检索结果-内蒙古大学图书馆

IEEE Education engineering (EDUCON)

作者： Gerasimos Vonitsanos Ioanna Moustaka Spyridon Doukakis 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)9798350394023

ISBN: (纸本)9798350394030

The education sector, a cornerstone for social and economic development, has seen minimal transformation despite technological advancements. The shift towards digital evolution in adult education and lifelong learning is imperative for societal progress. Utilizing digital tools enhances learning experiences and employment prospects, crucial for attracting skilled workers in a flexible work environment. Modern digital technologies contribute to global competitiveness, fostering social cohesion and improving the quality of teaching. The 21st-century education revolution emphasizes internet-based pedagogy, bridging formal and experiential learning through technology. Lifelong learning, essential for skills enhancement, gains significance with emerging technologies, thus reducing barriers to access while promoting inclusiveness. Digital platforms, e-learning, and innovative methods revolutionize adult education beyond dispute, transcending traditional classrooms into engaging learning environments. The global “right to quality and inclusive education” is therefore facilitated by digital technology, offering flexibility, accessibility, and adaptability. Expanding beyond conventional classrooms nurtures inclusive and effective adult education, thereby propelling overall progress. The education landscape evolves, emphasizing on remote learning, interdisciplinary collaboration, and the acquisition of digital skills to meet the demands of a dynamic future job market.

关键词： Economics Electronic learning Distance learning Employment Collaboration Propulsion engineering education

来源：评论

学校读者我要写书评

暂无评论

Designing Quantum-Resilient Blockchain Frameworks: Enhancing Transactional Security with Quantum Algorithms in Decentralized Ledgers

引用

International Journal of Advanced computer Science and Applications 2025年第4期16卷 618-628页

作者： Kale, Meenal R. Baker El-Ebiary, Yousef A. Sathiya, L. Burugari, Vijay Kumar Yulduz, Erkiniy Muniyandy, Elangovan Alanazi, Rakan Department of Humanities Yeshwantrao Chavan College of Engineering Hingna Nagpur India Faculty of Informatics and Computing UniSZA University Malaysia Department of CSE Panimalar Engineering College Chennai India Dept of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan Department of Information Technology Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia

Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secure blockchain like Rivest–Shamir–Adleman (RSA), Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm 256-bit (SHA256) are the characteristic of the traditional cryptographic techniques vulnerable to attack by quantum algorithms: Shor’s and Grover’s algorithms: can efficiently break asymmetric encryption and speed up brute force attacks. Because of this vulnerability, there exists a need to develop an advance quantum resilient blockchain framework to protect the decentralized ledgers from the future threats of the quantum. This research proposes Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD) and Quantum Random Number Generation (QRNG) as a formidable architectural integration, to fortify security of blockchain. Classical encryption is replaced with PQC, QKD with secure key exchange by detecting eavesdropping, and QRNG with improving cryptographic randomness to remove the predictable key vulnerability. Only with a small loss of transaction efficiency, we increase transaction encryption accuracy, key exchange security, and resistance to quantum attacks. In this quantum enhanced blockchain design, the idea is to preserve the decentralization, transparency and security and at the same time overcome the future quantum threat. By going through rigorous analysis and comparative evaluation, we demonstrate that the approach saves blockchain networks from the emerging quantum risks to make sure that the decentralized finance, smart contracts and cross chain transactions. © (2025), (Science and Information Organization). All rights reserved.

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Analysis of Gamification and Blockchain Integration in Intelligent Learning Systems 3

Analysis of Gamification and Blockchain Integration in Intel...

引用

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

来源：评论

学校读者我要写书评

暂无评论

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...

引用

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

来源：评论

学校读者我要写书评

暂无评论

Evaluating Machine Learning Techniques for Enhanced Prediction of Building Energy Consumption

Evaluating Machine Learning Techniques for Enhanced Predicti...

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

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 ...

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：