Search results for: Megha Khanna

Authors: Ruchika Malhotra, Megha Khanna

Abstract:

The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: Change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics.

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Authors: Porag Jyoti Ligira, Gargi Khanna

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The paper presents a simulation study of the electrical characteristic of Bulk Planar Junctionless Transistor (BPJLT) using spacer. The BPJLT is a transistor without any PN junctions in the vertical direction. It is a gate controlled variable resistor. The characteristics of BPJLT are analyzed by varying the oxide material under the gate. It can be shown from the simulation that an ideal subthreshold slope of ~60 mV/decade can be achieved by using highk dielectric. The effects of variation of spacer length and material on the electrical characteristic of BPJLT are also investigated in the paper. The ION / IOFF ratio improvement is of the order of 107 and the OFF current reduction of 10-4 is obtained by using gate dielectric of HfO2 instead of SiO2.

Keywords: BPJLT, double gate, high-k, spacer.

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Authors: Aditya Khanna, Andrei Kotousov

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A novel method is presented for obtaining the stress field induced by an edge dislocation in a multilayered composite. To demonstrate the applications of the obtained solution, we consider the problem of an interfacial crack in a periodically layered bimaterial medium. The crack is modelled as a continuous distribution of edge dislocations and the Distributed Dislocation Technique (DDT) is utilized to obtain numerical results for the energy release rate (ERR). The numerical implementation of the dislocation solution in MATLAB is also provided.

Keywords: Distributed dislocation technique, Edge dislocation, Elastic field, Interfacial crack, Multi-layered composite.

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Authors: Parul Khanna, Pavol Zavarsky, Dale Lindskog

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Doxing is a term derived from documents, and hence consists of collecting information on an organization or individual through social media websites, search engines, password cracking methods, social engineering tools and other sources of publicly displayed information. The main purpose of doxing attacks is to threaten, embarrass, harass and humiliate the organization or individual. Various tools are used to perform doxing. Tools such as Maltego visualize organization’s architecture which helps in determining weak links within the organization. This paper discusses limitations of Maltego Chlorine CE 3.6.0 and suggests measures as to how organizations can use these tools to protect themselves from doxing attacks.

Keywords: Advanced Persistent Threat, FOCA, OSINT, PII.

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Authors: S. Yamini Sudha, Ashok Khanna

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Owing to the stringent environmental legislations, CO2 capture and sequestration is one of the viable solutions to reduce the CO2 emissions from various sources. In this context, Ionic liquids (ILs) are being investigated as suitable absorption media for CO2 capture. Due to their non-evaporative, non-toxic, and non-corrosive nature, these ILs have the potential to replace the existing solvents like aqueous amine solutions for CO2 separation technologies. Thus, the present work aims at studying the important aspects such as the interactions of CO2 molecule with different anions (F-, Br-, Cl-, NO3 -, BF4 -, PF6 -, Tf2N-, and CF3SO3 -) that are commonly used in ILs through molecular modeling. In this, the minimum energy structures have been obtained using Ab initio based calculations at MP2 (Moller-Plesset perturbation) level. Results revealed various degrees of distortion of CO2 molecule (from its linearity) with the anions studied, most likely due to the Lewis acid-base interactions between CO2 and anion. Furthermore, binding energies for the anion-CO2 complexes were also calculated. The implication of anion-CO2 interactions to the solubility of CO2 in ionic liquids is also discussed.

Keywords: CO2, Ionic liquids, capture, molecular modeling, sequestration.

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Authors: Pooja, Megha Kulshrestha, V. K. Banga, Parvinder S. Sandhu

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To support mobility in ATM networks, a number of technical challenges need to be resolved. The impact of handoff schemes in terms of service disruption, handoff latency, cost implications and excess resources required during handoffs needs to be addressed. In this paper, a one phase handoff and route optimization solution using reserved PVCs between adjacent ATM switches to reroute connections during inter-switch handoff is studied. In the second phase, a distributed optimization process is initiated to optimally reroute handoff connections. The main objective is to find the optimal operating point at which to perform optimization subject to cost constraint with the purpose of reducing blocking probability of inter-switch handoff calls for delay tolerant traffic. We examine the relation between the required bandwidth resources and optimization rate. Also we calculate and study the handoff blocking probability due to lack of bandwidth for resources reserved to facilitate the rapid rerouting.

Keywords: Wireless ATM, Mobility, Latency, Optimization rateand Blocking Probability.

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Authors: Swati Khanna, Arun Goyal, Vijayanand S. Moholkar

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Batch fermentation of 5, 10 and 25 g/L biodiesel derived crude glycerol was carried out at 30, 37 and 450C by Clostridium pasteurianum cells immobilized on silica. Maximum yield of 1,3-propanediol (PDO) (0.60 mol/mol), and ethanol (0.26 mol/mol) were obtained from 10 g/L crude glycerol at 30 and 370C respectively. Maximum yield of butanol (0.28 mol/mol substrate added) was obtained at 370C with 25 g/L substrate. None of the three products were detected at 45oC even after 10 days of fermentation. Only traces of ethanol (0.01 mol/mol) were detected at 450C with 5 g/L substrate. The results obtained for 25 g/L substrate utilization were fitted in first order rate equation to obtain the values of rate constant at three different temperatures for bioconversion of glycerol. First order rate constants for bioconversion of glycerol at 30, 37 and 45oC were found to be 0.198, 0.294 and 0.029/day respectively. Activation energy (Ea) for crude glycerol bioconversion was calculated to be 57.62 kcal/mol.

Keywords: activation energy, Clostridium pasteurianum, crude glycerol, immobilization

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Authors: Rajlaxmi Chouhan, Pritee Khanna

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In this manuscript, a wavelet-based blind watermarking scheme has been proposed as a means to provide security to authenticity of a fingerprint. The information used for identification or verification of a fingerprint mainly lies in its minutiae. By robust watermarking of the minutiae in the fingerprint image itself, the useful information can be extracted accurately even if the fingerprint is severely degraded. The minutiae are converted in a binary watermark and embedding these watermarks in the detail regions increases the robustness of watermarking, at little to no additional impact on image quality. It has been experimentally shown that when the minutiae is embedded into wavelet detail coefficients of a fingerprint image in spread spectrum fashion using a pseudorandom sequence, the robustness is observed to have a proportional response while perceptual invisibility has an inversely proportional response to amplification factor “K". The DWT-based technique has been found to be very robust against noises, geometrical distortions filtering and JPEG compression attacks and is also found to give remarkably better performance than DCT-based technique in terms of correlation coefficient and number of erroneous minutiae.

Keywords: Fingerprint watermarking, minutiae, discrete wavelet transform, PN sequence

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Megha Rao, Søren H. Jensen, Xiufu Sun, Anke Hagen, Mogens B. Mogensen

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Solid oxide electrolysis cells have an immense potential in converting CO₂ and H₂O into syngas during co-electrolysis operation. The produced syngas can be further converted into hydrocarbons. This kind of technology is called power-to-gas or power-to-liquid. To produce hydrocarbons via this route, durability of the cells is still a challenge, which needs to be further investigated in order to improve the cells. In this work, various nickel-yttria stabilized zirconia (Ni-YSZ) fuel electrode supported or YSZ electrolyte supported cells, cerium gadolinium oxide (CGO) barrier layer, and an oxygen electrode are investigated for durability under co-electrolysis conditions in both galvanostatic and potentiostatic conditions. While changing the gas on the oxygen electrode, keeping the fuel electrode gas composition constant, a change in the gas concentration arc was observed by impedance spectroscopy. Measurements of open circuit potential revealed the presence of leaks in the setup. It is speculated that the change in concentration impedance may be related to the leaks. Furthermore, the cells were also tested under pressurized conditions to find an inter-play between the leak rate and the pressure. A mathematical modeling together with electrochemical and microscopy analysis is presented.

Keywords: Co-electrolysis, solid oxide electrolysis cells, leaks, durability, gas concentration.

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Authors: Deepti Tamrakar, Pritee Khanna

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This manuscript presents, palmprint recognition by combining different texture extraction approaches with high accuracy. The Region of Interest (ROI) is decomposed into different frequencytime sub-bands by wavelet transform up-to two levels and only the approximate image of two levels is selected, which is known as Approximate Image ROI (AIROI). This AIROI has information of principal lines of the palm. The Competitive Index is used as the features of the palmprint, in which six Gabor filters of different orientations convolve with the palmprint image to extract the orientation information from the image. The winner-take-all strategy is used to select dominant orientation for each pixel, which is known as Competitive Index. Further, PCA is applied to select highly uncorrelated Competitive Index features, to reduce the dimensions of the feature vector, and to project the features on Eigen space. The similarity of two palmprints is measured by the Euclidean distance metrics. The algorithm is tested on Hong Kong PolyU palmprint database. Different AIROI of different wavelet filter families are also tested with the Competitive Index and PCA. AIROI of db7 wavelet filter achievs Equal Error Rate (EER) of 0.0152% and Genuine Acceptance Rate (GAR) of 99.67% on the palm database of Hong Kong PolyU.

Keywords: DWT, EER, Euclidean Distance, Gabor filter, PCA, ROI.

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Authors: Shyam Kumar, Nannuri Srinivasulu, Ashok Khanna

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Bubble columns have a variety of applications in absorption, bio-reactions, catalytic slurry reactions, and coal liquefaction; because they are simple to operate, provide good heat and mass transfer, having less operational cost. The use of Computational Fluid Dynamics (CFD) for bubble column becomes important, since it can describe the fluid hydrodynamics on both local and global scale. Euler- Euler two-phase fluid model has been used to simulate two-phase (air and water) transient up-flow in bubble column (15cm diameter) using FLUENT6.3. These simulations and experiments were operated over a range of superficial gas velocities in the bubbly flow and churn turbulent regime (1 to16 cm/s) at ambient conditions. Liquid velocity was varied from 0 to 16cm/s. The turbulence in the liquid phase is described using the standard k-ε model. The interactions between the two phases are described through drag coefficient formulations (Schiller Neumann). The objectives are to validate CFD simulations with experimental data, and to obtain grid-independent numerical solutions. Quantitatively good agreements are obtained between experimental data for hold-up and simulation values. Axial liquid velocity profiles and gas holdup profiles were also obtained for the simulation.

Keywords: Bubble column, Computational fluid dynamics, Gas holdup profile, k-ε model.

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Authors: Harish Chander, Balwinder Singh, Ravinder Khanna

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In this paper, we present the comparative subjective analysis of Improved Minima Controlled Recursive Averaging (IMCRA) Algorithm, the Kalman filter and the cascading of IMCRA and Kalman filter algorithms. Performance of speech enhancement algorithms can be predicted in two different ways. One is the objective method of evaluation in which the speech quality parameters are predicted computationally. The second is a subjective listening test in which the processed speech signal is subjected to the listeners who judge the quality of speech on certain parameters. The comparative objective evaluation of these algorithms was analyzed in terms of Global SNR, Segmental SNR and Perceptual Evaluation of Speech Quality (PESQ) by the authors and it was reported that with cascaded algorithms there is a substantial increase in objective parameters. Since subjective evaluation is the real test to judge the quality of speech enhancement algorithms, the authenticity of superiority of cascaded algorithms over individual IMCRA and Kalman algorithms is tested through subjective analysis in this paper. The results of subjective listening tests have confirmed that the cascaded algorithms perform better under all types of noise conditions.

Keywords: Speech enhancement, spectral domain, time domain, PESQ, subjective analysis, objective analysis.

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