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Multimodal Online Manipulation: Empirical Analysis of Fact-Checking Reports 10

Multimodal Online Manipulation: Empirical Analysis of Fact-C...

引用

10th Italian Conference on Computational Linguistics, CLiC-it 2024

作者： Uryupina, Olga Department of Information Engineering and Computer Science University of Trento Italy

This paper presents an in-depth exploratory quantitative study of the interaction between multimedia and textual components in online manipulative content. We discuss relations between content layers (such as proof or support) as well as unscrupulous techniques compromising visual content. The study is based on fakes reported and analyzed by PolitiFact and comprises documents from Facebook, Twitter and Instagram. We identify several pervasive phenomena currently, affecting the impact of manipulative content on the reader and the possible strategies for effective de-bunking actions, and discuss possible research directions. © 2024 CEUR-WS. All rights reserved.

关键词： Tweets

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Enhanced Video Monitoring Using Stae Autoencoder 2

Enhanced Video Monitoring Using Stae Autoencoder

引用

2nd International Conference on Artificial Intelligence Trends and Pattern Recognition, ICAITPR 2024

作者： Kumar, Vitta Yaswanth Abdullah, Shaik Jayvardhan, G. Reddy, G.S. Prasada Vardhaman College of Engineering Computer Science Department Hyderabad India

ISBN: (纸本)9798350368000

Big data applications have become widespread across different sectors and research domains, incorporating a vast array of sources such as social media information, sensor data, agricultural data, medical data, and data derived from space exploration. A significant contributor to unstructured big data is the use of video feeds from surveillance cameras. These cameras are deployed extensively in critical areas where security is paramount. The manual monitoring of surveillance footage is both labour-intensive and time-consuming. Security concerns in this context vary from identifying thefts to detecting violent incidents and even anticipating potential explosions. In densely populated public spaces, security encompasses monitoring a broad spectrum of abnormal events, with violence detection being particularly challenging due to the complexity of group dynamics. Analysing anomalous activities in crowded video scenes presents substantial challenges due to real-world constraints. This survey paper delves into a comprehensive review starting from action recognition to crowd analysis, culminating in the intricate task of violence detection in crowded environments. The majority of the studies reviewed in this survey rely on deep learning *** this paper, we employ the State Spatiotemporal Auto-Encoder (STAE) alongside a combination of LSTM (Long Short-Term Memory) layers and convolutional networks. These advanced techniques are pivotal in our approach to tackle the challenges of analysing surveillance videos, particularly in detecting anomalous activities such as violence in crowded environments. © 2024 IEEE.

关键词： NASA

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Strengthening QR code Anti-Counterfeit through Multi-Encryption Algorithm 1

Strengthening QR code Anti-Counterfeit through Multi-Encrypt...

引用

1st IEEE International Conference on Cognitive Robotics and Intelligent Systems, ICC - ROBINS 2024

作者： Narayanan, S. Dhivyalakshmi Prabhu, S. Department of Computer Science and Engineering Tamil Nadu Erode India

ISBN: (纸本)9798350372748

The rise in digital information sharing poses risks to privacy and personal identity, making data vulnerable to theft and swift modifications during transfer. Safeguarding digital data against attackers is crucial. To enhance QR code security and combat counterfeiting, a novel approach is presented in this study. This method integrates the Advanced Encryption Standard (AES) algorithm and Rubik's Cube Principle, fortifying anti-counterfeit measures in QR codes. The QR code image is divided into RGB channels using the Rubik's Cubic Principle. The AES encryption key encrypts these channels, and the results are combined into an encrypted image. Experimental outcomes affirm the effectiveness of the proposed scheme, demonstrating robust encryption and impeccable concealment capabilities. © 2024 IEEE.

关键词： Cryptography

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Delay Minimization for Offloaded Tasks in UAV-Assisted Mobile Edge Computing Using Ant Colony Optimization 6

Delay Minimization for Offloaded Tasks in UAV-Assisted Mobil...

引用

6th International Conference on Sustainable Technologies for Industry 5.0, STI 2024

作者： Ahmed, Tanzir Ahmed, Jargis Green University of Bangladesh Department of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798331531973

Mobile Edge Computing (MEC) server plays a crucial role in executing the tasks offloaded by the edge users. As MEC is deployed at the edge of the network, it helps to reduce computation latency and increase reliability for users. Due to enormous tasks offloading requests MEC may require extra resources to mitigate resource demand. In this case, MEC can deploy multiple unmanned aerial vehicles (UAVs) as computing nodes to assist with resource requirements. Now distributing the offloaded tasks and reducing the latency for task completion is a challenging problem. In this regard, we developed a delay minimization problem considering the delay and latency constraints in this paper. The formulated problem is a mixed integer problem and NP-Hard in nature. Hence we proposed an ant colony optimization (ACO) based algorithm to handle task placement in different server nodes. Extensive performance analysis indicates significant improvement in reducing delay, energy consumption of users, and success rate compared to the state-of-the-art work. © 2024 IEEE.

关键词： Ant colony optimization

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An MEC-based Platform for IoT Applications 23

An MEC-based Platform for IoT Applications

引用

2023 International Conference on Intelligent Computing and Its Emerging Applications, ICEA 2023

作者： Chen, Whai-En Department of Computer Science and Information Engineering Asia University Taichung Taiwan Computer Science and Information Engineering National Ilan University Yilan Taiwan

ISBN: (纸本)9798400709050

The key technologies for the future development of mobile communications are: Provide end-To-end ultra-low latency, reliability and availability;Provide different network slices according to different business needs;Provide edge computing power;Smart network manage. Ultra-low latency and reliability and the ability to handle large-scale Internet of Things (IoT) connections are two important requirements. However, this cannot be achieved by simply improving the performance of wireless transmission (*** radio access network). It is also necessary to improve the core network and creates edge computing platforms to achieve this goal. To address this issue, this article develops and deploys a mobile edge computing platform, also known as a multi-Access edge computing (MEC) platform, to meet the requirements of ultra-low latency, high reliability, and massive connections. This article takes a smart pig farm as an example to demonstrate the design and deployment of an MEC applications. Specifically, this article develops an IoT system for the pig farm on the MEC platform and creates a virtualized MEC application to provide real-Time packet processing and image recognition for the pig farm monitoring. In addition, this paper analyzes the performance of this MEC App, including the recognition accuracy and the latency in error recovery of the MEC App. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Internet

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Application of Generative Graph Models in Biological Network Regeneration: A Selective Review and Qualitative Analysis

Application of Generative Graph Models in Biological Network...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Teji, Binon Roy, Swarup Guzzi, Pietro Hiram Bhandari, Dinabandhu Lab Department of Computer Applications Gangtok India University of Catanzaro School of Computer Science and Biomedical Engineering Italy Heritage Institute of Technology Department of Computer Science and Engineering Kolkata India

ISBN: (纸本)9798350386226

Biological networks are essential for understanding the complex cellular mechanisms of living organisms. Simulating biological networks allows researchers to model and understand complex cellular processes without the need for extensive and costly experiments. The ability to generate synthetic graphs that closely resemble these real-world, complex biological processes is a vital research area. Graph generation in the context of biological networks is particularly significant because it can lead to insights into cellular functions, disease mechanisms, and therapeutic targets. Recent advances in deep learning, particularly in graph generative models, have opened new avenues for applications in the biological domain. These advancements have the potential to revolutionize our understanding of biological systems. However, despite the development of numerous effective graph generation models, there has been limited work assessing the qualitative aspects of the generated graphs within the context of biological networks. Addressing this gap is crucial for ensuring that synthetic graphs are not only structurally accurate but also biologically *** various graph generation models are available, their application to biological network recreation has been limited. In this paper, we focus on graph generation, specifically edge and node-independent models for biological networks. We assess four candidate models across four gene expression networks. Our systematic assessment examines the models' qualitative aspects, including graph structural properties, generation diversity, and computational efficiency. Our findings highlight the strengths and limitations of current models, offering insights to guide the development of more robust graph generation techniques that accurately replicate biological network characteristics. © 2024 IEEE.

关键词： Biotic

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Cryptographic Analysis: Popular Social Media Applications and Mitigations of Vulnerabilities 26

Cryptographic Analysis: Popular Social Media Applications an...

引用

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Moon, Iffath Tanjim Mimi, Afsana Rahman Mridha, Md. Musfiqur Pundra University of Science & Technology Department of Computer Science & Engineering Bogura Bangladesh Varendra University Department of Computer Science & Engineering Rajshahi Bangladesh

ISBN: (纸本)9798350359015

In this paper, we have conducted a cryptographic analysis of the most widely used Android social media applications. In Android social media applications, cryptography plays a vital role in protecting data and communication. End-to-end encryption, digital signatures, authentication and authorization, password hashing, data encryption, Transport Layer Security (TLS), blockchain, and decentralized social networks are some of the important uses of cryptography in social media applications. However, inappropriate use of cryptography in social media applications can result in data leaks, financial losses, identity theft, breaches of privacy, exploitation of vulnerabilities, and an adverse user experience. Therefore, developers must follow the best practices for cryptography in order to strengthen the cybersecurity of these applications. In this paper, we present the cryptographic analysis of 10 popular Android social media applications. Firstly, we have conducted static analysis of these applications. We have assessed the findings based on some cryptographic issues such as the random number generator, cipher and padding, cipher configuration, hashing algorithm, and cryptographic classes. We have also identified vulnerable issues in the cryptography of the applications and provided remedies. Our cryptographic evaluation can strengthen the cybersecurity of any Android social media application. © 2023 IEEE.

关键词： Android applications cryptographic analysis cryptography cybersecurity social media applications static analysis

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Synergistic Approach for UAV Target Tracking: A Voronoi-GWO-Reinforcement Learning Framework 30th

Synergistic Approach for UAV Target Tracking: A Voronoi-GWO-...

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30th International Conference on Computational and Experimental engineering and sciences, ICCES 2024

作者： Bhat, Pranamya P. Sudheer, Neeraj Manoj, Nandana Kumar, Preethika Ajay Sharma, Richa Arya, Arti Department of Computer Science Engineering PES University Karnataka Bengaluru India

ISBN: (纸本)9783031829062

Unmanned Aerial Vehicles (UAVs) are integral to diverse applications, spanning surveillance, search and rescue operations, and precision agriculture. This paper addresses a critical challenge in these domains offering efficient and reliable target tracking, especially in the context of multiple UAV deployments. It presents an innovative approach, Volf-RL (Voronoi based-Grey Wolf Optimisation-Reinforcement Learning), leveraging Voronoi subspaces to optimize the spatial distribution of UAVs, coupled with the integration of the Grey Wolf Optimizer (GWO) for advanced target tracking capabilities. To enhance overall mission safety and efficiency, we further incorporate reinforcement learning techniques, ensuring collision avoidance among UAVs. This multifaceted approach aims to create a sophisticated UAV swarm optimization system. The collaboration of Voronoi subspaces, GWO and Deep-Q Networks not only refines the spatial arrangement of UAVs but also contributes to dynamic target tracking in complex environments. The primary objectives of this research include achieving optimal area coverage for target detection, addressing collision avoidance challenges, exploring moving swarm formations for comprehensive surveillance, and refining UAV-based target tracking accuracy using GWO. The amalgamation of computational geometry, meta-heuristic techniques, and reinforcement learning underscores the commitment of the work towards advancing UAV swarm intelligence. This research lays the foundation for an intelligent, coordinated, and adaptive UAV swarm optimization system, poised to excel in challenging environments with an accuracy of 96.77% in collision avoidance and 98.79% accuracy in target tracking. Through this successful realization of these objectives, we anticipate a paradigm shift in UAV swarm capabilities, fostering advancements in defense, transportation, and logistics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Unmanned aerial vehicles (UAV)

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Generating Images from Text Using GANs vs Transformers 8

Generating Images from Text Using GANs vs Transformers

引用

8th International Conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2025

作者： Kumar, Jatin Tanvi, Tanisha Ghosh, Aitijya Mondal, Ritankar Das, Soma Institute of Engineering and Management University of Engineering and Management Department of Computer Science and Engineering Kolkata India

ISBN: (纸本)9798331520762

This paper compares Generative Adversarial Networks (GANs) and transformer-based models for text-to-image generation, examining each approach's ability to convert textual descriptions into realistic images. GANs, leveraging a generator-discriminator framework, have made strides with models like DF-GAN [1] and StackGAN [2], which improve image fidelity through multi-stage generation and attention. However, GANs face challenges with complex datasets. Transformer-based models, initially used in natural language processing, offer robust handling of dependencies, enhancing the capture of image features from text. Emerging hybrid models combine GAN and transformer strengths for improved stability and image quality. This study aims to identify optimal techniques by analyzing their architectures, training, and output quality, contributing to advancements in multi-modal generative modeling. © 2025 IEEE.

关键词： Chatbots

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A Strategic Framework for the Development of a Microtext AI Chatbot for Tourism in Indian Cities 8

A Strategic Framework for the Development of a Microtext AI ...

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8th International Conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2025

作者： Sultan, Adnan A. Mukherjee, Unmesh Mondal, Anupam Institute of Engineering & Management University of Engineering & Management Department of Computer Science & Engineering Kolkata India

ISBN: (纸本)9798331520762

Tourism plays a crucial role in India's economy, with its diverse cultural, historical, and geographical richness attracting millions of domes-tic and international visitors annually. To cater to the needs of these travelers and enhance their overall experience, there is a growing need for inno-vative technological solutions. This paper presents a comprehensive literature survey, analyzing existing research, trends, and practical implementations of microtext normalization as well as the application of chatbots in the context of tourism. Furthermore, it proposes a strategic framework for the development and deployment of an effective microtext AI chatbot tailored to the requirements of tourism in India. The proposed design leverages modern machine learning and natural language processing (NLP) strategies for providing personalized, context-aware assistance to tourists in order to enhance their overall experience while exploring the various cities of India. © 2025 IEEE.

关键词： Tourism

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