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检索条件"任意字段=International Conference on Simulation and Modeling Methodologies, Technologies and Applications"

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“Optimizing Algorithmic Efficiency: Exploring Advanced Data Structures for High-Performance Computing”

“Optimizing Algorithmic Efficiency: Exploring Advanced Data...

引用

Computational Modelling, simulation and Optimization (ICCMSO), international conference on

作者： Lade. Gunakar Rao Erupaka Nitya Jyoshna Devi Kusumba K. Rajchandar S. Narasimha Murthy School of Computer Science and Artificial Intelligence SR University Warangal Telangana India Department of CSE(DS) CVR College of Engineering Hyderabad Telangana India Computer Science And Applications Government Degree College Warangal Telangana India Department of Computer Science and Engineering Hyderabad Telangana India

ISBN: (数字)9798350361391

ISBN: (纸本)9798350361407

This work explores advanced data structures as a means of optimizing algorithmic efficiency in high-performance computing. The search for faster and more scalable algorithms becomes essential as computing demands rise further. This paper explores state-of-the-art data structures intended to improve overall performance, memory usage, and computational speed. We hope to offer insights into the applicability and impact of various advanced data structures on high-performance computing tasks through a thorough review and analysis of them, including but not limited to self-balancing trees, hash tables, and advanced graph structures. The results of this study not only advance our theoretical knowledge of these data structures but also provide developers and researchers with useful advice on how to utilize algorithmic efficiency in quickly fully. It is important to remember that algorithmic urban planning is an interdisciplinary field that encompasses data science, computer science, urban planning, and many other fields. The goal of integrating algorithms and smart technologies is to build more efficient, sustainable, and liveable urban environments.[8].

关键词： Reviews High performance computing Computational modeling Scalability Urban planning Algorithmic efficiency Data structures

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Mycelium-Based ELM Emulation Utilizing Memristive Oscillating Cellular Automata

Mycelium-Based ELM Emulation Utilizing Memristive Oscillatin...

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IEEE conference on Nanotechnology

作者： Theodoros Panagiotis Chatzinikolaou Ioannis Tompris Ioannis K. Chatzipaschalis Iosif-Angelos Fyrigos Michail-Antisthenis Tsompanas Andrew Adamatzky Georgios Ch. Sirakoulis Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Department of Electronic Engineering Universitat Politécnica de Catalunya Barcelona Spain Department of Computer Science and Creative Technologies University of the West of England Bristol UK

ISBN: (数字)9798350386240

ISBN: (纸本)9798350386257

Engineered Living Materials (ELMs) represent a novel class of materials that possess intrinsic properties and capabilities inspired by living organisms. Among ELMs, fungal mycelium stands out due to its low-cost manufacturing process, ubiquity in nature, and significant environmental benefits owing to its biodegradability. modeling mycelium's complex behaviors challenges scientists due to its intricate natural phenomena, leading to the adoption of digital twins for accurate simulations and deeper insights. Memristors, with their unique state-transition capabilities and non-volatility, emerge as promising for implementing a low-power, efficient digital twin of mycelium, demonstrating versatility across various applications beyond conventional hardware limits. This paper explores the use of memristive nanoelectronic circuits to simulate the evolution of biological mycelium hyphae, introducing a novel computational approach, Memristive Oscillating Cellular Au-tomaton (MOCA), to model the dynamic behavior of mycelium. The MOCA design mirrors the activator and suppressor processes observed in reaction-diffusion systems, thus simulating mycelium tip growth and branching patterns. The simulation results demonstrate the successful propagation of oscillating signals across a MOCA grid, reflecting the biological pathways within mycelium.

关键词： Manufacturing processes Biological system modeling simulation Memristors Organisms Digital twins Nanobioscience

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Evolving Autonomous Navigation: A NEAT Approach for Firefighting Rover Operations in Dynamic Environments

Evolving Autonomous Navigation: A NEAT Approach for Firefigh...

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IEEE international conference on Electro-Information Technology

作者： D. Shrestha D. Valles Department of Computer Science Texas State University Ingram School of Engineering Texas State University

ISBN: (数字)9798350330649

ISBN: (纸本)9798350330656

This paper introduces a novel approach for automating rover navigation in dynamic environments, explicitly focusing on firefighting applications, using the NeuroEvolution of Augmenting Topologies (NEAT) [1]. The research leverages NEAT's capability to evolve intricate neural networks, aiming to create a sophisticated rover navigation system. This system is designed to adeptly maneuver through complex terrains, avoid obstacles, and locate humans in highrisk fire scenarios. The motivation for this research is rooted in the urgent need for advanced autonomous technologies in lifesaving operations, particularly firefighting, where a rapid, precise response is crucial. The system's performance is rigorously assessed through comprehensive simulation experiments, showcasing its ability to achieve superior navigation efficiency and convergence. Additionally, the research provides an in-depth analysis of the rover's evolved behaviors using various visualization tools such as charts, statistics, and heatmaps. The approach we have used, the NEAT-based solution, demonstrates promising potential, offering a more adaptable and practical approach for real-world firefighting and rescue missions.

关键词： Adaptation models Visualization Solid modeling Three-dimensional displays Navigation System performance Transfer learning

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Robust estimation of sparse EEG source based on Laplacian distribution

Robust estimation of sparse EEG source based on Laplacian di...

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IEEE international conference on Computational Intelligence and Virtual Environments for Measurement Systems and applications

作者： Yuzuo Liu Peiyang Li Ziyi Wang Xiaohui Gao Chengcheng Tang Yin Tian Chongqing University of Posts and Telecommunications Chongqing China Northwestern Polytechnical University Xi’an China

ISBN: (数字)9798350322996

ISBN: (纸本)9798350323009

Locating the neural electric current sources and calculating their magnitudes through scalp electroencephalography (EEG) offer a way to explore the transient brain activity inside the head. However, because the EEG recordings are inevitably influenced by the outliers caused by eye blinking artifacts and head movements, the inferred cortical source activity are usually biased, which may limit its applications in both neural science study and clinical analysis. In our current study, by assuming that the model noises of EEG inverse problem follow the Laplacian distribution and searching the optimal model coefficients in the sparse space, an outlier robust sparse source location method was proposed. To verify its robustness to complex noises and its effectiveness in capturing the activations of multiple cortical sources, we conducted a simulation experiment. By measuring the differences between the predefined cortical sources and the estimated ones through four indexes, we quantitatively assessed its performance. The experimental results consistently proved that comparing with commonly used source estimation technologies such as wMNE, sLORETA, FOCUSS, and LASSO, our proposed method can resist the influence of outliers efficiently and recovered the EEG sources closer to those predefined. These observations verified its powerful capability of offering an alternative for EEG source imaging, especially in the condition that the spiking noise are frequently occurred.

关键词： Laplace equations Noise Imaging Estimation Virtual environments Brain modeling Search problems

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Research on Signal Processing and Sensor Fusion Technology in Electrical Engineering Automation

Research on Signal Processing and Sensor Fusion Technology i...

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IEEE international conference on Civil Aviation Safety and Information Technology (ICCASIT)

作者： Rong Chen Zhenjiang Vocational Technical College Zhenjiang China

ISBN: (数字)9798350389418

ISBN: (纸本)9798350389425

This study introduces an electrical measurement system grounded in multi-sensor fusion. Through the incorporation of information fusion techniques and parallel computing strategies, the system achieves reconstruction and optimization. The system is designed with a dynamic clustering algorithm that effectively merges data from various sensors, thereby enhancing both the precision and real-time performance of the measurements. To validate the system’s effectiveness, this paper conducts simulations and carries out detailed data analysis of the simulation outcomes. The findings demonstrate that the proposed sensor fusion approach substantially increases the measurement accuracy of the electrical measurement system while maintaining robust stability in challenging environments. Furthermore, the system’s parallel computing capabilities notably boost processing efficiency, reducing the time required for data handling. These outcomes indicate that the signal processing and sensor fusion technologies explored in this research hold significant potential for applications in electrical engineering automation, offering a solid theoretical foundation and technical support for future engineering implementations.

关键词： Electrical engineering Automation Heuristic algorithms Computational modeling Electric variables measurement Signal processing algorithms Clustering algorithms Sensor fusion Signal processing Parallel processing

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Design and Development of a Miniaturized Multi-Frequency Microstrip Patch Antenna for IoT applications: Enhancing Bandwidth and Performance Through Slotted Geometry

Design and Development of a Miniaturized Multi-Frequency Mic...

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Microwave, Antenna and Communication (MAC), international conference on

作者： Sheetal Khanderao Ghorpade Santosh D Bhopale Dept. of Electronics and Telecommunication D.Y. Patil College of Engineering & Technology Kolhapur Maharashtra India

ISBN: (数字)9798350350104

ISBN: (纸本)9798350350111

This electronic document is a "live" template and already defines. This paper presents the design and development of a miniaturized multiband microstrip patch antenna operating in the wireless spectrum for IoT applications. With the requirement for multiple IoT devices that are compact in size and that operate below 6 GHz, there is a need to have compact size antennas without deterioration in performance. Thus, the antenna designed should be wideband with minimum size for operation at 2.4 GHz corresponding to the Wi-Fi frequency band. In this design, the approach used is slotted geometry, which reduces the dimensions of the antenna without performance compromise. modeling and optimization are carried out using the Mentor Graphics electromagnetic simulation software. The main performance parameters include bandwidth, gain, directivity, and return loss, which are analyzed and optimized. The present work focuses on the fabrication and validation of the simulated results using Vector Network Analyzer measurements. It is expected from this letter that a wideband microstrip patch antenna offering high bandwidth with positive gain should be realized with a compact form factor so as to easily deploy on an IoT device. In this respect, research is continuous contributions regarding the miniaturization of antennas for new wireless technologies, especially in the IoT domain.

关键词： Microwave antennas Geometry Wireless communication Performance evaluation Patch antennas Microstrip antennas Internet of Things Microstrip Wideband Wireless fidelity

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modeling and Intelligent Identification of Axis Orbit for Rotating Machinery Based on the Convolution Neural Networks 3

Modeling and Intelligent Identification of Axis Orbit for Ro...

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2020 3rd international conference on modeling, simulation and Optimization technologies and applications, MSOTA 2020

作者： He, Xiaofeng Liu, Xiaofeng Lu, Xiulian He, Lipeng Ma, Yunxiang Guo, Sheng Yang, Tao Jiangsu Frontier Electric Technologies Co Ltd Nanjing211102 China School of Energy and Power Engineering Huazhong University of Science and Technology Wuhan430074 China

Based on the high dimensional complex feature recognition capability of convolutional neural networks (CNN), this paper proposes a method for orbit intelligent identification of rotating machinery based on CNN. In this method, the orbit is purified based on the frequency-domain filtering algorithm. Then an algorithm for converting the vibration signal to the orbit matrix is proposed to construct the input matrix of CNN. Finally the classification model of the CNN is established to realize the automatic identification of the orbit of rotating machines. Case studies show that the proposed method has high identification accuracy over 85% on experimental data and good universality over 73% in field data identification. © Published under licence by IOP Publishing Ltd.

关键词： Rotating machinery

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Design and modeling of Spiral Circular Magnetic Probe for Near Field Measurements in CST Microwave Studio 26

Design and Modeling of Spiral Circular Magnetic Probe for Ne...

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international conference on Applied Electronics (AE)

作者： Abdulhameed, Abdulghafor A. Kubik, Zdenek Univ West Bohemia Fac Elect Engn Dept Elect & Informat Technol Plzen Czech Republic

ISBN: (纸本)9788026109730

This paper presents the designing, modeling, and simulation of the spiral circular magnetic field probe for near field measurements. Two configurations of this probe have been investigated using both reference boards - conventional and microstrip. Furthermore, this probe has a compact size of (4x5) mm(2) printed on an FR-4 substrate of 1.6 mm height. This probe's operation frequency covers a range from 1 MHz to 1 GHz, making it suitable to measure the electromagnetic interference in the near field region over PCB working at electromagnetic compatibility applications.

关键词： DUT EMC Application Magnetic Field Microstrip Probe

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Visual Sentiment-based on FER for Improving Feedback Analysis using Transfer Learning

Visual Sentiment-based on FER for Improving Feedback Analysi...

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international conference on Computing and Networking Technology (ICCNT)

作者： Kriti Jhadi Namita Tiwari Meenu Chawla CSE Department MANIT Bhopal India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Image sentiment analysis has recently become more popular than text sentiment analysis for making various judgments nowadays. Despite this, sentiment analysis based on images only provides sentiment polarities for input that might not accurately represent the user’s emotional state. The development of end-to-end image sentiment analysis methodologies has made extensive use of Transfer Learning(TL) techniques in recent times, and this trend is supposed to continue. Deep learning(DL) algorithms’ autonomous feature-learning capabilities have led to outstanding results in a variety of applications. Despite the challenges of image-based sentiment analysis, there is still significant potential for advancement. This research aims to improve feedback mechanisms using Facial Emotion Recognition(FER), by integrating emotional context with sentiment polarities,utilizing the well-known Deep Convolutional Neural Network(DCNN) VGG19, with its other deep features which enables the network to capture small fine details. By finetuning the VGG-19 architecture, Sentiment-Emotion detection and classification can be efficiently performed using the FER2013 dataset. The accuracy of the proposed method can reach up to $83.23 \%$, as demonstrated by a comparison of its results with various recent studies, This method makes it possible to analyze a person’s visual sentiments based on feelings and emotional patterns, which provides insightful information about the preferences, behaviors, and satisfaction levels of customers.

关键词： Sentiment analysis Visualization Emotion recognition Analytical models Adaptation models Accuracy Face recognition Transfer learning Tuning Context modeling

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Numerical simulation Study on Air-side of Diesel Locomotive Finned Tube Double Channel Radiator 3

Numerical Simulation Study on Air-side of Diesel Locomotive ...

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2020 3rd international conference on modeling, simulation and Optimization technologies and applications, MSOTA 2020

作者： Guan, Ying Cui, Hongjiang Li, Minghai School of Locomotive and Vehicle Engineering Dalian Jiaotong University Dalian Liaoning China

Based on the heat transfer and flow resistance of diesel locomotive radiator, the influence was studied about the cooling air inlet speed on heat transfer coefficient and pressure loss of finned tube double channel radiator with louver by using CFD method. Temperature field, speed field and pressure field distribution of radiator calculation results were analyzed. The radiator was tested at different cooling air inlet speed, compared test results with simulation results, the greatest relative error of the heat transfer coefficient and pressure loss were 7.21% and 7.72%, respectively. © Published under licence by IOP Publishing Ltd.

关键词： Tubes (components)

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