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Design and analysis of APB and AHB Lite Protocol

Design and Analysis of APB and AHB Lite Protocol

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conference on modeling of Systems Circuits and Devices (MOS-AK India)

作者： I Hameem Shanavas P Akhil Reddy Milan M Baburaj N Chaitanya Krishna Nithin S Department of ECE MVJ College of Engineering Bengaluru India Department of ECE MVJ College of Engineering Bangalore India

ISBN: (数字)9798350395556

ISBN: (纸本)9798350395563

The Verification is very crucial in the VLSI segment. APB and the AHB Lite protocols are the prime focus in this paper. The AMBA consists of the APB (Advanced Peripheral Bus) and the AHB (Advanced High-performance Bus). Unlike the AHB, APB follow the non-pipelined convention. Inside the IC communication takes place between the master and the slave using both the models. Verilog language and testbench is used to perform synthesis and design. The data transfer is the most critical aspect that is very important in the communication process involving the master and the slave cells of the IC. Both APB and the AHB deal with the communication itself. The basic understanding of the APB and the AHB protocol is dealt with here and how efficiently the data is transmitted from the master to the slave is seen. We should always use a protocol that will transfer data at a higher speed, offer more modes of transmission, provide security to the data that is being transmitted and also ensure that less power is consumed in the entire process. If a protocol can satisfy all of the above properties, then it is ideal to use that protocol for our communication.

关键词： Technological innovation Protocols Codes Very large scale integration data transfer Security Integrated circuit modeling

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Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces 36

Tree ensemble kernels for Bayesian optimization with known c...

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36th conference on Neural Information processing Systems (NeurIPS)

作者： Thebelt, Alexander Tsay, Calvin Lee, Robert M. Sudermann-Merx, Nathan Walz, David Shafei, Behrang Misener, Ruth Imperial Coll London London England BASF SE Ludwigshafen Germany Cooperat State Univ Mannheim Germany

ISBN: (纸本)9781713871088

Tree ensembles can be well-suited for black-box optimization tasks such as algorithm tuning and neural architecture search, as they achieve good predictive performance with little or no manual tuning, naturally handle discrete feature spaces, and are relatively insensitive to outliers in the training data. Two well-known challenges in using tree ensembles for black-box optimization are (i) effectively quantifying model uncertainty for exploration and (ii) optimizing over the piece-wise constant acquisition function. To address both points simultaneously, we propose using the kernel interpretation of tree ensembles as a Gaussian process prior to obtain model variance estimates, and we develop a compatible optimization formulation for the acquisition function. The latter further allows us to seamlessly integrate known constraints to improve sampling efficiency by considering domain-knowledge in engineering settings and modeling search space symmetries, e.g., hierarchical relationships in neural architecture search. Our framework performs as well as state-of-the-art methods for unconstrained black-box optimization over continuous/discrete features and outperforms competing methods for problems combining mixed-variable feature spaces and known input constraints.

关键词： Uncertainty analysis

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Hybrid modeling of Cyber-Physical Distribution Grids

Hybrid Modeling of Cyber-Physical Distribution Grids

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2021 IEEE International conference on Communications, control, and Computing Technologies for Smart Grids, SmartGridComm 2021

作者： Hassani, Sina Bendtsen, Jan Dimon Olsen, Rasmus Lovenstein Aalborg University Wireless Communication Networks Department of Electronic Systems Aalborg Denmark Aalborg University Automation and Control Department of Electronic Systems Aalborg Denmark

ISBN: (纸本)9781665415026

Penetration of distributed generation into distribution grids brings new demands for both centralized and distributed control at the low-voltage level. In particular, when trying to coordinate the production from distributed generation, communication becomes an important aspect of control design. However, whereas local control typically occurs at sub-second resolution, communication between geographically separate locations based on e.g., smart meter data, commonly takes place at much lower frequencies, such as on an hourly basis or even slower. Therefore, novel distribution grids should be analyzed and controlled within the context of cyber-physical systems. Hybrid systems, which cover systems that have both continuous and discrete dynamics, provide the natural setting for such analysis. In this paper, a hybrid model of the distribution grid considering both the continuous states of the power network and the discrete nature of the communication is presented, capturing the different update rates of centralized and local controllers in the modeling process. Simulation results show good agreement with data from a real-life system. © 2021 IEEE.

关键词： Hybrid systems

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Research on the Development of New Energy Electric Vehicles Based on Factor analysis and Intervention Optimization of LSTM Model

Research on the Development of New Energy Electric Vehicles ...

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control, Electronics and Computer Technology (ICCECT), IEEE International conference on

作者： Lijing Yang Yuhan Huang Hanlin Shi Zijing Yuan Chun Yuan Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9798350380958

ISBN: (纸本)9798350380965

Given the two-carbon strategy, the new energy vehicle industry is expanding rapidly. This paper studies the problems related to the development of new energy electric vehicles in China through modeling analysis. In this paper, the random forest algorithm is first used to evaluate the main factors affecting the development of new energy electric vehicles in China, and then the principal component analysis algorithm is used to determine the impact of each factor. The survey results show that the number of public charging stations, the number of state-supported policies and the level of population consumption are dominant; Then, we collected the development data of China's new energy electric vehicle industry, and used the Logistic algorithm to create an EV prediction model to predict the progress of China's new energy electric vehicles in the next ten years. Further, this paper collects data on electric vehicles powered by new energy sources and analyze their impact on the established global conventional energy vehicle industry. Using the VAR model, this study assesses possible correlations between the production and sales of new energy electric vehicles in China and globally. Subsequently, the functional equation of domestic and global joint production and sales of new energy electric vehicles is derived. The influence of policies restrict the development of new sustainable energy electric vehicles on the development of new sustainable energy electric vehicles in China is analyzed. First, the data that is not affected by the policy restriction, which is selected, and the rationality of the model is verified by LSTM algorithm. An intervention analysis model is introduced to optimize the LSTM model while considering the policy constraints. Through this optimized fitting process, the fitting results are consistent with the actual results, and the impact of policy restrictions on the development of new electric vehicles in China can be quantified.

关键词： Industries Analytical models Reactive power Fitting Production Electric vehicles Mathematical models

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Vehicle queueing model at signalized intersections in a random environment

Vehicle queueing model at signalized intersections in a rand...

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Computer Information Science and Application Technology (CISAT), International conference on

作者： Jiaxi Tang Department of Automation Lanzhou Jiaotong University Lanzhou Gansu China

ISBN: (数字)9798350375107

ISBN: (纸本)9798350375114

This study addresses the limitations of traditional vehicle queueing models in real-world traffic environments, in particular the lack of consideration for stochastic fluctuations in vehicle arrivals, by leveraging smart transportation and big data models. We have developed and presented a novel computational traffic queueing model that can dynamically simulate and quantitatively analyze the uncertainty and variability of vehicle arrivals, truly reflecting the complex situation in traffic flow. Detailed numerical experiments have shown that our model significantly outperforms traditional models when dealing with scenarios with rapidly changing traffic demands. It can capture and quantify various dynamic features of the queueing process in real-time, providing a more detailed and accurate interpretation of the queueing problem at high-traffic junctions. Moreover, this model provides more scientific decision support for traffic management, which can optimize signal control strategies at intersections and effectively respond to the challenges posed by demand fluctuations.

关键词： Fluctuations Uncertainty Computational modeling Stochastic processes data models Real-time systems Numerical models Smart transportation Vehicle dynamics Queueing analysis

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1st International conference on Advances in Signal processing and Communication Engineering, ICASPACE 2021

1st International Conference on Advances in Signal Processin...

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1st International conference on Advances in Signal processing and Communication Engineering, ICASPACE 2021

ISBN: (纸本)9789811955495

The proceedings contain 44 papers. The special focus in this conference is on Advances in Signal processing and Communication Engineering. The topics include: Single-Precision Floating-Point Multiplier Design Using Quantum-Dot Cellular Automata with Power Dissipation analysis;compression Techniques for Low Power Hardware Accelerator Design: Case Studies;sequence Set Design for Radar System;design of an All Digital Phase-Locked Loop Using Cordic Algorithm;analysis of Deep Learning Algorithms for Image Denoising;an Extensive Survey on Assessment of Multicore processors for Embedded Systems;image Segmentation Techniques and Optimization Algorithms for Lung Cancer Detection;handwritten to Text Document Converter;An Efficient Energy Aware for Reliable Route Discovery Using Energy with Movement Detection Technique in MANET;Lumped Circuit modeling at Nanoscale (Part-ii: Coupling Between Two Nanospheres);design and Implementation of Imprecise Adders for Low-Power Applications;speech processed Public Addressing System;an Approach Towards data Privacy Issues in Distributed Cyber Physical System;Classification of LPI Radar Signals Using Multilayer Perceptron (MLP) Neural Networks;a Systematic Review on Screening of Diabetic Retinopathy and Maculopathy Using Artificial Intelligence;Area Efficient and High-Throughput Radix-4 1024-Point FFT processor for DSP Applications;air Quality Monitoring System Based on Artificial Intelligence;an Improved Technique for Identification of Forgery Image Detection Using Clustering Method;EEG Signal analysis During Stroop Task for Checking the Effect of Sleep Deprivation;UWB Localization Procedures with Range control Methods—A Review;deep Learning Model for Multiclass Classification of Diabetic Retinal Fundus Images Using Gradient Descent Optimization;multilevel Authentication to Wireless Sensor Networks Against Malicious Attacks Using Butterfly Method.

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A Digital Twin modeling for the Production Line Optimized Management in the Soft and Deformable Food Sector

A Digital Twin Modeling for the Production Line Optimized Ma...

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IEEE International conference on Engineering, Technology and Innovation

作者： Stefano Croci Giovanni Mazzuto Marco Ortenzi Filippo Emanuele Ciarapica Maurizio Bevilacqua Gilberto Osler Department of Industrial Engineering and Mathematical Sciences Università Politecnica delle Marche Ancona Italy IT Manager - ICT Sant'Orsola s.c.a. Località Cirè di Pergine Valsuagana (TN) Italy

ISBN: (数字)9798350362435

ISBN: (纸本)9798350362442

The Production Logistics system is generally a large-scale complex system with various operational phases and management levels that must integrate. In the specific context of soft and deformable food products, the core of AGILEHAND European project, this complexity increases further due to challenges related to the handling and movement of such items. Efficient coordination of production and logistics phases becomes crucial to ensure product quality, prevent losses, and optimize the entire process. In this article, focus will be placed on a data-driven framework for the automated generation of simulation models, serving as the foundation for digital twins in intelligent factories within the previously mentioned sector. The proposed framework represents a multi-layered data-driven system designed for real-time/near-real-time simulation, planning and synchronization of production and logistics systems during line reconfiguration. The digital model forms the basis for a digital twin with simulation and optimization capabilities, designed to facilitate decision-making at various management levels in the production and logistics process and control activities such as changes, maintenance, quality and safety. Exploiting information provided by the Enterprise Traceability system, the digital twin aims to establish a real-time/near-real-time information flow. This flow enables accurate capturing of dynamics occurring in the physical layer and effective assessment of their negative effects on the overall operational state of the system in the digital layer. In this context, the use of the digital twin is intended to simplify and expedite the reconfiguration of production and logistics systems. This is achieved through the early detection of system design or process sequence through cross-sectional simulation.

关键词： Deformable models Technological innovation Biological system modeling Production Companies Digital twins Synchronization Sustainable development System analysis and design Logistics

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Comparative Performance analysis of SQL and NoSQL databases for Optimizing Retail and E-Commerce Operations

Comparative Performance Analysis of SQL and NoSQL Databases ...

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International conference on Communication and Electronics Systems (ICCES)

作者： Javid Iqbal Thirupattur Angel Xian Theng Tan Su-Lyn Lim Lauren Hyun-Ee Wong Mae Jhin Yong Sathishkumar Veerappampalayam Easwaramoorthy School of Engineering and Technology No. 5 Jalan Universiti Selangor Darul Ehsan Malaysia

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377989

Accelerated by the COVID-19 pandemic, the rapid growth of online retail, or electronic commerce, has transformed the way consumers fulfil their needs and desires. This expansion introduced new business opportunities that expedites international market growth. The digitalization of economy and consumer behaviour necessitates advancements in technologies and the selection of a database to process incoming customer data. The exponential increase in data has also increased the demand for robust and scalable database management systems. This paper aims to select the most suitable data model for online retail industries by conducting comparative analysis between relational, graph, wide-column, key-value, and document database models. The study explores the performance, strengths, and weaknesses of each model in handling various aspects of retail and e-commerce functionalities, including order processing and customer relationship management (CRM). Each database model is rigorously tested against thousands of records to accurately assess their effectiveness and performance within the retail industry. After deliberate testing, it is discovered that relational databases outshine the other NoSQL databases in terms of client performance - CPU speed in GHz, the CPU utilization and memory usage in percentage, and its capacity in handling large datasets in the e-commerce industry.

关键词： Industries Access control Analytical models databases NoSQL databases Biological system modeling Customer relationship management Relational databases data models Electronic commerce

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Mitigating Cyber-Security Risks using Cyber-Analytics

Mitigating Cyber-Security Risks using Cyber-Analytics

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International conference on Trends in Electronics and Informatics (ICEI)

作者： Abhishek Anand Abhijit Chirputkar P Ashok Symbiosis Institute of Digital and Telecom Management (SIDTM) Symbiosis International (Deemed University) (SIU) Lavale Pune Maharashtra India

Cybercrime is a global issue that has taken over the digital space. data is sent over networks every second, information is compromised, and systems are exposed to multiple threats. This paper on Cyber Security Analytics aims to deliver real-time analytics and operational intelligence in a simple format. Cyber Security Analytics includes real-time data collection, continuous monitoring of security controls, log processing and analysis, and immediate flagging of suspicious activity. This research study provides a fundamental platform for cybersecurity enthusiasts by detailing how to mitigate cybersecurity risks by utilizing a whole new and different perspective of AI and ML. This paper also focuses on IT issues that affect the real world. It also discusses potential vulnerabilities in an organization's IT infrastructure, networks, hardware, and software and reports on hacking attempts to develop more robust security procedures. This paper begins by understanding the various cybersecurity problems and challenges and how machine learning shapes cybersecurity analysis. This paper also considers multiple data science and predictive modeling applications in cybersecurity. This paper is expected to aid in developing predictive as well as detective modeling products and counter-cyber-attack solutions.

关键词： Shape process control Machine learning Predictive models Market research Real-time systems Software

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analysis of the Impact of Urban and Electric Power Big data Economy on Pollution Reduction and Carbon Reduction Based on Benchmark Regression Model

Analysis of the Impact of Urban and Electric Power Big Data ...

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Clean Energy Storage and Power Engineering (CESPE), International conference on

作者： Zixuan Qi Xiangyu Kong Yang Wang Yi Gao Shuai Luo Tianchun Xiang Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin University of Technology Tianjin China Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin China China State Grid Tianjin Electric Power Company Tianjin China Economic and Technical Research Institute of State Grid Tianjin Electric Power Company Tianjin China

ISBN: (数字)9798331511708

ISBN: (纸本)9798331511715

Currently, in promoting ecological civilization construction in China, the coordinated governance of pollution and carbon reduction is regarded as the core strategy and implementation focus. As a new economic transformation and upgrading model, the Electric power big data economy is becoming essential in promoting this process. The entropy method is used to construct evaluation indicators for the Electric power big data economy, pollution reduction, and carbon reduction. Subsequently, a benchmark regression model was built for testing based on carefully considering other variables that may affect pollution reduction and carbon reduction through benchmark regression analysis. Finally, exploring the diversity and specificity of the impact of the Electric power big data economy on pollution reduction and carbon reduction from different dimensions - regional economic differences, Electric power size classification, and specific backgrounds of each city's development stage aims to provide targeted strategic recommendations for policymakers, ensuring the coordinated promotion of the healthy development of Electric power big data economy and environmental protection goals.

关键词： Economics Analytical models Pollution Biological system modeling Urban areas Carbon dioxide Big data Benchmark testing data models Power systems

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