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Natural convection of water-copper nanoliquids confined in low-porosity cylindrical annuli
Natural convection in cylindrical porous annuli saturated by a nanoliquid whose inner and outer vertical radial walls are respectively subjected to uniform heat and mass influxes and out fluxes is studied analytically using the modified Buongiorno-Darcy model (MBDM) and the Oseen-linearization technique. Nanoliquid-saturated porous medium made up of water as base liquid, copper nanoparticles of five different shapes, viz., spheres, bricks, cylinders, platelets and blades, and glass balls porous material is considered as working medium for investigation. The thermophysical properties of nanoliquid -saturated porous medium is modeled using phenomenological laws and mixture theory. The effect of various parameters and individual effects of five different shapes of copper nanoparticles on velocity, temperature and heat transport are found. From the study, it is clear that the addition of a dilute concentration of nanoparticles increases the effective thermal conductivity of the system and thereby increases the velocity and the heat transport, and decreases the temperature. In other words, the heat transport is more in the case of heat and mass driven convection compared to purely heat-driven convection. Among the five different shapes of nanoparticles, blade-shaped nanoparticles facilitate the transport of maximum temperature compared to all other shapes. Maximum heat transport is achieved in a shallow cylindrical annulus compared to square and tall circular annuli. The increase of the inner solid cylinder's radius is to decrease heat transport. The results of the KVL single-phase model are obtained from the present study by setting to zero the value of the nanoparticles concentration Rayleigh number. Also, neglecting the curvature effect in the present problem, we obtain the results of the rectangular enclosure problem. 2020 The Physical Society of the Republic of China (Taiwan) -
Study of rotating Bard-Brinkman convection of Newtonian liquids and nanoliquids in enclosures
Taylor-Bard convection of water and water-based nanoliquids confined in three different types of high porosity rectangular enclosures, viz., shallow, square and tall, is studied analytically using both infinitesimal and finite amplitude stability analyses. We make use of the modified-Buongiorno-Brinkman model(MBBM) for the governing equations concerning nanoliquid-saturated porous enclosures bounded by rigid-rigid boundaries and obtain analytical results. Among three types of enclosures, maximum and minimum heat transfers are observed in tall and shallow enclosures respectively. Water well dispersed with a dilute concentration of single-walled carbon nanotubes(SWCNTs) is considered as a working medium. The water-SWCNTs is able to flow in the porous medium because the medium is loosely-packed with porosity in the range 0.5 ? ? ? 1. In addition to this, the maximum volume fraction of nanoparticles considered in the system is 6% and thus this does not alter the fluidity of the system. We found from the study that the presence of low concentration(volume fraction-0.06) of SWCNTs in a water-saturated porous medium effectively improves the heat transport of the system due to its high thermal conductivity and large surface area. Due to the presence of a porous medium, however, the onset of convection gets delayed and heat transport in nanoliquids gets substantially reduced in a Bard-Brinkman configuration resulting from the weak thermal conductivity of the porous medium. Thus the porous medium acts as the heat storage system. Also, in a rotating frame of reference the heat transport gets reduced and rotation serves as an external mechanism of regulating heat transport in the system. The nonlinear dynamics of the system is studied using the 6-mode Lorenz model. Chaotic motion in the system is studied using the maximum Lyapunov exponent(MLE). The Hofp-bifurcation point of the system along with the MLE is used to investigate periodic, nearly periodic and mildly chaotic behaviors of the system. 2020 -
Achievenment motivation and self esteem among handicapped children
How the children with handicap perceive themselves and their self esteem levels are important yet not much focussed aspect in disability research. If we have a correct evaluation of their motivational level and self esteem it may help us to modify their training interventions and also would make them feel more satisfied and confident. So we planned to study achievement motivation and self esteem levels of handicapped children. The Objective of the study is that to to compare achievement motivation of physically handicapped to that of non-handicapped school children, and to compare self esteem of physically handicapped to that of non-handicapped school children. Methodology 40 physically handicapped school students and 40 age, gender and education matched non handicapped students were included in the study. Handicapped children of other categories like sensory disability, visual impairment, hearing impairment and speech impairment were excluded. Achievement motivation questionnaire was used to measure the motivational behaviour and Rosenberg self-esteem scale was applied by asking the respondents to reflect on their current feelings. Results and Conclusions Achievement motivation and self esteem were observed to be significantly lower in physically handicapped students compared to healthy controls. Significant gender difference in favour of females was observed i.e., self esteem and achievement motivation was significantly higher in females of both the groups compared to males. The study emphasizes need for interventions to improve self esteem and motivation levels of handicapped children. -
A Hybrid Approach Against Black Hole Attackers Using Dynamic Threshold Value and Node Credibility
Detecting black hole attackers is tedious in Vehicular Ad Hoc Networks due to vehicles' high mobility. The main consequence faced because of these attackers is an increase in the number of dropped packets which converts secure and fastest paths to compromised ones. Since these attackers can act individually and collaboratively as a group, early detection of these attackers must be feasible to preserve the network's performance. The majority of current methods rely on predetermined threshold and trust score values, which are ineffective in accurately identifying black hole attackers. Hence, this paper proposes a hybrid approach using dynamic threshold value and node credibility for early detection of black hole attackers. RSUs periodically compute the dynamic threshold value and categorize the vehicles into categories 1, 2, and 3. Vehicles classified as Category 1 are legitimate, whereas Category 3 vehicles are attackers. Vehicles in Category 2 are suspicious, requiring further analysis using node credibility values to identify attackers. It is protected against single, multiple, and collaborative black hole attackers. The NS2 simulation results demonstrate that the suggested method is optimal concerning PDR, Throughput, Delay, and Packet Loss Ratio compared to recent techniques. Since the proposed scheme efficiently identifies the attackers, it has 89.67% PDR, which is higher when compared to other schemes. 2013 IEEE. -
Strengthening of brick masonry using biaxial polypropylene geogrid as confinement reinforcement
Recent and past earthquakes have once again reiterated the requirement of strengthening the masonry structures to withstand both in-plane and out-of-plane loads. In this experimental investigation, biaxial polypropylene geogrid was used as a confinement reinforcement on the surfaces to strengthen masonry specimens. The masonry specimens without and with geogrid have been subjected to a compression test, flexural bond strength test and diagonal tension (shear) test as per IS 1905, ASTM E518 and ASTM E519, respectively. From the results, it has been found that biaxial polypropylene geogrid significantly enhances the strength in masonry specimens with geogrid and also reduces crack propagation in all three tests. The relationship between compressive strength and flexural bond strength, compressive strength and shear strength of masonry specimens with geogrid has been established. Furthermore, based on the cost analysis of various strengthening techniques, it was concluded that the use of biaxial polypropylene geogrid is an economically feasible alternative to other reinforcing materials, such as stainless-steel wire mesh and polyester geogrid. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. -
FOXS HEAD OR LIONS TAIL? WORK LIFE BALANCE OF WOMEN ENTREPRENEURS IN AGRICULTURE AND FARM VENTURES AND ITS ANTECEDENT EFFECT ON QUALITY OF LIFE; [CABE DE RAPOSA OU RABO DE LE? EQUILRIO DA VIDA PROFISSIONAL DAS MULHERES EMPREENDEDORAS NA AGRICULTURA E EMPREENDIMENTOS AGROLAS E SEU EFEITO ANTECEDENTE NA QUALIDADE DE VIDA]; [CABEZA DE ZORRO O COLA DE LE? LA CONCILIACI DE LA VIDA LABORAL Y FAMILIAR DE LAS MUJERES EMPRESARIAS EN LA AGRICULTURA Y LAS EXPLOTACIONES AGROLAS Y SU EFECTO ANTECEDENTE EN LA CALIDAD DE VIDA]
Purpose: The objective of this study was to identify the factors that influence work life balance of women entrepreneurs in the field of agriculture and allied products and how the family demands affect their work-life balance. Further, the paper explores the conflict between parental demand and running a business. Theoretical framework: Literature review points out that despite, an increase in the number of women entrepreneurs over the years, according to the (Global entrepreneurship monitor report, 2020), fewer women pursue entrepreneurship due to various challenges of managing personal and business responsibilities and striking the right balance. Work-life balance is frequently examined in the context of human resource management (Etienne St-Jean and Duhamel M.,2020)but not much has been explored in an entreprenurial context.Hence this study is to investigate and understand the influence of various factors affecting work life balance from an entrepreneurial standpoint. Design/methodology/approach: Triangulation method was used for the study by utilizing both quantitative and qualitative data. The researchers developed a questionnaire to measure work-life balance experienced by women entrepreneurs with 12 independent variables to measure the dependent variable work-life balance.The sample consisted of 450 women agripreneurs Findings: The findings reveal that the age of the children is a major determinant of the extent of parental demand a woman goes through in her life and family support systems are critical in reducing overlap and conflict between the life domains. A positive spillover between the domains significantly enhances quality of life of women entrepreneurs. Research, Practical & Social implications: We suggest a future research into other Personality traits and macro environmental factors which can have a bearing on work life balance of women entrepreneurs which would enable an inclusive entrepreneurial ecosystem. Originality/value: The researchers have concluded that positive spillover between the domains significantly enhances quality of life of women entrepreneurs. 2022 The authors. -
IOT-BASED cyber security identification model through machine learning technique
Manual vulnerability evaluation tools produce erroneous data and lead to difficult analytical thinking. Such security concerns are exacerbated by the variety, imperfection, and redundancies of modern security repositories. These problems were common traits of producers and public vulnerability disclosures, which make it more difficult to identify security flaws through direct analysis through the Internet of Things (IoT). Recent breakthroughs in Machine Learning (ML) methods promise new solutions to each of these infamous diversification and asymmetric information problems throughout the constantly increasing vulnerability reporting databases. Due to their varied methodologies, those procedures themselves display varying levels of performance. The authors provide a method for cognitive cybersecurity that enhances human cognitive capacity in two ways. To create trustworthy data sets, initially reconcile competing vulnerability reports and then pre-process advanced embedded indicators. This proposed methodology's full potential has yet to be fulfilled, both in terms of its execution and its significance for security evaluation in application software. The study shows that the recommended mental security methodology works better when addressing the above inadequacies and the constraints of variation among cybersecurity alert mechanisms. Intriguing trade-offs are presented by the experimental analysis of our program, in particular the ensemble method that detects tendencies of computational security defects on data sources. 2023 The Authors -
Being a therapeutic clown- an exploration of their lived experiences and well-being
Therapeutic clowning uses humor and play to minimize the stress for patients and their families during hospitalization. This study aims to explore the subjective meaning of therapeutic clowning through clowns perspective, understand why they continue clowning and interpret how it has impacted them. The research design takes a qualitative approach using phenomenological paradigm. Nine therapeutic clowns between 20 and 60years with clowning experience of 6months-4years from Compassionate Clowns, located at Bangalore were interviewed. The results reflected that the journey of being a therapeutic clown has been equally therapeutic for the clowns. Based on the thematic data analysis network, it was found that clowning has instilled many values in the way they think. It has given them a platform to learn new things from the children they clown. Therefore, looking at these results it could be said that therapeutic clowning serves as a medium for community service and in maintaining personal wellbeing. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
A Novel Survey for Young Substellar Objects with the W-band Filter. V. IC 348 and Barnard 5 in the Perseus Cloud
We report the discovery of substellar objects in the young star cluster IC 348 and the neighboring Barnard 5 dark cloud, both at the eastern end of the Perseus star-forming complex. The substellar candidates are selected using narrowband imaging, i.e., on and off photometric technique with a filter centered around the water absorption feature at 1.45 ?m, a technique proven to be efficient in detecting water-bearing substellar objects. Our spectroscopic observations confirm three brown dwarfs in IC 348. In addition, the source WBIS 03492858+3258064, reported in this work, is the first confirmed brown dwarf discovered toward Barnard 5. Together with the young stellar population selected via near- and mid-infrared colors using the Two Micron All Sky Survey and the Wide-field Infrared Survey Explorer, we diagnose the relation between stellar versus substellar objects with the associated molecular clouds. Analyzed by Gaia EDR3 parallaxes and kinematics of the cloud members across the Perseus region, we propose the star formation scenario of the complex under influence of the nearby OB association. 2022. The Author(s). Published by the American Astronomical Society. -
Study on gravitational waves from binary mergers and constraints on the Hubble parameter
Einsteins general theory of relativity predicted the existence of gravitational waves (GWs), which offer a way to explore cosmic events like binary mergers and could help resolve the Hubble Tension. The Hubble Tension refers to the discrepancy in the measurements of the Hubble Constant, Ho, obtained through different methods and missions over various periods. By analyzing gravitational wave data, particularly from mergers that also emit light (electromagnetic radiation), such as Bright Sirens, we aim to reduce this tension. This paper will investigate the properties of GWs produced by these binary mergers and utilize a mathematical framework to tackle the Hubble Tension. Future advancements in gravitational wave astronomy, particularly with initiatives like LIGO-India and LISA, promise to enhance research outcomes. The ground-based LIGO-India will increase sensitivity and improve localization, while the space-based LISA will target lower frequency ranges of GWs, enabling the detection of signals from a wider array of sources. Indian Association for the Cultivation of Science 2025. -
Trends in virtual influencers (VIs): A bibliometric analysis and SPAR-4-SLR protocol
This study aims to comprehensively understand qualitative and quantitative information about the current trends in VIs. It examines 106 articles published in Scopus-indexed journals between 2020 and 2024. The analysis was done with the help of Biblioshiny, an R-developed online application from the Bibliometrix package, and VOSviewer software for analytical and visualization purposes. This study was conducted using the SPAR-4-SLR protocol. The findings showed that recent years have been more productive, and many authors have demonstrated their interest in studying the VIs. Recent trends are social media, virtual reality, marketing, social networking, etc. The study employs a systematic review and bibliometric analysis to extract valuable insights from the extensive body of literature. These insights suggested several areas for future research, providing a roadmap for future researchers to proceed with their research in this area. The comprehensive scientific cartography of the area has yet to be presented; therefore, this study aims to synthesize the current knowledge frameworks within the field and determine the dominant research patterns in the specific area of investigation. 2024, Malque Publishing. All rights reserved. -
Automatic Diagnosis of Autism Spectrum Disorder Detection Using a Hybrid Feature Selection Model with Graph Convolution Network
A neurodevelopmental disorder is called an autism spectrum disorder (ASD) that influences a persons assertion, interaction, and learning abilities. The consequences and severity of symptoms of ASD will vary from person to person; the disorder is mainly diagnosed in children aged 15years and older, and its symptoms may include unusual behaviors, interests, and social challenges. If it is not resolved at this stage, it will become severe in the coming days. So, in this manuscript, we propose a way to automatically tell if someone has ASD that works well by using a combination of feature selection and deep learning. Four phases comprise the proposed model: preprocessing, feature extraction, feature selection, and prediction. At first, the collected images are given to the preprocessing stage to remove the noise. Then, for each image, three types of features are extracted: the shape feature, texture feature, and histogram feature. Then, optimal features are selected to minimize computational complexity and time consumption using a new technique based on a combination of adaptive bacterial foraging optimization (ABFO), support vector machines-recursive feature elimination (SVM-RFE), minimum redundancy and maximum relevance (mRMR). Then, the graph convolutional network (GCN) classifier uses the selected features to identify an image as normal or autistic. According to the research observations, our models accuracy is enhanced to 97.512%. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
Multi-atlas Graph Convolutional Networks and Convolutional Recurrent Neural Networks-Based Ensemble Learning for Classification of Autism Spectrum Disorders
Autism spectrum disorder (ASD) has an influence on social conversation and interaction, as well as encouraging people to engage in repetitive behaviors. The complication begins in childhood and persists through adolescence and maturity. Autism spectrum disorder has become the most common kind of childhood development worldwide. ASD hinders the capacity to interact, socialize, and build connections with individuals of all ages, and thus its early intervention is critical. This paper discusses some of the most recent approaches to diagnostics using convolutional networks and multi-atlas graphs for autism spectrum disorders. Also, several pre-processing approaches are elaborated. Graph convolutional neural networks (GCNs) to diagnose autism spectrum disorder (ASD) because of their remarkable effectiveness in illness prediction using multi-site data. Convolutional neural network (CNN) and recurrent neural networks (RNN) infrastructure studies functional connection patterns between various brain regions to find particular patterns to diagnose ASD. In our research, we implemented the GCN + CRNN ensemble method and achieved 89.01% accuracy based on resting-state data from the fMRI (ABIDE-II), a novel framework for detecting early signs of autism spectrum disorders is presented and discussed. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
Growth, survival and haemato-biochemical profiles of the freshwater catfish, Pangasius sutchi (Fowler, 1937) fingerlings fed with Tinospora cordifolia leaf extract supplemented diet
The present study documents the possible effects of Tinospora cordifolia leaf extract supplemented diets on growth, survival and haemato-biochemical profiles of the catfish, Pangasius sutchi fingerlings. P. sutchi fingerlings were fed with formulated diets, supplemented with four different concentrations of T. cordifolia leaf extract (viz. 100, 200, 400 and 800 mg kg-1 of feed) for 45 days. Fingerlings fed with basal diet served as control. Various parameters of serum biochemical and haematology such as serum total protein content, albumin content, globulin content, albumin globulin ratio, glucose, erythrocytes count, leucocytes count were evaluated along with growth parameters. The results indicated that Specific Growth Rate (SGR), Feed Conversion Ratio (FCR), Protein Efficiency Ratio (PER), survival and Haemato-biochemical profiles such as total serum protein, albumin, globulin, albumin globulin ratio and serum glucose were high in the fingerlings fed with T. cordifolia leaf extract supplemented diets, irrespective of dosage, compared to control. Among the four concentrations of T. cordifolia leaf extract used, 400 mg/kg of feed group showed increased growth, survival and enhanced the health status of P. sutchi fingerlings. 2020, Egyptian Society for the Development of Fisheries and Human Health. All rights reserved. -
Design of digital filters for multi-standard transceivers
This paper addresses on three different architectures of digital decimation filter design of a multi-standard RF transceivers. Instead of using single stage decimation filter network, the filters are implemented in multiple stages using FPGA to optimize the area, delay and dynamic power consumption. The proposed decimation filter architectures reflect the considerable reduction in area and dynamic power consumption without degradation of performance. The filter coefficients are derived from MATLAB, the filter architectures are implemented and tested using Xilinx SPARTAN FPGA.First, the types of decimation filter architectures are tested and implemented using conventional binary number system. Then the two different encoding schemesi.e. Canonic Signed Digit (CSD) and Minimum Signed Digit (MSD) are used for filter coefficients and then the architecture performances are tested.The results of CSD and MSD based architectures show a considerable reduction in the area and power against the conventional number system based filter design implementation. The implementation results reflect that considerable reduction in area of 47.89% and dynamic power reduction of 28.64% are achieved using hybrid architecture. 2015 School of Electrical Engineering and Informatics. All rights reserved. -
Hybrid architecture of digital filter for multi-standard transceivers
This paper addresses on three different architectures of digital decimation filter design of a multi-standard RF transceivers. Instead of using single stage decimation filter network, the filters are implemented in multiple stages using FPGA to optimize the area and power. The proposed decimation filter architectures reflect the considerable reduction in area & power consumption without degradation of performance. First, the types of decimation filter architectures are tested and implemented using conventional binary number system. Then the two different encoding schemes i. e. Canonic Signed Digit (CSD) and Minimum Signed Digit (MSD) are used for filter coefficients and then the architecture performances are tested using FPGA. The results of CSD and MSD based architectures show a considerable reduction in the area & power against the conventional number system based filter design implementation. The implementation results reflect that considerable reduction in area of 25. 64% and power reduction of 16. 45% are achieved using hybrid architecture. Research India Publications. -
Digital filter architectures for multi-standard wireless transceivers
This paper addresses on two different architectures of digital decimation filter design of a multi-standard RF transceivers. Instead of using single stage decimation filter network, the filters are implemented in multiple stages using FPGA to optimize the area and power. The proposed decimation filter architectures reflect the considerable reduction in area & power consumption without degradation of performance. The filter coefficients are derived from MATLAB , the filter architectures are implemented and tested using Xilinx SPARTAN FPGA . The Xilinx ISE 9.2i tool is used for logic synthesis and the Xpower analysis tool is used for estimating the power consumption. First, the types of decimation filter architectures are tested and implemented using conventional binary number system. Then the different encoding scheme i.e. Canonic Signed Digit (CSD) representation is used for filter coefficients and then the architecture performance is tested .The results of CSD based architecture shows a considerable reduction in the area & power against the conventional number system based filter design implementation. -
Impact of lockdown during COVID-19 pandemic on the learning status of undergraduate and postgraduate students of Bangalore
Background: The COVID 19 pandemic has created various impacts on every human's life. COVID 19 lockdown has provoked enormous changes in the education sector which in turn influences the student's life in many aspects. The scope of this study is to understand the impact in both undergraduate and postgraduate students. Aim: This study aims at incisively analyzing the impact of lockdown imposed due to the COVID-19 pandemic on graduate students of Bangalore. Method: It is an online survey that encompasses a structural questionnaire with open-ended questions created using Google Forms, which were sent across the students through social media platforms. Results: A total of 115 students from both undergraduate and postgraduate programs have participated in this survey. Simple percentage distribution was estimated to evaluate the pedagogy, opinion on educational decisions, modes of learning, socio-economic conditions, and problems pertaining to academia because of this pandemic. As per this analysis, 80.9% of students faced difficulty due to lockdown. 67% of students thought that their family's income will be affected by this pandemic. 68.7% of students felt stressed, depressed and 52.3% of students could not find a suitable environment in their home to study during this lockdown. When we see this pandemic in an optimistic light, it has created various opportunities such as Digital learning and adoption of new health habits. 2021. RIGEO. All Rights Reserved. -
A Scoping Review of Formal Care to Children with Special Needs during the Covid-19 Pandemic
The Covid-19 pandemic caused an unprecedented closure of direct service for children with special needs (CSNs), which shifted service to remote mode. This scoping review analyzed the strategies adopted by different formal care services for CSNs, their strengths and weaknesses, and the challenges faced by the formal care providers (FCPs). This study identified relevant articles through academic databases and Google searches using appropriate search strings and keywords. It included ten journal articles (n=10) and eight pieces (n=8) of grey literature through a meticulous selection process and extracted data. This review drew results by collating the descriptive numerical data analysis and qualitative thematic analysis and interpreting them. Reporting incor-porated all the possible items recommended by the PRISMA-ScR guidelines. This review demonstrated that pediatric rehabilitation adopted the telehealth approach and that special education changed to remote learning. When childcare programs in the USA functioned according to specific guidelines, residential care in South Asian countries faced a financial crunch. FCPs faced personal and professional challenges that required systematic training to deal with pandemic situations. This scoping review made suggestions for relevant policy formulations for equitable and effective service delivery to CSNs during pandemic situations, and it exposed new avenues for research. 2022 Authors. -
Web mining patterns discovery and analysis using custombuilt Apriori Algorithm
International Journal of Engineering Inventions Vol.2, Issue 5,pp.16-21 ISSN No. 2278-7461