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Dr. Rabindra Nath Shaw
Galgotias University

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Research Keywords & Expertise

0 Power Electronics
0 Solar Energy
0 artificial intelligence
0 Power & energy
0 Renewable & Clean Energy Resources

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artificial intelligence
Power Electronics
Solar Energy

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Short Biography

Dr. Rabindra Nath Shaw is a Senior Member of IEEE (USA), currently holding the post of Director, International Relations, Galgotias University India. Dr. Shaw is an alumnus of the applied physics department, University of Calcutta, India and he has more than eleven years of teaching experience in leading institutes like Motilal Nehru National Institute of Technology Allahabad, India, Jadavpur University, and others at UG and PG level and he has successfully organized more than fifteen International conferences as Conference Chair, Publication Chair, and Editor. Dr. Shaw has published more than hundred Scopus/ WoS/ ISI indexed research papers in International Journals and Proceedings and he is the editor of several Springer and Elsevier books. His primary area of research is optimization algorithms and machine learning techniques for power systems, IoT applications, Renewable Energy, and Power electronics converters. He also worked as University Examination Coordinator, University MOOC’s Coordinator, University Conference Coordinator, and Faculty- In Charge, Centre of Excellence for Power Engineering and Clean Energy Integration.

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Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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Nanomagnets are used in spintronics/straintronics devices, with their non-volatile and non-leakage feature, and are opening new possibilities of replacing conventional digital logic using transistor-based electronics. Correlated switching of spins is presented in nanomagnets, and this novel feature offers credibility of replacing CMOS VLSI technology with high integration density and energy efficiency. In the present paper, the authors studied the unit domain cell of a circular-shaped nanomagnet cylinder using micromagnetic simulation software OOMMF. The simulation result would help to determine the minimum domain size in nanomagnet-based devices using spintronics.

ACS Style

Amlan Sen; Rabindra Nath Shaw; Ankush Ghosh. Magnetization Pattern Study of Unit Domain Multiferroic Nanomagnet for Spintronics Devices. Lecture Notes in Electrical Engineering 2021, 533 -542.

AMA Style

Amlan Sen, Rabindra Nath Shaw, Ankush Ghosh. Magnetization Pattern Study of Unit Domain Multiferroic Nanomagnet for Spintronics Devices. Lecture Notes in Electrical Engineering. 2021; ():533-542.

Chicago/Turabian Style

Amlan Sen; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Magnetization Pattern Study of Unit Domain Multiferroic Nanomagnet for Spintronics Devices." Lecture Notes in Electrical Engineering , no. : 533-542.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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Blockchain technology serves a breakthrough for many solutions like that of poor payment facilities, lesser productivity, trust among different levels of the industry in sharing of the gathered field reports, or the commands of the higher authority in the construction industry. Thus, the decentralized ledger system has facilitated an automatic chain of the flow of data or information among the peers and the subordinates. The aim is to make a digital world more trustable giving a new open arena to a better security solution, resilient nature and the enhancement of the systems. It is already known that industry progress upon its embracing of newer technologies that bind a better relationship with the customers and the giving of the best quality project basing on the low cost of trade estimates; the blockchain facilitates the use of smart contracts, agreements with the party directly without the involvement of a third party. The new version of the industries is supposedly aiming towards more digitized industrialization with more involvement in construction management with building information modelling (BIM). The aim is to provide a pre-step towards the use cases of blockchain technology in the construction industry after the reviving of the industry using the utmost digitization.

ACS Style

Priyanka Singh; Debarati Sammanit; Paritosh Krishnan; Krishna Mohan Agarwal; Rabindra Nath Shaw; Ankush Ghosh. Combating Challenges in the Construction Industry with Blockchain Technology. Lecture Notes in Electrical Engineering 2021, 707 -716.

AMA Style

Priyanka Singh, Debarati Sammanit, Paritosh Krishnan, Krishna Mohan Agarwal, Rabindra Nath Shaw, Ankush Ghosh. Combating Challenges in the Construction Industry with Blockchain Technology. Lecture Notes in Electrical Engineering. 2021; ():707-716.

Chicago/Turabian Style

Priyanka Singh; Debarati Sammanit; Paritosh Krishnan; Krishna Mohan Agarwal; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Combating Challenges in the Construction Industry with Blockchain Technology." Lecture Notes in Electrical Engineering , no. : 707-716.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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Concrete is the widely used composite material to build infrastructures that should remain durable and serviceable. This study focuses on sustainable concrete produced by replacing cement with waste products (fly ash and slag) to obtain good mechanical long-term and desirable durability. The use of fly ash and slag in concrete in place of cement lowers global energy demand and saves money on the verge of depletion. Fly ash provides increased workability, mechanical and durability properties and a wide range of advantages, including decreased strain on natural resources and a lower CO2 footprint. Fly ash in concrete structures is used as a partial substitute for Ordinary Portland Cement. Experimental work about concrete contributes to a waste of resources, time and money. Nominal concrete is a heterogeneous mixture of cement, water, coarse and fine aggregates. Therefore, for efficient use of such materials in various engineered structures, a clear understanding of such complex behavior is important. In this paper, the ANN is used to execute and provide output for compressive strength and workability of concrete, which we are predicting by use of 103 datasets obtained from available technical literatures. The focus is to find out the ideal equation for workability and compressive strength for concrete with the help of ANN.

ACS Style

Priyanka Singh; Saurav Bhardwaj; Saurav Dixit; Rabindra Nath Shaw; Ankush Ghosh. Development of Prediction Models to Determine Compressive Strength and Workability of Sustainable Concrete with ANN. Lecture Notes in Electrical Engineering 2021, 753 -769.

AMA Style

Priyanka Singh, Saurav Bhardwaj, Saurav Dixit, Rabindra Nath Shaw, Ankush Ghosh. Development of Prediction Models to Determine Compressive Strength and Workability of Sustainable Concrete with ANN. Lecture Notes in Electrical Engineering. 2021; ():753-769.

Chicago/Turabian Style

Priyanka Singh; Saurav Bhardwaj; Saurav Dixit; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Development of Prediction Models to Determine Compressive Strength and Workability of Sustainable Concrete with ANN." Lecture Notes in Electrical Engineering , no. : 753-769.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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Darkweb also called as sinkholes, blackholes, network telescopes, and darknet is the environment and the most favorable platform for illegal activities due to hidden IP address and therefore counted as unused address space, which is not available for normal user, and the anonymous behavior acts as catalyst for criminal or unauthorized behavior conduction. It is very difficult to suddenly trace the location of malicious activity origin but by traffic analysis and understanding the patterns, suspicious activities including email communication, audio–video streaming, chatting P2P, browsing data, chatting, and voice over Internet protocol constitute the hidden world web traffic. Several methods have been deployed to analysis and classify darkweb network traffic. The proposed work detects worms, dos attack, backdoor, DDos attack, RDoS attack, spam, and malicious contents. In the proposed work, term frequency-inverse document frequency (TF-IDF) and light gradient boosted machine algorithm method has been implemented on darknet traffic data. The light gradient boosted machine algorithm shows the value of 98.97% as accuracy and thus outperforms the other algorithms based on experiment values.

ACS Style

Romil Rawat; Vinod Mahor; Sachin Chirgaiya; Rabindra Nath Shaw; Ankush Ghosh. Analysis of Darknet Traffic for Criminal Activities Detection Using TF-IDF and Light Gradient Boosted Machine Learning Algorithm. Lecture Notes in Electrical Engineering 2021, 671 -681.

AMA Style

Romil Rawat, Vinod Mahor, Sachin Chirgaiya, Rabindra Nath Shaw, Ankush Ghosh. Analysis of Darknet Traffic for Criminal Activities Detection Using TF-IDF and Light Gradient Boosted Machine Learning Algorithm. Lecture Notes in Electrical Engineering. 2021; ():671-681.

Chicago/Turabian Style

Romil Rawat; Vinod Mahor; Sachin Chirgaiya; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Analysis of Darknet Traffic for Criminal Activities Detection Using TF-IDF and Light Gradient Boosted Machine Learning Algorithm." Lecture Notes in Electrical Engineering , no. : 671-681.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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The power captured by a tidal conversion system depends highly on the applied control strategies. In fact, nonlinear properties of the generator, parameter uncertainties, and external disturbances make the controller design a challenging problem. This paper contributes with the novel fuzzy gain supervisor passivity-based control (FGSPBC) method that allows the PBC to be faster, combined with a PI controller where its gains are adopted by the FGSPBC, applied to the PMSG based variable tidal turbine with grid connection via back-to-back converter to bring the PMSG to work at an optimal point while ensuring stability, fast convergence of the conversion system, and performance improvement. The aims of this work are that the regulation of the DC voltage and the reactive power at their respective values, whatever the disturbances related to the PMSG. Numerical investigation under MATLAB/Simulink addresses the effectiveness, stability, and fast convergence of the studied system.

ACS Style

Youcef Belkhier; Abdelyazid Achour; Rabindra Nath Shaw; Ankush Ghosh. Performance Improvement for PMSG Tidal Power Conversion System with Fuzzy Gain Supervisor Passivity-Based Current Control. Lecture Notes in Electrical Engineering 2021, 81 -93.

AMA Style

Youcef Belkhier, Abdelyazid Achour, Rabindra Nath Shaw, Ankush Ghosh. Performance Improvement for PMSG Tidal Power Conversion System with Fuzzy Gain Supervisor Passivity-Based Current Control. Lecture Notes in Electrical Engineering. 2021; ():81-93.

Chicago/Turabian Style

Youcef Belkhier; Abdelyazid Achour; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Performance Improvement for PMSG Tidal Power Conversion System with Fuzzy Gain Supervisor Passivity-Based Current Control." Lecture Notes in Electrical Engineering , no. : 81-93.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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Wind conversion system-based permanent magnet synchronous generator (PMSG) controller design is still a challenging work due to the PMSG nonlinear operation conditions and external disturbances. This work proposes a passivity-based control (PBC) associated with backstepping technique which ensures asymptotic convergence to the maximum power extraction, and stability of the closed-loop system that allows the PMSG to operate at an optimal speed and robustness of the system dynamics. The studied conversion system is constituted by a wind turbine, PMSG and buck-to-buck converter with DC-link voltage connected to the grid. The proposed method is used to control the generator-side converter, while a proportional–integral (PI) controller is used in the grid-side, to transmit only the active power to the distribution network. The objectives are achieved, and the reactive power and DC voltage quickly track their set values. The effectiveness of the proposed strategy is illustrated by numerical simulation results under MATLAB/Simulink.

ACS Style

Youcef Belkhier; Abdelyazid Achour; Rabindra Nath Shaw; Walid Sahraoui; Ankush Ghosh. Adaptive Linear Feedback Energy-Based Backstepping and PID Control Strategy for PMSG Driven by a Grid-Connected Wind Turbine. Lecture Notes in Electrical Engineering 2021, 177 -189.

AMA Style

Youcef Belkhier, Abdelyazid Achour, Rabindra Nath Shaw, Walid Sahraoui, Ankush Ghosh. Adaptive Linear Feedback Energy-Based Backstepping and PID Control Strategy for PMSG Driven by a Grid-Connected Wind Turbine. Lecture Notes in Electrical Engineering. 2021; ():177-189.

Chicago/Turabian Style

Youcef Belkhier; Abdelyazid Achour; Rabindra Nath Shaw; Walid Sahraoui; Ankush Ghosh. 2021. "Adaptive Linear Feedback Energy-Based Backstepping and PID Control Strategy for PMSG Driven by a Grid-Connected Wind Turbine." Lecture Notes in Electrical Engineering , no. : 177-189.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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In recent years, it is seen that the amount of energy consumption is increasing rapidly as everyone is looking for development and economical growth; also, we have limited resources fossil fuel, electrical energy, and mechanical energy which are still maximum source of energy of the world. That is why electrical energy is one of the major components for fulfilling the needs of the world. Many analysts tried to create electrical energy in the ground of renewable sources using different sensors, so that they can reduce the use of fossil fuel and also for the fulfillment of electrical energy for different appliances. In this chapter, we are focusing on the same challenges and making it work to generate an electrical energy using sensors, i.e., photovoltaic plate, which is based on Internet of things (IoT) system for different appliance. Energy developed by photovoltaic plate is connected to the power storage circuit. Here, total power generated to exploit to different AI models approval is done through the measurable boundaries like RMSE and RRMSE.

ACS Style

Harshit Kumar Huneria; Pavan Yadav; Rabindra Nath Shaw; D. Saravanan; Ankush Ghosh. AI and IOT-Based Model for Photovoltaic Power Generation. Lecture Notes in Electrical Engineering 2021, 697 -706.

AMA Style

Harshit Kumar Huneria, Pavan Yadav, Rabindra Nath Shaw, D. Saravanan, Ankush Ghosh. AI and IOT-Based Model for Photovoltaic Power Generation. Lecture Notes in Electrical Engineering. 2021; ():697-706.

Chicago/Turabian Style

Harshit Kumar Huneria; Pavan Yadav; Rabindra Nath Shaw; D. Saravanan; Ankush Ghosh. 2021. "AI and IOT-Based Model for Photovoltaic Power Generation." Lecture Notes in Electrical Engineering , no. : 697-706.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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Determining the identification of faulty phase in six-phase power transmission network (SPPTN) is intricate in comparison with other configurations of transmission network based upon the six-phases. For this issue, the feasible faulty phase is identified with the presented scheme in this study. Haar wavelet transform (HWT) is used to the current data only as a feature extraction tool, and thereafter, a threshold method is used for deciding the faulty phase. To endorse the justification, the scheme is applied to SPPTN model implemented in MATLAB. Faults on SPPTN have been successfully identified by using the fault current measured at the sending end bus of the SPPTN.

ACS Style

Gaurav Kapoor; Pratima Walde; Rabindra Nath Shaw; Ankush Ghosh. HWT-DCDI-Based Approach for Fault Identification in Six-Phase Power Transmission Network. Lecture Notes in Electrical Engineering 2021, 395 -407.

AMA Style

Gaurav Kapoor, Pratima Walde, Rabindra Nath Shaw, Ankush Ghosh. HWT-DCDI-Based Approach for Fault Identification in Six-Phase Power Transmission Network. Lecture Notes in Electrical Engineering. 2021; ():395-407.

Chicago/Turabian Style

Gaurav Kapoor; Pratima Walde; Rabindra Nath Shaw; Ankush Ghosh. 2021. "HWT-DCDI-Based Approach for Fault Identification in Six-Phase Power Transmission Network." Lecture Notes in Electrical Engineering , no. : 395-407.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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A fault detection scheme is presented in this paper based on reverse biorthogonal wavelet (RBW). The usefulness of the RBW-based scheme has been tested and authenticated on power transmission system connected with distributed generation. Simulation effects exhibit that very accurate fault detection using the features extracted from the fault currents is feasible.

ACS Style

Gaurav Kapoor; Vishesh Kumar Mishra; Rabindra Nath Shaw; Ankush Ghosh. Fault Detection in Power Transmission System Using Reverse Biorthogonal Wavelet. Lecture Notes in Electrical Engineering 2021, 381 -393.

AMA Style

Gaurav Kapoor, Vishesh Kumar Mishra, Rabindra Nath Shaw, Ankush Ghosh. Fault Detection in Power Transmission System Using Reverse Biorthogonal Wavelet. Lecture Notes in Electrical Engineering. 2021; ():381-393.

Chicago/Turabian Style

Gaurav Kapoor; Vishesh Kumar Mishra; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Fault Detection in Power Transmission System Using Reverse Biorthogonal Wavelet." Lecture Notes in Electrical Engineering , no. : 381-393.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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In this paper, we work on suspicious big text data analysis technique for prediction of terrorism activity like financial fraud, money laundering, recruitment, radicalization, fundraising, violent and illegal post and video sharing on darkweb environment also called as cosmic web due to hidden content attributes. The consequent activity prognosis (CAP) is required for minimizing the risk associated with cyber information and personal security compromise for collectively data analysis referred as big data. The cyberterrorist and criminal hackers generated denial of service attack (DoS), distributed DoS attack (DDoS) and ransom-related DoS attack (RDoS) attack thereby overloading the server and increasing and blocking the server execution. The cyber threats and activities could only be reducing the execution time of activities marked suspicious and not safe. The propose model is based on computational intelligence technique using MapReduce technique, by classifying the malicious patterns found in big data sets collected from authentic channels and designed using machine learning supporting languages to implement the enhanced model and magnify the existing Intelligent techniques of computation with evaluated parameters. The work is highly adaptable for analysis and outline terrorist and criminal activities and would be beneficial for cyber police and security agencies.

ACS Style

Anand Singh Rajawat; Romil Rawat; Vinod Mahor; Rabindra Nath Shaw; Ankush Ghosh. Suspicious Big Text Data Analysis for Prediction—On Darkweb User Activity Using Computational Intelligence Model. Lecture Notes in Electrical Engineering 2021, 735 -751.

AMA Style

Anand Singh Rajawat, Romil Rawat, Vinod Mahor, Rabindra Nath Shaw, Ankush Ghosh. Suspicious Big Text Data Analysis for Prediction—On Darkweb User Activity Using Computational Intelligence Model. Lecture Notes in Electrical Engineering. 2021; ():735-751.

Chicago/Turabian Style

Anand Singh Rajawat; Romil Rawat; Vinod Mahor; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Suspicious Big Text Data Analysis for Prediction—On Darkweb User Activity Using Computational Intelligence Model." Lecture Notes in Electrical Engineering , no. : 735-751.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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The Internet of Things (IoT) idea has arisen as interconnected components of the healthcare tracking facilities of smart linked healthcare networks. Hard sensor-based data aggregation with the help of devices in the form of wearables or intrusive samples attached with the acquisition of soft sensors like crowd sensor results in the aggregated sensor data being concealed in patterns. This problem is tackled through several secret stages of interpretation of deep learning techniques. In this research work, we proposed hybrid deep learning (HDL) techniques to develop estimation and enhance quality of smart health services on health monitoring data. We also showed a detailed comparison of methods on the basis of health surveillance types. Hence, our proposed models work for risk detection in health information which will help us to increase the efficiency of existing healthcare industry.

ACS Style

Anand Singh Rajawat; Kanishk Barhanpurkar; Rabindra Nath Shaw; Ankush Ghosh. Risk Detection in Wireless Body Sensor Networks for Health Monitoring Using Hybrid Deep Learning. Lecture Notes in Electrical Engineering 2021, 683 -696.

AMA Style

Anand Singh Rajawat, Kanishk Barhanpurkar, Rabindra Nath Shaw, Ankush Ghosh. Risk Detection in Wireless Body Sensor Networks for Health Monitoring Using Hybrid Deep Learning. Lecture Notes in Electrical Engineering. 2021; ():683-696.

Chicago/Turabian Style

Anand Singh Rajawat; Kanishk Barhanpurkar; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Risk Detection in Wireless Body Sensor Networks for Health Monitoring Using Hybrid Deep Learning." Lecture Notes in Electrical Engineering , no. : 683-696.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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Herein, spectral amplitude coding-optical code division multiple access (SAC-OCDMA) technology is investigated and simulated. Thus, a comparative analysis is done between the random diagonal (RD), modified double weight (MDW) and enhanced double weight (EDW) codes, aiming to obtain results with better performances. The suggested system that exploits lasers as transmitter shows significantly perfect performances as compared to the bit error rate (BER), eye’s diagram, and Q factor of others standard SAC-OCDMA.

ACS Style

Walid Sahraoui; Hakim Aoudia; Angela Amphawan; Smail Berrah; Youcef Belkhier; Rabindra Nath Shaw. Enhanced Performances of SAC-OCDMA System Operating with Different Codes. Lecture Notes in Electrical Engineering 2021, 473 -485.

AMA Style

Walid Sahraoui, Hakim Aoudia, Angela Amphawan, Smail Berrah, Youcef Belkhier, Rabindra Nath Shaw. Enhanced Performances of SAC-OCDMA System Operating with Different Codes. Lecture Notes in Electrical Engineering. 2021; ():473-485.

Chicago/Turabian Style

Walid Sahraoui; Hakim Aoudia; Angela Amphawan; Smail Berrah; Youcef Belkhier; Rabindra Nath Shaw. 2021. "Enhanced Performances of SAC-OCDMA System Operating with Different Codes." Lecture Notes in Electrical Engineering , no. : 473-485.

Conference paper
Published: 25 May 2021 in Lecture Notes in Electrical Engineering
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The mainstream use of the Internet and mobile technology has made it easier to reach a wide range of globalized resources. By having the numerous lawful design principles offered by Internet merchants, unregulated cyber terrorist and hacking markets by intruders actively working at online platform. Illicit web store and markets are capitalizing on the privacy and at globalized existence on the Internet, posing problems, hidden unsecure environment and obstacles for policing and security agencies. The proposed work offers a summary of the anonymous crime favored place at Dark Web and recent research on illegal Internet drug trafficking, human trafficking, terrorist funding and recruitment, money laundering, contract hacking, organ trafficking, cracked key distribution, killing contracts, forged passport, illegal post sharing and forum discussion, fraud and credit card selling, weapons order, and cybercrime and child sexual abuse markets in the Dark Web. The work presented here outlines the Tor network crawling procedure and evaluation of hidden links for analysis with the crawling of drug trafficking, Criminal activity-related signatures and posts put light on the negative side of the Dark Web platform and their services, techniques and methods use for data crawling, pattern recognition and behavior understanding of criminals followed by terrorist organizations, campaigning on social network platform using hidden identities for recruitment, fundraising and radicalization.

ACS Style

Romil Rawat; Anand Singh Rajawat; Vinod Mahor; Rabindra Nath Shaw; Ankush Ghosh. Dark Web—Onion Hidden Service Discovery and Crawling for Profiling Morphing, Unstructured Crime and Vulnerabilities Prediction. Lecture Notes in Electrical Engineering 2021, 717 -734.

AMA Style

Romil Rawat, Anand Singh Rajawat, Vinod Mahor, Rabindra Nath Shaw, Ankush Ghosh. Dark Web—Onion Hidden Service Discovery and Crawling for Profiling Morphing, Unstructured Crime and Vulnerabilities Prediction. Lecture Notes in Electrical Engineering. 2021; ():717-734.

Chicago/Turabian Style

Romil Rawat; Anand Singh Rajawat; Vinod Mahor; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Dark Web—Onion Hidden Service Discovery and Crawling for Profiling Morphing, Unstructured Crime and Vulnerabilities Prediction." Lecture Notes in Electrical Engineering , no. : 717-734.

Journal article
Published: 27 April 2021 in Actuators
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Higher efficiency, predictability, and high-power density are the main advantages of a permanent magnet synchronous generator (PMSG)-based hydro turbine. However, the control of a PMSG is a nontrivial issue, because of its time-varying parameters and nonlinear dynamics. This paper suggests a novel optimal fuzzy supervisor passivity-based high order sliding-mode controller to address problems faced by conventional techniques such as PI controls in the machine side. An inherent advantage of the proposed method is that the nonlinear terms are not canceled but compensated in a damped way. The proposed controller consists of two main parts: the fuzzy gain supervisor-PI controller to design the desired dynamic of the system by controlling the rotor speed, and the fuzzy gain-high order sliding-mode control to compute the controller law. The main objectives are feeding the electrical grid with active power, extracting the maximum tidal power, and regulating the reactive power and DC voltage toward their references, whatever the disturbances caused by the PMSG. The main contribution and novelty of the present work consists in the new robust fuzzy supervisory passivity-based high order sliding-mode controller, which treats the mechanical characteristics of the PMSG as a passive disturbance when designing the controller and compensates it. By doing so, the PMSG tracks the optimal speed, contrary to other controls which only take into account the electrical part. The combined high order sliding-mode controller (HSMC) and passivity-based control (PBC) resulted in a hybrid controller law which attempts to greatly enhance the robustness of the proposed approach regardless of various uncertainties. Moreover, the proposed controller was also validated using a processor in the loop (PIL) experiment using Texas Instruments (TI) Launchpad. The control strategy was tested under parameter variations and its performances were compared to the nonlinear control methods. High robustness and high efficiency were clearly illustrated by the proposed new strategy over compared methods under parameter uncertainties using MATLAB/Simulink and a PIL testing platform.

ACS Style

Youcef Belkhier; Abdelyazid Achour; Rabindra Shaw; Nasim Ullah; Shahariar Chowdhury; Kuaanan Techato. Fuzzy Supervisory Passivity-Based High Order-Sliding Mode Control Approach for Tidal Turbine-Based Permanent Magnet Synchronous Generator Conversion System. Actuators 2021, 10, 92 .

AMA Style

Youcef Belkhier, Abdelyazid Achour, Rabindra Shaw, Nasim Ullah, Shahariar Chowdhury, Kuaanan Techato. Fuzzy Supervisory Passivity-Based High Order-Sliding Mode Control Approach for Tidal Turbine-Based Permanent Magnet Synchronous Generator Conversion System. Actuators. 2021; 10 (5):92.

Chicago/Turabian Style

Youcef Belkhier; Abdelyazid Achour; Rabindra Shaw; Nasim Ullah; Shahariar Chowdhury; Kuaanan Techato. 2021. "Fuzzy Supervisory Passivity-Based High Order-Sliding Mode Control Approach for Tidal Turbine-Based Permanent Magnet Synchronous Generator Conversion System." Actuators 10, no. 5: 92.

Chapter
Published: 25 April 2021 in Econometrics for Financial Applications
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Due to the potentially catastrophic effects in the event of an attack, security-enabled design and algorithms are required to protect automated applications and instruments based on Internet Industries of Thing called as IIoT. The most potential developed techniques for analyzing, designing, and protecting the Internet of Things (IoT) technologies are computational intelligence and big data analysis. These strategies will also help to enhance the protection of IIoT networks (home automation, traffic lighting, power stations, oil and gas stations, smart warehouses, automated vehicles, smart robotics). First, we present the popular IIoT computational intelligence (CIA) algorithm and its related vulnerabilities in this article. We then conduct a cyber-threat-vulnerability review by investigating the use of CIA model to combat illicit behaviors of dark Web environment. The proposed work is based on the literature data analysis within the available solutions for the prevention of cyber terrorism threats using algorithm models of computational intelligence (CIA) is then discussed. Finally, we address our work, which provides scenario of a real-world hidden cyber world activities designed to carry out a cyber terrorist attack and to build a structure for a cyber threat. Device attacks to illustrate how a CIA-based vulnerability analysis system will do well to detect these attacks. To have a rational point of view on the success of the approaches, we have measured the performance across representative metrics.

ACS Style

Anand Singh Rajawat; Romil Rawat; Kanishk Barhanpurkar; Rabindra Nath Shaw; Ankush Ghosh. Vulnerability Analysis at Industrial Internet of Things Platform on Dark Web Network Using Computational Intelligence. Econometrics for Financial Applications 2021, 39 -51.

AMA Style

Anand Singh Rajawat, Romil Rawat, Kanishk Barhanpurkar, Rabindra Nath Shaw, Ankush Ghosh. Vulnerability Analysis at Industrial Internet of Things Platform on Dark Web Network Using Computational Intelligence. Econometrics for Financial Applications. 2021; ():39-51.

Chicago/Turabian Style

Anand Singh Rajawat; Romil Rawat; Kanishk Barhanpurkar; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Vulnerability Analysis at Industrial Internet of Things Platform on Dark Web Network Using Computational Intelligence." Econometrics for Financial Applications , no. : 39-51.

Chapter
Published: 25 April 2021 in Econometrics for Financial Applications
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In the financial sectors like banking, anti-money laundering (AML) is a very challenging issue. To prevent the money laundering, various set of procedures, government policies, and ordinances are designed which are known as anti-money laundering, where income through illegal actions, e.g., market operations, deal of illegal commodities, and corruption of public funds, and tax evasion, can be stopped. The major objective of the chapter is classification of any transaction correctly as illegal or not. To achieve this, we have used the big data analytics technique for a dataset to identify money laundering activities. The dataset with 10,000 transactions is used in our analysis. The overall process includes data cleaning, statistical analysis, and data mining process. The linear support vector machine and decision tree classifier are used to find money laundering activities. The analysis has been done using Python and customized datasets. The result obtained through analysis is very significant and shows accuracy is higher in the decision tree classifier. Other parameters, namely recall and precision, is also better in the decision tree.

ACS Style

Ashwini Kumar; Sanjoy Das; Vishu Tyagi; Rabindra Nath Shaw; Ankush Ghosh. Analysis of Classifier Algorithms to Detect Anti-Money Laundering. Econometrics for Financial Applications 2021, 143 -152.

AMA Style

Ashwini Kumar, Sanjoy Das, Vishu Tyagi, Rabindra Nath Shaw, Ankush Ghosh. Analysis of Classifier Algorithms to Detect Anti-Money Laundering. Econometrics for Financial Applications. 2021; ():143-152.

Chicago/Turabian Style

Ashwini Kumar; Sanjoy Das; Vishu Tyagi; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Analysis of Classifier Algorithms to Detect Anti-Money Laundering." Econometrics for Financial Applications , no. : 143-152.

Chapter
Published: 25 April 2021 in Econometrics for Financial Applications
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The creating centrality of sentiment assessment agrees with the advancement of the electronic stage, for instance, cyber-vulnerability reviews, gathering discussions for cyber-dangers studies, malicious movement-based overview web diaries, more modest scope sites, and casual associations related to the cyber-lawbreakers exercises study. The choices and approach, used to intrigue this present reality, are generally adjusted to how others see and survey the world about feeling and sentiment. For such an explanation, the ordinarily looking through method is utilized, when it is needed to settle down the decision, for ends, conduction, and evaluation of others. This is certifiable for individuals just as for affiliations and associations and society. This work is a broad inclination assessment which implies the task of ordinary language processing (NLP) to choose if a touch of substance contains some theoretical information and what enthusiastic information it imparts using cyber-malicious post overview, i.e. whether or not the way behind this substance is certain (+) or negative (−). Since radical advances the hoodlums cyber-occasions utilizing on the web interpersonal organization and security offices and validate user blocks it. Understanding the emotions behind the web user delivered substance and instructive file subsequently is of unbelievable help for business and individual use, among others. The task can be coordinated on different levels of substance taking care of, requesting the furthest point of words, sentences or entire educational assortments. Here, the methodology investigates a predominant system for cyber-weaknesses overviews subject to the AI approach.

ACS Style

Romil Rawat; Vinod Mahor; Sachin Chirgaiya; Rabindra Nath Shaw; Ankush Ghosh. Sentiment Analysis at Online Social Network for Cyber-Malicious Post Reviews Using Machine Learning Techniques. Econometrics for Financial Applications 2021, 113 -130.

AMA Style

Romil Rawat, Vinod Mahor, Sachin Chirgaiya, Rabindra Nath Shaw, Ankush Ghosh. Sentiment Analysis at Online Social Network for Cyber-Malicious Post Reviews Using Machine Learning Techniques. Econometrics for Financial Applications. 2021; ():113-130.

Chicago/Turabian Style

Romil Rawat; Vinod Mahor; Sachin Chirgaiya; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Sentiment Analysis at Online Social Network for Cyber-Malicious Post Reviews Using Machine Learning Techniques." Econometrics for Financial Applications , no. : 113-130.

Chapter
Published: 25 April 2021 in Econometrics for Financial Applications
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The most important part of IoT architecture is WSN which constitutes the physical world in which heterogeneous devices are able to collect data required for processing and providing meaningful information to the users through Internet. However, WSN and IoT are two independent structures with subtle differences. Hence, the integration of WSN to the IoT is not a mere aggregation of tiny sensors and actuators to the Internet. This integration leads to the combinations of heterogeneous systems to collaborate and serve a common goal. Connecting sensor nodes to the Internet opens up security threats which have to be addressed during integration as because the combination of WSN and IoT can become more vulnerable to new attacks. This chapter represents the design challenges of Internet-integrated WSN with specific attack types and the corresponding security measures. Nevertheless, these security measures are not ultimate as IoT evolves through time and vast domain in which it has to be deployed with specific applications. With the diversity of applications, the WSN and IoT should be merged in such a way that would give the best performance with appropriate security backbone. The design taxonomy and specific protocols for low-power sensor devices require lightweight security mechanisms such as intrusion detection system (IDS) implemented with soft computing-based tools. This chapter introduces such a lightweight IDS for WSN-integrated IoT along with its performance analysis which will help the reader to understand the design methodology of such approach.

ACS Style

Aditi Paul; Somnath Sinha; Rabindra Nath Shaw; Ankush Ghosh. A Neuro-Fuzzy based IDS for Internet-Integrated WSN. Econometrics for Financial Applications 2021, 71 -86.

AMA Style

Aditi Paul, Somnath Sinha, Rabindra Nath Shaw, Ankush Ghosh. A Neuro-Fuzzy based IDS for Internet-Integrated WSN. Econometrics for Financial Applications. 2021; ():71-86.

Chicago/Turabian Style

Aditi Paul; Somnath Sinha; Rabindra Nath Shaw; Ankush Ghosh. 2021. "A Neuro-Fuzzy based IDS for Internet-Integrated WSN." Econometrics for Financial Applications , no. : 71-86.

Chapter
Published: 25 April 2021 in Econometrics for Financial Applications
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Sleep apnea is a syndrome that repetitively starts breathing ans stops. It causes a major issue in terms of quality of sleep and affects daily activities. It can be treated by laboratory tests or imaging on diagnosed with sleep apnea disorder. Numerous researchers have proposed and implemented automatic scoring processes to address these issues, based on fewer sensors and automatic classification algorithms. The proposed work develops an optimized CNN and LSTM smart deep learning model that classified the data set based on physical contact and without physical contact from patients for analysis and detects the OSA condition of the patient. We proposed a deep learning model for detecting torso and head by various sleep patterns. We achieved 93.02%, 94.50%, and 98.30% accuracy on frames using conversional CNN model, and received accuracy as 92.1%, 90.2%, 80.50% and 89.6% using CNN-LSTM architecture.

ACS Style

Anand Singh Rajawat; Romil Rawat; Kanishk Barhanpurkar; Rabindra Nath Shaw; Ankush Ghosh. Sleep Apnea Detection Using Contact-Based and Non-Contact-Based Using Deep Learning Methods. Econometrics for Financial Applications 2021, 87 -103.

AMA Style

Anand Singh Rajawat, Romil Rawat, Kanishk Barhanpurkar, Rabindra Nath Shaw, Ankush Ghosh. Sleep Apnea Detection Using Contact-Based and Non-Contact-Based Using Deep Learning Methods. Econometrics for Financial Applications. 2021; ():87-103.

Chicago/Turabian Style

Anand Singh Rajawat; Romil Rawat; Kanishk Barhanpurkar; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Sleep Apnea Detection Using Contact-Based and Non-Contact-Based Using Deep Learning Methods." Econometrics for Financial Applications , no. : 87-103.

Chapter
Published: 24 April 2021 in Econometrics for Financial Applications
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In this work, an algorithm of machine learning for self-driving car using udacity and unity self-driving car simulation software has been presented. Using the software, the car is driven on the simulated circuit having three cameras mounted on car hood which generate three images simultaneously and acceleration and de-acceleration of the car steering angle and brake. This method includes a behavior cloning approach and tries to replicate a behavior of human driver. For training the model, approximately, 18,000 training samples are required, and by using image augmentation technique, an increase in the data sample with few times is obtained, which leads to little robust simulated self-driving car.

ACS Style

Abhishek Soni; Dharamvir Dharmacharya; Amrindra Pal; Vivek Kumar Srivastava; Rabindra Nath Shaw; Ankush Ghosh. Design of a Machine Learning-Based Self-driving Car. Econometrics for Financial Applications 2021, 139 -151.

AMA Style

Abhishek Soni, Dharamvir Dharmacharya, Amrindra Pal, Vivek Kumar Srivastava, Rabindra Nath Shaw, Ankush Ghosh. Design of a Machine Learning-Based Self-driving Car. Econometrics for Financial Applications. 2021; ():139-151.

Chicago/Turabian Style

Abhishek Soni; Dharamvir Dharmacharya; Amrindra Pal; Vivek Kumar Srivastava; Rabindra Nath Shaw; Ankush Ghosh. 2021. "Design of a Machine Learning-Based Self-driving Car." Econometrics for Financial Applications , no. : 139-151.