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Shikha Gupta

Bio: Shikha Gupta is an academic researcher from Indian Institute of Technology Mandi. The author has contributed to research in topics: Support vector machine & Kernel (image processing). The author has an hindex of 5, co-authored 33 publications receiving 83 citations. Previous affiliations of Shikha Gupta include Delhi Technological University & Lokmanya Tilak College of Engineering.

Papers
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Proceedings ArticleDOI
01 Jan 2019
TL;DR: The introduction of Electronic Stability Control and other features have made cars much ahead and safer than before, the concept of Smart Helmet aims to provide the same for Bikes with features like built-in Black Box, GPS logging, collision sensing and sending emergency SMS.
Abstract: The introduction of Electronic Stability Control and other features have made cars much ahead and safer than before. The concept of Smart Helmet aims to provide the same for Bikes. With features like built-in Black Box, GPS logging which will keep track of the rider's location and can be accessed in case of emergency. A collision sensor will alert in case the rider meets with an accident and or is drunken driving. The helmet makes use of ATMega32u4 with AI Thinker's A7 GSM-GPS module for GPS logging, collision sensing and sending emergency SMS. The helmet also features an Alcohol sensor which will act as a breath-analyser and send a help messages to the registered phone numbers along with the rider's location. The Black-Box built on Raspberry Pi will help in analysing the cause of accident. The footage of the accident will be recorded automatically in case the rider meets with an accident. It will provide a safer travel for bikers and help them in case of an emergency.

12 citations

Proceedings ArticleDOI
01 Jul 2016
TL;DR: In this paper, an optimal power evacuation and reactive power compensation solution has been proposed to address the subject concerns of grid connected WES with source side control and grid side converter control.
Abstract: Solar, Wind, PV, MT are commercially available Distributed generation system for long time but suffers from grid integration issues. In case of Wind Energy System (WES), power quality is challenging issue for grid connected system. Further there are challenges associated with extract of maximum power and reliability of supply. To address the subject concerns, optimum power evacuation and reactive power compensation solution has been proposed in the paper. This paper presents grid connected WES with source side control and grid side converter control. It further contains comparison between grid side conventional controller and TS fuzzy controller along with design of LCL filter. Control of the inverter has been done by Synchronous reference frame (SRF) scheme. The objective behind the grid side converter control is to evacuate the active power and reactive power from WSES. In case load requirement exceeds wind energy generation, the control architecture will ensure that remaining demand will meet through grid supply. Reactive power compensation of the load is done through the control algorithm. Working of proposed system is investigated under nonlinear, unbalance, varying load and with change in wind speed. Grid code compliances were considered to verify the effectiveness of proposed system. Simulation is performed using MATLAB/Simulink platform.

11 citations

Journal ArticleDOI
TL;DR: A multi-objective inverter based on hybrid intelligent controller, adaptive neuro-fuzzy inference system, and overall power management strategy has been designed to manage power flows among the RES, load and grid.
Abstract: As a consequence of fast socio-economic progress, the requirement of auxiliary energy sources is creating new opportunities in the field of renewable energy sources (RES). This paper presents a hybrid photovoltaic (PV)–fuel cell (FC) energy structure for grid-connected applications. The key challenges associated with the integration of RES are managing harmonic distortions, voltage fluctuations and power sharing. To mitigate these problems and to enhance the overall performance of the system, multi-objective inverter based on hybrid intelligent controller, adaptive neuro-fuzzy inference system has been designed. In the proposed system, PV acts as a primary energy source, while FC serves as a secondary energy source. An overall power management strategy has been designed to manage power flows among the RES, load and grid. The effectiveness of the proposed multi-objective inverter control and energy management of the system is validated under MATLAB/Simulink platform.

11 citations

Proceedings ArticleDOI
01 Aug 2016
TL;DR: A novel segment-level pyramid match kernel (SLPMK) is proposed for the classification of varying length patterns of long duration speech represented as sets of feature vectors, designed by partitioning the speech signal into increasingly finer segments and matching the corresponding segments.
Abstract: Classification of long duration speech, represented as varying length sets of feature vectors using support vector machine (SVM) requires a suitable kernel. In this paper we propose a novel segment-level pyramid match kernel (SLPMK) for the classification of varying length patterns of long duration speech represented as sets of feature vectors. This kernel is designed by partitioning the speech signal into increasingly finer segments and matching the corresponding segments. We study the performance of the SVM-based classifiers using the proposed SLPMKs for speech emotion recognition and speaker identification and compare with that of the SVM-based classifiers using other dynamic kernels.

10 citations

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a filter-specific threshold-based approach that leads to the removal of non-prominent concepts from data and then group the same pseudo-concepts using subspace modeling of filter responses to achieve a non-redundant representation.
Abstract: In this work, we address the task of scene recognition from image data. A scene is a spatially correlated arrangement of various visual semantic contents also known as concepts, e.g., “chair,” “car,” “sky,” etc. Representation learning using visual semantic content can be regarded as one of the most trivial ideas as it mimics the human behavior of perceiving visual information. Semantic multinomial (SMN) representation is one such representation that captures semantic information using posterior probabilities of concepts. The core part of obtaining SMN representation is the building of concept models. Therefore, it is necessary to have ground-truth (true) concept labels for every concept present in an image. Moreover, manual labeling of concepts is practically not feasible due to the large number of images in the dataset. To address this issue, we propose an approach for generating pseudo-concepts in the absence of true concept labels. We utilize the pre-trained deep CNN-based architectures where activation maps (filter responses) from convolutional layers are considered as initial cues to the pseudo-concepts. The non-significant activation maps are removed using the proposed filter-specific threshold-based approach that leads to the removal of non-prominent concepts from data. Further, we propose a grouping mechanism to group the same pseudo-concepts using subspace modeling of filter responses to achieve a non-redundant representation. Experimental studies show that generated SMN representation using pseudo-concepts achieves comparable results for scene recognition tasks on standard datasets like MIT-67 and SUN-397 even in the absence of true concept labels.

10 citations


Cited by
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01 Jan 2016
TL;DR: This power electronics converters applications and design helps people to enjoy a good book with a cup of tea in the afternoon, instead they cope with some malicious virus inside their desktop computer.
Abstract: Thank you for downloading power electronics converters applications and design. Maybe you have knowledge that, people have look numerous times for their favorite readings like this power electronics converters applications and design, but end up in harmful downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they cope with some malicious virus inside their desktop computer.

754 citations

Journal ArticleDOI
TL;DR: A comprehensive study of power quality in power systems, including the systems with dc and renewable sources is done, and power quality monitoring techniques and possible solutions of the power quality issues for the power systems are elaborately studied.
Abstract: This paper discusses the power quality issues for distributed generation systems based on renewable energy sources, such as solar and wind energy. A thorough discussion about the power quality issues is conducted here. This paper starts with the power quality issues, followed by discussions of basic standards. A comprehensive study of power quality in power systems, including the systems with dc and renewable sources is done in this paper. Power quality monitoring techniques and possible solutions of the power quality issues for the power systems are elaborately studied. Then, we analyze the methods of mitigation of these problems using custom power devices, such as D-STATCOM, UPQC, UPS, TVSS, DVR, etc., for micro grid systems. For renewable energy systems, STATCOM can be a potential choice due to its several advantages, whereas spinning reserve can enhance the power quality in traditional systems. At Last, we study the power quality in dc systems. Simpler arrangement and higher reliability are two main advantages of the dc systems though it faces other power quality issues, such as instability and poor detection of faults.

223 citations

Posted Content
TL;DR: In this article, the authors explored the relationship between globalization and CO2 emissions by incorporating energy consumption, financial development and economic growth in CO2 emission function for India using annual data for the period 1970-2012.
Abstract: Using annual data for the period 1970-2012, the study explores the relationship between globalization and CO2 emissions by incorporating energy consumption, financial development and economic growth in CO2 emission function for India. It applies Lee and Strazicich (2013) unit root test for examining the stationary properties of variables in presence of structural breaks and employs the cointegration method proposed by Bayer-Hanck (2013) to test the long-run relationships in the model. The robustness s of cointegration result from the latter model was further verified with the application of the ARDL bounds testing approach to cointegration proposed by Pesaran, Shin and Smith (2001). After confirming the existence of cointegration, the overall long run estimates of the estimation of carbon emission model points out that acceleration in the process of globalization (measured in its three dimensions - economic, social and political globalizations) and energy consumption result in increasing CO2 emissions, along with the contribution of economic development and financial development towards the deterioration of the environmental quality by raising CO2 emissions over the long-run. This finding validates holding of environmental Kuznets Curve (EKC) hypothesis for the Indian context.

144 citations

Posted Content
TL;DR: For small open economies, increases in real output and international reserves, as well as declines in tariff rates are associated with growth in the trade/income ratio as mentioned in this paper, and there are important differences in the behavior of the trade ratio across time and country size.
Abstract: Trade of the OECD countries has grown faster than income during the postwar period. This paper tests a number of different hypotheses for the observed growth in the trade/income ratio. For small open economies, increases in real output and international reserves, as well as declines in tariff rates are associated with growth in the ratio. There are important differences in the behavior of the trade ratio across time and country size.

62 citations

Journal ArticleDOI
TL;DR: The present study demonstrated a high prevalence of drug resistance amongst pulmonary TB isolates of M. tuberculosis from north India as compared to the WHO estimates for India in 2010, though this could possibly be attributed to the clustering of more serious or referred cases at the tertiary care centre.
Abstract: Multidrug resistant (MDR) and extensively-drug resistant (XDR) tuberculosis (TB) are a serious threat to the national TB control programs of developing countries, and the situation is further worsened by the human immunodeficiency virus (HIV) pandemic. The literature regarding MDR/XDR-TB is, however, scanty from most parts of India. We carried out this study to assess the prevalence of MDR/XDR-TB in new and previously treated cases of pulmonary TB and in HIV seropositive and seronegative patients. Sputum and blood specimens were obtained from 2100 patients suspected of pulmonary tuberculosis and subjected to sputum microscopy and culture for TB, and HIV serology at our tertiary care centre in north India. The culture positive Mycobacterium tuberculosis isolates were subjected to drug susceptibility testing (DST) for first line anti-tuberculosis drugs, and the MDR isolates were further subjected to second line DST. Various parameters of the patients’ were analyzed viz. clinical presentation, radiology, previous treatment history, demographic and socioeconomic data and microbiology results. Of the 2100 patients, sputum specimens of 256 were smear positive for acid-fast bacilli (AFB), 271 (12.9%) grew Mycobacterium spp., and M. tuberculosis was isolated in 219 (10.42%). Of the 219 patients infected with M. tuberculosis, 20.1% (44/219) were found to be seropositive for HIV. Overall, MDR-TB was observed in 17.4% (39/219) isolates. There were 121 newly diagnosed and 98 previously treated patients, of which MDR-TB was found to be associated with 9.9% (12/121) and 27.6% (27/98) cases respectively. There was significantly higher association of MDR-TB (12/44, 27.3%) with HIV seropositive patients as compared to HIV seronegative patients (27/175, 15.4%) after controlling previous treatment status, age, and sex (odd’s ratio, 2.3 [95% CI, 1.000-5.350]; p-value, 0.05). No XDR-TB was found among the MDR-TB isolates. The present study demonstrated a high prevalence of drug resistance amongst pulmonary TB isolates of M. tuberculosis from north India as compared to the WHO estimates for India in 2010, though this could possibly be attributed to the clustering of more serious or referred cases at our tertiary care centre. The prevalence of MDR-TB in HIV seropositive patients was significantly higher than seronegative individuals. The study emphasizes the need to monitor the trends of drug resistance in TB in various populations in order to timely implement appropriate interventions to curb the menace of MDR-TB.

62 citations