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Enhancing Customer Experience and Sales Performance in a Retail Store Using Association Rule Mining and Market Basket Analysis
The retail business grows steadily year after year andemploys an abounding amounts of people globally, especially with the soaring popularity of online shopping. The competitive character of this fast-paced sector has been increasingly evident in recent years. Customers desire to blend the advantages of old purchasing habits with the ease of use of new technology. Retailers must thus guarantee that product quality is maintained when it comes to satisfying customer demands and requirements. This research paper demonstrates the potential value of advanced data analytics techniques in improving customer experience and sales performance in a retail store. Apriori, FP-Growth, and Eclat algorithms are applied in the real time transactional data to discover sociations and patterns in transactional data. Support, confidence and lift ratio parameters are used and apriori algorithm puts out several candidate item sets of increasing lengths and prunes those that fail to offer the assistance that is required threshold. We identified lift values are more when considering frozen meat, milk, and yogurt. if the customer decides to buy any of these items together, there is a chance that the customer will buy 3rd item from that group. Research arrived High confidence score is for Items like Semi Finished Bread and Milk so these products should be sold together, Followed by Packaged food and rolls. As retailers continue to face increasing competition and pressure to improve their operations, The aforementioned techniques may provide you a useful tool to comprehend consumer buying habits and tastes and for utilising that knowledge to come up with data-driven decisions that optimise product placement, enhance customer satisfaction, and attract sales. 2023 IEEE. -
Protection of Artificial Intelligence Autonomously Generated Works under the Copyright Act, 1957-An Analytical Study
Artificial Intelligence (AI) is not new anymore; it has become a new normal. In the present 3A era (Advanced, automated and autonomous), the Next Rembrandt paintings, Shimons lyrics and songs and Bot Dylans Irish folk songs are the works generated by the AI without any considerable human contribution. In the US, the Copyright Act, 1976 does not protect the works generated independently by the AI without human intervention and thus dropping such works in the public domain immediately after their creation. However, in the UK, the Copyright, Patents and the Designs Act, 1988 under Section 9 (3) attributes copyright to the person by whom the arrangements necessary for the creation of the work are undertaken in case of AI generated works. India has taken a giant leap by considering AI as the joint author along with the human responsible for the creation of work. However, there is not much comprehensive literature available that focuses on the impact of AI being considered as a joint author. This paper aims to create a concrete foundation by emphasising such impact under the Copyright Act, 1957. Furthermore, the paper considers the stance of the US, UK and Australia in protecting AI generated works to suggest measures to the current copyright regime in India. 2023, National Institute of Science Communication and Policy Research. All rights reserved. -
Social Identity of Kodavas Understanding Evolution and Transitions
The Kodavas of Kodagu district in Karnataka have a distinct social structure and follow a set of unique social codes and values peculiar to the community. Various influences have resulted in shifting social identities, which maybe a potential indicator of an identity crisis within the group. The present study follows a Constructivist Grounded Theory approach to inquiry, to arrive at an analytical schema of the process of social identity formation of the Kodavas. The analysis of data collected from forty-one middle and older adults, highlight the core traditional attributes of the Kodava identity, factors contributing to identity transition and its reflection in contemporary times. 2023 Tata Institute of Social Sciences. All rights reserved. -
Yield management in hotel industry: An exploratory study on selected northern states of India: A time series analysis
Asian Journal of Research in Business Economics and Management, Vol. 7, Issue 3, pp. 37-63, ISSN No. 2249-7307. -
Empowering women through livelihood interventions: Case studies from an impoverished community
This chapter looks at the influence of a livelihood project in empowering women belonging to an impoverished community from one of the most backward regions of the state of Karnataka in Southern India. Jamkhandi taluq of Bagalkote district is one of the poorer taluqs in the state, with a sex ratio of 938 and a female literacy rate of 50.75%. The Centre for Social Action began working in the area around a decade ago. The livelihood project was an offshoot of a project on Population displacement that was undertaken in the region. CSA adopted the Self-Help Approach (SHA) to meet the needs of this community. This gave the necessary impetus for the creation of a livelihood project for disadvantaged women. The central theme of the chapter is to study the extent of empowerment that is evident among the project's women beneficiaries. This chapter presents the evidence of empowerment using the qualitative case study methodology using ten cases. The theoretical framework provided by the 'Three Dimensional Model of Women Empowerment' is used to present the analysis. Document review and in-depth interviews are the prominent data sets used to present the study's major findings. The hybrid approach to coding and thematic analysis is used to integrate the insights from the theory used as well as observations from the study. Both within-case analysis and cross-case analysis are used for analysis. The personal, relational, and societal dimensions of empowerment are presented through themes emerging from the data. The implication of the chapter is the reiteration of the efficacy of the model in empowering women. This model can be replicated in other project areas, and livelihood strategies can be adopted extensively. 2024 Nova Science Publishers, Inc. -
Assessment of diversity, abundance, and seasonal variatons of bird species in Bengaluru District, India during COVID-19 lockdown
The study investgates bird populaton dynamics in Bengaluru, India, post-lockdown, focusing on occurrence, seasonal abundance, species diversity, richness, dominance, and evenness. It covers 55 bird species across 52 genera, grouped into 32 families within 13 orders, with a notable peak in winter. Various indices, including Shannon Wiener, Margalefs, Pielous, and Simpsons, reveal signifcant seasonal diferences in bird populaton characteristcs. The Rock Pigeon Columba livia dominates, while the Black-headed Ibis Threskiornis melanocephalus is less prevalent. The study identfes Near Threatened species like Black-headed Ibis and Oriental Darter Anhinga melanogaster, along with Least Concern species per the IUCN Red List. Common species include Rock Pigeon, Large-billed Crow Corvus macrorhynchos, House Crow Corvus splendens, Black Drongo Dicrurus macrocercus, Brown Shrike Lanius cristatus, Common Myna Acridotheres trists, Jungle Myna Acridotheres fuscus, Red-whiskered Bulbul Pycnonotus jocosus, and Streak-throated Swallow Petrochelidon fuvicola. The study aims to inform improved management and conservaton strategies for Bengalurus diverse bird species. Hemanth et al. 2024. Creatve Commons Atributon 4.0 Internatonal License. JoTT allows unrestricted use, reproducton, and distributon of this artcle in any medium by providing adequate credit to the author(s) and the source of publicaton -
Advancing Nutrient Removal and Resource Recovery Through Artificial Intelligence: A Comprehensive Analysis and Future Perspectives
The increasing difficulties associated with effectively controlling wastewater treatment operations while simultaneously satisfying the imperatives of nutrient removal and resource recovery have necessitated the use of advanced technology. This book chapter provides a comprehensive analysis of the use of artificial intelligence (AI) methods within this complex context. Utilizing a vast array of scholarly investigations and real-world implementations, this study explores the intricate domain of wastewater treatment, providing a comprehensive understanding of how artificial intelligence algorithms are used to enhance the efficiency of nutrient removal procedures and expedite the recovery of valuable resources. This chapter presents a thorough examination of the impact of artificial intelligence (AI) on sustainable innovations in wastewater treatment facilities. It accomplishes this through a comprehensive analysis of relevant data and the inclusion of real-world case studies. The findings of this research highlight the transformative effect of AI on conventional approaches to wastewater treatment, enabling the adoption of environmentally friendly and resource-efficient practices. The integration of artificial intelligence (AI) with wastewater management offers a fascinating story that highlights the shifting paradigm in the field of environmental engineering and the efficient exploitation of resources. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Early stage detection of osteoarthritis of the joints (hip and knee) using machine learning
This study explores the developing relationship between health care and technology, with a special emphasis on the use of machine learning (ML) algorithms to detect early stage osteoarthritis (OA) in the hip and knee joints. OA, a substantial worldwide health problem, requires improved diagnosis techniques. In this analysis, we illuminate the limitations of traditional methods, emphasizing the inherent subjectivity of clinical assessments and the delay in detection using routine imaging techniques. The research investigates the potential of ML to bring about significant changes. It focuses on combining various algorithms with extensive datasets and highlights the need to select relevant features and prepare the data to improve the accuracy of the models. The use of ML is closely connected to ethical issues, which include the protection of data privacy and the capacity to comprehend the models used. To bridge the gap between theory and practice, the chapter presents concrete examples of ML's practical use in detecting OA, opening possibilities for customized therapy and enhanced patient results. The chapter also highlights potential areas for future study, emphasizing the urgent requirement for additional progress in ML-based early detection techniques to alleviate the worldwide impact of OA. 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Evaluation of mechanical properties of e-glass and coconut fiber reinforced with polyester and epoxy resin matrices
Composite manufacturing is the novel branch of science, which finds its immense applications in various industries such as sporting, automotive, aerospace and marine industries. The superior properties of composites such as stiffness, better mechanical properties, low density and light weight make it a candidate in engineering applications. The need for seeking alternate materials with increased performance in the field of composites revived this research, to prepare fiber reinforced composites by hand layup method using E-glass and coconut fibers with length 5-6 mm. The resin used in the preparation of composites was epoxy and polyester. Fiber reinforced composites were synthesized at 18:82 fiber-resin weight percentages. Samples prepared were tested to evaluate its mechanical and physical properties, such as tensile strength, flexural strength, impact strength, hardness and scanning electron microscope (SEM). Scanning electron microscope analysis revealed the morphological features. E-glass fiber reinforced epoxy composite exhibited better mechanical properties than other composite samples. The cross linking density of monomers of the epoxy resin and addition of the short chopped E-glass fibers enhanced the properties of E-glass epoxy fiber reinforced composite. TJPRC Pvt. Ltd. -
Silenced, Scarred & Shattered: Unmasking the Wounds of Child Sexual Abuse in Select American Memoirs
The research brings to light the marginalized voices of three American women who have written about their sexual abuse in their respective memoirs Roxane Gay, Hunger: A Memoir of my Body (2017), Nikki Dubose, Washed Away: From Darkness to Light (2016) and Neesha Arter Controlled: The worst Night of my Life and its Aftermath (2015). Using these memoirs as primary data and using thematic analysis the study identified three themes which were further classified into different subthemes. Firstly, the research discovered the challenges faced by the survivors in expressing and communicating about sexual abuse due to fear and shame, the survivors do not come forward because of threats, because of rape stereotypes that permeate the society and the fear of what parents and others might think. Secondly, the research explores the various impact of trauma that is caused by sexual abuse which include shame, guilt and self blame, unworthy self, uncontrollable rage, disruption of safety and trust, isolating themselves from everyone, hostility towards body, destructive behaviours which include eating disorder from Anorexia Nervosa to Binge eating disorder, it also includes self harm and substance abuse. Thirdly, the research focuses on the recovery aspect on how the survivors learn to live with the wounds caused by sexual abuse. It focuses on how the survivors came in terms with the abuse, the conflicting feelings of forgiveness and revenge and how they sought redemption through writing their journey. 2025 Sciedu Press. All rights reserved. -
Evaluation of lime juice as potential green corrosion inhibitor using gravimetric and electrochemical studies
Lime, a vibrant fruit of citrus family is known for its antioxidant as well as anti-microbial properties. The constituents of lime juice include organic acids, polyphenols, soluble sugars, vitamins, minerals and amino acids. These details prompted to experiment lime juice as corrosion inhibitor for mild steel in 1 M HCl. The weight loss studies showed that the corrosion inhibition efficiency increased with increase in concentration of the lime juice as well as increase of temperature. The inhibition efficiency reached a maximum of 96% for an immersion period of 24 h. The best fit for the adsorption process obeyed Langmuir isotherm. The negative value of ?Gads showed the spontaneity of the corrosion inhibition process. The corrosion inhibition efficiency of the acidified lime juice was further validated by electrochemical studies namely AC impedance studies and potentiodynamic polarization studies. The surface morphology study was performed used optical profilometer. 2020 Chemical Publishing Co.. All rights reserved. -
An iot-based fog computing approach for retrieval of patient vitals
Internet of Things (IoT) has been an interminable technology for providing real-time services to end users and has also been connected to various other technologies for an efficient use. Cloud computing has been a greater part in Internet of Things, since all the data from the sensors are stored in the cloud for later retrieval or comparison. To retrieve time-sensitive data to end users within a needed time, fog computing plays a vital role. Due to the necessity of fast retrieval of real-time data to end users, fog computing is coming into action. In this paper, a real-time data retrieval process has been done with minimal time delay using fog computing. The performance of data retrieval process using fog computing has been compared with that of cloud computing in terms of retrieval latency using parameters such as temperature, humidity, and heartbeat. With this experiment, it has been proved that fog computing performs better than cloud computing in terms of retrieval latency. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Segmentation and Recognition of E. coli Bacteria Cell in Digital Microscopic Images Based on Enhanced Particle Filtering Framework
Image processing and pattern recognitions play an important role in biomedical image analysis. Using these techniques, one can aid biomedical experts to identify the microbial particles in electron microscopy images. So far, many algorithms and methods are proposed in the state-of-the-art literature. But still, the exact identification of region of interest in biomedical image is a research topic. In this paper, E. coli bacteria particle segmentation and classification is proposed. For the current research work, the hybrid algorithm is developed based on sequential importance sampling (SIS) framework, particle filtering, and Chan–Vese level set method. The proposed research work produces 95.50% of average classification accuracy. 2019, Springer Nature Singapore Pte Ltd. -
3D face recognition based on symbolic FDA using SVM classifier with similarity and dissimilarity distance measure
Human face images are the basis not only for person recognition, but for also identifying other attributes like gender, age, ethnicity, and emotional states of a person. Therefore, face is an important biometric identifier in the law enforcement and human-computer interaction (HCI) systems. The 3D human face recognition is emerging as a significant biometric technology. Research interest into 3D face recognition has increased during recent years due to availability of improved 3D acquisition devices and processing algorithms. A 3D face image is represented by 3D meshes or range images which contain depth information. In this paper, the objective is to propose a new 3D face recognition method based on radon transform and symbolic factorial discriminant analysis using KNN and SVM classifier with similarity and dissimilarity measures, which are applied on 3D facial range images. The experimentation is done using three publicly available databases, namely, Bhosphorus, Texas and CASIA 3D face database. The experimental results demonstrate the effectiveness of the proposed method. 2017 World Scientific Publishing Company. -
3D face recognition based on symobolic FDA using SVM classifier with similarity and dissimilarity distance measure /
International Journal of Pattern Recognition and Artificial Intelligence, 31, Issue 4, ISSN: 1793-6381. -
GNSS Signal Obstruction Removal Tool for Evaluating and Improving Position Accuracy in Satellite Networks
The positioning accuracy of Global Navigation Satellite System (GNSS) is largely affected by the site's surroundings. However, the methods to simulate GNSS signal obstruction and the nature of signal obstruction have not yet been explored fully. In this research, we investigated a way to remove the signals received from a specific region by specifying azimuth and elevation from GNSS observation files and evaluating how the removal of signals affects GNSS positioning accuracy. In addition, we also investigated the signal blockage for buildings of certain dimensions and a mountain. Python was used as a programming language to develop a program for the signal removal. RTKPOST was used for the GNSS data processing, and RTKPLOT was used for the visualisation of processed data and analysis of positioning accuracy. We successfully developed a Python shell script to remove the signals in GNSS data file from specific region by specifying azimuth and elevation. It was also found that removing signals from azimuth 0 to 100 degree and elevation 0 to 30 degree increased the positioning accuracy within a low multipath dataset. However, when the maximum elevation angle was increased to 45 degrees, positioning accuracy degraded, indicating that the signal from certain elevations have a positive or negative impact on positioning accuracy. Further research avenues are explored as an extension of work done here. 2023 IEEE. -
A short review on environmental impacts and application of iron ore tailings in development of sustainable eco-friendly bricks
Increased mining activity of iron ore has led to the generation of voluminous wastes of various nature, especially during the different stages of its extraction and production. The improper disposal of such waste causes negative impact on the environment. One such waste which is generated during the beneficiation process of iron ore is waste iron ore tailings, which is also termed as IOT. Further, dumping of IOT on open ground creates huge dumping sites. This dumping sites have been a concern to the environment and human population in its close vicinity. Therefore, a need to effectively use IOT has become one of the subjects of interest for many researchers. This article provides a short review of environmental problems caused due to improper disposal of IOT, and also reviews on the reuse methods of IOT in the construction sector, which helps to alleviate the environmental pollution associated with improper disposal of IOT. Furthermore, reuse of IOT in construction sector reduces the exploitation of the virgin materials for production of construction material, and thus reducing depletion of natural resources. Based on the existing literatures and findings it was observed that the use of IOT to develop stable building blocks using unconventional methods showed great potential and improved performance, when compared with conventional materials such as clay fired bricks. 2021 -
Phytochemicals of Nardostachys jatamansi as potential inhibitors of HCV E2 receptor: An in silico study
Hepatitis C virus (HCV) is the causative agent of acute and chronic hepatitis and can lead to liver cirrhosis. High variability in the HCV genome renders vaccine formulation strenuous. Modern pharmaceuticals rely heavily on plant-based compounds for drug production. This study focuses on in-silico screening of phytochemicals derived from an herbal plant, Nardostachys jatamansi, for the treatment of HCV by inhibiting its E2 receptor, which binds to the hepatocytes, enabling viral entry into the liver. Computer-aided drug design utilizes various tools such as molecular docking tools, including AutoDock Vina, Avogadro, PyMol, Discovery Studio Visualizer, LigPlot+, and online tools like SwissADME (Absorption, Delivery, Metabolism and Excretion) for analysis of pharmacokinetics and pharmacodynamics of phytochemicals. Toxicity studies were carried out using pkCSM. 25 bioactive phytochemicals of N. jatamansi were analysed. The analysis was validated by comparing the data of the phytochemicals with an established antiviral drug, ribavirin. This is a novel approach to docking studies, exploring the possibility of medicinal plants as anti-hepatic drugs. Of the 25 compounds, nardosatachysin and ?-gurjunene are the standout performers and are considered potent inhibitors of HCV E2 receptor. The two compounds are recommended for further in vivo and in vitro trials to assess their efficacy in treating HCV infection. 2024 Lalrintluanga Hnamte, et al. -
Purpose-driven leadership and organizational success: a case of higher educational institutions
Purpose: This paper aims to examine the relationships between organizational purpose, leadership practices and sustainable outcomes for universities in emerging economies. We propose that a strong sense of purpose is a fundamental and defining feature in the leadership practices of these institutions, which ultimately contributes to their success. Design/methodology/approach: The authors present a research model that defines the relationships between a sense of purpose, leadership practices, student success outcomes, alumni involvement outcomes and societal reputation outcomes. Over 200 higher education administrators in India participated in the study. Findings: The institutions' sense of purpose directly relates to their leadership engagement practices and their student success outcomes. Student success outcomes are a crucial linkage between leadership engagement practices and alumni involvement outcomes to achieve their societal reputation. Practical implications: As competitiveness intensifies, educational institutions under resource constraints must differentiate their organizational practices. This paper demonstrates how their core purpose and leadership actions result in achieving effective outcomes and overall sustainable societal reputation. Originality/value: There is a significant difference between having an organizational purpose and enacting that purpose through their leadership practices. These results highlight the cascading effect from the institution's fundamental sense of purpose to their leadership practices and the positive outcomes of student success, alumni involvement and societal reputation. 2021, Emerald Publishing Limited. -
The merging odyssey of trade, investment and partnership: a linkage model of India and Korea interactions
With the rising presence of India as a global power and Korea as an advanced economy, the collaborative alliance between two nations is of growing research interest. India and Korea are vastly different in terms of demographics, cultural traditions and historical experiences. However, they are unusually compatible for their shared vision and amazingly comparable in their unique positions in the dynamic world that involves strong coordinating linkage mechanisms and constructive influences. This paper aims to examine how India and Korea come to forge strategic alliance both in business relationships and national interests. We briefly review the history of interactions between India and Korea and define a unique model of linkage roles. After discussing network theory of interactions in liberal international order, propositions explain step by step how India and Korea merge to create better future for countless people through trade, investment, and partnerships. Growth stages of global firms for domestic advantage and global competitiveness are presented as well. Managerial implications and future research issues are discussed. Copyright 2022 Inderscience Enterprises Ltd.