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Towards the Acceleration of the Sparse Blossom Algorithm for Quantum Error Correction

Towards the Acceleration of the Sparse Blossom Algorithm for...

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1st international conference on Smart Energy Systems and Artificial Intelligence (SESAI)

作者： Venere, Marco Guerrini, Valentino Branchini, Beatrice Conficconi, Davide Sciuto, Donatella Santambrogio, Marco D. Politecn Milan Dipartimento Elettron Informaz & Bioingn Milan Italy

ISBN: (纸本)9798350364613;9798350364606

Quantum computing is a new computing paradigm that exploits laws of quantum mechanics to achieve an exponential speedup compared to classical logic. However, noise strongly limits current quantum hardware, reducing achievable performance. Quantum Error Correction (QEC) techniques are a valuable approach to reduce the effects of noise. Nevertheless, the high computational complexity of QEC algorithms is incompatible with the tight time constraints of quantum devices. Thus, hardware acceleration is paramount to achieving real-time QEC. This work represents the first step in the FPGA acceleration of the Sparse Blossom Algorithm (SBA), a state-of-the-art decoding algorithm for QEC. We provide a performance profiling and a design methodology for the hardware development of the SBA. We evaluate the execution time, and energy efficiency of our solution, attaining up to 2.75x speedup and 9.59x improvement in energy efficiency compared to the software baseline.

关键词： Quantum Error Correction Quantum computing Reconfigurable Architectures

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Smart Switch technology: IoT Integration with Touch Control for Improved Accessibility 1

Smart Switch Technology: IoT Integration with Touch Control ...

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1st international conference on Innovative Engineering Sciences and Technological Research, ICIEstR 2024

作者： Baloch, Farah Khaliq Abro, Ghulam E. Mustafa Alansari, Zainab Hitec University Electrical Engineering Department Taxila Cantt Rawalpindi Pakistan King Fahd University of Petroleum & Minerals Interdisciplinary Research Centre for Aviation and Space Exploration Dhahran Saudi Arabia University of Technology and Applied Sceicnes College of Computing and Information Sciences Muscat Oman

ISBN: (纸本)9798350348637

The internet of Things (IoT) has ushered in an era of transformative innovation, revolutionizing the way we interact with our surroundings. In the context of home automation, the IoT-Based Smart Switch with Touch Control project represents a leap forward in convenience and efficiency. This research explores the development and implementation of a switch board devoid of mechanical components, relying instead on touch sensors and advanced microcontroller technology. The aim is to create a touch-operated switchboard, of standard size and uncompromising reliability, with the potential to revolutionize everyday living. The research delves into the methodology, key components, beneficiaries, and the constraints involved in this innovative project. Moreover, it provides a detailed account of the project's first evaluation task and the technology used, including the PZEM Power Module, ESP8266 NodeMCU, and Home Assistant. This research illuminates the potential of IoT in simplifying and enhancing the lives of not only the technologically inclined but also senior citizens and the middle class, who may have been previously unable to afford high-cost switch boards with advanced functionality. © 2024 IEEE.

关键词： Microcontrollers

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Research on distributed storage Algorithm for Multi-Source Survey Data in Power Grid Engineering 3

Research on Distributed Storage Algorithm for Multi-Source S...

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3rd international conference on Artificial Intelligence, internet of Things and Cloud computing technology, AIoTC 2024

作者： Zhang, Jiyong Yu, Gao Liu, Donghui Sun, Xiaohu Huang, Jiangqian He, Bangzheng State Grid Economic and Technical Research Institute Co. State Grid Corporation of China Beijing China Economic and Technical Research Institute State Grid Zhejiang Electric Power Co. State Grid Corporation of China Zhejiang China School of Geomatics and Urban Spatial Information Beijing University of Civil Engineering and Architecture Beijing China

ISBN: (纸本)9798331530280

With the rapid development of power grid engineering, especially the rapid development of extra-high voltage engineering, the multi-source heterogeneous investigation data is on the increase, and the traditional investigation data storage methods can no longer meet the basic needs. Based on this situation, this paper adopts the consistent hash algorithm to achieve horizontal elasticity expansion of the storage system, and combines the virtual nodes of consistent hash with the weighted polling algorithm to improve the storage strategy of distributed file system (HDFS) under the Hadoop platform, to achieve balanced effect of distributed data storage. Experimental results show that the distributed storage algorithm for heterogeneous survey data from multiple sources proposed in this paper reduces the cluster load difference to different degrees under different conditions, and shows better load balance performance compared to HDFS and ordinary consistent hashing algorithms, which proves that the algorithm can effectively reduce the load difference between cluster nodes and satisfy the needs of distributed storage of power grid engineering survey data. © 2024 IEEE.

关键词： consistent hash algorithm distributed storage Survey data weighted polling algorithm

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Detection and Prevention Various Network Attacks Using Soft computing Approaches: An Overview 1

Detection and Prevention Various Network Attacks Using Soft ...

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1st international conference on AIML-Applications for Engineering and technology, ICAET 2025

作者： Deore, Mahendra Gosavi, Chhaya MKSSS's Cummins College of Engineering for women Department of Computer Engineering Pune India

ISBN: (纸本)9798350355611

The internet of Things (IoT) has emerged as a powerful tool for remote environmental monitoring, attracting considerable interest from the research community. Through IoT-enabled wireless technologies, various applications such as Intelligent Transport Systems (ITS), healthcare, home automation, and precision agriculture have benefited from enhanced monitoring capabilities. The functionality of IoT applications is centred around sensor nodes, which are deployed in the field to collect data and transmit it to a base station (BS) for processing. However, IoT networks that utilize Wireless Sensor Networks (WSN) face significant challenges. Two major issues are energy efficiency, which affects the longevity and performance of the network, and security vulnerabilities, which expose the system to a variety of threats such as sinkhole attacks, black hole attacks, and Denial of Service (DoS) attacks. These security concerns can severely disrupt communication and compromise the integrity of the data being transmitted. This survey paper focuses on examining recent security strategies designed to mitigate such threats in IoT networks. A systematic review was conducted to explore lightweight security solutions, with particular attention to trust-based and probe route-based mechanisms. These mechanisms offer promising approaches to safeguarding IoT networks while maintaining efficiency. The paper also presents a comparative analysis of these methods, evaluating them based on security techniques, types of attacks they address, and key performance metrics such as energy consumption and response times. The findings of this paper serve as a critical evaluation of the existing research, highlighting the strengths and limitations of the security measures reviewed. Through this comparative analysis, the study provides valuable insights into the effectiveness of various security approaches in protecting IoT-enabled networks from evolving cyber threats. © 2025 IEEE.

关键词： Probes

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Exploring Factors Influencing Energy Consumption Behavior Among Higher Education students Using Deep Learning 1

Exploring Factors Influencing Energy Consumption Behavior Am...

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1st international conference on computing, Sciences and Communications, ICCSC 2024

作者： Mishra, Amit Kumar Singh, Jagendra Yadav, Alok Kumar Diwakar, Manoj Singh, Prabhishek Lamba, Sumita Graphic Era Hill University Department of CSE Dehradun India School of Computer Science Engineering & Technology Bennett University Greater Noida India Naraina Vidya Peeth Engineering and Management Institute Department of Computer Science and Engineering Kanpur India Graphic Era Deemed to be University Department of CSE Dehradun India School of Computing DIT University Mussoorie India

ISBN: (纸本)9798350353648

This research examines the dynamics of university students' energy usage behaviour using internet of Things (IoT) technologies. The assignment meticulously positions a range of sensors in labs and lecture rooms and combines them with gadget learning algorithms to be able to maximize energy consumption. For a month, the internet of Things sends actual-time notifications to students approximately the need for careful strength management. Before the implementation observations provide a comparative evaluation of student behavior and draw interest to the subtle behavioural adjustments as a result of psychological shifts. Machine studying fashions are built to forecast destiny energy use by way of using the information generated by way of those processes. These fashions include Decision Trees, Random Forests, Support Vector Machines, and Artificial Neural Networks. The consequences display a noteworthy decrease in strength use with the IoT machine in region, highlighting the significance of technological interventions in encouraging environmentally pleasant behaviour. From an academic angle, this advances our expertise of strength behaviour and gives useful information to educational establishments trying to find creative techniques to implementing responsible electricity control. © 2024 IEEE.

关键词： students

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Anomaly Detection for IoT Security: Comprehensive Survey 1

Anomaly Detection for IoT Security: Comprehensive Survey

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1st IEEE international conference on Advances in Electronics, Communication, computing and Intelligent Information Systems, ICAECIS 2023

作者： Rokhade, Aditya Anil Vithapnavar, Amogh S Amruth, S. Shettigar, Akarsh Jayanth V Supreetha, S. Honnavalli, Prasad B Pes University Department of Cse Bengaluru India

ISBN: (纸本)9798350348057

The increasing adoption of the internet of Things (IoT) technology in various fields like smart home appliances, smart grids, health care systems etc., is transforming the way we live and work. But this has also called for a robust security mechanism and anomaly detection has been proven to be an effective solution to securing IoT devices. The rapid development in Machine learning, Deep Learning and related studies have brought rise to a lot of advanced methods to solve the anomaly detection problems. The objective of this paper is to discuss the challenges faced by smart devices that make use of IoT technology, in detecting anomalous behaviors in threat and risk analysis domains. This article could help readers better understand the common IoT security problems and countermeasures using anomaly detection techniques, as well as have an insight into the research trends, challenges and limitations in this domain. © 2023 IEEE.

关键词： internet of things

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Secure MAC-Based Two Way Authentication System (MTWAS) for Data Communication in internet of Vehicle 1

Secure MAC-Based Two Way Authentication System (MTWAS) for D...

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1st international conference on computing, Sciences and Communications, ICCSC 2024

作者： Singh, Dhananjay Kumar Bhardwaj, Diwakar Mathura India

ISBN: (纸本)9798350353648

The internet of Vehicles (IoV) is a rising area within the perspective of the Intelligent Transportation System (ITS) that has gained research emphasis in recent years. It enables the people involved in the network to make collaborative decisions. Huge-scale information monitoring, accumulating, and exchanging among automobiles, roadside units, and other intelligent components in the environment are all made possible by IoV, enabling dynamic and impromptu communication. Nevertheless, there are still many obstacles to overcome in terms of confidentiality and security for these IoV connections, making them more vulnerable to security breaches. The present research proposes an encrypted communication mechanism between automobiles and various other IoV smart components, along with a reliable and affordable Secure MAC -based Two Way Authentication System (MTWAS) in (/oV). Leveraging the BAN logic, we propose a strict verification of reliability and authenticity for the suggested (MTW AS) approach. The research culminates with both quantitative and qualitative assessments showing that the proposed approach outperforms than other recent state-of-the-art systems. © 2024 IEEE.

关键词： IoV security MAC - based verification security two way authentications in IoV vehicle authentication

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Parallel computing Optimization of Tourism Big Data based on Crawler Programs 1

Parallel Computing Optimization of Tourism Big Data based on...

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1st international conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Zhou, Xiaoyu Wuhan Donghu University School of Management Hubei Wuhan China

ISBN: (纸本)9798331529246

With the rapid development of the tourism industry, traditional tourism methods are undergoing significant transformation, and online tourism is gradually becoming a new highlight in the market. However, faced with the challenges of big data, online tourism data experiences tremendous pressure in terms of storage, computation, and management, and the issue of information overload seriously affects the user experience. Therefore, there is an urgent need for innovative platforms and recommendation algorithms to optimize the screening and recommendation of tourism information. This paper proposes an optimization scheme based on the Spark cloud computing platform to improve the efficiency of tourism data processing. First, utilizing Spark's distributed computing and memory management capabilities, tourism data can be stored and processed in a distributed manner, thus accelerating the computation speed of recommendation algorithms. Secondly, a Python-written crawler program is used to obtain real tourism data, including user ratings and comments on attractions, to evaluate the effectiveness of the improved algorithm. Finally, a weighted algorithm combining the LDA topic model is proposed. This algorithm analyzes the topic distribution of comment texts and weights the comments based on user ratings, calculating the predicted score for unrated attractions for the target user, thereby achieving accurate attraction recommendations. The experimental results show that the algorithm proposed in this study demonstrates significant advantages in prediction accuracy. © 2025 IEEE.

关键词： Cloud platforms

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SYstEM DEVELOPMENT MODELS EstABLISHMENT IN PRACTICE – A GROUNDED THEORY METHOD stUDY 21

SYSTEM DEVELOPMENT MODELS ESTABLISHMENT IN PRACTICE – A GRO...

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21st international conference on Applied computing 2024, AC 2024 and 23rd international conference on WWW/internet 2024, ICWI 2024

作者： Williamsson, Ia Askenäs, Linda Tsertsidis, Antonios Department of Information Technology Allégatan 1 Borås501 90 Sweden

ISBN: (纸本)9789898704627

Information technology is essential to most products and services, requiring effective software development process models (SPMs). However, academic models are often underused or slow to be adopted in real-world applications, highlighting a gap between development and practice and posing a challenge for model diffusion. This study aims to establish a theoretical framework for understanding the diffusion of SPMs. Data from 31 participants were analyzed using a grounded theory approach, incorporating the diffusion of innovations (DoI) theory to reinforce the findings. The grounded theory that emerged, referred to as "Establishment Patterns of Model Diffusion" (EPMD), highlights four key areas—Motivation, Establishment, Usage, and Quality—and examines how these elements interact and influence model diffusion. The study concludes that the diffusion process is shaped by the characteristics of these areas, the existing conditions, available knowledge, and the way these factors are assessed. The findings suggest that model diffusion follows complex, time-sensitive, and often unpredictable patterns. © 2024 Proceedings of the international conferences on Applied computing and WWW/internet 2024. All rights reserved.

关键词： Software design

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An Improving Intrusion Detection Model Based on Novel CNN Technique Using Recent CIC-IDS Datasets 2

An Improving Intrusion Detection Model Based on Novel CNN Te...

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2nd international conference on distributed computing and Optimization Techniques, ICDCOT 2024

作者： Selvam, R. Velliangiri, S. Srm Institute of Science and Technology Department of Computational Intelligence Kattankulathur Campus Chengalpattu India

ISBN: (纸本)9798350382952

The internet of Things (IoT) concept past far utilized in the past years, resulting in the establishment of Smart Cities. IoT has been A key player in a variety of sectors, including healthcare, Industry 4.0, smart transportation, home automation. Smart Cities are a relatively new concept that efficiently uses adaptive optimization of the resources at hand to offer people outstanding facilities. IoT devices are designed to gather information from the privilege of surroundings and send it to other systems over the internet. Cybersecurity risks including denial-of-service attacks, brute-force assaults, and unauthorized access might result from this. The safety and privacy of residents are the most pressing concerns that require attention. Deep learning-based IDS system. Data gathering from common datasets like CIC-IDS 2017 and CIC-IDS 2018 comprises multiple assault kinds. By using algorithms, pre-processing removes normalizations and missing values. Time stamps are selected and largely removed from an assault dataset using Random Forest (RF). Subsequently, essential traits are retrieved from those data using Deep Autoencoder (AE), after which among those many features. In this paper an appropriate comparison of the initial two datasets produced good findings for every deep learning system put to the test. Measurements in CIC IDS 2017 Precision, F1-score, and Recall were 99.5%, 98.7%, and 99.8%, respectively. For CIC IDS 2018, Precision, F1-score, and Recall were 99.5% for all algorithms. Our Novel CNN method yields the greatest outcomes. © 2024 IEEE.

关键词： internet of things

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