Browse Items (5511 total)
Sort by:
-
Towards an Epistemology of Reading: Defining the Process of Reading in Modern Terms
The chaotic space caused by information explosion in present times has made the process and purpose of reading to be always questioned. Technological advancement has made reading appear as a mere mockery at the very outset. But the world still prioritizes knowledge that is acquired through observation, valuation and interpretation. At the time of Big Data, there still persists a sense of agency to define a given information as episteme. The present essay emphasizes on looking at reading as a modern phenomenon by presupposing the epistemological presence at the centre of any rational pursuit. Based on the Kantian precepts on enlightenment, the paper attempts to understand this presence of knowledge by delving into the major disciplines of modern philosophy that help in observing, valuing and interpreting the act of reading in present times. More than laying terms for defining the text within the modern space, the study essentializes reading in a virtually driven algorithmic world. AesthetixMS 2021 -
Towards Automated and Optimized Security Orchestration in Cloud SLA
In cloud computing, providers pool their resources and make them available to customers. Next-generation computer scientists are flocking to the cutting-edge field of cloud computing for their research and exploration of uncharted territory. There are still several barriers that cloud service providers must overcome in order to provide cloud services in accordance with service level agreements. Each cloud service provider aspires to achieve maximum performance as per Service Level Agreements (SLAs), and this is especially true when it comes to the delivery of services. A cloud service level agreement (SLA) guarantees that cloud service providers will satisfy the needs of large businesses and offer their clients with a specified list of services. The authors offer a web service level agreementinspired approach for cloud service agreements. We adopt patterns and antipatterns to symbolize the best and worst practices of OCCI (Open Cloud Computing Interface Standard), REST (Representational State Transfer), and TOSCA (Topology and Orchestration Specification for Cloud Applications) with DevOps solutions, all of which API developers should bear in mind when designing APIs. When using this method, everything pertaining to the cloud service, from creation to deployment to measurement to evaluation to management to termination, may be handled mechanically. When distributing resources to cloud apps, our system takes into account the likelihood of SLA breaches and responds by providing more resources if necessary. We say that for optimal performance, our suggested solution should be used in a private cloud computing setting. As more and more people rely on cloud computing for their day-to-day workloads, there has been a corresponding rise in the need for efficient orchestration and management strategies that foster interoperability. 2023 International Journal on Recent and Innovation Trends in Computing and Communication. All rights reserved. -
Towards developing an automated technique for glaucomatous image classification and diagnosis (AT-GICD) using neural networks
Glaucoma is the eye defect that has become the second leading cause of blindness worldwide and also stated as incurable, may cause complete vision loss. The earlier diagnosis of glaucoma in Human Eye is a great confrontation and very important in present scenario, for providing efficient and appropriate treatments to the persons. Though there is much advancement in Ocular Imaging that affords methods for earlier detection, the appropriate results can be obtained by integrating the data from structural and functional evaluations. With that note, this paper involves in developing automated technique for glaucomatous image classification and diagnosis (AT-GICD). The model considers both the textural and energy features for effectively diagnosing the defect. Image Segmentation is processed for obtaining the exact area of optic nerve head; histogram gradient based conversion is employed for enhancing the fundus image features. Further, Wavelet Energy features are extracted and applied to the artificial neural networks (ANN) for classifying the NORMAL and GLAUCOMA images. The Accuracy rate based comparison with other existing models is carried out for evidencing the effectiveness of the proposed model in glaucomatous image classification. 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management. -
Towards sustainable resource management: A short and long-run dynamics of mineral production on ecological footprint
The effect of mineral production on ecological footprint is examined in this study while controlling for economic growth, renewable energy consumption, and trade openness as additional determinants for Pakistan. On the empirical front, the study uses the Dynamic Autoregressive Distributed Lag (DYNARDL) simulations for the data collected between 1990 and 2021. The result portrays movement to the long-run equilibrium relationship when considering the ecological footprint as the outcome variable amidst mineral production, economic growth, renewable energy consumption, and trade openness as the covariates. Further, the finding shows temporal dynamics of mineral production on environmental quality with a short-term degradation versus long-term amelioration, which suggests that mineral production can be conducted more sustainably over time with an implication towards taking measures such as technological advancements, improved efficiency, and better waste management practices. Additionally, it failed to find evidence for the conventional Environmental Kuznets Curve, implying a need for policy reevaluation, reassessment of economic development models and accounting for environmental externalities in economic decision-making. Besides, as expected, the outcome demonstrates that using renewable energy lowers the ecological footprint both in long and short terms, which indicates that utilization of renewable energy sources reduces reliance on fossil fuels, resulting in decreased environmental degradation, thereby fostering the need for emphasis on the importance of continued technological innovation in renewable energy technologies to reduce the ecological footprint further. Moreover, it shows that trade openness improves the environmental quality in the short run (worsens it in the long run), thereby highlighting that trade openness may lead to short-term environmental benefits by promoting cleaner technologies and increasing resource efficiency. However, in the long term, trade openness can exacerbate environmental degradation due to economic priorities often taking precedence over environmental concerns. 2024 Elsevier Ltd -
Towards Visibility: Subaltern Counterpublics in Paul Chirakkarodes Pulayathara
Christianity has always been celebrated as a catalyst towards modernity for the Dalits of Kerala. Though missionary accounts and ethnographic studies confirm the progress of the community, there was rampant casteism and separatism too. This is succinctly revealed in Dalit Christian texts. Pulayathara by Paul Chirakkarode stands as a testimony to the Dalit Christian dilemma and traces the history of the Kuttanadan Pulaya community in the pre- and post-conversion scenarios. Conversions could not change the existing public sphere of Kerala, where upper castes were the dominant party. They (Dalits) continued to be marginalized and subordinated and lacked a class consciousness. The article highlights the limitations in the public sphere that emerged in Kerala as part of the missionary endeavours in accommodating the converted Dalits. The article attempts to trace the emergence of subaltern counterpublics among the Dalit Christians to oppose the continued oppression and casteism by situating Pulayathara at the centre of the analysis. 2022 Indian Institute of Management, Ahmedabad. -
Toxic heavy metal ion detection by fluorescent nanocarbon sensor derived from a medicinal plant
In the twenty-first century, the importance of environmental pollution sensing cannot be overstated. Cadmium is a well-known poisonous heavy metal that seriously endangers human health. In terms of screening for poisons and diagnosing illnesses, the sensitive and focused detection of cadmium in cells is crucial. In this work, we developed Green fluorescent Carbon nanomaterial (Carbon nanomaterial) synthesized from a novel precursor, Justicia Wynaadensis, by the most eco-friendly, cost-effective hydrothermal method, which acts as a fluorescent probe for Cadmium fluorescence sensing technique with the concentration range of 1 nM1 M. The sensor displays remarkable linear detection with a 5.235 nM detection limit. 2022 The Author(s) -
Toxic waste colonialism : A re-evaluation of global management of transboundary hazardous waste /
Journal On Environment Law Policy And Development, Vol.3, pp.85-119, ISSN: 2348-7046. -
Toxicity analysis of endocrine disrupting pesticides on non-target organisms: A critical analysis on toxicity mechanisms
Endocrine disrupting compounds are the chemicals which mimics the natural endocrine hormones and bind to the receptors made for the hormones. Upon binding they activate the cascade of reaction which leads to permanent activating of the signalling cycle and ultimately leads to uncontrolled growth. Pesticides are one of the endocrine disrupting chemicals which cause cancer, congenital birth defects, and reproductive defects in non-target organisms. Non-target organisms are keen on exposing to these pesticides. Although several studies have reported about the pesticide toxicity. But a critical analysis of pesticide toxicity and its role as endocrine disruptor is lacking. Therefore, the presented review literature is an endeavour to understand the role of the pesticides as endocrine disruptors. In addition, it discusses about the endocrine disruption, neurological disruption, genotoxicity, and ROS induced pesticide toxicity. Moreover, biochemical mechanisms of pesticide toxicity on non-target organisms have been presented. An insight on the chlorpyrifos toxicity on non-target organisms along with species names have been presented. 2023 Elsevier Inc. -
Toxicological Profiling of Onion-Peel-Derived Mesoporous Carbon Nanospheres Using In Vivo Drosophila melanogaster Model
Toxicological profiling of the novel carbon materials has become imperative, owing to their wide applicability and potential health risks on exposure. In the current study, the toxicity of mesoporous carbon nanospheres synthesized from waste onion peel was investigated using the genetic animal model Drosophila melanogaster. The survival assays at different doses of carbon nanoparticles suggested their non-toxic effect for exposure for 25 days. Developmental and behavioral defects were not observed. The biochemical and metabolic parameters, such as total antioxidant capacity (TAC), protein level, triglyceride level, and glucose, were not significantly altered. The neurological toxicity as analyzed using acetylcholinesterase activity was also not altered significantly. Survival, behavior, and biochemical assays suggested that oral feeding of mesoporous carbon nanoparticles for 25 days did not elicit any significant toxicity effect in Drosophila melanogaster. Thus, mesoporous carbon nanoparticles synthesized from waste onion peel can be used as beneficial drug carriers in different disease models. 2022 by the authors. Licensee MDPI, Basel, Switzerland. -
Tracing the outer disk of NGC300: An ultraviolet view
We present an ultra-violet (UV) study of the galaxy NGC300 using GALEX far-UV (FUV) and near-UV (NUV) observations. We studied the nature of UV emission in the galaxy and correlated it with optical, HI and mid-infrared (3.6 ?m) wavelengths. Our study identified extended features in the outer disk, with the UV disk extending up to a radius of 12 kpc (> 2 R25). We estimated the FUV and NUV disk scale-length as 3.05 0.27 kpc and 2.66 0.20 kpc respectively. The scale-length in FUV is 2.3 times larger than that at 3.6 ?m, and we also find the disk to gradually become flatter from longer to shorter wavelengths. We performed a statistical source subtraction to eliminate the background contaminants and identified 261 unresolved UV sources between the radii 5.3 kpc and 10 kpc (1 ? 2 R25). The identified UV sources show an age range between 1300 Myr with a peak at 25 Myr and a mass range between 10 3M? to 10 6M?, estimated using Starburst99 models. The north-eastern spiral arm is found to be populated by young low mass sources suggesting that the star formation in this spiral arm is a recent phenomenon. The UV emission beyond the R25 radius has contribution from these low mass sources and is extended up to ? 2 R25 radius. We conclude that NGC300 has an extended UV disk, mainly populated by young low mass sources. The star formation rate is measured to be ?0.46M?/yr which is comparable to its near optical twin M33. 2019, Indian Academy of Sciences. -
Tracking Greenfield FDI During the COVID-19 Pandemic: Analysis by Sectors
We study the trends and fluctuations in greenfield foreign direct investment (GFDI) during the first wave of the COVID-19 pandemic crisis on a global scale. We analyse the data of a data set of GFDI provided by fDi Markets (Financial Times) to understand the contraction of GFDI during the first three quarters of the year 2020, taking into account the sector of the investment and the host and home country. We analyse both the long-run trends and the quarter-over-quarter changes in GFDI to capture its fluctuations before and during the first wave of the COVID-19 crisis and the 2008 global financial crisis. Our findings cast light on which countries and industries GFDIs were most affected by the pandemic crisis and draw a comparison to the global financial crisis. To our surprise, many services industries have shown unexpected resilience of GFDI due to the flexibility for remote work. On the contrary, GFDI in the manufacturing industries, as well as the extractives and the utility industries, has shown a dramatic decline during the pandemic. These contractions raise questions of stability and resilience of the global supply chains these industries are a part of. JEL Codes: F21. 2021 Indian Institute of Foreign Trade. -
Tracking the transmission channels of fiscal deficit and food inflation linkages: A structural var approach
This empirical analysis aspired to unearth the transmission channels of fiscal deficit and food inflation linkages in the Indian perspective by reasonably exerting the data for 1991 to 2017. The precise results of structural vector autoregressive (SVAR) analysis proffered that there were three different mechanisms of transmission such as consumption, general inflation, and import channels that led to food inflation in response to the high fiscal deficit. The first channel revealed that government deficit spending had a positive impact on income which further led to food inflation through surging the household consumption expenditure. It was concluded that fiscal deficit passed through general inflation finally leading to a food price surge in the economy and seemed to work as cost-push inflation for the food and agricultural industry. The outcome also revealed that the impact of fiscal deficit passed to food inflation through external linkages such as import and export. 2020 The Society of Economics and Development, except certain content provided by third parties. -
Trade in Pollution-intensive Products: Evidence from India
This article explains Indias trade from an environmental perspective. Besides explaining trends and patterns of trade in pollution-intensive products, we investigate Indias comparative advantage in these products and discuss the emerging issues. The exercise based on the UN Comtrade dataset reveals that much of Indias exports happen under this category with better revealed comparative advantage (RCA) values, which do have high environmental concerns. We sum up the article by arguing that there is a need to attend to sector-specific problems encountered by these industries and have a well-knit environmental policy, so that trade and industrial expansion do not have a major environmental concern. 2022 Management Development Institute. -
Trade Integration and Export Aspiration: Evidence from India's Trade in Goods with BRICS Countries
The purpose of this study was to examine the dynamics of trade between India and the BRICS countries as well as to gauge the relative strength of Indian exports to those nations. The trade integration patterns among BRICS countries were also analyzed. To quantify the extent to which India's exports correspond to the needs of its BRICS counterparts, a novel export aspiration index was constructed. The index of trade integration patterns has also been employed to quantify India's trade integration pattern with other BRICS members. Further, the gravity model of trade has been employed to analyze the fundamentals of India-BRICS trade. The export aspiration in individual BRICS countries shows a diverse pattern. However, India's export aspiration in these countries has improved, although marginally in the long run. Such empirical evidence substantiates that the relative strength of India's exports within its BRICS counterparts has marginally improved over time. Moreover, the trade integration index indicates a similar trade integration pattern among the BRICS countries and corroborates the presence of inter-industry trade. Added to the conventional variables of the gravity model, India's outward multilateral trade resistance and BRICS inward multilateral trade resistance significantly promote India-BRICS trade. Hence, the relative strength of Indian exports will increase substantially if India's commodity composition is diversified by including more commodities in its export baskets that correspond to the needs and changing conditions of the BRICS economies. Copyright 2022 Mudaser Ahad Bhat, Aamir Jamal, Mirza Nazrana Beg. -
Training in Cultural Competence for Mental Health Care: A Mixed-Methods Study of Students, Faculty, and Practitioners from India and USA
Although the need to train clinicians to provide effective mental health care to individuals from diverse backgrounds has been recognized worldwide, a bulk of what we know about training in cultural competence (CC) is based on research conducted in the United States. Research on CC in mental health training from different world populations is needed due to the context-dependent nature of CC. Focusing on India and USA, two diverse countries that provide complementary contexts to examine CC, we explored graduate students, practicing clinicians, and faculty members perspectives regarding CCtraining they received/provided and future training needs using mixed-methods. The data were collected using focus groups (n = 25 groups total: 15 in India, 11 in USA), and a survey (n = 800: 450 in India, 350 in USA). Our data highlight the salient social identities in these countries, and the corresponding constituents of CC training. Participants in India described a practical emphasis to their CC training (e.g., learning about CC through life experiences and clinical practice experiences) more so than through coursework, whereas participants in USA described varying levels of courseworkrelated toCC along with practice. Participants in both countries considered enormity of CC as a challenge, while those in the US also identified CC training limited to a white, straight, male perspective, hesitancy in engaging with diversity topics, and limited time and competence of the faculty. Strengths of CC training in India and USA are mutually informative in generating recommendations for enhancing the training in both countries. The Author(s) 2024. -
Training multi-layer perceptron with enhanced brain storm optimization metaheuristics
In the domain of artificial neural networks, the learning process represents one of the most challenging tasks. Since the classification accuracy highly depends on the weights and biases, it is crucial to find its optimal or suboptimal values for the problem at hand. However, to a very large search space, it is very difficult to find the proper values of connection weights and biases. Employing traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local optima. Most commonly, back-propagation is used for multi-layer-perceptron training and it can lead to vanishing gradient issue. As an alternative approach, stochastic optimization algorithms, such as nature-inspired metaheuristics are more reliable for complex optimization tax, such as finding the proper values of weights and biases for neural network training. In this work, we propose an enhanced brain storm optimization-based algorithm for training neural networks. In the simulations, ten binary classification benchmark datasets with different difficulty levels are used to evaluate the efficiency of the proposed enhanced brain storm optimization algorithm. The results show that the proposed approach is very promising in this domain and it achieved better results than other state-of-the-art approaches on the majority of datasets in terms of classification accuracy and convergence speed, due to the capability of balancing the intensification and diversification and avoiding the local minima. The proposed approach obtained the best accuracy on eight out of ten observed dataset, outperforming all other algorithms by 1-2% on average. When mean accuracy is observed, the proposed algorithm dominated on nine out of ten datasets. 2022 Tech Science Press. All rights reserved. -
Transfer Learning-Based Osteoporosis Classification Using Simple Radiographs
Osteoporosis is a condition that affects the entire skeletal system, resulting in a decreased density of bone mass and the weakening of bone tissues micro-architecture. This leads to weaker bones that are more susceptible to fractures. Detecting and measuring bone mineral density has always been a critical area of focus for researchers in the diagnosis of bone diseases such as osteoporosis. However, existing algorithms used for osteoporosis diagnosis encounter challenges in obtaining accurate results due to X-ray image noise and variations in bone shapes, especially in low-contrast conditions. Therefore, the development of efficient algorithms that can mitigate these challenges and improve the accuracy of osteoporosis diagnosis is essential. In this research paper, a comparative analysis was conducted Assessing the accuracy and efficiency of the latest deep learning CNN model, such as VGG16, VGG19, DenseNet121, Resnet50, and InceptionV3 in detecting to Classify Normal and Osteoporosis cases. The study employed 830 X-ray images of the Spine, Hand, Leg, Knee, and Hip, comprising Normal (420) and Osteoporosis (410) cases. Various performance metrics were utilized to evaluate each model. The findings indicate that DenseNet121 exhibited superior performance with an accuracy rate of 93.4% Achieving an error rate of 0.07 and a validation loss of only 0.57 compared with other models considered in this study. 2023, International journal of online and biomedical engineering. All Rights Reserved. -
Transformation of hydrocarbon soot to graphenic carbon nanostructures
Graphenic carbon nanostructures were synthesized from different precursors of petroleum and agricultural origin by oxidative scissoring. In the present study soot, an environmental pollutant is converted to a value-added product by facile synthesis techniques. The physicochemical changes of the nanostructures are investigated by means of XRD, AFM, FTIR, Raman spectroscopy, XPS analyses SEM-EDS and TEM analysis. XRD analysis confirms the formation of few layer oxidized carbon nanostructures with smaller lateral dimensions. Raman spectra reveal the existence of graphenic layer with a fewer defect. AFM and SEM analyses reveal the formation of stacked tiny fragments of graphenic carbon lamellae. XPS and IR analyses confirm the incorporation of oxygen functionalities into the carbon backbone. 2018 by the authors. -
Transformation of India as investor of outward fdi: A systematic investigation of literature
Besides the economic transformation and industrial up-gradation, Indian enterprises have steadily intensified their overseas investment venture during recent years. A systematic literature review performed to inspect the strategic motives and Outward FDI (OFDI) impact on emerging economies like India. This paper explores relevant theories, strategic rationale, and economic policies that propel the present OFDI trend from India. The effort taken by the Indian government to promote innovations were Cross border commercial and industrial collaboration. These efforts flagged the way for more Outward FDI possibilities in the future (Welch, 1988). This study comprises the literature works till the year 2019, which includes research journals and reports. The analysis observes that knowledge-based industries drive India's Outward FDI and examine whether knowledge-based industries contribute to sustaining long-term domestic and international growth (Pradhan J.P., 2005; Narayanan, 2016). Indian Institute of Finance. -
Transformational educational leaders inspire school educators commitment
Introduction: Transformational school leaders play an important role in promoting educational innovation and restructuring by creating a vision for the future, building a culture of collaboration, and empowering others to become leaders themselves. Through their leadership style, they inspire and motivate others to work towards a common goal, leading to positive change and growth within the educational system. The aim of this study is to measure the impact of transformational leadership on various types of commitment that school teachers have in Bengaluru, India. Methods: A survey was conducted using standardised instruments to measure the leadership style of principals and personal commitment of teachers. The data was collected from 1,173 school teachers through a questionnaire and analysed using SPSS V23 statistical software. Results: The study found that transformational leadership had a significant impact on the different types of commitment that teachers possess in school education. The three domains of commitment - commitment towards the institution, student development, and self-development - were positively influenced by transformational leadership. Discussion: Transformational school leaders play an important role in promoting educational innovation and restructuring by creating a vision for the future, building a culture of collaboration, and empowering others to become leaders themselves. This study provides evidence that transformational leadership has a positive impact on different types of commitment among school teachers in Bengaluru, India. Leaders of school management are advised to take into account the three domains of commitment of their teachers to facilitate organisational learning through more integrative methods. Copyright 2023 Kareem, Patrick, Prabakaran, B, Tantia, M. P. M. and Mukherjee.