Browse Items (11807 total)
Sort by:
-
A space for the space theorist remembering henri lefebvre
Despite being somewhat ignored in Indian academia, Henri Lefebvre comes to our rescue every time, helping us understand and respond to spacetime challenges. 2020 Economic and Political Weekly. All rights reserved. -
A Space Vector Modulated Direct Torque Control of Induction Motor with Improved Transient Performance and Reduced Parameters Dependency
Direct torque control (DTC) of induction motors is hampered by high torque and current ripple. Integrating DTC with space vector pulse width modulation (DTC-SVPWM) is one of the frequently used approaches to solve this problem. However, it adds to the computational complexity, increases the number of necessary motor parameters needed for control scheme implementation, and also affects the transient performance of the induction motor; this approach compromises the robustness and simplicity of DTC scheme. To get around these restrictions, a novel control strategy is put forth in this paper. The suggested scheme enhances the steady-state performance and transient response of the motor while preserving the simplicity and robustness of the DTC scheme. To accomplish this, the proposed control scheme operates at varying switching frequencies during transient conditions and constant switching frequencies during steady-state. The suggested speed control method does not employ any rotating reference frame transformations or usage of many rotor parameters for computation, nor does it call for sector identification and operates with a single PI controller. The suggested topology also uses a bus-clamped PWM modulation technique, which lowers the average switching frequency to 2/3 times the actual switching frequency. Thus, switching losses are also decreased. Simulation results show the effectiveness of the proposed topology in enhancing the transient and steady-state performance of the induction motor. The results are compared with the traditional DTC and DTC-SVPWM scheme. 2023 IEEE. -
A Spatio-temporal Model for the Analysis and Classification of Soil Using the IoT
The Internet of Things (IoT) is an evolving trend in the field of computer applications where various hardware and software are connected together to address a specific problem. With the help of the IoT, the world has become smart and enabled itself to connect various objects (e.g., cars, computers, mobile phones, and smart appliances) with distinctive Internet protocol addresses, which allows them to interact with one another, thus accomplishing various procedures. Applications of the IoT include but are not restricted to smart cities, healthcare, industry, and robotics. Amongst a huge list of applications furnished by the IoT, agricultural IoT is the theme of this chapter. The IoT in agriculture transforms entities such as crops, soils, and livestock in a smart way by utilizing underlying technologies such as embedded systems, pervasive computing, sensor networks, ubiquitous computing, ad hoc networks, various wireless communication technologies, Internet protocols and other advanced technologies. The research here focuses on the most important agriculture entity soil. It is the soil that determines the yield of a crop. The more fertile the soil, more qualitative is the yield. The main idea behind the research is to identify the soil most suitable for agriculture. Using a spatio-temporal model, the soil samples collected from various parts of the country are classified into agricultural soil and non-agricultural soil. This classification is done by the aid of features such as the pH of the soil, and its humidity, moisture, and temperature collected from IoT sensors. The chapter begins with an introduction to the usage of IoT technology in different areas of agriculture followed by an account of the proposed state-of-the-art model, and its results, analysis, and a conclusion. 2022 selection and editorial matter, Vikram Bali, Vishal Bhatnagar, Deepti Aggarwal, Shivani Bali, and Mario JosDiv; individual chapters, the contributors. -
A Specular Reflection Removal Technique in Cervigrams
Cancer detection through medical image segmentation and classification is possible owing to the advancement in image processing techniques. Segmentation and classification tasks carried out to predict and classify diseases need to be dependable and precise. Specular reflections are the high-intensity and low-saturation areas that reflect the light from the probing devices that capture the picture of the organ surface. These areas sometimes mimic the features that are key identifying factors for cancers like acetowhite lesions. This review article examines the various methods proposed for removing specular reflections from medical images, especially those captured by colposcopes. The fundamentals of specular reflection removal and its associated challenges are discussed. The paper reviews several prominent approaches for removal of specular reflections proposes a novel method to remove the specular reflections. The comprehensive review can be a strong foundation for researchers looking to decide on appropriate techniques to employ in their respective research approaches. 2023 IEEE. -
A Stacked BiLSTM based Approach for Bus Passenger Demand Forecasting using Smart Card Data
Demand forecasting is crucial in the business sector. Despite the inherent uncertainty of the future, it is essential for any firm to be able to accurately predict the market for both short- and long-term planning in order to place itself in a profitable position. The proposed approach focus on the passenger transport sector because it is particularly vulnerable to fluctuations in consumer demand for perishable commodities. At every stage of the planning process from initial network designs to final pricing of inventory for each vehicle in a route-an accurate prediction of demand is essential. Forecasting passenger demand is crucial since passenger transportation is responsible for a substantial chunk of global commerce. The suggested method relies on three distinct techniques: data preparation, feature selection, and model training. Data modification, cleansing, and reduction are the three sub-processes that make up preprocessing. When it comes to feature selection, partition-based clustering algorithms like k-means are the norm. Let's go on to training the models with stacked BiLSTM. The proposed method is demonstrably superior to both LSTM and BiLSTM, the two most common competing approaches. The proposed method had a success rate of 98.45 percent. 2023 IEEE. -
A stakeholder theory approach to analysing strategies for improving pandemic vaccine supply chain performance
This study aims to formulate strategies that impact the vaccine supply chain (VSC). This study measures the VSC performance using the proposed strategy concerning stakeholders theory. From the literature review and experts consent, the strategies are classified into six broad strategies as-VSC traceability, VSC visibility, VSC velocity, digitalising VSC, localising VSC, and vaccine inventory. A questionnaire is developed for surveying healthcare organisations and hospitals. All six proposed hypotheses got accepted. The developed model satisfies all the model fit parameters. Strategies like VSC traceability, VSC visibility, VSC velocity, digitalising VSC, localising VSC, and vaccine inventory have positively impacted vaccine supply chain performance. This research will be helpful for healthcare professionals and organisations for the faster delivery of the vaccine. This research will also help policymakers in improving the performance of VSC. This study is also the first to use the stakeholder theory approach for measuring VSC performance. Copyright 2024 Inderscience Enterprises Ltd. -
A Statistical Analysis and Comparison of the spread of Swine Flu and COVID-19 in India
Introduction: The world is currently experiencing the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [COVID-19], however, this is not a new phenomenon; it occurred in 2009-2010 in the form of novel influenza A. (H1N1). The H1N1 virus primarily afflicted people between the ages of 26 and 50, but SARS-CoV-2 primarily afflicted those over the age of 60, increasing the number of deaths owing to their weakened immunity. The report provides a case study of the impact of H1N1 and SARS-CoV-2 in India. Methods: Data is obtained from The Hindustan Times newspaper, GoI press releases and World Health Organization (WHO) reports. Results: The incidence rate was initially low and it was only by the 10-15th week that it started increasing. There is an initial upward trend before levelling out followed by a second wave and third wave. COVID-19 exhibited a steeper growth, where the steps taken by the Government were ineffective leading to higher death cases. Kerala was affected due to the travellers returning from the Middle East, while Maharashtra and Delhi saw large incidence rates due to the migrant influx and communal gathering. Conclusion: The most effective and practical approach is to test the symptomatic patients and aggressive testing to contain the transmission. Awareness campaigns to educate the public about social distancing and personal hygiene is more practical. There is still scope of improvement with regards to the public health care support, preparedness and response. Lockdown measures could have been avoided if the initial screening was conducted properly. 2022 UPM Press. All rights reserved. -
A statistical analysis of the stochastic drift between sensex & nifty - An in-depth study /
International Journal Of Innovative Research & Development, Vol.4, Issue 5, pp.208-212, ISSN No: 2278-0211 (Online) -
A statistical approach to study anatomical changes of pink guava cultivar (Psidium guajava L. cv Arka Kiran) during its ripening at the room temperature storage
The ripening of climacteric fruit like guava is a complex process that is highly coordinated with its cellular backbone. In the present study, we combined microscopy, spectrophotometry, and statistical analysis to evaluate the anatomical changes in the pink variety of guava during five ripening stages (pre-ripe, ripe, color-turn, half over-ripe, and over-ripe) during its storage at room temperature (282 C). The cholorophyll content of the peel, as determined by the measurement of chlorophyll a, b, and total chlorophyll, showed a significant decrease during the maturation process (4.05, 4.53, and 8.62 ?g/cm2, respectively, in the pre-ripe stage to not detectable in the over-ripe stage). Gradual loss of integrity of the fruit pulp (pericarp) from the preserved bee-hive structure to cell mass was also monitored by studying the cellular anatomy with brightfield and scanning electron microscopy. The epidermal thickness and width of the cortical parenchyma cells revealed statistical differences from the initial pre-ripe stage to the final full-ripe stage. Finally, based on the cellular dimensions, multivariate analysis using PCA (Principal Component Analysis) tool grouped the stages into three clusters, namely, pre-ripe: ripe, color-turn: half-over ripe, and over-ripe stages. In conclusion, this study provided significant insights into cultivar-specific anatomical changes in guava fruit, with potential for future research to develop variants with longer post-harvest storage life. 2024 The Author(s) -
A Statistical Search for Star-Planet Interaction in the Ultraviolet Using GALEX
Most (?82%) of the over 4000 confirmed exoplanets known today orbit very close to their host stars, within 0.5 au. Planets at such small orbital distances can result in significant interactions with their host stars, which can induce increased activity levels in them. In this work, we have searched for statistical evidence for star-planet interactions in the ultraviolet (UV) using the largest sample of 1355 Galaxy Evolution Explorer (GALEX) detected host stars with confirmed exoplanets and making use of the improved host-star parameters from Gaia DR2. From our analysis, we do not find any significant correlation between the UV activity of the host stars and their planetary properties. We further compared the UV properties of planet host stars to that of chromospherically active stars from the RAdial Velocity Experiment (RAVE) survey. Our results indicate that the enhancement in chromospheric activity of host stars due to star-planet interactions may not be significant enough to reflect in their near- and far-UV broadband flux. 2020. The American Astronomical Society. All rights reserved.. -
A Stochastic Method for Optimizing Portfolios Using a Combined Monte Carlo and Markowitz Model: Approach on Python
The main of the study is to comprehend how the mean variance efficient frontier method may be used in conjunction with Markowitz portfolio theory to produce an optimal portfolio. The study uses daily observations 8 pharma companies closing price namely Auropharma, Granules, Glaxo, Lauruslabs, Pfizer, Sanofi and Torntpharma. Further, Nifty pharma index is considered as benchmark index to check the performance of the chosen companies. The study chosen the reference period from 2020 to 2023 and required data has been extracted from the National Stock Exchange (NSE). This research is based on implementing a stochastic method for efficient portfolio optimisation employing a blended Monte Carlo and Markowitz model. In order to forecast the price of these indices in the future and to determine the likelihood of profit or loss while investing in a portfolio of stocks representing the aforementioned indices, the study also uses Monte Carlo simulation. The study involves two algorithms, namely the deterministic optimisation algorithm, which uses Markowitz Portfolio Theory, and the probabilistic optimisation algorithm, which uses Monte Carlo simulation. The study employed correlation matrix to find the exist relationship between the chosen companies and benchmark index. Also, expected return and volatility has been identified with the help of standard deviation using Python. The study found that the NIFTY Pharma index offers a higher return of 14.35. In addition to this, NIFTY Pharma portfolio's volatility is considerably higher. The study concludes that the NIFTY pharma portfolio is more suitable for those investors who have an appetite for risk. 2024 R. Mallieswari et al., published by Sciendo. -
A Stochastic Method for Optimizing Portfolios Using a Combined Monte Carlo and Markowitz Model: Approach on Python
The main of the study is to comprehend how the mean variance efficient frontier method may be used in conjunction with Markowitz portfolio theory to produce an optimal portfolio. The study uses daily observations 8 pharma companies closing price namely Auropharma, Granules, Glaxo, Lauruslabs, Pfizer, Sanofi and Torntpharma. Further, Nifty pharma index is considered as benchmark index to check the performance of the chosen companies. The study chosen the reference period from 2020 to 2023 and required data has been extracted from the National Stock Exchange (NSE). This research is based on implementing a stochastic method for efficient portfolio optimisation employing a blended Monte Carlo and Markowitz model. In order to forecast the price of these indices in the future and to determine the likelihood of profit or loss while investing in a portfolio of stocks representing the aforementioned indices, the study also uses Monte Carlo simulation. The study involves two algorithms, namely the deterministic optimisation algorithm, which uses Markowitz Portfolio Theory, and the probabilistic optimisation algorithm, which uses Monte Carlo simulation. The study employed correlation matrix to find the exist relationship between the chosen companies and benchmark index. Also, expected return and volatility has been identified with the help of standard deviation using Python. The study found that the NIFTY Pharma index offers a higher return of 14.35. In addition to this, NIFTY Pharma portfolio's volatility is considerably higher. The study concludes that the NIFTY pharma portfolio is more suitable for those investors who have an appetite for risk. 2024 R. Mallieswari et al., published by Sciendo 2024. -
A stochastic propagation model to the energy dependent rapid temporal behaviour of Cygnus X-1 as observed by AstroSat in the hard state
We report the results from analysis of six observations of Cygnus X-1 by Large Area X-ray Proportional Counter (LAXPC) and Soft X-ray Telescope (SXT) onboard AstroSat, when the source was in the hard spectral state as revealed by the broad-band spectra. The spectra obtained from all the observations can be described by a single-temperature Comptonizing region with disc and reflection components. The event mode data from LAXPC provides unprecedented energy dependent fractional root mean square (rms) and time-lag at different frequencies which we fit with empirical functions.We invoke a fluctuation propagation model for a simple geometry of a truncated disc with a hot inner region. Unlike other propagation models, the hard X-ray emission (>4 keV) is assumed to be from the hot inner disc by a single-temperature thermal Comptonization process. The fluctuations first cause a variation in the temperature of the truncated disc and then the temperature of the inner disc after a frequency dependent time delay.We find that the model can explain the energy dependent rms and time-lag at different frequencies. 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. -
A storage system for data encryption and decryption using line and method thereof /
Patent Number: 202141013775, Applicant: Sanjana Theresa.
The present invention discloses a storage system in a computer network for data encryption and decryption using line graphs and method thereof. The system includes, but not limited to, a processing unit in a computer network that includes at least one hardware processor, the processing system configured to perform: to represent data as vertices in a graph; wherein each character is correspond to a vertex while all adjacent characters in the plaintext will be represented as adjacent vertices in the graph. -
A storage system for data encryption and decryption using line and method thereof /
Patent Number: 202141013775, Applicant: Sanjana Theresa.
The present invention discloses a storage system in a computer network for data encryption and decryption using line graphs and method thereof. The system includes, but not limited to, a processing unit in a computer network that includes at least one hardware processor, the processing system configured to perform: to represent data as vertices in a graph; wherein each character is correspond to a vertex while all adjacent characters in the plaintext will be represented as adjacent vertices in the graph. -
A storage system for data encryption and decryption using line and method thereof /
Patent Number: 202141013775, Applicant: Sanjana Theresa.
The present invention discloses a storage system in a computer network for data encryption and decryption using line graphs and method thereof. The system includes, but not limited to, a processing unit in a computer network that includes at least one hardware processor, the processing system configured to perform: to represent data as vertices in a graph; wherein each character is correspond to a vertex while all adjacent characters in the plaintext will be represented as adjacent vertices in the graph. -
A storage system for data encryption and decryption using line graphs and method thereof /
Patent Number: 202141013775, Applicant: Sanjana Theresa.
The present invention discloses a storage system in a computer network for data encryption and decryption using line graphs and method thereof. The system includes, but not limited to, a processing unit in a computer network that includes at least one hardware processor, the processing system configured to perform. -
A storage system for data encryption and decryption using line graphs and method thereof /
Patent Number: 202141013775, Applicant: Sanjana Theresa.
The present invention discloses a storage system in a computer network for data encryption and decryption using line graphs and method thereof. The system includes, but not limited to, a processing unit in a computer network that includes at least one hardware processor, the processing system configured to perform. -
A storage system for data encryption and decryption using line graphs and method thereof /
Patent Number: 202141013775, Applicant: Sanjana Theresa.
The present invention discloses a storage system in a computer network for data encryption and decryption using line graphs and method thereof. The system includes, but not limited to, a processing unit in a computer network that includes at least one hardware processor, the processing system configured to perform. -
A strategic evaluation on competency of Karanataka destinations through destination management organizations /
American Journal Of Industrial and Business Management, Vol.6, pp.102-108, ISSN: 2164-5175.