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Particle Swarm Optimization Based Support Vector Regression for Blind Image Restoration

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Journal of Computer Science & Technology 2012年第5期27卷 989-995页

作者： Ratnakar dash Pankaj Kumar Sa Banshidhar Majhi Computer Science and Engineering Department National Institute of Technology RourkelaRourkela 769008India

This paper presents a swarm intelligence based parameter optimization of the support vector machine （SVM） for blind image restoration. In this work, SVM is used to solve a regression problem. Support vector regression （SVR） has been utilized to obtain a true mapping of images from the observed noisy blurred images. The parameters of SVR are optimized through particle swarm optimization （PSO） technique. The restoration error function has been utilized as the fitness function for PSO. The suggested scheme tries to adapt the SVM parameters depending on the type of blur and noise strength and the experimental results validate its effectiveness. The results show that the parameter optimization of the SVR model gives better performance than conventional SVR model as well as other competent schemes for blind image restoration.

关键词： image restoration support vector regression particle swarm optimization

A novel control strategy of a variable-speed doubly-fed-induction-generator-based wind energy conversion system

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Clean Energy 2024年第1期8卷 153-170页

作者： Shibani Prasad Mohapatra Pradipta Kishore dash Department of Electrical Engineering Siksha O Anusandhan Deemed to be UniversityBhubaneswar-751030OdishaIndia Multidisciplinary Research Cell Siksha O Anusandhan Deemed to be UniversityBhubaneswar-751030OdishaIndia

This paper aims to address the issue of control of a variable-speed wind turbine based on doubly-fed induction generators. In this work,an effort is made to extract the maximum efficiency from a doubly-fed induction generator-based variable-speed wind turbine by controlling the rotor current. In the first step, a maximum power point tracking technique is used to extract the maximum power from theturbine. Then a stator-flux-oriented vector control strategy is employed to control the rotor-side current. Subsequently, a grid voltagevector-oriented control strategy is used to control the grid-side system of the grid-connected generator. Considering the nonlinearityand parameter uncertainty of the system, an active disturbance rejection controller with a sliding-mode-based extended-state observeris developed for the above-mentioned control strategies. Furthermore, the stability of the controller is tested and the performance of thecontroller is compared with the classical proportional-integral controller based on disturbance rejection, robustness and tracking capability in a highly non-linear wind speed variation scenario. Modelling, control and comparison are conducted in the MATLAB®/Simulink®environment. Finally, a real-time hardware set-up is presented using the dSPACE ds-1104 R&D processing board to validate the controlscheme. From the result of the experiments, it is seen that the proposed controller takes 10-15 control cycles to settle to its steady-statevalues, depending on the control loop, whereas the conventional proportional-integral controller takes 60-75 control cycles. As a result,the settling time for the proposed control scheme is shorter than that of the proportional-integral controller.

关键词： doubly-fed induction generator variable-speed wind turbine vector control active disturbance rejection controller stability analysis

In vitro antioxidant assessment and a rapid HPTLC bioautographic method for the detection of anticholinesterase inhibitory activity of Geophila repens

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Journal of Integrative Medicine 2017年第3期15卷 231-241页

作者： Umesh Chandra dash Atish Kumar Sahoo Regional Plant Resource Centre Medicinal & Aromatic Plant Division Forest & Environment DepartmentGovt. of Odisha Nayapalli Bhubaneswar 751015 India

OBJECTIVE： Geophila repens （L.） I. M. Johnst. （Rubiaceae）, a small, creeping, perennial herb, is claimed to have memory-enhancing property. The goal of this study was to assess its antioxidant and anticholinesterase activity and conduct a rapid bioautographic enzyme assay for screening acetylcholinesterase （ACHE） and butyrylcholinesterase （BChE） inhibition of G. repens extracts. METHODS： Antioxidant activity of G. repens extracts was assessed by performing 1,1-diphenyl-2- picrylhydrazyl （DPPH）, nitric oxide （NO）, superoxide （SOD）, hydroxyl （OH） and total antioxidant capacity （TAC） assays. Anticholinesterase activity was investigated by quantifying the AChE and BChE inhibitory activities of chloroform （CGR）, ethyl acetate （EGR） and methanol （MGR） extract fractions from G. repens leaves. A rapid high-performance thin-layer chromatography （HPTLC） bioautographic method for the detection of AChE and BChE inhibition was performed. RESULTS： Among all extract fractions, EGR exhibited the highest half maximal inhibitory concentration （IC50） in DPPH, SOD, NO, OH and TAC assays, with IC50 of （38.33 ± 3.21）, （45.14 ±1.78）, （59.81± 1.32）, （39.45 ± 0.79） and （43.76 ± 0.81 ） μg/mL respectively. EGR displayed competitive, reversible inhibition of AChE and BChE activities with IC50 of （68.63±0.45） and （59.45 ±0.45）μg/mL, respectively. Total phenolic and flavonoids contents of EGR were found to be 360.42 mg gallic acid equivalents and 257.31 mg quercetin equivalents per gram of extract. Phytoconstituents of the EGR extract that were inhibitors of cholinesterase produced white spots on the yellow background of HPTLC plates in the bioautographic test. CONCLUSION： The results of this study revealed that phenols and flavonoids could be responsible for the antioxidant, anticholinesterase activities of G. repens.

关键词： Geophila repens Alzheimer disease acetylcholinesterase butyrylcholinesterase fingerprint bioautographic phenolic, antioxidant

A new protection scheme for PV-wind based DC-ring microgrid by using modified multifractal detrended fluctuation analysis

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Protection and Control of Modern Power Systems 2022年第1期7卷 100-123页

作者： Kanche Anjaiah Pradipta Kishore dash Mrutyunjaya Sahani Department of Electrical Engineering Siksha‘O’Anusandhan Deemed to be UniversityBhubaneswarOdishaIndia Multidisciplinary Research Cell Siksha‘O’Anusandhan Deemed to be UniversityBhubaneswarOdishaIndia Department of Electrical and Electronics Engineering Siksha‘O’Anusandhan Deemed to be UniversityBhubaneswarOdishaIndia

This paper presents fault detection,classification,and location for a PV-Wind-based DC ring microgrid in the MATLAB/SIMULINK ***,DC fault signals are collected from local measurements to examine the outcomes of the proposed *** detection is carried out for all faults,(i.e.,cable and arc faults)under two cases of fault resistance and distance variation,with the assistance of primary and secondary detection techniques,***-order differential current derivatived2I3 dt2and sliding mode window-based Pearson’s correlation *** fault classification a novel approach using modified multifractal detrended fluctuation analysis(M-MFDFA)is *** advantage of this method is its ability to estimate the local trends of any order polynomial function with the help of polynomial and trigonometric *** also doesn’t require any signal processing algorithm for decomposition resulting and this results in a reduction of computational *** detected fault signals are directly passed through the M-MFDFA classifier for fault type *** enhance the performance of the proposed classifier,statistical data is obtained from the M-MFDFA feature vectors,and the obtained data is plotted in 2-D and 3-D scatter plots for better *** fault distance estimation is carried out for all types of faults in the DC ring bus microgrid with the assistance of recursive least squares with a forgetting factor(FF-RLS).To verify the performance and superiority of the proposed classifier,it is compared with existing classifiers in terms of features,classification accuracy(CA),and relative computational time(RCT).

关键词： DC ring microgrid Differential current Fault resistance Detection Classification Fault location estimation Multifractal detrended fluctuation analysis

Effect of Silver Nanoparticles on Growth of Eukaryotic Green Algae

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Nano-Micro Letters 2012年第3期4卷 158-165页

作者： Anjali dash Anand P.Singh Bansh R.Chaudhary Sunil K.Singh Debabrata dash Department of Biochemistry Institute of Medical SciencesBanaras Hindu University Centre of Advanced Study in Botany Banaras Hindu University

Silver nanoparticles,endowed with powerful antimicrobial property,are the most widely used nanomaterial in consumer products,with associated risk of their easy access to environment and freshwater ecosystems by surface *** toxic effects of nanosilver on bacterial,fungal and mammalian cells have been documented,its impact on algal growth remains *** oedogonia and Chara vulgaris are predominant members of photosynthetic eukaryotic algae,which form major component of global aquatic *** we report for the first time that nanosilver has significant adverse effects on growth and morphology of these filamentous green algae in a dose-dependent *** of algal thalli to increasing concentrations of silver nanoparticles resulted in progressive depletion in algal chlorophyll content,chromosome instability and mitotic disturbance,associated with morphological malformations in algal *** micrographs revealed dramatic alterations in cell wall in nanoparticle-treated algae,characterized with cell wall rupture and degradation in *** these observations underscore severe deleterious effects of nanosilver on aquatic environment,the information can also be exploited as a bioengineering strategy to control unwanted and persistent growth of noxious algal weeds that clog the municipal water supply and water channels and produce fouling of water bodies.

关键词： Silver nanoparticles Green algae Algal growth Photosynthetic pigment Nanotoxicity

Simulation of abrasive flow machining process for 2D and 3D mixture models

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Frontiers of Mechanical Engineering 2015年第4期10卷 424-432页

作者： Rupalika dash Kalipada MAITY Mechanical Engineering Department National Institute of TechnologyRourkela 769008 India

Improvement of surface finish and material removal has been quite a challenge in a finishing operation such as abrasive flow machining （AFM）. Factors that affect the surface finish and material removal are media viscosity, extrusion pressure, piston velocity, and particle size in abrasive flow machining process. Performing experiments for all the parameters and accurately obtaining an optimized parameter in a short time are difficult to accomplish because the operation requires a precise finish. Computational fluid dynamics （CFD） simulation was employed to accurately determine optimum parameters. In the current work, a 2D model was designed, and the flow analysis, force calculation, and material removal prediction were performed and compared with the available experi- mental data. Another 3D model for a swaging die finishing using AFM was simulated at different viscosities of the media to study the effects on the controlling parameters. A CFD simulation was performed by using commercially available ANSYS FLUENT. Two phases were considered for the flow analysis, and multiphase mixture model was taken into account. The fluid was considered to be a Newtonian fluid and the flow laminar with no wall slip.

关键词： abrasive flow machining (AFM) computational fluid dynamics (CFD) modeling mixture model

Stress distribution variations during nanoindentation failure of hard coatings on silicon substrates

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Nanotechnology and Precision Engineering 2023年第4期6卷 1-10页

作者： Ritambhara dash Kushal Bhattacharyya Arnab S.Bhattacharyya Department of Metallurgical and Materials Engineering Central University of JharkhandRanchi 835205India Department of Mechanical Engineering Netaji Subhash Engineering CollegeKolkata 700152India Centre of Excellence in Green and Efficient Energy Technology(CoE GEET) Central University of JharkhandRanchi 835205India

Regarding quality inspection of technologically important nanocomposite hard coatings based on Ti,B,Si,C,and N and bioceramics such as hydroxyapatite that are used in small-scale high-precision devices and bio-implants,it is essential to study the failure mechanisms associated with nanoindentation,such as fracture,delamination,and *** stress imposed by the indenter can affect the fracture morphology and the interfacial fracture energy,depending on indenter shape,substrate type,crystallographic properties,pre-existing flaws,internal microcracks,and *** here are finite-element-based fracture studies that provide insights into the different cracking mechanisms related to the aforementioned failure process,showing that the fracture morphology is affected by the interaction of different cracking *** interfacial fracture energy,toughness,and residual stress are calculated using existing models with minor adjustments,and it is found that increasing the indenter sharpness improves the shear stress distribution,making the coating more prone to *** on the prevailing type of stress,the stress distribution beneath the depression results in either crack formation or a dislocation pile-up leading to strain *** forms of resistances resulting from the indentation process are found to affect the tip–sample conduction,and because of its stronger induced plasticity than that of a Berkovich indenter tip,a sharper cube-corner tip produces more resistance.

关键词： Nanoindentation Hard film Finite-element analysis(FEA) Cracking mechanism Stress

Prospects of gallium nitride double drift region mixed tunneling avalanche transit time diodes for operation in F, Y and THz bands

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Journal of Semiconductors 2016年第5期37卷 24-29页

作者： Pranati Panda Gananath dash Electron Devices Group at the School of Physics Sambalpur University

The potential of GaN as a wide band gap semiconductor is explored for application as double drift region mixed tunneling avalanche transit time （MITATT） diodes for operation at 120 GHz, 220 GHz and 0.35 THz using some computer simulation methods developed by our group. The salient features of our results have uncovered some peculiarities of the GaN based MITATT devices. An efficiency of more than 20% right up to a frequency of 0.35 THz （from the GaN MITATT diode） seems highly encouraging but a power output of only 0.76 W is indicative of its dismal fate. The existence of a noise measure minimum at the operating frequency of 0.35 THz is again exhilarating but the value of the minimum is miserably high i.e. more than 33 dB. Thus, although GaN is a wide band gap semiconductor, the disparate carrier velocities prevent its full potential from being exploited for application as MTATT diodes.

关键词： GaN MITATT tunneling carrier velocity

Automatic Classification of Cardiac Arrhythmias Based on Hybrid Features and Decision Tree Algorithm

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International Journal of Automation and computing 2020年第4期17卷 551-561页

作者： Santanu Sahoo Asit Subudhi Manasa dash Sukanta Sabut Department of Electronics and Communication Engineering ITERSOA UniversityBhubaneswar 751030India Department of Mathematics Silicon Institute of TechnologyBhubaneswar 751024India School of Electronics Engineering KIIT deemed to be UniversityBhubaneswar 751024India

Accurate classification of cardiac arrhythmias is a crucial task because of the non-stationary nature of electrocardiogram(ECG)*** a life-threatening situation,an automated system is necessary for early detection of beat abnormalities in order to reduce the mortality *** this paper,we propose an automatic classification system of ECG beats based on the multi-domain features derived from the ECG *** experimental study was evaluated on ECG signals obtained from the MIT-BIH Arrhythmia *** feature set comprises eight empirical mode decomposition(EMD)based features,three features from variational mode decomposition(VMD)and four features from RR *** total,15 features are ranked according to a ranker search approach and then used as input to the support vector machine(SVM)and C4.5 decision tree classifiers for classifying six types of arrhythmia *** proposed method achieved best result in C4.5 decision tree classifier with an accuracy of 98.89%compared to cubic-SVM classifier which achieved an accuracy of 95.35%*** accuracy measures,all other parameters such as sensitivity(Se),specificity(Sp)and precision rates of 95.68%,99.28%and 95.8%was achieved better in C4.5 *** the computational time of 0.65 s with an error rate of 0.11 was achieved which is very less compared to *** multi-domain based features with decision tree classifier obtained the best results in classifying cardiac arrhythmias hence the system could be used efficiently in clinical practices.

关键词： Electrocardiogram(ECG) cardiac arrhythmias empirical mode decomposition(EMD) variational mode decomposition(VMD) hybrid features decision tree classifier