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Sensory processing sensitivity in relation to coping strategies: exploring the mediating role of depression, anxiety and stress
Existing research on sensory processing sensitivity (SPS) focuses majorly on populations involving children, those with Autism Spectrum Disorder, and those belonging to the Western countries. This study aims to contribute in bridging this gap by exploring the mediating role of Depression, Anxiety, Stress on the relationship between SPS and coping strategies in the general population, while also assessing the prevalence of these variables. Data was collected from a convenience sample of 107 participants (mean age = 20.6years, 57.9% females). Participants responses were recorded for the Highly Sensitive Person Scale (HSPS), the Depression, Anxiety, Stress Scale (DASS-21), and the Coping Strategies Inventory-Short Form (CSI-SF). Correlational and mediation analyses of SPS, coping strategies and Depression, Anxiety and Stress were done. In the sample, 31.78% of individuals were found to be Highly Sensitive Persons (HSPs). The findings revealed significant relationships between SPS, Depression, Anxiety, Stress and coping strategies. Depression and Anxiety were observed to be significant mediators. While SPS as a trait may not be inherently modifiable, our results on its association with emotion-focused disengagement coping provide insight into target dysfunctional patterns for effective management of depression, stress, and anxiety. Further research is warranted to enhance the applicability of this study. The Author(s) 2024. -
Quality assurance in big data analytics: An IoT perspective
Emergence of IoT as one of the key data contributors in a big data application has presented new data quality challenges and has necessitated for an IoT inclusive data validation ecosystem. Standardized data quality approaches and frameworks are available for data obtained for a variety of sources like data warehouses, webblogs, social media, etc. in a big data application. Since IoT data differs significantly from other data, challenges in ensuring the quality of this data are also different and thus a specially designed IoT data testing layer paves its way in. In this paper, we present a detailed review of existing data quality assurance practices used in big data applications. We highlight the requirement for IoT data quality assurance in the existing framework and propose an additional data testing layer for IoT. The data quality aspects and possible implementation models for quality assurance contained in the proposed layer can be used to construct a concrete set of guidelines for IoT data quality assurance. 2019 Telecommunications Society and Academic Mind. -
Multi-level Prediction of Financial Distress of Indian Companies Using Machine Learning
Predicting Financial Distress (FD) and shielding companies from reaching that stage is vital, even indispensable for every business. FD, if not attended to on time, ultimately leads to bankruptcy. Prediction variables are essential to forecast the wreckage in the business; however, the prediction is successful when suitable models are used. This study aims to predict FD at three levels: from mild to severe, by applying a machine learning algorithm. The study identifies modern models using the machine learning approach for predicting multi-level FD and summarises the significance of modern models through machine learning technology, to sustain the future development of the economy. The modern models are free from rigid assumptions and have proved to be the best in the prediction of FD. The results show that FD prediction is important at multiple stages. The models performance will be high when the best features are selected using the Pearson Correlation and SFS Feature selection approach. Among the ten models used in the study, LightGBM Classifier shows the highest performance of 80.43% accuracy without feature selection. However, with Pearson Correlation Approach and SFS Feature Selection methods, the accuracy is 82.68% and 86.95% respectively. This study has major implications for the stakeholders of the company to take timely decisions on their investment and for the management as a yardstick to check the performance of the business. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
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Synchronous learning and asynchronous learning during COVID-19 pandemic: a case study in India
Purpose: This research aims to study the students' perspectives on synchronous and asynchronous learning during the COVID-19 Pandemic. Both synchronous and asynchronous learning approaches used in online education have positive and negative outcomes. Hence, the aim is to study online education's positive and negative consequences, reflecting sync and async approaches. This research followed a mixed research approach. The key stakeholders of this research are the Indian educational institutions and students. Design/methodology/approach: This research collected data from the students undergoing synchronous and asynchronous learning amidst the COVID-19 Pandemic. The data were collected (N=655) from various students taking online classes during the pandemic. A questionnaire survey was distributed to the students through online platforms to collect the data. In this research, the authors have collected data using simple random sampling, and the same has been used for data analysis using SPSS version 26. The collected data were exposed to a factor analysis using a principal component analysis technique to reduce the vast dimensions. Findings: The study findings show that synchronous learning is sometimes stressful, placing more responsibility on students mainly because of the increased screen time. At the same time, asynchronous learning allows the students to self-explore and research the topics assigned to them. Students also felt that asynchronous activities create a burden because of many written assignments to be submitted within a short period. Overall, the COVID-19 pandemic has been challenging for the students and the teachers. However, teachers have helped students to learn through digital platforms. The majority of the respondents opined that technological disruptions and death in the family circle had been significant reasons for not concentrating during online classes. However, the combination of synchronous and asynchronous learning has led to a balanced education. Practical implications: Higher education has undergone multiple transformations in a short period (from March 2020, 2021 and beyond). Educational institutions underwent a rapid transition in remote teaching and learning in the initial stages. As time progressed, educational institutions did course navigation where they relooked into their course plans, syllabus and brought a structural change to match the pandemic requirements. Meanwhile, educational institutions slowly equipped themselves with infrastructure facilities to bring academic integrity. At present, educational institutions are ready to face the new normality without disrupting services to society. Social implications: Educational institutions create intellectual capital, which is important for the development of the economy. In the light of COVID-19, there are new methods and approaches newly introduced or old methods and approaches, which are reimplemented, and these approaches always work for the benefit of the student community. Originality/value: The authors collected data during the COVID-19 pandemic; it helped capture the students' experience about synchronous and asynchronous learning. Students and faculty members are newly exposed to synchronous and asynchronous learning, and hence, it is essential to determine the outcome that will help many stakeholders. 2022, Cassandra Jane Fernandez, Rachana Ramesh and Anand Shankar Raja Manivannan. -
Digital Forensics Chain of Custody Using Blockchain
In todays world, Digital Forensics is a crucial subject with much scope as data storage becomes more decentralised. The collection and preservation of digital media is a topic of concern across the Cyber Security and Digital Forensics field. With Cloud Infrastructure and other technologies, data is not permanently stored in one place and gathering and analysing it can become a headache for Forensic Investigators. Blockchain, however, works as a decentralised, distributed peer-to-peer network and thus can be considered a suitable solution for the mentioned problems. With the help of a blockchain network and Smart Contracts, Digital Forensics can be significantly improved to adapt to modern digital architecture. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
A Feature Selection Study on the Bot-IoT Dataset Using Ensemble Classification Techniques
IoT is an emerging giant in the field of technol- ogy, taking over traditional systems, providing interconnected- ness, convenience, efficiency, and automation, making our lives unimaginably better. However, security for these IoT systems is challenging, especially due to their interconnectedness, making them vulnerable to various cyber threats. The rising tide of IoT botnets, especially, presents a unique challenge. This has urgently increased the need for Intrusion Detection research. Modern Intrusion Detection approaches often employ Machine Learning for effective results. Feature Selection is extremely important while creating Machine Learning Classification models to avoid overfitting and poor performance. This paper focuses on running a Feature Selection study on the Bot-IoT dataset provided by UNSW to increase the accuracy of a ML model. The paper tests 5 types of Feature Selection methods, from Filter- based, Wrapper-based and Embedded methods, combined with two distinct ensemble classifiers: Random Forest + Adaboost and XGBoost. Each combination is tested with the dataset, and the accuracy is compared to find the most effective and versatile feature selection method that can assist both Stacking and Voting- type Ensemble classifiers. The results show that Karl Pearson can provide the best accuracy when applied to both Ensemble Classifiers. 2024 IEEE. -
Effects of Rough Boundaries on RayleighBenard Convection in Nanofluids
A linear stability analysis of RayleighBenard convection in a Newtonian nanofluid is carried out using most general boundary conditions. A single-phase description of nanofluids is adopted in the study. The nanofluids used for the study are wateralumina and watercopper nanofluids in order to analyze how a choice between them can be made. The values of thermophysical quantities of nanofluids are calculated using the mixture theory and phenomenological-laws. The paper applies the Maclaurin series in solving the boundary-eigenvalue-problem through a simple and innovative approach. A single-term Galerkin technique is adopted to obtain the guess value of the critical Rayleigh number and the wave number. Further, improved values of the Rayleigh number and the wave number are obtained using the solution of a system of three linear-algebraic equations. A detailed discussion is made on the effect of rough-boundaries and Robin-boundary conditions for temperature on the onset of convection. A comparative study between the results of two nanofluids is made and the destabilizing effect of nanoparticles in the Newtonian carrier-fluid on the onset of convection is studied. Copyright 2023 by ASME. -
Sectoral correlations and interlinkages: NSE
An efficient portfolio is a well-diversified portfolio that gives the investor opportunities to earn money and provide cover against risks. Understanding the intersectoral linkages and correlations among various sectors in a stock market will help an investor to diversify the portfolio and reduce risk efficiently. This study aims at examining the underlying linkages and correlations among eight sectors in the Indian National Stock Exchange (NSE) using a Granger causality test under VAR environment. The results of the study based on nine years' data from 2009 to 2018 show that an effective portfolio can have two classifications -stocks from Pharma and Media as group one (defensive stocks) and picks from IT, Bank, Financial Services, Realty, Auto and FMCG sector as group two (somewhat Cyclical). The study further proves that the usual definition for cyclical and defensive sectors have undergone some profound changes. 2020 SCMS Group of Educational Institutions. All rights reserved. -
Traditional Ecological Knowledge Repository in the Indian Himalayas: An Overview
Traditional ecological knowledge (TEK) refers to a body of informa-tion that is also referred to as local knowledge, traditional knowledge, native knowledge, and indigenous technological knowledge. A number of studies show the role of traditional ecological knowledge in decision-making in social-ecological systems that support sustainability and resilience. International agencies have also highlighted and emphasised the importance of TEK practises in the preservation of biological variation. For instance, the UN Convention on Biodiversity, Article 8 (j), makes it very plain that respect, maintain, and promote innovation and practises of indigenous and aboriginal populations connected with sustainable use of biolog-ical diversity are essential. The benefits of TEK for sustainable forest management were acknowledged in the 2005 Millennium Ecosystem Assessment Report by the World Bank. As environmentalists, anthropologists, and arborists share interests in TEK for academic, social, or economic reasons, this highlights the significance of TEK in difficulties relating to biodiversity protection. Numerous components of TEK are seen favourably by experts in fields of forestry, irrigation, architecture, ethno-biology, irrigation, agriculture, medicine, sun and water conservation, conventional weather prediction, adaptation to climate change, and disaster risk reduction. Indian Himalayan Region (IHR) is predominantly populated by indigenous peoples and local societies, which are quite diverse in terms of socio-culture and race. The region has nearly 40% of all of Indias indigenous tribes. This area is also special for its tradi-tional ecological knowledge. Many of the TEK-based practices have supported local communities in earning a livelihood. The indigenous peoples expertise and expe-riences are said to play a crucial part in preventing climate change, and they may give important information on the implications of climate change. Hence, sustaining biodiversity in the IHR is also a means of defending indigenous peoples rights. By making the TEK the focal point of governance systems at the IHR, the variety of options for sustainable growth and even the co-production of the body of knowl-edge would be expanded. Therefore, it seems sensible to get knowledge from the TEK before it is lost to the onslaught of modernity. However, there are numerous problems or issues with traditional ecological knowledge in India, including igno-rance in considering conservation policies by the Indian government and the lack of effective documentation of this priceless knowledge. To develop sustainable and culturally suitable management techniques, it is currently a challenge to combine indigenous knowledge standards and management methods with Western science. Realising the above, this chapter attempts to comprehend the concept of TEK and its application throughout a variety of resource management contexts throughout a variety of resource management scenarios. Further, it will explore various issues and challenges and examine the regulations thereof. Lastly, this chapter concludes by highlighting the strategies and suggestions for an effective repository of traditional ecological knowledge in the Indian Himalayan Region. 2024 The Author(s). -
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Computationally efficient wavelet domain solver for florescence diffuse optical tomography
Estrogen induced proliferation of mutant cells is a growth signal hallmark of breast cancer. Fluorescent molecule that can tag Estrogen Receptor (ER) can be effectively used for detecting cancerous tissue at an early stage. A novel targetspecific NIRf dye conjugate aimed at measuring ER status was synthesized by ester formation between 17-? estradiol and a hydrophilic derivative of ICG, cyanine dye, bis-1,1-(4-sulfobutyl) indotricarbocyanine-5-carboxylic acid, sodium salt. In-vitro studies provided specific binding on ER+ve [MCF-7] cells clearly indicating nuclear localization of the dye for ER+ve as compared to plasma level staining for MDAMB-231. Furthermore, cancer prone cells showed 4.5-fold increase in fluorescence signal intensity compared to control.; A model of breast phantom was simulated to study the in-vivo efficiency of dye with the parameters of dye obtained from photo-physical and in-vitro studies. The excitation (754 nm) and emission (787 nm) equation are solved independently using parallel processing strategies. The results were obtained by carrying out wavelet transformation on forward and the inverse data sets. An improvisation of the Information content of system matrix was suggested in wavelet domain. The inverse problem was addressed using LevenbergMarquardt (LM) procedure with the minimization of objective function using Tikhonov approach. The multi resolution property of wavelet transform was explored in reducing error and increasing computational efficiency. Our results were compared with the single resolution approach on various parameters like computational time, error function, and Normalized Root Mean Square (NRMS) error. A model with background absorption coefficient of 0.01 mm-1 with anomalies of 0.02 mm-1 with constant reduced scattering of 2.0 mm for different concentration of dye was compared in the result. The reconstructed optical properties were in concurrence with the tissue property at 787 nm. We intend our future plans on in-vivo study on developing a complete instrumentation for imaging a target specific lipophilic dye. Springer International Publishing Switzerland 2014. -
Gravity-modulated RayleighBard convection in a Newtonian liquid bounded by rigidfree boundaries: a comparative study with other boundary conditions
Effect of different boundaries on the gravity-modulated RayleighBard convection has been investigated with an emphasis on rigidfree boundaries. Small-amplitude and large-amplitude modulations are studied using the linear stability analysis. The modified Venezian approach is used to study small-amplitude modulations using different modes of perturbations and the superposition principle. The existence of subharmonic motions for the case of large-amplitude modulations was explored using the Mathieu equation arising from the linear stability analysis. Floquet theory was used together with Hills infinite determinant method to compute the critical Rayleigh number for the case of large-amplitude modulations. Weakly non-linear analysis is performed leading to the cubic StuartLandau equation from the Lorenz system. Heat transport was quantified using the Nusselt number and the mean Nusselt numbers for different amplitudes and frequencies. It was found that gravity modulation has, in general, a stabilizing effect on the convection process in all three boundary types, and the heat transport was found to be an increasing function of amplitude. Another important outcome of the study is that the critical Rayleigh number for the onset of convection for rigidfree boundaries lies between those of the corresponding values of the freefree and rigidrigid boundaries in the case of both harmonic and subharmonic motions which could be exploited in controlling convection. 2023, The Author(s), under exclusive licence to Springer Nature B.V. -
Innovation journey: Unleashed business applications framework
This chapter gives a thorough framework for understanding the dynamics and applications of innovation in the business environment. In today's fast-paced and competitive world, innovation is essential for organizational growth, adaptation, and sustainability. This study takes a descriptive approach, addressing the complexities of creativity across multiple dimensions. This chapter offers a conceptual overview before examining the various aspects of innovation and its function as a driving force behind strategic initiatives and a means of fostering competitive advantage. It provides a thorough study that clarifies the various stages of the innovation process, from ideation to optimization, emphasizing key challenges and opportunities at each level. It provides a road map for businesses looking to foster an innovative culture and use it as an outlet for value creation and competitive advantage by adopting a comprehensive viewpoint. 2024, IGI Global. -
Harmonizing human resource strategies navigating employer branding in sustainable organizations
In the framework of sustainable businesses, this chapter examines the synergies between employer branding and human resource (HR) strategies. In order to establish a harmonic organizational framework, this chapter thoroughly investigates how HR practices might be strategically aligned with sustainability goals. It explores the opportunities and challenges of managing employer branding within sustainable business practices. It sheds light on specific variables and practices that must be considered to develop an employer brand that reflects the organization's commitment to sustainability. In order to create an integrated, attractive, and socially responsible employer brand, it is important to align their human resources practices with sustainability initiatives. It provides insights into the strategic integration of employer branding and human resources, presenting a roadmap for businesses looking to match their HR procedures with sustainability programs. 2024, IGI Global. All rights reserved. -
Corporate social responsibility and its impact on organizational attractiveness: Unveiling the mediating role of perceived organizational support
The central aim of the study is to investigate the mediating role of perceived organizational support (POS) in the relationship between corporate social responsibility (CSR) initiatives and organizational attractiveness (OA). It employs a cross-sectional quantitative design, collecting data from diverse organizations. Multistage convenient sampling was used to collect responses from employees of 20 IT companies in Bengaluru. Insights from employees working in IT companies are collected through the questionnaire. There were 740 questionnaires distributed, of which only 396 were returned in their completeness state. Statistical analyses, including regression and bootstrapping techniques, were done using SPSS and AMOS to examine the mediating effect of POS. The study highlights a noteworthy mediating effect of perceived organizational support (POS) on the relationship between CSR initiative and organizational attractiveness. It was also revealed that POS partially mediates CSR and OA, significantly influencing CSR and OA. Managerial implications of this study are that the organization focusing primarily on employee support measures enhances the external reputation and develops internal commitment and loyalty. These insights furnish organizations with a strategic roadmap to navigate the dynamic realm of CSR and organizational attractiveness. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Catchment-specific approaches in human resource management: Enhancing recruitment practices
In today's dynamic business outdoors, identifying the most skilled employees has become a challenging and captivating challenge. This chapter explores the catchment-specific approach in human resource management in the information technology (IT) industry. This conceptual chapter analyzed peer-reviewed academic literature, the business press, and other media outlets. This conceptual chapter outlines the key issues for catchment-specific approaches in human resource management in the area of recruitment with the changing trends of the recruitment process. Certain emergent practices include analyzing the catchment area, tailoring recruitment strategies, and evaluating and refining catchment-specific in recruitment. This chapter helps raise awareness and understanding of this new and emerging aspect of catchment-specific approach in human resource management. 2024, IGI Global. All rights reserved. -
Modelling and CFD simulation of vortex bladeless wind turbine
When the forces act on a bluff body in the wind flow direction, vortices are formed. Vortex bladeless wind turbine oscillates as a result of the vortices generated due to VIV. When the vortex shedding frequency is nearer to the natural frequency of the structure, maximum amplitude of vibration occurs and coincidentally power is generated. 3D models are designed to stimulate flow at a Reynolds number of 50000. This paper focuses on modelling the bladeless wind turbine based on semi-vortex angle and also 1) to study the vortices pattern and vorticity of different models 2) to study the drag and lift coefficients. In this paper vortex turbine is designed with certain parameters of dimension in Solid Edge and CFD analysis is carried out in Simscale software. Different model performance parameters like power, natural frequency and coefficient of power are compared among different models to opt for the best vortex bladeless wind turbine design. 2022 Author(s).