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Optical design studies for national large optical-IR telescope
A 1012 m class national large optical-IR telescope (NLOT) is envisaged to meet the growing scientific requirements in astronomy and astrophysics. Telescopes of such dimensions can only be made by segmenting the primary mirror, as it eases a more prominent primary mirrors fabrication, transportation, operation, and maintenance process. This paper presents the various optical designs analyzed for NLOT that can be fabricated using the India TMT Optics Fabrication Facility (ITOFF) at the Centre for Research and Education in Science and Technology (CREST) campus. We present the primary mirror segmentation details, its ideal optical performance, and study each designs advantages and technical complexities. Based on the above analysis, we have narrowed it down to an optimal design, and its performance analysis is also discussed. Indian Academy of Sciences 2024. -
The role of religious and financial factors in eudaimonic well-being among Indian adults
Purpose: The available literature has explored the various psychosocial determinants of well-being to some extent. The earlier works have focused primarily on hedonic well-being with little focus on eudaimonic aspects. Therefore, this study aims to understand the role of parentchild religious attendance during childhood, religious connectedness, and financial-material stability on eudaimonic well-being among adults in India. Design/methodology/approach: The authors used the India data from Global Flourishing Study Wave 1 that addressed flourishing among adults above 18 years. The authors considered 9,076 Indian adults and used descriptive and correlation statistics. In addition, the authors conducted path analysis and t-test. Findings: The likelihood of eudaimonic well-being increased with parentchild religious attendance during childhood (= ?0.044, p < 0.01) along with religious connectedness (= ?0.112, p < 0.01) and financial-material stability (= 0.145, p < 0.01) as an adult. In addition, a significant difference existed in terms of religious connectedness and eudaimonic well-being with income and perceived feelings about income. Originality/value: This study emphasizes financial stabilitys relevance in well-being and suggests the importance of considering religious factors during childhood and adulthood. Emphasizing factors influencing eudaimonic well-being is relevant due to its influence on mental health and quality of life. 2024, Emerald Publishing Limited. -
A Model for Detecting Type 2 Diabetes Using Mixed Single-Cell RNA Sequencing with Optimized Data
Diabetes is a critical disease and is crucial to personage agility. Type 2 Diabetes (T2D) accounts for 92% of epithetical cases. This paper proposes an optimized type 2 diabetes detection model using mixed single-cell RNA sequencing (scRNA-seq) technology. Diabetes is a chronic metabolic disorder affecting millions of people worldwide. Early detection of the disease can greatly improve treatment outcomes, but current diagnostic methods have limitations. Our proposed model integrates scRNA-seq data from both human pancreatic beta cells to identify gene expression patterns associated with diabetes. Our study shows that the proposed model is highly accurate in identifying diabetes, achieving an area under the curve (AUC) of 0.98. We employed an optimized model to improve the detection of diabetes at an early stage, leading to better treatment outcomes and an improved quality of life for patients. We initially incorporated optimal features from the dataset using the Monte Carlo (MC) feature selection method. This method helped us to estimate the relative importance (RI) score of each gene or feature, which is then used to rank the features. Further, we proposed an optimized deep belief network (ODBN) as a classification model to classify T2D and non-diabetes. To improve the performance of ODBN, an adaptive chimp optimization algorithm (AChOA) is introduced to optimize the weight parameters and achieved a performance accuracy of 96.57%. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
An Investigation of Complex Interactions Between Genetically Determined Protein Expression and the Metabolic Phenotype of Human Islet Cells Using Deep Learning
The relationship between gene modules and several genome-scale metrics was examined, including heterozygosity that caused type 2 diabetes due to insulin deuteration, differential expression, genotyping association, methylation, and copy number changes. This work investigates the complex relationships between protein expression, genetic polymorphisms, and metabolic properties of human islet cells using expression quantitative trait loci (eQTL) detection. We looked at the genomic, transcriptomic, and proteomic information from islet cells in persons with type 2 diabetes. From the information from different levels, we noticed novel eQTLs that regulate crucial metabolic and signaling pathways in islet cells. Our study highlights the importance of a systems-level approach in understanding the complicated biological processes by highlighting the complexity of the link between genetic variants, protein expression, and metabolic abnormalities using the PIMA Indian dataset. Our findings provide novel insights into the molecular mechanisms behind islet cell failure in type 2 diabetes, potential targets for emerging treatment strategies, and the genomic implications of variations in gene expression, mutations, and other factors. To accomplish this purpose, we proposed a novel BLB model and obtained 99.89%. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
An Human Islet Cell RNA-Seq for Genome-Wide Genotype Deepsec Framework Using Deep Learning Based Diabetes Prediction
Evaluating the tissues responsible for complicated human illnesses is important to rank significance of genetic revision connected to features. In order to make predictions about the regulatory functions of geneticsvariations athwart wide range of epigenetic changes, this article introduces a Convolutional neural network (CNN) model upgraded filters and Deepsec framework incorporated with comprehensive ENCODE and Roadmap consortia have compiled a human epigenetic map that indicates specificity to certain tissues or cell types. Deepsec framework integrates transcription factors, histone modification markers, and RNA accessibility maps to comprehensively evaluate the consequences of non-coding alterations on the most important components, even for uncommon variations or novel mutations. By using trait-associated loci and more than 30 different human pancreatic islets and their subsets of cells sorted using fluorescence-activated cell sorting, annotations of epigenetic profiling were obtained (FACS) on a genome-wide scale. The proposed model, used '1492' publicly available GWAS datasets. My team presented that deepsec framework does epigenetic annotations found important GWAS associations and uncover regulatory loci from background signals when exposed to CNN-based analysis, offering fresh intuition underlying nadir causes of type 2diabetes. The suggested approaches are anticipated to be extensively used in downstream GWAS analysis, making it possible to assess non-coding variations and conduct downstream GWAS analysis 2023 IEEE. -
An Predictive Deep Learning Model is used to Identify Human Tissue-Specific Regulatory Variations For Diabetes
A predictive deep learning model is designed to predict a target variable based on a set of input variables to diagnose the tissue base regulatory variants in the human islets. In this article, the identification on human tissue-specific regulatory variations for Diabetes using the Pima dataset converting data into images, and then the input variables may include genetic data, gene expression data, and the proposed model uses Pima Indian dataset with the attributes such as age, sex, and BMI to predict whether a person has Diabetes or not. And this dataset is incorporated a combination two layered ResNet18 + ResNet50 and SVM classifier. The results obtained are compared with KNN, Naive bayes, SVM Random Forest, Gradient descent and the accuracy achieved is 98%. 2023 IEEE. -
Prognosis of Diabetes Mellitus Paradigm Predictive Techniques
Human life is in the era of data, when almost everything is straped on to data wellspring more- over entire esse are digitises telerecorded. That is data is generated every milli second through several means like Agriculture, Bioinformatics, Web, Cybersecurity, Smart city data, classified in- formation, pda data, flexibility evidence, medical facts, Covid related data from official state too central government portals and a number of other sources are available in todays technological con- text. There are various forms of data like structured, semi-structured, and unstructured data, text, graphics are all feasible. Every day, week, month new genre natural-world features to be resolved, machine learning adroitness have emerged as problem resolver. As a result, data management tools and analytical methodologies capable of extricate penetrated realization related specifics felicitous methodical manner ceaselessly whereby world of nature enactment rely urgently needed. The vast majority of research is focused on machine learning prediction algorithms; thus, we focus on these. Our evaluation aims to provide newbies to the field, as well as more seasoned readers, with a thorough understanding of the primary approaches and algorithms developed over the previous two decades, with an emphasis on the most notable and continuing work. We also present a new taxonomy of state of the art Model, which highlights the many conceptual and technical approaches to training with labeled and unlabeled data. Finally, we show how the fundamental assumptions underlying most machine learning methods are linked to the well-known assumptions. Grenze Scientific Society, 2023. -
Systematic Contemplate Paradigm on Diabetes Mellitus using different Machine Learning Predictive Techniques
As the foodies love fast food, from micro to combined families across the world the ratio of family members 1:4 is affected with silent killer named as diabetes. A very high blood glucose levels, metabolism, improper carbohydrate, damaged hormone insulin alleviating a human body disability leading to the silent killer of the body parts is the diabetes. An estimated 425 million of people around the globe suffering with diabetes up to 108 million to 1.7 trillion will be affected with diabetes. Therefore millennium, the universe ubiquity suffering with diabetes has next to quadrupled, growing from 9 percent and above among the people. As the eating habits of people in this trendy 21st century is dramatically devastating to the risk of overweight or obese. The silent killer diabetes consequences include kidney failure, Diabetic retinopathy, Heart attack, Stiffness of body muscles, Nerves stroke and lower limb amputation leads to type I and type II diabetes. As the researchers across the globe are using the machine learning algorithms as the reliable problem solver, The complications still continue. The purpose of this percu is to help with the apt selection of features garnishing with machine learning paradigm techniques in selecting the accurate attributes for each person to be properly diagnosed. In this archetype survey paper, we have done a systematic review chronologically a decade research which will help the researchers to explore and get the contemplate on various tangible and intangible data sets they can adopt in diagnosing the mellitus diabetes. Grenze Scientific Society, 2023. -
An ecology intervention in an English studies programme: Contexts, Complexities and Choices
Over the past few decades, there has been a critical mass gained regarding the need to engage purposefully with Ecology. Unfortunately, this has not provoked any stimulating work within the Humanities and Social Sciences academia. In fact, alongside growing realisations about the necessity to address Ecology, there is a glaring absence of any significant engagement. In response to such a vexing reality, the Department of English at Christ University chose to initiate an Ecological venture within its Honours programme. This paper captures - the vigorous debates it lit up, the tough choices that had to be made, and the promise it offers - that complex journey. 2014 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (Dharmaram Vidya Kshetram, Bangalore). -
Emotional Intelligence and General Well-Being Among Middle Aged People
International Journal of Research in Social Sciences, Vol-2 (4), pp. 454-471. ISSN-2249-2496 -
A Study on Factors Impeding Online Buying of Households in Bangalore City
Indian Journal of Marketing, Vol. 46, Issue 4, pp. 7-23, ISSN No. 0973-8703 -
Inquiry into reverse logistics and a decision model
A process in which a product is moving in reverse along the supply chain network is called as reverse logistics. The objective of reverse logistics is to recapture the value of the final product. Reverse logistics is gaining ground because of its importance in managing a closed loop supply chain. Companies across the world are showing concern about environmental degradation and are realising the need for sustainable development. Many countries have already passed legal regulations. Good reverse logistics process indicates lot of reuse, recycling and reducing the material consumed, thereby ensuring sustainability. Improving reverse logistics will result in increase in sales up by 10%, a reduction in the supply chain costs by 25% to 40%. In retail sector the profit margins are less and strengthening reverse logistics can increase the profit margins. This paper attempts to inquire into the reverse logistics area and come out with the prioritised variables impacting the different reverse logistics disposition decision. The paper attempts to propose a conceptual model for reverse logistics disposition decision. Copyright 2019 Inderscience Enterprises Ltd. -
A study on factors impeding online buying of household items in Bangalore city
The tremendous growth of the Internet in India has fuelled the growth of e-commerce in the country. The retail business has been affected like all other businesses. This research paper attempted to study the factors responsible for impeding the online buying of household items by customers. The study was limited to Bangalore city only. The study was conducted during June 2013 and December 2014. The data was collected through questionnaires which were distributed among 500 respondents. Among these, 25 questionnaires were partially filled, and were not included as final responses; 280 completely filled questionnaires were utilized for this study. The non online respondents' profile and descriptive statistics were analyzed. Factor analysis was carried out to find the important factors involved in the non online buying decisions of customers. Some recommendations have been made on the strategies which online retailers can adopt to convert non - online buyers to online buyers of household items by addressing some of their concerns. 2016. -
Determinants of consumer product return behavior with respect to online shopping of apparels
This research aims at finding the determinants of consumer product return newlinebehavior with respect to online shopping of apparel in Bangalore city. The study was administered to 600 respondents, and the response received was from 465 respondents. The convenience sampling method was used to collect samples across Bangalore city. Product return behavior was measured using a newlinefive-point Likert scale for 34 items. The literature review was conducted extensively, covering both Indian and international context. This research is designed to address the literature gaps. Many hypotheses were proposed in the thesis and were examined using structural equation modeling. The hypotheses were tested with the software newlineAMOS 25 and SPSS 25 to fulfill the research objectives. Confirmatory factor analysis was done on the data to confirm the instrument reliability and validity. Confirmatory factor analysis was used to verify the constructs developed from the detailed literature review. ANOVA post hoc test was done to check the relationship among the demographic variables. Descriptive statistics were used newlineto interpret the data. With the help of structural equation modeling, the causal newlinerelationship between the dependent variable and the independent variables were identified. The study on the determinants of product return behavior has provided a lot of newlineinsights. Customer attitude has a significant and negative impact on product return behavior. The customers with a positive attitude towards online apparel purchases will be less likely to return products. The previous customer experience and their consumption pattern have a significant and negative impact on product return behavior. The customers with a bad experience with newlinebuying online apparel products, tend to return their products more. The perceived risk of online apparel purchases has a significant and positive impact on product return behavior. The customers with a high perceived risk of online apparel purchases will be more likely to return their products. -
Forensic Investigation Approaches of DNA Analysis and Criminal Investigation
Deoxyribonucleic acid (DNA) has been a significant factor in the criminal justice system since it was first used in forensic investigations. The reference sample's DNA profile is typically compared to the DNA profile from the evidence sample from the crime scene criminal cases. Familial DNA analysis can identify a person and provide significant investigation leads even without a reference sample for comparison in a criminal investigation process. The potential source of a forensic biological sample is determined using several indirect database searching techniques. These DNA-based techniques include Mitochondrial DNA (mtDNA) analysis, investigative genetic genealogy (IGG), familial searching, and Y-STR database searching. This study examined these methods and compares them in terms of searching efficiency, database structures, searching methods, genotyping technologies, data security, data quality, and costs. It also raises several possible legal and privacy problems for scientists to consider further. The significance of familial DNA analysis, the procedures used for finding and identifying relatives using familial DNA, and its benefits in forensics are all covered in this paper. Additionally, future options for the appropriate application of this technology and social, legal, and ethical concerns related to familial DNA analysis have been considered. 2023 WITPress. All rights reserved. -
Secure Image Transmission Scheme based on DNA Sequences
Cryptography and steganography are the most widely utilized and adopted fields of secure data communication. Data transfer can be secured using a combination of these methods. The data is transmitted from sender to receiver using cryptography, the most secure method. At the same time, steganography performs the information hiding in the form of video, image, or text within a cover image. The sensitive data is hidden, so it is not visible to the human eye. The data is stored and transferred more securely by adding DNA technology to the cryptography. It provides additional data security level and is most commonly employed to implement computation. This research developed a new method for combining cryptography with steganography. There are two phases to the proposed method: image encryption and hide phases and image extraction phases. Encryption is done by using the Signcryption algorithm. Four standard images were utilized as test material for the evaluation. Four factors are used to determine the performance of the proposed method as Peak signal-to-noise ratio (PSNR), Mean Square Error, Entropy, and Structural Similarity Index Measure (SSIM) for hiding and extracting the messages. The implementation is done in python. The proposed method achieves better performance when compared to the previously published works. 2022 Seventh Sense Research Group -
A Study on DNA Profiling Techniques and Transnational Exchange of DNA Data from Databank
DNA technology has shown to be a valuable investigative tool in the release of innocent people and the identification of those responsible for serious crimes. In the battle against illegal immigration, cross-border crime, and terrorism, the transnational DNA data interchange from national DNA databanks has become a current trend. The data types that can be shared and the system is managed by a national authority are governed by individual national legislation, which determines the scope of the data exchange. Furthermore, one of the most difficult problems in forensic science is DNA profiling, and it is a hotly debated topic. The number of unknowns in a combination raises the computational difficulty of DNA profiling dramatically. To overcome this issue, various approaches have been designed and implemented. As a result, we examine DNA profiling methodologies and tools in this study, focusing on their computational accuracy and performance. Furthermore, this research examines the available data on DNA exchange and comparison across borders. We hope this review provides more ideas for future research to choose efficient profiling techniques. 2022 Lavoisier. All rights reserved. -
Transformations to and implications for the human rights concept in the internet age
The critical shifts in the utility, implementation, and enforcement of human rights have been achieved as a result of the rise of cutting-edge technological innovation. As a result, there has been a plethora of research on the expansion of beneficiaries of the human rights and the subject matter of such rights. The authors of this chapter contend that in this era of technology, we need to reevaluate our approach to human rights, broaden the scope of those to whom obligations relating to human rights apply by including corporations and other organizations, and be ready to consider the possibility that artificial intelligence will become a topic of discussion in public relations and fundamental rights. In this chapter, a three-pronged approach to thinking about digital rights is presented. This method takes into consideration the subtle structural impact that considering human rights in the digital age has on the job that the courts do. 2024 by IGI Global. All rights reserved. -
Significance of key distribution using quantum cryptography
The main challenge to the cryptosystems is providing secrecy in distributing key. This challenge is explained through key distribution problem. The key distribution in classical cryptosystems is based on classical information or bits. As bits can be replicable, there will be scope for an eavesdropper to make copies of information. The classical key distribution methods rely on computational assumptions which are not potential to offer anticipated results. Consequently, it is solved using laws of quantum mechanics, and the solution is Quantum Key Distribution (QKD). In QKD, the bits are encoded into quantum states or qubits using photon polarization. The qubits cannot be replicated as per the laws of quantum mechanics. An attempt to replication will introduce errors. Thus an eavesdropping will inevitably lead to detectable traces and then the legitimate entities will decide upon discarding a particular qubit. BB84 protocol is the first QKD protocol evolved in 1984. This paper notifies the significance of QKD over key distribution performed using classical methods. It is evidently shown that the time taken to distribute a secret key through BB84 QKD protocol is comparatively less than the classical methods of key distribution. 2018 ICIC International. -
Provably secure quantum key distribution By applying quantum gate
The need for Quantum Key Distribution (QKD) is strengthening due to its inalienable principles of quantum mechanics. QKD commences when sender transforms bits into qubits or quantum states by applying photon polarization and sends to the receiver. The qubits are altered when measured in incorrect polarization and cannot be reproduced according to quantum mechanics principles. BB84 protocol is the primary QKD protocol announced in 1984. This paper introduces a new regime of secure QKD using Hadamard quantum gate named as PVK16 QKD protocol. Applying quantum gate to QKD makes tangle to the eavesdroppers to measure the qubits. For a given length of key, it is shown that the error rate is negligible. Also, the authentication procedure using digital certificates prior to QKD is being performed which confers assurance that the communicating entities are legitimate users. It is used as a defensive mechanism on man in the middle attack. The Japan Society for Analytical Chemistry.