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Massive-Parallel Game of Politicians 7th

Massive-Parallel Game of Politicians

引用

8th Asia Pacific Web and Web-Age information Management Joint International Conference on Web and Big Data

作者： Schumann, Andrew Pancerz, Krzysztof Univ Informat Technol & Management Rzeszow Dept Cognit Sci & Math Modelling Sucharskiego 2 PL-35225 Rzeszow Poland John Paul II Catholic Univ Lublin Al Raclawickie 14 PL-20950 Lublin Poland

ISBN: (纸本)9789819600540;9789819600557

Mould or fungal propagation can serve as a universal model for a massive-parallel game of many players, moving concurrently. Based on this model, a game of politicians is introduced to occupy as many political keywords as possible in the media. If a politician begins to be mentioned every time with some word or group of words, then this means that he or she has occupied this word or group of words. In the election campaign, the winner is the politician who has occupied the most words. The study was carried out on the example of Polish politicians. In addition, a space for keywords related to mentions in the messages of 780 politicians of the Sejm and Senate of the last two terms of office was created. Thus, the reflection game of politicians for keywords was implemented. In this game, you can explain the role of politicians in their activities for their party or for themselves. The period of the game is for three years. This game shows the dynamics of political discourse in Poland during this period. In different media, this game is realized in different ways. For example, party-related keywords in the media correlate differently with party program texts. This means that journalists from various portals influence this game of politicians. Data modeling as a game of politicians for keywords makes it possible to identify hidden players and their degree of reflexivity.

关键词： Concurrent Game Massive-Parallel Game Fungi

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A Machine Learning (ML)-Inspired Method for Intrusion Detection in IoT Devices Networks 5th

A Machine Learning (ML)-Inspired Method for Intrusion Detect...

引用

5th International Conference on Computing science, Communication and Security

作者： Venkatesh, Veeramuthu Raj, Pethuru Nedium, Roshitha Edara, Jahnavi Reddy, Kalluru Amarnath Anushiadevi, R. SASTRA Deemed Univ Sch Comp Thanjavur 613401 Tamilnadu India Reliance Jio Cloud Serv JCS Bangalore 560025 Karnataka India

ISBN: (纸本)9783031751691;9783031751707

The Internet of Things (IoT) and Machine Learning (ML) represent dynamic research fields with significant growth. IoT applications have gained popularity among technology researchers and developers, and the increasing deployment of IoT devices in critical infrastructures improves efficiency and reliability and raises concerns about cyber-attacks. Enterprises have effectively implemented IoT services, enabling automated production through remote and intelligent control. However, this adoption has concurrently introduced novel security vulnerabilities. Addressing the security and privacy challenges in IoT, especially considering energy limitations and scalability issues, remains a critical focus in computer security. This paper aims to prevent multiple attacks targeting sensor nodes' data manipulation. It encompasses a range of threats, such as sensing layer attacks, malfunctions, tamper attacks, false data injection, base node and clone attacks. The proposed approach involves a threat model and a pairing algorithm that utilizes machine learning to associate each sensor node with its corresponding node. To accomplish the goal, the performance of the proposed solution is compared with various machine learning models, including Decision Tree, Linear Regression, k-nearest neighbors (KNN), Random Forest, and AdaBoost. The evaluation utilized two openly accessible real-world datasets, with metrics such as accuracy in attack detection, training time, and testing time being considered. By incorporating machine learning algorithms to improve attack detection in IoT environments, the proposed approach represents a significant advancement in enhancing security and privacy. The results highlight the importance of adopting advanced techniques to safeguard IoT systems from potential threats. The proposed method achieved an impressive 96.75% accuracy rate in detecting attacks, surpassing existing solutions with nearly twice the speed in training and testing times. As the IoT landsc

关键词： Sensor nodes Security attacks Intrusion Detection System Critical infrastructure Machine learning Internet of Things (IoT)

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Current Design Practices in Applied Augmented Reality Research: A Methodological Review 1

引用

8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Teutenberg, Lukas D. Fitz, Lukas R. G. Scheeg, Jochen Brandenburg Univ Appl Sci Dept Business & Management Magdeburger Str 50 D-14770 Brandenburg Germany

ISBN: (数字)9783031826337

ISBN: (纸本)9783031826320;9783031826337

Successful Augmented Reality (AR) solutions require high technology acceptance and desire among users. Applying appropriate design methodologies can enhance the development of desirable AR systems and help to streamline design research projects. This article presents a methodological literature review of 58 pertinent articles, exploring the representation of methodological design frameworks in currently applied AR research practice. In result, User-Centered Design was identified most frequently by a large margin. Though, it could be observed that most articles from the field of applied AR only marginally describe any design processes. Moreover, Human-Centered Design, Participatory Design and Value Sensitive Design were only scantily represented;less than half of the papers followed a Design science Research or Action Design Research approach. Several implications for applied research and practice are derived from these findings and discussed together with future research opportunities. Overall, this study contributes to the refinement of methodological design practice in the field of applied AR research.

关键词： Augmented reality Design methods Applied science Literature review

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Handcrafted and Deep Features for Synthetic Data Generation in Offline Handwritten Signature Verification 4th

Handcrafted and Deep Features for Synthetic Data Generation ...

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4th International Conference on Intelligent Systems and Pattern Recognition-ISPR

作者： Arab, Naouel Nemmour, Hassiba Bouibed, Mohamed Lamine Chibani, Youcef Univ Sci & Technol Houari Boumediene USTHB Lab Ingn Syst Intelligents & Commun LISIC Fac Elect Engn Algiers Algeria

ISBN: (纸本)9783031821554;9783031821561

One of the major limitations which obstruct the development of an efficient offline signature verification system is the lack of genuine signatures required to perform a reliable training stage. To deal with this issue, data augmentation techniques are employed to add synthetic genuine signatures. Presently, the signature verification system is developed by applying an algorithm for synthetic features generation. We evaluate the effectiveness of this feature generator with two different signature descriptors. The first descriptor is the Local Directional Strength Patterns while the second descriptor is based on the SigNet deep features. The verification phase is carried out with an SVM classifier. Experiments are performed on CEDAR and MCYT-75 datasets according to the writer-dependent verification approach. The inclusion of synthetic features considerably enhances the system performance, yielding a gain of 17% when the verification system employs only one real signature. Compared to handcrafted features, the SigNet provide more effective synthetic features with both datasets.

关键词： Artificial Immune System Handwritten Signature Verification Local Directional Strength Pattern SigNet features Synthetic feature generation

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From Theory to Practice: Digital Innovations in Humanitarian Logistics for Real-World Disaster Management 5th

From Theory to Practice: Digital Innovations in Humanitarian...

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5th 5th Olympus - International Conference on Supply Chain

作者： Aretoulaki, Eleni Ponis, Stavros T. Plakas, George Tzanetou, Dimitra Kitsantas, Antonios Natl Tech Univ Athens Sch Mech Engn Heroon Polytech 9 Athens 15780 Greece

ISBN: (纸本)9783031693502;9783031693519

The rapid advancement of digital technologies has significantly impacted the field of humanitarian logistics and disaster management, prompting a paradigm shift in addressing emergencies. In this paper, a literature review is conducted, drawing on grey literature, reports, case studies, operational updates and European research projects. The review delves into the transformative impact of unmanned aerial vehicles and other digital innovations on disaster response strategies. Through an analysis of real-life implementations, the study underscores the essential role of technology in enhancing situational awareness, facilitating rapid responses, and ensuring robust communication during crises in practice. By examining the deployment of drones, machine learning, the Internet of Things, and other digital technologies, this review expands the humanitarian logistics' community comprehension of the dynamic humanitarian aid and disaster relief landscape. This research reveals that these technologies offer unmatched capabilities in monitoring, assessment, and aid delivery, reshaping traditional disaster management mechanisms. Nonetheless, despite noteworthy progress, the review uncovers a persistent gap in the creation of a holistic system covering the entire disaster management cycle, mirroring concerns highlighted in academic literature. This gap underscores the critical need for integrated solutions that address mitigation, preparedness, response, and recovery, i.e., the four disaster management stages, comprehensively. In essence, this research distinguishes itself by juxtaposing real-life project outcomes with scholarly insights and validates the identified gap in holistic solutions, underlining the necessity for developing a future-oriented unified framework that leverages digital technologies to meet the complex demands of disaster management, closely aligned with humanitarian objectives.

关键词： humanitarian logistics disaster management digital technologies drones unmanned aerial vehicles internet of things

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Decentralized Education and Incentivization: A Study of Decentralized Autonomous Universities 4th

Decentralized Education and Incentivization: A Study of Dece...

引用

4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： van Bijlevelt, Danny Rafiee, Amin Bittopia Fdn Cheyenne WY 82001 USA

ISBN: (纸本)9783031840777;9783031840784

As a result of blockchain technology and other decentralized systems, Decentralized Autonomous Universities (DAUs) have emerged as a foundational element in decentralized education. DAUs offer efficiency, transparency, and accessibility, featuring incentive and reward systems unattainable in traditional centralized models. This paper examines Bittopia University, the world's first DAU, highlighting its role in both revolutionizing and decentralizing education via modern innovations. Bittopia positions students as primary stakeholders. Bittopia combines innovation and technology and introduces new frameworks, such as Decentralized Courses (DACs), personalized learning pathways and content, incentivized learning, and gamification of student progress. Additionally, this paper delves into system architecture, ethical considerations, sustainability of DAUs, and simultaneously explores broader implications for the future of decentralized education.

关键词： Decentralized Autonomous University (DAU) Decentralized Education Bittopia Decentralized Autonomous Organization (DAO)

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Cross-Domain Adversarial Attacks and Robust Defense Mechanisms for Multimodal Neural Networks 4th

Cross-Domain Adversarial Attacks and Robust Defense Mechanis...

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4th International Conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Barach, Jay Syst Staffing Grp Inc IT Operat & Recruitment King Of Prussia PA 19401 USA

ISBN: (纸本)9783031837951;9783031837968

This paper addresses the challenge of defending neural networks against adversarial attacks and environmental noise by proposing a cross-modal architecture that combines image and audio data streams. With the MNIST and Audio MNIST datasets, the model integrates specialized Convolutional Recurrent Neural Network (CRNN) encoders for each modality, followed by a late fusion layer that synthesizes features into a unified, resilient representation. This fusion mechanism exploits the inherent consistency between modalities, reducing the impact of adversarial perturbations targeting a single data stream. Preprocessing steps, including normalization, Gaussian noise injection, and adversarial example generation through FGSM and PGD, are applied to simulate diverse attack scenarios. The adversarial training loop, designed to expose the model to clean and adversarial samples, further strengthens its robustness by minimizing the adversarial success rate (ASR) while preserving high accuracy. Evaluation metrics like F1-score, precision, recall, and accuracy confirm the effectiveness of this defense strategy. Our results highlight a marked improvement in performance over unimodal approaches, with a substantial reduction in ASR and enhanced resilience in noisy environments. By uniting cross-modal consistency checks and adversarial training, this approach offers a promising defense mechanism for real-world applications where security and reliability are paramount.

关键词： Adversarial Attacks Cross-Modal Consistency Neural Network Defense Multimodal Fusion Adversarial Training Noise Robustness Convolutional Recurrent Neural Networks (CRNN) Adversarial Success Rate (ASR)

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Eyecare for All, a Service Design Approach 1

引用

15th Indian Conference on Human-computer Interaction Design and Research

作者： Chinnaswamy, Kumaresh Nair, Manjusha Neelakanthan, Manoj Infosys Ltd Plot 44Hosur Rd Bengaluru 560100 Karnataka India

ISBN: (数字)9783031808326

ISBN: (纸本)9783031808319;9783031808326

This paper investigates the critical issue of limited eyecare accessibility in India, a significant concern where 80% of blindness and vision impairments are preventable with early detection and treatment. It presents a comprehensive solution to the dire need for improved eyecare accessibility, particularly in rural regions where the prevalence of preventable blindness and vision impairments remains high. The core of this innovative approach combines a service model dedicated to expanding eyecare access and affordability with a sophisticated mobile application designed for preliminary eye condition screenings. The combined solution addresses the critical challenges of early detection and treatment by enabling users to conduct self-assessments for common vision disabilities such as cataracts, uncorrected refractive errors, and front-eye diseases remotely. The mobile app, an integral part of the service model, features a clinically mimicked vision test, a triage system to assess treatment urgency, and the capability for capturing detailed eye images. Aimed at empowering individuals regardless of their geographical or financial constraints, the paper details the development, usability enhancements, and the transformative potential of this service model and app to bridge the eyecare accessibility gap. Additionally, it outlines plans for further implementation and assessment, emphasizing a system thinking approach and close collaboration with stakeholders across the eyecare ecosystem to ensure scalability and impact. Through this pioneering combination of service design and digital tool, the initiative marks a significant leap towards reducing the burden of untreated eye conditions and advancing preventive eye health care in underserved communities.

关键词： Preventive eyecare Healthcare in India Blindness prevention Accessibility in rural areas Service design Mobile application

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Text Mining in Supply Chain Risk Management: A Bibliometric Analysis 5th

Text Mining in Supply Chain Risk Management: A Bibliometric ...

引用

5th 5th Olympus - International Conference on Supply Chain

作者： Gelastopoulos, Georgios Keramydas, Christos Tsolakis, Naoum Int Hellen Univ Sch Econ & Business Adm Dept Supply Chain Management Thermi 57001 Greece

ISBN: (纸本)9783031693434;9783031693441

In Supply Chain Risk Management (SCRM), the use of text mining is gaining increasing attention as the application of modern algorithms enable rapid, real-time interpretation of huge volume of unstructured data. Online data has the potential to provide critical insights for proactive risk identification and mitigation in the complex and interconnected global supply chain networks, especially in periods of man-made disasters or crises such as the Ukrainian-Russian conflict. This paper delivers an overview of how text mining of online data is being used in SCRM. More specifically, by using bibliometric methodologies, this study identifies primary areas of focus and collaborative networks in SCRM's research field. The most common analysis methods such as citation analysis, co-authorship patterns, keyword co-occurrence, and publication trends take place as a comprehensive corpus of peer-reviewed articles from Scopus database is collected and analyzed. By employing bibliometric tools and network analysis measures the study explores how the use of text mining techniques is evolving for the past ten years, and where it is heading. This is achieved by visualizing the networks with suitable programmes, by using indices like the modularity index and with cluster analysis which are applied to the networks created from the bibliographic data. This study aims to uncover trends, disciplines, and howindividual studies are related to one another. The results suggest thematic clusters, influential studies and authors, and research methods that are significant to the field and they map trends and future directions, providing valuable insights for both academic researchers and industry practitioners.

关键词： Bibliometric Analysis Supply Chain Risk Management Text Mining Online Data

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Botnet-Based DDoS Attack: Automatic Detection, Mitigation, and Real-Time Traffic Filtering in Cloud Environments 4th

Botnet-Based DDoS Attack: Automatic Detection, Mitigation, a...

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4th International Conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Basuli, Suman Padhya, Mukti Natl Forens Sci Univ Sch Cyber Secur & Digital Forens Gandhinagar 382007 Gujarat India

ISBN: (纸本)9783031837821;9783031837838

Distributed Denial of Service (DDoS) attacks pose a persistent threat to cloud infrastructure, often disrupting services and affecting legitimate user traffic. Traditional DDoS mitigation techniques, including network-based defenses and anomaly detection, are effective but frequently fail to handle complex, high-volume attacks in dynamic cloud environments. This study addresses the above-mentioned limitations by developing a scalable DDoS mitigation framework specifically for cloud infrastructure. We propose a dynamic and adaptive approach to DDoS detection that integrates real-time traffic analysis with automated and intelligent mitigation strategies. Unlike traditional methods, our solution emphasizes automated, real-time decision-making and adjusting defenses based on evolving attack patterns. This minimizes the need for manual intervention, enhances system resilience, and ensures quicker response to threats. A key contribution of this study is an automated DDoS mitigation mode that dynamically filters malicious traffic and employs CAPTCHA for legitimate users, thereby offering an efficient method for protecting cloud services. This framework is not intended to replicate existing solutions, such as Cloudflare, but instead serves as a novel approach for organizations to customize and scale their own DDoS mitigation systems. Furthermore, testing conducted in a controlled simulation environment evaluated the system's resilience to various attack types, including volumetric, application-layer, and IP spoofing attacks. The key findings reveal the system's capability to efficiently block malicious traffic while ensuring minimal disruption to legitimate users. Comparative analysis with Cloudflare demonstrates the effectiveness of our approach in terms of detection accuracy and resource efficiency.

关键词： DDoS Mitigation Cloud Infrastructure Security Cloud Security Traffic Filtering Automated Detection and Response

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