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A Deep Convolutional Kernel Neural Network based Approach for Stock Market Prediction using Social Media Data
Several economists and social scientists have held a longstanding fascination with the practice of stock market prediction. As the stock market is essentially uncontrollable chaos, many experts believe that trying to predict it is futile. Due to the complexity of the numerous factors, accurate stock price predictions are notoriously difficult to achieve. While the market behaves more like a scale than a voting machine over the long run, its behavior may be predicted with some certainty. Information from Twitter is used into the algorithm. In this proposed method, a convolutional extreme learning machine model with kernel support was introduced (CKELM). To improve feature extraction and data classification, the CKELM model builds on the KELM's hidden layer by adding convolutional and subsampling layers. The convolutional layer and the subsampling layer do not employ the gradient technique to fine-tune their parameters because some designs worked well with random weights. When compared to popular models like CNN and KELM, The proposed model fares quite well, with an accuracy of around 98.3 percent. 2023 IEEE. -
A Comprehensive Review of Linear Regression, Random Forest, XGBoost, and SVR: Integrating Machine Learning and Actuarial Science for Health Insurance Pricing
Actuarial science and data science are being studied as a fusion using Industry 4.0 technologies such as the Internet of Things, artificial intelligence, big data, and machine learning (ML) algorithms. When analyzing earlier components of actuarial science, it could have been more accurate and quick, but when later stages of AI and ML were integrated, the algorithms weren't up to the standard, and actuaries experienced some accuracy concerns. The company requires actuaries to be precise with analysis to acquire reliable results. As a result of the large amount of data these companies collect, a choice made manually may turn out to be incorrect. We will, therefore, examine alternative models in this article as part of the decision-making process. Once we have chosen the best path of action, we will use our actuarial expertise to evaluate the risk associated with specific charges features. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Enhanced Multi-Model Approach for Motion and Violence Detection using Deep Learning Methods Using Open World Video Game Dataset
For today's environment, it is extremely important to understand hostility and motion in a variety of contexts, particularly where accidents are concerned. There's also a high safety risk in public places if there is no proper identification of suspicious activities that occur fast and cannot be accurately observed through traditional surveillance systems that rely on constant human monitoring. Although deep learning algorithms have proven useful for detecting anomalies such as fraud recently, there has been little research on real-time crime detection because of issues related privacy when using live data sets. To tackle the key problem of motion and violence detection with current deep learning methods, this work exploits the Open World Game Dataset which provides realistic activities. The reliance on only one technique undermined the previous models' accuracy while this study comes up with various models to raise the detection precision and real-time processing capability. This work applies MobileNet SSD, YOLOv8 (You Only Look Once), and SSD (Single Shot MultiBox Detector) techniques to create a more accurate movement detection system. To identify violent or illegal behavior from videos, 3D convolutional neural networks (3DCNN) will be used alongside attention approaches. A diverse inexpensive training environment that enables simulating. 2024 IEEE. -
Recommender system for surplus stock clearance
Accumulation of the stock had been a major concern for retail shop owners. Surplus stock could be minimized if the system could continuously monitor the accumulated stock and recommend those which require clearance. Recommender Systems computes the data, shadowing the manual work and give efficient recommendations to overcome stock accumulation, creating space for new stock for sale to enhance the profit in business. An intelligent recommender system was built that could work with the data and help the shop owners to overcome the issue of surplus stock in a remarkable way. An item-item collaborative filtering technique with Pearson similarity metric was used to draw the similarity between the items and accordingly give recommendations. The results obtained on the dataset highlighted the top-N items using the Pearson similarity and the Cosine similarity. The items having the highest rank had the highest accumulation and required attention to be cleared. The comparison is drawn for the precision and recall obtained by the similarity metrics used. The evaluation of the existing work was done using precision and recall, where the precision obtained was remarkable, while the recall has the scope of increment but in turn, it would reduce the value of precision. Thus, there lies a scope of reducing the stock accumulation with the help of a recommender system and overcome losses to maximize profit. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Reward Based Garbage Monitoring and Collection System Using Sensors
Most of the time in our surroundings we come across the overfilled garbage bins near the lakes. When the bins are full, people just throw the waste here and there, which eventually goes into the lakes and pollutes the water bodies. This is because of improper dumping of garbage that is practiced in our society. With the increase in population, this problem is taking really bad shape. The prime need is to maintain a clean and healthy environment with proper disposal of waste. This paper presents a small effort to reduce this garbage problem. An Android app has been created which keeps on checking whether the dustbin is full. Also, the people will be rewarded for throwing waste into the dustbins. A QR code has been attached to the dustbin which will be scanned for rewarding the people. The dustbins use an IR sensor that detects the receiver of waste in bins. Major part of this proposed system includes the proper working of mobile application and proximity sensors. Arduino is used to maintain the proper connection with sensors and application and that is done by Bluetooth sensor. The main objective of this proposed system is to lure people to put waste into the dustbin along with the contribution towards smart city vision. This paper also gives a brief overview of the technologies and work done so far in this field. 2024 River Publishers. -
Still Waters Run Deep: Groundwater Contamination and Education Outcomes in India
We investigate the impact of groundwater contamination on educational outcomes in India. Our study leverages variations in the geographical coverage and timing of construction of safe government piped water schemes to identify the effects of exposure to contaminants. Using self-collected survey data from public schools in Assam, one of the most groundwater-contaminated regions in India, we find that prolonged exposure to unsafe groundwater is associated with increased school absenteeism, grade retention, and decreased test scores and Cumulative Grade Point Average (CGPA). To complement our findings and to study the effect of one such contaminant, arsenic, we use a large nationally representative household survey. Using variations in soil textures across districts as an instrument for arsenic concentration levels we find that exposure to arsenic beyond safe threshold levels is negatively associated with school attendance. 2024 Elsevier Ltd -
Revisiting cognitive assessment in the Indian prison setting
Purpose: Individuals with cognitive impairment are more likely to come into contact with the criminal justice system (Kimbell, 2016). Yet, only a handful of studies describe the nature of cognitive impairment experienced by inmates and the different types of challenges faced by researchers and clinicians while conducting cognitive assessments in correctional settings specifically in low-and middle-income countries. Design/methodology/approach: In the present paper, the authors describe different types of ethical and logistical challenges they faced while conducting cognitive assessments with inmates in India and suggest ways in which future researchers and clinicians could overcome them. Findings: Authors raise a discussion on the purpose, advantages, and limitations of psychological testing, highlighting alternative ways of cognitive assessment that may be more effective, resource-efficient, and sustainable. Originality/value: Implications for education and training in psychological assessment, forensic and clinical practice and policymaking are discussed. 2020, Emerald Publishing Limited. -
Examining psychometric properties of the Interpersonal Needs Questionnaire among college students in India
Background: With the second-highest population in the world, suicide-related deaths in India are high, and adults under 30 are particularly at an increased risk. However, empirical examinations of factors contributing to suicide in India and assessments of reliability and validity of self-report measures assessing these constructs are rare. Aims: The present study examined the psychometric properties of the Interpersonal Needs Questionnaire (INQ). Materials & Methods: Undergraduate students in India (N=432) completed the INQ and questionnaires assessing suicidal ideation, depression, fearlessness about death, and pain tolerance. Results: Confirmatory factor analyses of the 15-item INQ indicated that after removing three items assessing perceived burdensomeness, the two-factor structure of INQ demonstrated acceptable fit with good internal consistency for each of the subscales (?=.84.90). In line with the interpersonal-psychological theory of suicidal behavior (IPTS), thwarted belongingness and perceived burdensomeness interacted to predict suicidal ideation. Additionally, these constructs were positively associated with suicidal ideation and depression, and weakly correlated with fearlessness about death and pain tolerance. Discussion: Results support the relevance of the IPTS for understanding suicidal ideation among college students in India. Conclusion: The results suggest that modified INQ demonstrates strong internal consistency, as well as good construct, criterion, and discriminant validity among Indian college students. 2021 The American Association of Suicidology. -
Scripts About Happiness Among Urban Families in South India
The ways in which parents socialize positive emotions have important implications for youth wellbeing, though little is known about parental goals and responses to adolescents happiness in culturally diverse families. Using an open-ended qualitative methodology, we explored parent and adolescent views about situations leading to happiness, responses and justifications to the expression of happiness, and what parents would like to teach their children about happiness in a sample of 209 parent (56.3% fathers; Mage = 42.79years) and adolescent (85.2% girls, Mage = 14.95years) dyads in Bengaluru, India. When prompted to identify adolescents recent experiences of happiness, both parents and adolescents primarily described academic and extracurricular achievements, followed by special events and receipt of tangible items, social interactions, and overcoming difficult situations. The two most common parent responses to adolescents happiness were responding with appreciation or encouragement of the achievement and providing further instruction or advice, with fewer responses focusing on enhancing/maintaining the emotional state of happiness itself. A substantial proportion of participating parents reported that their child should focus on task improvement when feeling happy, followed by affect maintenance (i.e., the child should be happy), or express their emotion with restraint. The findings contribute to developing a culturally-informed understanding of socialization of happiness in diverse families. 2021, The Author(s), under exclusive licence to Springer Nature B.V. -
Examining the impact of uncertainty on business performance via strategic cost management adoption and implementation: the case of agro-based industries in and around Punjab, India
Dynamic business environments require a change to survive. Strategic cost management (SCM) must re-conceive its future as new, improved, or reformed under opportunities and tough demands. Traditional cost management may not be adaptable to business turbulence. Increasing shareholder and customer demand, rapid information and technology improvements in manufacturing, and worldwide market rivalry with antiquated tools can be difficult. SCM goes beyond cost reduction and includes revenue generation and competitive advantage. This article examines the relationship between adopting and applying SCM approaches and company success in agro-based industrial businesses. Empirical survey data from agro-based industrial companies in Punjab were analysed using multivariate data analysis. According to contingency theory, size, technology, total productivity maintenance, strategy, and organisation culture are factors related to strategic cost management. All dependent factors, including control variable size, favourably affected SCM acceptance and utilisation, which has a pragmatic effect on agro-based businesses. SCM utilisation also mediated performance. 2025 Inderscience Enterprises Ltd. -
CoFe2O4-APTES nanocomposite for the selective determination of tacrolimus in dosage forms: Perspectives from computational studies
An innovative and cost effective electrochemical sensor was fabricated to determine tacrolimus (TAC) in pharmaceutical samples. In the present study, cobalt ferrite nanoparticles (CFO) were synthesized hydrothermally using chitosan as the template and were further functionalized using (3-Aminopropyl) triethoxysilane (APTES). The synthesized CFO were characterized using various analytical techniques such as X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, vibrating sample magnetometry and high- resolution transmission electron microscopy. The CFO and CFO-APTES were further drop-casted on to the glassy carbon electrode (CFO-NH2/GCE) for the electrochemical determination of TAC. Under the optimum conditions, the CFO-NH2/GCE showed a very low detection limit of 0.03 nM with a high sensitivity of 21,448 ?A?M?1cm?2 and a wide linear TAC concentration range of 0.14 nM 75.83 nM. The proposed sensor showed good sensitivity, selectivity, reproducibility and stability for the sensing of TAC and this has been demonstrated by analysing TAC in different dosage forms. This is the first study to report the interaction of CFO-TAC and CFO-NH2-TAC at the electrode/electrolyte interface. To support the experimental findings qualitatively, extensive density functional theory simulations were carried out to study the interaction at the interface. Hence the proposed sensor is very selective and sensitive towards the detection of TAC. 2022 Elsevier B.V. -
Highly Surface Active Anisotropic Silver Nanoparticles as Antimicrobial Agent Against Human Pathogens, Mycobacterium smegmatis and Candida albicans
Rapid synthesis of anisotropic silver nanoparticles via cost-effective, non-hazardous, and eco-friendly methods using naturally available gums are of greater significance as their chemical synthesis is associated with high toxicity. This study aims to synthesize highly surface-active anisotropic silver nanoparticles and evaluate their antimicrobial efficacy against human pathogens, Mycobacterium smegmatis and Candida albicans. Anisotropic silver nanoparticles were synthesized using silver nitrate as the metal precursor and gum arabic as the template. The synthesized silver nanoparticles were characterized by UV-visible spectroscopy, fourier transformation infra-red (FTIR) spectroscopy, dynamic light scattering (DLS) analysis, high-resolution transmission electron microscopy and selected area electron diffraction (HRTEM-SAED) analysis and thermogravimetric analysis (TGA). TEM analysis showed the anisotropy and monodispersed nature of silver nanoparticles with an average size of less than 20 nm. The antibacterial and antifungal properties of the anisotropic silver nanoparticles were also studied keeping rifampicin and fluconazole as the reference. The minimum inhibitory concentration (MIC) was found to be 1 mM silver nanoparticles for both M. smegmatis and C. albicans. Synthesized anisotropic silver nanoparticles can be used as an alternative to antibiotics to treat the infections caused by M. smegmatis and C. albicans. Further, the effect of silver nanoparticles on haemolytic activity was also studied. 2021 Wiley-VCH GmbH -
Nanobiosensors: A Promising Tool for the Determination of Pathogenic Bacteria
Pathogenic bacterial detection is a significant concern for the well-being of all human beings. These tiny microbes are capable of causing numerous diseases, which can be nipped in the bud through proper monitoring and controlling at the early stages itself. Some common pathogenic bacteria include Mycobacterium tuberculosis, Bacillus anthracis, Streptococcus pneumoniae, Escherichia coli, Salmonella spp., etc. These microbes contaminate air, food, and water through different modes of transmission. The classical methods used for the identification of these bacteria are time-killing and backbreaking. Rapid pathogenic bacteria determination became possible through the intervention of biosensors. Biosensors are further modified with nanoparticles to build nanobiosensors that are tenfold efficient in bacterial detection. The optical and electrochemical nanobiosensors provide hassle-free detection of pathogenic bacteria, and pointof- care detection is also possible. This book chapter aims to give a brief idea about nanobiosensors starting from the principle to the advantages and disadvantages of bacterial detection. Relevant works of literature on different methods to detect bacteria, types of nanobiosensors, and their efficacy in pathogenic bacterial detection portray the current stand and the need for more innovations in the area of nanobiosensors. The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2022. -
Tuning of the surface structure of silver nanoparticles using Gum arabic for enhanced electrocatalytic oxidation of morin
Gum arabic stabilized silver nanoparticles have been used to modify carbon paste electrodes (AgNPs-GA/CPE) for the electrochemical sensing of morin, a flavanoid. The synthesized nanoparticles, before and after modification of electrodes were characterized by UVvisible spectroscopy, X-ray diffraction (XRD), fourier transformation infrared (FTIR) spectroscopy, transmission electron microscopy (TEM), dynamic light scattering (DLS), zeta potential measurements, and thermogravimetric analysis (TGA). The uniform-sized spherical silver nanoparticles have particle sizes less than 10 nm. AgNPs-GA/CPE electrode has shown excellent electrocatalytic activity towards the oxidation of morin at a potential of 0.14 V. The factors influencing the electrochemical determination of morin such as the effect of pH, the effect of scan rate, and the effect of concentration were studied in detail. The linear dynamic range was found to be 0.65 nM to 7.0 nM with a detection limit of 0.216 nM. The developed sensor has been successfully applied for the determination of morin in mulberry leaves and almonds. 2021 The Author(s) -
Transition metal oxides in electrochemical and bio sensing: A state-of-art review
This review article portrays the progress in developing novel electrochemical sensors using morphologically varied transition metal oxides. The role and applications of transition metal oxide nanoparticles of iron, titanium, manganese, zirconium, cobalt, nickel and their composites in the field of electrochemical and bio sensing are conferred in detail. Appropriate chemical functionalization of these nanomaterials guarantees the selective and sensitive determination of target molecules including DNA or creating antigen/antibody complexes. Substantial data is summed up in the tables. This review article highlights the significance of transition metal oxide nanoparticles as promising electrode modifiers for fabrication of sensors. The review ends up with a relevant discussion, existing challenges and future scopes. 2021 The Author(s) -
CoFe2O4-APTES nanocomposite for the selective determination of tacrolimus in dosage forms: Perspectives from computational studies /
Surfaces and Interfaces, Vol.35, ISSN No: 2468-0230.
An innovative and cost effective electrochemical sensor was fabricated to determine tacrolimus (TAC) in pharmaceutical samples. In the present study, cobalt ferrite nanoparticles (CFO) were synthesized hydrothermally using chitosan as the template and were further functionalized using (3-Aminopropyl) triethoxysilane (APTES). The synthesized CFO were characterized using various analytical techniques such as X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, vibrating sample magnetometry and high- resolution transmission electron microscopy. The CFO and CFO-APTES were further drop-casted on to the glassy carbon electrode (CFO-NH2/GCE) for the electrochemical determination of TAC. -
Impediments of product recovery in circular supply chains: Implications for sustainable development
Product recovery has fascinated the concentration of organizations and is prominent among industry practitioners and researchers due to improved environmental concerns, social awareness, and economic benefits. Circular supply chain (CSC) compounds the concept of product recovery in global supply chain management to present a sustainable perspective. Therefore, this study aims to determine impediments of product recovery and CSC toward sustainable production and consumption in the background of manufacturing organizations. This study determines potential impediments from literature and in consultation with experts. Further, a fuzzy VIKOR approach is practiced to prioritize the impediments of product recovery and CSC. Then, a sensitivity analysis is conducted to verify the robustness of the framework attained. The results from the study reflect that lack of collaboration from supply chain performers, lack of tax policies for facilitating CSC models and limited expertise, technology, information on CSC practices are the critical impediments to product recovery in CSCs. The findings of the study could assist industry managers and practitioners in developing procedures and strategies to attain sustainable development. 2022 The Authors. Sustainable Development published by ERP Environment and John Wiley & Sons Ltd. -
Achieving SDGs through MSMEs: An empirical assessment of environmental consideration initiatives in India
Today, addressing environmental concerns and reducing carbon emissions has become imperative for every organization. Hence, eliminating the adverse impacts of business operations is no longer limited to large organizations, even small business organizations are taking a proactive approach in this direction. The present study aims to investigate pertinent issues related to the adoption of environmental practices faced by MSMEs in India and how these practices can fulfill the aim of achieving sustainable development goals (SDGs 2030). However, in this chapter, the authors are only going to emphasize the environmental aspect of the sustainability dimensions. Further, this study also identifies the factors that impact the adoption of environmental consideration initiatives among MSMEs in India. The findings of the study offer significant contributions to the research related to environmental consideration initiatives of the Indian MSMEs sector. Further, it also highlights the need for mandatory frameworks and guidelines to facilitate the adoption of sustainability practices among MSMEs in India. 2024, IGI Global. All rights reserved. -
Complex and Multifaceted Nature of Cryptocurrency Markets: A Study to Understand its Time-Varying Volatility Dynamics
Decentralised Finance (DeFi) provides a new way to perform complex financial transactions by exploiting blockchain's ability to maintain a decentralised ledger of transactions without being constrained by centralised systems or human intermediaries. DeFi provides alternative financial instruments that might lessen portfolio risk, especially given the erratic state of the financial markets today. This study analyses the association between the year of the coin in which it was introduced and the market capitalisation of the respective companies. Furthermore, the study also tries to understand the volatility associated with cryptocurrencies using EGARCH & GJR-GARCH models. The results reveal that market capitalisation is not similar for all three stages of the age of cryptocurrency. Also, negative news tends to impact Bitcoin more than positive news, and the volatility is persistent and long-lasting. Ethereum, BNB & Solana see more volatility from absolute past shocks; however, Tether exhibits low but persistent volatility as a stablecoin. 2024, Creative Publishing House. All rights reserved. -
Can Renewable Energy Be a Driving Factor for Economic Stability? An In-Depth Study of Sector Expansion and Economic Dynamics
India has emerged as one of the world's most appealing locations for renewable energy development. It has set lofty renewable energy goals to reach 450 gigawatts (GW) capacity by 2030. These aims indicate India's determination to move to greener and more sustainable energy sources. India has been investing in R&D to promote technological innovation in renewable energy. This includes improvements to solar photovoltaic technology, wind energy, energy storage technologies, and smart grid systems. Innovation is critical for improving efficiency, lowering prices, and increasing the reliability of renewable energy sources. This paper aims to analyse the linkages between economic growth and renewable energy usage in India. For this, the Granger Causality technique is adopted, and it is found that no short-run causality exists among the economic growth and RE installed capacity. However, Industrial Production Granger Causes both GDP and Renewable Energy Capacity. When the stock price data of the last five years of top renewable energy companies was also collected, it was found that all the companies are showing an upward trend. While renewable energy is growing rapidly, especially solar and wind power, it is insufficient to meet the bulk of India's energy demands. Renewables contribute to reducing carbon emissions and diversifying the energy mix, but they still account for a smaller percentage compared to thermal power. 2024, Creative Publishing House. All rights reserved.