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Enhancing food crop classification in agriculture through dipper throat optimization and deep learning with remote sensing
Remote sensing images (RSIs), a keystone of modern agricultural technology, refer to spectral or visual data captured from drones, satellites, or aircraft without direct physical contact with the Earth's surface. These images provide a wide-ranging view of agricultural landscapes, providing valuable insights into land use, crop health, and environmental conditions. Agricultural food crop classification, a vital application within precision agriculture, includes the detection and classification of different crops cultivated in a certain region. Traditionally reliant on manual techniques, the development of technologies, particularly the incorporation of RSIs, has revolutionized this process. Agricultural food crop classification has become more sophisticated and automated by harnessing the wealth of data received from RS, which facilitates precise management and monitoring of crops on a large scale. Deep learning (DL), a branch of artificial intelligence, plays a more effective role in these synergies. The incorporation of DL into the RSI analysis enables high-precision and efficient detection of various crop types, assisting more informed decision-making in agriculture. This study proposes a new Dipper Throat Optimization Algorithm with Deep Learning based Food Crop Classification (DTOADL-FCC) algorithm using Remote Sensing Imaging for Agricultural Resource Management. The DTOADL-FCC method aims to apply DL algorithms for the classification of different crop types. In the DTOADL-FCC method, fully convolutional network (FCN) based segmentation process is performed. Next, the DTOADL-FCC method exploits the SE-ResNet model for learning intrinsic and complex features. The DTOADL-FCC method makes use of DTOA for the hyperparameter tuning process. Lastly, the classification of crop types takes place using the extreme learning machine (ELM) model. The study utilizes mathematical formulations including activation functions, loss functions, fitness calculations, and iterative update processes. A brief set of simulations showcases that the DTOADL-FCC method achieves remarkable performance over other techniques with much improved results. 2024 The Author(s) -
Paired Domination Integrity of Graphs
The concept of vulnerability in a communication network plays an important role when there is a disruption in the network. There exist several graph parameters that measure the vulnerability of a communication network. Domination integrity is one of the vulnerability parameters that measure the performance of a communication network. In this paper, we introduce the concept of paired domination integrity of a graph as a new measure of graph vulnerability. Let G = (V,E) be a simple, connected graph. A set of vertices in a graph G, say S, is a paired dominating set if the following two conditions are satisfied: (i) every vertex of G has a neighbor in S and (ii) the subgraph induced by S contains a perfect matching. The paired domination integrity of G, denoted by PDI(G), is defined as PDI(G) = min{|S| + m(G - S): S is a paired dominating set of G}, where m(G - S) is the order of the largest component in the induced subgraph of G - S. In this paper, we determine few bounds relating paired domination integrity with other graph parameters and the paired domination integrity of some classes of graphs. 2024 World Scientific Publishing Company. -
Lung tuberculosis detection using x-ray images
This research work is based on the various experiments performed for the detection of lung tuberculosis using various methods like filtering, segmentation, feature extraction and classification. The results obtained from these experiments are discussed in this paper. Lung tuberculosis is a bacterial infection that causes more deaths in the world than any other infectious disease. Two billion people are infected with tuberculosis all around the world. Lung tuberculosis is a disease caused by a bacteria known as Mycobacterium tuberculosis or Tubercle bacillus. This research work strives to identify methods by which patients, who require second opinion for an already identified result, can save a lot of money. Once we receive X-ray image an input, pre-processing methods like Gaussian filter, median filter is applied. These filters help to remove unwanted noise and aid to get fine textural features. The output obtained from this is taken as an input and applied to water shed segmentation and gray level segmentation which helps to focus on the lung area of the obtained results. Output from these segmentation methods is fused to get a Region of Interest (ROI). From the ROI, the statistical features like area, major axis, minor axis, eccentricity, mean, kurtosis, skewness and entropy are extracted. Finally, we use KNN, Sequential minimal optimization (SMO), simple linear regression classification methods to detect lung tuberculosis. The results obtained in this paper suggests KNN classifier performs well than the other two classifiers. Research India Publications. -
A novel automated method for the detection of strangers at home using parrot sound
The sound produced by parrots is used to gather information about their behavior. The study of sound variation is important to obtain indirect information about the characteristics of birds. This paper is the first of a series in analyzing bird sounds, and establishing the adequate relation of bird's sound. The paper proposes a probabilistic method for audio feature classification in a short interval of time. It proposes an application of digital sound processing to check whether the parrots behave strangely when a stranger comes. The sound is classified into different classes and the emotions of the birds are analyzed. The time frequency of the signal is checked using spectrogram. It helps to analyze the parrot vocalization. The mechanical origin of the sound and the modulation are deduced from spectrogram. The spectrogram is also used to check the amplitude and frequency modulation of sound and the frequency of the sound are detected and analyzed. This research and its findings will help the bird lovers to know the bird behavior and plan according to that. The greater understanding of birds will help the bird lovers to feed and care for birds. BEIESP. -
A Paradigm shift in Family therapy in India : Exploration from Socioeconomic, Cultural and Spiritual Perspectives
International Journal of Physical and Social Sciences Vol. 3, Issue 3,pp. 153-166 , ISSN No. 2249-5894 -
Exploring the effectiveness of mindfulness-based intervention among college students in India
This study investigated the effectiveness of an eight-week mindfulness-based intervention program on the trait mindfulness, psychological well-being and emotion regulation of college-going students. The experimental group participants were college-going students (N = 40) who enrolled for the intervention, and the participants in the control group (N = 40) were interested in the intervention and considered as a wait-list control group. The experimental group underwent mindfulness-based interventions, which included 1112 sessions, including brief exercises and meditations related to their trait mindfulness, emotion regulation, and psychological well-being. They received 23h of training per week for eight weeks. Repeated Measures of ANOVA together with an independent sample t-test were used to evaluate the effectiveness of this intervention programme. Further, Cohens d was used to calculate the effect size to explain the variance caused by the intervention program in trait mindfulness, emotion regulation, and psychological well-being. The results indicated that students significantly improved in their trait mindfulness, emotion regulation, and psychological well-being after receiving mindfulness training. In conclusion, the application of this eight-week mindfulness-based intervention sheds light on the common psychological issues confronted by college students in India, presenting itself as an advantageous tool for the professionals working in this field and offering positive effects on the overall well-being of college students. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Further studies on circulant completion of graphs
A circulant graph C(n, S) is a graph having its adjacency matrix as a circulant matrix. It can also be interpreted as a graph with vertices v0, v1,,vn?1 that are in one-to-one correspondence with the members of Zn and with edge set {vivj: i ? j ? S}, where S known as the connection set or symbol, is a subset of non-identity members of Zn that is closed under inverses. This work extends the study of circulant completion and general formulae for calculating circulant completion numbers in two different perspectives, one in terms of circulant span and the other in terms of the adjacency matrix. (2024), (SciELO-Scientific Electronic Library Online). All Rights Reserved. -
DETERMINANTS OF CREDIT RISK: EMPIRICAL EVIDENCE FROM INDIAN COMMERCIAL BANKS
Credit risk is a significant factor affecting the financial stability of banks. Keeping the credit risk under control is essential to maintain a banks cash flow. This paper examines the various profitability, microeconomic and macroeconomic indicators that affect a banks credit risk. The study uses the dataset of 31 banks from 2012 to 2021 and employs a panel data modelling approach to account for any variations in risk-taking behavior. The results revealed a statistically significant negative relationship between return on equity and credit risk when nonperforming loans proxy credit risk. This finding was consistent across fixed effect, random effect, and pooled OLS methods, at 1 percent significance (P value < 0.00), indicating that the extent of credit risk decreases as profitability increases. It was further found that bank age and ownership type positively affect a banks credit risk, while factors such as bank size and operational efficiency negatively affect credit risk when nonperforming loans proxy credit risk. Further, macroeconomic variables showed that gross domestic product is positively associated with credit risk, while inflation negatively affects credit risk. Overall, the findings of this paper demonstrated that credit risk is affected by both micro and macroeconomic factors. The paper also addresses significant policy implications as it helps various stakeholders to examine the determinants of credit risk, make credit decisions, and ultimately lower their credit risk. Tisa Maria Antony, Suresh G., 2023. -
Intelligence in Children Whose Either Parent Is Treated For Schizophrenia.
G.J.B.A.H.S.,Vol.2(4):119-123- October- December ISSN: 2319-5584 -
Social media addiction, culture code and mediation effect of mindfulness: A structural equation modelling access
This study has been initiated with a view to understand the social media addiction and its influence on culture codes a mediation effect of mindfulness. The social media addiction would be a very common problem in the social and the organizational set up. The employees are getting distracted easily because of social media addiction. The organisations are taking much action to rectify this problem but end up with the talent lose because the employees are ready to quit the job when they are not allowed to use social media in the organisation. It has been an inevitable problem for the organisations so many techniques have been initiated in order to solve this problem. Many studies are concentrating on mindfulness which is a tool to remove the distractions and to be a focused employee in the organisation. The social media addiction many a times create a toxic culture among the employees. It needs a high attention to be cured. The employee relationship are highly under stake when they are social media addict. This study would attempt to understand the empirical evidence on this relationship by examining the association among addiction in social media and its effect on culture code and mediating role of mindfulness. This study also concentrates on the moderating role of gender on the proposed model. BEIESP. -
The Effectiveness of Micro Finance Institutions on Socio-Economic Development of Women in Karnataka
International Journal of Research in Commerce, Economics & Management, Vol-2 (11), pp. 74-77. ISSN-2231-4245 -
Identification of new classical Ae stars in the Galaxy using LAMOST DR5
We report the first systematic study to identify and characterize a sample of classical Ae stars in the Galaxy. The spectra of these stars were retrieved from the A-star catalogue using the Large sky Area Multi-Object fibre Spectroscopic Telescope (LAMOST) survey. We identified the emission-line stars in this catalogue from which 159 are confirmed as classical Ae stars. This increases the sample of known classical Ae stars by about nine times from the previously identified 21 stars. The evolutionary phase of classical Ae stars in this study is confirmed from the relatively small mid- and far-infrared excess and from their location in the optical colour-magnitude diagram. We estimated the spectral type using MILES spectral templates and identified classical Ae stars beyond A3, for the first time. The prominent emission lines in the spectra within the wavelength range 3700-9000 are identified and compared with the features present in classical Be stars. The H ? emission strength of the stars in our sample show a steady decrease from late-B type to Ae stars, suggesting that the disc size may be dependent on the spectral type. Interestingly, we noticed emission lines of Fe ii, O i, and Paschen series in the spectrum of some classical Ae stars. These lines are supposed to fade out by late B-type and should not be present in Ae stars. Further studies, including spectra with better resolution, is needed to correlate these results with the rotation rates of classical Ae stars. 2021 2020 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Analysis of nonlinear convection and diffusion in viscoelastic fluid flow with variable thermal conductivity and thermal radiations
The study offers a thorough evaluation of the complex fluid dynamics and heat transfer phenomena in Williamson viscoelastic fluid flow, taking into account thermal radiations and variable thermal conductivity. The paper extends its analysis to include heat transfer effects, which are critical in several engineering and industrial applications, and digs into the complexity of non-Newtonian fluid behavior, with a special focus on thermal radiation, heat production, diffusion and viscous dissipation. The study makes use of mathematical models and numerical method RK4 to clarify the nonlinear interactions between convection and diffusion processes in this viscoelastic fluid. The energy and concentration equations are simulated in the presence of the modified Fourier and Fick laws. Moreover, the predicted heat flow is based on the Cattaneo-Christov theory. This research also sheds light on the interaction between rheological properties and thermal characteristics, providing important new knowledge to the broader field of fluid dynamics and heat transfer. 2024 World Scientific Publishing Company. -
Clay-based cementitious nanofluid flow subjected to Newtonian heating
In recent years, a novel technique for producing robust cementitious materials, called nanocomposites, has emerged. These materials are comprised of clay minerals and polymers. As a result, a vertical flat plate has been used to evaluate a clay-based cementitious nanofluid in this research. The impacts of first-order chemical reactions, heat generation/heat absorption, and the Jeffrey fluid model are taken into account for the study of flow. Newtonian heating and the conditions for slippage velocity have also been considered. The mathematical problem for the flow analysis has been established in relations of partially coupled partial differential equations and the model has been generalized using constant proportional Caputo (CPC) fractional derivative. The problem is solved using the Laplace transform technique to provide precise analytical solutions. On the concentration, temperature, and velocity fields, the physics of a number of crucial flow parameters have been examined graphically. The acquired results have been condensed to a very well-known published work to verify the validity of the current work. It is important to note here that the rate of heat transfer in the fluid decreases by 10.17% by adding clay nanoparticles, while the rate of mass transfer decrease by 1.31% when the value of ? reaches 0.04. 2023 World Scientific Publishing Company. -
MHD nanofluid flow through Darcy medium with thermal radiation and heat source
In this analysis, we have considered heat transmission in two-dimensional steady laminar nanouid ow past a wedge. Magnetohydrodynamic (MHD), Brownian motion, viscous dissipation and thermophoresis eects are considered over the porous surface. Similarity transformations have been used to change the governing partial dierential equations (PDEs) into nonlinear higher-order ordinary dierential equations (ODEs). Governing ODEs with boundary conditions are then converted to the system of first-order initial value problem. After that the modeled system is solved numerically by RK4 technique. Impact of the magnetic number, Eckert number, Prandtl number, Lewis number, Brownian motion, thermophoresis and permeability parameters on the ow domain is analyzed graphically as well as in tabular form. It is noted that magnitude of Nusselt number for the ow regime increases with the increase of nondimensional parameter Pr; Nb; Nt while opposite behavior is observed in case of R. World Scientific Publishing Company. -
Heat Convection in a Viscoelastic Nanofluid Flow: A Memory DescriptiveModel
Modeling of physical phenomena with fractional differential equations is as old as modeling with ordinary differential equations. There are two stages in modeling of a memory process. One of them is short with persistent impact and other is usually governed by fractional mathematical model. It is established that fractional models fit the experimental data for the memory phenomena in better way when compared with the ordinary models, particularly in mechanics, psychology and in biology. Fractional model of viscoelastic nanofluid flow through permeable medium is studied in this communication. Convection parameters in the flow domain are used to account for buoyancy forces. The governing flow equations are computed using a numerical algorithm that combines finite difference and finite element techniques. The governing models friction coefficient, Sherwood numbers, and Nusselt numbers are calculated. Change in noninteger numbers behave similarly in concentration, temperature, and velocity fields, according to simulations. It is also noted that heat flux, ?1 and mass flux, ?2 numbers have contradictory effects on friction coefficient. Various flow patterns, particularly in the polymer industry and electrospinning for nanofiber manufacture, can be addressed in a similar manner 2023 L&H Scientific Publishing, LLC. All rights reserved -
Cloud security based attack detection using transductive learning integrated with Hidden Markov Model
In recent years, organizations and enterprises put huge attention on their network security. The attackers were able to influence vulnerabilities for the configuration of the network through the network. Zero-day (0-day) is defined as vulnerable software or application that is either defined by the vendor or not patched by any vendor of organization. When zero-day attack is identified within the network there is no proper mechanism when observed. To mitigate challenges related to the zero-day attack, this paper presented HMM_TDL, a deep learning model for detection and prevention of attack in the cloud platform. The presented model is carried out in three phases like at first, Hidden Markov Model (HMM) is incorporated for the detection of attacks. With the derived HMM model, hyper alerts are transmitted to the database for attack prevention. In the second stage, a transductive deep learning model with k-medoids clustering is adopted for attack identification. With k-medoids clustering, soft labels are assigned for attack and data and update to the database. In the last phase, with computed HMM_TDL database is updated with computed trust value for attack prevention within the cloud. 2022 -
Understanding the social identity of adolescents in the Indigenous Kodava Community of India
The social identity development of adolescents in marginalized communities across the globe holds paramount significance in determining the overall well-being of its future population. Focusing on one such community, the Kodavas, an Indigenous community in South India, this study aims to understand the shifting configurations of social identity based on the changing sociocultural structure and its implications on identity perception among the adolescents belonging to the Kodava community in Kodagu district in Karnataka, India. This study used a qualitative research design to develop an analytical framework of social identity formation and its transitions in the context of the Kodavas. Data were collected from 188 adolescents (47% boys, 53% girls) between 13 and 17 years (M age = 15 years), in the form of essay writing. The findings based on thematic analysis highlight the core traditional elements of Kodava identity, factors influencing the transition in identity, and its reflection in the contemporary period. 2024 Society for Research on Adolescence. -
The behaviour of macro and micro economic variables and the impact on systematic risk of non-banking finance companies
The reforms initiated by the Government of India during 1990s have brought fundamental changes in the structure and functioning of Banking and Non-Banking Institutions, their business models and the products and services offered by them. Global economic developments have altered the macro economic conditions of the respective nations and make the nations and their economies vulnerable to economic shocks in the form of systematic risk associated with their business activities. Macro-economic factors and micro economic factors have had effect on the risk level, assessing risk, measuring and managing risk has become paramount for Non-Banking financial Institutions. Individual influence of factors on the systematic risk as there is weak relationship with Beta but combined effect of factors is very positive on the systematic risk of the companies. Indian Institute of Finance.