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NSS-ML: a Novel spectrum sensing framework using machine learning for cognitive radio IoT networks
A key component of cognitive radio systems is spectrum sensing, which reduces coexistence problems and maximises spectrum efficiency. However, the introduction of multiple situations with distinct characteristics brought about by 5G communication presents problems for spectrum sensing to support a wide range of applications with high performance and flexible implementation. Inspired by these difficulties, a new method with a multi-layer extreme learning machine optimised for bats is presented in this study. This technique makes use of a variety of input vectors, such as channel ID, energy, distance, and received signal intensity, to enhance user categorization and sensing capabilities. Moreover, we compare the proposed method with the state-of-the-art spectrum sensing approaches in order to evaluate its effectiveness in 5G situations, especially in healthcare applications. Evaluation metrics including channel detection probability, sensitivity, and selectivity are carefully examined. The findings unequivocally prove the suggested spectrum sensing approachs superiority over current methods and highlight its potential for smooth incorporation into a variety of 5G applications. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024. -
Food Security and Its Impact on Society: Cases of Developing World
Food security is a matter of concern in the twenty-first century as is evident from the importance given to it in the United Nations Sustainable Development Goals. Despite attempts to address food scarcity concerns at global conventions such as the World Food Summit of 1996, food remains scarce. Scholars further suggest that though food scarcity is a global issue, its roots and impact is local. Consequently, a study of food must study the major challenges that converge to undermine food security worldwide including conflicts, climate change, global policies and in recent times even the Covid 19 pandemic. However, at a fundamental level food scarcity is the by-product of not just a legacy of past failures to build more just, sustainable, and resilient food systems, but rather a by-product of our inability to be responsible and sustainable consumers. This chapter highlights that despite surplus food production, developing nations often face food insecurity owing to the diversion of food towards developed nations. These nations, instead of sharing global resources (including food and agricultural labour), often contribute towards the global food crisis. Moreover, some of these developed nations engage in an industrialised system of food produc-tion which might meet the nations food requirements but are not sustainable modes of production and pose a serious threat to the environment. Nevertheless, the indis-cretions of the developed nations affect the developing nations economically as well as socially. As social outcasts, marginalised communities and individuals within the developing world are worst affected. As a result, this chapter offers insight into the social struggle brought on by inaccessibility to food. The chapter further suggests that addressing concerns of food security is not only a matter of addressing the inequalities manifest in the production, distribution and consumption of food but also learning to be responsible and sustainable consumers. Simply stated, the chapter recommends connecting SDG 2 with SDG 12. This chapter would also include the position of India in GHI, the Ukraine crisis and its aftermath in various developing countries, the earthquake in Turkey and how it affects the food security, and a few instances from Africa to highlight the concepts of food security and its correlation with sustainability of any society. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Artificial Intelligence in Fostering Sustainable Development
Sustainable development is vital to mankind. The world is finding a growing effort of Artificial Intelligence (AI) towards sustainability, and we made an attempt to address the development in sustainability using AI systems. Sustainable development has three pillars of sustainability (i.e. social, economic, environment), and as such, the pillars of sustainable AI. The entire Life cycle of AI products can foster change in the movement of sustainability from which greater integrity and social justice can be achieved. Sustainable AI helps us to address the whole socio-technical system more than AI applications. This paper tried to address the positive impacts of AI on sustainable indicators in terms of Environmental, Societal and Economy factors. This paper is prepared to make readers, policymakers, AI ethicists and AI developers to inspire and connect with the environment for the current and future generations as there are few AI costs to be made compatible with the environment. 2023 American Institute of Physics Inc.. All rights reserved. -
Unveiling the Future: Exploring Stock Price Prediction in the Finance Sector through Machine Learning and Deep Learning - A Comprehensive Bibliometric Analysis
The investigation of predicting share prices is a captivating and beneficial area of study within the realm of economic research. precise projections and findings can potentially benefit shareholders by reducing the risk of making suboptimal investment selections. The objective of this investigation is to examine the present state of research pertaining to the prognostication of share price predictions through the utilization of Machine Learning (ML) and Deep Learning techniques. The present study examined the existing body of scientific works on methods involving DL and ML in the context of predicting the value of stocks. This study presents a comprehensive overview of research trends, methodologies, and applications in a particular field by conducting a bibliometric analysis of publications indexed in the Scopus database. Drawing from the presented data, recommendations for optimal methodologies can be formulated. The data was visually represented through the utilization of the R programming language and Vos Viewer software. The investigation additionally discerns the primary authors, institutions, and nations that are making contributions to this particular field of research. The outcomes of this investigation possess the potential to guide future research trajectories and offer significant perspectives for professionals and policymakers who are keen on utilizing machine learning and deep learning in the financial sector. 2024 IEEE. -
A Study on the Impact of Intervention Program for the Care Givers of People with Head and Neck Cancer
Head and neck cancer patients experienced profound psychosocial and functional abilities because of the location of the disease and treatment. It hampers their activities of daily living making them dependant on the caregivers. Subsequently caregivers have different needs especially during the initial phase of hospitalization because they are unfamiliar to the whole process, unprepared for the new task and new role and lack the necessary knowledge and skills in care giving. Thus they face a number of problems. Hence this study aimed to understand their needs, develop psycho educational intervention program based on it and assess its feasibility. It was taken up because of limited number of Indian studies and increase in the number of incidences owing to the changing life style. Quasi experimental research design and sequential mixed research design was used. The variables taken for the study were Caregiver burden and distress. Zarit burden interview schedule and Caregiver Self Assessment Questionnaire was used to collect data from 30 caregivers of head and neck cancer patient before and after the Psycho educational intervention program was delivered. Paired sample t test and Cohen s d tests were used for data analysis. The effect size for burden and distress was 2.01 and 1.91 respectively. Findings showed that the intervention program significantly reduced the level of burden -
Thermorheological and magnetorheological effects on Marangoni-Ferroconvection with internal heat generation
Marangoni convectiveinstability in a ferromagnetic fluid layer in the presence of a spatial heat sourceand viscosity variation is examined by means of the classical linear stability analysis. The higher order Rayleigh-Ritz technique is used to compute the critical Marangoni number. The effective viscosity of the ferromagnetic liquid is taken to be a quadratic function of both the temperature and magnetic field strength. It is shown that the ferromagnetic fluid is significantly influenced by the effect of viscosity variation and is more prone to instability in the presence of heat source compared to that when viscosity is constant. On comparing the corresponding results of heat source and heat sink it is found that heat sink works in tandem with the effect of viscosity variation if magnetic field dependence of viscosity dominates over temperature dependence. If the temperature dependence of viscosity dominates, the effects of viscosity variation and heat sink are mutually antagonistic. Published under licence by IOP Publishing Ltd. -
Bard-Taylor ferroconvection with time-dependent sinusoidal boundary temperatures
The combined effect of centrifugal acceleration and time-varying boundary temperatures on the onset of convective instability of a rotating magnetic fluid layer is investigated by means of the regular perturbation method. A perturbation expansion in terms of the amplitude of applied temperature field is implemented to effectively deal with the effects of temperature modulation. The criterion for the threshold is established based on the condition of stationary instability manifesting prior to oscillatory convection. The modulated critical Rayleigh number is computed in terms of Prandtl number, magnetic parameters, Taylor number and the frequency of thermal modulation. It is shown that subcritical motion exists only for symmetric excitation and the destabilizing effect of magnetic mechanism is perceived only for asymmetric and bottom wall excitations. It is also delineated that, for bottom wall modulation, rotation tends to stabilize the system at low frequencies and the opposite is true for moderate and large frequencies. Furthermore, it is established that, notwithstanding the type of thermal excitation, the modulation mechanism attenuates the influences of both magnetic stresses and rotation for moderate and large frequencies. Published under licence by IOP Publishing Ltd. -
Adoption and Usage of Artificial Intelligence in Food Processing Industries
In recent years, technological changes and advancements have forced Fast Moving Consumer Goods (FMCG) industries, especially food processing, to redesign their functionality. This includes the integration of technologies like Artificial Intelligence (AI) to enhance performance. Future trends in the food processing industry will be shaped by sustainability, efficiency, traceability, wellness, safety, hygiene, health, and newlinetransparency. Food processing industries are compelled to embrace digitalization in the newlinecurrent era of globalization and digital transformation. AI encompasses programs, newlinealgorithms, robotics, drones, data mining, cloud computing, sensors, driver-less newlinevehicles, the internet of things, digital platforms, and machines, representing a new newlinelevel of intelligence. AI aims to replicate human reasoning and problem-solving newlinecapabilities, leading to task automation, increased efficiency, and reduced human newlineeffort. The growth of AI is reshaping the food processing industry, with potential newlineapplications spanning from cultivation, supply chain management, storage and safety, newlineHuman Resource Management (HRM), and Customer Relationship Management (CRM). Integrating and adopting AI in food processing can address unique challenges and offer substantial benefits across these functions. While large-scale food processing newlineindustries have made significant progress in adopting AI systems, small and mediumscale food industries are also integrating AI technology. The current research study employs a quantitative research methodology and obtained data from 320 small and medium-scale food processing industries employees in the city of Bengaluru. The primary surveyed data were analyzed using the Structural Equation Modeling (SEM) approach through AMOS 26. The research used the UTAUT 2 model to measure the usage and adoption of Artificial Intelligence (AI) among the employees of small and medium-scale food processing industries. -
Unfolding the aggression and locus of control paradigm in sportspersons and non-sportspersons
The present study investigated Aggression and Locus of Control on Combat Sports Persons, Non-Combat Sports Persons, and Non-Sports Persons. In this study, a sample of 240 individuals (80 Combat sports, 80 Non-Combat Sports & 80 Non-Sportspersons) was used through purposive sampling. The tools administered were the Buss and Perry Aggression Questionnaire by Arnold H. Buss and Mark Perry and Rotters Locus of Control Scale by Julian Rotter respectively. The objective of the study was to investigate Aggression and Locus of Control in males and females from Combat, Non-Combat, and Non-Sports persons. This research also aims to explore the relationship between Aggression and Locus of Control. Mean, t-test, F-value (ANOVA), and correlation have been computed over SPSS-16. Results suggest that males from Combat have higher Aggression than people from non-sports and non-combat sports. There is also a significant difference between non-sports persons and sports people over the Locus of Control, sports persons showed internal locus of control compared to non-sports persons who were higher on external locus of control. The result also indicates a significant relationship between the anger dimension of the Aggression and Locus of Control. 2025 ARD Asociaci Espala. -
An Efficient Compressive Data Collection Scheme for Wireless Sensor Networks
The Compressive Data Collection (CDC) scheme is an efficient data-acquiring method that uses compressive sensing to decrease the bulk of data transmitted. Most existing schemes are modeled as Non-Uniform Sparse Random Projection (NSRP), and an NSRP-based estimator is used. These models cannot deal with anomaly readings that deviate from their standards and norms. Therefore, we provide a new CDC strategy in this study that uses an opportunistic estimator and routing. Initially, neighbor nodes are identified using the covariance function following the Gaussian process regression, and the data transfer to the neighbor node is done using the compressive sensing technique. Compressed data are then projected by using conventional random projection. Finally, the sample required to retrieve data is estimated using margin-free and maximum likelihood estimators. Results show that the sample needed to retrieve the data is less in the proposed scheme. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
A self-cooperative trust scheme against black hole attacks in vehicular ad hoc networks
The main objective of the Vehicular Adhoc NETwork (VANET) is to provide secure communications for the vehicles in the network without fixed infrastructures. It inherits all the properties of the MANET. Achieving reliable routing to avoid various routing attacks is the major concern in the vehicular network. Routing attacks degrade the performance of the network. Black hole attack is one of the routing attacks, which drops the data packets without forwarding them to the destination vehicle. Different routing schemes are proposed to provide security against these attacks, which still have security issues. Hence a new self-cooperative trust scheme is proposed in this paper, to detect single as well as collaborative black hole attackers in the network. Two processes: self-detection and cooperative detection, are used to detect attackers in the network. Results show that the proposed scheme has better performance in terms of throughput, PDR and delay. Copyright 2021 Inderscience Enterprises Ltd. -
Stability Analysis ofSalt Fingers forDifferent Non-uniform Temperature Profiles inaMicropolar Liquid
This paper describes the linear stability analysis of salt finger convection for different non-uniform temperature profiles by keeping the solutal concentration uniform throughout the system. The system consists of two parallel plates separated by a thin layer of micropolar liquid with infinite length, in which the system is heated and soluted from above the plate. Normal mode techniques are used to convert the system of partial differential equations into ordinary differential equations; further, Galerkian method is introduced to get the eigenvalue for isothermal, permeable with no-spin boundary conditions. The study also explains the effect of different micropolar parameters on the onset of convection. The phase of temperature flow for different boundary conditions explains the graphical solution of the energy equation and its gradients. It is shown that non-uniform temperature profiles, diffusivity ratio, coupling parameter, and solutal Rayleigh number influence the stability of the system. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Study on Work Engagement among the School Teachers
Work engagement is a measurable degree of an persons positive or negative emotional attachment to their job, colleagues and organization which profoundly influences their willingness to learn and perform at work. Now a days it is observed that the commitment and dedication of the teachers in their profession as decreasing. It is also seen that teacher turnover is also becoming high. Even though the teachers in the schools were paid good, the turn over seems to be increasing. The study here tries to investigate the relationship with the work engagement and the socio demographic characteristics of teachers where the demographic variables could explain the relationship between the dimensions of work engagement. Descriptive research design is being used in the study . This design is helpful to identify the socio demographic characteristics and its relationship between the Work engagement among School teachers . The sample consisted of 100 school teachers who having more than one years of experience and the sample was selected by using the convenient sampling method. The study was done using the UWES Scale developed by Wilmar Schaufeli and Arnold Bakker in 2003 and nineteen other questionnaires were developed to know the other factors contributing to work engagement. The resourceful work environment can foster teachers work engagement. Consequently, the study shows that the older experienced married teachers shows the high level of work engagement where the educational qualification has no much role in it. This means that the young generation is not much interested in the profession with a a passion rather than they themselves consider it as a job. The work engagement can be increased among them through making interventions like improving and enhancing effective job and personal resources. -
Performance Analysis of Different Classifiers to Build a Classification Model and to Improve the Vigilance Skills in Crime Detection Using Data Mining Techniques
International Journal of Advanced Research in Computer Science, Vol-3 (7), pp. 314-317. ISSN-0976-5697 -
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Interaction of Nanomaterials with Plant Macromolecules: Nucleic Acid, Proteins and Hormones
Nanotechnology has the ability to change a wide range of industrial and agricultural operations. To harness these possibilities, it is essential to construct nano-materials that have minimum impact on the human body, plant systems as well as the environment. Using different materials can up-or down-regulate diverse genes of plants, create stimulating or stressful conditions and even cause production of metabolites that affect plant-associated microbes. The same nanoparticle can promote one plant species growth and be toxic to another. A small change in the concen-trations could cause either flourishment or senescence. It is crucial to understand how nanomaterials interact with nucleic acids, the most fundamental plant macro-molecule, as well as with the proteins and hormones made by biochemical processes. This chapter explores the basics of nanotechnology, with a brief classification and notes on some of the most recently used nanomaterials in agriculture such as metals and their oxides, quantum dots, graphene, arabinoxylan and chitosan nanoparticles, single and multi-walled carbon nanotubes. Interactions with these above-mentioned macromolecules are explored, along with futuristic applications in plants that are currently being tested, like nanocarriers and nanovalves. Through this work, it is hoped that the field will further be extended through proper understanding of the environmental implications of nanomaterials, and that green technology will become the norm. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
SCSLnO-SqueezeNet: Sine Cosine-Sea Lion Optimization enabled SqueezeNet for intrusion detection in IoT
Security and privacy are regarded as the greatest priority in any real-world smart ecosystem built on the Internet of Things (IoT) paradigm. In this study, a SqueezeNet model for IoT threat detection is built using Sine Cosine Sea Lion Optimization (SCSLnO). The Base Station (BS) carries out intrusion detection. The Hausdorff distance is used to determine which features are important. Using the SqueezeNet model, attack detection is carried out, and the network classifier is trained using SCSLnO, which is developed by combining the Sine Cosine Algorithm (SCA) with Sea Lion Optimization (SLnO). BoT-IoT and NSL-KDD datasets are used for the analysis. In comparison to existing approaches, PSO-KNN/SVM, Voting Ensemble Classifier, Deep NN, and Deep learning, the accuracy value produced by devised method for the BoT-IoT dataset is 10.75%, 8.45%, 6.36%, and 3.51% higher when the training percentage is 90. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Impact of domestic investment, market size, and trade openness on outward fdi: A panel data analysis on brics
The recent phenomenal increase in the outward foreign direct investment (FDI) of emerging countries has raised concerns among policymakers. One school of thought argues that when multinational firms relocate production facilities abroad, it reduces the likelihood of concurrent investments in the home country, resulting in reduced domestic output. In this case, the outward FDI would harm the domestic investments. The other argues that the outward FDI would be more advantageous for the domestic investment when firms internationalize for entering into new markets and/or to import intermediate goods, wherein outward investments boost the returns in the home country, leading to a positive impact of outward FDI on domestic investment. The influence of the outward FDI on the domestic investment of any country or a region state cannot be generalized as each country is unique, and the drivers of investments would differ for different countries at the different development phases of each country. An attempt was made in this study to empirically trace the impact of the domestic investment, market size, and trade openness of the BRICS's members on the BRICS's outward FDI as a group. The results of the panel least square method highlighted that the variables - domestic investment and trade openness of BRICS had a positive effect on the outward FDI; whereas, the market size of BRICS was inversely related to outward FDI of BRICS. The data were tested for stationarity and Hausman test validated the results. 2019, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
On ideal sumset labelled graphs
The sumset of two sets A and B of integers, denoted by A + B, is defined as (formula presented). Let X be a non-empty set of non-negative integers. A sumset labelling of a graph G is an injective function (Formula Presented) such that the induced function (Formula Presented) is defined by (Formula presented). In this paper, we introduce the notion of ideal sumset labelling of graph and discuss the admissibility of this labelling by certain graph classes and discuss some structural characterization of those graphs. 2021 Jincy P. Mathai, Sudev Naduvath, and Satheesh Sreedharan. This is an open access article distributed under the terms of the Creative Commons License, which permits unrestricted use and distribution provided the original author and source are credited. -
Influence of positive psychological capacities emotional intelligence and subjective well being of nurses in healthcare sector
The aim of this research is to address the insufficient empirical investigation of newlinepositive psychological variables among the nurses in the healthcare sector in India. Here we explore positive psychological capacities proposed by Luthan and team 2007), newlinecomprising of self-efficacy, hope, optimism and resilience their influence on emotional newlineintelligence; a concept of empirical interest among the nursing population (Freshwater newlineand Stickley 2004) and subjective well-being. Gill (2011) has mentioned that the health newlineworker determines the quality and nature of services offered in any healthcare system. newlineAdhering to the conceptual framework of positive psychology, psychological capital, newlineconservation of resource and broaden-and-build theory, this study is an exploration of newline(a) the positive psychological capacities, (b) its influence on emotional intelligence, and (c) subjective well-being of nurses (n=302) across government, private and trust newlinehospitals in Bangalore. The hospitals were chosen based on stratified sampling with the nursing respondents identified through random sampling and judgemental sampling. A pilot newlinestudy was carried out (n=100) to validate the standardized scales used for measuring the newlinevariables. An explanatory sequential mixed method design was proposed through which newlinethe quantitative analysis using a detailed descriptive statistics and regression analysis suggested that efficacy, hope, optimism and resilience influenced emotional newlineintelligence. While resilience and optimism influenced subjective well-being of nurses newlinethere was no influence of emotional intelligence, self-efficacy and hope. A qualitative follow-up interview was executed (n=15) to understand the reason for no influence. The findings substantiated that most of the nurses viewed themselves as happy individuals despite their work-related dissatisfactions as almost all saw their profession as service to mankind. The implications of these findings are traced along with the suggestions for future research.