The Internet of Things (IOT) connects Tangible assets via data fusion facilitating information interchange. Ranging from basic temperature sensors to sophisticated industrial robots, IOT covers a wide range of applica...
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The proceedings contain 21 papers. The special focus in this conference is on High-Performance computing Systems and Technologies in Scientific Research, automation of control and Production. The topics include: Adapt...
ISBN:
(纸本)9783031510564
The proceedings contain 21 papers. The special focus in this conference is on High-Performance computing Systems and Technologies in Scientific Research, automation of control and Production. The topics include: Adaptive Methods for the Structural Optimization of Neural Networks and Their Ensemble for Data Analysis;self-adaptation Method for Evolutionary Algorithms Based on the Selection Operator;application of U-Net Architecture Neural Network for Segmentation of Brain Cell Images Stained with Trypan Blue;language Model Architecture Based on the Syntactic Graph of Analyzed Text;classic and Modern Methods of Automatic Parking control of Self-driving Cars;application of Smoothing Technique to Model Predictive Traffic Signal control;design Features of the Frequency-controlled Electric Drive for Positioning Mechanisms;Development of a Mathematical Model to Study the Energy Indicators of Electric Drives Using the DFC-IM System;intelligent Data Analysis for Materials Obtained Using Selective Laser Melting Technology;speech Enhancement Based on Two-Stage Neural Network with Structured State Space for Sequence Transformation;fourier Chromagrams for Fingerprinting, Verification and Authentication of Digital Audio Recordings;methodology of Expert-Agent Cognitive Modeling for Preventing Impact on Critical Information Infrastructure;designing a Graphics Accelerator with Heterogeneous Architecture;spectrophotometer for Field Studies;comparative Study of Practical Implementation of Time Delay Estimation Methods on Single Board Computer;study of the Functional Characteristics of TiNi Coatings by the Computer-Aided Simulation Using Parallel computing;on Hierarchical Convergence of the Heterogeneous Multiscale Finite Element Method Using Polyhedral Supports;parallelization of Finite-Volume Numerical Methods of Computational Fluid Dynamics by Means of Shared Memory computing Systems.
Factory automation is evolving from a hierarchical structure towards an interconnected architecture in which systems at different levels can communicate seamlessly with each other. This requires an appropriate replace...
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ISBN:
(纸本)9798350325621
Factory automation is evolving from a hierarchical structure towards an interconnected architecture in which systems at different levels can communicate seamlessly with each other. This requires an appropriate replacement of proprietary fieldbus systems in the automation sector. A promising solution to implement cross-plane end-to-end real-time capable communication between computing nodes is proposed in literature. The usage of Open Platform communication Unified Architecture (OPC UA) as the information model with the Publish-Subscribe (PubSub) communication mechanism in combination with Time Sensitive Networking (TSN) is presented to fulfill the requirements for message transmission. In contrast to the state of the art of configuring fieldbus systems, the configuration of such a real-time communication node has to be done manually. This process is complex, as deep knowledge in different domains is required. In this work we elaborate the requirements for such a communication node and present the resulting implementation challenges, which can be used as the basis for a configuration tool.
The growing adoption of bank automation technologies is bringing about a transformational shift in the global financial sector. The banking industry is seeing significant changes in traditional roles and duties due to...
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ISBN:
(纸本)9798350387919;9798350387902
The growing adoption of bank automation technologies is bringing about a transformational shift in the global financial sector. The banking industry is seeing significant changes in traditional roles and duties due to the growing integration of modern automation techniques such as robotic assistance, artificial intelligence (AI), and process automation by banking institutions. The rise of new job profiles such as AI data scientists, AI analysts, and robotics process automation specialists shows how the nature of work in the banking industry and the entire financial sector seems to be evolving. The increasing need for technical abilities has led to a greater focus on acquiring and developing a workforce with a distinct combination of technology proficiency and domain understanding. This paper investigated the extent to which the adoption of bank automation is a key determinant of the changing nature of work from a banking industry's perspective. Hence, a hypothetical path was developed to answer the following research question: How is adopting automation changing the nature of work in the banking industry? To answer this question, we considered the five largest banking institutions in South Africa. The findings revealed the paramount transformative changes that occur every time automation technologies are implemented.
In the era of advanced technology, students as well as teachers are more demanding innovative university campus life. Technologies like IoT and Cloud computing can provide solutions for smart and a sustainable campus ...
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Human emotion recognition plays a vital role in brain-to-brain communication, human-machine interactions and affective computing interfaces. This paper presents electroencephalogram (EEG) based emotion recognition usi...
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ISBN:
(纸本)9798350315684
Human emotion recognition plays a vital role in brain-to-brain communication, human-machine interactions and affective computing interfaces. This paper presents electroencephalogram (EEG) based emotion recognition using variational mode decomposition (VMD) and convolutional neural network (CNN) by finding optimal hyperparameters for recognizing three emotional classes: positive, neutral and negative. The two-stage VMD based EEG processing is proposed for effectively removing artifacts and noises from the EEG signal and also for decomposing EEG signal into five brain waves such as delta, theta, alpha,beta and gamma. The CNN based emotion recognition is presented based on the differential entropy feature extracted from 1 second brain waves instead of using brain waves directly in order to reduce size of CNN model. In this study, we created twelve CNN models using three number of layers (2, 5, and 7) and four activation functions with major objective of finding best CNN model(s). The standard SEED database is used to obtain trained CNN models and test their performance. Evaluation results show that the CNN architecture with rectified linear unit (ReLU) yielded higher accuracy of 90.33% among four activation functions. For predicting emotions of positive, negative and neutral, the CNN model with 2-layer and ReLU achieves an accuracy of 100%, 94.44% and 78.2%, respectively whereas the CNN model with 7-layer results in accuracy of 100%, 94.40% and 89.13%, respectively. This study also demonstrates significance of selecting optimal hyperparameters and best activation function.
This study explores a vision-based formation control algorithm for nonholonomic mobile robots operating under visibility constraints without relying on inter-robot communication. The camera used to monitor the leading...
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ISBN:
(纸本)9798331517939;9788993215380
This study explores a vision-based formation control algorithm for nonholonomic mobile robots operating under visibility constraints without relying on inter-robot communication. The camera used to monitor the leading agent has field of view (FOV) constraints, making it crucial to maintain real-time visibility for effective leading agent tracking. To address these challenges, we designed a barrier function based on the camera's pixel coordinates and showed that the control barrier function based quadratic programming satisfies both the visibility maintenance and nonholonomic property. The effectiveness of the proposed method is validated through simulations that demonstrate its ability to maintain visibility and achieve the desired formation.
This study explores the application of control Barrier Function (CBFs) for a dynamic constrained control for autonomous vehicle addressing road rules such as lane-keeping, lane changing, overtaking, and right-of-way. ...
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ISBN:
(纸本)9798350362350;9798350362343
This study explores the application of control Barrier Function (CBFs) for a dynamic constrained control for autonomous vehicle addressing road rules such as lane-keeping, lane changing, overtaking, and right-of-way. In particular, it shows the suitability of CBFs in encoding specific driving styles and strategies. This architecture doesn't need Vehicle-to-Vehicle (V2V) communication, relying only on vehicle and infrastructure sensors. Results from experiments in a simulated urban scenarios highlight the feasibility and efficiency of the proposed approach.
Intelligent surveillance robots dominate the entire world with its efficiency and accuracy helping in performing dangerous *** surveillance robot helps to survey the area. The violence keeps on growing day by *** pape...
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Existing fully distributed protocols for flocking are built upon the network of mobile agents with only cooperative interactions. Rather than investigating such networks, this paper deals with the problem of leader-fo...
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ISBN:
(纸本)9798331518509;9798331518493
Existing fully distributed protocols for flocking are built upon the network of mobile agents with only cooperative interactions. Rather than investigating such networks, this paper deals with the problem of leader-follower flocking control over signed communication networks, where there impose less restrictions on the distributions of cooperations and competitions in the network of mobile agents. Firstly, for the second-order dynamics model, a novel state feedback controller that relies only on the relative velocity information of neighboring agents is developed. Secondly, the solvability of flocking control problem is transformed to the asymptotic stability of error system, and the latter is guaranteed by treating the product convergence of infinite super-stochastic matrices. Then, sufficient condition for the solvability of flocking control problem is proposed by establishing the inequality constraints on positive and negative edge weights. Finally, a numerical example is performed to illustrate the correctness of the theoretical result.
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