Gaussian processes (GP) are becoming more and more popular way to solve statistics and machine learning problems. One of the reasons is the increase in computational power that can handle the inherent computational pr...
详细信息
ISBN:
(纸本)9798350311075
Gaussian processes (GP) are becoming more and more popular way to solve statistics and machine learning problems. One of the reasons is the increase in computational power that can handle the inherent computational problem for GP models. Still, in the case of big data, the computational burden can be impractical. For this reason, various approximation methods are developed. In our work, we would like to present an alternative to the internal approximation by using the properties of Chebyshev polynomials. The idea is to calculate the GP model only at Chebyshev nodes and use the property of transforming function values in them to Chebyshev coefficients giving a solution to the original problem. In our research, we propose our version of the algorithm and test it on cases of various functions.
This project introduces an innovative o industrial processcontrol using Programmabl controllers (PLCs) - an mication. The primary goal is to create a system that can monior and manage various physical parameters in r...
详细信息
A situation-aware wearable computing system is defined as a wearable device with the capability to perceive, comprehend, and project the situations occurring in the environment in order to adapt its behavior according...
详细信息
ISBN:
(纸本)9798350358513;9798350358520
A situation-aware wearable computing system is defined as a wearable device with the capability to perceive, comprehend, and project the situations occurring in the environment in order to adapt its behavior accordingly. For this kind of devices, the identification of complex situations related to the activities performed by users in various contexts is of great interest. This requires the capability to identify context states. A well-known technique for this task is the Context Space Theory (CST), which provides a multidimensional space representing contexts. Although powerful and lightweight, this technique has the drawback of requiring manual definition of such a space, a time-consuming process that involves domain experts. To address this issue, this work proposes a data-driven approach for defining context spaces in CST using kernel density estimation. This approach is compared with a state-of-theart expert-based CST technique and a fuzzy inference system for context representation, demonstrating superior performance on the Extrasensory dataset.
This study presents a method for simultaneously localizing and mapping magnetic fields (SLAM) via unscented Kalman filter (UKF) coupled with reduced-rank Gaussian process (GP) regression with the magnetic field measur...
详细信息
ISBN:
(纸本)9798331518509;9798331518493
This study presents a method for simultaneously localizing and mapping magnetic fields (SLAM) via unscented Kalman filter (UKF) coupled with reduced-rank Gaussian process (GP) regression with the magnetic field measurement. The goal is to enhance the efficiency and precision of magnetic field-based localization in environments with spatial variations. The approach first involves breaking down the magnetic field potential into a series of basic functions. By employing Reduced-Rank GP Regression, the representation becomes more stream-lined, leading to quicker computations and decreased storage needs. Then, two estimation techniques are compared: extended Kalman filter (EKF) and UKF filtering methods for estimating the states of the dynamic model. Simulation results indicate the effectiveness of the proposed methods in estimating the true dynamic states. Additionally, the proposed UKF design exhibits a slight improvement in accuracy at specific magnetic field length scales compared to the EKF approach.
This paper presents an effective online process fault diagnosis method by integrating recurrence plots (RP) with convolutional neural networks (CNN). To cope with the high dimension of process data, principal componen...
详细信息
ISBN:
(纸本)9798350360882;9798350360899
This paper presents an effective online process fault diagnosis method by integrating recurrence plots (RP) with convolutional neural networks (CNN). To cope with the high dimension of process data, principal component analysis (PCA) is applied to the original process data. RPs are then produced using the major principal components (PCs). As RPs are symmetric, this paper proposes to merge the two RPs for the first and second PCs into one to represent more information. The merged RPs serve as the inputs to a CNN, which is trained for fault diagnosis. The proposed fault diagnosis method is demonstrated on a simulated continuous stirred tank reactor (CSTR) system. It is shown that the proposed fault diagnosis system gives enhanced diagnosis performance.
Industrial automation systems are pivotal in enhancing the digitization and intelligence of the industrial sector. In recent years, wireless communication technologies (such as B5G/6G) and Cloud Fog automation (CFA) h...
详细信息
Industrial controllers and plants are crucial tools for teaching in universities, colleges, and institutes to bridge the gap between academia and industry. This paper introduces a multi-functional industrial plant tha...
详细信息
ISBN:
(纸本)9783031533815;9783031533822
Industrial controllers and plants are crucial tools for teaching in universities, colleges, and institutes to bridge the gap between academia and industry. This paper introduces a multi-functional industrial plant that employs a programmable logic controller (PLC) for processautomation. The industrial plant consists of a pump, a heating system, various types of sensors (such as pressure and temperature sensors), and different valves (including manual acting, pneumatic, and proportional solenoid valves), which can be configured in different combinations to serve different processcontrol purposes. To expand the input and output capabilities and distribute the input/output (I/O) modules, a Siemens SIMATIC ET 200SP I/O system is connected to a Siemens SIMATIC S7-1200 PLC using Profinet communication networks. A case study is provided to verify the effectiveness of the processcontrol station.
The complexity of absolute time processcontrol in industries has increased. Despite this, these processes generally involve significant quantities of data that must be analyzed and controlled quickly to maintain the ...
详细信息
Robotic processautomation is an insightful way to manage work across those tasks for which Al can easily be categorized. Nowadays, with the help of the concord of Al (Artificial Intelligence) and RPA (Robotic process...
详细信息
Many human-computer interactions and automated processes are dependent on data. We need to correctly store data and retrieve data to support these processes. Large Language Models (LLMs) have made significant progress...
详细信息
ISBN:
(纸本)9798331518509;9798331518493
Many human-computer interactions and automated processes are dependent on data. We need to correctly store data and retrieve data to support these processes. Large Language Models (LLMs) have made significant progress in comprehension and reasoning. However, we have found that their ability to handle professional data is weak, which significantly limits their applications in automated processes and professional applications. These scenarios often involve a large number of similar data entries, which are challenging for LLMs such as ChatGPT-4 Omni. In this paper, we propose a Rational Intelligence Model that comprehends human experts' knowledge of data structure and process requirements of data, automatically extracts data from conversations with end users, and effectively stores the data and retrieves it for supporting the interaction and process. Experiments show that ChatGPT-4o can achieve 0% error in simple queries, 2.6% errors when data entries are out of order, and 38% errors when the queries are reasonably complex. However, with our proposed Rational Intelligence Model (RIM), we can achieve 0% error rate in all tests. RIM fundamentally changes software engineering and expert system development approaches. Instead of having a software engineer understand expert knowledge of data processing, this is now achieved by RIM, which means it is much more flexible, lower in cost, and requires much less development time.
暂无评论