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Lightweight Sybil attack detection framework for wireless sensor network with cluster topology
The development of communication and networking technology has made it possible for wireless sensor networks to play a significant role in many fields. Wireless sensor networks are vulnerable to a variety of security threats because of their remote hostile features. The Sybil attack, which generates several identities to gain access to wireless sensor networks, is one such devastating but simple to spread exploit. This Paper proposes a novel identity and trust-based system to ensure protection against Sybil attacks. Analysis of the RSSI and location parameter increases the accuracy. It recognises the attackers and broadcasts information about them to all adjacent sensor nodes. Additionally, it offers other crucial security features. 2025 Author(s). -
Lightweight Spectral-Spatial Squeeze-and- Excitation Residual Bag-of-Features Learning for Hyperspectral Classification
Of late, convolutional neural networks (CNNs) find great attention in hyperspectral image (HSI) classification since deep CNNs exhibit commendable performance for computer vision-related areas. CNNs have already proved to be very effective feature extractors, especially for the classification of large data sets composed of 2-D images. However, due to the existence of noisy or correlated spectral bands in the spectral domain and nonuniform pixels in the spatial neighborhood, HSI classification results are often degraded and unacceptable. However, the elementary CNN models often find intrinsic representation of pattern directly when employed to explore the HSI in the spectral-spatial domain. In this article, we design an end-to-end spectral-spatial squeeze-and-excitation (SE) residual bag-of-feature (S3EResBoF) learning framework for HSI classification that takes as input raw 3-D image cubes without engineering and builds a codebook representation of transform feature by motivating the feature maps facilitating classification by suppressing useless feature maps based on patterns present in the feature maps. To boost the classification performance and learn the joint spatial-spectral features, every residual block is connected to every other 3-D convolutional layer through an identity mapping followed by an SE block, thereby facilitating the rich gradients through backpropagation. Additionally, we introduce batch normalization on every convolutional layer (ConvBN) to regularize the convergence of the network and scale invariant BoF quantization for the measure of classification. The experiments conducted using three well-known HSI data sets and compared with the state-of-the-art classification methods reveal that S3EResBoF provides competitive performance in terms of both classification and computation time. 1980-2012 IEEE. -
Lightweight Model for Occlusion Removal from Face Images
In the realm of deep learning, the prevalence of models with large number of parameters poses a significant challenge for low computation device. Critical influence of model size, primarily governed by weight parameters in shaping the computational demands of the occlusion removal process. Recognizing the computational burdens associated with existing occlusion removal algorithms, characterized by their propensity for substantial computational resources and large model sizes, we advocate for a paradigm shift towards solutions conducive to low-computation environments. Existing occlusion riddance techniques typically demand substantial computational resources and storage capacity. To support real-time applications, it's imperative to deploy trained models on resource-constrained devices like handheld devices and internet of things (IoT) devices possess limited memory and computational capabilities. There arises a critical need to compress and accelerate these models for deployment on resource-constrained devices, without compromising significantly on model accuracy. Our study introduces a significant contribution in the form of a compressed model designed specifically for addressing occlusion in face images for low computation devices. We perform dynamic quantization technique by reducing the weights of the Pix2pix generator model. The trained model is then compressed, which significantly reduces its size and execution time. The proposed model, is lightweight, due to storage space requirement reduced drastically with significant improvement in the execution time. The performance of the proposed method has been compared with other state of the art methods in terms of PSNR and SSIM. Hence the proposed lightweight model is more suitable for the real time applications with less computational cost. 2024 by the author(s). -
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. -
Lightning Cards! /
Patent Number: 202141060863, Applicant: Bundela Disha Hitenbhai.
The present system or invention, Lightning Cards, is an online multiplayer card game that utilises computer vision and machine learning techniques in order to deliver a fast-paced reactions card game unheard of not only online, but also as a physical card game. The present system is enabled by way of ML tools to recognise the hand keypoint landmarks and other algorithms for recognising the actual hand gesture. -
Lightning Cards! /
Patent Number: 202141060863, Applicant: Bundela Disha Hitenbhai.
The present system or invention, Lightning Cards, is an online multiplayer card game that utilises computer vision and machine learning techniques in order to deliver a fast-paced reactions card game unheard of not only online, but also as a physical card game. The present system is enabled by way of ML tools to recognise the hand keypoint landmarks and other algorithms for recognising the actual hand gesture. -
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. -
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 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 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. -
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. -
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. -
Life Skills Development for Adolescent Girls at Risk with Special Reference to Rescued Devadasi Girls: An Intervention Study
Devadasi means to servant of God. The word is derived from Sanskrit language. It is originated from two words ??deva and ??dasi which mean God and servant respectively. The devadasi is attributed to girls dedicated to a Goddess called Yellama through the marriage to the deity. There are some important psycho social implications of devadasi system. The system of devadasi is a form of slave trade. In this system the young girls are exploited in the name of religious practices. A major disadvantage of this system is that it disintegrates an individual especially an adolescent girl in context of her overall development and social development in particular. Intervention has always been the essence of social work. Life skills education can be given prime importance and adolescent girls especially in situations such as rescued devadasi can be trained to apply life skills to redress their mental health problems. Teaching life skills to adolescents would help them to transform knowledge, skills, attitudes and values into real abilities. The aim of the current study was to assess the level of Life skills among the rescued devadasi adolescent girls and provide life skills training and evaluation of the overall effectiveness of the Programme. The design used was a pre experimental research design without a control group. 25 adolescent girls who are rescued from the devadasi system were part of the study from northern Karnataka. Based on the need assessment carried in the initial phase of the study, an intervention Programme was developed for the participants based on the 10 life skills laid out by the World Health Organization. A standardized Life skills assessment scale developed by Vranda (2009) was used in pre assessment and post assessments. The results indicate that the Programme was effective and displayed statistical significance in rendering the participants with Life skills. The implication of the study reiterates the importance of developing tailor made life skills Programme for vulnerable groups and girls at risk. KEY WORDS: Life skills, rescued devadasi girls -
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. -
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. -
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. -
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. -
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 -
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. -
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.