of loss in the volume of transmitted data as a result of the amount of rainfall with the use of different transmission frequencies. In this research, we designed an objective routing protocol called Fuzzy Clustering with Ant Colony System FCACS, which has been utilized as a simulation program using the MATLAB 2018b application. The practical results of the proposed protocol for data transmission in free space and under different weather conditions were examined, and the simulation results were compared with those of two well-known routing protocols, which are DEEC and Z-SEP. In terms of the quantity of data received from the CH or BS a

关键词： Data transfer

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Database Systems in the Big Data Era: Architectures, Performance, and Open Challenges

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IEEE Access 2025年 13卷 95068-95084页

作者： Elias Dritsas Maria Trigka Department of Informatics and Computer Engineering University of West Attica Egaleo Park Campus Athens Greece

The advent of Big Data has fundamentally transformed the database management systems (DBMS) field, necessitating the development of innovative paradigms, architectures, and technologies to address unprecedented challenges. Despite their historical dominance, traditional systems falter under the high velocity, massive volume, and diverse variety of Big Data. These limitations have catalyzed the emergence of alternative solutions such as not only structured query language (NoSQL), NewSQL, and cloud-native databases, each offering unique approaches to scalability, flexibility, and performance optimization. This survey provides a comprehensive and systematic overview of the evolving database ecosystem in the Big Data era. It delves into the historical progression from traditional relational DBMS (RDBMS) to modern paradigms, emphasizing these transformations’ motivations, trade-offs, and innovations. The classification of databases based on data models, deployment strategies, scalability mechanisms, and consistency models is explored in depth, providing a structured framework for understanding their diverse capabilities. Furthermore, critical performance characteristics, including throughput, latency, fault tolerance, and cost efficiency, are analyzed to assess their effectiveness in real-world applications. By highlighting persistent challenges such as data heterogeneity, security, and interoperability, this survey outlines key research directions, fostering a holistic understanding of the domain and inspiring future advancements in database technologies.

关键词： Databases Scalability Big Data Surveys Data models Database systems Fault tolerant systems Fault tolerance Throughput Relational databases

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Evaluating Machine Learning Techniques for Enhanced Prediction of Building Energy Consumption

Evaluating Machine Learning Techniques for Enhanced Predicti...

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South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

作者： Gerasimos Vonitsanos Andreas Kanavos Phivos Mylonas Computer Engineering and Informatics Department University of Patras Patras Greece Department of Informatics Ionian University Corfu Greece Department of Informatics and Computer Engineering University of West Attica Athens Greece

ISBN: (数字)9798331504489

ISBN: (纸本)9798331504496

Accurate prediction of energy usage is crucial for optimizing resource allocation, enhancing energy efficiency, and reducing environmental impact, pivotal for sustainable development. This study examines electricity consumption in three Cornell University buildings, utilizing advanced machine learning techniques to tackle the challenges of sustainable energy management effectively. We specifically evaluated the performance of Support Vector Machine (SVM), Random Forest, Decision Tree, and K-Nearest Neighbors (KNN) in forecasting electricity usage. Our findings reveal that SVM consistently outperforms the other models across various performance metrics, including accuracy and efficiency. These results provide vital insights into the efficacy of these algorithms in predicting energy consumption, thereby supporting strategic energy management decisions in educational institutions and potentially other similar settings.

关键词： Support vector machines Energy consumption Machine learning algorithms Accuracy Social networking (online) Electricity Buildings Nearest neighbor methods Prediction algorithms Sustainable development

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Sound of Reason: Using AI to build a Digital Twin after the Kanon of Pythagoras in school settings 10

Sound of Reason: Using AI to build a Digital Twin after the ...

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10th IEEE Smart World Congress, SWC 2024

作者： Anthis, Zach Basiakoulis, Alexandros Efstathiou, Kyriakos Efstathiou, Marianna Department of Communication Culture and Media London United Kingdom Aristotle University of Thessaloniki Laboratory for Machine Tools and Manufacturing Engineering Department of Mechanical Engineering Thessaloniki Greece Cyprus University of Technology Digital Heritage Research Lab Department of Electrical Engineering Computer Engineering and Informatics Limassol Cyprus

ISBN: (纸本)9798331520861

This paper presents ongoing work on kanON, an AI-driven EdTech tool designed to foster interactive learning and support Digital Cultural Heritage (DCH) preservation. kanON facilitates the digital reconstruction of the infamous Pythagorean monochord, by allowing users to seamlessly manipulate parameters such as origin (location and epoch), materials, and shape/dimensions. Through the integration of Machine Learning (ML) algorithms, the tool predicts missing archaeological data and generates real-time 3D renderings based on user input, accompanied by corresponding confidence metrics. A mixed-methods (pilot) study was conducted in classroom environments to evaluate its educational impact via quantitative Likert scale assessments and qualitative content analysis of educator feedback. Preliminary results demonstrate high levels of student engagement and reflect positive educator responses, highlighting its potential to enhance the in-class accessibility and understanding of complex historical concepts, as well as to enable the preservation and exploration of cultural artifacts through digital means. Future work will focus on refining kanON and expanding its applicability within both educational and DCH contexts, by introducing the capability of outputting a fully operational digital twin, that integrates mixed reality functionalities. The idea is to enable users to later engage with their (personalized) model dynamically (e.g., readjusting string length and tension), thus allowing them to produce different soundscapes in real-time. This advancement aims to deepen the pedagogical impact by merging tactile interaction with visual and auditory feedback, further enhancing the educational experience via immersive, experiential learning. © 2024 IEEE.

关键词： Adversarial machine learning

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Wireless Sensor Networks: From Fundamentals and Applications to Innovations and Future Trends

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IEEE Access 2025年 13卷 96365-96399页

作者： Maria Trigka Elias Dritsas Department of Informatics and Computer Engineering University of West Attica Egaleo Park Campus Athens Greece

Wireless Sensor Networks (WSNs) have transformed data acquisition and processing across diverse domains such as environmental monitoring, healthcare, and industrial automation. Recent advancements in areas such as federated intelligence, blockchain-based trust mechanisms, and quantum sensing are reshaping the landscape of WSNs. Yet, their full implications for next-generation applications demand deeper exploration. This survey is driven by the need to synthesize these emerging directions through a forward-looking and interdisciplinary lens, highlighting their transformative potential in evolving WSNs into intelligent, autonomous systems. It examines key solutions in energy harvesting, adaptive communication, and edge intelligence, which address persistent constraints like limited energy availability, dynamic topologies, and scalability. Moreover, it highlights the integration of WSNs with disruptive technologies such as the Internet of Things (IoT), artificial intelligence (AI), and digital twins, enabling intelligent, autonomous systems capable of real-time analytics. Critical energy optimization, security, and data management challenges are explored alongside cutting-edge solutions like federated learning (FL), quantum sensing, and blockchain-based trust mechanisms. Future research directions emphasize bio-inspired architectures, hybrid communication in extreme environments, and efficient multi-modal data fusion. This survey serves as a foundational reference for researchers and practitioners seeking to design resilient, intelligent WSN-based systems for the next generation of applications.

关键词： Wireless sensor networks Security Surveys computer architecture Technological innovation Sensors Scalability Protocols Market research Environmental monitoring

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Line Patterns Segmentation in Blurred Images Using Contrast Enhancement and Local Entropy Thresholding

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Journal of computer and Communications 2024年第2期12卷 116-141页

作者： Marios Vlachos Evangelos Dermatas Institute of Communication and Computer Systems Athens Greece Department of Computer Engineering and Informatics University of Patras Patras Greece

Finger vein extraction and recognition hold significance in various applications due to the unique and reliable nature of finger vein patterns. While recently finger vein recognition has gained popularity, there are still challenges associated with extracting and processing finger vein patterns related to image quality, positioning and alignment, skin conditions, security concerns and processing techniques applied. In this paper, a method for robust segmentation of line patterns in strongly blurred images is presented and evaluated in vessel network extraction from infrared images of human fingers. In a four-step process: local normalization of brightness, image enhancement, segmentation and cleaning were involved. A novel image enhancement method was used to re-establish the line patterns from the brightness sum of the independent close-form solutions of the adopted optimization criterion derived in small windows. In the proposed method, the computational resources were reduced significantly compared to the solution derived when the whole image was processed. In the enhanced image, where the concave structures have been sufficiently emphasized, accurate detection of line patterns was obtained by local entropy thresholding. Typical segmentation errors appearing in the binary image were removed using morphological dilation with a line structuring element and morphological filtering with a majority filter to eliminate isolated blobs. The proposed method performs accurate detection of the vessel network in human finger infrared images, as the experimental results show, applied both in real and artificial images and can readily be applied in many image enhancement and segmentation applications.

关键词： Finger Vein Vessel Enhancement Vessel Network Extraction Non-Uniform Images Binarization Morphological Post-Processing

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A Review of Imbalanced Datasets and Resampling Techniques in Network Intrusion Detection System 8

A Review of Imbalanced Datasets and Resampling Techniques in...

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8th International Conference on Information Technology and Digital Applications, ICITDA 2023

作者： Rajasa, Mahesa Cadi Rahma, Fayruz Rachmadi, Reza Fuad Pratomo, Baskoro Adi Purnomo, Mauridhi Hery Institut Teknologi Sepuluh Nopember Department of Electrical Engineering Surabaya Indonesia Universitas Islam Indonesia Department of Informatics Yogyakarta Indonesia Institut Teknologi Sepuluh Nopember Department of Computer Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Informatics Surabaya Indonesia

ISBN: (纸本)9798350344691

The rapid development of network connections and the widespread use of Internet of Things (IoT) devices has increased network traffic. The surge in network traffic has created new vulnerabilities in cyberspace, making it vulnerable to cyber-attacks. To address this challenge, researchers have turned to intelligent techniques, especially machine learning and deep learning, to improve the detection of network traffic attacks. However, a common problem arises: the data imbalance problem, where normal samples occur more often than attack samples, which hurts the performance and classification of machine learning or deep learning models. This study conducted a systematic literature review to identify the imbalanced datasets and the use of resampling techniques for addressing data imbalances in network intrusion detection research. We found four widely-used imbalanced datasets: NSL-KDD, CIC-IDS2017, UNSW-NB15, and KDD-Cup 1999. Researchers used three resampling approaches to tackle the imbalance problem: oversampling, undersampling, and hybrid sampling (combining oversampling and undersampling approaches). Researchers and practitioners can improve the security and efficiency of attack detection across network traffic by applying resampling techniques. © 2023 IEEE.

关键词： Internet of things

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Edge Metric Dimension of Honeycomb and Hexagonal Networks for IoT

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computers, Materials & Continua 2022年第5期71卷 2683-2695页

作者： Sohail Abbas Zahid Raza Nida Siddiqui Faheem Khan Taegkeun Whangbo Department of Computer Science College of Computing and InformaticsUniversity of SharjahSharjah27272UAE Department of Mathematics College of SciencesUniversity of SharjahSharjah27272UAE Artificial Intelligence Lab Department of Computer EngineeringGachon UniversitySeongnam13557Korea

Wireless Sensor Network(WSN)is considered to be one of the fundamental technologies employed in the Internet of things(IoT);hence,enabling diverse applications for carrying out real-time *** navigation in such networks was the main motivation for the introduction of the concept of landmarks.A robot can identify its own location by sending signals to obtain the distances between itself and the *** networks to be a type of graph,this concept was redefined as metric dimension of a graph which is the minimum number of nodes needed to identify all the nodes of the *** idea was extended to the concept of edge metric dimension of a graph G,which is the minimum number of nodes needed in a graph to uniquely identify each edge of the *** plane networks can be easily constructed by repeating regular *** design is of extreme importance as it yields high overall performance;hence,it can be used in various networking and IoT *** honeycomb and the hexagonal networks are two such popular mesh-derived parallel *** this paper,it is proved that the minimum landmarks required for the honeycomb network HC(n),and the hexagonal network HX(n)are 3 and 6 *** bounds for the landmarks required for the hex-derived network HDN1(n)are also proposed.

关键词： Edge metric dimension internet of things wireless sensor network honeycomb network hexagonal network hex-derived networks

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Blockchain and Artificial Intelligence: Enhancing Security and Efficiency in Metaverse Payment Transactions 6th

Blockchain and Artificial Intelligence: Enhancing Security a...

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6th International Conference on Recent Innovations in Computing, ICRIC 2023

作者： Rajawat, Anand Singh Goyal, S.B. Shaari, Rosnizah Bt Verma, Chaman Singh, Pradeep Kumar School of Computer Sciences and Engineering Sandip University Nashik Nashik India City University Petaling Jaya Malaysia City University Petaling Jaya46100 Malaysia Department of Media and Educational Informatics Faculty of Informatics Eötvös Loránd University Budapest1053 Hungary Department of Computer Science and Engineering Central University of Jammu Jammu India

ISBN: (纸本)9789819778614

Blockchain and artificial intelligence (AI) are two revolutionary technologies that are significantly impacting various sectors, including the metaverse. The integration of these technologies is particularly influential in enhancing security and efficiency in metaverse payment transactions. Blockchain, with its decentralized and immutable ledger, provides a secure and transparent way to record transactions. This characteristic is crucial in the metaverse, where digital assets and virtual currencies are frequently exchanged. By leveraging blockchain, metaverse platforms can ensure the integrity and traceability of transactions, reducing the risk of fraud and unauthorized access. On the other hand, AI contributes to the efficiency and intelligence of payment systems. Through machine learning algorithms and data analytics, AI can detect and prevent fraudulent activities, provide personalized recommendations, and automate complex transaction processes. This not only improves the user experience but also enhances the overall security of the system by identifying and mitigating risks in real time. The convergence of blockchain and AI in the metaverse enables the development of more sophisticated and secure payment solutions. These technologies work together to ensure that transactions are not only fast and efficient but also robust against various security threats. This synergy is essential for building trust in the digital economy of the metaverse, encouraging more users and businesses to engage in this emerging virtual space. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blockchain

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