arXiv subjects

Vivek Kumar

Publications and source records attributed to Vivek Kumar.

At least 91 records · Page 5Linked to original sources

arXiv2020

An empirical study of Conv-TasNet

Conv-TasNet is a recently proposed waveform-based deep neural network that achieves state-of-the-art performance in speech source separation. Its architecture consists of a learnable encoder/decoder and a separator that operates on top of this learned space. Various improvements have been proposed to Conv-TasNet. However, they mostly focus on the separator, leaving its encoder/decoder as a (shallow) linear operator. In this paper, we conduct an empirical study of Conv-TasNet and propose an enhancement to the encoder/decoder that is based on a (deep) non-linear variant of it. In addition, we experiment with the larger and more diverse LibriTTS dataset and investigate the generalization capabilities of the studied models when trained on a much larger dataset. We propose cross-dataset evaluation that includes assessing separations from the WSJ0-2mix, LibriTTS and VCTK databases. Our results show that enhancements to the encoder/decoder can improve average SI-SNR performance by more than 1 dB. Furthermore, we offer insights into the generalization capabilities of Conv-TasNet and the potential value of improvements to the encoder/decoder.

eess.AS↗

arXiv2019

A Reference Architecture for Smart and Software-defined Buildings

The vision encompassing Smart and Software-defined Buildings (SSDB) is becoming more and more popular and its implementation is now more accessible due to the widespread adoption of the IoT infrastructure. Some of the most important applications sustaining this vision are energy management, environmental comfort, safety and surveillance. This paper surveys IoT and SSB technologies and their cooperation towards the realization of Smart Spaces. We propose a four-layer reference architecture and we organize related concepts around it. This conceptual frame is useful to identify the current literature on the topic and to connect the dots into a coherent vision of the future of residential and commercial buildings.

cs.SE↗

arXiv2019

Prediction of Malignant & Benign Breast Cancer: A Data Mining Approach in Healthcare Applications

As much as data science is playing a pivotal role everywhere, healthcare also finds it prominent application. Breast Cancer is the top rated type of cancer amongst women; which took away 627,000 lives alone. This high mortality rate due to breast cancer does need attention, for early detection so that prevention can be done in time. As a potential contributor to state-of-art technology development, data mining finds a multi-fold application in predicting Brest cancer. This work focuses on different classification techniques implementation for data mining in predicting malignant and benign breast cancer. Breast Cancer Wisconsin data set from the UCI repository has been used as experimental dataset while attribute clump thickness being used as an evaluation class. The performances of these twelve algorithms: Ada Boost M 1, Decision Table, J Rip, Lazy IBK, Logistics Regression, Multiclass Classifier, Multilayer Perceptron, Naive Bayes, Random forest and Random Tree are analyzed on this data set. Keywords- Data Mining, Classification Techniques, UCI repository, Breast Cancer, Classification Algorithms

cs.LG↗

arXiv2019

A Conjoint Application of Data Mining Techniques for Analysis of Global Terrorist Attacks -- Prevention and Prediction for Combating Terrorism

Terrorism has become one of the most tedious problems to deal with and a prominent threat to mankind. To enhance counter-terrorism, several research works are developing efficient and precise systems, data mining is not an exception. Immense data is floating in our lives, though the scarce availability of authentic terrorist attack data in the public domain makes it complicated to fight terrorism. This manuscript focuses on data mining classification techniques and discusses the role of United Nations in counter-terrorism. It analyzes the performance of classifiers such as Lazy Tree, Multilayer Perceptron, Multiclass and Naïve Bayes classifiers for observing the trends for terrorist attacks around the world. The database for experiment purpose is created from different public and open access sources for years 1970-2015 comprising of 156,772 reported attacks causing massive losses of lives and property. This work enumerates the losses occurred, trends in attack frequency and places more prone to it, by considering the attack responsibilities taken as evaluation class.

cs.LG↗

arXiv2019

Comparative Performance Analysis of Image De-noising Techniques

Noise is an important factor which when get added to an image reduces its quality and appearance. So in order to enhance the image qualities, it has to be removed with preserving the textural information and structural features of image. There are different types of noises exist who corrupt the images. Selection of the denoising algorithm is application dependent. Hence, it is necessary to have knowledge about the noise present in the image so as to select the appropriate denoising algorithm. Objective of this paper is to present brief account on types of noises, its types and different noise removal algorithms. In the first section types of noises on the basis of their additive and multiplicative nature are being discussed. In second section a precise classification and analysis of the different potential image denoising algorithm is presented. At the end of paper, a comparative study of all these algorithms in context of performance evaluation is done and concluded with several promising directions for future research work.

cs.CV↗

arXiv2019

Image De-Noising For Salt and Pepper Noise by Introducing New Enhanced Filter

When an image is formed, factors such as lighting (spectra, source, and intensity) and camera characteristics (sensor response, lenses) affect the appearance of the image. Therefore, the prime factor that reduces the quality of the image is noise. It hides the important details and information of images. In order to enhance the qualities of the image, the removal of noises become imperative and that should not at the cost of any loss of image information. Noise removal is one of the pre-processing stages of image processing. In this paper a new method for the enhancement of grayscale images is introduced, when images are corrupted by fixed valued impulse noise (salt and pepper noise). The proposed methodology ensures a better output for the low and medium density of fixed value impulse noise as compared to the other famous filters like Standard Median Filter (SMF), Decision Based Median Filter (DBMF) and Modified Decision Based Median Filter (MDBMF) etc. The main objective of the proposed method was to improve peak signal to noise ratio (PSNR), visual perception and reduction in the blurring of the image. The proposed algorithm replaced the noisy pixel by trimmed mean value. When previous pixel values, 0s, and 255s are present in the particular window and all the pixel values are 0s and 255s then the remaining noisy pixels are replaced by mean value. The gray-scale image of mandrill and Lena were tested via the proposed method. The experimental result shows better peak signal to noise ratio (PSNR), mean square error values with better visual and human perception.

cs.CV↗

arXiv2018

Voice Conversion with Conditional SampleRNN

Here we present a novel approach to conditioning the SampleRNN generative model for voice conversion (VC). Conventional methods for VC modify the perceived speaker identity by converting between source and target acoustic features. Our approach focuses on preserving voice content and depends on the generative network to learn voice style. We first train a multi-speaker SampleRNN model conditioned on linguistic features, pitch contour, and speaker identity using a multi-speaker speech corpus. Voice-converted speech is generated using linguistic features and pitch contour extracted from the source speaker, and the target speaker identity. We demonstrate that our system is capable of many-to-many voice conversion without requiring parallel data, enabling broad applications. Subjective evaluation demonstrates that our approach outperforms conventional VC methods.

cs.SD↗

arXiv2017

Dynamic Load Balancing Strategies for Graph Applications on GPUs

Acceleration of graph applications on GPUs has found large interest due to the ubiquitous use of graph processing in various domains. The inherent \textit{irregularity} in graph applications leads to several challenges for parallelization. A key challenge, which we address in this paper, is that of load-imbalance. If the work-assignment to threads uses node-based graph partitioning, it can result in skewed task-distribution, leading to poor load-balance. In contrast, if the work-assignment uses edge-based graph partitioning, the load-balancing is better, but the memory requirement is relatively higher. This makes it unsuitable for large graphs. In this work, we propose three techniques for improved load-balancing of graph applications on GPUs. Each technique brings in unique advantages, and a user may have to employ a specific technique based on the requirement. Using Breadth First Search and Single Source Shortest Paths as our processing kernels, we illustrate the effectiveness of each of the proposed techniques in comparison to the existing node-based and edge-based mechanisms.

cs.DC↗

arXiv2017

Discovery of Magnetic Antiskyrmions Beyond Room Temperature in Tetragonal Heusler Materials

Skyrmions, topologically stable spin textures, are of great interest for new generations of spintronic devices. In general, the stabilization of skyrmions has been achieved in systems with broken inversion symmetry, where the asymmetric Dzyaloshinskii-Moriya interaction (DMI) modifies the uniform magnetic state to a swirling state. Depending on the crystal symmetries, two distinct types of skyrmions, Bloch and Néel types, have been observed experimentally. Here, we present, the experimental manifestation of a special type of spin-swirling, namely antiskyrmions, in a family of acentric tetragonal Heusler compounds with D2d crystal symmetry. A spiral magnetic ground-state, which propagates in the tetragonal basal plane, is transformed into a skyrmion lattice-state under magnetic fields applied along the tetragonal axis over a wide temperature interval. Direct imaging by Lorentz Transmission Electron Microscopy (LTEM) shows field stabilized antiskyrmion lattices and isolated antiskyrmions between 100 K and 400 K, and zero-field metastable antiskyrmions at low temperatures.

cond-mat.mtrl-sci↗

arXiv2016

Edge Detection Based Shape Identification

Image recognition is the need of the hour. In order to be able to recognize an image, it is of immense importance that the image should be distinguishable from the background. In the present work, an approach is presented for automatic detection and recognition of regular 2D shapes in low noise environments. The work has a large number of direct applications in the real world. The algorithm proposed is based on locating the edges and thus, in turn calculating the area of the object helps in identification of a specified shape. The results were simulated using MATLAB tool are encouraging and validate the proposed algorithm. Index Terms: Edge Detection, Area Calculation, Shape Detection, Object Recognition

cs.CV↗

arXiv2016

Lossy Data Compression Using Logarithm

Lossy compression algorithms take advantage of the inherent limitations of the human eye and discard information that cannot be seen. In the present paper, a technique termed as Lossy Data Compression using Logarithm (LDCL) is proposed to compress incoming binary data in the form of a resultant matrix containing the logarithmic values of different chosen numeric sets. The proposed method is able to achieve compression ratio up to 60 in many major cases. Keywords: LDCL, Lossy Data Compression, Binary Reduction, Logarithmic Approach

cs.IT↗

arXiv2016

Cryptompress: A Symmetric Cryptography algorithm to deny Bruteforce Attack

Cryptompress, a new 128-bit (initial) private-key cryptography algorithm is proposed. It uses a block size of at least 30 bits and increments prior key size to additional 32 bits on each unsuccessful attempt of any means, including bruteforcing, further changing a specific portion of the cyphertext using the reformed Feistel network. Encryption process results from a proposed compression sequence developed using lookup table and shift operations followed by key generation. Eventually, four matrixes named add-sub matrix, reduced matrix, sequence matrix and term matrix are obtained which ultimately forms a cyphertext.

cs.CR↗

arXiv2016

Role of Metal Nanoparticles on porosification of silicon by metal induced etching (MIE)

Porosification of silicon (Si) by metal induced etching (MIE) process have been studies here to understand the etching mechanism. The etching mechanism has been discussed on the basis of electron transfer from Si to metal ion (Ag$^+$) and metal to H$_2$O$_2$. Role of silver nanoparticles (AgNPs) in the etching process has been investigated by studying the effect of AgNPs coverage on surface porosity. A quantitative analysis of SEM images, done using Image J, shows a direct correlation between AgNPs coverage and surface porosity after the porosification. Density of Si nanowires (NWs) also varies as a function of AgNPs fractional coverage which reasserts the fact that AgNPs governs the porosification process during MIE.

cond-mat.mes-hall↗

arXiv2015

Interplay between Phonon Confinement and Fano Effect on Raman line shape for semiconductor nanostructures: Analytical study

Theoretical Raman line shape functions have been studied to take care of quantum confinement effect and Fano effect individually and jointly. The characteristics of various Raman line shapes have been studied in terms of the broadening and asymmetry of Raman line shapes. It is shown that the asymmetry in the Raman line-shape function caused by these two effects individually does not add linearly to give asymmetry of line-shape generated by considering the combined effect. This indicates existence of interplay between the two effects. The origin of interplay lies in the fact that Fano effect itself depends on quantum confinement effect and in turn provides an asymmetry. This can not be explained by considering the two effects contribution independent of each other.

cond-mat.mes-hall↗

arXiv2014

Micro-Raman and field emission studies of silicon nanowires prepared by metal assisted chemical etching

Micro-Raman scattering and electron field emission characteristics of silicon nanowires (SiNWs) synthesized by metal assisted chemical etching (MACE) are investigated. Scanning electron microscopy images reveal the growth of well aligned vertical SiNWs. Raman shift and size relation from bond-polarizability model has been used to calculate exact confinement sizes in SiNWs. The Si optical phonon peak for SiNWs showed a downshift and an asymmetric broadening with decreasing diameter of the SiNWs due to quantum confinement of optical phonons. The field emission characteristics of these SiNWs are studied based by carrying out current-voltage measurements followed by a theoretical analysis using Fowler-Nordheim equation. The electron field emission increased with decreasing diameter of SiNWs. Field emission from these SiNWs exhibits significant enhancement in turn-on field and total emission current with decreasing nanowire size. The reported results in the current study indicate that MACE is a simple technique to prepare well-aligned SiNWs with potentials for applications in field emission devices.

cond-mat.mes-hall↗

arXiv2014

Comparison of porous silicon prepared using metal-induced etching (MIE) and laser-induced etching (LIE)

Porous silicon (p-Si), prepared by two routes (metal induced etching (MIE) and laser induced etching (LIE)) have been studied by comparing the observed surface morphologies using SEM. A uniformly distributed smaller (submicron sized) pores are formed when MIE technique is used because the pore formation is driven by uniformly distributed metal (silver in present case) nanoparticles, deposited prior to the porosification step. Whereas in p-Si, prepared by LIE technique, wider pores with some variation in pore size as compared to MIE technique is observed because a laser having gaussian profile of intensity is used for porosification. Uniformly distribute well-aligned Si nanowires are observed in samples prepared by MIE method as seen using cross-sectional SEM imaging. A single photoluminescence (PL) peak at 1.96 eV corresponding to red emission at room temperature is observed which reveals that the Si nanowires, present in p-Si prepared by MIE, show quantum confinement effect. The single PL peak confirms the presence of uniform sized nanowires in MIE samples. These vertically aligned Si nanowires can be used for field emission application.

cond-mat.mes-hall↗

arXiv2010

Adapting MAC 802.11 Adapting MAC 802.11 for Performance Optimization of MANET using Cross Layer Interaction

In this research, we study the optimization challenges of MANET and cross-layer technique to improve its performance. We propose an adaptive retransmission limits algorithm for IEEE 802.11 MAC to reduce the false link failures and predict the node mobility. We implemented cross layer interaction between physical and MAC layers. The MAC layer utilizes the physical layer information for differentiating false link failure from true link failure. The MAC layer adaptively selects a retransmission limit (short and long) based on the neighbour signal strength and sender node speed information from the physical layer. The proposed approach tracks the signal strength of each node in network and, while transmitting to a neighbour node, if it's received signal strength is high and is received recently then Adaptive MAC persists in its retransmission attempts. As there is high probability that neighbour node is still in transmission range and may be not responding due to some problems other then mobility. In this paper, we evaluate the performance of MANET and show that how our Adaptive MAC greatly improves it. The simulation is done using Network Simulator NS-2.

cs.NI↗

arXiv2009

Defect free visible photoluminescence from laser-generated germanium nanoparticles

Origin of room temperature visible photoluminescence (PL) from defect free germanium (Ge) nanoparticles have been discussed here. The Ge nanoparticles produced by laser-induced etching technique show broad visible PL around 2.0 - 2.2 eV at room temperature. Size dependent PL peak shift in Ge nanoparticles has been explained in terms of quantum confinement. Theoretical calculations of radiative lifetime using oscillator strength, which is closely related to the size of the nanostructures, suggests that the PL is originating from a radiative recombination process in quantum confined Ge nanostructures.

cond-mat.mes-hall↗