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Spectral quasi-linearization and irreversibility analysis of magnetized cross fluid flow through a microchannel with two different heat sources and Newton boundary conditions
Fluid flow in a microchannel with heat transport effects can be seen in various applications such as micro heat collectors, mechanicalelectromechanical systems, electronic device cooling, micro-air vehicles, and micro-heat exchanger systems. However, little is known about the consequence of internal heat source modulations on the flow of fluids in a microchannel. Therefore, in this work, the heat transfer of a magnetized cross fluid is carried out in a micro-channel subjected to two different heat source modulations. Entropy production analysis is also performed. The mathematical model consists of a cross fluid model. In addition, the effects of Joule heating, external magnetism, and the boundary conditions of Newton's heating are also examined. Determinant equations are constructed under steady-state conditions and parameterized using dimensionless variables. The numerical spectral quasi-linearization (SQLM) method was developed to interpret the Bejan number, entropy production, temperature, and velocity profiles. It is established that the power-law index of the cross fluid reduces the magnitude of the entropy production, velocity, and thermal field in the entire microchannel region. Furthermore, a larger Weissenberg number is capable of producing greater entropy, velocity, and thermal fields throughout the microchannel region. The variation in temperature distribution is more noticeable for the ESHS aspect than the THS aspect. The values of the pressure gradient parameter and the Eckert number must be kept high for maximum heat transport of the cross fluid. The entropy production of the cross fluid increases significantly with the physical aspects of Joule heating and convection heating in the system. 2021, The Author(s), under exclusive licence to SocietItaliana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature. -
Spectral Properties of the Soft X-Ray Transient MAXI J0637-430 Using AstroSat
Soft X-ray transients are systems that are detected when they go into an outburst, wherein their X-ray luminosity increases by several orders of magnitude. These outbursts are markers of the poorly understood change in the spectral state of these systems from the low/hard state to the high/soft state. We report the spectral properties of one such soft X-ray transient: MAXI J0637-430, with data from the SXT and LAXPC instruments on board the AstroSat mission. The source was observed for a total of ?60 ks in two observations on 2019 November 8 and 21 soon after its discovery. Flux-resolved spectral analysis of the source indicates the presence of a multicolor blackbody component arising from the accretion disk and a thermal Comptonization component. The stable low temperature (?0.55 keV) of the blackbody component points to a cool accretion disk with an inner disk radius of the order of a few hundred kilometers. In addition, we report the presence of a relativistically broadened Gaussian line at 6.4 keV. The disk-dominated flux and photon power-law index of ?2 and a constant inner disk radius indicate the source to be in the soft state. From the study we conclude that MAXI J0637-430 is a strong candidate for a black hole X-ray binary. 2022. The Author(s). Published by the American Astronomical Society. -
Spectral characteristics of the black hole binary 4U 1957+115: a multi mission perspective
We report spectral analysis of the persistent black hole X-ray binary, 4U 1957+115, using AstroSat, Swift, and NuSTAR observations carried out between 2016 and 2019. Modelling with a disc emission, thermal Comptonization, and blurred reflection components revealed that the source was in the high-soft state with the disc flux ?87 per cent of the total and high-energy photon index ?2.6. There is an evidence that either the inner disc radius varied by ?25 per cent or the colour hardening factor changed by ?12 per cent. The values of the inner disc radius imply that for a non-spinning black hole, the black hole mass is < 7 M ? and the source is located > 30 kpc away. On the other hand, a rapidly spinning black hole would be consistent with the more plausible black hole mass of < 10 M ? and a source distance of ?10 kpc. Fixing the distance to 10 kpc and using a relativistic accretion disc model, constrained the black hole mass to 6 M? and inclination angle to 72. A positive correlation is detected between the accretion rate and inner radii or equivalently between the accretion rate and colour factor. 2022 The Author(s). -
Spectral and type I X-ray burst studies of 4U 1702?429 using AstroSat observations
4U 1702?429, an atoll-type neutron star low-mass X-ray binary, was observed twice by the AstroSat/Soft X-ray Telescope (SXT) and Large Area X-ray Proportional Counters (LAXPC-20) on 2018 April 27 and 2019 August 8. Persistent emission spectra of the source were well fitted with the model combination - constant tbabs (thcomp diskbb+powerlaw). The parameters obtained from the spectral analysis revealed the source to be in a hard spectral state during the observations. Time-resolved spectral analyses were performed on the three type I X-ray bursts detected from the source. Burst analysis showed that the source underwent a photospheric radius expansion. Consequently, the radius of the neutron star and distance to the source (with isotropic and anisotropic burst emission) were obtained as 12.65+?008690 km and 6.92+?000916 and 8.43+?001020 kpc, respectively. 2024 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. -
Spectral and Timing Properties of Selected Black Hole Binaries
X-ray binaries hosting a black hole (accretor) and a main sequence or a post-main sequence star (companion star) are called black hole X-ray binaries (BHXBs). BHXBs are gravitationally bound systems where the matter from the companion star is accreted onto the accretor either via a Roche lobe overand#64258;ow (low-mass companion star) or stellar wind (high-mass companion star). The accreted matter spirals towards the accretor, losing its angular momentum in the process. The gravitational potential energy of the in-falling matter is converted to kinetic energy which is eventually released as X-rays. X-ray spectrum of BHXB is quite complex by nature, which is contributed by various X-ray production processes. Systematic and comprehensive investigations of the X-ray production mechanisms are essential for understanding the fundamentals of accretion physics and exploring the general relativistic effects in extreme gravity environments. Launch of several dedicated X-ray missions like Uhuru, Ginga, RXTE, Chandra, XMM-Newton, NuSTAR, Swift, etc. for over half a century have led to the discovery, classifcation and fair understanding of spectro-temporal properties of BHXBs. Despite the continuous and ongoing newlineefforts, the physics of the accretion mechanism in BHXBs, accretion disk geometry, the origin of quasi periodic oscillations (QPOs), energy-dependent time lags and coherence of X-ray photons in different energies, etc., are yet to be completely understood. Hence, there is a need for newlinerevisiting these problems using the data from more sensitive instruments, that have broadband energy coverage and have better spectral and timing resolutions than RXTE. Thus, data from the latest missions like AstroSat, Swift, NuSTAR with their broadband energy coverage, especially in the lower energy regime (and#8804; 3.0 keV), and larger effective area can help fll in the gap in the newlineexisting body of knowledge and provide a holistic understanding of these sources. -
Spectral and temporal studies of Swift J1658.24242 using AstroSat observations with the JeTCAF model
We present the X-ray spectral and temporal analysis of the black hole X-ray transient Swift J1658.2-4242 observed by AstroSat. Three epochs of data have been analysed using the JeTCAF model to estimate the mass accretion rates and to understand the geometry of the flow. The best-fitting disc mass accretion rate (? d) varies between 0.90+-000102 and 1.09+-000304 M?Edd in these observations, while the halo mass accretion rate changes from 0.15+-000101 to 0.25+-000102 M?Edd. We estimate the size of the dynamic corona that varies substantially from 64.9+-3319 to 34.5+-1250 rg and a moderately high jet/outflow collimation factor stipulates isotropic outflow. The inferred high disc mass accretion rate and bigger corona size indicate that the source might be in the intermediate to soft spectral state of black hole X-ray binaries. The mass of the black hole estimated from different model combinations is ?14 M?. In addition, we compute the quasi-periodic oscillation (QPO) frequencies from the model-fitted parameters, which match the observed QPOs. We further calculate the binary parameters of the system from the decay profile of the light curve and the spectral parameters. The estimated orbital period of the system is 4.0 0.4 h by assuming the companion as a mid or late K-type star. Our analysis using the JeTCAF model sheds light on the physical origin of the spectrotemporal behaviour of the source, and the observed properties are mainly due to the change in both the mass accretion rates and absorbing column density. 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Spectral and temporal features of GX 13+1 as revealed by AstroSat
GX 13+1, a neutron star low-mass X-ray binary that exhibits the properties of both atoll and Z sources, is studied using data from Soft X-ray Telescope and Large Area X-ray Proportional Counter (LAXPC) onboard AstroSat. The source traces a ? shaped track in its hardness-intensity diagram (HID). Spectral modelling of the data in the 0.7-30.0 keV energy range, with the model-+, yields orbital inclination angle (?) of 77. Flux resolved spectral analysis reveals the ? shaped pattern in the plots of spectral parameters kTe, kTbb, and ? versus Fbol, closely resembling the pattern traced in LAXPC HID. This indicates changes in the spectral properties of the corona and the boundary layer/accretion disc. Assuming that the accretion disc truncates at the AlfvCrossed D sign n radius, the upper limit of the magnetic field strength (B) at the poles of neutron star in GX 13+1 is calculated to be 5.10 108 G (for kA = 1 and ? = 0.1), which is close to that of atoll sources. Furthermore, thickness of the boundary layer is estimated to be 5.70 km, which results in the neutron star radius value of 14.50 km. Quasi-periodic oscillations (QPOs) at 56 4 and 54 4 Hz are detected in Regions D and E of HID, respectively. The frequencies of these QPOs are similar to the characteristic frequency of horizontal branch oscillation and these do not exhibit a positive correlation with mass accretion rate. -
Spectral and power efficiency investigation in single- and multi-line-rate optical wavelength division multiplexed (WDM) networks /
Photonic Network Communications, Vol.33, Issue 1, pp.39–51, ISSN: 1572-8188 (Online) 1387-974X (Print). -
Spectral and power efficiency investigation in single- and multi-line-rate optical wavelength division multiplexed (WDM) networks
In order to tackle the increasing heterogeneous global Internet traffic, mixed-line-rate (MLR) optical wavelength division multiplexed (WDM) networks have emerged as the cost- and power-efficient solution. In MLR WDM networks, channels are structured as sub-bands, each of which consists of wavelengths operating at a similar data rate. By reducing the (1) spacing within a sub-band, or (2) spacing between sub-bands operating at different data rates, spectral efficiency can be improved. However, owing to high physical layer impairment levels, decrease in sub-band spacing adversely affects transmission reach of the channels, which results in higher power consumption due to requirement of increased signal regeneration. In this work, we compare power efficiency of various MLR and single-line-rate (SLR) solutions, and also investigate the trade-off that exists between spectral and power efficiency in a WDM network. Simulation results indicate that (1) for high transmission capacities, a combination of 100Gbps transponders and 40Gbps regenerators will obtain the highest power efficiency; (2) for long connection distances, a point ofmerging occurs for various SLR and MLR designs, where power consumption is independent of the frequency band distribution; and (3) for MLR systems, both spectral and power efficiency can be improved by using either shorter links with higher bandwidth assignment to 100Gbps wavelengths, or longer links with higher bandwidth assignment to 40Gbps wavelengths. Finally, the results indicate that focusing on spectral efficiency alone results in extra power consumption, since high quality of transmission and spectral efficiency leads to increased regeneration. 2016, Springer Science+Business Media New York. -
Specific learning disability and psychological impact among school going adolescents
Specific Learning disability (SLD) is a mental health concern among school going children in India. Considering the need for early identification and intervention, this study has been contextualized to explore the impact. Methodology: Samples have been selectedfrom five schools which are situated in South Bengaluru, India, 100 children have been identified with SLD and further they have been screened for mental health Problems. Results: High prevalence ofmild to moderate anxiety, depression and stress is major finding of the study. High rate of anxiety (37%), depression (47%) and stress (33%) among adolescents with SLD indicate the gravity of the problem. Conclusion: Findings underline the need of the structured interventions by school psychologists in school settings. 2019 Institute for Leadership and Organization Effectiveness. All rights reserved. -
Specialized CNN Architectures for Enhanced Image Classification Performance
Image classification is one of the important tasks in computer vision, with a greater number of applications from facial recognition, medical imaging, object recognition and many more. Convolutional Neural Networks (CNNs) have developed as the foundation for image all classification tasks, showcasing the capacity to learn the hierarchical features automatically. In this study proposed three custom CNN models and its comprehensive analysis for the image classification tasks. The models are evaluated using CIFAR-10 dataset to assess the performance and efficiency. The experimental results shows that the proposed custom CNN Model-3 performance is better than the other two models. Our findings demonstrate that Model 3, featuring with the global average pooling, achieves the highest overall accuracy of 94 % with competitive computational efficiency. This suggests that global average pooling is the valuable technique for balanced and accurate image classification. 2024 IEEE. -
Special Military Application Antenna for Robotics Process Automation
A special military application antenna for robotics process automation is presented in the following chapter. An antenna is a device that uses wireless communication. Wireless communications main advantage is protecting our soldiers from undefined enemies. To keep this thing in mind, we have designed a special military application antenna. The presented antenna is useful for defense and satellite communication, including wi-fi and Wimax, which is useful for the robotics automation process. Most of the military robotics automation is based on wireless communication. Our proposed antenna is very useful and capable of receiving or transmitting high signals in terms of GHz. The presented geometry can radiate the large frequency band from 2.9 to 11.6 GHz, which covers the 5G-(I) Sub- 6GHz band and X-Band Communication, with high efficiency. The impedance bandwidth of the radiator is 120%, with an electrical size of .14?x.14?x0.014? in lambda. The antenna is simulated with an FR4 substrate using a CST Simulator. Simulations also investigate the 08-stages evolution process and corresponding S-parameter results are presented. The proposed structure also demonstrates stable radiation patterns across the operating bandwidth. The proposed radiator has a high gain of 6.78 dBi and an efficiency of 89%. Therefore, it is useful for 5G-(I) Sub-6GHz band and X-band military applications, including satellite mobile, Radar, and Satellite microwave communication. 2023 Scrivener Publishing LLC. -
Spatio-temporal crime analysis using KDE and ARIMA models in the Indian context
In developing countries like India, crime plays a detrimental role in economic growth and prosperity. With the increase in delinquencies, law enforcement needs to deploy limited resources optimally to protect citizens. Data mining and predictive analytics provide the best options for the same. This paper examines the news feed data collected from various sources regarding crime in India and Bangalore city. The crimes are then classified on the geographic density and the crime patterns such as time of day to identify and visualize the distribution of national and regional crime such as theft, murder, alcoholism, assault, etc. In total, 68 types of crime-related dictionary keywords are classified into six classes based on the news feed data collected for one year. Kernel density estimation method is used to identify the hotspots of crime. With the help of the ARIMA model, time series prediction is performed on the data. The diversity of crime patterns is visualized in a customizable way with the help of a data mining platform. Copyright 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. -
Spatio-temporal Crime Analysis and Forecasting on Twitter Data Using Machine LearningAlgorithms
The concept of social media began to gain popularity in the late 1990s and has played a significant role in connecting people across the globe. The constant addition of features to old social media platforms and the creation of new ones have helped amass and retain an extensive user base. Users could now share their views and provide detailed accounts of events from worldwide to reach like-minded people. This led to the popularization of blogging and brought into focus the posts of the commoner. These posts began to be verified and included in mainstream news articles bringing about a revolution in journalism. This research aims to use a social media platform, Twitter, to classify, visualize, and forecast Indian crime tweet data and provide a spatio-temporal view of crime in the country using statistical and machine learning models. The Tweepy Python module's search function and '#crime' query have been used to scrape relevant tweets under geographical constraints, followed by substring-keyword classification using 318 unique crime keywords. The Bokeh and gmaps Python modules create analytical and geospatial visualizations, respectively. Time series forecasting of crime tweet count is performed by comparing the accuracy of Long Short-Term Memory (LSTM), Auto-Regressive Integrated Moving Average (ARIMA), and Seasonal Auto-Regressivee Integrated Moving Average (SARIMA) models to determine the best model. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
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Spatio temporal crime analysis and forecasting using social media data
Now a days, people communicate, share ideas, and interact through social media platforms. It has given us an ability to talk about career interests, post videos, and pictures for sharing with others. The data present in social media enables the analysis of various human aspects. The social media data and domain is used for crime analysis, customer behaviour analysis, and healthcare analysis provides much information useful to predict human behaviours. Crime is the most common social problem faced in a developing country. In developing countries like India, crime plays a detrimental role in economic growth and prosperity. With the increase in delinquencies, law enforcement needs to deploy limited resources optimally to protect citizens. Crime affects the reputation of a nation and the quality of life of its citizens. Crime also affects the economy of the country, increasing the financial burden of the government due to the need for expenditure in the police force and judicial system. Various initiatives are taken by law enforcement to reduce the crime rate. An example of these initiatives includes an accurate and real-time prediction of crime occurrences. Crime analytics and prediction have lengthily studied among research analytics communities. In recent years, crime knowledge from one of a kind heterogeneous source (Twitter, News Feeds, Facebook, Instagram and so forth.) have given enormous opportunities to the research group to comfortably study crime pattern and prediction duties in specific real knowledge. Data mining and predictive analytics provide the best options for the same. Law enforcement organizations are increasingly looking to use data from social media such as Facebook, Newsfeeds, Twitter, etc. investing in research in this area. Using the intelligence gained through these data, the agencies can identify future incidents and plan for active patrolling. -
Spatio - Temporal Analysis of Temperature in Indian States
Data, the oil of the century, is available in multiple formats for various applications. It is collected, stored, and distributed across different use cases in various forms. Researchers study, analyse and use data for numerous analyses and predictions. There is an increase in demand and consideration of spatiotemporal data analysis. Analysing and obtaining insights from the spatiotemporal data are carried out by various researchers. Many investigations have started investigating the strategies for spatial-transient examination and applying spatial-transient information investigation procedures to different areas. Analysing spatiotemporal data has been an advanced task; with the help of various Python libraries, Spatio Temporal dataset about the temperature of states of India is analysed to support the harsh climate near the region of tropic of cancer. Across the decade, there has been a cyclic trend in the temperature, which keeps toggling yet increases over time. It remains a question of worry and genuine concern to predict climatic conditions. Spatio-temporal analysis of temperature in Indian states involves analysing the spatial and temporal variations in temperature across different states in India. The study can use various statistical and geographic information systems (GIS) tools. Spatio-temporal analysis of temperature in Indian states can provide valuable insights into the changing climate patterns in different regions of the country, which can be helpful for policymakers, researchers, and other stakeholders to make informed decisions related to climate change mitigation and adaptation. 2023 American Institute of Physics Inc.. All rights reserved. -
Spatial variations of landslide severity with respect to meteorological and soil related factors
Landslides, a prevalent natural disaster, wreak havoc on both human lives and vital infrastructure, making them a significant global concern. Their devastating impact is immeasurable, necessitating proactive measures to minimize their occurrence. The ability to accurately forecast the severity of a landslide, including its potential fatality rate and the scale of destruction it may cause, holds tremendous potential for prevention and mitigation to reduce the risk and the damage caused by a landslide to infrastructure and life. In this study, the spatial variability in severity of landslides (in terms of mortality rates) and its dependence on various meteorological, geographical and soil composition has been attempted to be established. To do this, Ordinary Least Squares (global) and various Geographically Weighted (local) models have been employed to observe the varying relation between mortality rates and its various causative factors. Existence of geographical heterogeneity in the relationships is also investigated. The spatial pattern of landslide mortality and its associations with various causative variables in the South Asian Region are investigated and analysed. Through this, insights into targeting of prevention and mitigation measures for landslides based on a given location can be obtained by studying the various forms of heterogeneous spatial associations observed. The outcomes highlight that the local models in the form of Gaussian GWR and Poisson GWR outperform their global counterparts by a huge margin with better R2 and Adj R2 values. In comparison with Poisson GWR and Gaussian GWR, it is seen that Poisson GWR outperforms Gaussian GWR in terms of Mean Absolute Error, Mean Squared Error and Corrected Akaike Information Criterion. Furthermore, several intriguing local relationships patterns are also noted. The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
Spatial and seasonal association study between PM2.5 and related contributing factors in India
Global environmental pollution and rapid climate change have become a serious matter of concern. Remarkable spatial and seasonal variations have been observed due to rapid industrialization, urbanization, different festive occasions, etc. Among all the existing pollutants, the fine airborne particles PM2.5 (with aerodynamic equivalent diameter ?2.5?m) and PM10 (with aerodynamic equivalent diameter ?10?m) are associated with chronic diseases. This leads to carry out the study regarding the varying relationship between PM2.5 and other associated factors so that its concentration level might be under control. Existing literature has explored the geographical association between the pollutants and a few other important factors. To address this problem, the present study aims to explore the wide spatio-temporal relationships between the particulate matter (PM2.5) with the other associated factors (e.g., socio-demographic, meteorological factors, and air pollutants). For this analysis, the geographically weighted regression (GWR) model with different kernels (viz. Gaussian and Bisquare kernels) and the ordinary least squares (OLS) model have been carried out to analyze the same from the perspective of the four major seasons (i.e., autumn, winter, summer, and monsoon) in different districts of India. It may be inferred from the results that the local model (i.e., GWR model with Bisquare kernel) captures the spatial heterogeneity in a better way and their performances have been compared in terms of R2 values (>0.99 in all cases) and corrected Akaike information criterion (AICc) (maximum value -618.69 and minimum value -896.88). It has been revealed that there is a strong negative impact between forest coverage and PM pollution in northern India during the major seasons. The same has been found in Delhi, Haryana, and a few districts of Rajasthan during the 1-year cycle (October 2022September 2023). It has also been found that PM concentration levels become high over the specified period with the temperature drop in Delhi, Uttar Pradesh, etc. Moreover, a strong positive association is visible in PM pollution level with the total population. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. -
Spatial analysis of CO poisoning in high temperature polymer electrolyte membrane fuel cells
The improved tolerance of the High Temperature-Polymer Electrolyte Membrane Fuel Cell (HT-PEMFC) to CO allows the use of reformate as an anode feed. However, the presence of several per cent of CO in the reformate, which is inevitable particularly in on-board reformation in automobiles, which otherwise demands complex systems to keep the CO level very low, will significantly lower the cell performance, especially when the HT-PEMFC is operated at 160 C or below. In this study, a three-dimensional, non-isothermal numerical model is developed and applied to a single straight-channel HT-PEMFC geometry. The model is validated against the experimental data for a broad range of current densities at different CO concentration and operating temperatures. A significant spatial variation in current density distribution is observed in the membrane because the CO sorption is a spatially non-homogeneous process depending on local operating conditions and dilution of the H2 stream. To investigate the local spatial effects on HT-PEMFC operation, the model is applied to a real cell of size 49.4 cm2 with an 8-pass serpentine flow-field at the anode and the cathode. The membrane and anode catalyst layer are segmented into 5 array to investigate the spatial resolution of the polarization curves, H2 concentration, current density, and anode polarization loss. The simulation results show that the presence of CO in the anode feed reduces cell performance, however, the results reveal that uniformity in current density distribution in the membrane improves when the cell is operated in potentiostatic mode. The results are discussed in detail with the help of several line plots and multi-dimensional contours. The study also emphasizes on the importance of optimizing the reformate anode feed rate to improve cell performance. 2020 Hydrogen Energy Publications LLC