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An efficient hybrid digital architecture for space vector PWM method for multilevel VSI
This paper presents an efficient, cost effective design implementation of a hybrid digital architecture for space vector pulse width modulation (SVPWM) method for multilevel inverters (MLIs). The SVPWM method is one of the most popular real time PWM method for three phase voltage source inverter (VSI). The implementation of SVPWM method becomes complex with an increase in the number of levels in a multilevel inverter. The SVPWM method for multilevel inverter is a multitask system. The main constraint when it comes to implementing SVPWM for multilevel inverters is the processing of dwell time computation and the generation of PWM gate signals for all of the switches with an accurate delay. A hybrid hardware structure consisting of a simple low-cost, low-power dsPIC micro controller (dsPIC 30F4011) and a state of the art Field Programmable Gate Array (FPGA) (Cyclone V 5CGXFC5C6F27C7N) is used to implement SVPWM. The proposed hybrid digital architecture utilizes the advantages and resources of the dsPIC and FPGA. The hybrid digital architecture meets the timing constraints of multitasking through synchronization and parallelism. A communication interface between the dsPIC and the FPGA reduces the design complexity. The software overhead for the communication interface remains fixed for any number of levels. The hybrid structure of the digital architecture provides scalability for the SVPWM method with more number of levels in multilevel inverter. The operation of the proposed hybrid digital architecture is experimentally validated with an optimized SVPWM method for a five level VSI. An optimized region identification algorithm and simple dwell time expressions are described for a five level SVPWM. The input DC of the five level VSI is obtained from a differential power processing (DPP) based PV system. Experimental results under different operating conditions are presented. 2020, The Korean Institute of Power Electronics. -
An efficient image denoising method based on bilateral filter model and neighshrink SURE
In all the instances of image acquisition, transmission and storage, the unwanted noise gets into the information content of the image and thereby introduces an unpleasant visual quality to the observer. So the field of image processing has produced a lot of image denoising algorithms and techniques to improve the visual quality of the image. Since noise cannot be reduced to zero practically, the need for faithful and efficient denoising techniques to produce almost noiseless images demands a systematic research work in the field of denoising methods. The denoising process using a bilateral filter even though produces improvement in the image quality, it does not show consistency when the noise level is high and also the peak signal to noise ratio (PSNR) and Image quality Index (IQI) do not show any improvement. This paper proposes an improved algorithm that incorporates the function of bilateral filter model and wavelet thresholding using Neighshrink SURE method. The results show significant improvement in both PSNR and IQI values with respect to the four standard test images under various noise conditions. BEIESP. -
An Efficient Inclusion Complex Based Fluorescent Sensor for Mercury (II) and its Application in Live-Cell Imaging
The formation of an inclusion complex between hydroxypropyl-?-cyclodextrin (H-CD) and 4-acetylphenyl-4-(((6-chlorobenzo[d]thiazol-2-yl)-imino)-methyl)-benzoate (L) was investigated by FT-IR, 1H-NMR, X-ray diffraction (XRD), FT-Raman, scanning electron microscope (SEM) techniques in the solid-state, absorption and emission spectroscopy in the liquid state and the virtual state as molecular docking technique. The binding properties of the inclusion complex (H-CD: L) with cations in deionized water was observed via absorbance and photoluminescence (PL) emission spectroscopy. The fluorescence probe (H-CD: L) inclusion complex (IC) was examined for several heavy metal cations, and identified that the PL emission wavelength of the complex displayed a continuous rise in the fluorescence intensity for Hg2+. A linearity range of 1 108 11 108M and limit of detection value of 2.71 1010M was found to be achieved for the detection of Hg2+. This outcome proves that the inclusion complex H-CD: L would be a promising material for the development a solid-state fluorescence probe for detecting Hg2+. It also shows application in real sample analysis and cell imaging. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
An efficient inclusion complex based fluorescent sensor for mercury (II) and its application in live-cell imaging /
Journal of Fluorescence, Vol.32, pp.1109–1124, ISSN No: 1573-4994.
The formation of an inclusion complex between hydroxypropyl-β-cyclodextrin (H-CD) and 4-acetylphenyl-4-(((6-chlorobenzo[d]thiazol-2-yl)-imino)-methyl)-benzoate (L) was investigated by FT-IR, 1H-NMR, X-ray diffraction (XRD), FT-Raman, scanning electron microscope (SEM) techniques in the solid-state, absorption and emission spectroscopy in the liquid state and the virtual state as molecular docking technique. The binding properties of the inclusion complex (H-CD: L) with cations in deionized water was observed via absorbance and photoluminescence (PL) emission spectroscopy. -
An efficient load balancing in cloud computing using hybrid Harris hawks optimization and cuckoo search algorithm
Cloud computing has rapidly emerged as a burgeoning research field in recent times. However, despite this growth, a comprehensive examination of this domain reveals persistent issues in the application of cloud-based systems concerning workload distribution. The abundance of resources and virtual machines (VMs) within cloud computing underscores the importance of efficient task allocation as a critical process. Within the infrastructure as a service (IaaS) architecture, load balancing (LB) remains a pivotal but challenging task. The occurrence of overloaded or underloaded hosts/servers during cloud access is undesirable, as it leads to operational delays and system performance degradation. To address LB issues effectively, it is imperative to deploy a proficient access scheduling algorithm capable of distributing tasks across the available resources. A novel approach was introduced by combining the Harris hawks optimization and cuckoo search algorithm (HHO-CSA), with a specific focus on critical service level agreement (SLA) parameters, particularly deadlines, to uphold LB in a cloud environment. The primary objective of the hybrid HHO-CSA methodology is to provide task attributes, resource allocation, VMs prioritization, and quality of service (QoS) to clients within cloud computing applications. The outcome analysis reveals that the proposed hybrid HHO-CSA algorithm results in a resource utilization reduction of 52%, with an execution time of 529.84 ms and a makespan of 638.88 ms. These values outperform those of existing SLA-based LB algorithms. Effective task scheduling plays a pivotal role in ensuring the seamless execution of tasks within a cloud system, while LB significantly aligns with the SLAs available to users. Drawing insights from the existing literature, the suggested hybrid HHO-CSA method addresses the research gap by effectively mitigating the challenges. 2023, Accent Social and Welfare Society. All rights reserved. -
An efficient low complexity compression based optimal homomorphic encryption for secure fiber optic communication
Latest advancements in fiber optic communication have gained significant attention among researchers owing to many benefits such as high data rate, acceptable cost, bandwidth, low attenuation, etc. Fiber optic networks are found to be a commonly utilized platform to transfer data in several applications such as personal, commercial, military areas, etc. Although fiber optic networks are highly beneficial, security remains a challenging design issue. Numerous state of art works has been developed to achieve security in fiber optic communication. Among the various methods, compression then encryption is an effective way to effectively and securely transmit the data. With this motivation, this paper presents a new Low Complexity Compression Then Encryption using Optimal Homomorphic Encryption (LCCE-OHE) technique for secured fiber optic communication. The proposed LCCE-OHE technique operates on two major phases namely compression and encryption. At the first stage, low complexity compression using Neighboring Indexing Sequence (NIS) with Deflate algorithm, named Normalized Information Distance (NID) is used. Besides, in the second stage, Quasi Oppositional Sail Fish Optimizer with Homomorphic Encryption (QOSFO-HE) technique is employed. The QOSFO algorithm is derived by incorporating the quasi oppositional learning (QOBL) concept to the SFO algorithm and is applied to optimally select the encryption keys. The performance validation of the proposed model takes place on two benchmark datasets and the experimental results are examined interms of different performance measures. The experimental values highlighted the improved compression efficiency and security level of the LCCE-OHE technique over the other techniques. 2022 Elsevier GmbH -
An efficient methodology for resolving uncertain spatial references in text documents
In recent decades, all the documents maintained by the industries are getting transformed into soft copies in either structured documents or as an e-copies. In text document processing, there is a number of ways available to extract the raw data. As the accuracy in finding the spatial data is crucial, this domain invites various research solutions that provide high accuracy. In this article, the Fuzzy Extraction, Resolving, and Clustering (FERC) architecture is proposed which uses fuzzy logic techniques to identify and cluster uncertain textual spatial reference. When the text corpus is queried with a spatial-keyword, FERC returns a set of relevant documents sorted in view of the fuzzy pertinence score. Any two documents may be compared in light of the spatial references that exist in them and their fuzzy similarity score is presented. This enables finding the degree to which the two documents speak about a specified location. The proposed architecture provides a better result set to the user, unlike a Boolean search where the document is either rated relevant or irrelevant. Copyright 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. -
An efficient nonlinear access policy based on quadratic residue for ciphertext policy attribute based encryption
Ciphertext Policy Attribute Based Encryption (CP-ABE) is an efficient encryption scheme as data owner is making decision about the attributes that can access his data and adding that attributes to access structure while encrypting that message. Most existing CP-ABE scheme are based traditional access structure such as linear secret sharing scheme which incur large ciphertext size and linearly increases according to the number of attributes. And those schemes have more computational overhead for calculating share for each attribute and when recalculating secret in data user side. In this paper, we propose a different secret sharing scheme that can be used in access policy for CP-ABE which will reduce the size of ciphertext and there by communication overhead. Furthermore, the proposed scheme reduced computational overhead of secret sharing scheme and improved overall efficiency of the scheme. 2021 Little Lion Scientific -
An efficient optimization based lung cancer pre-diagnosis system with aid of feed forward back propagation neural network ( FFBNN)
Vol. 56. No.2, October. ISSN: 1817-3195 -
An efficient optimization based lung cancer pre-diagnosis system with aid of feed forward back propagation neural network (FFBNN)
World Health Organization (WHO) reports that worldwide 7.6 million deaths are caused by cancer each year. Uncontrollable cell development in the tissues of the lung is called as lung cancer. These uncontrollable cells restrict the growth of healthy lung tissues. If not treated, this growth can spread beyond the lung in the nearby tissue called metastasis and, form tumors. In order to preserve the life of the people who are suffered by the lung cancer disease, it should be pre-diagonized. So there is a need of pre diagnosis system for lung cancer disease which should provide better results. The proposed lung cancer prediagnosis technique is the combination of FFBNN and ABC. By using the Artificial Bee Colony (ABC) algorithm, the dimensionality of the dataset is reduced in order to reduce the computation complexity. Then the risk factors and the symptoms from the dimensional reduced dataset are given to the FFBNN to accomplish the training process. In order to get higher accuracy in the prediagnosis process, the FFBNN parameters are optimized using ABC algorithm. In the testing process, more data are given to well trained FFBNN-ABC to validate whether the given testing data predict the lung disease perfectly or not. 2005-2013 JATIT & LLS.All rights reserved. -
An efficient privacy-preserving model based on OMFTSA for query optimization in crowdsourcing
Crowdsourcing is now one of the most important and transformative paradigms, with great success in a variety of application tasks. Crowdsourcing obtains knowledge and information to solve cognitive or intelligence-intensive tasks from an evolving group of participants via the Internet. Unfortunately, providing a hard privacy guarantee and query optimization is incompatible when a higher task acceptance rate needs to be accomplished and this case is common in most existing crowdsourcing solutions. The state of art systems suffered from different complexities such as lack of crowdsourcing optimization techniques, increased cost, latency, security, and scalability issues. In this paper, we have proposed a crowdsourcing model to optimize the cost and latency, issues that occur while query optimization using the Moth Flame and Tunicate Swarm Algorithm (MF-TSA). The TSA algorithm is added to the MF algorithm to enhance its exploitation capability and yield fast convergence. The data privacy concerns of the worker and the requestor are addressed using homomorphic encryption that simultaneously enhances the efficiency of the crowdsourcing framework. The main aim of this work is to optimize the cost and latency for query plan selection along with security. Initially, the homomorphic encryption model is used to encrypt the data. In query design, two kinds of crowd-controlled administrators, that is, Crowd Powered Selection (CSelect) and Crowd Powered Join (CJoin) are connected for assessing query. The proposed framework utilizes MF-TSA to optimize the selection and join queries with low cost and latency. Finally, the experimental results demonstrate better query optimization performance than other existing algorithms such as sequential, parallel, and CrowdOp. 2021 John Wiley & Sons Ltd. -
An efficient reconfigurable band tuning filter design for channelizer in transponder satellite system
For improved performance in a variety of applications, the transponder in satellite systems must be very flexible. The channelizer-dependent transponder system significantly boosts the operation of a satellite system. When channelizing wideband input signals, a digital filter bank is typically used to extract several small sub-bands. In this research, a reconfigurable band tuning (RBT) design for the channelizer in the satellite transponder system is designed and implemented. Cosine modulation, exponential modulation and IFIR filter are the techniques behind the RBT design. The RBT design facilitates the generation of many channels enabling channelization with non-uniform narrow transition width. A number of examples are presented to illustrate how well the RBT design performs. Findings indicate that there are fewer filter coefficients in the RBT design than there are in the current approaches Effective implementation of a properly designed RBT design lowers power consumption and simplifies the hardware. 2024 The Franklin Institute -
An Efficient Routing Strategy for Energy Management in Wireless Sensor Network Using Hybrid Routing Protocols
In these days, Wireless Sensor Networks (WSN) shows a huge impact on all appliances but one of the huge challenges in WSN is management of energy because the nodes in the network run with battery power. As the replacement of energy drained nodes is difficult, and frequent failure of links may occur and it incurs huge data loss. To avoid this issue the we proposed a Hybrid Krill Herd and Spider Monkey with Grid-Based Data Dissemination (HKHSM-GBDD) protocol with the Shortest Energy Resourceful Routing (SERR) mechanism to develop an efficient and better wireless communication channel. The presented HKHSM framework is utilized to classify malicious and energy drained nodes in earlier stage and to detect the link failure. Furthermore, the SERR mechanism is processed to recover the link and route maintenance. This novel proposed protocol has improved packet delivery ratio and energy consumption. It also enhances energy state of sensor nodes by mounting its lifetime and rerouting. Finally, the competence of the proposed mechanism is compared with existing works and it shows significant improvement over existing algorithms for the considered parameters. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
An efficient scheme for water leakage detection using support vector machines (SVM)-Zig
Water is one of the most essential and valuable resources for all living beings, yet in the present day, there is a scarcity of it. Half of the water loss in large cities and industries is due to leaks and illegal lines. 10%-20% of water loss can be reduced by detecting leaks but without the presence of advanced monitoring systems, this problem is typically worsened. Monitoring the consumption and leak detection for such large areas is a challenging task. To overcome this issue a small prototype is prepared called Zig. Zig is designed for both household and industrial purposes. Its main aim is to monitor the flow and consumption of water at different levels of a building like a first-floor and so on which may represent some industrial and household situation. This work focuses on pressure/flow monitoring method to reduce the operational cost and also to detect leakage. One of the machine learning algorithms, Support Vector Machines (SVM) has been applied to detect the leakage and it is compared with Random Forest algorithm to show that proposed scheme is detecting water leakage better. BEIESP. -
An Efficient Sorting Algorithm for Capacitor Voltage Balance of Modular Multilevel Converter With Space Vector Pulsewidth Modulation
Thisarticle presents an efficient analogue sorting algorithm for balancing the submodule (SM) capacitor voltages of modular multilevel converter (MMC). The proposed analogue sorting algorithm offers the advantage of fast convergence rate without any need of recursive loops for the implementation on embedded devices. It can be easily implemented with combinational logic operations on field programmable gate array (FPGA) and provides less hardware and computational overhead. The functionality and performance of the proposed analogue sorting algorithm is evaluated with the simulation model of three phase five-level MMC in MATLAB/Simulink environment. The real time implementation of the proposed sorting algorithm with the SM capacitor voltage balancing strategy is implemented on Altera/Cylone - I (EP1C12Q240C8N) FPGA. A five-level continuous space vector pulsewidth modulation (CSVPWM) is realized on a PIC microcontroller (PIC18F452). A down-scaled model of single-phase five-level MMC is designed and constructed to investigate the reliable and stable operation of MMC with the proposed analogue sorting algorithm and SVPWM method. Simulation and experimental results are presented for validation. 1986-2012 IEEE. -
An efficient technique for generalized conformablePochhammerChree models of longitudinal wave propagation of elastic rod
In this article, we introduce analytical-approximate solutions of time-fractional generalized Pochhammer-Chree equations for wave propagation of elastic rod by means of the q-homotopy analysis of the transform method (q-HATM). In the Caputo sense, basic concepts for fractional derivatives are defined. Several examples are given and the results are illustrated via some surface plots to present the physical representation. The results show that the current methodology is productive, powerful, efficient, easy to use, and ready to incorporate a wide variety of partial fractional differential equations. 2022, Indian Association for the Cultivation of Science. -
An Efficient Technique for One-Dimensional Fractional Diffusion Equation Model for Cancer Tumor
This study intends to examine the analytical solutions to the resulting one-dimensional differential equation of a cancer tumor model in the frame of time-fractional order with the Caputo-fractional operator employing a highly efficient methodology called the q-homotopy analysis transform method. So, the preferred approach effectively found the analytic series solution of the proposed model. The procured outcomes of the present framework demonstrated that this method is authentic for obtaining solutions to a time-fractional-order cancer model. The results achieved graphically specify that the concerned paradigm is dependent on arbitrary order and parameters and also disclose the competence of the proposed algorithm. 2024 The Authors. -
An efficient technique to analyze the fractional model of vector-borne diseases
In the present work, we find and analyze the approximated analytical solution for the vector-borne diseases model of fractional order with the help of q -homotopy analysis transform method ( q -HATM). Many novel definitions of fractional derivatives have been suggested and utilized in recent years to build mathematical models for a wide range of complex problems with nonlocal effects, memory, or history. The primary goal of this work is to create and assess a Caputo-Fabrizio fractional derivative model for Vector-borne diseases. In this investigation, we looked at a system of six equations that explain how vector-borne diseases evolve in a population and how they affect community public health. With the influence of the fixed-point theorem, we establish the existence and uniqueness of the models system of solutions. Conditions for the presence of the equilibrium point and its local asymptotic stability are derived. We discover novel approximate solutions that swiftly converge. Furthermore, the future technique includes auxiliary parameters that are both trustworthy and practical for managing the convergence of the solution found. The current study reveals that the investigated model is notably dependent on the time chronology and also the time instant, which can be effectively studied with the help of the arbitrary order calculus idea. 2022 IOP Publishing Ltd. -
An efficient ZnO and Ag/ZnO honeycomb nanosheets for catalytic green one-pot synthesis of coumarins through Knoevenagel condensation and antibacterial activity
This study pioneers the synthesis of porous Ag/ZnO nanosheets, focusing on their role as a catalyst in Knoevenagel condensation. Notably, these nanosheets display exceptional catalytic efficacy and captivating antibacterial properties. The research delves into the Ag/ZnO catalyst's recyclability and proposes a potential reaction mechanism, marking the first comprehensive exploration of Knoevenagel condensation on porous Ag/ZnO nanosheets. Key findings underscore the successful synthesis of coumarin derivatives using various o-hydroxy benzaldehyde and 1,3-dicarbonyl compounds, with nano-Ag/ZnO serving as a catalyst via a monomode microwave-assisted approach. X-ray diffraction (XRD), Field Emission Scanning Electron Microscopy (FE-SEM), Transmission Electron Microscopy (TEM) and UV-Vis spectroscopy were used in conjunction with other physicochemical methods to characterize the synthesized catalytic samples. The method boasts advantages such as high product yields, brief reaction durations, and the ability to reuse the catalyst for multiple cycles. The Ag/ZnO nanosheets, functioning as an acid catalyst, activate carbonyl groups and facilitate their interaction with methylene-containing active molecules. In addition, antibacterial activity assessments demonstrate the superior effectiveness of Ag/ZnO nanocomposites compared to ZnO nanosheets against Staphylococcus aureus germs. This multifaceted study not only advances catalytic synthesis but also unveils promising biological applications of porous Ag/ZnO nanosheets. 2024 Walter de Gruyter GmbH, Berlin/Boston 2024. -
An electrochemical sensor for nanomolar detection of caffeine based on nicotinic acid hydrazide anchored on graphene oxide (NAHGO)
A simple modified sensor was developed with nicotinic acid hydrazide anchored on graphene oxide (NAHGO), by ultrasonic-assisted chemical route, using hydroxy benzotriazole as a mediator. Structural and morphologies of NAHGO samples were investigated in detail by Fourier-Transform Infrared spectroscopy (FT-IR), Powder X-ray diffraction (P-XRD), Raman spectroscopy, Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and Thermogravimetric analysis (TGA). The detailed morphological examination and electrochemical studies revealed the delaminated sheet with the tube-like structure of NAHGO provided the route for more electroactive surface which influenced the electrooxidation of caffeine with increased current. The electrochemical behaviour of NAHGO on a glassy carbon electrode (GCE) for caffeine detection was demonstrated by employing voltammetric techniques. The influence of scan rate, pH, and concentration on caffeine's peak current was also studied. The NAHGO sensor was employed for the determination of caffeine in imol plus and energy drinks. The detection limit determined was 8.7 109M, and the best value was reported so far. The results show that NAHGO modified electrodes are one of the best preferences to establish new, efficient, and reliable analytical tools for the detection of caffeine. 2021, The Author(s).