The proceedings contain 299 papers. The topics discussed include: time series modelling approach for predictive analytics;research on the recognition of accounting information distortion by random forest algorithm;rec...
ISBN:
(纸本)9798350318609
The proceedings contain 299 papers. The topics discussed include: time series modelling approach for predictive analytics;research on the recognition of accounting information distortion by random forest algorithm;reconstruction and update of 3D model of mechanical products based on 3D point cloud data;prediction of soil organic carbon content using machine learning based fuzzy C-means clustering;fault detection and classification in power transmission lines using discrete wavelet transform-based swish recurrent neural network;immersive dramatic space 3D layout using panoramic image reconstruction algorithm;multi-objective optimization of noise in a high-speed railway by a hybrid algorithm;new energy vehicle customer mining model based on machine learning algorithm;and robotization of agriculture using image processing techniques.
The proceedings contain 168 papers. The topics discussed include: communication induced checkpointing based fault tolerance mechanism – a review and CIAC-FTM framework in IoT environment;a semantic review on challeng...
ISBN:
(纸本)9781665462006
The proceedings contain 168 papers. The topics discussed include: communication induced checkpointing based fault tolerance mechanism – a review and CIAC-FTM framework in IoT environment;a semantic review on challenges, trends towards defensive ids in Internet of things;semantic segmentation in medical image based on hybrid Dlinknet and UNet;smart car - one stop for all automobile needs;hybrid cryptography algorithm for the internet of things based plant information security;5G network: architecture, protocols, challenges and opportunities;fiber Bragg grating temperature sensor and calibration scheme in high magnetic field environment : an application for aluminum electrolysis cell in potline;federated learning with blockchain: a study of the latest decentralized couple;an enhanced copy-deterrence scheme for secure image outsourcing in cloud;decentralized data privacy protection and cloud auditing security management;land registry and title management using blockchain and smart contracts;breast cancer modeling and prediction combining machine learning and artificial neural network approaches;and confluence of artificial intelligence and blockchain powered smart contract in finance system.
In response to the demands and harsh conditions of underwater environments, developing sensor networks and underwater Internet of Things (IoT) has paved the way for wireless communication, ocean exploration, and vario...
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The sensor Sharing Marketplace (SenShaMart) enables IoT applications to find IoT sensors, which are owned and managed by other parties, integrate them, and pay for using their data. To provide corresponding services t...
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ISBN:
(纸本)9798350339864
The sensor Sharing Marketplace (SenShaMart) enables IoT applications to find IoT sensors, which are owned and managed by other parties, integrate them, and pay for using their data. To provide corresponding services that implement that FAIR (Findable, Accessible, Interoperable, Reusable) principles of IoT, SenShaMart incorporates a specialized blockchain that manages all the information its services need to allow different parties in IoT to describe, query, integrate, pay for, and use IoT sensors and their data. The paper presents the SenShaMart's architecture, implementation, evaluation, and demonstration.
Traditional farm autonomous feeding robot path planning systems have low target detection accuracy, poor planning efficiency, and insufficient adaptability to environmental changes when facing complex farm environment...
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Blockchain and SDN are combined in the "DistB-SD Cloud" architecture to secure and execute cloud-integrated IoT data. Cloud computing Management and Services, distributed Secure Blockchain Methodology, SDN E...
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With the continuous development of train operation control technology, the iteration of train operation control systems has been accelerated, leading to an increasing workload of system testing. Currently, most system...
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The proceedings contain 216 papers. The topics discussed include: implementation of a wireless energy monitoring and databasing system using PLC;optimizing the integration of distributed generation, shunt capacitors, ...
ISBN:
(纸本)9798350387193
The proceedings contain 216 papers. The topics discussed include: implementation of a wireless energy monitoring and databasing system using PLC;optimizing the integration of distributed generation, shunt capacitors, and electric vehicle charging stations into radial distribution systems;comparative analysis of TFET structures for low power sensor design;comparison of PID tuning methods for buck converter system;frequency control of power system under denial of service attack;GACNNXAI: employing genetic algorithm-enhanced convolutional neural networks and explainable artificial intelligence and its applications;and implementation of a non-invasive PCB embedded Rogowski coil current sensor for control of high frequency GaN LLC resonant converter with active rectification.
The proceedings contain 21 papers. The topics discussed include: enhancing the performance of photonic crystal and gates with machine learning optimization;bitcoin price prediction based on financial data, technical i...
ISBN:
(纸本)9798350381580
The proceedings contain 21 papers. The topics discussed include: enhancing the performance of photonic crystal and gates with machine learning optimization;bitcoin price prediction based on financial data, technical indicators, and news headlines sentiment analysis using CNN and GRU deep learning algorithms;promoting cybersecurity knowledge via gamification: an innovative intervention design;modeling and verification of the causal broadcast algorithm using colored Petri Nets;GPU-based parallel technique for solving n-similarity problem in textual data mining;a novel approach for specification and verification of symmetric distributed algorithms using spin;optimizing geophysical workloads in high-performance computing: leveraging machine learning and transformer models for enhanced parallelism and processor allocation;and rational Jacobi kernel functions: a novel massively parallelizable orthogonal kernel for support vector machines.
In this paper, we investigate the efficacy of the divide and conquer approach for implementing distributed logistic regression and distributed support vector machine (SVM) algorithms for classification of large-scale ...
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ISBN:
(纸本)9798350372977;9798350372984
In this paper, we investigate the efficacy of the divide and conquer approach for implementing distributed logistic regression and distributed support vector machine (SVM) algorithms for classification of large-scale datasets. This approach is designed to handle datasets that exceed the capacity of a single processor, necessitating the partitioning of data into multiple subsets. Logistic regression or SVM is then applied to each subset, yielding individual local classifiers. Subsequently, a global classifier is derived by aggregating these local classifiers to make the final decision. We propose three strategies for the aggregation stage: voting based on predicted labels, averaging of real-valued predictions, and averaging of posterior probabilities. Our analysis reveals that for distributed logistic regression, probability averaging is the most robust approach and is therefore recommended. Conversely, in the context of distributed SVM, probability averaging requires additional modeling but has a minimal impact on the performance. Therefore, functional averaging is recommended instead.
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