the intrinsic redundancy of large-scale control systems allows to differentiate between the nominal system configuration, where the dynamics of the plant are controlled through a specific subset of actuators, and the ...
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ISBN:
(数字)9781728159539
ISBN:
(纸本)9781728159546
the intrinsic redundancy of large-scale control systems allows to differentiate between the nominal system configuration, where the dynamics of the plant are controlled through a specific subset of actuators, and the possible configurations that arise from the combination of all the existing actuators (nominal plus back-up ones). After the occurrence of an unexpected event (component fault, isolation of a specific area due to security concerns, etc), some of the back-up system actuators can be used in order to guarantee that the system performance will remain within some admissible margins. thus, given a scenario that causes a non-admissible system operation withthe nominal configuration, the possibility to use back-up actuators in order to improve the system performance expands the traditional fault tolerant control scenario defining a new problem. Accordingly, this work is devoted to the introduction of the problem which is solved by formulating the actuator selection as a mixed-integer programming optimization. A water distribution network is used withthe aim to illustrate the new problem implications as well as to demonstrate the validity of the proposed solution.
Technological developments in information and communication (ICT) have completely changed a paradigm in computing. the creation of several new communication channels, including the Internet of things (IoT), is a conse...
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ISBN:
(数字)9798350372816
ISBN:
(纸本)9798350372823
Technological developments in information and communication (ICT) have completely changed a paradigm in computing. the creation of several new communication channels, including the Internet of things (IoT), is a consequence of these advancements. Sensitive data can be transmitted between medical devices using the Internet of Medical things (IoMT), it serves as a component of the Internet of things. However potential dangers such as internet hijackings, impersonation, lack of service violence, password inference, and man-in-the-middle make security a problem, IoT technology for healthcare improves patient contact and treatment. Safeguarding IoMT ecosystem against malware attacks is crucial for patient safety and maintaining high touch and care. this paper presents a method to detect cyber-attacks in the medical field using Multiagent Reinforcement learning. Initially, data for processing is collected from the NSL-KDD and preprocessed using Improved generative Adversarial Imputation Network (I-GAIN) for missing value replacement. Ordered Quantile normalization (ORQN) is used to converts an arbitrary vector into a normal (Gaussian) vector. then, t-distributed stochastic neighbor embedding (t-SNE) is then used to reduce the dimensionality of the dataset. Number of components in t-SNE is optimally selected using the Zebra Optimization Algorithm (ZOA). Multiagent Reinforcement learning (MARL) is a technique utilized to detect data attacks based on the simulated environment. According to simulated research, the proposed approach achieves 95.3% accuracy, 4.7% error, and 93.5% precision. the developed technique outperforms existing methods in performance, resulting in a better prediction to detect cyber-attack in medical data.
the current situation of environmental resources requires their efficient usage through efficient process control. But, process control can not be achieved without an essential component: the communication between all...
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ISBN:
(纸本)9781467361408
the current situation of environmental resources requires their efficient usage through efficient process control. But, process control can not be achieved without an essential component: the communication between all devices, such as sensors, controllers, actuators, programming stations etc. the aim is to achieve the irrigation process of plants in greenhouse conditions. therefore, it is submitted a comprehensive application that proposes to be a distributed control system including data acquisition and processing, both local and remote monitoring of the process parameters. the distributed system is based on modern equipment: Siemens Simatic PLCs and HMI, Memsic e̅Ko Pro wireless sensors network, level sensors for irrigation tanks and actuators such as on/off valves and pumps. In terms of communication between equipments, an industrial bus and protocols were used - Profinet and wireless communication. the software part is provided by TIA Portal with STEP 7 and WinCC flexible RT and LOGO! Soft Comfort for programmingthe automation devices. ModbusTCP was used to develop the communication protocol between central devices.
Energy system choices for zero-carbon parks are challenged by the drive towards a low-carbon transition. Traditional wind-power-gas integrated energy systems centred on natural gas and combined heat and power (CHP) ar...
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ISBN:
(数字)9798350384093
ISBN:
(纸本)9798350384109
Energy system choices for zero-carbon parks are challenged by the drive towards a low-carbon transition. Traditional wind-power-gas integrated energy systems centred on natural gas and combined heat and power (CHP) are limited by high carbon capture and storage costs. the aim of this study is to assess the economic viability of an innovative hydrogen-electricity coupled integrated energy system centred on hydrogen production from renewable energy sources and to conduct a comparative analysis with conventional systems. the study begins withthe collection of historical data on wind speed and solar radiation in the park over a number of years, which is used to analyse the output characteristics of the wind and photovoltaic systems in depth, providing a solid data base for the optimal design of the hydrogen-electric coupled system. Next, a techno-economic model was constructed to meet the park's demand for electricity, heat and transport energy. the capacity of each component in both systems was optimally configured to reduce the annualised cost of the system through a mixed integer linear programming (MILP) approach. Based on this, a comprehensive techno-economic analysis was conducted to compare the economic indicators of the two systems. the results of the analyses show that the hydrogen-electric coupling system has significant economic advantages, including a higher net present value (improved by 70.79%), a shorter payback period (reduced by 6.61%), and a higher internal rate of return. Sensitivity analyses further revealed the main factors affecting the economics of the hydrogen-electric coupling system, including the demand for hydrogen from vehicles in the park, electrolyser costs and wind turbine costs. the findings of this study provide an important reference for planning and decision-making on the energy system of a zero-carbon park and highlight the potential of hydrogen in the future energy supply of the park.
In this paper, benefiting from the strong ability of deep neural network in estimating non-linear functions, we propose a discriminative embedding function to be used as a feature extractor for clustering tasks. the t...
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In this paper, benefiting from the strong ability of deep neural network in estimating non-linear functions, we propose a discriminative embedding function to be used as a feature extractor for clustering tasks. the trained embedding function transfers knowledge from the domain of a labeled set of morphologically-distinct images, known as classes, to a new domain within which new classes can potentially be isolated and identified. Our target application in this paper is the Gravity Spy Project, which is an effort to characterize transient, non-Gaussian noise present in data from the Advanced Laser Interferometer Gravitational-wave Observatory, or LIGO. Accumulating large, labeled sets of noise features and identifying of new classes of noise lead to a better understanding of their origin, which makes their removal from the data and/or detectors possible.
Due to growth of AI enabled IOT devices, their use in sports feature identification can be beneficial in terms of recognition quality. Computer Vision is a powerful tool for moving object recognition and tracking. Foo...
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this paper presents the development of a robot that can be controlled semi-autonomously and has the capability to detect toxic and combustible gases. the purpose of this research is to develop a semi-autonomous robot ...
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ISBN:
(纸本)9781665401685
this paper presents the development of a robot that can be controlled semi-autonomously and has the capability to detect toxic and combustible gases. the purpose of this research is to develop a semi-autonomous robot that can detect gases that are harmful to human workers. the robot is designed to be able to function properly with little human intervention. It has the ability to detect specified types of gases inside a confined space and move on its own to cover the specified operating area. the study is composed of component designing, programming, calibration, development of the user interface, fabrication, initial gas concentration test, mobility tests, and actual tests. the design of this robot is an improvement of the previous model. the mobility and semi-autonomous function of the robot is programmed using Raspberry Pi microcomputer and the sensors are programmed using the Arduino microcontroller. the gases that the robot can detect are alcohol (C2H6O), benzene (C6H6), hydrogen (H2), carbon monoxide (CO), LPG, and methane (CH4). the sensors that were used are MQ3 for alcohol and benzene, MQ7 for hydrogen and carbon monoxide, and MQ9 for methane and LPG. the results of the tests showed that the robot can operate semi-autonomously and in an omnidirectional manner easily. the actual testing procedures were done inside a confined parking area, printing shop, and LPG storage area.
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