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Comparative Analysis of Flow and Cardano Blockchains: Navigating Adoption Challenges, Computing Techniques and Implications for the Blockchain Landscape

Comparative Analysis of Flow and Cardano Blockchains: Naviga...

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Computing Conference

作者： Bransia, Ayda Molnar, Balint Thompson, Simon Eotvos Lorand Univ Fac Informat Doctoral Sch Informat Budapest Hungary Eotvos Lorand Univ Fac Informat Informat Syst Dept Budapest Hungary Univ Kent Canterbury Kent England

ISBN: (纸本)9783031622793;9783031622779;9783031622762

This research compares and contrasts the capabilities, adoption barriers, and computing processes of the Flow and Cardano blockchains in detail. We investigate environmental sustainability, regulatory compliance, security, and scalability, as well as looking into data analysis, security enhancement, and quantum computing preparedness using computational approaches. Results demonstrate the distinct advantages and room for development of both platforms. Understanding how Flow and Cardano handle these issues is crucial for blockchain stakeholders in a quickly changing blockchain environment. Our study offers information that decision-makers, academics, and developers may use to better understand the trajectory of the blockchain ecosystem. We provide ideas for future study areas, innovations, and tactics to improve blockchain technology by examining the consequences of our analysis.

关键词： Cardano Flow Computation

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Central Bank Digital Currencies in the Global Economy: Lessons from China's Digital Yuan for the Development of the European Central Bank's Digital Euro 4th

Central Bank Digital Currencies in the Global Economy: Lesso...

引用

4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Benlemlih, Youssef El Hiri, Abderrazak Amina, Haoudi Sidi Mohamed Ben Abdellah Univ Fez Fes Morocco

ISBN: (纸本)9783031686528;9783031686535

The primary objective of this article is to provide a comprehensive examination of the Central Bank Digital Currency (CBDC), its potential benefits and the risks it might pose to traditional banking systems. To fulfil this objective, the article offers a holistic analysis of Central Bank Digital Currency (CBDC), examining risks inherent in traditional banking and the merits of CBDC adoption. It delves into the motivation behind increasing CBDC adoption by central banks and outlines various experimental programs. It mainly explores the digitalization of the Euro and the transformative potential of CBDCs on aspects like financial inclusion and monetary policy. Included within is an exploration of the wholesale CBDC with Bank of France followed by a practical example of the digital yuan within the Chinese economy. The research methodology encompasses a rigorous literature review, analysis of the research context, and retrieval of pertinent studies. The results and discussions section reveal critical findings and potential global financial impacts of CBDC. The article concludes with prospects and challenges of CBDC implementation, underlining its importance in financial systems' evolution.

关键词： Bank of France CBDC adoption Central banks Central Bank Digital Currency (CBDC)

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Sounds Prediction Instruments Based Using K-Means and Bat Algorithm 6th

Sounds Prediction Instruments Based Using K-Means and Bat Al...

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6th International Conference on Soft Computing and Data Mining (SCDM)

作者： Mohamed, Rozlini Samsuddin, Noor Azah Yusof, Munirah Mohd Univ Tun Hussein Onn Malaysia Batu Pahat 86400 Kagawa Malaysia

ISBN: (纸本)9783031669644;9783031669651

This study focuses on predicting sound categories in music datasets, employing classification to match predicted sounds with correct instrument categories. Sound classification in music datasets is challenging due to factors such as sampling and digital representation. Discretization at a sufficiently high rate helps preserve the original signal than ensures that classify all relevant information to appropriate group. This study proposes a novel approach that integrates K-Means clustering and the Bat Algorithm for efficient data discretization, aiming to improve sound category prediction accuracy. Unlike existing methods, our approach optimizes the data split points, leading to more informative and well-separated groups for classification. We tested our method with two classifiers, Naive Bayes and K-Nearest Neighbors, and observed significant improvements in classification performance compared to using raw data or other discretization methods. This approach offers a promising way to enhance the accuracy of sound prediction in music applications.

关键词： Bat Algorithm Discretization Prediction K-Means

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Smart Watch Assisted Multi-disease Detection Using Machine Learning: A Comprehensive Survey

Smart Watch Assisted Multi-disease Detection Using Machine L...

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International Conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Mujawar, Md Sami Salunke, Dipmala Mulani, Dastagir Gajare, Aadarsh Deshmukh, Pruthviraj Mane Ranjan, Nihar M. Tekade, Pallavi JSPMs Rajarshi Shahu Coll Engn Dept Informat Technol Pune India

ISBN: (纸本)9789819984756;9789819984763

Due to the proliferation of wearable technologies, it has become possible to collect vast amounts of data on personal health and wellness. Smartwatches, in particular, are becoming increasingly popular due to their ability to collect data on heart rate, blood pressure, sleep patterns, and also on physical activity levels. With this data, algorithms for machine learning can be trained to predict the likelihood of developing certain diseases, such as cardiovascular disease, sleep disorders, diabetes, respiratory diseases, and neurological disorders. This review study looks at the state of the art in studies on disease prediction using data from smartwatches. We begin by exploring the types of data that can be collected by smartwatches and the machine learning algorithms used to analyze this data. Then, we reviewed research that made use of data from smartwatches to predict specific diseases and examine the accuracy of these predictions which was lying between range of 98.54% to 75.33% using machine learning algorithms such as Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and many more such. Additionally, we discuss the potential benefits and limitations of using smartwatch data for disease prediction, including privacy concerns and the need for validation studies.

关键词： Smartwatch Wearables Disease detection

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Circular Intuitionistic Fuzzy Linear Regression Analysis: A Novel Approach for Modeling Uncertainty in Marketing Expenses and Revenues 1

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Traneva, Velichka Tranev, Stoyan Prof Asen Zlatarov Univ Prof Yakimov Blvd Burgas 8000 Bulgaria

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

Circular Intuitionistic Fuzzy Sets (C-IFSs) represent an extension of Intuitionistic Fuzzy Sets (IFSs), wherein each element is depicted as a circle in the IFS interpretation triangle rather than a point. Regression analysis serves as a predictive tool, commonly employed to quantify the causal relationship between two variables. We propose an extension of the traditional linear least squares approach by incorporating C-IFSs and the concepts of index matrices (IMs) to manage and analyze extensive IF datasets, referred to as CIFIM-LRA. Additionally, we introduce a criterion for assessing the adequacy of the CIFIM-LRA model. The study explores the relationship between monthly marketing expenses and revenues for Mladost Ltd in 2022, the leading manufacturer of pipe installation faucets in Bulgaria, using both the conventional and proposed CIFIM-LRA approaches. Decision-makers are presented with pessimistic, optimistic, and average scenarios to consider before making a final decision. The uniqueness of the article lies in the development of the CIFIM-LRA approach and its application to analyze the marketing costs and revenues of Mladost Ltd. in 2022.

关键词： Index Matrix Circular Intuitionistic Fuzzy Logic Regression

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A Game-Based Learning Approach for Enterprise Organization 14th

A Game-Based Learning Approach for Enterprise Organization

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14th International Conference on Learning Factories (CLF)

作者： Grimmel, Philipp Siemon, Lukas Posselt, Gerrit Mennenga, Mark Tech Univ Carolo Wilhelmina Braunschweig Inst Machine Tools & Prod Technol IWF Chair Sustainable Mfg & Life Cycle Engn Langer Kamp 19 B D-38106 Braunschweig Germany BeSu Solut GmbH Salzdahlumer Str 196 D-38126 Braunschweig Germany

ISBN: (纸本)9783031653995;9783031654008

Amidst a thriving entrepreneurial culture, understanding business organization is vital for emerging professionals. Practical implications of corporate structures and processes are hard to convey and must thus be experientially understood. The required knowledge is predominantly imparted in education through theoretical classes, in which participants often find themselves in a passive learning mode. Game-based learning approaches have demonstrated their efficacy in enhancing the understanding of intricate interrelationships present in both theoretical and application-based educational content. They thus provide a didactic supplement to foster holistic educational concepts in learning factories. This contribution proposes a game-based learning approach for application in lectures and courses with reference to enterprise organization. In the game, participants form start-up groups that follow the pathway of competing virtual companies that grow towards large companies. The companies' representatives face several organizational crises that are translated into team work tasks. Along the crises, companies merge according to participants' performance on the respective tasks. This realistically represents the communication and leadership challenges of growing companies. The approach has received positive feedback in a first trial and will be further extended.

关键词： Enterprise organization Game-based learning Learning environment Company growth dynamics

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Adaptive Controller Using Genetic Algorithm for Autonomous Wheeled Mobile Robot 28th

Adaptive Controller Using Genetic Algorithm for Autonomous W...

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2024 International Conference Automation

作者： Penar, Pawel Hendzel, Zenon Rzeszow Univ Technol Dept Appl Mech & Robot Fac Mech Engn & Aeronaut Rzeszow Poland

ISBN: (纸本)9783031782657;9783031782664

This paper presents the application of a genetic algorithm (GA) to the problem of tracking and stabilizing the motion of a wheeled mobile robot (WMR) operating under variable conditions. The proposed approach is to apply GA to adaptive control. Its novelty is the transformation of the parameter adaptation law into an iterative form, which allows the application of GA in real time. In addition, by introducing a supervisory control into the control signal, the asymptotic stability of the closed-loop control system can be obtained. This is confirmed by the simulation carried out, which indicates that the control system achieves a high degree of motion accuracy under varying operating conditions.

关键词： Adaptive control genetic algorithms supervisory control

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Development of a Biomechanical System for Rehabilitation Purposes of Bedridden Patients with Prolonged Immobility - Prototype and Preliminary Results 11th

Development of a Biomechanical System for Rehabilitation Pur...

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Roseiro, Luis Ribeiro, Tomas Silva, Marco Santos, Frederico Andre, Alexandra Duraes, Ruben Xavier, William Cruz, Armenio Malca, Candida Polytech Inst Coimbra Coimbra Inst Engn Rua Pedro Nunes Quinta Nora P-3030199 Coimbra Portugal Univ Coimbra CEMMPRE Ctr Mech Engn Mat & Proc P-3045043 Coimbra Portugal Polytech Inst Coimbra Coimbra Hlth Sch Rua 5 Outubro S Martinho BispoAp 7006 P-3046854 Coimbra Portugal Orthos XXI Rua Santa Leocadia 2735 P-4089012 Guimaraes Portugal Wiseware R 12 Lt 51 E Gafanha Da Encarnacao Portugal Nursing Sch Coimbra ESEnfC Hlth Sci Res Unit P-3000 Coimbra Portugal Polytech Inst Leiria Ctr Rapid & Sustainable Prod Dev Rua Portugal P-2430028 Marinha Grande Portugal

ISBN: (纸本)9783031456473;9783031456480

Citizens with physical limitations, mainly bedridden patients, cannot perform physical activity, which can translate into long periods of immobilization, with severe consequences for their health. This type of patient usually stays in bed for long periods, leading to getting several motor problems due to immobility. Thus, it is vital to develop biomechanical systems to implement physical rehabilitation activities for this type of patient. This work presents a prototype designed as Ablefit, created explicitly for bedridden patients, aiming to prevent complications associated with their immobility for long periods. The developed equipment is based on structural support and positioning unit, an active/passive linear module, and an active/passive rotary module, allowing them to perform different types of physical movements by the user. The work presented describes system requirements and the developed prototype's concept, emphasizing the equipment's mechanical system and its interface with the user. The first tests on the prototype of the system made it possible to identify the adjustments to be implemented and showed the possibility that it could represent an added value in physical motor rehabilitation procedures for bedridden patients.

关键词： Biomechanics of Rehabilitation Bedridden Mobilization Mechanical Interface with Patient

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Applying the Reverse Mode of Data Gathering to Improve Panoramic Radio Control 13th

Applying the Reverse Mode of Data Gathering to Improve Panor...

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13th Computer Science Online Conference

作者： Studenikin, Aleksey Tokarev, Anton Karimova, Gulmira Chernoiarova, Elena Chernoyarov, Oleg Voronezh State Tech Univ Moscow Ave 14 Voronezh 394026 Russia JSC IRCOS Rabochiy Ave 101B Voronezh 394049 Russia Kyrgyz State Tech Univ Manas Ave 66 Bishkek 720044 Kyrgyzstan Natl Res Univ MPEI Krasnokazarmennaya Str 14 Moscow 111250 Russia

ISBN: (纸本)9783031702846;9783031702853

Modern radio monitoring equipment (RME) is able to cover a very wide band of simultaneous analysis (BSA). Nevertheless, the frequency bands to be analyzed, as a rule, significantly exceed it in width. It necessitates the use of a panoramic analysis of the radio environment, which implies the cyclic scanning by RME equipment of a set of adjacent BSAs included in the analyzed frequency range (AFR). At the same time, the unidirectional data gathering mode is considered classic. According to it, firstly, the BSA set scanning in the frequency increasing direction is completed, and then the RME radio receiver is retuned to the AFR beginning, thus starting a new scanning cycle. However, such a mode is not the only possible one and, in some cases, it turns out to be suboptimal from the standpoint of data gathering efficiency and the probability of detecting signals such as, in particular, single radio pulses (SP). The goal of the work is to increase the efficiency of data gathering and the probability of signal detection by optimizing the RME data gathering mode. The reverse data gathering mode proposed in the work makes it possible to reduce the BSA data gathering interval, and thereby increase the efficiency of data gathering as well as the probability of SP detection. As a result, replacing the classic unidirectional data gathering mode with a reverse mode requires only the adjustment of the software that controls the tuning of RME heterodynes, taking into consideration that the "ARGAMAK-D11" RME model 4 application can increase the efficiency of data gathering by up to 95% and the probability of SP detection by up to 42% in the standard RME operating modes. Thus, the application of a reverse data gathering mode in the panoramic analysis of a radio environment enables the significant improvement of RME performance when detecting signals in wide frequency bands #CSOC1120.

关键词： Radio monitoring equipment Panoramic radio monitoring Band of simultaneous analysis Analyzed frequency range Data gathering Signal detection

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Design and Implementation of First-In-First-Out (FIFO) Buffer for Distributed Load Balancing systems 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Rathi, Ruchi Narkhede, Nitin Hasamnis, M. A. Shri Ramdeobaba Coll Engn & Management Nagpur India

ISBN: (数字)9789819713295

ISBN: (纸本)9789819713288;9789819713295

The rapid growth of digital data processing and communication systems has led to an increased demand for efficient data buffering techniques. The First-In-First-Out (FIFO) buffer has emerged as a fundamental building block for managing data flow between different components or modules in digital systems. Simple load balancer for distributed system uses FIFO in combination with other algorithms. Load balancing system is important for improving the performance of multimachine system. The proposed work presents the design, simulation, and FPGA implementation of a FIFO buffer, which can be used for distributed load balancing system, using the Verilog Hardware Description Language (HDL). The proposed FIFO buffer employs a modular and synchronous design approach to ensure reliable data storage and retrieval. The Verilog HDL design encompasses both behavioral and structural modeling, accurately representing the FIFO buffer's functional behavior and internal structure. Simulation using Verilog testbenches validates the correctness and performance of the FIFO buffer under different scenarios, assessing its ability to handle simultaneous read and write operations with empty and full status signals. The designed FIFO buffer is synthesized and implemented on a Xilinx Artix 7 FPGA board (xc7a100tcsg324-2). Synthesis results demonstrate the efficient resource utilization and good timing characteristics of the design. The implemented design is tested in real hardware, verifying its functionality and validating its performance against the simulation results. The designed FIFO buffer can serve as a vital component in data-intensive applications such as communication systems, digital signal processing, and memory interfaces.

关键词： FPGA Synchronous FIFO Load balancer Distributed environment Dual-port RAM VLSI

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