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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. -
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. -
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. -
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 -
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. -
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. -
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. -
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. -
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. -
Implementation of Supervised Pre-Training Methods for Univariate Time Series Forecasting
There has been a recent deep learning revolution in Computer Vision and Natural Language Processing. One of the biggest reasons for this has been the availability of large-scale datasets to pre-train on. One can argue that the Time Series domain has been left out of the aforementioned revolution. The lack of large scale pretrained models could be one of the reasons for this.While there have been prior experiments using pre-trained models for time series forecasting, the scale of the dataset has been relatively small. One of the few time series problems with large scale data available for pre-training is the financial domain. Therefore, this paper takes advantage of this and pretrains a ID CNN using a dataset of 728 US Stock Daily Closing Price Data in total, 2,533,901 rows. Then, we fine-tune and evaluate a dataset of the NIFTY 200 stocks' Closing Prices, in total 166,379 rows. Our results show a 32% improvement in RMSE and a 36% improvement in convergence speed when compared to a baseline non pre trained model. 2023 IEEE. -
The Capital structure puzzle
International Journal of Research in Commerce & Management Vol.4, No.03, pp.134-136 ISSN No. 0976-2183 -
Context Driven Software Development
The Context-Driven Software Development (CDSD) is a novel software development approach with an ability to thrive upon challenges of 21st century digital and disruptive technologies by using its innovative practices and implementation prowess. CDSD is a coherent set of multidisciplinary innovative and best practices like context-aware and self-adaptive system modelling, human-computer interaction, quality engineering, software development-testing-and continuous deployment frameworks, open-source tools-technology-and end-to-end automation, software governance, engaging stakeholders, adaptive solutioning, design thinking, and group creativity. Implementation prowess of CDSD approach stems from its three unique characteristics, namely, its principles, Contextualize-Build-Validate-Evolve (CBVE) product development element, and iterative and lean CDSD life cycle with Profiling, Contextualizing, Modelling, Transforming, and Deploying phases with in-process and phase-end Governance and Compliances. CDSD approach helps to address issues like complexity, software ageing, risks related to internal and external ecosystem, user diversity, and process-related issues including cost, documentation, and delay. 2021, Springer Nature Switzerland AG. -
A study on the perception of MOOC (Massive Open Online Course) amongst the students of Christ University, Bengaluru /
Massive open online courses (MOOC) are a recent innovation in the field of online learning. Several top-tier universities around the world have started offering MOOC programmes in a wide array of professional, technical as well as creative fields. Top MOOC providers such as Coursera, Udacity and edX have a student fellowship from all across the world, pursuing one or more from the thousands of courses offered by these MOOC giants. -
Quantum Convolutional Neural Network for Medical Image Classification: A Hybrid Model
This study explores the application of Quantum Convolutional Neural Networks (QCNNs) in the realm of image classification, particularly focusing on datasets with a highly reduced number of features. We investigate the potential quantum computing holds in processing and classifying image data efficiently, even with limited feature availability. This research investigates QCNNs' application within a highly constrained feature environment, using chest X-ray images to distinguish between normal and pneumonia cases. Our findings demonstrate QCNNs' utility in classifying images from the dataset with drastically reduced feature dimensions, highlighting QCNNs' robustness and their promising future in machine learning and computer vision. Additionally, this study sheds light on the scalability of QCNNs and their adaptability across various training-test splits, emphasizing their potential to enhance computational efficiency in machine learning tasks. This suggests a possibility of paradigm shift in how we approach data-intensive challenges in the era of quantum computing. We are looking into quantum paradigms like Quantum Support Vector Machine (QSVM) going forward so that we can explore trade offs effectiveness of different classical and quantum computing techniques. 2024 IEEE. -
Gut Homeostasis; Microbial Cross Talks In Health and Disease Management
The human gut is a densely populated region comprising a diverse collection of microorganisms. The number, type and function of the diverse gut microbiota vary at different sites along the entire gastrointestinal tract. Gut microbes regulate signaling and metabolic pathways through microbial cross talks. Host and microbial interactions mutually contribute for intestinal homeostasis. Rapid shift or imbalance in the microbial community disrupts the equilibrium or homeostatic state leading to dysbiosis and causes many gastrointestinal diseases viz., Inflammatory Bowel Disease, Obesity, Type 2 diabetes, Metabolic endotoxemia, Parkinsons disease and Fatty liver disease etc. Intestinal homeostasis has been confounded by factors that disturb the balance between eubiosis and dysbiosis. This review correlates the consequences of dysbiosis with the incidence of various diseases. Impact of microbiome and its metabolites on various organs such as liver, brain, kidney, large intestine, pancreas etc are discussed. Furthermore, the role of therapeutic approaches such as ingestion of nutraceuticals (probiotics, prebiotics and synbiotics), Fecal Microbial Treatment, Phage therapy and Bacterial consortium treatment in restoring the eubiotic state is elaborately reviewed. 2021 The Author(s). Published by Enviro Research Publishers. -
Author profiling: Age prediction of blog authors and identifying blog sentiment
Authorship profiling is about finding out different characteristic of an author like age, gender, native languages, education background etc., by finding out the patterns in their writing. Blog authors write about a lot of topics like purchase decisions, digital advertising, personality development, fitness, technology updates etc., and these authors play an influential role on its readers. In this paper, we are categorizing the blog authors in three different age groups based on the content available from the blog. Natural Language Toolkit (NLTK) is a set of libraries used for natural language processing to distinguish among the different writing pattern of the author based on the different age groups. NLTK helps to make analysis on the words of the blogs which is an important feature in our research. We also wanted to conduct sentiment analysis on the blog in order to understand the insight on how the author feels about the blog topic. Thus, we have used Nae Bayes Classifier for doing the analysis and considered two sentiments for the same: positive and negative. An average accuracy of 66.78% was achieved in predicting the age of authors. From the sentiment analysis we figured out that elder authors tend to have more positivity in their blogs as compared to younger authors. 2019, Institute of Advanced Scientific Research, Inc.. All rights reserved. -
Complicated Grief during COVID-19: An International Perspective
Cultures across the globe have evolved time-tested rituals to honor those who die and offer solace and support to survivors with the goal of helping them to accept the reality of the death, cope with the feelings of loss, adjust to life without the deceased, and find ways to maintain a connection to the memory of the deceased. The COVID-19 pandemic has disrupted these rituals and brought significant changes to the way we mourn. Specifically, public health responses to COVID-19 such as social distancing or isolation, delays or cancellations of traditional religious and cultural rituals, and shifts from in-person to online ceremonies have disrupted rituals and thus made it more difficult to access support and complete the psychological tasks typically associated with bereavement. This paper conceptualizes the common bereavement tasks including emotion-focused coping, maintaining a connection to the deceased, disengagement and reframing death and loss, and problemfocused coping. It provides examples of how the COVID-19 pandemic has altered mourning rituals across several cultures and religions and contributed to prolonged grief disorder as defined by the ICD-11 that includes depressive symptoms and post-traumatic stress. Early evidence suggested that the suddenness of loss, the social isolation, and the lack of social support often associated with COVID-19-related death are salient risk factors for complicated grief. As a consequence, psychological assessments, grief counseling, and mental health support are needed by families of patients who died from COVID-19. These services must be essential components of any comprehensive public health response to the pandemic. 2022 Hogrefe Publishing. -
An empirical analysis of android permission system based on user activities
In today's world there has been an exponential growth among smart-phone users which has led to the unbridled growth of smart-phone apps available in Google play store, app store etc., In case of android application, there are many free applications for which the user need not shell out a penny to use the services. Here the magic word is "free" which entices millions of pliant people into installing those apps and giving unnecessary access to their data and device control. Current studies have shown that over 70% of the apps in market, request to gather data digressive to the most functions of apps that might cause seeping of personal data or inefficient use of mobile resources. Of late, couple of malignant applications gather unobtrusive information of the user through third-party applications by increasing their permissions to high-level on the Android Operating System. Android permission system provides, the user access to the third party apps and in return based on the permissions granted by the user, an app can access the related resource from the user's mobile. A user is bound to grant or deny permits during the installation of the application. For the most part, users don't focus on the asked permissions, or sometimes users do not understand the meaning of the permission and install the app on their device. They allow a way for attackers to perform the malicious task by demanding for more than expected set of permissions. These extra permissions permit the attacker to exploit the device and also retrieve sensitive information from it. In this research paper we describe how permission system security can create an awareness among the users that would assist them in deciding on permission grants. This improved and responsible user activities in Android OS can help the users in utilizing their device securely. 2018 Ankur Rameshbhai Khunt and P. Prabu. -
Inhibiting extracellular cathepsin d reduces hepatic steatosis in spraguedawley rats y
Dietary and lifestyle changes are leading to an increased occurrence of non-alcoholic fatty liver disease (NAFLD). Using a hyperlipidemic murine model for non-alcoholic steatohepatitis (NASH), we have previously demonstrated that the lysosomal protease cathepsin D (CTSD) is involved with lipid dysregulation and inflammation. However, despite identifying CTSD as a major player in NAFLD pathogenesis, the specific role of extracellular CTSD in NAFLD has not yet been investigated. Given that inhibition of intracellular CTSD is highly unfavorable due to its fundamental physiological function, we here investigated the impact of a highly specific and potent small-molecule inhibitor of extracellular CTSD (CTD-002) in the context of NAFLD. Treatment of bone marrow-derived macrophages with CTD-002, and incubation of hepatic HepG2 cells with a conditioned medium derived from CTD-002-treated macrophages, resulted in reduced levels of inflammation and improved cholesterol metabolism. Treatment with CTD-002 improved hepatic steatosis in high fat diet-fed rats. Additionally, plasma levels of insulin and hepatic transaminases were significantly reduced upon CTD-002 administration. Collectively, our findings demonstrate for the first time that modulation of extracellular CTSD can serve as a novel therapeutic modality for NAFLD. 2019 by the authors.