Multiferroic properties of composites of PLZT and substituted CoFe2O4

Dipti,Parveen Kumar,J. K. Juneja,Sangeeta Singh,K.K. Raina,Chandra Prakash 한양대학교 세라믹연구소 2015 Journal of Ceramic Processing Research Vol.16 No.4

The magnetoelectric composite with composition xCo0.8Ni0.2Fe2O4 + (1-x) Pb0.9925La0.005Zr0.55Ti0.45O3, x = 0.00, 0.05, 0.10, 0.15 and 1.00 were prepared by solid state reaction method. The structural, microstructural, dielectric, ferroelectric and magnetic properties were studied. The X-ray diffraction and Reitveld refinement of samples confirm the formation of mixed phases of tetragonal and cubic spinel structure in composite. The microstructure of composites shows the coexistence both types of grains corresponding to their phases. Frequency dependent dielectric studies at room temperature depict the decrease in dielectric constant (ε) and increase in tangent loss (tanδ) in composites with increase in ferrite content. P-E Hysteresis loop and M-H hysteresis loop confirms the ferroelectric and ferromagnetic nature of composites. Existence of P-E (ferroelectric) and MH (magnetic) at room temperature confirms the multiferroicity in the composites.

Multiclass covert speech classifi cation using extreme learning machine

Dipti Pawar,Sudhir Dhage 대한의용생체공학회 2020 Biomedical Engineering Letters (BMEL) Vol.10 No.2

The objective of the proposed research is to classify electroencephalography (EEG) data of covert speech words. Six subjectswere asked to perform covert speech tasks i.e mental repetition of four diff erent words i.e ‘left’, ‘right’, ‘up’ and ‘down’. Fifty trials for each word recorded for every subject. Kernel-based Extreme Learning Machine (kernel ELM) was used formulticlass and binary classifi cation of EEG signals of covert speech words. We achieved a maximum multiclass and binaryclassifi cation accuracy of (49.77%) and (85.57%) respectively. The kernel ELM achieves signifi cantly higher accuracycompared to some of the most commonly used classifi cation algorithms in Brain–Computer Interfaces (BCIs). Our fi ndingssuggested that covert speech EEG signals could be successfully classifi ed using kernel ELM. This research involving theclassifi cation of covert speech words potentially leading to real-time silent speech BCI research.

Investigating the Effect of Object-oriented Metrics on Fault Proneness Using Empirical Analysis

Dipti Kumari,Kumar Rajnish 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.2

This paper presents an innovative metric based on a class abstraction to capture aspects of software complexity through combinations of class characteristics. The study also used software metrics effectiveness in finding the classes in different error categories for the three versions of Eclipse, the Java-based open-source Integrated Development Environment. Many studies used Logistic regression models to investigate the ability of OO software metrics to predict fault prone classes. We also used this method not only for binary but also multinomial categorization and empirically validate the ability of metrics to predict fault prone classes in different category using fault data. We conclude that this proposed metric is as effective as the traditional metrics in identifying fault-prone classes in binary categorization and also showing most efficient result for multinomial categorization. We also find that Univariate model for these metrics have same performance as the individual metric with no any learning technique in prediction of fault-proneness.

Seismic behavior of concentrically braced frames designed using direct displacement-based method

Dipti Ranjan Sahoo,Ankit Prakash 한국강구조학회 2019 International Journal of Steel Structures Vol.19 No.1

This study is focussed on the evaluation of seismic performance of concentrically steel braced frames (CBFs) designed using direct displacement-based (DDBD) method. Design displacement profi le in this method is derived from the inelastic mode shape normalized based on fi rst story displacement. Design base shear of a structure is determined using design displacement spectrum and the equivalent viscous damping. Two low- and medium-rise CBFs, namely, 3-story and 6-story, are designed using DDBD method as well as current practice. These study frames are modelled and analysed in a computer software OpenSEES to compare their seismic performance under a set of selected ground motions. Braces are modelled using force-based fi bre-discretized non-linear beam-column elements simulating the eff ects of inelastic buckling, large strain and low-cycle fatigue. The main parameters investigated are the maximum story displacements, the interstory drifts, the residual drifts and the yield mechanisms. DDBD frames exhibited the improved seismic response as compared to those design as per current practice.

Behavior of Unstiffened Steel Plate Shear Wall with Simple Beam-to-column Connections and Flexible Boundary Elements

Dipti Ranjan Sahoo,Balsher Singh Sidhu,Arunesh Kumar 한국강구조학회 2015 International Journal of Steel Structures Vol.15 No.1

This study investigates the effect of type of beam-to-column connections on the overall performance of steel plate shear wall(SPSW) systems under lateral loading condition. An analytical study using finite-element analysis has been conducted on a twostorySPSW system with rigid and pinned beam-to-column connections having constant panel aspect ratio and plate slendernessratio. All boundary elements are designed as per the current code provisions. The influence of the type of connections betweenthe web plates and the boundary elements on the overall performance of SPSW systems is also studied. In addition, the behaviorof SPSW system with flexible boundary members along with pinned beam-to-column connections is also investigated underlateral loading condition. An experimental study has been carried out on a two-story SPSW specimen with flexible boundaryelements to investigate its overall performance under the slow-cyclic loading. Based on the analytical and experimental results,various design issues of SPSW systems are discussed.

Finding Best Mining Scheme for Development of Multinomial Software Fault Prediction Model

Dipti Kumari,Kumar Rajnish 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.5

This paper discuss different classification methods toward reliability and quality improvement of software systems by predicting fault-prone module before testing. Classification capability of Data mining techniques and Object-oriented property based knowledge stored in Object-Oriented metrics are used to classify the software module as fault-prone in different error categories or not fault-prone. Three versions of Eclipse, the java-based Open source Integrated Development environment as dataset for training and testing all the classification based data mining techniques are used. First of all, Threshold base feature ranking (i.e. Area under the ROC curve) is used for selecting effective OO-metrics in building prediction model. After that using those subsets of selected attributes, classification models are built with 41 different classifiers for multinomial classification in fault detection systems. Finally, the performance of a classifier is evaluated with respect to the PRC performance metric. Based on the performance results appropriate classifiers (Random Committee, Random Tree, Randomizable Filtered classifier and IBK) which depict a higher performance and accuracy compared to the others are selected. Our results indicate that Random Tree, Random Committee and Randomizable Filtered Classifier have same performance. IBK classifier also has same performance but little bit less and Kstar has less performance compared to previous four selected classifiers.

Large area flexible pressure/strain sensors and arrays using nanomaterials and printing techniques

Dipti Gu,Chithra Parameswaran 나노기술연구협의회 2019 Nano Convergence Vol.6 No.28

Sensors are becoming more demanding in all spheres of human activities for their advancement in terms of fabrication and cost. Several methods of fabrication and configurations exist which provide them myriad of applications. However, the advantage of fabrication for sensors lies with bulk fabrication and processing techniques. Exhaustive study for process advancement towards miniaturization from the advent of MEMS technology has been going on and progressing at high pace and has reached a highly advanced level wherein batch production and low cost alternatives provide a competitive performance. A look back to this advancement and thus understanding the route further is essential which is the core of this review in light of nanomaterials and printed technology based sensors. A subjective appraisal of these developments in sensor architecture from the advent of MEMS technology converging present date novel materials and process technologies through this article help us understand the path further.

Different nanostructure cathode catalysts application for direct methanol fuel cell

Dipti, Sharmin Sultana,Chung, Uoo-Chang,Kim, Jong-Pil,Chung, Won-Sub WILEY-VCH Verlag 2007 Physica status solidi. PSS. A, Applications and ma Vol.204 No.12

<P>Direct methanol fuel cell (DMFC) belongs to the same family of energy conversion device and the application of new hydrogen storage nanomaterials such as carbon nanotube (CNTs) supported catalysts is being addressed in an increasing industrial approach. In this present study, multiwall carbon nanotube supported Pt and Pt-Ni nanoparticles were prepared as cathode catalysts for direct methanol fuel cell application. Transmission electron microscopy and X-ray diffraction analyses indicated the formation of well-dispersed Pt and Pt-Ni nanoparticles having sizes of around 2 ∼ 4 nm on carbon nanotube. Furthermore, the electrochemical characterization by the cyclic voltammetry (CV) demonstrated that these catalysts have higher catalytic activity and the methanol oxidation reaction of the Pt-Ni/CNTs is respectively almost similar and slightly higher than Pt/CNTs electrocatalysts. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)</P>

Proline-based polymeric monoliths: Synthesis, characterization, and applications as organocatalysts in aldol reaction

Garg, Dipti,Ahn, J.-H.,Chauhan, Ghanshyam S. Wiley Subscription Services, Inc., A Wiley Company 2010 Journal of polymer science Part A, Polymer chemist Vol.48 No.5

<P>Proline-based polymer monoliths were synthesized via green protocol using lipase-catalyzed esterification of methacrylic acid and 4-hydroxyproline. Prolinyl methacrylate thus prepared was polymerized in situ as crosslinked monolith. The monolith was characterized by various techniques such as Fourier transform infrared, <SUP>1</SUP>H-NMR, <SUP>13</SUP>C-NMR, scanning electron microscopy (SEM), X-ray diffraction (XRD), and nitrogen analysis and used as catalyst in aldol reactions. The swelling behavior of the monolith was also studied as function of various external parameters like pH and temperature. The monoliths synthesized with 1% crosslinker was selected as candidate monolith for use as catalyst in aldol reaction, which was studied as a function of time, temperature, substrate structure, and amount of water:EtOH. The catalysts exhibited high efficiency in the cross aldol reaction, especially with the aromatic substrates having electron withdrawing substituent, and also good activity retention was observed when recycleability was studied up to five cycles. © 2010 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 48: 1007–1015, 2010</P> <B>Graphic Abstract</B> <P>Proline-based polymer monoliths were synthesized via green protocol using lipase-catalyzed esterification of methacrylic acid and 4-hydroxyproline. The monomer was polymerized to polymer monoliths, and the latter were used as heterogeneous polymer catalysts in the aldol reaction that was studied in three forms viz. simple aldol, cross aldol, and ketone-aldehyde reaction. The catalysts exhibited high efficiency in the cross aldol reaction, especially with the aromatic substrates having electron withdrawing substituent, and reasonable retention of catalytic efficiency up to five cycles. <img src='wiley_img/0887624X-2010-48-5-POLA23845-gra001.gif' alt='wiley_img/0887624X-2010-48-5-POLA23845-gra001'> </P>

Salinity-Induced Changes in Peroxidase Activity and Cell-Wall Polysaccharides in Vigna

Pujari, Dipti S.,Chanda, Sumitra V. 한국식물학회 2003 Journal of Plant Biology Vol.46 No.2

We investigated the effect of salinity on the development of seedlings of Vigna unguiculata. At various time intervals, the hypocotyls were measured to estimate the effect of salt concentration on growth parameters. Control plants were tallest and had the greatest fresh weights, whereas these values were lowest in seedlings treated with high levels of salt. Three hydrogen donors -- caffeic acid, ferulic acid, and pyrogalol -- were studied to determine the changes in peroxidase activity for both cytoplasmic and wall-bound fractions. Activity was inversely correlated with hypocotyl elongation. A clear concentration effect was also observed for contents of pectic polysaccharides, low-molecular-weight xyloglucan, and high-molecular-weight xyloglucan, with control seedlings showing lower levels of those wall components than that recorded in the salt-treated seedlings. Here, we also discuss the role of peroxidase and wall components in hypacotyl elongation and growth of Vigna when seedlings undergo saline stress.