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Embedded Real-Time Human Activity Recognition on an ESP32-S3 Microcontroller Using Ambient Audio data 12

Embedded Real-Time Human Activity Recognition on an ESP32-S3...

引用

12th ieee international conference on intelligent data acquisition and advanced computing systems: Technology and Applications, IDAACS 2023

作者： Pfitzinger, Thomas Wohrle, Hendrik Dortmund University of Applied Sciences and Arts Dortmund Germany

ISBN: (纸本)9798350358056

The task of Human Activity Recognition (HAR) finds application in smart homes and assisted living and is mostly approached with machine learning. Sensor data for HAR is often collected and processed by separate devices. Performing the recognition task directly on the sensor device can decrease network traffic and reduce the related energy consumption and privacy concerns. In this work, an intelligent sensor device is developed that performs real-time HAR on an ESP32-S3 microcontroller using ambient audio data. A convolutional neural network to classify human activities is designed and subsequently reduced in size and computation cost in order to enable its inference on the microcontroller. This is achieved with neural architecture search, resulting in multiple simplified model variations. These are tested on the ESP32-S3 and a feasible version is identified. © 2023 ieee.

关键词： Embedded systems Human Activity Recognition Machine Learning Microcontrollers Neural Architecture Search

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Method of data Processing System Synthesis for Heterogeneous Distributed databases Based on Network-Centric Control 12

Method of Data Processing System Synthesis for Heterogeneous...

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12th ieee international conference on intelligent data acquisition and advanced computing systems: Technology and Applications, IDAACS 2023

作者： Mukhin, Vadym Kornaga, Yaroslav Zavgorodnii, Valerii Bazaka, Yurii Zavgorodnya, Anna Mukhin, Oleg National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of System Design Kiev Ukraine National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of Information Systems and Technologies Kiev Ukraine Igor Sikorsky Kyiv Polytechnic Institute Department of the Artificial Intellect National Technical University of Ukraine Kiev Ukraine

ISBN: (纸本)9798350358056

The methodology for the synthesis of a distributed computer system that includes the database was developed. There are suggested the new models for the data processing parameters evaluation and along with the analysis and forecasting of the functional parameters. The proposed methods for the number of data processing nodes determining in the systems with dynamic structure based on a network-centric control mechanism allows increase the efficiency of the heterogeneous distributed databases. The implementation of the proposed methodology allows synthesizing a distributed data processing system for processing requests to heterogeneous databases, taking into account the parameters of the nodes and the bandwidth of the channels between the nodes. © 2023 ieee.

关键词： characteristic heterogeneous distributed database method methodology for the synthesis node parameter

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Assessment of the Possibility of Using 5G to Build Telemedicine Networks in Various Environment 12

Assessment of the Possibility of Using 5G to Build Telemedic...

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12th ieee international conference on intelligent data acquisition and advanced computing systems: Technology and Applications, IDAACS 2023

作者： Talha, Saad Malik Siden, Serhii Tsaryov, Roman Nikityuk, Lesya State University of Intelligent Technologies and Telecommunications

ISBN: (纸本)9798350358056

The paper discusses the main requirements that arise when using 5G networks in telemedicine. First, in the paper investigate the network bandwidth requirements, as the transfer of large amounts of medical data, such as video consultations, medical images, and data from mounting devices, requires a fast and reliable connection. As a potential solution to this problem, proposed integration into the telemedicine network of segments based on 5G technology, which provide the necessary parameters to improve the efficiency and quality of telemedicine services. The main idea is to assess the capabilities of 5G technology from the point of view of solving the problem of creating a scalable telemonitoring platform. As part of this task, it is necessary to determine the possibilities of the fifth-generation technology for the organization of telemonitoring at the maximum possible distance while simultaneously ensuring a guaranteed data transfer speed, considering the simultaneous connection of a large number of devices and sensors. Capability analysis was performed for different environments (signal propagation models) and for different raw data. © 2023 ieee.

关键词： 5G propagation models telemedicine

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On Two Variants of Fuzzy Clustering for Relational data 13

On Two Variants of Fuzzy Clustering for Relational Data

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Joint 13th international conference on Soft computing and intelligent systems and 25th international Symposium on advanced intelligent systems, SCIS and ISIS 2024

作者： Saga, Shujin Kanzawa, Yuchi Shibaura Institute of Technology 3-7-5 Toyosu Koto-ku Tokyo135a-8548 Japan

ISBN: (纸本)9798350373332

In this paper, two fuzzy clustering algorithms are proposed for relational data. The first algorithm is obtained by regularizing a conventional algorithm for relational data, which is similar to how the Yang's penalized Fuzzy c-means can be regarded as regularizing the Bezdek's Fuzzy c-means. The second algorithm is obtained using the following two steps: First, separating the fuzzification parameter for membership and the cluster size controller in a conventional algorithm for relational data, second, regularizing the Tsallis-entropy. This procedure is similar to that a conventional algorithm for vectorial data can be regarded as separating the fuzzification parameter for the membership and that for the cluster size controller in that for another conventional algorithm and then regularizing the Tsallis-entropy. The features of our proposed algorithms are observed through numerical experiments using an artificial dataset. © 2024 ieee.

关键词： fuzzy c-means fuzzy clustering relational data

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Malware Detection By Distributed systems with Partial Centralization 12

Malware Detection By Distributed Systems with Partial Centra...

引用

12th ieee international conference on intelligent data acquisition and advanced computing systems: Technology and Applications, IDAACS 2023

作者： Savenko, Bohdan Kashtalian, Antonina Lysenko, Sergii Savenko, Oleg Khmelnytskyi National University Khmelnytskyi29016 Ukraine

ISBN: (纸本)9798350358056

The paper proposes approach to use new tools for malware detection in corporate networks, which are distributed systems with partial centralization. To make decision about malware presence, the components which includes specified decision-making for the system's center are defined as a decentralized subsystem. To determine the states of the system components, characteristic indicators are proposed, and generalized analytical expressions for their calculation are developed. Such calculations make it possible to assess the state of the components in the system in order to determine its further steps. As a result, the system is the basis for usage of different malware detection methods in combination with the system components as an integral sensor. To test the system, a worm-virus detection method was implemented and experiments were conducted. The results of experimental studies approved the efficiency of the proposed solution. © 2023 ieee.

关键词： distributed systems malware malware detection network security partial centralization worm-virus

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Composite Indicators Building Based on Concordant of Expert-Statistical Information Using Biased Ridge Kernel Regression 12

Composite Indicators Building Based on Concordant of Expert-...

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12th ieee international conference on intelligent data acquisition and advanced computing systems: Technology and Applications, IDAACS 2023

作者： Lyubchyk, Leonid Grinberg, Galyna Konokhova, Zoia Yamkovyi, Klym National Technical University Kharkiv Polytechnic Institute Computer Mathematics and Data Analysis Department Ukraine National Technical University Kharkiv Polytechnic Institute Marketing Department Ukraine

ISBN: (纸本)9798350358056

The problem of constructing a complex composite indicator based on expert scores and statistical information about particular indicators is considered. A procedure for estimating the parameters of a nonlinear model of a composite indicator based on the method of biased kernel ridge regression is proposed;at the same time, the problem of optimal concordant of expert and statistical information is solved by choosing the appropriate regularization functional. Using the method of Lagrange multipliers, expressions for estimating the parameters of a nonlinear model and a kernel-based model of a composite indicator are obtained. The results of a numerical experiment on the construction of a composite indicator model using real data are presented. © 2023 ieee.

关键词： composite indicator concordat expert assessment kernel model regularization ridge regression

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Traffic data Augmentation Using GANs for ITS 20

Traffic Data Augmentation Using GANs for ITS

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20th Annual international conference on Distributed computing in Smart Sensor systems and the Internet of Things (DCOSS-IoT)

作者： Dabboussi, Abdul Hamid Jammal, Manar York Univ Elect Engn & Comp Sci Toronto ON Canada York Univ Sch Informat Technol Toronto ON Canada

ISBN: (纸本)9798350369458;9798350369441

intelligent Transportation systems (ITS) play a pivotal role in shaping the foundation of smart cities, providing data-driven solutions for traffic management, prediction, and safety. However, these applications often face a significant challenge data scarcity. Insufficient data limits the effectiveness of machine learning models in the context of ITS. To address this issue, this paper presents a novel data augmentation solution using Generative Adversarial Networks (GANs). By collecting sensor-based traffic speed data with contextual labels and training a GAN-based model to generate realistic traffic data for specific days and times, this research successfully proposes a solution to the problem of data scarcity. The generated data undergoes comprehensive qualitative and quantitative evaluations, demonstrating its potential to enhance ITS applications. Furthermore, the generated data is utilized to augment the training data for multiple traffic prediction models, effectively enhancing their performance. This approach opens new avenues for the development of intelligent and sustainable transportation systems, ultimately contributing to the advancement of smarter and more resilient cities.

关键词： intelligent Transportation systems IoT Smart Cities GAN Wasserstein GAN Traffic Prediction Machine Learning

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Design and Implementation of Dynamic Secure Storage Algorithm Based on MongoDB and Blockchain 6

Design and Implementation of Dynamic Secure Storage Algorith...

引用

6th ieee international conference on Power, intelligent computing and systems, ICPICS 2024

作者： Cui, Xiaoxin Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350374315

The combination of blockchain technology provides an innovative solution to the widespread application and critical security challenges of big data in the current digital era. Therefore, this paper proposes a novel blockchain-based secure storage strategy for unstructured big data, which utilizes blockchain's distributed ledger technology to ensure the integrity and traceability of data storage, and strengthens the security protection of the data in the transmission and storage process by employing advanced encryption algorithms, such as asymmetric encryption and hash functions. Finally, we use MongoDB in conjunction with blockchain technology to realize a system architecture aimed at enhancing data confidentiality and tamper resistance through efficient encryption techniques. © 2024 ieee.

关键词： data integrity

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Principal Component Analysis Visualization and State Discovery with Soil data 12

Principal Component Analysis Visualization and State Discove...

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12th ieee international conference on intelligent data acquisition and advanced computing systems: Technology and Applications, IDAACS 2023

作者： Sirola, Miki Koskinen, Markku Polvinen, Tatu Pihlatie, Mari University of Helsinki HelsinkiFI-00014 Finland

ISBN: (纸本)9798350358056

data exploration helps to gain understanding of the dataset and the system itself. There are methodologies to handle large number of sensors as well. In this paper operational states are defined to interpret physical behaviour in a soil ecosystem. Dimensionality reduction is achieved with Principal Component Analysis (PCA) method giving another view to the soil dataset from spring term. K-means algorithm groups data densities by clustering the data. This grouping is the basis for defining operational states in the system. Soil data as a part of an ecosystem involves specific features. In the applied approach dynamic visualization including animations constitute an important exploration view. All experiments are realized in Jupyter programming environment with Python 3 programming language. Related literature about data visualization is reviewed. Combining methods and tools with this data as a result soil ecosystem features are recognized. © 2023 ieee.

关键词： Principal Component Analysis Soil data State Discovery Visualization

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PULRAS: A Novel PUF-based Lightweight Robust Authentication Scheme 20

PULRAS: A Novel PUF-based Lightweight Robust Authentication ...

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20th Annual international conference on Distributed computing in Smart Sensor systems and the Internet of Things (DCOSS-IoT)

作者： Yaqub, Zohaib Yigit, Yagmur Maglaras, Leandros Tan, Zhiyan Wooderson, Paul Edinburgh Napier Univ Edinburgh EH10 5DT Midlothian Scotland HORIBA MIRA Watling St Nuneaton CV10 0TU England

ISBN: (纸本)9798350369458;9798350369441

In the rapidly evolving landscape of intelligent Transportation systems (ITS), Vehicular Ad-hoc Networks (VANETs) play a critical role in enhancing road safety and traffic flow. However, VANETs face significant security and privacy challenges due to their high mobility, dynamic topology, and reliance on open wireless communication. This study addresses the critical question of enhancing the security and privacy of VANET communications amidst the challenges of high mobility, dynamic topology, and the threat of various cyber-attacks. This paper presents a comprehensive solution to enhance the security of VANETs by introducing a novel Physically Unclonable Function (PUF)-based authentication scheme. Our approach leverages the intrinsic security features of PUFs, integrating them with lightweight cryptography to fortify the network against physical acquisition attacks and ensure secure communication over potentially insecure channels. The proposed scheme is meticulously designed to address the unique security and privacy requirements of VANETs, offering a scalable and resilient framework for authenticating and managing the network's entities. Through an extensive evaluation using a realistic experimental setup, our solution demonstrates its efficacy in providing a secure, reliable, and efficient authentication mechanism for VANETs. The scheme balances computational efficiency with advanced security features, making it well-suited for the resource-constrained environment of vehicular networks.

关键词： Vehicular Ad-Hoc Networks Physically Unclonable Functions Lightweight Cryptography intelligent Transportation systems

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