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Semi-automatic performance support robot that can attach and detach guitars 13

Semi-automatic performance support robot that can attach and...

引用

13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Tsurumi, Kazuki Marutsuka, Ryo Koutaki, Gou Kumamoto University Dept. of Computer Science and Electrical Engineering Kumamoto860-8555 Japan

ISBN: (纸本)9798350355079

Research has primarily focused on fully automatic instrument-playing robots. However, it is difficult to support the experience of playing musical instruments for people with physical disabilities or those who are inexperienced in playing musical instruments. To address this issue, we studied a "semi-automatic"instrument-playing robot based on human-robot collaboration. Our research specifically focused on the guitar, which are stringed instruments with complex pressed strings. The developed robot enables individuals with physical disabilities and those without musical experience to easily play musical instruments. Additionally, the instruments can be easily removed without causing damage. © 2024 IEEE.

关键词： User centered design

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Polygenic Risk Scores are Associated to Aβ-τ Protein Accumulation in Alzheimer's Disease 3

Polygenic Risk Scores are Associated to Aβ-τ Protein Accum...

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3rd IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2024

作者： Treccani, Irene Dolci, Giorgio Brusini, Lorenza Cruciani, Federica Galazzo, Ilaria Boscolo Menegaz, Gloria University of Verona Dept. of Engineering for Innovation Medicine Verona Italy University of Verona Dept. of Computer Science Verona Italy

ISBN: (纸本)9798350378009

Alzheimer's (AD) is a complex and multi-domain neurodegenerative disease characterized by amyloid-β (Aβ) and proteins aggregation holding both genotype and phenotype signatures. Increasing evidence suggests that the accumulation of -τ proteins plays a crucial role in disease onset and progression. In order to shade light on these issues, in this study we exploited the Partial Least Squares model to investigate the link between neuroimaging-derived features and genetic factors. Cortical thickness and Polygenic Risk Scores were used as pheno/geno-typing features, respectively. The model was trained on a cohort of subjects including healthy controls (CN) and AD patients, and tested on a discovery set consisting of - τ - and+τ+individuals. The working hypothesis being that these last two groups with different biological profiles would cluster closer to the CN and AD classes, respectively. In agreement with previous results, segregation was observed in the latent space between CN and AD and was also confirmed when applying the model to the - - and++discovery set. These outcomes, together with a significant association found among the respective projection weights, encourage further investigation. © 2024 IEEE.

关键词： Neuroimaging

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Improving Fake News Detection with a Mixture of Experts: Leveraging Sentiment Analysis and Sarcasm Detection as Core Expert Models 6

Improving Fake News Detection with a Mixture of Experts: Lev...

引用

6th International Conference on Advancements in Computing, ICAC 2024

作者： Gunasekara, Tharindu Thihan, Disira Kodithuwakku, Sansika Dissanayake, Dinuka Fernando, Harinda Vidhanaarachchi, Samitha Sindhujan, Archchana Sri Lanka Institute of Information Technology Malabe Dept. of Software Engineering Sri Lanka Sri Lanka Institute of Information Technology Malabe Dept. of Computer Computer Systems Engineering Sri Lanka University of Surrey Dept. of Computer Science and Electronic Engineering United Kingdom

ISBN: (纸本)9798331517878

Fake news continues to proliferate, posing an increasing threat to public discourse. The paper proposes a framework of a Mixture of Experts, Sentiment Analysis, and Sarcasm Detection experts for improved fake news detection. This approach captures the emotional cues in the text through a Sentiment Analysis expert, which is based on bidirectional encoder representations from Transformers (BERT) models with sentiment vectors generated using SentiWordNet and Integrated Gradients. It combines a sarcasm detection expert based on BERT, recognizing sarcasm and its type to help classify fake news. By fusing these experts through a Mixture of Experts gateway, subtle linguistic cues often found in fake news are more effectively analyzed, leading to improved accuracy in detecting misinformation. Experimental results are presented as 96% for the Sarcasm expert with the BERT base model and 83% for the Sentiment Analysis expert with the distilled version of the BERT (DistilBERT) base model, proving the effectiveness of the proposed approach in beating traditional methods. © 2024 IEEE.

关键词： fake news detection gateway mixture of experts sarcasm detection sentiment analysis

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HealthLink: A Cutting-Edge System for Secure Healthcare Data with IoT, Blockchain, and IPFS 3

HealthLink: A Cutting-Edge System for Secure Healthcare Data...

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Vijayakumar, Kallur V. Chethan, A.S. Muneshwara, M.S. Swetha, M.S. Anand, R. Shivakumara, T. Bmsit&m Dept. of Mathematics India Bmsit&m Dept. of Computer Science & Engineering India Bmsit&m Dept. of Information Science & Engineering India Bmsit&m Dept. of Mca India

ISBN: (纸本)9798350354348

In today's rapidly evolving healthcare landscape, the integration of cutting-edge technologies such as IoT and wearable devices has led to significant advancements, particularly in the realm of remote patient monitoring. Despite these advancements, the traditional client/server architecture prevalent in current implementations presents substantial challenges related to security and privacy, leaving healthcare systems vulnerable to various attacks. Consequently, stringent regulatory and security measures are imperative to safeguard health data. To address these challenges and meet regulatory requirements, transitioning to a distributed architecture is essential. Blockchain technology, renowned for its distributed nature and robust security features, offers a promising solution to mitigate the security risks inherent in IoT-based systems. Motivated by these considerations, this study introduces HealthLink - a secure healthcare framework that seamlessly integrates IoT and Blockchain *** is designed to facilitate remote patient monitoring, particularly for chronic diseases that require continuous oversight. The framework prioritizes security, scalability, and processing efficiency. Security measures include the use of re-encryption proxies combined with Blockchain for hash data storage, while access control is managed through smart contracts. To enhance Blockchain scalability, an off-chain IPFS-based database is employed for data storage, and the Ethereum Blockchain-based proof of authority is leveraged to expedite data storage processes. As a practical demonstration, we apply the HealthLink system to diabetes management, presenting execution results through system interfaces. Experimental findings highlight substantial enhancements in the security of healthcare systems compared to conventional methodologies, underscoring the potential of HealthLink to revolutionize remote patient monitoring and data security in healthcare. © 2024 IEEE.

关键词： Remote patient monitoring

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Strategies for Data Security and Privacy Protection in Cloud Infrastructure 3

Strategies for Data Security and Privacy Protection in Cloud...

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Naikwade, Namrata Pathan, Shafi Mit Art Design and Technology University Dept. of Computer Science & Engineering Pune India

ISBN: (纸本)9798350354348

In today's rapidly growing digital era, cloud computing has emerged as an important technology, providing the ability to scale resources efficiently, accessibility, and cost-effectiveness for storing and processing huge amounts of data. However, alongside its numerous benefits, the adoption of cloud computing has also introduced deep concerns regarding data protection and privacy. The current scenario of cloud computing is characterized by increase in usage of cloud services and an exponential growth of data. While organizations leverage the cloud to enhance agility and innovation, the data sharing ability of cloud and the outsourcing of data management raise significant challenges for ensuring the privacy, integrity, and availability of sensitive data. Moreover, the rising cyber threats, regulatory compliance requirements, and the possibility for unauthorized access bring out the critical importance of robust data protection mechanisms in the cloud *** paper presents a comprehensive survey of strategies for data protection and identity protection in the context of cloud based systems. It examines encryption techniques, access control mechanisms, identity management solutions, among other approaches, highlighting their strengths, limitations, and applicability in different cloud deployment models and use cases. Furthermore, the paper discusses emerging trends such as homomorphic encryption, Attributes Based Encryption (ABE) Schemes and Identity Based Encryption (IBE), which hold promise for enhancing data protection in the developing landscape of cloud technology. © 2024 IEEE.

关键词： Cloud security

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Adaptive Forward Error Correction for Voice over IP with Random Linear Network Coding 2

Adaptive Forward Error Correction for Voice over IP with Ran...

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2nd IEEE Virtual Conference on Communications, VCC 2024

作者： Su, Yi-Chiuan Wu, Quincy National Chi Nan University Dept. of Computer Science and Information Engineering Nantou Taiwan

ISBN: (纸本)9798331530099

This paper proposes the use of Random Linear Network Coding (RLNC) as an erasure code in the forward error correction (FEC) mechanism for Internet telephony. It also designs and implements a forward error correction algorithm applied to the Real-time Transport Protocol (RTP), which we call Adaptive Systematic RLNC (AS-RLNC). The algorithm learns the current packet loss rate of the network through the Real-time Transport Control Protocol (RTCP) and dynamically adjusts the number of redundant packets sent. Compared with traditional forward error correction methods based on block codes, this approach can enhance the reliability of data transmission and improve audio quality by 31%. © 2024 IEEE.

关键词： Internet telephony

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Exploring Large Language Models for Semantic Analysis and Categorization of Android Malware 40

Exploring Large Language Models for Semantic Analysis and Ca...

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40th Annual computer Security Applications Conference Workshops, ACSACW 2024

作者： Walton, Brandon J Khatun, Mst Eshita Ghawaly, James M Ali-Gombe, Aisha Louisiana State University Dept. of Computer Science and Engineering Baton Rouge United States

ISBN: (纸本)9798331532819

Malware analysis is a complex process of examining and evaluating malicious software's functionality, origin, and potential impact. This arduous process typically involves dissecting the software to understand its components, infection vector, propagation mechanism, and payload. Over the years, deep reverse engineering of malware has become increasingly tedious, mainly due to modern malicious codebases' fast evolution and sophistication. Essentially, analysts are tasked with identifying the elusive needle in the haystack within the complexities of zero-day malware, all while under tight time constraints. Thus, in this paper, we explore leveraging Large Language Models (LLMs) for semantic malware analysis to expedite the analysis of known and novel samples. Built on GPT-4o-mini model, MalParse is designed to augment malware analysis for Android through a hierarchical-Tiered summarization chain and strategic prompt engineering. Additionally, MalParse performs malware categorization, distinguishing potential malware from benign applications, thereby saving time during the malware reverse engineering process. Despite not being fine-Tuned for Android malware analysis, we demonstrate that through optimized and advanced prompt engineering MalParse can achieve up to 77% classification accuracy while providing highly robust summaries at functional, class, and package levels. In addition, leveraging the backward tracing of the summaries from package to function levels allowed us to pinpoint the precise code snippets responsible for malicious behavior. © 2024 IEEE.

关键词： Android malware

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Using Blockchain for Incentive-Driven FHIR-based Health Record Exchange 24

Using Blockchain for Incentive-Driven FHIR-based Health Reco...

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39th Annual ACM Symposium on Applied Computing, SAC 2024

作者： Rosar, Moritz Chuang, Kun-Ta Dept. of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9798400702433

Medical data is highly sensitive data, and patients are particularly concerned about the exposure of their identities [1]. A study found that 64% of participants were agreeable to sharing their health data when anonymized, highlighting the importance of privacy in medical data sharing [5]. © 2024 Copyright held by the owner/author(s).

关键词： Sensitive data

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Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions 40

Vertical Validation: Evaluating Implicit Generative Models f...

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40th Conference on Uncertainty in Artificial Intelligence, UAI 2024

作者： Elkady, Mai Bui, Thu Ribeiro, Bruno Inouye, David I. Computer Science Dept. Purdue University West LafayetteIN United States Electrical and Computer Engineering Dept. Purdue University West LafayetteIN United States

There has been a growing excitement that implicit graph generative models could be used to design or discover new molecules for medicine or material design. Because these molecules have not been discovered, they naturally lie in unexplored or scarcely supported regions of the distribution of known molecules. However, prior evaluation methods for implicit graph generative models have focused on validating statistics computed from the thick support (e.g., mean and variance of a graph property). Therefore, there is a mismatch between the goal of generating novel graphs and the evaluation methods. To address this evaluation gap, we design a novel evaluation method called Vertical Validation (VV) that systematically creates thin support regions during the train-test splitting procedure and then reweights generated samples so that they can be compared to the held-out test data. This procedure can be seen as a generalization of the standard train-test procedure except that the splits are dependent on sample features. We demonstrate that our method can be used to perform model selection if performance on thin support regions is the desired goal. As a side benefit, we also show that our approach can better detect overfitting as exemplified by memorization. © 2024 Proceedings of Machine Learning Research. All rights reserved.

关键词： Generative adversarial networks

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Sea Erosion Prediction and Monitoring Using IOT and ML 2

Sea Erosion Prediction and Monitoring Using IOT and ML

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2nd International Conference on Recent Trends in Microelectronics, Automation, Computing, and Communications Systems, ICMACC 2024

作者： Usha Bala, V. Harshavardhan Sai, Y. Slipa Shramila, V. Asritha, M. Bharath, M. Chandu, A. Anil Neerukonda Institute of Technology & Sciences Dept. of Computer Science & Engineering Visakhapatnam India

ISBN: (纸本)9798350366570

One of the major environmental issues that the world is currently facing is sea erosion, which requires an innovative solution for early detection and mitigation. Our paper focuses on the integrated system that combines both IoT and Machine Learning. The four main important environmental factors that are responsible for sea erosion are temperature, wave height, wave speed, and soil moisture. IoT sensors deployed along the prototype design are used to monitor these environmental parameters. Another key component is the machine learning algorithm, which is used analyse the interactions, patterns, and relations among the environmental data. By analysing the patterns among the previous data, the model can predict the likelihood of sea erosion events. This allows for the early detection of erosion events and timely interventions that can minimize the damage or loss caused by sea erosion. The main aim of this project is to help the coastal management authority take smart decisions and proactive steps using both real-time and past data analysis. © 2024 IEEE.

关键词： Soil erosion

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