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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 -
Spanning graph topology of graphs
The collection of subgraphs of a graph G containing G and the null graph K0, which is closed under union and intersection, is said to be a graph topology defined on G. In this paper, we investigate the idea of spanning graph topology of a graph G, where we consider the collection of spanning subgraphs of G satisfying the axioms analogous to the axioms of graph topology. We begin with the basic concepts of spanning graph topological space and later and introduce two spanning subgraph complements to define closed graphs in spanning graph topological spaces. 2023 World Scientific Publishing Company. -
Space taxonomy: Need for a progressive tax regime
Konstantin Tsiolkovsky famously stated that while the Earth serves as the birthplace of humanity, it is not a place where mankind can indefinitely remain. Perhaps during that period, the prospect of exploring the mysteries of outer space appeared to be an unattainable aspiration. However, in the present day, there are no longer any limitations, not even the sky, since human ingenuity has facilitated access to outer space for humanity. This access is not just for the purposes of research and exploration but also for economic endeavours. Until now, the commercial utilisation of outer space has advanced at a very sluggish rate. However, firms including SpaceX, Orion Span, Virgin Galactic, and Blue Origin have achieved significant advancements in the growth of the space industry. The revenue generated by various space-related endeavours has experienced a significant 73% increase over the last ten years. The global space economy, estimated to be valued at USD one trillion in the coming years, is primarily driven by commercial activities. This presents a formidable challenge to the existing national and international taxation systems. Similar to the open seas, space is also considered res communis omnium, meaning it belongs to the entire community, and presents comparable taxing challenges with potentially uncertain solutions. The three fundamental elements of every taxation regulation, such as the Organisation for Economic Co-operation and Development or the United Nations Model Double Taxation Convention, are the taxpayer's place of residence, the origin of their income, and the methods by which they generate their money. The current tax system does not have the necessary concepts and provisions to adapt to the rapid advancements in commercial space technology. This paper examines the legal issues surrounding commercial activities conducted in space, including the nature and handling of the income generated in various legal systems. It also addresses concerns such as tax avoidance and excessive taxation, emphasising the necessity for a globally coordinated approach to effectively tax commercial activities in space. 2024 -
SOURCES OF OCCUPATIONAL STRESS AND ITS CONSEQUENCES AMONG TEACHERS
Occupational Stress in workplace occurs when the job demands that are required by the individual cannot be fulfilled at a given time, which in turn leads to adverse effect on individual. Teaching has been identified as one of the most stressful occupations in many countries. The Purpose of this research was to measure the Sources of Occupational Stress and its Consequences among Private and Government Teachers of Pre- University College of Shillong, Meghalaya. The sample of the study consisted of 60 participants from Shillong city, Meghalaya, where 16 male and 44 female teachers and the participants between the age group of 20-51 years and above who are working in Private and Government institutions were considered for the study. The data was collected using structured, open and close ended questionnaire which was mailed to some participants and personally distributed to 70 participants out of which only 60 participants responded from Private and Government institution using Purposive Sampling. The Objectives of the study were, to study the demographic details of the teachers, to identify the sources of occupational stress, to study the consequences among teachers; to compare government and private teachers in terms of sources of occupational stress and its consequences. The Tools used were demographic details, Teacher Stress Inventory (Fimian & Fastenau, 1990). The collected data were analyzed using Statistical Package for social sciences (SPSS) 17.0 version. Frequency and Percentage: was used to interpret the demographic characteristics, sources of occupational stress and its consequences. T-test: was used for the comparison between two groups. Pearson's chi-square test was used to discover if relationship exist between two categorical variables. One way ANOVA was used for the comparison between three groups. The results shows that there were no significant differences found between private teachers and government teachers on sources of occupational stress and its consequences. Significant differences were found between male and female teachers on sources of occupational stress and its consequences. Keywords: Occupational Stress, Higher Secondary Teachers, Consequences of Stress -
Source-load-variable voltage regulated cascaded DC/DC converter for a DC microgrid system
Solar energy is available abundantly, the utilization of solar energy is developing rapidly and the photovoltaic based direct current (DC) microgrid system design is under demand but the stability of the DC voltage is of most important issue, as the variation of the output DC voltage is a common problem when the load or source voltage varies, hence a regulated DC output voltage converter is proposed. This paper presents source-load-variable (SLV) voltage regulated cascaded DC/DC converter which is used to obtain regulated output voltage of 203.1 V DC at 0.4 duty ratio with 2% voltage fluctuations for the variation in the input source voltage and 1.5% voltage fluctuations for the variation in load resistance of the nominal value with lower output voltage ripple and without use of sub circuits. A simulation model of SLV voltage regulated cascaded DC/DC converter in LTspice XVII software environment for the assessment of converter performance at different input source voltages and load resistances are verified. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Sonochemical assisted impregnation of Bi2WO6 on TiO2 nanorod to form Z-scheme heterojunction for enhanced photocatalytic H2 production
In this work, Bi2WO6/TiO2 nanorod heterojunction was prepared by sonochemical assisted impregnation method. After loading 2 wt% Bi2WO6 on TiO2 nanorods, the photocatalytic hydrogen production rate of 2026 mol/h/g was achieved. Compared to commercial P25 and TiO2 nanorods, ?13 and ?3 folds enhanced activity was observed. The excellent photocatalytic performance of Bi2WO6/TiO2 nanorod photocatalyst was mainly attributed to i) reduction of bandgap due to heterojunction formation, ii) quick transport of photogenerated charge carriers, and iii) efficient charge carrier separation supported by UV-DRS, photocurrent measurement, Impedance study, and photoluminescence spectra analysis. The Z-scheme band alignment for Bi2WO6/TiO2 nanorod heterojunction was proposed based on the Mott-Schottky measurement. This result demonstrated the effective utilization of Z-scheme heterojunction of Bi2WO6/TiO2 for photocatalytic reduction application. 2021 The Society of Powder Technology Japan -
Somnolent musings
RIGHT IN THE MIDDLE