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Leveraging transparency and privacy through blockchain technology
Blockchain is a conveyed record innovation that can be utilized to keep exchanges in a safe and straightforward way. This makes it a promising innovation for various applications, for example inventory network the executives, monetary administrations, and medical services. One of the vital advantages of blockchain is its capacity to guarantee information consistency. This is on the grounds that all information on the blockchain is put away in a disseminated way, and every hub in the organization has a duplicate of the record. This makes it truly challenging for any one party to mess with the information. One more key advantage of blockchain is its straightforwardness. All exchanges on the blockchain are public, and anybody can see them. This can assist with building trust and straightforwardness among partners. Blockchain can likewise present difficulties regarding information security. This is on the grounds that all information on the blockchain is put away in a public record. This implies that anybody with admittance to the blockchain can see the information, including delicate data, for example individual recognizable proof numbers (PII). There are various ways of tending to the difficulties of information protection in blockchain. One methodology is to utilize encryption to safeguard delicate information. Another 2024, IGI Global. All rights reserved. -
Leveraging unsupervised machine learning to optimize customer segmentation and product recommendations for increased retail profits
The retail sector's success hinges on understanding and responding adeptly to diverse consumer behaviours and preferences. In this context, the burgeoning volume of transactional data has underscored the need for advanced analytical methodologies to extract actionable insights. This research delves into the realm of unsupervised machine learning techniques within retail analytics, specifically focusing on customer segmentation and the subsequent recommendation strategy based on clustered preferences. The purpose of this study is to determine which unsupervised machine learning clustering algorithms perform best for segmenting retail customer data to improve marketing strategies. Through a comprehensive comparative analysis, this study explores the performance of multiple algorithms, aiming to identify the most suitable technique for retail customer segmentation. Through this segmentation, the study aims not only to discern and profile varied customer groups but also to derive actionable recommendations tailored to each cluster's preferences and purchasing patterns. 2024, IGI Global. All rights reserved. -
Leveraging Usage of AI in education: Knowledge, Attitude and Behavioral Analysis on Students
The paper explores the possible advantages and drawbacks of artificial intelligence (AI) on sustainability, with an emphasis on using AI to positively achieve SDGs. The study finds a significant vacuum in the literature on the association between knowledge, attitudes, and behaviors towards the use of AI tools and techniques in education and demographic characteristics (sex, age, education level, area of study, and city of origin). The purpose of this research is to close this knowledge gap and advance our understanding of how these demographic factors affect the integration of AI in educational environments. The study specifically aims to comprehend how students awareness, beliefs, and actions towards AI in educational situations are influenced by demographic characteristics. This research attempts to offer insights into practical methods for utilizing AI in education while addressing potential obstacles and minimizing negative effects through a thorough analysis of data gathered from students across a range of demographic backgrounds. 2025, Binghamton University Libraries. All rights reserved. -
Lexical Richness of Adolescents Across Multimodalities: Measures, Issues and Future Directions
Lexical Richness (LR) is a scarcely researched subject in India. The objective of this paper is twofold: (i) To statistically inquire whether LR varies across three multimodalities: visual-only, audio-only, and audio-visual; and (ii) To see which of the two measures of LR (MATTR and Guiraud) is independent of text length and is best suited for short oral productions. 270 students across three types of schools were examined, out of whom 100 willingly completed all three oral tasks. The students were asked to retell the stories transacted in each modality in their own words. Randomization of sampling is done to mitigate the confounding modality bias. Additionally, the genre and parts of the storyline in each modality are similar. The students oral speech samples were recorded, transcribed and analyzed on WordCruncher and TextElixir software. The results revealed that there is statistically significant variance among the modalities. Furthermore, the Moving Average Type Token Ratio (MATTR) is seen to be independent of text length compared to Index of Guiraud. This study also throws light on the observations made during the study, pertinent issues in the field of education, and future directions for research on LR. 2023 IUP. All Rights Reserved. -
LGBT inclusion in UNSDGs - Has the Situation Improved for Sexual Minorities at Indian Workplaces?
In India, the acceptance of the sexual minorities has been considerably poor and challenging owing to societal biases and traditional misinformation. Speaking of workplaces in India, sexual minorities find it relatively difficult to have a complete breakthrough in these existing waves of biases as the policies are not that effective to help them survive in such competitive environment. The authors through this article have presented a qualitative account depicting an in-depth analysis of experiences that the sexual minorities have had in their workplaces. The paper examines the current situation of sexual minority employees at Indian workplaces after inclusion of the Universal value in UNSDGs. The authors in this paper have studied the existing issues that the sexual minorities are still facing in their respective workplaces further comparing it with the sustainable development goals on the grounds of the implicated hindrances that the practice imposes on the aim of United Nations. The Electrochemical Society -
LGBTQIA+ rights, mental health systems, and curative violence in India
This commentary examines the spaceattitudeadministrative complex of mainstream mental health systems with regard to its responses to decriminalisation of nonheteronormative sexual identities. Even though the Supreme Court, in its 2018 order, instructed governments to disseminate its judgment widely, there has been no such attempt till date. None of the governmentrun mental health institutions has initiated an LGBTQIA+ rights-based awareness campaign on the judgment, considering that lack of awareness about sexualities in itself remains a critical factor for a noninclusive environment that forces queer individuals to end their lives. That the State did not come up with any awareness campaign as mandated in the landmark judgment reflects an attitude of queerphobia in the State. Drawing on the concept of biocommunicability, analysing the public interfaces of staterun mental health institutions, and the responses of mental health systems to the death by suicide of a queer student, I illustrate how mental health institutions function to further antiLGBTQIA+ sentiments of the state by churning out customerpatients out of structural violence and systemic inequalities, benefitting the mental health economy at the cost of queer citizens on whom curative violence is practised. Indian Journal of Medical Ethics 2022. -
Liability of Artificial Intelligence System: A Bibliometric Study of Current and Emerging Trends (20112024)
The Integration of Artificial intelligence across the various sector such as Transportation as Autonomous vehicle, Business, education and healthcare has introduced the remarkable efficiencies such as data interpretation, data analysis, predictive analysis and Advance decision making, however it also purposed the unprecedented Legal issues. The Artificial intelligence system has become autonomous and obtained the capability of self decision making from the data. These advances of the AI system challenged the various aspect of Legal framework such as Insurance policy, intellectual property in AI and the Liability in case fault. The question of liability has become pressing concern because the Black box nature of AI and the involvement of various stakeholder complicated the assignment of legal responsibility in case of Failure. The present study aimed to investigate the research landscape including the knowledge, emerging area and the trends available in the literature on the Artificial intelligence liability. This research adopted the Bibliometric analysis methodology using the R software Biblioshiny Package, the analysis conducted on Liability focused studies related to artificial intelligence from timespan of 2011-2024. A total 154 document were obtained from the scientific databased SCOPUS and Web of Science after rigorous manual review of keywords Liability and Artificial intelligence in Title and abstract. This study employed the several analyses on the data including growth of research area, leading document, distribution of studies by the author, leading county, collaboration network, trend topic and factorial analysis. The finding indicates a notable increase in the number of publication form 2011-2024 focusing the healthcare sector. The emerging research area includes the area such as insurance, product liability, civil liability, strict liability of artificial intelligence. The study underscored the AI rule, regulation framework underdeveloped which require the further study in relation of legal liability. Finally, the findings suggest that the increasing focus on liability framework will foster the trustworthy AI and better regulating policies. 2025, National Institute of Science Communication and Policy Research. All rights reserved. -
Liberalisation and cashew industry: evidence from India (1965 to 2018)
We examine the impact of liberalisation on production, import, export and area under cultivation of cashew industry in India during 1965 to 2018 period using regression method. We divide data into two sub-periods. The liberalisation and pre-liberalisation period is from 1965 to 1991 and the post-liberalisation period covers the period from 1992 to 2018. We find that cashew production is not influenced post trade liberalisation. This study also finds trade liberalisation has a significant and positive impact on export. Further, we reveal an insignificant impact of liberalisation on import. This study show that the area under cultivation is not changed after the trade liberalisation. 2024 Inderscience Publishers. All rights reserved. -
License Plate Recognition Model based on Improved YOLOv5 and Convolutional LSTM
An end-to-end deep learning model is proposed in this research, for licence plate recognition (LPR) and identification in natural circumstances, which addresses the accuracy and speed limitations of standard licence plate recognition approaches. By adding a better channel attention mechanism and including position data in the output, the proposed method improves the You Only Look Once (YOLOv5) down sampling process and reduces information loss during sampling for better feature extraction. An optimised the YOLO layer is used for single-class recognition to improve efficiency and accuracy. Additionally, Convolutional Long Short-Term Memory (ConvLSTM) combined with Connectionist Temporal Softmax (CTS) is used for character segmentation-free recognition. The utilization of an optimized YOLO layer for single-class recognition enhances both efficiency and accuracy. The integration of ConvLSTM in conjunction with CTS proves to be a breakthrough, facilitating faster convergence, reduced training time, and increase the precision of the model. This configuration speeds up convergence, lowers training time, and increases identification accuracy. The experimental results demonstrate average recognition precision of 99.24% and also robustness, especially in complex situations, with better performance than conventional algorithms. 2025 IEEE. -
Lie group analysis of flow and heat transfer of a nanofluid in conedisk systems with Hall current and radiative heat flux
A study of the rheological and heat transport characteristics in conedisk systems finds relevance in many applications such as viscometry, conical diffusers, and medical devices. Therefore, a three-dimensional axisymmetric flow with heat transport of a magnetized nanofluid in a conedisk system subjected to Hall current and thermal radiation effects is investigated. The simplified NavierStokes (NS) equations for the conedisk system given by Sdougos et al. [18] Journal of Fluid Mechanics, 138, 379404 are solved by using the asymptotic expansion method for the four different models, such as rotating cone with static disk (Model I), rotating disk with static cone (Model II), co-rotating cone and disk (Model III), and counter-rotating cone and disk (Model IV). The KhanaferVafaiLightstone (KVL) model along with experimental data-based properties of 37 nm Al2O3H2O nanofluid is considered. To obtain the transformations leading to self-similar equations from the NavierStokes (NS) and energy conservation equations, the Lie group technique is used. The self-similar nonlinear problem is solved numerically to examine the effects of physical parameters. There are critical values of the power exponent at which no heat transport from the disk surface occurs. Nanoparticles significantly enhance heat transport when both the cone and disk rotate in the same or opposite directions. The centrifugal force and thermal radiation improve the heat transport in conedisk systems. 2023 John Wiley & Sons Ltd. -
Life Cycle Assessment of Battery Energy Storage Technologies for Vehicular Applications
The necessity of sustainable energy sources and storage technologies is emerging due to growing energy demands. Thus, it encourages the need to perform sustainability analysis in terms of energy efficiency. For battery technologies, energy production and recycling holds a significance. In this study, the direct and indirect requirements of various battery technologies including production to transportation. The five battery technologies taken into account for the analysis are Lithium ion, Nickel Metal Hydride, Lead acid, Valve Regulated lead Acid, and Nickel Cadmium. The characteristics analyzed here are cycle life, energy density and energy efficiency. The study also covers the life cycle assessment in an structured way from raw to evaluation of materials, energy flow, installation, usage to end of life. The Authors, published by EDP Sciences, 2024. -
Life skills for personal well-being
This investigation examines the integrative and transformative qualities of service learning in higher education, specifically focusing on its contribution to developing personal well-being-related life skills. By integrating significant community service with academic goals, service learning provides a comprehensive educational experience. Its defined components, theoretical framework, and real-world applications underscore the subject's significance. Student experiences and case studies illustrate its influence on empathy, resiliency, and communication. Strategic implementation approaches serve as a compass for purposeful undertakings. Service learning connects theoretical concepts with practical application, cultivating globally literate and socially conscious individuals who can navigate the everchanging realm of higher education. 2024, IGI Global. -
Lifestyle Diseases Prevalent in Urban Slums of South India
Lifestyle diseases have always been considered to be a malady of the middle and upper classes of society. Recent findings indicate that these chronic non-communicable diseases are common among the lower socioeconomic classes as well. The objective of this study was to assess the prevalence of lifestyle diseases in three cohorts of urban slums, namely, waste pickers living in non-notified slums, communities living in notified slums, and BBMP Pourakarmikas, and to identify the risk factors among the three cohorts contributing to the common lifestyle diseases including hypertension, diabetes, and cardiovascular diseases. In this study, the data was collected by conducting health camps, followed by analysis of the data using logistic regression, HosmerLemeshow test and ROC Curve Analysis. The prevalence of hypertension was found 13.35%, diabetes-8.53% and cardiovascular disease-3.59%. These were significantly associated with substance abuse, high BMI, and age. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Light as an elicitor for enhanced production of secondary metabolites in plant cell, tissue, and organ cultures
Currently, in vitro cell, tissue, and organ cultures are used to produce plant secondary metabolites that are used as natural coloring agents, nutraceuticals, and medications. Various strategies have been applied for the hyperaccumulation of biomass and bioactive secondary compounds in vitro. The elicitation of cultured cells and organs with biotic and abiotic elicitors is an excellent strategy that has yielded promising results. Among various abiotic elicitors, light parameters such as light quality, intensity, and photoperiod have evolved as biotechnological tools to elicit cultures. Of the various light sources tested, ultraviolet (UV) lights, particularly UV-B, red, blue, and a mixture of light emitted by fluorescent light or light-emitting diodes, have yielded outstanding results and boosted the accumulation of bioactive compounds in cultured cells and organs. The objective of the current study was to evaluate light as an elicitor source and summarize the advantages and limitations of various light sources as elicitors for the bioaccumulation of secondary metabolites in vitro. The mechanism of the elicitation of secondary metabolism by UV and spectral light is discussed in this review. The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
Light Tracking Bot Endorsing Futuristic Underground Transportation
Controlling a bot machine that uses non-conventional energy form, i.e. light is said to have an upper hand in pioneering transportation system. The expanding request of making the streets more secure has persuaded a ton of organizations to create finest autonomous vehicles. This paper will concentrate on the potential outcomes of utilizing just light-sensing gadgets alone for the light tracking bot using advanced color detection algorithm. The algorithm would help the bot in sensing the color of light and act accordingly, for instance green color to proceed, red color to stop. This particular requisition has high scope in real time application over the emergent underground transportation system; speculating on how the emerging innovative advances fit to the fiddle urban areas of the 21st century. 2020, Springer Nature Switzerland AG. -
Light weight authentication protocol for WSN using ECC and hexagonal numbers
Wireless Sensor Network (WSN) is a spatially distributed network. It contains many numbers of distributed, self-directed, small, battery powered devices called sensor nodes or motes. In recent years the deployment of WSN in various application domains are growing in a rapid pace as with the upcoming boom of Internet of Things (IoT) and Internet of Everything (IoE). However, the effectiveness of the WSN deployment is restricted due to the constrained computation and power source. Hence, many researchers have been proposing new approaches and models to improve the efficiency of the domain specific WSN deployment procedures. Though, many research communities addressing various issues in WSN deployment, still the privacy and security of such networks are susceptible to various network attacks. Thus, it is necessary to practice different models for authentication and privacy preservation in a highly dynamic resource constrained WSN environment to realize the effectiveness and efficiency of the deployment. Hence, this paper addressing an authentication scheme that can reduce energy consumption without compromising on security and privacy. In order to provide a light weight authentication mechanism, this paper proposing an authentication mechanism for WSN deployment by combining the features of Elliptic Curve Cryptography (ECC) and Hexagonal numbers. The feature of ECC is used to reduce the key size and the effectiveness of generating hexagonal numbers is used for minimizing the energy consumption in a resource constrained WSN environment. The results of the proposed approach are evaluated with the different authentication models and the results were indicating that the proposed approach can perform better than the other approaches. 2019 Institute of Advanced Engineering and Science. -
Light-induced advanced oxidation processes as pfas remediation methods: A review
PFAS substances, which have been under investigation in recent years, are certainly some of the most critical emerging contaminants. Their presence in drinking water, correlated with diseases, is consistently being confirmed by scientific studies in the academic and health sectors. With the aim of developing new technologies to mitigate the water contamination problem, research activity based on advanced oxidation processes for PFAS dealkylation and subsequent mineralization is active. While UV radiation could be directly employed for decontamination, there are nevertheless considerable problems regarding its use, even from a large-scale perspective. In contrast, the use of cheap, robust, and green photocatalytic materials active under near UV-visible radiation shows interesting prospects. In this paper we take stock of the health problems related to PFAS, and then provide an update on strategies based on the use of photocatalysts and the latest findings regarding reaction mechanisms. Finally, we detail some brief considerations in relation to the economic aspects of possible solutions. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Lights and Shadows in Autodesk 3ds Max: Methods and Features
Using the 3ds Max software, this paper describes the intricate modelling process of implying shadows onto various objects to make it look more realistic. In this article, Various Shadow types and controls are used in order to demonstrate the functions of shadows in Autodesk 3ds Max. The paper helps the reader understand the nature of the lights and shadows in a computer-generated environment and its implementation in the real-world situations. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Lightweight Anti DDoS Security Tool: Edge Level Filtering in SDN using P4
Software Defined Network (SDN) which has a promising future in satellite communication was first introduced as the solution to solve problems existing in the traditional network architecture. So far in SDN, mitigation strategies employed hardware installation or software solution which is heavily dependent on SDN controllers. The disadvantage of these approaches is the a) cost for implementation, b) intensive resource usage, and 3) costly optimization strategy necessary to enhance SDN performance. This research aims to fill the gap of the previously seen defense mechanism by enabling edge-level filtering without involving the control plane. By implementing filtering functions in edge switches, it can provide an efficient and effective defense layer in SDN network systems so that SDN switch can become the first line of defense against packet injection attacks. The proposed solution, Lightweight Anti-DDoS Software (LADS) focuses on lightweight workloads and provisioning of effective filtering mechanism to allow SDN switches to drop and block malicious packets sent by attackers. It utilizes Programming Protocol-independent Packet Processors (P4) programming language to create custom functionalities in SDN switches. P4 allows SDN switches to conduct host authentication and malicious packet filtering as well as blacklisting to isolate attackers. Simulation result proves that LADS efficiently manages malicious activities and maintains network performance during attacks at the data plane independent of SDN controller. 2023 IEEE.