Showing papers in "Lecture Notes in Electrical Engineering in 2022"
TL;DR: In this article , the authors present a comparison of contrasting maximum power point tracking algorithms centered on artificial intelligence and simulate a model under uniform and partial shading conditions using MATLAB/SIMULINK.
Abstract: AbstractSpeedy exaggeration of CO2 emissions stimulates global warming. In order to slow down global warming, ongoing hydrocarbon deposit systems need to be put back by renewable systems like solar and wind. In addition to above approach, upcoming grid is expected to cater developments like renewable energy production, intelligent energy management systems to satisfy extending requirements. The main motive is to boost efficiency of the renewable energy system; for this, PV systems are always provided with maximum power point tracking algorithm to make sure that PV module operates at its maximum power point. This chapter presents comparison of contrasting maximum power point tracking algorithms centered on artificial intelligence. A detailed comparison is carried out based on the review from available literature and by simulating a model under uniform and partial shading conditions using MATLAB/SIMULINK. The overall objective is to deduce an algorithm that is meaningful, intelligent, optimized, and efficient.KeywordsMaximum power point tracking (MPPT)Artificial intelligence (AI)Fuzzy logic control (FLC)Artificial neural network (ANN)Genetic algorithm (GA)Swarm intelligence (SI)Machine learning (ML)
9 citations
TL;DR: In this article , a method of interval modeling for the Cuk converter is proposed, where state space averaging (SSA) technique is used to find the output to control transfer function for CUK converter, the combined state space description is obtained by SSA technique.
Abstract: This paper proposes a method of interval modeling for the Cuk converter. State space averaging (SSA) technique is used to find the output to control transfer function for Cuk converter. The combined state space description is obtained by SSA technique. The deviation in physical parameters is present in system due to uncertainties and imperfect modeling. To consider the effect of parametric variations in system, the interval modeling for Cuk converter is done.
9 citations
8 citations
TL;DR: ICASPACE 2021 proceedings cover several theoretical and mathematical approaches addressing day-to-day challenges in signal, image, and speech processing as discussed by the authors , and discuss the challenges of signal processing.
Abstract: ICASPACE 2021 proceedings covers several theoretical and mathematical approaches addressing day-to-day challenges in signal, image, and speech processing
8 citations
TL;DR: In this article , a collection of research has been carried out to identify and collect artifacts of web browsers having secrecy features for examination, validation, and find out potential ways to use the collected information during active investigations.
Abstract: Web browsers are ubiquitous applications to access public and private applications over the Internet, Intranet, and Extranet. The increased demand for cybersecurity, including data privacy, secrecy, and anonymity, becomes the reason for enhanced privacy and anonymity in common web browsers and specialized web browsers to achieve such purposes. These features are great challenges and obstacles for forensic investigators. In this paper, a collection of research will be analyzed, that have been carried out to identify and collect artifacts of web browsers having secrecy features for examination, validation, and find out potential ways to use the collected information during active investigations. As a result, live forensics can become more relevant and dependable for collecting reasonable artifacts from private browsers. From common browsers using private browsing facilities, even removing web browsers after committing criminal activities can also be identified by analyzing the registry, supporting factual evidence gathering in any Digital Forensic investigation.
8 citations
7 citations
TL;DR: In this article , a combination BFPSO-based ANN controller is proposed to improve the power output of a grid-integrated solar photovoltaic (PV) farm with the help of a combination of a particle swarm optimization (PSO) tuned intelligent ANN controller.
Abstract: Renewable energy resources are non-pollution resources that can meet up the electricity needs without inflicting any environmental troubles. In this research work, Maximum Power Point Tracking (MPPT) behavior is taken into account for improving the power output for the grid-integrated solar photovoltaic (PV) farm with the help of a combination BFPSO tuned intelligent ANN controller. An Artificial Intelligence (AI)-based MPPT technique is utilized in solar PV arrays to maximize the electrical power output and satisfy the power demand. The combination BFPSO algorithm is selected for optimizing the connection weights in the ANN controller, and the developed ANN controller regulates the duty cycle of the DC/DC converter by monitoring the voltage and current profile of the solar PV farm. The developed optimization algorithm is implemented to get maximum feasible power from the 400 kW PV farm. Also, the proposed combination BFPSO tuned ANN controller is evaluated through means of predictable procedures like Particle Swarm Optimization (PSO), Bacterial Foraging Optimization Algorithm (BFOA). The simulation part of the proposed work is carried out in MATLAB/SIMULINK software.
6 citations
TL;DR: In this paper , an extensive survey is conducted to focus on the comparison of VANETs and IoV networks to give the researchers a clear understanding of the difference between these two networks.
Abstract: AbstractThe Internet of Vehicles (IoV) is one of the trending concepts in the automotive industry domain. It introduces the idea of smart transportation and smart cities due to the merging of Internet of things (IoT) and vehicular ad hoc networks (VANETs). IoV intends to overcome the existing flaws of VANETs to improve traffic efficiency, safety and ease the driving experience. The main objective of IoV is to strengthen the existing intelligent transportation systems (ITS) by the use of numerous intelligent technologies like cloud computing, intelligent sensing techniques, fog computing, Edge computing, etc. It has achieved a lot of market attention due to reliable Internet connectivity, smart device compatibility, smart decision making, and heterogeneous vehicular network and thus is a better alternative for existing transportation systems. In this paper, an extensive survey is conducted to focus on the comparison of VANETs and IoV networks to give the researchers a clear understanding of the difference between these two networks. Also, a sincere attempt is made to explore the diverse range of applications of IoV in detail before bringing it into actual deployment. In the last, open problems of IoV are also outlined that need to be resolved while deploying the IoV network.KeywordsApplicationsEfficiencyHazardsIntelligenceIoVSmart citiesSafetyVANETsVehicle
6 citations
6 citations
TL;DR: In this paper , a detailed discussion on wireless power transfer and relevant methodologies and operation techniques is presented, and four fundamental compensation topologies of resonant WPTs are described.
Abstract: AbstractWireless power transfer (WTP) emerged back in the early 1890s. This electrical technology captured major attention when a group of MIT researchers designed a functioning model of a WPT system that was efficiently able to transmit power and light a bulb of 60 W at a distance of 2 m. However, this concept was first put up by a Serbian scientist, Nikola Tesla, who introduced a system that could auspiciously transfer electrical power wirelessly. In this chapter, a detailed discussion on WPT and relevant methodologies and operation techniques is presented. A wireless power transfer system employs three distinct technologies: inductive, capacitive, and radiant. In this article, four fundamental compensation topologies of resonant WPTs are described, which are series–series (SS), parallel–parallel (PP), series–parallel (SP) and parallel–series (PS). Standard parameters and equation modelling have been discussed in this chapter. The world needs a wire-free system, and that is the hope of every other Tesla-influenced researcher. Every knowledge provided in the chapter is purely true to its deepest extent. The production and development of battery-powered devices face unparalleled technological difficulties because of the drawbacks of poor power density, exorbitant prices and bulky structure, etc. The wireless power transfer introduces a new energy acquisition method for electric vehicles as a novel energy pattern. This chapter also summarizes WPT approaches focusing on operating structures, mathematical and technological challenges focusing on the system for WPT.KeywordsWireless power transferTeslaTopologiesElectric vehiclesPlug-in charging
TL;DR: In this article , an extensive review of the available literature is done on recently developed fabrication and material synthesis techniques of various layers used in DSSCs for enhancing efficiency and durability, and the importance of using metal nanoparticles along with metal-oxide nanostructures as photoanode for enhancing light absorption and charge transport is also discussed.
Abstract: AbstractThe demand for solar-powered portable, wearable, lightweight and flexible electronic devices is increasing in the market. Hence, the development of flexible, lightweight and reliable solar cells is required to meet the market demand. Dye-sensitized solar cells (DSSCs) may be an alternative to fulfill this demand. The reported maximum power conversion efficiency (PCE) of DSSCs is ~14.1% only. Hence, there is a huge scope for increasing the PCE of DSSCs by using different nanostructure designs and materials in various layers of DSSCs. So, an extensive review of the available literature is done on recently developed fabrication and material synthesis techniques of various layers used in DSSCs for enhancing efficiency and durability. Again, the importance of using metal nanoparticles along with metal-oxide nanostructures as photoanode for enhancing light absorption and charge transport is also discussed in detail. Furthermore, the challenges currently faced by researchers in developing Flexible DSSCs (FDSSCs) are also addressed. Therefore, the main objective of this book chapter is to discuss the different materials and synthesis techniques for developing a novel photoanode layer. Another focus is to find out different synthesis techniques developed for the counter electrode (CE), electrolytes and dye layers for designing highly efficient rigid and FDSSCs.KeywordsDSSCsFlexibleMetal nanoparticleMetal-oxidePhotoanode
TL;DR: In this article , the root causes behind large power failure are discussed and different root causes of power failure which attracts the readers to develop new concept for mitigating blackout issues and provide new root causes for mitigating the blackout issues.
Abstract: This book provides different root causes behind large power failure which attracts the readers to develop new concept for mitigating blackout issues
TL;DR: In this article , interval modeling of RP system is done to accommodate the effect of parametric variations, and a comparative study of original system with its interval model is shown with the help of step response and impulse response.
Abstract: Riverol-Pilipovik (RP) water treatment system is a reverse osmosis-based desalination plant which is represented by a set of transfer functions. At times, there may be variations in the parameters of the system which may change its behavior. In this paper, interval modeling of RP system is done to accommodate the effect of parametric variations. A comparative study of original system with its interval model is shown with the help of step response and impulse response. Also, the characteristics of the response are compared to demonstrate the resemblance of the interval model to the original system.
TL;DR: In this article , a collaborative innovation platform for enterprises based on big data, and integrate information technology into the recruitment and placement, training and development, career planning and performance management of innovative talents, so as to help enterprises become digitization and improve their sustainable development ability.
Abstract: With the development of technology, cloud computing, big data, artificial intelligence and other digital technologies are in the ascendant. The world is rapidly entering the era of digital economy, and the wave of enterprise digital transformation has arrived. Gartner predicts that 75% companies’ business will be digital by 2020 in the world. The purpose of this paper is to form an innovative talent ecosystem integrating with enterprises, universities and the government combined with the trend of digital transformation of enterprises. Besides, this paper will build a collaborative innovation platform for enterprises based on big data, and integrate information technology into the recruitment and placement, training and development, career planning and performance management of innovative talents, so as to help enterprises become digitization and improve their sustainable development ability.
TL;DR: The authors proposed a heavily pre-trained language representation BioBERT based clustering framework for biomedical document analysis in order to improve the clustering accuracy, which achieved better clustering accuracies than other models.
Abstract: The large volumes of biomedical documents have been generating exponentially in modern applications. Document clustering methods play an important role in gathering textual content documents into a few meaningful coherent groups. However, clustering unstructured and unlabeled text is challenging to extract informative representations and find the relevant articles from the rapid growth biomedical literature. Therefore, traditional text document clustering methods often represent unsatisfactory results due to general non-contextualized vector space representations, which neglect the semantic relation between bio medical texts. Pre-trained language models have been gaining attention recently in variety of natural language processing tasks. In this paper, we propose a heavily pre-trained language representation BioBERT based clustering framework for biomedical document analysis in order to improve the clustering accuracy. In experimental architecture, we provide benchmarks of the pre-trained transformer model, statistical technique and word-embedding methods while incorporating with clustering algorithms. In order to distinguish the efficiency of the models, Fowlkes mallows score (FM), silhouette coefficient (SC), adjusted rand index (ARI), Davies-Bouldin score (DB) metrics are used. The comprehensive experimental results show that the BioBERT based K-means model achieves better clustering accuracies than other models.
TL;DR: In this paper , a brief review is done about how data collected by UAV mounted RFID can be used accessed by the users from a far distance using LoRa technology (LPWAN) and discussed briefly about the real-time applications and the upcoming challenges in the concerned research field.
Abstract: AbstractDominance of IoT in today’s market has expedited unmanned aerial vehicle (UAV) in various applications. UAV is borne with different sensors to detect and localize the concerned target in various environmental conditions. According to the government survey analysis, it is predicted that RFID tags will see a growth of 7.7% CAGR by 2023. So, both RFID and UAV are the revolutionary technology which can be used to loom toward adverse situation applications. In this paper, a brief review is done about how data collected by UAV mounted RFID can be used accessed by the users from a far distance using LoRa technology (LPWAN technology) and discussed briefly about the real-time applications and the upcoming challenges in the concerned research field.KeywordsUnmanned aerial vehicle (UAV)RFID sensorInternet of Things (IoT)Wireless sensor network (WSN)LoRa
TL;DR: The authors proposed a teaching quality evaluation method based on genetic algorithm (GA) and RBF neural network, GA is used to optimize the initial weights of RBF Neural Network, the experimental results show that the method can effectively evaluate the quality of English teaching, and has high accuracy and real-time performance.
Abstract: Aiming at the problem that the accuracy of English teaching quality evaluation is not high at present, this paper proposes a teaching quality evaluation method based on genetic algorithm (GA) and RBF neural network, GA is used to optimize the initial weights of RBF neural network. The experimental results show that the method can effectively evaluate the quality of English teaching, and has high accuracy and real-time performance.
TL;DR: In this paper , the authors point out how the current public blockchain infrastructure is generally incompatible with today's energy infrastructure, and also enlightens the new infrastructures that will enable the transition and examples of applications in the energy infrastructure.
Abstract: Our Electricity or energy market was designed a long time ago. The regulation that applies to it today that disciples the innovation were put in place about a 100 years ago has been lobbied to keep in place. Since then, there have been massive inefficiencies in the entire ecosystem and infrastructure, and the control and distribution of energy today are quite antiquated. Much regulation prevents new companies from implementing a new system, so it becomes necessary to work with the incumbents to integrate this system. Therefore, this paper aims to frame today's situation of the energy markets’ state. Also, to find the opportunity for a new energy paradigm. We point out how the current public blockchain infrastructure is generally incompatible with today's energy infrastructure. Furthermore, it also enlightens the new infrastructures that will enable the transition and examples of applications in the energy infrastructure.
TL;DR: In this paper , a new artificial neural network (ANN) topology is designed to predict the load of electric power distribution substation in order to operate network more reliableReliable and also to participate successfully in energy trading.
Abstract: ActiveVeeramsetty, Venkataramana powerRakesh Chandra, D. loadActive power load forecastingForecasting isFeature selection an essentialMachine learning taskSalkuti, Surender Reddy for electric utilities in order to operate network more reliableReliable and also to participate successfully in energy trading. In this chapter a new artificial neural networkArtificial neural network (ANN) topology is designed to predict the load. The most efficient input features to predict the load have been selected using correlationCorrelation factors. The active power loadActive power load data has been taken from 33/11 kV electric power distribution substation. The proposed ANN architecture is designed, implemented and tested in Microsoft Azure Notebook environment. Based on the simulation results, it has been observed that the proposed ANN model predicts the load with good accuracyAccuracy.
TL;DR: Wang et al. as mentioned in this paper proposed a new swarm intelligence optimization algorithm named Tumbleweed Algorithm (TA) which simulates the two processes of tumbleweed from seedling to adulthood and the propagation of tumble weed seeds after adulthood.
Abstract: In this paper, a new swarm intelligence optimization algorithm named Tumbleweed Algorithm (TA) is proposed. The TA algorithm simulates the two processes of tumbleweed from seedling to adulthood and the propagation of tumbleweed seeds after adulthood. And by introducing the concept of growth cycle, the two stages are combined. In order to verify the effectiveness of the new algorithm proposed to solve the problems, this paper uses the CEC2013 function set to test, and compares the 10D, 30D and 50D dimensions with six swarm intelligence optimization algorithms. By comparing the experimental results under different dimensions, the TA algorithm proposed in this paper is generally superior to other intelligent optimization algorithms compared, and has strong optimization ability and competitiveness. Finally, the TA algorithm is applied to the location problem of logistics distribution center to verify the practicability of the algorithm. In solving this problem, the TA algorithm can also obtain better optimization results.