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Robust Bidirectional Long Short-Term Memory-Based Class Imbalance Handling in Dyslexia Prediction at its Early Stage
Dyslexia is a neurological condition that presents difficulties and obstacles in learning, particularly in reading. Early diagnosis of dyslexia is crucial for children, as it allows the implementation of appropriate resources and specialized software to enhance their skills. However, the evaluation process can be expensive, time-consuming, and emotionally challenging. In recent years, researchers have turned to machine learning and deep learning techniques to detect dyslexia using datasets obtained from educational and healthcare institutions. Despite the existence of several deep learning models for dyslexia prediction, the problem of handling class imbalance significantly impacts the accuracy of detection. Therefore, this study proposes a robust deep learning model based on a variant of long short-term memory (LSTM) to address this issue. The advantage of Bidirectional LSTM, which has the ability to traverse both forward and backward, improves the pattern of understanding very effectively. Still, the problem of assigning values to the hyper-parameters in BLSTM is the toughest challenge which has to be assigned in a random manner. To overcome this difficulty, the proposed model induced a behavioral model known as Red Fox Optimization algorithm (RFO). Based on the inspiration of red fox searching behavior, this proposed work utilized the local and the global search in assigning and fine-tuning the values of hyper-parameters to handle the class imbalance in dyslexia dataset. The performance evaluation is conducted using two different dyslexia datasets (i.e., dyslexia 12_14 & real-time dataset). The simulation results explore that the proposed robust Bidirectional Long Short-Term Memory accomplishes the highest detection rate with reduced error rate compared to other deep learning models. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
Robust Control of DFIG Based Wind Energy System Using an H? Controller
Wind Energy Conversion System (WECS) using a Doubly Fed Induction Generator (DFIG) is popular due to its control flexibility and higher conversion efficiency, but maintaining the operational stability and optimal efficiency under dynamic wind conditions is still a control challenge. In this paper, a nonlinear mathematical model for a DFIG based WECS was developed from fundamentals and its characteristics near the operating point were studied. A Proportional Integral (PI) controller and a Linear Quadratic Regulator (LQR) controller were designed to control the system and the behavior of the closed-loop system with these controllers was studied. While the designed PI controller failed to ensure stability, the LQR controller was giving stability but an LQR controller is vulnerable to loss of stability under uncertainties due to parameter variations or changes in operating points. A suboptimal H? controller was then synthesized to obtain robust control. The closed-loop system performance of the DFIG system with the proposed controller was found to be stable and superior to PI and LQR controllers in terms of performance. 2021, The Korean Institute of Electrical Engineers. -
Robust Deep Learning Empowered Real Time Object Detection for Unmanned Aerial Vehicles based Surveillance Applications
Surveillance is a major stream of research in the field of Unmanned Aerial Vehicles (UAV), which focuses on the observation of a person, group of people, buildings, infrastructure, etc. With the integration of real time images and video processing approaches such as machine learning, deep learning, and computer vision, the UAV possesses several advantages such as enhanced safety, cheap, rapid response, and effective coverage facility. In this aspect, this study designs robust deep learning based real time object detection (RDL-RTOD) technique for UAV surveillance applications. The proposed RDL-RTOD technique encompasses a two-stage process namely object detection and objects classification. For detecting objects, YOLO-v2 with ResNet-152 technique is used and generates a bounding box for every object. In addition, the classification of detected objects takes place using optimal kernel extreme learning machine (OKELM). In addition, fruit fly optimization (FFO) algorithm is applied for tuning the weight parameter of the KELM model and thereby boosts the classification performance. A series of simulations were carried out on the benchmark dataset and the results are examined under various aspects. The experimental results highlighted the supremacy of the RDL-RTOD technique over the recent approaches in terms of several performance measures. 2022 River Publishers. -
Robust feature selection using rough set-based ant-lion optimizer for data classification
The selection of an algorithm to tackle a certain problem is a vital undertaking that necessitates both time and knowledge. Non-functional needs, such as the size, quality, and nature of the data, must frequently be taken into account. To develop a generalized machine learning model for any domain, the most relevant features must be chosen because noisy and irrelevant characteristics degrade data mining performance. However, the selection of the dominating features is still dependent on the search technique. When there are a high number of input features, stochastic optimization can be applied to the search space. In this research, the authors investigate the ant lion optimization (ALO), a natureinspired algorithm that mimics the hunting process of ant lions and is further stimulated to identify the smallest reducts. They also investigate rough set-based ant lion optimizer for feature selection. The actual results reveal that the ant lion-based rough set reduct selects a better feature subset and classifies them more accurately. 2022 Information Resources Management Association. All rights reserved. -
Rock abrading in South India /
Encyclopedia of Global Archaeology, pp.1-10 -
Role of charged impurities in thermoelectric transport in molybdenum disulfide monolayers
A theoretical study of the electronic properties, namely, electrical conductivity (EC), electronic thermal conductivity (ETC) and thermoelectric power (TEP) in 2D MoS2 monolayers (MLs), over a wide range of temperatures (10 < T < 300 K), is presented employing Boltzmann transport formalism. Considering the electrons to be scattered by screened charged impurities and the acoustic, optical and remote phonons, the transport equation is solved using Ritz iterative method. Numerical calculations of EC, ETC and TEP presented for supported and free-standing MLs with high electron concentrations, as a function of temperature, bring out the relative importance of the various scattering mechanisms operative. The role of CIs, with regard to both concentration and separation from the substrate-ML interface, in determining the properties of supported MLs is demonstrated for the first time. Validity of Wiedemann-Franz law and Mott formula are examined for supported and free standing MLs. Calculations are in consonance with recent experimental data on mobility and TEP of exfoliated SiO2-supported MoS2 ML samples. In the case of TEP it is found that though the diffusion contribution is dominant the inclusion of the drag component, incorporating contributions from all relevant phonon scattering mechanisms, is needed to obtain good agreement with the data. 2017 IOP Publishing Ltd. -
Role of Constructivism Developing Metacognitive Abilities Among Secondary School Students
Research Tracks, Vol-1 (1), pp. 125-128. ISSN-2347-4637 -
Role of corporate innovation and uncertainty in determining corporate investment of the firm: does financial constraint, executive risk preference and firm risk-taking ability play any role
Purpose: This paper aims to investigate the relationship between corporate innovation and the firms corporate investment. Further, the authors begin with the assertion that the relationship between corporate innovation and corporate investment is impacted by significantly a) uncertain periods, b) financial constraint, c) executives risk preference and d) firm risk-taking ability. Design/methodology/approach: This study has considered non-financial listed companies (774 firms) for the period spanning from 20102022. The authors use a fixed effect regression model within a panel data framework to examine the relationship between corporate innovation and investment. For robustness, the authors use system generalised methods of moments to investigate the relationship between corporate investment and corporate innovation across all the samples. Findings: This study finds a positive relationship between corporate innovation and corporate investment, which means when the firm tries to make some innovation, it will increase its expenditure on fixed assets. However, the positive relationship between corporate innovation and corporate investment reduces with uncertainty. Additionally, financial constraint plays a significant role in determining this relationship. Executives and firms with high risk-taking ability tend to be more inclined to make investments. Originality/value: The study is unique because it determines the impact of corporate innovation on corporate investment. The current literature is focused on corporate innovation and uncertainties. However, no light has been shed on the relationship between corporate innovation and investment. At the same time, the authors have introduced three more variables which play a significant role in determining the corporate innovation-investment relationship. , Emerald Publishing Limited. -
Role of digital technologies to combat COVID-19 pandemic
Purpose: The unexpected epidemic of the latest coronavirus in 2019, known as COVID-19 by the Globe, a number of governments worldwide have been put in a vulnerable situation by the World Health Organization. The effect of the COVID-19 outbreak, previously experienced by Chinas citizens alone, has now become more pronounced. For practically every nation in the world, this is a matter of grave concern. The lack of assets to withstand the infection of COVID-19, mixed with the perception of overwhelmed medical mechanisms, pressured a number of places in a state of partial or absolute lockdown. Design/methodology/approach: The medical photos such as computed tomography (CT) and X-ray playa key role in the worldwide battle against COVID-19, while artificial intelligence (AI) has recently appeared. The power of imaging is further increased by technology tools and support for medical specialists. In comparison to the related direct health effects because of the COVID-19 disaster, this research identifies its impacts on the overall society. Findings: This paper hereby examines the rapid answers in the medical imaging community toward COVID-19 (empowered by AI). For example, the acquisition of AI-empowered images will significantly assist automate the scanning process and reshape the procedure as well. AI, too, may improve the quality of the job by correctly delineating X-ray and CT image infections, promoting subsequent infections, quantification. In addition, computer-aided platforms support radiologists make medical choices, i.e. for illness tracking, diagnosis and prognosis. Originality/value: This research encompasses the whole medical imaging pipeline and methods for research related to COVID-19, include a collection of images, segmentation, diagnosis and monitoring. In drawing stuff to minimize the effects of the COVID-19 epidemic, this paper is investigating the use of technologies such as the internet of things, unmanned aerial vehicles, blockchain, AI, big data and 5G. 2021, Emerald Publishing Limited. -
Role of Digitalization and Government Effectiveness in Sustainable Energy Transition: Evidence From Asian Economies
This study explores how digitalization, through resident and non-resident innovation initiatives, along with government effectiveness, affects the transition to renewable energy generation in five Advanced (Australia, Hong Kong, Japan, New Zealand and Singapore) and seven Emerging (China, India, Indonesia, Malaysia, Philippines, Thailand and Vietnam) Asian economies. The research uses annual data from 1985 to 2022 and applies several econometric methods to analyse the impact of these factors on renewable energy generation in a panel setup while also considering economic growth and human capital as key control variables. The findings reveal that residential innovation negatively impacts renewable energy generation in Advanced Asia but has a positive effect in Emerging Asia. Additionally, government effectiveness and non-residential innovation hinder renewable energy generation in Emerging Asia while contributing positively in Advanced Asia. Economic growth and human capital show a positive association with renewable energy generation in both Advanced and Emerging Asian economies. These findings are robust to an alternative method used. Besides, additional robust results further indicate that artificial intelligence patents used as an alternative measure of digitalization hinder renewable energy generation in Emerging Asia and promote it in Advanced Asia. These findings provide valuable guidance for policymakers and stakeholders, highlighting the need for tailored strategies to drive sustainable energy transition in different economic contexts. 2025 John Wiley & Sons Ltd. -
Role of E-Shopping Orientation and Trust in predicting Impulsive Buying Behaviour. A Study Based on members of Generation Y in India; [El papel de la orientaci y la confianza en las compras electricas en la predicci del comportamiento de compra impulsiva. Un estudio basado en miembros de la Generaci Y en la India]
Impulse Buying and the drivers of similar consumer behaviours have captured the interest of researchers for quite some time now. The construct was first explored in the context of offline or brick and mortar stores. However, with the growing popularity of online retail stores has led to the concept being included in studies on customer behaviour, specifically in the online context. In the current study, the researchers attempt to contribute to literature on customer behaviour in the online environment by exploring the relationship between E-Shopping Orientation, Trust and Impulsive Buying Behaviour. The focus of the currents study is the members of Generation Y. The scope was limited to this specific section, given that each generation differs from the other in terms of their behaviour, needs and drivers. While the direct impact of E-shopping Orientation on Impulsive Buying Behaviour was found to be not statistically significant, the indirect effect was found to be significant. This suggests that Trust fully mediates the relationship between E-Shopping Orientation and Impulsive Buying Behaviour. In addition to contributing to literature in the area of customer behaviour, the findings also add to our understanding of a major section of the Indian customer base. (2024), (Universidad Pablo de Olavide). All Rights Reserved. -
Role of energy sources in promotion of sustainable development: moderating implications of globalisation
This study empirically investigates the impact of renewable and non-renewable energy generation on sustainable development for a balancedpanel of 68 developed and developing economies from 1990 to 2019. This is done to scrutinise the intricate interplay between energy sources and sustainable development outcomes at the global level. The estimated models also control for the effects of globalisation, urbanisation, and government expenditure. The Westerlund cointegration establishes a significant long-run relationship between the variables under consideration. In this regard, the two-step dynamic system-generalised moment method (system GMM) demonstrates a positive impact of renewable energy, globalisation, and government expenditure on sustainable development. In contrast, non-renewable energy and urbanisation exert detrimental influences on it. However, both the energy sources demonstrate an amplified positive impact on sustainable development under the moderating influence of globalisation. The Feasible Generalised Least Squares estimation also confirms the long-run reliability of these baseline findings. Furthermore, Granger based non-causality test establishes a significant causal relationship between the variables under consideration. Potential policy suggestions for promoting the sustainable development are also discussed. The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
Role of Experiential Learning Program on Business Writing Skills of Management Students
Purpose: Writing has been identified as an important skill. Business writing refers to the form of writing that is used to communicate in formal settings in various corporations and organizations. A number of research studies have identified writing as a crucial skill that needs to be developed by students. The purpose of the study is therefore to understand how an experiential learning module on business writing can improve the email-writing and report-writing skills of management postgraduates. Design/Methodology/Approach: The study uses an experimental research methodology based on experiential learning pedagogy to obtain the results of the intervention on the business writing skills of the management postgraduate students. The module was developed by the researcher and then was taught to the students through the online platform Zoom. Pretest, posttest, and delayed posttest analysis was conducted to find the impact of the intervention. The students were evaluated by an industry expert to avoid bias as they were trained by the researcher. Findings: The results of the study indicated that the intervention had a significant impact on the business writing skills of the participants. The results of the component analysis also indicated a large effect on the content, persuasive abilities, lateral thinking abilities, and the interpersonal skills of the participants in written communication. The analysis of the test scores revealed that an initial training based on the experiential learning methods can have a long-term impact on the improvement of the skills of the students, as the delayed posttest results were more than the posttest results. Originality/value: The study will be beneficial to educators, trainers, as well as students in understanding how experiential learning can impact the business writing skills of the students. 2024 by the Association for Business Communication. -
Role of Factoring in Financing SMEs in India
The International Journals Research Journal of Social Science and Management, Vol. 2, No. 5, pp 165-172, ISSN No. 2251-1571 -
Role of Globalization and Innovation Pattern in Growth of Bank Credit: Evidence From Emerging and Advanced Asia
This study examines the role of globalization and innovation pattern (i.e., innovation by the residents and non-residents) in the growth of domestic bank credit across emerging and advanced Asian economies spanning from 1996 to 2022. The bank credit growth model includes economic growth and real interest rate as important control variables. This study employs Cross Sectional-Autoregressive Distributed Lag (CS-ARDL) as an appropriate baseline method because of the cointegration, endogeneity, and cross-sectional dependency present in the data. The long-run results for emerging Asian economies indicate that globalization exhibits a negative impact on banking credit, contrasting with the positive influence observed in advanced Asian economies due to heightened economic growth and increased credit demand. Residential innovation consistently bolsters banking credit in both sets of economies, albeit with mixed effects stemming from non-resident innovation. The long-run results further indicate the positive (negative) impact of economic growth (real interest rate) on bank credit in emerging and advanced Asian economies. These findings are reliable due to the similar results obtained from using Driscoll-Kraay Robust Standard Errors (DKSEs) as robust method. For policymakers in emerging economies, the imperative policy lies in striking a delicate balance between economic openness and bank credit, while counterparts in advanced economies are poised to bolster bank credit accessibility through foreign innovation while upholding stringent regulatory oversight. 2024 John Wiley & Sons Ltd. -
Role of knowledge management strategies on employees performance in selected information technology companies In Bangalore /
International Journal of Management And Social Sciences, Vol.8, Issue 2.1, pp.54-58, ISSN No: 2349-9761. -
Role of management education in adapting the Indian public sector to market-based economic reforms
Purpose: In 1991, India embarked on market-based economic reforms initiatives pillared on liberalization, privatization and globalization (LPG). The reforms exposed the public sector enterprises to competitive market forces, raising the need to identify and develop the competencies necessary for survival. Executive training programs were initiated to prepare public enterprises for the market-based reforms. Three decades later, the reforms especially privatization is witnessing renewed interest under the current administration. In this context, the article takes a closer look at the structure of management education provided to public sector officers in India. The article also identifies barriers for implementing the learnings from the management courses in the workplaces and suggests approaches for closing the gap. Design/methodology/approach: The study follows a thematic approach based on unstructured interviews of senior executives of Indian public sector enterprises covering oil and gas, aeronautical, power and transportation sectors. New public management (NPM) is used as a yardstick of business-like characteristics of public sector enterprises. Findings: Despite heavy investment, trainings have had only partial success in implementing the core objective of NPM, i.e. to provide quality services in a professional manner to meet citizen requirements. The study found that though concepts of NPM are introduced at multiple management training programs, thepublic enterprises lag in the implementation of NPM. The ingrained hierarchical and procedural culture of the enterprises was often highlighted as the challenge to its implementation. Practical implications: The study will be of significance to Indian policymakers in designing management education programs to public sector employees. It brings out (1) various models of management education provided to public servants across industries, (2) provide evidence on the extent of NPM implementation, (3) identify barriers for transitioning the learnings from the management courses to workplace and (4) suggest changes for improving effectiveness. Originality/value: The existing research on LPG in India covers the economic transformation post-implementation and the factors contributing to the success of its implementation. This study adds to the limited literature available on the management education of public servants in the country. 2023, Emerald Publishing Limited. -
Role of mesoporous silica supported mixed oxides of ceria and samaria for the synthesis of ?-caprolactone at room temperature
Mesoporous silica was prepared from rice husk by pyrolysis method. Mixed oxides of ceria and samaria (50/50) were disp?ersed on silica by rotavapor assisted wet impregnation method. Catalysts were further modified by doping with MoO3, La2O3 and mixed MoO3La2O3. The prepared systems were characterized by various physicochemical techniques such as BET surface area analysis, scanning electron microscopy, elemental detection analysis, transmission electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, Thermogravimetric analysis, n-butylamine titration and X-ray photoelectron spectroscopy analysis. The catalytic activity of all the systems were studied in the oxidation of cyclohexanone to ?-caprolactone. Various parameters such as time, molar ratio of cyclohexanoneH2O2, temperature, solvent and the amount of catalyst were studied thoroughly to optimize the favorable conditions for the oxidation reaction. Higher ?-caprolactone selectivity of 88.9% was observed in the presence of hydrogen peroxide in acetonitrile medium. The recyclability tests were performed up to six cycles without any appreciable loss in activity, which confirmed the stability of the prepared systems. Good yield with high selectivity was achieved at room temperature, which makes the protocol greener. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Role of mixed molecular weight PEO-PVDF polymers in improving the ionic conductivity of blended solid polymer electrolytes
Blended solid polymer electrolytes (BSPE) were prepared by mixing different molecular weight polymers PEO6 (Mw = 1 106 g/mol), PEO5 (Mw = 1 105 g/mol), and PVDF (Mw = 5.25 105 g/mol) complexed with lithium salt. Conductivity and dielectric studies at different temperatures were carried out on these BSPE systems by varying the wt% of PEO5 and PVDF with respect to PEO6, keeping the wt% of lithium salt constant. The electrical characterizations of BSPE systems have been investigated using impedance spectroscopy in the frequency range 0.1106 Hz. The conductivity data shows that inclusion of PEO5 and PVDF into the PEO6 matrix improved the overall lithium-ion dynamics in the polymer matrix. The composition, PEO6 (94 wt%)-PEO5 (3 wt%)/PVDF (3 wt%)-LiClO4, exhibited maximum conductivity of 6.44 10?4 Scm?1 at 303 K. TheDC conductivity variation with temperature of BSPE systems follows Arrhenius relation and variation of AC conductivities with frequency obeys Jonschers power law. The real and imaginary part of dielectric constant and the dielectric relaxation were also investigated. 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Role of mixed nanofluids on fluid flow and intensify energy transfer in a boundary layer region driven by a free convective force
This research study explores boundary layer flow and intensification of heat transfer through a porous medium accompanied by buoyant forces with the support of appended mixed nanofluids. The generated partial differentiation model is altered to a couple of the highly complicated nonlinear differentiation model by support of the similarity conversion. The resultant model is then resolved by the shooting method for finding the initial approximation and thereafter the Runge-Kutta-Fehlberg 45th-order method is used to get the desired result. The energy transfer and the flow of mixed nanofluids are analyzed by considering vital factors, like convection, porous and volume fraction. The acquired results fairly agree with erstwhile published articles. The major finding is that for greater values of the volume fraction, both fluid flow and energy transfer of a mixed nanofluid will be greater when compared with a regular nanofluid. 2019 Wiley Periodicals, Inc.