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A Study on Revolution of Healthcare Industry with Transformational Artificial Intelligence Tool
The world is under the turbulence of the transformation from the age-old traditional healthcare systems to contemporary, patient centric and clinicians need based operations. The introduction of Artificial Intelligence in the healthcare industry though besets with a bunch of demerits deserves special mention with respect to its over brewing merits. In contrast with the global standard, India, a developing country has obvious financial and infrastructure specific bottlenecks in bringing the success of the mass implementation of Artificial intelligence in the healthcare operations. However, the genuine and continuous efforts are made in streamlining the critical and stereotyped operations for the benefits of the medical service seeker and also for the competitive survival of medical service provider. The present study focused on the historical development of Artificial Intelligence in healthcare, the reason of its gradual popularity, the application of the tool, some of the notable used cases where the Artificial Intelligence gained its momentum and a host of pros and cons in dealing with it. The study also featured the futuristic intensity of its application of Artificial Intelligence in the healthcare units in India to ease out the pain of availing the emergent medical services without the typical intervention of the medical experts and on the contrary also the administering the hassle-free diagnostic procedures with transparency and smart approach. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
A Study on Robust Feature Selection Methods Using LASSO, LASSO Variants and Ridge Regression in Sports
Regularization tools like Lasso have made a substantial progresses in regression modelling, particularly to high-dimensional data and multicollinear data. Whereas Ridge regression uses L2 regularization to address the problem of multicollinearity, Lasso uses L1 regularization to conduct regression and feature selection together. The weaknesses of Lasso under correlated predictors have inspired the creation of a number of improved variants. The present paper will do a comparative analysis of simple Lasso, Ridge and Lasso extensions like Elastic Net, Adaptive Lasso, Group Lasso and Relaxed Lasso on real-world sports data, with special focus on a new implementation of the improved Relaxed Lasso that involves three optimization strategies: systematic grid search, extended lambda sequences, and nested cross-validation structures. The comparison has been done in terms of feature selection, resistance to outliers, and prediction accuracy on Ice Hockey, Cricket, and NBA data. Various measures of errors are used to analyze models: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Coefficient of Determination (R2 ). The results have shown that the Enhanced Relaxed Lasso performs best regarding improvements in performance especially in cricket data and still serves as a competitive data in different sporting scenarios. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
A study on role of cooperative banks in micro-finance with special reference to Karnataka /
The International Journal of Business & Management, Vol.4, Issue 10, pp.9-11, ISSN No: 2321-8916. -
A Study on Sense of Community: Case Example of Public Housing Project, Bengaluru, India
Background: In the realm of collective public housing, certain societal segments currently favor low-rise residential blocks due to their affordability and lower number of dwelling units per block, thus affording increased privacy for residents. However, the concept of associating residents benefits with social relationships has yet to garner sufficient attention. Objective: This article seeks to understand and examine the impact of public housing on the sense of community (SOC) within a public housing community. Methods: The study was conducted at the Bangalore Development Author-ity Jnanabharathi Residential Enclave in Kengeri, Bengaluru, Karnataka. This understanding was attained through a comprehensive review of existing literature and an on-site evaluation carried out using questionnaire surveys and photographs for visual interpretations. Findings: The results indicated a relatively deficient sense of ownership within the community. Homeowners exhibited higher levels of community involvement and engagement in various activities compared with tenants. Conclusions: Furthermore, the study recommends that public authorities reevalu-ate their perspectives on public housing developments and develop a policy-orien-ted approach for planning, design, and additional amenities to foster a stronger SOC belonging. 2023 Springer Publishing Company. -
A study on significance of cashback offered by online companies and its impact on customer preferences in online purchases
The emergence of e-commerce is redefining the entire business process across the word. This mode of doing business is presently being used in every industry and sale of all products. The retail industry has seen the major shift towards e commerce business model. With more and more customers opting for online purchases, a number of companies have entered into this sector. This had led to extreme competition in the market. The companies compete each other fiercely with sharp marketing tactics. The price based sales strategy is the one that attracts the customers more. The research study is being done to understand the significance of the cashback strategy used by online companies to generate more sales. The study will try to analyse the perception of the customers towards cashbacks and what are the factors related to cashbacks that attracts them. The findings will help the online companies in designing the best cashback model. The study has been carried out in Bangalore as it is one of the leading locations for online business. 2019, Institute of Advanced Scientific Research, Inc. All rights reserved. -
A study on smart device application platform
Cloud Computing is considered to be one of the hottest research areas as it provides an approach through which the data is stored and accessed over the Internet in a virtual environment. The main idea to adapt this technology is that it shares the available resources rather than having separate local servers. This technology plays a crucial role in the healthcare sector as the healthcare industries believe that by incorporating cloud services within the healthcare sector it could provide quality services to the patients. Many industrial specialists suggest ways of converting the huge amount of data collected from the healthcare into meaning information and later sharing this valuable information to the user at the right time. The smart device is an electronic rig that is efficient to answer, sympathize and interact mutually with its users and other smart devices, one of the upcoming smart devices are smart shirts. Smart shirts allow the user to share information like Facebook or LinkedIn profile details. This paper focuses on providing wearable devices to the user in order to have monitored over his/her health. Springer Nature Singapore Pte Ltd. 2019 -
A Study on Student Cyber Safety Consciousness in the Light of Online Learning
Our world online and networked is immersed under a wave of populism; populism spreads on the wings of internet. The recent technological advancements like the use of social media platforms and different applications made the information exchange faster and more efficient making the information access easier. To keep our information, gadgets such as cell phones, laptops, desktops, and tablets and also the internet safe, knowledge of cybersecurity is vital everywhere. In many colleges and Universities who are in to interconnected complex systems, data privacy is a huge challenge among their users. In most of the situations, due to lack of knowledge and awareness, users may engage in data breaches knowingly or unknowingly and the complete interconnected systems among the users may have a consequence of a cybercrime. This article seeks to unpack the rise of cyber-crimes and its relationship to cyber security among student groups during the pandemic where much of their interaction is online. The research aims to inquire in to the level of knowledge and awareness on cybersecurity among students during their online learning interaction using a well-structured questionnaire. The questionnaire will be focused on five parts: Awareness and Knowledge, Monitoring and Privilege, Security and Prevention, Protection from malware s and usage of removable Devices. The study is conducted using quantitative research methodology to quantitatively evaluate the knowledge of cybersecurity and inculcate an awareness against Cybercrime protection among the students. Finally, based on the analysis of collected data we present recommendations which will not forego the safety concerns for e mails, viruses, phishing, pop-up windows and forged ads which is a common problem. Some technological solutions and paths for the regulation of the cybercrimes are suggested to the respondents at the end. 2022 IEEE. -
A Study on the Bank Financing of SMEs in India
The International Journal's Research Journal of Social Science & Management, Vol-2 (7), pp. 104-108. ISSN-2251-1571 -
A Study on the Effect of Canny Edge Detection on Downscaled Images
Abstract: Nowadays user devices such as phones, tablets etc. allows processing the images with help of high-end applications and softwares developed. Most of the times, the images are downscaled to make them compatible with these end devices. This leads to the loss of image quality. This loss of information on downscaling an image results in distortion of edges and while zoomed in results into a blurred image. As the edge detection is a basic step for many image processing applications such as object detection, object segmentation, object recognition, etc. It is necessary to know the impact of edge detection on downscaled image. In this paper, we are using Canny Edge detection method to detect the edges. The original images are downscaled using different interpolation methods. Canny Edge detection is applied on original images and downscaled images to compare the distortion in the edges. We used Structural Similarity Index Method for comparison. We are also comparing execution time taken by Canny Edge Detection on different interpolation methods to check for optimal interpolation method. We observed that the distortion in edges and time efficiency differ for different interpolation methods which are detailed below in the result section. As blurring is also a disadvantage of downscaling, we are applying Gaussian Blur on the images to compare the blurring due to Gaussian blur technique and blurring due to downscaling. 2020, Pleiades Publishing, Ltd. -
A Study on the Effect of Food Advertisements on Children and their influence on Parents Buying Decision
International Journal of Research in Commerce and Management Vol. 3, No. 7, pp 92-104, ISSN No. 0976-2183 -
A Study on the Efficacy of Homogeneous and Heterogeneous Stacking in Machine Learning
This study addresses the crucial issue of early and accurate plant disease diagnosis by comparing the performance of homogeneous and heterogeneous stacking models. The study seeks to introduce a novel homogeneous multi-layered stacking model that combines the Light Gradient Boosting Method (LightGBM) and Extreme Gradient Boosting (XGBoost) for plant disease detection and compare it with a heterogeneous stacking model that employs diverse classifiers. While traditional methods typically use basic stacking techniques, this research explores the complexities of various model architectures. By leveraging the strengths of both LGBM and XGB classifiers, the approach aims to deliver a highly accurate and efficient disease detection system. A comprehensive evaluation reveals that the homogeneous stacking model achieves superior performance, with a ROC AUC of 85.12%, compared to 83.09% for the single LGBM model. The study utilizes metrics such as AUC-ROC curves, accuracy, and precision-recall curves to assess performance. Future work will focus on integrating these models with real-time monitoring systems and extending their applications to a wider range of crops and environmental conditions. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
A Study on the Ethics of using Artificial Intelligence in Mental Health Treatment and its Legality
The development of artificial intelligence (AI) has transformed mental health care through offering new and feasible solutions to old assumptions. The moral concerns related to the use of AI in the mental health, however, could not be overlooked. A thorough grasp of how AI can be used throughout the patient journey is essential to advancing AI technology in the realm of mental health and overcoming its present restrictions. To reduce it to three columns, or one dataset, five Facebook datasets were gathered from Kaggle. The preprocessing procedure enhances the dataset's quality by using user tweets. Four datasets about depression were taken from the Kaggle website. After the preprocessing is finished, we will refine four pre-trained BERT models using the Hugging Face package. We will be able to create a predictive model for identifying depression with this method. The effectiveness of our refined BERT models for depression identification was assessed using a number of metrics. Our healthcare system could be greatly enhanced by AI, but we can only realise this potential if we begin addressing the moral and legal issues that currently confront us. 2025 IEEE. -
A Study on the Factors Affecting Infants' Health-Related Issues and Child Mortality using Machine Learning
Child mortality and infant health-related issues remain significant challenges worldwide. Understanding the factors that influence these outcomes is crucial for implementing effective interventions and improving child health outcomes. In this study, we employ machine learning techniques to identify and analyze the key factors affecting infants' health-related issues and child mortality. Further, we identify several significant factors that influence infants' health-related issues and child mortality. These factors include maternal health indicators, access to healthcare services, socioeconomic status, environmental factors, and demographic characteristics. The machine learning models provide insights into the relative importance of these factors, enabling policymakers and healthcare professionals to prioritize interventions and allocate resources effectively. Additionally, we investigate the potential interaction effects among these factors and their impact on child health outcomes. This analysis helps in understanding the complex relationships and causal pathways involved in infants' health-related issues and child mortality. The findings of this study contribute to the existing knowledge by leveraging machine learning techniques to identify and analyze the factors affecting infants' health-related issues and child mortality. The insights gained from this research can inform evidence-based policies and interventions aimed at reducing child mortality rates and improving infant health outcomes globally. By addressing the underlying factors identified through this study, we can work towards achieving better health outcomes for infants and reducing the burden of child mortality worldwide. 2023 IEEE. -
A study on the factors affecting usage of voice assistants and the interface transition from touch to voice
The interface simplicity has always been one of the most important factors which makes any new technology or device successful. Once an individual gets attached to a particular interface it becomes easy for them to use any devices which follows the same interface pattern. But to adapt to a new interface for the same device or the same need it will take a lot of effort from both the user and the companies which advances those to support each other to make the interface shift happen. The timespan required for this interface shift depends on the mindset of each individual and the simplicity of the proposed interface. Voice Assistants (VA) are an important achievement, which have become an inseparable and integral part of many smart devices. The mobile penetration in India has allowed rapid acceleration among metropolitan Indian adults in the usage of the wearable devices and other such smart technologies. Voice as an interface is going to improve the next generation of social conversation, content searches and medium of commerce. The rapidly increasing competition in this segment has led to several improvements. We already have many such voice-enabled devices that help us to set routines, automate the home appliances and provides us on-demand information. Also, the smart speakers category in Indiagrew 43 per cent in the second quarter of 2018.Many big corporates like Amazon, Apple, Google and Microsoft offers an entire digital platform infrastructure that can be controlled by voice assistants. The future of Voice Assistants depends to a large extent on how natural and fluid the communication with the user can take place. The interface transition from touch to voice has several factors involved in it. This study is majorly to find out what are the major factors which are influencing this transition and how relevant are these identified factors for the transition to happen in Indian market. 2020 SERSC. -
A Study on the Factors Influencing Customer Satisfaction in Multi-brand Apparel Retail
International Academic Research Journal of Business and Management Vol.1, Issue No. 7 ISSN No. 2227-1287 -
A study on the impact of brand preference and furniture on consumer preference of coffee houses
The food and beverage industry in India is developing at a rapid pace. These changes need to be met by the various sectors and runners in the business to be able to satisfy their customers. This statement applies most importantly for the coffee house industry, as today consumers are looking to use these spaces for different purposes. The study revolves around the coffee houses in Bangalore, India. The social aspects of the food and beverage industry, inclined towards coffee houses will be studied with various elements. It aims at studying the impact of elements including music, brand preference, taste preference, furniture, lighting and crown, on consumer preference to visit a coffee house. A total of 371 responses were collected, which included corporate and students residing in Bangalore. 2019 by Advance Scientific Research. -
A Study on the Impact of Brick and Mortar Stores and e-Commerce on Impulsive Buying Behaviour of Consumers
In the changing business landscape in retail and e-commerce, impulsive buying behaviour has played a significant role in the field of marketing and consumer psychology. The study aims to compare the impulsive buying behaviour in brick-and-mortar stores and e-commerce platforms. To execute the research, the primary data was collected through a structured questionnairethe data from collected from 300 respondents who were living in urban Bengaluru. The findings revealed that the physical stores stimulate impulsive buying through the sensory cues, through various internal promotional activities, and also through product gratification. The e-commerce also triggers impulsive buying with the help of recommendations, which are driven by algorithms, with limited-period offers, lucrative deals, discounts, and bundle offers. On the other hand, the demographic variables also have an impact on impulsive buying behavior. The research highlights the ever-evolving nature of consumer behaviour in the digital era and provides quality information that would be used as tactics to trigger impulsive buying. The research paper concludes with practical inputs for companies and marketing agencies. The research can be further extended to various other Omni-channel. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
A Study on the impact of print advertisement on the youth population
International Journal of Multidisciplinary Research Vol. 1, Issue 12 (IV) pp. 91-98, ISSN No. 2277-9302 -
A Study on the Indian Small Car Market and Factors Influencing Customers' Decisions Towards Purchase of Small Cars
International Journal of Research in Computer Application & Management, Vol-2 (11), pp. 65-69. ISSN-2231-1009 -
A Study on the Influence of Geometric Transformations on Image Classification: A Case Study
The present research work involves the study of the geometrical transformations which influences the training and validation accuracies of machine learning models. For the study, rice plant leaf disease dataset of 2096 images consisting of 4 classes with 523 images per class were used. The dataset subjected to 24 models out of which three models namely - DenseNet201, Densenet169 and InceptionResNetV2 are selected based on highest training accuracy and less difference between training and validation accuracy. To evaluate the performance of the selected three models, loss functions and accuracies have been computed. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.