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Predictors of online buying behaviour
This study creates a framework by looking into various research on customer acceptance of new selfservice technologies and internet purchasing behaviour systems. According to this research, customers' attitudes towards online purchasing are initially influenced by the direct impacts of relevant characteristics of online shopping. These characteristics include functional, utilitarian characteristics and usefulness, emotional and hedonic characteristics. It looks at the technology acceptance theory (TAM) established by David in 1989 and the theory of reasoned action (TRA) to understand factors determining the attitudes of users towards online shopping for users using technology. It also provides conceptual models by using the brand image of the online platform, past experiences of buyers, information related to the product, convenience of the shoppers and trust of the customers towards online shopping. 2024, IGI Global. All rights reserved. -
Successful footprints of ChatGPT deployments in the education sector: Pros outweigh cons by embracing ethics and etiquette
Artificial intelligence (AI) is essential in all aspects of life. One crucial area to examine is the integration of artificial intelligence in education. The true essence is in providing individuals with the necessary knowledge, skills, and values needed to have a fulfilling and meaningful life. Education must adapt to equip students with essential abilities to navigate life's challenges while upholding integrity in a dynamic world. Artificial intelligence (AI), shown by technologies such as ChatGPT, exhibits significant promise in educational environments. This chapter explores personalized learning enabled by artificial intelligence (AI). Furthermore, intelligent tutoring systems are also analyzed. The text delves into various facets of the educational system where ChatGPT might offer help. Additionally, offering explanations for the prohibition of Chat GPT in many countries and educational institutions. The discussion has focused on how AI affects the socio-economic gap in the education sector. 2024, IGI Global. All rights reserved. -
Household waste management policy and practices in bengaluru
Households play a very important role in waste management policy development and its implementation in any city. This study is done among households of 12 wards in Urban Bengaluru(India). It is observed that waste management is open of the most important issue among households and households in general are not satisfied by waste collection, segregation its transport service and maintenance of public places, provided by local municipal body. Garrett's ranking method is also used to give ranking for various waste management practices adopted by various wards. The results suggest that problems faced by households across the city is not same, also perception towards the policy and practices of local bodies towards waste management differs significantly across the city. Cleanliness of public places and waste collection process should be given highest priority by the policy makers. The study also determines a different perspective towards understanding behaviour of household. the policymakers may use this technique to identify specific geographic areas where immediate action is required. BEIESP. -
We wear multiple hats: Exploratory study of role of special education teachers of public schools in India
The role of special education teachers (SETs) is multifaceted. A gap was recognised in the literature in the lack of studies on the roles and responsibilities of SETs in India and the field realities of carrying out the role. The aim was to explore to what extent the special education teachers fulfil their roles and responsibilities. The following is an exploratory study, using open-ended questions that interviewed 12 SETs from five public schools in Delhi, India. The policy documents shared that the SETs were responsible for direct instruction to special needs students, parentteacher collaboration and documentation, including IEPs for students with special needs. But in practice, there were not any clear-cut boundaries, the SETs played multiple rolesSubject teacher, taking substitution periods, para teachers, these were keeping the SETs away from their core responsibilities. The results of the study demonstrated an undervaluation of the work of SETs and lack of support from the principal and regular teachers. The results concluded with recommendations for policy proposal with regards to defining the role of all stakeholders in an inclusive education school and improvements for the teacher education program. 2024 National Association for Special Educational Needs. -
Voicing Out Parental Experiences of Schooling Their Children with Learning Disabilities: A Qualitative Study of Inclusive Government Schools of India
The paper shone light on the lived experiences of parents of children with learning disabilities. The specific objective was to understand the challenges, experiences and aspirations of parents for their children. A phenomenological study was adopted for the study so as to focus on the experiences of the parents. Participants were parents (female- 17 and male- 3) of children in primary classes, who were identified through purposive sampling from government schools of Delhi, NCR from 3 underdeveloped areas of Delhi - Nangloi, Mangolpuri and Ranhaula. The data was collected by semi-structured interviews and later thematically analyzed. The findings were on the basis of the past and present experiences and further their future aspirations for the children. They revealed that the parents faced challenges with applying and issuance of the UDID certificates, but with the collaborative efforts of the special educator and the parents along with various support systems that are provided by the school their experiences became positive. It was also brought to light that the mother was the main caregiver in most of the cases. All the parents were worried, what will happen to their children if they are not there with them. They aspired that the students will be financially independent and have a safe future ahead of them. They dream of a society where all the students are equal in an inclusive environment. The Author(s) 2025. -
Creating inclusive spaces in virtual classroom sessions during the COVID pandemic: An exploratory study of primary class teachers in India
The research paper reports insights into the primary class teachers experiences and inclusive methodologies in India during virtual class sessions. Teaching online during the COVID pandemic has turned out to be an adaptive and transformative challenge for teachers. Though Indian teachers are used to the chalk-and-talk method, an online setup has compelled them to discover innovative strategies to maintain an inclusive classroom. It was found that teachers are using puppetry, storytelling, energizers, ice-breakers in their sessions to make it engaging. An in-depth study was undertaken to understand the experiences of five primary class teachers from private schools in India. Data thus collected were analyzed qualitatively. The study results demonstrated that the teachers had improved professionally they have become independent in using the internet and exploring new ways of teaching them per their needs. Nevertheless, it was also found that the schools lack support, fear among the teachers of being asked to quit the job, blocking students from the online class if they fail to pay the fees, and exorbitant salary cuts. The challenges related to young students were - lack of proper resources for online sessions, low attention span, technical distractions, lack of physical development, excessive interference of the parents and lack of socialization. The paper concludes with policy proposals regarding standardized online education platforms and provisions for proper resources for virtual class sessions to marginalized families to minimize India's digital divide. 2021 -
A First Report of Docosahexaenoic Acid-Clocked Polymer Enveloped Gold Nanoparticles: A Way to Precision Breast Cancer and Triple Negative Breast Cancer Therapy and Its Apoptosis Induction
Functionalized gold nanoparticles (GNPs) are extensively utilized in various disciplines due to their excellent bioactivity, biocompatibility, and extended drug half-life, influenced by the ligands and size that are changed on surfaces. In this study, we successfully fabricated GNPs coated with ligands containing docosahexaenoic acid (DHA) and polyethylene glycol (PEG) clocked by a carboxyl group. These nanoparticles are referred to as MPA@GNPs-PEG-DHA. The cytotoxicity results demonstrate that MPA@GNPs-PEG-DHA exhibits superior cell selectivity, explicitly inhibiting the proliferation of breast cancerous cells than noncancerous cell lines. Apoptosis is involved in the reduction of cell proliferation by MPA@GNPs-PEG-DHA, as demonstrated clearly through many assays measuring apoptotic index, including AO/EB staining, DAPI, annexin V-FITC staining, mitochondrial membrane potential (MMP), and reactive oxygen species (ROS) measurement. The efficacy of MPA@GNPs-PEG-DHA in inducing apoptosis was demonstrated by its inhibition of mitochondrial dysfunction by ROS. MPA@GNPs-PEG-DHA has the potential to improve the induction of apoptosis in breast cancerous cells. 2024 Wiley Periodicals LLC. -
A comparative study on decision tree and random forest using konstanz information miner (KNIME)
With vast amounts of data floating around everywhere, it is imperative to comprehend and draw meaningful insights from the same. With the proliferation of Internet and Information Technology, data has been increasing exponentially. The 5 Vs of data i.e. Value, volume, Velocity, variety and veracity will only make sense if we are able to examine the data and uncover the hidden, yet meaningful insights. With large data becoming a norm, a lot of data mining algorithms are available that help in data mining. We have tried to compare two classification algorithms, primarily Decision trees and Random forest. A total of 10 datasets have been taken from UCI Repository and Kaggle and with the help of Konstanz Information Miner (KNIME) workflows, a comparative performance has been made pertaining to the accuracy statistics of Random Forest and decision Tree. The results show that Random Forest gives better and accurate results for a dataset as compared to decision trees. 2020 SERSC. -
Minimizing the waste management effort by using machine learning applications
Waste management is a process of collecting, transporting, disposing, and monitoring waste materials generated by human activities. It is an essential part of maintaining public health, hygiene, and environmental sustainability. Waste management systems can be designed to handle different types of waste, such as household waste, industrial waste, hazardous waste, and medical waste. The increasing amount of waste has become a major issue for the development of sustainable communities. Machine learning can help solve this problem by allowing scientists to analyze and reduce waste. This chapter aims to provide a comprehensive overview of the various aspects of waste management using machine learning. The chapter covers the various aspects of waste disposal, generation, transportation, and collection. It also explores machine learning's potential in this area, such as data analysis and prediction. It additionally compiles case studies about how machine learning has been utilized in this field. 2024, IGI Global. -
Eco-friendly innovations in food packaging: A sustainable revolution
Packaging is crucial in ensuring the quality and safety of food, protecting it from various contaminants, and extending its shelf life. Materials used for packaging food must be economical, durable, and possess good barrier properties. One of the major challenges faced by the food industry is developing an eco-friendly, economical, and sustainable packaging system. The conventional materials, which majorly depend on petroleum-derived polymers, are associated with several significant problems, such as environmental pollution, depletion of resources, generation of single-use wastes, leakage of chemicals into food products, limited recycling, and so on. As the food sector focuses on reducing its environmental impact, by encouraging revolutionary changes for an effective sustainable food packaging approach. The core objective of industrial packaging was to innovate a biodegradable material, especially derived from renewable biomass resources as eco-friendly alternatives in the food industry. One of the significant trends involves production of bioplastics, which are derived from renewable polymers such as corn starch, sugarcane, or algae. These materials offer a viable alternative to traditional petroleum-based plastics, as they are often compostable or biodegradable. The development of advanced bioplastics with improved barrier properties and durability is gaining traction, addressing environmental and health concerns and functionalizing a packaging material. The present review discusses the limitations of conventional packaging materials used in the food industry and focuses on the various polymers derived from natural sources, their physio-chemical properties, and their potential application as a sustainable material that reduce carbon emission, and enhance preservation of food and ensure food safety. 2024 Elsevier B.V. -
Machine Learning Methods leveraging ADFA-LD Dataset for Anomaly Detection in Linux Host Systems
Advancement in network technology and revolution in the global internet transformed the overall Information Technology (IT) infrastructure and its usage. In the era of the Internet of Things (IoT) and the Internet of Everything (IoE), most everyday gadgets and electronic devices are IT-enabled and can be connected over the internet. With the advancements in IT technologies, operating systems also evolved to leverage these advancements. Today's operating systems are more user-friendly and feature-rich to support current IT requirements and provide sophisticated functionalities. On the one hand, these features enabled operating systems accomplish all current requirements, but on the other hand, these modern operating systems increased their attack surface considerably. Intrusion detection systems play a significant role in providing security against the broad spectrum of attacks on host systems. Intrusion detection systems based on anomaly detection have become a prominent research area among diverse areas of cyber security. The traditional approaches for anomaly detection are inadequate to discover the operating system level anomalies. The advancement and research in Machine Learning (ML) based anomaly detection open new opportunities to tackle this challenge. The dataset plays a significant role in ML-based system efficacy. The Australian Defence Force Academy Linux Dataset (ADFA-LD) comprises thousands of normal and attack processes system call traces for the Linux platform. It is the benchmark dataset used for dynamic approach-based anomaly detection. This paper provided a comprehensive and structured study of various research works based on the ADFA-LD for host-based anomaly detection and presented a comparative analysis. 2022 IEEE. -
Education suffering within structural inequalities: A Critical Discourse Analysis of a policy framework
Education acts as an important catalyst for socioeconomic and democratic evolution in society and is a critical tool for building an equitable system. In our paper, we have historicized one of the most important educational policies, viz. Samagra Shiksha Abhiyan (SAMSA) in India that carries large expectations to minimize the educational divide. We have studied the policy through the lens of Political Economy and have further critiqued it through the framework of Critical Discourse Analysis. We find in our paper that the budget allocated to SAMSA was revised in 2022, from its preceding years with a 28 per cent slash. We critically reflect on the principles mentioned in the policy and find that although there has been an attempt to mitigate the hazards of banking education the Public-Private Partnership initiative reinforces struggles for equitable education, and further, the privatization sets the government free from any accountability. Moreover, a constitutional right like the Right to Education (RTE) is not sufficient enough to meet the goals of universalisation of education. Besides, we analyse the principles such as Education for All, Equity, Equal Opportunity, Access, Gender Concern, Centrality of teacher, Moral Compulsion, and Convergent and integrated system of education management, and argue that although some of the facets of societal structural inequalities are addressed, however, there exists hardly a proper roadmap that could be monitoring the process of creating an inclusive educational paradigm. 2023, Institute for Education Policy Studies. All rights reserved. -
Fake News Detection Using TF-IDF Weighted with Word2Vec: An Ensemble Approach
Social media platforms' utilization for news consumption is steadily growing due to their accessibility, affordability, appeal, and ability to propagate misinformation. False information, whether intentionally or unintentionally created, is being disseminated across the internet. Certain individuals spread inaccurate information on social media to gain attention, financial benefits, or political advantage. This has a detrimental impact on a substantial portion of society that is heavily influenced by technology. It is imperative for us to develop better discernment in distinguishing between fake and genuine news. In this research paper, we present an ensemble approach for detecting fake news by using TF-IDF Weighted Vector with Word2Vec. The extracted features capture specific textual characteristics, which are converted into numerical representations for training the models and balanced dataset with the Random over Sampling technique. The implementation of our proposed framework utilized the ensemble approach with majority voting which combines 2 machine learning models like Random Forest and Decision Tree. The proposed strategy was adopted empirically evaluated against contemporary techniques and basic classifiers, including Gaussian Nae Bayes, Logistic Regression, Multilayer Perceptron, and XGBoost Classifier. The effectiveness of our approach is validated through the evaluation of the accuracy, F1-Score, Precision, Recall, and Auc curve, yielding an impressive accuracy score of 94.24% on the FakeNewsNet dataset. 2023, Ismail Saritas. All rights reserved. -
ENHANCING FAKE NEWS DETECTION ON SOCIAL MEDIA THROUGH ADVANCED MACHINE LEARNING AND USER PROFILE ANALYSIS
Social media news consumption is growing in popularity. Users find social media appealing because it's inexpensive, easy to use, and information spreads quickly. Social media does, however, also contribute to the spread of false information. The detection of fake news has gained more attention due to the negative effects it has on society. However, since fake news is created to seem like real news, the detection performance when relying solely on news contents is typically unsatisfactory. Therefore, a thorough understanding of the connection between fake news and social media user profiles is required. In order to detect fake news, this research paper investigates the use of machine learning techniques, covering important topics like feature integration, user profiles, and dataset analysis. To generate extensive feature sets, the study integrates User Profile Features (UPF), Linguistic Inquiry and Word Count (LIWC) features, and Rhetorical Structure Theory (RST) features. Principal Component Analysis (PCA) is used to reduce dimensionality and lessen the difficulties presented by high-dimensional datasets. The study entails a comprehensive assessment of multiple machine learning models using datasets from "Politifact" and "Gossipofact," which cover a range of data processing methods. The evaluation of the XGBoost classification model is further enhanced by the analysis of Receiver Operating Characteristic (ROC) curves. The results demonstrate the effectiveness of particular combinations of features and models, with XGBoost outperforming other models on the suggested unified feature set (ALL). 2023 Little Lion Scientific. -
Do all shocks produce embedded herding and bubble? An empirical observation of the Indian stock market
Herding has a history of igniting large, irrational market ups and downs, usually based on a lack of fundamental support. Intuitively, most herds start with an external shock. This empirical study seeks to detect shock-induced herding and the creation of nascent bubbles in the Indian stock market. Initially, the multifractal form of the detrended fluctuation analysis was applied. Then the Reformulated Hurst exponent for the Bombay stock exchange (BSE) was determined using Kantelhardt's calibration. The investigation found evidence of high-level herding and a bubble in 2012, with a high value of Hurst Exponent (0.7349). The other years of the research period (2011, 2013, 2016, 2018, 2020-2021) observed mild to significant herding with comparatively lower Hurst values. The results confirm that herding behavior occurs during a crisis and harsh situations emitting shocks. The study concludes that shock-based herding is prevalent in all six shocks: the economic meltdown, commodities and currency devaluation, geo-political problems, the Central Bank's decision on liquidity management, and the Pandemic. Additionally, the years following the Financial Crisis and the years of the Pandemic are when herding and bubble are prominent. Tabassum Khan, Suresh G., 2022. -
Did Russia's Invasion of Ukraine Induce Herding Behavior in the Indian Stock Market?
This study empirically examines the herding behavior of the Indian stock market investors during the heightened geopolitical tensions between Russia and Ukraine in 2022. An intensified Russia-Ukraine geopolitical event window was constructed, and the high-frequency trading data (intraday) of the Nifty index was analyzed using Multifractal Detrended Fluctuation Analysis (MFDFA) to compute the 5th-order Hurst exponent (Hq (5)) that detects herding behavior. The study's empirical results revealed the presence of profound herding behavior during the intensified Russia-Ukraine geopolitical event window. The study contributes to the existing literature on herding behavior by examining the impact of a geopolitical event on the Indian stock market. Additionally, the study utilizes MFDFA to compute Hurst exponents, a relatively new approach to detecting herding behavior in financial markets. The findings of this study may assist investors and policymakers in understanding the impact of geopolitical events on financial markets and the potential for herding behavior among investors during times of heightened uncertainty. The study's results demonstrate the interconnectedness of global events and financial markets, highlighting the need for policymakers to consider the potential social and economic consequences of geopolitical events. 2023 The Author(s). -
Marine macrolides as an efficient source of FMS-like tyrosine kinase 3 inhibitors: A comprehensive approach of in silico virtual screening
Marine organisms are a definitive source of antibiotics and kinase inhibitors which provide cues for discovering novel drug leads. Marine macrolides are getting much attraction due to their enzyme inhibitory potential. The present study comprehensively dealt with the virtual screening and structure-based prediction of macrolide compounds against FMS-like tyrosine kinase 3 receptors (FLT3). The FLT3 was chosen as a biological target against the 990 marine macrolides. Before the virtual screening of macrolide compounds, validation of molecular docking was carried out by re-docking of co-crystallized Gilteritinib within the FLT3. Among the selected 990 candidates of marine macrolides, 311 were failed due to the generation of insufficient conformers. Amongst the successful compounds, 22 compounds were also failed to dock within the receptor, while the remaining 657 marine macrolide entities elicited successful docking. The HYBRID Chemguass4 Score ranged from -10.17 to -0.02. This vast difference in the HYBRID ChemGuass4 score is attributed to the difference in binding potential with the receptor's binding pocket. The top ten compounds were selected based on the HYBRID ChemGuass4 Score lower than -8.0 against FLT3. The pharmacokinetics and ADME properties revealed the drug likeliness of the macrolides. 2022 SAAB -
Simulation of IoT-based Smart City of Darwin: Leading Cyber Attacks and Prevention Techniques
The Rise of the Internet of Things (IoT) technology made the world smarter as it has embedded deeply in several application areas such as manufacturing, homes, cities, and health etc. In the developed cities, millions of IoT devices are deployed to enhance the lifestyle of citizens. IoT devices increases the efficiency and productivity with time and cost efficiency in smart cities, on the other hand, also set an attractive often easy targets for cybercriminals by exposing a wide variety of vulnerabilities. Cybersecurity risks, if ignored can results as very high cost to the citizens and management as well. In this research, simulated IoT network of Darwin CBD has been used with different IoT simulation tools. The treacherous effects of vulnerable IoT environment are demonstrated in this research followed by implementation of security measures to avoid the illustrated threats. 2023 IEEE. -
Comparing machine learning and ensemble learning in the field of football
Football has been one of the most popular and loved sports since its birth on November 6th, 1869. The main reason for this is because it is highly unpredictable in nature. Predicting football matches results seems like the perfect problem for machine learning models. But there are various caveats such as picking the right features from an enormous number of available features. There have been many models which have been applied to various football-related datasets. This paper aims to compare Support Vector Machines a machine learning model and XGBoost an Ensemble learning model and how Ensemble Learning can greatly improve the accuracy of the predictions. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved.