bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectiveness of Self-Instructional Module on Knowledge Regarding Natural Birthing Methods among Antenatal Mothers
Authors: Supriya Ray Prajakta Rajesh Jadhav,
Published: December 2023

Background:This study aims to assess the effectiveness of self -instructional - module on knowledge regarding natural birthing methods among antenatal mothers of selected hospitals. It is quasi experimental research. Purpose of the study was to know the pre assessment knowledge regarding natural birthing methods followed by the intervention, which included administration of self-instruction-module, which was based on the content related to natural birthing methods. After administration post evaluation of the knowledge score was done to compare the effectiveness of the intervention.

Material and method: A quasi experimental research design was used while the approach utilized was quantitative. Pre-test- post-test control group research design was used for the study. The study was done at tertiary hospital of a cosmopolitan city, while the samples were antenatal mothers who were attending the OPD’s. Data collection tool used was a structured questionnaire on natural birthing methods which included demographic questions and knowledge based questions. Analysis was done by using descriptive inferential statistics.

Result:Results revealed that experimental group knowledge score in pre-test was 9.2 as compared to 11.2 in the post-test for the p-value of 0.05. In control group, knowledge score in pre-test was 8 as compared to 8.5 in the post-test. Association was found with the demographic variable of education

Conclusion: Average mean difference in knowledge score in antenatal mothers in experimental group was significantly higher than that in control group hence It is evident that the self-instructional module is significantly effective in improving the knowledge among antenatal mothers regarding natural birthing methods.
Developing on the Quality Evaluation Mechanism of Innovative Talents in International Education through Stakeholder Theory
Authors: Patchara Dechhome Aiwei Mu, Buranajit Kaewsrimol, Niran Sutheeniran,
Published: December 2023

With the growing trend of international education, universities, and higher education institutions have gradually begun to pay attention to cultivating innovative talents. Among them, the evaluation mechanism of the quality of innovative talents is the path of feedback on innovative education in universities, and it has a vital guiding role in the reform of innovative education. Stakeholder theory is a theoretical guidance to coordinate the development of the overall situation from the manager's point of view. Analyzing the quality evaluation mechanism of innovative talents in international education from the perspective of stakeholders is based on the interests and needs of stakeholders in innovative education, considering the requirements for the quality of innovative talents in highly relevant groups, and timely revising the dynamics of the talent training program mechanism. In this study, fully considering the interests and needs of high-related stakeholders, that is, the social demand for innovative talents, puts forward better revision suggestions for the quality evaluation mechanism of innovative talents in international education and finally gives a simple mechanism feedback model.
Guidelines for Development Instructional Leadership for Secondary School Teachers in Qingdao
Authors: Patchara Dechhome Huang Yonggang,Nonnadhi Dulyadaweesid , Niran Sutheeniran,
Published: December 2023

The objectives of this research were: 1) To study the current level of instructional leadership of secondary school teachers in Qingdao. 2) To develop the guidelines of instructional leadership of secondary school teachers in Qingdao. 3) To evaluate the adaptability and feasibility of instructional leadership of secondary school teachers in Qingdao. The sample group of this research was 291 teachers. The Interview group was 9 secondary school teachers in Qingdao and the evaluate 9 experts from secondary school in Qingdao. Research instruments include: 1) questionnaire. 2) semi-structured interview. 3) evaluation form. Data analysis by using percentage, mean, standard deviation and content analysis.

The results were: 1) the current situation of instructional leadership of secondary school teachers in Qingdao was at high level, 2) the guidelines for developing the instructional leadership of secondary school teachers in Qingdao in four aspects, which contain 23 articles. there are 6 guidelines for optimizing professional development, 6 guidelines for enhancing teaching practice, 5 guidelines for improving school culture, and 6 guidelines for promoting learn. 3) adaptability of guidelines for developing the instructional leadership of secondary school teachers in Qingdao in four aspects were at highest level. and feasibility of guidelines for developing the instructional leadership of secondary school teachers in Qingdao in four aspects were at high level.
Hiligaynon Vocabulary Knowledge of Ilonggo Student Teachers
Authors: Ciriaco, Joel A.
Published: December 2023

The Department of Education in the Philippines is implementing the K-12 curriculum, mandating native languages in classroom instruction from kindergarten to grade 3. However, teachers are not well-versed in the native language, particularly Hiligaynon, and are learning to use it as the language of instruction. A 2006 World Bank study found that children experience lower learning levels when their language is not used in school. UNESCO recommends prioritising mother tongue acquisition, recruiting teachers with cognitive proficiency in the first language, providing teacher training, and promoting policies that position parents as "first teachers." Quantitative-descriptive research found that elementary teachers used 83% of the combination language, 6% of the mother tongue, and English was the least used. Hiligaynon vocabulary knowledge was highest in "Kinaandan Nga Panamyaw" and "Mga Numero", while English was the least used. Age, gender, high school, and elementary school did not significantly affect vocabulary knowledge.
Designing a Fault-Tolerant System for Hearing Aids: Echo Detection and Rectification Using SVM Classifier
Authors: Aravinda H S Vijay Kumar Reddy I,
Published: December 2023

Hearing aids, akin to various mechanical instruments, emit specific auditory signals indicative of operational health, accurate parameter settings, or maintenance requirements. Analogous to automobile users discerning vehicle health via auditory cues without formal instruction, such auditory recognition emerges rapidly. Yet, embodying this auditory discernment within an artificial framework introduces intricate challenges. The scope of artificial structures capable of pre-emptive defect or maintenance identification through auditory signals remains expansive. In hearing aids, commonly observed complications encompass inadequate amplification, acoustic reverberations presenting as echoes, and diminished acoustic integrity leading to auditory deformities, frequently labelled as Non-linear harmonic distortion. The present study predominantly concentrates on the pervasive issue of auditory reverberations in hearing aids, often leading to user discomfort. The primary goal revolves around developing a resilient system harnessing an SVM classifier to detect echoes. Notably, the outlined architecture has showcased an accuracy metric of 95.4%.
Narrative Techniques and Symbolism in the Ramayana: A Literary Analysis
Authors: Neha Singh , Dr. Priya Raghav,  Dr Hanan Khalid Khan
Published: December 2023

For ages, academics have been fascinated by the epic poem known as the Ramayana, which is considered to be one of the most respected works of Indian literature. This study will conduct an extensive literary examination of the Ramayana, with a special emphasis on the Ramayana's storytelling strategies and symbolism. This research aims to discover the deeper levels of significance that are buried in the epic's verses by conducting an investigation of the complex narrative techniques that are used throughout the text. It explores the use of allegory, metaphor, and allegorical storytelling that the sage Valmiki, the epic's original author, and successive retellers utilised in their narratives. The look at the ubiquitous symbolism in the Ramayana and analyses how it functions as a potent vehicle for transmitting important philosophical, ethical, and cultural ideas. This research aims to shed light on the enduring literary significance of the Ramayana and its capacity to resonate with readers across a wide variety of cultural and temporal contexts by dissecting the text on both a structural and thematic level. The research was carried out in order to achieve this goal. As a result of this, it provides new insights into the ageless allure and everlasting significance of this ancient epic.
Hybrid Nil Rapid Fuzzy Bi-Ideals of Near Rings
Authors: Dr. M. Himaya Jaleela Begum, G. Rama
Published: December 2023

In this paper, our mains focus is on exploring the concept of hybrid nil rapid fuzzy bi-ideals of near rings, including an investigation of their properties. We also delve into the hybrid intrinsic product of these bi-ideals and establish relevant theorems. Our contribution lies in advancing the field of hybrid nil rapid fuzzy bi-ideals in near rings by deepening our understanding of these concepts.
Comparative Analysis on Image Compression Algorithm Based on Block Truncation Coding
Authors: C. Jenifer Kamalin, Dr. G. Muthu Lakshmi
Published: December 2023

Block Truncation Coding is a quick and effective method for compressing images, because it employs a non-parametric one-bit or two-bit quantization procedure that adapts to the features of the image. This paper describes and compares the performance of BTC and BTC based techniques such as Enhanced Block Truncation Coding (EBTC), Modified Block Truncation Coding (MBTC), and Adaptive Block Truncation Coding – Edge Quantization (ABTC – EQ). These techniques were applied on the general images and their performance were measured using the metrics such as Peak Signal Noise Ratio (PSNR), Structured Similarity Index Measure (SSIM), Weighted Peak Signal Noise Ratio (WPSNR), Feature Similarity Index Measure (FSIM) and Compression Ratio (CR).
Detecting Ocular Tb With Modified Co-Occurrence Matrix
Authors: Dr. C. Kumuthini, P. Nithya
Published: December 2023

Image mapping is a method both for identifying and retrieving similar images from a large database of digital images. This system utilizes the low level image features such as color, texture and shape for retrieving similar images. Among the low level image features, color and texture are perceptually important low level features.  Hence this paper entitled “Detecting  ocular  TB  with  modified co-occurrence matrix ”  uses  the color and  texture  information for  identifying similar images from the database. The texture features are extracted from images using the modified co-occurrence matrix which is called texton co-occurrence matrix and the RGB color model is used for color texture.
Encoding And Decoding Process Using Prime Graceful Labeling
Authors: M. V. Nayana, K. R. Sobha
Published: December 2023

In this paper, an interesting application of Prime graceful labeling in the field of coding theory is examined. Here, a new algorithm for encoding and decoding blended with prime graceful labeling is constructed and an interpretation for the proposed algorithm is also presented.
Economic Vulnerability of Coastal Households in Southern Tamilnadu
Authors: Dr. D. Radhika, Dr. A. Priyanka, Dr. F. Cisma
Published: December 2023

India is the world's largest fish employer and a leader in the fish business, according to statistics on fisheries and aquaculture. Regrettably this industry is largely affected by the change in the nature and one among it is climate changes. The effects of this climatic change manifest in the form of extreme weather events with varying frequency and intensity and due to which the sea level is increasing by the end of 21st century. The lives of coastal communities are also made more difficult by the increase in cyclones, storm surges, and coastal floods as well as the decrease in ocean fish catch brought on by human-caused climate change. Tamil Nadu is one of the top fish producing States located on the southern coast of India. In 2019 Tamilnadu produces 3.56 million metric tons of marine fish up 2.1% year on year. Tamil Nadu recorded 21 fishing villages in Thoothukudi district while the district’s revenue and administrative boundaries mention 24 fishing villages or hamlets in six coastal taluks. A structured questionnaire was administered and the respondents were personally contacted upon getting receiving assistance from the religious and community leaders. Employing random sampling, 689 samples from 24 coastal villages in Thoothukudi District. Economic Vulnerability Index (EVI) was measured with three different constructs namely; Exposure, Sensitivity, and Adaptive Capacity for each taluks. During the lean period, extreme weather conditions and climate change, the traditional fishing communities are also forced to adopt alternate livelihoods to satisfy their needs and the economic development of the country. The findings of the study show that the extreme weather conditions make costal households more vulnerable and lead to financial loss to the economically backward people. Out of six taluks Tiruchendur and Srivaikundam region people are more vulnerable due to the high degree of dependency on fishing and fishing- related economic activities.
Analysing The Diverse Perspectives On Balance Of Power
Authors: Kleophas Narzary, Anjima Narzary
Published: December 2023

The concept of the Balance of Power has long been a significant factor in the realm of international politics. This article examines the evolution of power dynamics across time, starting with its inception in the early modern European state system and extending to its expansion on the global scale. The study delves further into the intricate dynamics of power equilibrium by examining the impact of various perspectives on its implementation and perception. The Peace of Westphalia, which was created in 1648 after the end of the Thirty Years' War, introduced a framework whereby governments aimed to prevent the dominance of a single power and maintain peace via the formation of alliances and the division of power. This event served as the foundational ground for the concept of the balance of power in historical context. The notion, which was originally centred in Europe, ultimately evolved into a fundamental principle of international law. The article also investigates several perspectives on power dynamics, with a specific emphasis on the realism paradigm that prioritizes state-centred evaluations of power and self-interest. The examination also includes an analysis of the liberal perspective, which prioritizes international institutions and collaborative endeavors aimed at maintaining stability. Furthermore, it engages with the constructivist paradigm, which emphasizes the significance of ideas, identities, and norms in shaping international power dynamics and conduct.
Analytical Studies on Techniques and Algorithms of Automatic Number Plate Recognition
Authors: Mr. Mehul T. Patel, Dr. Ashishkumar Parejiya
Published: December 2023

The city's efforts to improve traffic make a big step forward when license plates can be read. It explains how an intelligent transportation system should work and what steps should be taken for it to be successful. Because the number of cars is growing so quickly, ANPR is a must-have for managing traffic control. Automatic number plate recognition (ANPR) is mostly used to keep an eye on traffic and keep people safe. Number plate recognition uses image processing and the most recent advances in technology to automatically read the characters on a vehicle's license plate. In the last few years, there have been a number of technological advances in the field of studying how to read license plates. Image processing techniques like OCR make it possible for traffic surveillance to solve a wide range of problems that come up during criminal investigations, the collection of tolls, the monitoring of traffic, the regulation of speed, and the management of parking, among other things. If you want to control traffic and keep an eye on a large number of people in a transportation system, you need an ANPR system. Image processing techniques and the collection of photos of vehicles for use in the dataset have made it possible to keep an eye on traffic on a large scale. Automatic License Plate Reader (ANPR) is a way to take the steps needed to run a good intelligent transportation network. Traffic control has become an absolute must because the number of cars has grown so quickly. The main goal of ANPR is to keep an eye on and record traffic for defense purposes. To read the text on license plates, number plate recognition uses image processing, optical character recognition (OCR), and edge detection technology. The model is made up of three different parts called, respectively, the module for car detection, the module for license plate segmentation, and the module for recognition. Image processing made us more determined to stop a wide range of illegal activities, such as armed robberies of cars, breaking traffic rules, and the way law enforcement is handled. This review study looked at all of the different designs for reading license plates that have been put into use so far.
Optimizing Biodiesel Blend Performance with Nano Additives in Diesel Engines for Sustainable Environmental Impact
Authors: Neelapu Madhu Latha, Potnuru Sivaram, I.N.Niranjan Kumar
Published: December 2023

Biodiesel, a sustainable alternative to traditional petroleum-based diesel, can be derived from various sources such as vegetable oils, animal fats, and recycled cooking oils. Its production and use have gained momentum due to its potential to reduce greenhouse gas emissions and diminish our reliance on fossil fuels. The combustion of fossil fuels contributes significantly to climate change and various forms of pollution. In India's agricultural sector, the production of biodiesel from non-edible plant oils has witnessed a surge in popularity. However, the current supply of these biodiesels falls short of meeting the growing demand for fossil fuels. To address this challenge, a novel biodiesel formulation using non-edible oils has been developed. This study aims to create an innovative biodiesel blend comprising 50% cottonseed biodiesel, 50% rapeseed biodiesel, and diesel with the addition of cerium oxide. The results obtained with CR20N50 indicate a substantial 15–18% reduction in fuel consumption, a notable 12–22% decrease in carbon monoxide emissions, and a significant 13–20% reduction in hydrocarbon emissions compared to conventional diesel fuel.
Study On Moderate Distribution In The Statistical Framework
Authors: Susheel Kumar, Dr. Mahender Singh Poonia
Published: December 2023

This essay is a personal investigation into the origins, consequences, and significance of the concepts of "distribution" that we are working to instill in children. When creating learning experiences, these factors need to be in the back of our minds. The idea of "distribution" is formed as a filter through which statisticians view the variety in data. I investigate the causes of data variation, the distinction between empirical and theoretical distributions, the characteristics of statistical models, sampling distributions, the conditional nature of distributions used for modelling, and the foundations of inference.
From Sci-Fi to Reality: The Impact of AI on Automotive Manufacturing and Design
Authors: H. Ateeq Ahmed G. Saideeep,
Published: December 2023

As Artificial Intelligence (AI) continues to advance, it is having a significant impact on the automotive industry, particularly in the areas of manufacturing and design. This paper explores the impact of AI on automotive manufacturing and design, including its influence on autonomous vehicles, supply chain management, predictive maintenance, quality control, and the workforce. It also examines the role of AI in designing sustainable automotive systems, as well as the ethical considerations of its use in the industry. Additionally, the paper considers the impact of popular culture, specifically sci-fi movies and TV shows, on the development and adoption of AI in the automotive industry.
Women Managers in Healthcare: A View on Corporate Social Responsibility
Authors: Shailesh Kumari, Viney Lather, S. Mahalingham, K. Manivannan
Published: December 2023

Corporate Social Responsibility has become an integral part of business ethics and sustainability. In the healthcare sector, the role of women managers in promoting CSR is crucial. In the realm of healthcare management, the integration of corporate social responsibility (CSR) is vital for promoting ethical practices and social impact. This research article explores the role of women managers in healthcare, examining their unique contributions to CSR initiatives.
A Study of Health and Technology Use: Impact of Digital Media on Mental Health
Authors: Dr. Padmanabhan. T
Published: December 2023

In the era of digitalization, digital technologies and machines surpass and change daily activities. Digitalization significantly influenced daily practice, skills, and passion, significantly to the sleep cycle and work culture. It cuts human work and lowers errors. Digital media enables social interaction in a virtual world which is user-friendly, money-saving, energy efficient, and easily accessible. Likewise, social media usage has increased for communicating, learning, collaborating, and engaging in entertainment and shopping activities. Overuse of social media is associated with low work performance and other physical and mental issues such as less healthy social relationships, sleep problems, low life satisfaction, feelings of jealousy, anxiety, and depression. This study focuses on the impact on people's health due to the unrestricted use of technology. The study analyses people's physical and mental problems in association with technology.
The Monophonic Metric Dimension of Degree Splitting Graph
Authors: J. Suji Priya,  T. Muthu Nesa Beula
Published: December 2023

Let  be a simple graph and  be an ordered set and. The representation  of  with respect to  is the -tuple  . Then is called a monophonic resolving set if different vertices of  have different representations with respect to . A monophonic resolving set of minimum number of elements is called a minimum monophonic set for  and its cardinality is known as the monophonic metric dimension of , represented by  In this article, we determined the monophonic metric dimension of degree splitting graph.
Enhancing HEVC Compression: A Novel Algorithm for Swift and Efficient Intra Prediction
Authors: Aravinda H S M. N. Praphul,
Published: December 2023

High-Efficiency Video Coding (HEVC) represents the cutting-edge in video compression standards for high-resolution visual data. The prowess of HEVC lies in its utilization of prediction, capitalizing on signal redundancies to attain optimal compression efficiency. A key feature, the Intra-Picture prediction block, anticipates a block within the present frame by referencing information from adjacent blocks within that same frame. Nonetheless, this innovation introduces a significant surge in encoding complexity. Addressing this surge and reducing the computational demands of the coder becomes imperative. The present research introduces an innovative algorithm targeting mode decisions grounded on intra prediction. This algorithm assesses the texture intricacy of the coding unit and establishes an optimal threshold, enabling swift coding unit size selection. Subsequently, an enhanced search procedure minimizes the candidate modes of prediction. Culminating this approach, early termination gets implemented for rate-distortion optimized quantization (RDOQ) within Intra prediction. Findings indicate that the novel algorithm facilitates a reduction of approximately 40.9% in encoding duration.
Solar-Powered Drone for Extended Flight Time
Authors: Lakshmi K K Hareesha N G,
Published: December 2023

Drones can now fly for longer periods and have a smaller carbon footprint. These drones have solar cells that use sunlight's energy to power the drone and other components on board. Agriculture, disaster relief, and environmental protection can all benefit from the development of solar-powered drones. The present research aims to increase battery life so that flights can last longer. It gives a general overview of the drone's parts and solar cells, outlining potential applications. Incorrect weight distribution can cause instability and make it difficult to achieve lift, rendering the drone incapable of flight and confined to ground-based operations The drone being discussed has a well-balanced weight distribution, which restricts its functionality and prevents it from flying correctly. Proper weight distribution has been achieved in the drone under consideration in this study, leading to stable flight and improved endurance.
Digital Financial Literacy among Working Women in Kerala:a Study with Special Reference to Malappuram District
Authors: A.Anandalakshmy, Sajeer.Cdr. ,
Published: December 2023

In today's digital era, financial literacy plays a crucial role in empowering individuals to make informed decisions regarding their finances. With an increasing number of women joining the workforce and the growing importance of digital financial services, it is essential to understand the level of digital financial literacy among working women in Kerala. This study focuses on digital financial literacy among working women in Kerala, with a special reference to the Malappuram district. The study used descriptive research design and the primary data collected from 130 working women in Kerala. The researcher identified that the four factors such as Financial Inclusion, Awareness, Access to Technology, Peer Influence are the factors affecting the digital financial literacy. The result also identified that the digital financial literacy explains approximately 65.6% of the variation in the investment behaviour among working women in Kerala.
Studying the Cognitive Specifications of Perceiving Environment in Older Adults and Their Behavior Using Cognitive Maps, Case Study: Kahrizak Nursing House
Authors: Elham Ataei. Siamak Panahi, Farnaz Cheraghifar,
Published: December 2023

Cognitive aspects in different fields of older adults’ perception of architecture were discussed to determine cognitive specifications of the older adults living in Kahrizak Nursing Home (Tehran) using cognitive maps. The association between older adults’ cognitive maps and spatial structure of the nursing home was also examined. In terms of nature, this study is an applied-theoretical work. The study was carried out in two phases namely, qualitative and quantitative; and as to the objective, the study was an applied work. Data gathering was done through a library-document method and the status quo of the nursing house was examined through field observations. In addition, interviews were conducted for data gathering. The space syntax approach was used for analyzing the spatial structure of the nursing home. Simulations were carried out in Depth Map and as the results indicated the highest integration was equal to 7.3 and the mean value was equal to 3.5. The maximum and mean values of connectivity were 20 and 8.6 respectively; these figures for choice were 67 and 11.06 respectively. Maximum and mean values of total depth were 257 and 138.7 respectively. The results indicated a significant relationship between the cognitive maps of the older adults and the analyses based on the space syntax method. This can be attributed to the physical structure of architecture in Kahrizak Nursing Home.
Design and Applications of Digital Differentiators Using Model Order Reduction Techniques
Authors: Dhanarasi Gowtham B.T.Krishna ,
Published: December 2023

A model order reduction technique is employed to design novel digital differentiators. The new mapping technique from s domain to z domain conversion is investigated in this paper. The differentiators under consideration are second order one viz. Simpsons and Tick differentiators. The novel transfer functions obtained by the model order reduction technique can be used in many signal processing, Image processing applications. As an example, edge detection application is illustrated.
Dynamic efficacy of soil pollution using Fractional order model-An Adomian Decomposition approach
Authors: Sabarmathi A. Priya P.
Published: December 2023

In this paper, a nonlinear fractional order eco-epidemic model of soil pollution is considered with four compartments namely, Susceptible soil (S), Polluted soil (P), Remediate soil (T) and Recovered soil (R). The local and global stability of both pollution free equilibrium and pollution extinction equilibrium points are studied around the equilibrium points. Also, the non-negativity and existence of unique solution of the model is proved using fixed point theorem. Adomain decomposition method is used to find the approximate solution of the proposed model. Numerical simulations of the model are carried out through MATLAB which helps to understand the role of parameters and to validate the theoretical findings.
Breast cancer prediction using K Nearest Neighbors, Support Vector Machine Techniques
Authors: V. Sasirekha P. Visalatchi,
Published: December 2023

Breast cancer is the trickiest and sneakiest diseases that modern science is aware of. It is one of the most important causes of death for women worldwide. We introduce the SVM (Support Vector Machine) and KNN (K Nearest Neighbors), which are the machine learning algorithms for breast disease diagnosis by training its attributes, and we present an original prediction of breast cancer. The suggested system employs 10-fold cross validation to produce accurate results. The UCI machine learning warehouse was used to obtain the Wisconsin breast melanoma diagnosis data set. The accurateness, sensitiveness, specificity, false detection rate, false exclusion rate, and Matthews' correlation coefficient are used to evaluate the presentation of the suggested system.
Mathematical Model on Minimality of Vaccination Costs of Covid-19 Using Fractional Order
Authors: Roselyn Besi.P Vijayalakshmi.G.M,
Published: December 2023

An extremely efficient method of halting the horrible spread of pandemics is vaccination. This research investigates the cost-effectiveness of vaccine doses using a fractional-order commensurate model. The ABC type fract-integrals of COVID-19 multi-compartmental model is used to investigate the efficacy of vaccination dosages, vaccine shortages, and dose distribution. In order to assess the costs of vaccination and its use to combat COVID-19 in India, we created a fractional order model with 4 compartments of vaccinated and people waiting for booster shots have beed framed. Vaccination cost control model for this study is designed and analysed through the existence, stability and threshold measures. Through numerical convergence and simulations, the increase in disease severity brought on by microbial pathogens is investigated. Using fixed point theorems, the existence and singularity of the solution space for the framed model are assessed. Inventory control entropy on fractional derivative is used to assess the minimisation of vaccine costs
Assessment of a Coordinated Arrangement of Wearable Physiological Sensors for Stress Checking in Work Spaces by Utilizing Organic Markers
Authors: N.Ragupathi B.Manojkumar, S.Jeniton, S.Pragadeswaran,
Published: December 2023

The objectives of this investigation were to create and evaluate a wearable physiological sensor system for detecting human stress using ECG, EDA, and EEG data, as well as to see if the changes in physiological indicators were correlated levels. The main elements of the study are listed below. This study included 15 healthy volunteers with an average age of 40.8 years, comprising seven men and six women. They underwent the well-known Maastricht Intense Stress Test, a procedure that is known to cause significant physical and psychological stress, while wearing three commercial sensors have been employed to keep track of their physiologic responses.Throughout salivary samples were taken at various points. The use of a Salivary concentrations of cortisol were correlated with the obtained physiological indicators using an algorithm called the Support Vector Machine (SVM) segmentation technique were both part of the statistical analysis. A significant ability to discriminate between stress and relaxation was shown by fifteen features obtained from measurements including heart rate variability, electro dermal activity, and electroencephalography signals. Based on these important features, the classification system produced results with an accuracy rate of 86% that was satisfactory.Furthermore, the correlation analysis revealed, with an R-squared value of 0.714, a considerable consistency between changes in physiological characteristics and the trends in salivary cortisol levels. The study successfully showed that the wearable sensor system's implementation caught human stress levels and measured the state of stress with accuracy. The design of adaptable and controllable systems, such as medical devices, targeted at inducing interventions to stop stress-related effects, is particularly affected by these findings.
Medical Image Classification Using RNN in Quadri-Partitioned Neutrosophic Set
Authors: S. Santhosh Kumar A. Panimalar , D. Aarthi ,
Published: December 2023

The classification of brain tumor is essential for both diagnostic and therapeutic planning. Recurrent neural networks (RNNs) have demonstrated promising results in analyzing sequential data in recent years. Quadri-partitioned neutrosophic sets additionally offer a structure for capturing ambiguities and uncertainties in classification problems. This study investigates the categorization of brain tumors using an RNN with a quadri-partitioned neutrosophic set. The study aims to increase classification accuracy and offer information on how certain forecasts can be made. The suggested method QPN-RNN’s accuracy in classifying brain tumors while considering the quadri-partitioned neutrosophic set is shown by experimental data.
Trends of Atmospheric Black Carbon Concentration over the Bengaluru
Authors: G P Shivashankara A Jaswanth Gowda, G S Munawar Pasha, Suresh Tiwari,
Published: December 2023

This study investigates the spatial and temporal variations of atmospheric black carbon (BC) concentrations in Bangalore, focusing on the period from June 2018 to May 2020. BC mass concentrations were measured using a portable micro-Aethalometer (model: AethLabs AE-51) at seven different locations, representing a range of land use types from rural to urban areas. The study aimed to assess BC pollution levels, identify hotspots, and understand the factors influencing BC concentrations. The results revealed significant variations in BC concentrations among the different locations. The highest BC concentrations were observed in urban traffic and industrial areas, with average concentrations of 6.21 µg/m³ and 6.78 µg/m³, respectively. Urban centres also exhibited high BC levels, with an average concentration of 7.40 µg/m³. In contrast, rural areas recorded the lowest BC concentrations, with an average of 2.51 µg/m³. These findings highlight the influence of anthropogenic activities and land use patterns on BC pollution levels. Diurnal variations in BC concentrations exhibited distinct patterns, with significant peaks during morning and evening hours, primarily associated with increased traffic emissions. The study also identified seasonal trends, with higher BC concentrations observed during winter months, attributed to stable atmospheric conditions and increased fuel consumption for heating purposes. Notably, BC concentrations were generally lower during summer months due to higher wind speeds and increased vertical mixing of pollutants. The findings of this study emphasize the need for targeted mitigation strategies to reduce BC pollution in Bangalore. The identified hotspots, such as urban traffic and industrial areas, require specific attention to mitigate the adverse health and environmental effects of BC emissions. Furthermore, the study underscores the importance of comprehensive air pollution management approaches that consider both local emissions and meteorological factors to effectively tackle BC pollution.
The Actions of Leech Saliva Components and Their Mechanisms in Antitumor Activity
Authors: Nurul Azmir Amir Hashim Chen Chuang,Mo Lingling, LI Xiangshen, Pan Li,
Published: December 2023

Malignant tumor (hereinafter referred to as tumor) has become a major category of chronic diseases that curb human life and seriously threaten human health.For advanced tumors, chemotherapy, radiotherapy, targetedtherapy and immunotherapy effects are still not satisfactory, and they are particularly urgent to find new therapeutic drugs.The medical leech therapy(MLT) can be traced back to the period of ancient Greece and ancient India for disease treatment.The discovery and appraisal of the leech saliva of hirudin aroused the research interest on the saliva of the lequale.Yet of the more than 100 compounds of different molecular weights detected in leech saliva, only a small fraction have been identified as having therapeutic potential.Studies have shown that the saliva activity ingredients have certain advantages in anti-tumor metastasis, which has attracted the attention of scholars.This article reviews the role of the active ingredients of the saliva and its anti-tumor mechanism in recent years, and provides a reference for the application of the leech saliva.
Examining the Antecedents of Defence Indigenization for Modernization of Armed Forces in India
Authors: A.K. Srivastav Manpreet Kaur, PJS Pannu,
Published: December 2023

When it comes to protecting a nation's sovereignty and national security, the role that the defence industry plays is indispensable.In recent years, there has been an increasing emphasis on indigenization, which refers to the development and manufacturing of military items within the borders of a country. It entails putting in place a robust military industrial base that can both contribute to the nation's overall security and fulfill the requirements of the country's armed forces.The modernization of the armed forces is dependent on acquiring latest military hardware , best served through developing indigenous technology. Given the importance of defence indigenization, this paper tries to examine the antecedents of defence indigenization in India using structural equation modelling. The analysis of the data reveals that government policies and private-public partnership play a vital role in defence indigenization. However, transfer of technology is yet to play a significant role in indigenization. Further, there is a strong relationship between defence indigenization and modernization of armed forces. Defence indigenization can be facilitated by fostering private-public partnerships, enhancing technology transfers, and streamlining government regulations.
Causes and Consequences of Child Labour after Covid-19 Situation in Morigaon Town, Assam: A Study
Authors: Md. Wahidur Rahman Parbin Sultana, Rupa Sarmah,
Published: December 2023

‘Child Labour’ being a risk factor all over the worldnow a day is considered an urgent matter of discussion. It needs to sort out various causes and consequencesof child exploitation in any form and find immediate solutions to conduce a serene environment so that budding children can move freely, enjoy their childhood in fearless environment and grow mentally strong to become good human beings of the society. It is seen that child labour is increasing day by day at present due to the post effect of covid-19 and other causes like poverty, lack of education, societal negligence, addiction, illness, and so on. Thus, this paper aimsto find out various causes and factors responsible for child labour in Morigaon Town, Assam, at present. For this, the data will be collected with the help of questionnaire from theIn-Charge ofDistrict Child Protection Unit (DCPU),Morigaon, Assam, the Sarva Shiksha Abhiyan, Morigaon, Assam, the Secondary Schools of Morigaon Town, Assam,and by using observation and interaction method with the child-labourers and their parents belong to thiscentral area,connected from different villages and mini towns. Moreover, many case reports of child-labour after covid-19 will be collected from the Advocates of Morigaon court,will be analysed.
Role of Privacy Metrics in Next Generation Smart Cities
Authors: A.S.N. Chakravarthy Manas Kumar Yogi,
Published: December 2023

In the evolving landscape of urbanization, the concept of smart cities has gained momentum, integrating technology to enhance urban living. However, as cities become increasingly interconnected and data-driven, the paramount importance of privacy within this context cannot be overstated. This abstract delves into the multifaceted significance of privacy in the realm of smart cities. The seamless integration of data-driven technologies, such as Internet of Things (IoT) devices and advanced surveillance systems, offers unprecedented urban management opportunities. Nonetheless, this integration poses substantial threats to personal privacy. Balancing the potential benefits of smart city solutions with the preservation of individual autonomy and data security is a critical challenge that policymakers, technology developers, and citizens must collectively address. The abstract emphasizes that safeguarding privacy in smart cities is not merely a matter of individual preference, but a fundamental human right. Analyzing various dimensions, from the ethical implications of constant surveillance to the risks of data breaches, it becomes evident that effective privacy protection contributes to fostering trust among citizens, encouraging their active participation in the smart city ecosystem. Through a comprehensive review of current practices and regulatory frameworks, this abstract underscores the necessity of a holistic approach to privacy preservation. Ultimately, this abstract underscores that while smart cities hold immense potential to revolutionize urban living, ensuring privacy protection is not only a legal and ethical obligation but also a prerequisite for their long-term success and societal acceptance.
Role of Herd Behavior on Investment Decision of Mutual Fund Investors in India - An Empirical Study
Authors: Jyoti Mishra Rekha Gothe,
Published: December 2023

Behaviour finance helps to understand the attitude and perception of investors on their investment decisions. Every investor differs from others in all the aspects due to a range of factors like demographic and socio-economic background. An optimal investment decision plays a vital role and is a major deliberation.

This paper analyses the role of herding behaviour on Indian mutual fund investors. By referring to psychology and pointing out the imperfections of a human mind, it reveals mistakes committed by both individual and professional investors.

This study captures the impact of herding behavior and overconfidence biases on the investors’ decision-making in India The proposed study will collects the necessary data through questionnaires distributed among 113 respondents who were investing in mutual fund. The results show that overconfidence and herding bias have significant positive impact on investment decision. Overall results conclude that individual investors have limited knowledge and more prone towards making psychological errors. The findings of the study also indicate the existence of these four behavioral biases on individual investment decisions. This study will be helpful to financial intermediaries to advice their clients.
Study of the need of Gandhi ideology in the Present Era
Authors: Manisha, Dr. Sumeshta
Published: December 2023

This review paper examines the enduring relevance of Mahatma Gandhi's ideology in the contemporary world. Gandhi, an iconic figure in the Indian independence movement, was a proponent of nonviolent resistance, self-reliance, social justice, and ethical leadership. In an era marked by global conflicts, environmental challenges, and social inequalities, Gandhi's principles of nonviolence and peaceful resistance continue to offer valuable insights for addressing complex issues. This paper conducts a comprehensive analysis of the applicability of Gandhi's ideas in modern contexts, drawing on examples from various regions and disciplines. It explores how his philosophy resonates with contemporary concerns such as environmental sustainability, social justice, and ethical leadership. By critically assessing the strengths and limitations of Gandhi's ideology, this paper provides a nuanced understanding of its relevance in addressing pressing challenges in the 21st century. The findings of this review paper underscore the timeless wisdom of Gandhi's principles and their potential to inspire positive change and progress in the present era.
An ECG Signal Denoising Method Using Filtering Techniques
Authors: B. Trimula Krishna S. Bindu Bhargavi ,
Published: December 2023

This study presents a novel approach for denoising electrocardiogram (ECG) signals, aimed at improving their performance and availability under noisy conditions.The suggested method harnesses Conditional Generative Adversarial Networks (CGANs) tailored for the purpose of denoising Electrocardiogram (ECG) data. This approach comprises two essential elements: an improved Convolutional Auto-Encoder (CAE)-driven generator and a discriminator with four convolutional layers and a fully connected layer. It takes advantage of the ECG signal's innate ability to retain spatial proximity and neighboring patterns in more advanced feature representations, aided by skip connections that aid gradient propagation during the denoising training process, the resulting model exhibits strong performance and generalization capabilities. This method incorporates advanced filtering techniques, including IIR notch filters, The combination of l2 and l1 trend filtering along with a Kalman filter has been employed to enhance the quality of an ECG signal, rendering it more amenable for subsequent analysis and identification. These filtering methods prove particularly advantageous when dealing with ECG signals exhibiting a high Signal-to-Noise Ratio (SNR). Extensive experimentation conducted using the MIT-BIH database has validated the efficacy of these filtering techniques in effectively eliminating various sources of noise, while preserving the unique characteristics of the ECG signals.