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IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Nobuyuki Umezu Hideki Bando Dept. of Computer and Information Sciences Ibaraki University Hitachi Japan Dept. of Mechanical Systems Engineering Ibaraki University Hitachi Japan

ISBN: (数字)9798331521578

ISBN: (纸本)9798331521585

This paper introduces Augmented Karuta, an interactive floor projection experience inspired by traditional Japanese playing cards, known as ‘Karuta’. Designed to engage users and stimulate interest in local cultures, history, and traditions, the system utilizes three projectors. Two projectors project 46 “grabbing” cards onto the floor screen of 4.1 x 3.7 (m), while the third displays a corresponding “reading” card on a wall screen. Each matching pair of cards shares a poem or sentence that begins with one of the Japanese phonograms. During a session, users actively engage by stepping onto the projected ‘grabbing’ card that matches the ‘reading’ card displayed on the wall, effectively blending physical movement with cognitive skills to find the correct match. By integrating a two-dimensional LiDAR sensor, the system tracks the user's position on the interactive floor. This tracking is vital for the proposed system to immediately respond to the user's actions, ensuring an immersive and seamless interaction with the digital karutas on the floor. We conducted evaluation experiments at two museums, gathering positive feedback from 57 participants. Future work will focus on quantitatively evaluating the system's impact on learning effectiveness.

关键词： Laser radar Tracking Virtual reality Learning (artificial intelligence) Museums History Floors

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Iterative Detection Schemes for Uplink Highly Loaded User-Centric Hybrid Beamforming Based Frequency Selective Massive MIMO Networks

TechRxiv

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TechRxiv 2024年

作者： Karatas, Metehan Guvensen, Gokhan Muzaffer Dept. of Information Technology Division of Computer Systems Uppsala University Sweden Ankara Turkey

In cell-free (CF) networks, access points (APs) jointly serve the user equipments (UEs). In user-centric (UC) variant, only a handful of APs serve a particular UE, namely the ones with the best channels. In this paper, we propose a hybrid beamforming aided uplink receiver scheme for highly loaded UC massive MIMO (mMIMO) networks, operating in millimeter-wave(mmWave) frequencies, employing single carrier modulation under frequency selective channels. Every AP employs its own analog beamformer (AB) called the modified eigen-beamformer (MEB), which promotes a trend of fairness. In the digital domain, two detectors are proposed;Cell-Free Iterative Detector (CFI-D) and User-Centric Iterative Subset-Detector (UCIS-D). CFI-D introduces the iterative block decision feedback equalization (IBDFE) method for CF networks. UCIS-D is an alternative to CFI-D. UCIS-D is UC, has low computational complexity (CCP) and is scalable. UCIS-D relies on parallel interference cancellation (PIC) aided IB-DFE. Interfering UEs are divided into three sets. Weak interferers are processed with PIC, strong interferers with IBDFE which considers the residual interference from PIC. Weakest interferers are ignored. Both PIC and IB-DFE utilize the soft decisions from previous iterations. Simulation results show that these receivers can handle ultra high loads in terms of bit-error-rate (BER) and achievable information rate (AIR). © 2024, CC BY-NC-SA.

关键词： Decision feedback equalizers

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Harnessing Big Data for Economic Transformation in a Digitalized World

Harnessing Big Data for Economic Transformation in a Digital...

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Riswan Efendi Tarigan Triyono Mahyuni Harry Agustian Rifky Nurfaizi Achani Rahmania Az Zahra Dept. of Information Systems Pelita Harapan University Tangerang Indonesia Dept. of Information Technology University of Raharja Tangerang Indonesia Dept. of Teacher Training and Education Science University of Mataram Mataram Indonesia Dept. of Computer Systems Sesindo Tangerang Indonesia Dept. of Information Technology Bosindo Tangerang Indonesia Dept. of Information Systems Pandawan Sejahtera Indonesia Tangerang Indonesia

ISBN: (数字)9798350367492

ISBN: (纸本)9798350367508

Air is essential to life and health, with oxygen (20.94%) and the ozone layer protecting against ultraviolet radiation. Depletion of oxygen reduces the ozone layer, increasing UV exposure. Good air quality is crucial for living organisms. In 2022, Indonesia’s PM 2.5 pollution ranked 26th worst globally, exceeding WHO standards, yet awareness and trust in air quality devices remain low. This study aims to implement and evaluate an AI-based machine learning system to predict the Air Quality Index (AQI) in healthcare services. Using Structural Equation Modeling with Partial Least Square analysis via SmartPLS 4.0, the research involves 120 participants and historical air quality data. Comparative analysis of machine learning algorithms assesses accuracy, robustness, and efficiency, highlighting their potential in forecasting AQI and its implications for public health and urban planning. The study demonstrates the effectiveness of these algorithms in predicting AQI, with a significant value of 0.874 for forecasting accuracy.

关键词： Machine learning algorithms Accuracy Urban planning Loading Air quality Mathematical models Indexes Forecasting Public healthcare Uninterruptible power systems

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Harmonizing open banking in the European Union: an analysis of PSD2 compliance and interrelation with cybersecurity frameworks and standards

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International Cybersecurity Law Review 2024年第1期5卷 79-120页

作者： Gounari, Marianna Stergiopoulos, George Pipyros, Kosmas Gritzalis, Dimitris Dept. of Information & Communication Systems Engineering University of the Aegean Samos Greece Dept. of Computer Science Philips University Nicosia Cyprus Dept. of Informatics Athens University of Economics & Business Athens Greece

This paper focuses on the security protocols enacted in banking transactions across the European Economic Area (EEA), as stipulated by the Second or Revised Payment Service Directive (commonly referred to as ‘PSD2’ or simply ‘the Directive’). The study aims to comprehensively analyse the implementation and efficacy of these security measures within the specified jurisdiction. The Directive incorporates fundamental rights and obligations that all stakeholders are compelled to adhere to and delineates specific security measures and standards that both traditional banking institutions and third-party providers (TPP) are mandated to implement. In particular, one of the cardinal mandates for banking and financial institutions under PSD2 is the obligation to facilitate third-party access to customer data via open application programming interfaces (API). While this open banking paradigm and the consequent proliferation of data sharing unquestionably bring about various advantages, such as enhanced consumer choice and market competition, they concurrently expose the financial ecosystem to a slew of potential security vulnerabilities and privacy risks. Upon conducting a comprehensive review of the security requirements and measures stipulated under PSD2 and a comparative analysis with essential cybersecurity frameworks and standards (NIS2, Cybersecurity Act, GDPR, ISO 27001:22 and PCI DSS), we have ascertained a discernible lack of harmonisation and clarity concerning the technical security specifications for its effective implementation. This lacuna substantiates the challenges banks face in fully grasping the extensive spectrum of compliance obligations mandated by PSD2. The aim of this research is to offer a valuable contribution to both the comprehension and the pragmatic deployment of security standards in the context of banking transactions, as regulated by the PSD2. The paper serves as a valuable resource for traditional banking institut

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Efficient Blind Channel Estimation for IRS-Assisted Joint Communication and Sensing in 6G Networks

Efficient Blind Channel Estimation for IRS-Assisted Joint Co...

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2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024

作者： Siddig, Ali A. Al-Dweik, Arafat Iraqi, Youssef Pandey, Anshul Giacalone, Jean-Pierre Hamila, Ridha Al-Rimawi, Ashraf Khalifa University of Science and Technology Dept. of Computer and Information Eng. PO Box 127788 Abu Dhabi United Arab Emirates Mohammed VI Polytechnic College of Computing Benguerir Morocco Secure Systems Research Center Abu Dhabi United Arab Emirates Qatar University Dept. of Electrical Eng. Doha Qatar Birzeit University Dept. of Electrical and Computer Eng. Birzeit Palestine

ISBN: (纸本)9798350376715

To achieve the ultimate performance of intelligent reflecting surface (IRS), an accurate channel estimation is required, which in turns induces significant signaling overhead. This work presents a novel blind channel estimation scheme for IRS-assisted heterogeneous communications and sensing networks. The proposed scheme consists of two transmission stages, one for sensing and the other for communications. By noting that the sensing information have generally less stringent quality of service (QoS) requirements, the sensing stage is used for joint blind sensing data detection and blind channel estimation for the subsequent communications stage. Channel estimation is achieved using a specific frame structure where the modulated sensing symbols cooperate to estimate the channel coefficients for all IRS reflecting elements blindly and jointly. The simulation results obtained show that the proposed blind channel estimation accuracy is comparable to pilot-based schemes. © 2024 IEEE.

关键词： Channel estimation

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Real-Time Defogging using Dark Channel Prior for Enhanced Visibility

Real-Time Defogging using Dark Channel Prior for Enhanced Vi...

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Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE), International Conference on

作者： Zohaib Mushtaq Obaid Ur Rehman Usman Ali Muhammad A. Latif Dept. of Electrical Electronics and Computer systems University of Sargodha Sargodha Pakistan Dept. of Computer and Information System Cleveland State University OH USA

ISBN: (数字)9798331504861

ISBN: (纸本)9798331504878

The presence of fog is a notable obstacle for capturing images, particularly in the early morning hours. The diminished sight impedes the capacity to get distinct and comprehensive information from the surroundings. In order to tackle this issue, a rapid and live vision-based dehazing method is suggested. The objective of the technology is to dissipate the fog and enhance visual acuity. It does this by implementing four steps: using an exponential moving average filter to diminish the impact of noise and enhance clarity, preprocessing the filtered frames, detecting fog with the Gaussian blur technique, and applying the dark channel prior approach to achieve optimum contrast and remove fog. Comprehensive testing were carried out on live recordings to showcase the system's ability to significantly improve sight in different foggy situations. This technique demonstrates the superior performance in terms of following parameters like, an accuracy, precision, recall, and F1 score compared to previous investigations. Our methodology achieved the greatest accuracy when compared to state-of-the-art transfer learning convolutional neural networks.

关键词： Visualization Accuracy Transfer learning Noise Streaming media information filters Real-time systems Recording Remote sensing Testing

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Effective Connectivity of EEG Signals in Diagnosing Alcohol Use Disorder: A Machine Learning Approach 7

Effective Connectivity of EEG Signals in Diagnosing Alcohol ...

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7th IEEE International Conference on Electrical, Electronics, and System Engineering, ICEESE 2024

作者： Radzi, Noor'Izni Zafirah Mohd Yahya, Norashikin Nazri, Ainul Khairiyah Mohd Badruddin, Nasreen Khan, Danish M. Kamel, Nidal S. Electrical & Electronics Eng. Dept. Universiti Teknologi PETRONAS Perak Malaysia Maintenance Department PETRONAS Gas Berhad Terengganu Malaysia Dept. of Computing & Information Systems Sunway University Selangor Malaysia College of Eng. & Computer Sc. VinUniversity Hanoi Viet Nam

ISBN: (纸本)9798350367447

Alcohol consumption significantly impacts public health. Excessive drinking harms physical and emotional well-being, lifestyle, and social behavior, and chronic abuse alters brain structure, leading to Alcohol Use Disorder (AUD). AUD, characterized by persistent drinking and poor impulse control, is associated with neurotransmitter and metabolic changes in the brain. Diagnosis is based on DSM-5 criteria and subjective methods like surveys and psychiatric examinations, but EEG can help predict relapse and treatment effectiveness. This study aims to develop a precise method for detecting AUD using Directed Transfer Function (DTF) and Partial Directed Coherence (PDC) algorithms as input to machine learning model. The EEG dataset comprises 30 AUD and 30 healthy control subjects. The study evaluates the accuracy, sensitivity, and precision of the algorithms, with preprocessing of EEG signals from 19 channels and analysis using DTF and PDC. The data are transformed into 19×19 adjacency matrices across 64 frequency bands. The PDC method achieved higher accuracy (94.5%) compared to DTF (89.8%). © 2024 IEEE.

关键词： AUD Directed Transfer Function (DTF) Effective Connectivity Partial Direct Coherence (PDC)

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Blockchain-Enhanced Framework for Secure Third-Party Vendor Risk Management and Vigilant Security Controls

Blockchain-Enhanced Framework for Secure Third-Party Vendor ...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Gupta, Deepti Elluri, Lavanya Jain, Avi Moni, Shafika Showkat Aslan, Omer Texas A&m University - Central Texas Dept. of Computer Information Systems TX United States College of Business University of Tampa FL United States Embry-Riddle Aeronautical University Dept. of Electrical Engineering and Computer Science FL United States Bandirma Onyedi Eylül University Department of Software Engineering Bandirma Turkey

ISBN: (纸本)9798350362480

In an era of heightened digital interconnectedness, businesses increasingly rely on third-party vendors to enhance their operational capabilities. However, this growing dependency introduces significant security risks, making it crucial to develop a robust framework to mitigate potential vulnerabilities. This paper proposes a comprehensive secure framework for managing third-party vendor risk, integrating blockchain technology to ensure transparency, traceability, and immutability in vendor assessments and interactions. By leveraging blockchain, the framework enhances the integrity of vendor security audits, ensuring that vendor assessments remain up-to-date and tamperproof. This proposed framework leverages smart contracts to reduce human error while ensuring real-time monitoring of compliance and security controls. By evaluating critical security controls - such as data encryption, access control mechanisms, multi-factor authentication, and zero-trust architecture - this approach strengthens an organization's defense against emerging cyber threats. Additionally, continuous monitoring enabled by blockchain ensures the immutability and transparency of vendor compliance processes. In this paper, a case study on iHealth's transition to AWS Cloud demonstrates the practical implementation of the framework, showing a significant reduction in vulnerabilities and marked improvement in incident response times. Through the adoption of this blockchain-enabled approach, organizations can mitigate vendor risks, streamline compliance, and enhance their overall security posture. Our findings highlight the importance of employing blockchain to enforce security controls and maintain compliance with healthcare regulations such as HIPAA. In this paper, we present a comprehensive set of security controls and demonstrate how blockchain technology enhances their effectiveness, ensuring greater transparency, accountability, and automation in vendor assessments. By reducing human error, e

关键词： Smart contract

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A Tangible E-Learning Solution for Early Childhood Development 13

A Tangible E-Learning Solution for Early Childhood Developme...

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13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022

作者： Cholitha Hettiarachchi, Thiwanka Sathyajith Semasinghe, Lakisuru De Silva, Rajitha Lokuliyana, Shashika Gamage, Narmada Ratnasuriya, Manisha Sri Lanka Institute of Information Technology Dept. of Computer Systems Engineering Sri Lanka University of Lincoln United Kingdom

ISBN: (数字)9781665452625

ISBN: (纸本)9781665452625

Exploration and manipulation of physical objects are essential for early childhood learning. TangiGuru is an e-Learning platform that allows children to engage with real-world physical objects to provide that essential experience within an e-Learning application. TangiGuru consists of 12 tangible, manipulative objects known as TangiCubes, which are used as a tangible user interface between children and the e-Learning application. It can carry out cognitive learning activities related to colors, languages, shapes and basic math by dynamically varying assigned values by changing the external appearance of TangiCubes. This dynamic nature of the TangiCubes makes it possible to use the same tangibles with endless possibilities compared to traditional tangible learning solutions with static value for each tangible. With the initial observations of how children interact with computers, laptops, and mobile devices, the goal is to provide a playful interface for children by taking the approach to embedding and integrating technology into the children's daily activities. After the prototyping phase, children were evaluated with the traditional tangible learning solutions compared to TangiGuru. They concluded that the more interactive tangible interfaces could make the children perform activities more engagingly. © 2022 IEEE.

关键词： E-learning

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Exploring the Relationship Between Environmental Sustainability and Usability in Popular Sports Websites

Exploring the Relationship Between Environmental Sustainabil...

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Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

作者： Ganeshkumar Pandiarajan Sofia Ouhbi Jennifer Gross José A. García-Berná Joaquín Nicolás Dept. Information Technology Uppsala University Uppsala Sweden Dept. Computer Science and Systems University of Murcia Murcia Spain

ISBN: (数字)9798350380262

ISBN: (纸本)9798350380279

Sustainability has become a significant concern in software systems like websites, driven by their increasing adoption and environmental impact. As website usage grows, so does their energy consumption and carbon footprint, affecting their environmental sustainability. Understanding the relationship be-tween usability and environmental sustainability is essential for designing web sites that meet user needs while minimizing environmental impact. This paper examines this relationship, focusing on popular sports websites due to their substantial internet traffic. We evaluated ten English-language sports web sites for their environmental sustainability and usability using Nielsen's 10 usability heuristics. Our assessment considered factors such as Ecological Accommodation, Content, Operation, Multimedia, and HTTP Requests. The findings reveal a strong negative correlation between usability and sustainability, suggesting that improvements in usability may increase environmental impact and vice versa. This study's insights can inform website de-velopers in creating digital platforms that are both usable and environmentally sustainable.

关键词： Measurement Correlation Green products Software systems Web sites Servers Usability Sustainable development Sports Software engineering

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