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Association Between Emotional Intelligence and Marital Quality of Married Couples
International Journal of Physical and Social Sciences, Vol-2 (12), pp. 222-235. ISSN-2249-5894 -
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Assumptions of complete rationality and complete information in economics: A critique /
Economists conceived the discipline of economics to be a science of social relations. In fact they believed that social relations between individuals are moderated and regulated. The Physiocratic, Classical and Neo - classical school which firmly believed in human liberty considered this moderation to be a matter of self regulation1 and also that the laws controlling human association to be as clear as the laws of geometry. Contrary to this economists belonging to the utopian common wealth, and the Marxists school believed the same can be dealt out only through social control by the state.2 Irrespective of ones allegiance to any school of economic thought, human behaviour is central to the study of economics and to its place in knowledge structures as a social science. -
AstroSat's view of 4U 1735-44: spectral, temporal, and type I X-ray burst studies
This study utilizes the simultaneous broad-band observations of 4U 1735-44 from AstroSat, offering enhanced spectral and temporal resolution, to investigate its spectral properties, temporal behaviour, and burst characteristics. Spectral, type I X-ray burst, and temporal analyses on 4U 1735-44 were performed using AstroSat/Soft X-ray Telescope and Large Area X-ray Proportional Counter (LAXPC) observations. The hardness-intensity diagram from LAXPC-20 showed a positive correlation between hardness and intensity, with a pattern resembling the banana branch typical of atoll sources. Spectral analysis carried out in the 0.7-20.0 keV energy range, using the model combination - (), suggested a cool accretion disc truncated at a large distance from the neutron star in the system. Time-resolved spectral studies of two type I X-ray bursts detected from the source revealed evidence of photospheric radius expansion, allowing for an estimation of the source distance. Temporal analysis showed the presence of low-frequency quasi-periodic oscillation at 69 Hz (3.3 significance with more than 99 per cent confidence) and prominent noise features below 30 Hz. 2024 The Author(s). -
Asymmetric dynamic conditional copula correlation and fundamental determinants of interest rate comovement
We study time-varying interest rate comovement and its determinants for the retail banking sector in the euro area over pre-crisis and during crisis, between 2003 and 2018. The analysis is conducted for 11 euro area countries, each classified as either core or periphery. Copula Asymmetric DCC-GARCH is estimated for each country-pair to measure the dynamic interest rate correlations for deposits and loans to households. We then examine the determinants by regressing quarterly correlations on macroeconomic and cross-border linkages, banking, and sociological variables. We also assess the impact of the two crises and of policy initiatives, including negative interest rate, Single Supervisory Mechanism, and Single Regulatory Mechanism. Different panel regressions reveal limited, although varied, influence of determinants on correlations across different products, maturities, and country groups. We conclude that the intrinsic features of the retail banking industry, such as customers' trust, information asymmetry, and political influence, hinder strong interest rate convergence in the euro area. 2019-Center for Economic Integration, Sejong Institution, Sejong University, All Rights Reserved. -
Asymmetric dynamic conditional copula correlation and fundamental determinants of interest rate comovement /
Journal of Economic Integration, Vol.34, Issue 4, pp.667-704, ISSN No: 1225-651X. -
Asynchronous Method of Oracle: A Cost-Effective and Reliable Model for Cloud Migration Using Incremental Backups
Cloud Computing has reached a new level in flexibility to provide infrastructure. The proper migration method should be chosen for better cost management and to avoid overpayments to unused resources. So, the migrations from On-Premises to cloud infrastructure is a challenge. The migration can be done in synchronous or asynchronous modes. The synchronous method is mostly used to minimize downtime while doing the cloud migrations. The asynchronous methods can do the migrations in offline mode and very consistently. This paper addresses various issues related to the synchronous mode of Oracle while doing highly transactional database migrations. The proposed methodology provides a solution with a combination of asynchronous and incremental backups for highly transactional databases. This proposed method will be a more cost-effective and reliable model without compromising consistency and integrity. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
At the Interface of Colonial Knowing and Unknowing: A Critical Reading of the Golden Camellia in Amitav Ghoshs River of Smoke
This paper is a critical reading of Amitav Ghoshs fictional representation of modes of acquisition, assimilation and dissemination of colonial knowledge in River of Smoke (2012). The paper highlights the cultural exchange of botanical and horticultural knowledge between Europe and China in the nineteenth century narrativized by Ghosh. The novel illustrates the significance of non-Eurocentric modes of conserving knowledge that would otherwise suffer from the violence of utilitarian models of European epistemology. The paper explicates how Ghosh represents the Chinese as successful in ensuring that the Golden Camelliaa rare flowering variety in Chinais preserved from falling prey to the profiteering logic of botanical expeditions and epistemic hegemony by European naturalists. Using Pramod Nayars imperial cosmopolitanism and Robert Proctors agnotology as critical frames, the paper maps Ghoshs fictional representation of Chinese horticulturists using botanical illustration to disable Europeans from accessing the Golden Camellia. By circulating the nonexistence of the plant variety as the truth, the Chinese horticulturalists in the novel prevent the Golden Camellia from being usurped and profiteered by European botanists and plant traders. The paper also establishes how Ghoshs work functions as a significant addition to works foregrounding the South-South connection in the South Asian literary imagination. 2020 South Asian Literary Association. -
Atendo: The portable attendence recorder /
Patent Number: 202241019881, Applicant: Kevin Benny.
Attendance is the fact of being present or absent at a place or an event. One of the most basic things to understand and analyse the response of an event is by recording the attendance of the event. By tracking the sessions attended by the attendees and how long the attendees stay in the event, it is possible to derive a clear picture of how engaged the event was. Attendance monitoring is very important for examining the success or failure of an event. Tracking session attendance is an easy and accurate way to gather attendee feedback and translate this information into useful data. -
Atendo: The portable attendence recorder /
Patent Number: 202241019881, Applicant: Kevin Benny.
Attendance is the fact of being present or absent at a place or an event. One of the most basic things to understand and analyse the response of an event is by recording the attendance of the event. By tracking the sessions attended by the attendees and how long the attendees stay in the event, it is possible to derive a clear picture of how engaged the event was. Attendance monitoring is very important for examining the success or failure of an event. Tracking session attendance is an easy and accurate way to gather attendee feedback and translate this information into useful data. -
Atendo: The portable attendence recorder /
Patent Number: 202241019881, Applicant: Kevin Benny.
Attendance is the fact of being present or absent at a place or an event. One of the most basic things to understand and analyse the response of an event is by recording the attendance of the event. By tracking the sessions attended by the attendees and how long the attendees stay in the event, it is possible to derive a clear picture of how engaged the event was. Attendance monitoring is very important for examining the success or failure of an event. Tracking session attendance is an easy and accurate way to gather attendee feedback and translate this information into useful data. -
Atman's awakening: Bhagavad Gita's Path to Moksha through Karma Yoga and Atmabodha
Indian psychology is characterized by its diverse and rich traditions that have evolved over several centuries. This chapter tries to fulfill four objectives: 1) To provide a brief overview of the concept of self in Bhagavad Gita; 2) to give a brief overview of the two frameworks for moksha given in the Bhagavad Gita with the help of empirical evidence of current research; 3) to propose a conceptual model using Triguna Framework and Trimarg Framework; and 4) to provide the implications of the proposed model. The chapter begins with an explanation of the Indian philosophical understanding of self from the lens of Bhagavad Gita. In the second section, an effort has been made to compare and contrast the two frameworks given in Bhagavad Gita for Moksha. The last section introduces a conceptual model to enhance sattva guna and reduce the rajas and tamas gunas to attain atmabodha that can have positive psychological implications in modern times. 2024, IGI Global. All rights reserved. -
ATRSI: Automatic Tag Recommendation for Videos Encompassing Semantic Intelligence
There is a requirement for an automatic semantic-oriented framework for Web video tagging in the epoch of Web 3.0, as Web 3.0 is much denser, intelligent, but more cohesive compared to Web 2.0. This paper proposes the ATRSI framework which is the Automatic Tag Recommender framework which encompasses the semantic-oriented Artificial Intelligence that outgrows the dataset by making the use of informative terms using TF-IDF and bag of words model to build the intermediate semantic network which is further organized using an Lin similarity measure and is optimized using red deer optimization by encompassing the entities from the World Wide Web to focused crawling. RNN is a classifier that is used for the classification of the dataset, it is a strong deep-learning classifier. Semantic-oriented Intelligence is achieved using the CoSim rank and Morisita's overlap index. The bag of lightweight graphs is obtained from the semantic network which is an intermediate knowledge representation mechanism that is further embedded in the intrinsic model. A semantically consistent system for video recommendation, ATRSI outperforms the other baseline models in terms of average accuracy, average precision and F-measure for a variety of recommendations. 2024 IEEE. -
Attachment to God: Narratives of Roman Catholic Priests
This narrative analysis was aimed at exploring the attachment to God narratives of 28 middle-aged Roman Catholic Religious priests rendering their service in various settings in South India. The study found that majority of the Roman Catholic priests had developed representations of a secure attachment to God. Twenty-six priests had developed representations of a secure attachment to God, and two priests of an insecure attachment to God. The Majority of the Roman Catholic priests had developed representations of a secure attachment to more than one spiritual attachment figures. Along with God, most priests had also developed representations of a secure attachment to the Virgin Mary. All the major themes related to attachment to God were found in the narratives of the Roman Catholic Priests. Author(s) 2020. -
Attention Based Meta-Module to Integrate Cervigrams with Clinical Data for Cervical Cancer Identification
Cervical cancer remains a significant burden on public health, particularly in developing countries, where its malignancy and mortality rates are alarmingly high. Early diagnosis stands as a pivotal factor in effectively treating and potentially curing the cervical cancer. This study introduces a novel approach of meta module based on recurrent gate architecture designed to enhance the classification of cervix images efficiently. This innovative framework incorporates a meta module capable of dynamically selecting image modalities most pertinent attributes. Furthermore, it integrates clinical data with extracted image features and employs a range of EfficientNet architectures (B0-B5) for image classification. Our results indicate that the EfficientNet B5 architecture outperforms its counterparts, achieving an AUC (Area Under the Curve) score of 55.1 and an F1-Score of 75.1. Overall, this work represents a crucial step towards improving the early detection of cervical cancer, which in turn can lead to more effective treatment strategies and, ultimately, better outcomes for patients worldwide. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Attention based sentence classification using term frequency-inverse document frequency and n-gram /
Patent Number: 202241048840, Applicant: Nagendra N.
Attention Based Sentence Classification Using Term Frequency-Inverse Document Frequency and N-Gram On an e-commerce platform, products sold have critical and varying reviews from buyers which are difficult to analyze considering the hugenumber of reviews. The proposed model aspect extraction helps in categorizing sentence accurately. -
Attention to Economic Factors and Its Response to Foreign Portfolio Investment: An Evidence from Indian Capital Market
Stock market consists of a variety of investors. Among these, Foreign Portfolio Investors (FPIs) is a key investment influx. These investments can change or fluctuate due to several macroeconomic factors which can cause a shift in the dynamics of the markets in India. This paper examines the factors influencing for foreign portfolio investment in long run as well as short run. The sample comprises of 120 monthly observations on Foreign Portfolio Investment (FPIs) and Macro economic variables such as Oil prices (OP), Gross Domestic Product (GDP), Interest Rate (IR), Exchange rate of Indian Rupee with USD (ER), Inflation (CPI), Nifty Index (NSEI), 10year Bond Prices (BP) and Index of Industrial production (IIP) over a period of 10years, spanning from January 2013 to November 2022. The study employed Autoregressive Distributed Lag model (ARDL) to establish the long run association with error correction models. The result indicates that there is long run association between the Foreign Portfolio Investment and macro-economic variables. Among this, NSEI, IIP and ER played a significant role to determine FPI investments in the long run, whereas in the short run, FPI was impacted by ER and NSEI significantly. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Attenuation parameters of polyvinyl alcohol-tungsten oxide composites at the photon energies 5.895, 6.490, 59.54 and 662 keV
The growing demand for lightweight, non-toxic and effective X-A nd ?-ray shielding materials in various fields has led to the exploration of various polymer composites for shielding applications. In this study, tungsten filled polyvinyl alcohol (PVA) composites of varying WO3 concentrations (0-50 wt%) were prepared by solution cast technique. The structural, morphological, and thermal properties of the prepared composite films were studied using X-ray diffraction technique (XRD), Scanning electron microscopy (SEM) and Thermogravimetric analysis (TGA). The AC conductivity studies showed the low conductivity property of the composites. The X-ray (5.895 and 6.490 keV) and ?-ray (59.54 and 662 keV) attenuation studies performed using CdTe and NaI(Tl) detector spectrometers revealed a noticeable increase in shielding efficiency with increase in filler wt%. The effective atomic number (Zeff) calculated by the direct method agreed with the values obtained using Auto-Zeff software. The % heaviness showed that tungsten filled polyvinyl alcohol composites are lighter than traditional shielding materials. 2020 M V Muthamma et al., published by Sciendo 2020. -
Attenuation properties of epoxy-Ta2O5 and epoxy-Ta2O5-Bi2O3 composites at ?-ray energies 59.54 and 662 keV
Epoxy resin filled with suitable high Z elements can be a potential shield for X-rays and ?-rays. In this work, we present the ?-ray attenuation properties of epoxy composites filled with (030 wt%) Tantalum pentoxide (Ta2O5) and Ta2O5-Bi2O3, which were prepared by open mold cast technique. X-ray diffraction patterns showed crystalline peaks of Ta2O5 and bismuth oxide (Bi2O3) in the prepared epoxy-Ta2O5 and epoxy-Ta2O5-Bi2O3 composites. Homogeneity of the samples at higher filler wt% was revealed by SEM images. Mechanical characterization showed the enhanced mechanical strength of epoxy-Ta2O5-Bi2O3 composites compared to epoxy-Ta2O5. Higher storage modulus and glass transition temperature of the epoxy-Ta2O5-Bi2O3 composites showed enhanced stiffness and thermal stability when compared to neat and epoxy-Ta2O5. Decrease in the value of tan(?) at higher content of filler loadings indicated the good adhesion between filler and matrix. Mass attenuation coefficients of epoxy-Ta2O5 (30 wt%) composites at ?-ray energies 59.54 and 662 keV were found to be 0.876 cm2 g1 and 0.084 cm2 g1, while that of epoxy-Ta2O5-Bi2O3 (30 wt% Bi2O3) composite were 1.271 cm2 g1 and 0.088 cm2 g1, respectively. The epoxy-5% Ta2O5-30% Bi2O3 composites with higher ?/? value and tensile strength may be a potential ?-ray shield in various radiation environments. 2020 Wiley Periodicals, Inc. -
AttGRU-HMSI: enhancing heart disease diagnosis using hybrid deep learning approach
Heart disease is a major global cause of mortality and a major public health problem for a large number of individuals. A major issue raised by regular clinical data analysis is the recognition of cardiovascular illnesses, including heart attacks and coronary artery disease, even though early identification of heart disease can save many lives. Accurate forecasting and decision assistance may be achieved in an effective manner with machine learning (ML). Big Data, or the vast amounts of data generated by the health sector, may assist models used to make diagnostic choices by revealing hidden information or intricate patterns. This paper uses a hybrid deep learning algorithm to describe a large data analysis and visualization approach for heart disease detection. The proposed approach is intended for use with big data systems, such as Apache Hadoop. An extensive medical data collection is first subjected to an improved k-means clustering (IKC) method to remove outliers, and the remaining class distribution is then balanced using the synthetic minority over-sampling technique (SMOTE). The next step is to forecast the disease using a bio-inspired hybrid mutation-based swarm intelligence (HMSI) with an attention-based gated recurrent unit network (AttGRU) model after recursive feature elimination (RFE) has determined which features are most important. In our implementation, we compare four machine learning algorithms: SAE + ANN (sparse autoencoder + artificial neural network), LR (logistic regression), KNN (K-nearest neighbour), and nae Bayes. The experiment results indicate that a 95.42% accuracy rate for the hybrid model's suggested heart disease prediction is attained, which effectively outperforms and overcomes the prescribed research gap in mentioned related work. The Author(s) 2024.