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The paper titled „Gender stereotyping leads to misrecognition of one‟s own identity‟ is based on a Youtubeseries named „Man‟s World‟ by Y-Films Original, presented by The Global Goals For Sustainable Development (United Nations) having a tie-up with India‟s most reputed production house, Yash Raj Films. The series „Man‟s World‟ "is a what if story. It is a story about walking in the shoes of women, in that world. The series supports Goal Five of the UN‟s Global Goals for Sustainable Development which is about achieving Gender Equality and empowering all girls and women, everywhere." The aim of this paper is not about achieving the goal of gender equality but to show that gender stereotyping often leads to misrecognition of one‟s own identity, that is, it leads to a sense of identity which is not one‟s own but assigned by the society. One can argue that in thevery first place, identity is never one‟s own, instead we get a sense of our identity, our “self” by looking at the other. True, but there is also the idea of self-realization of our identity, when we recognize our true „self‟ and not the one which is assigned to us by the society, not how society looks at us as just male or female particularly, but how we look at ourselves as an individual.

Autism Spectrum Disorder may be a condition associated with brain development that impacts how a person perceives and socializes with others,causing issues in social interaction and communication.The disorder additionally includes restricted and repetitive patterns of behavior.The term “spectrum” in autism spectrum disorder refers to the wide selection of symptoms and inflexibility.Autism spectrum disorder includes conditions that were antecedently considered separate - Autism,Asperger’s syndrome,childhood disintegrative disorder and an unspecified form of pervasive developmental disorder.Some people still use the term “Asperger’s syndrome” which is mainly thought to be at the mild finish of autism spectrum disorder.Autism Spectrum disorder begin in early childhood and eventually lead to problems with social functioning-for example ,in social interaction,school,and work.Children usually show symptoms of autism within first year of life.A small number of children appear to be developing normally in the first year and then go through a regression phase when they develop autism symptoms between 18 and 24 months of age.Although there is no cure for autism spectrum disorder, early intensive treatment can significantly improve the lives of many children. The aim of this paper is to study different machine learning algorithm to detect and predict Autism Spectrum Disorder.

Around the world 8 to 15 percent of couples in their reproductive age have infertility problem. According to WHO estimates, there are 60-80 million infertile couples globally, with some parts of population having the greatest rate. Significant social, emotional and psychological stress has been brought on by infertility among couples, families, the individual in question, and the larger society. Few researches have used Artificial Intelligence (AI) techniques in the field of reproduction, despite the fact that the use of AI techniques in the medical profession is growing every year. In order to assist couples with unexplained infertility, this review study develops and assesses multiple artificial intelligence models that can differentiate infertile/fertile couples based on a variety of characteristics.

The main purpose of the study is to look into the perception of students about the online classes which they are attending during the COVID-19 pandemic. The present paper aims to study the college students' perception [both Undergraduate (UG) and Postgraduate (PG) level] about their online classes conducted during the pandemic period. The data was collected using structured questionnaire (online survey) from the college students in Puducherry. The students 'perception has been studied using various parameters viz., online class benefits, drawbacks of online class, changes needed in the online class and the effectiveness of online teaching. The analysis has been done using Mann-Whitney U Test, Correlation and Simple Linear Regression model. The study reveals that there exists a significant difference between UG and PG students with regard to the changes expected to be implemented in the online classes whereas the students' perception do not vary significantly with regard to the 'effectiveness' and the 'benefits' they obtained from online classes. Using correlation, the study found a significant positive relationship between online teaching and the benefits obtained from it. Finally, the study proved that the benefit obtained by the students in online classes is fully dependent on the effective method of teaching.

Agriculture in India employs more than 50% of the population. Constant support for agriculture from the public and private sources has not been able to reduce the plight of the farmers in India. They still lack access store sources and inputs needed for farming. In this scenario, Farmer Producer Organization (FPO) has been introduced to meet the needs of its members who arealso the shareholders. Farmers Organization are essential institutions for the empowerment,Poverty alleviation and advancement of farmers and also the rural poor. Politically, Farmers Organization strengthens the political power of farmers, by increasing the likelihood that theirnecessity and opinions are heard by policy makers and the public. Economically, Farmers Organizations can help to farmers gain skills, access inputs, form enterprises, process andmarket their products more effectively to generate higher incomes. The present study aims toidentify the services provided by the FPO.Government has initiated many FPO Initiative through different agencies such as State Governments, SFAC,NABARD, NCDEX, and NGOs.

Child growth is internationally recognized as an important indicator of nutritional status and health in populations. Nutritional status of children is a proxy indicator for assessing the entire population health status and one of the major predictors of child survival. Anthropometry is the scientific study of body measurements and in expensive and non-invasive methods for assessing children’s developing patterns. The literature found relationship between the age, gender, and anthropometric measures of young children. The present study was conducted to understand the relationship among the age, gender, and anthropometric indices across age and gender of pre-school children. The study sample was pre-school children attending Anganwadi in Tirupati town of Chittor district of Andhra Pradesh who were selected randomly. The results revealed that there was association between age, gender, and anthropometric data of pre-school children.

Introduction: Placenta previa is a key risk factor for obstetric hemorrhage particularly occurs in women with a previous uterine scar. It can be defined as an embedding of the placenta in the lower uterine segment, overlying or approaching the internal cervical os. One-third of all cases of APH caused due to placenta previa. Aim of the study: To assess the maternal complications and perinatal outcomes of patients with placenta previa by analyzing its obstetrical factors. Methods: This study is a cross-sectional observational study conducted at the Department of Obstetrics and Gynae, in Enam Medical College and Hospital, Savar, Bangladesh. The study was conducted for the duration of 1 year between January 21 to December 21. The sample size for this study was 109. Result: The most respondents 81(74.3%) were from the age group 25-29 years, 17(16%) were booked and 92(84%) were unbooked. 27(25%) were primi and 82(75%) were multi-para. Pain abdomen was present in only 2(1.8%) cases and absent in most 107(98.2%) cases. LSCS was done in 79(72%) patients and vaginal delivery was done in 30(28%) cases. Type 2b in most of the cases 50(45.9%). Blood transfusion was needed in 20(18.3%) and post hemorrhage was seen in 12(11%). APGAR at birth was 8-10 in 69(63.35) cases, 5-7 in 27(24.8%) cases and

A sensor node comprises of enormous nodes which can a variety of tasks such as recognize, indulgence, communication, and influence resource. Data transmission is the main aspect from starting to target. Once it is transferred between the node and within-cluster, the congestion will arise either node or in a resource allotment. So that it will affect the unremitting delay of reaching data, flow, the defeat of information to the destination, and the unfavorable use of a significant quantity of energy in the node. In this work, the impact of machine learning algorithms is studied using the GSTEB hierarchical protocol. By altering the type of input parameters, K-Means clustering on node energy usage can be performed. If congestion occurs, our proposal outlines a strategy for dealing with it and improving the CHPSCCC (Clustered Highly Prioritized Application-Specific Congestion Control Clustering Protocol) approach for congestion management. Simulation results show that in the proposed system there is significant growth of rises in the lifetime, energy, throughput, and packet loss.

This paper presents the air breathing fuel cell (ABFC) power system and its investigation for industrial applications. The ABFC actual behaviour is realized through the development of an empirical model by considering activation polarisation, ohmic polarisation and mass transport effects. The developed stack model feeds the power conditioning unit of the proposed power system. This paper will throw light on the usage of GaN wide bandgap (WBG) material based power semiconductor devices (PSDs) that are used to build 5-level cascaded H- bridge multilevel inverter and a boost converter. This in turn enhances the energy efficiency of the entire FC power system. These WBG PSDs present the phenomenal properties such as high saturated drift velocity, wide bandgap and high critical breakdown field. This multilevel inverter is implemented for facilitating a quality AC output besides offering the voltage control. The investigation is carried out with the development of power conditioning unit hardware setup besides the fabricated FC module for the validation the developed ABFC model.

The demand for increasing the shelf life of fresh food as well as the need for protecting the food against foodborne infections warrant the demand for increasing the shelf life of fresh food. The incorporation of nanoparticles into the packaging material can enhance the preservation of perishable foods. Silver nanoparticles (AgNPs), in particular, have antibacterial, anti-mold, anti-yeast, and anti-viral activities can be embedded into the biodegradable packaging materials for this purpose. This study focuses on antimicrobial packaging materials for food by mixing the extracts of different plants with silver nitrate and depositing this mixture as a layer on the blotting papers, which are thick sheets of paper made of cellulose. Because the blotting papers are highly absorbent and porous, silver nitrate solution along with the plant extracts can be easily applied and allowed for in situ synthesis of AgNPs. Subsequently, these papers were analyzed and characterized using scanning electron microscopy, transmission electron microscopy, atomic absorption spectroscopy, and energy dispersive X-ray analysis. The coated paper exhibited good antibacterial activity against Escherichia coli and Staphylococcus aureus. Furthermore, the coated paper when used as a packaging material for tomatoes and coriander leaf, the shelf life was extended to about 30 days and 15 days respectively. The prepared cost-effective silver packing material can be used in food packaging for various perishable foods.

Sentiment analysis through opinion mining is determined through significant and growing interest for many industries including hotel, tourism, educations and so on. Sentiment analysis includes design of the system to search the user opinions in blog posts, comments, reviews or tweets regarding the product, policy or area. Many researchers carried out their research on opinion mining to identify the polarity of the statements. But the main problem during opinion mining is that the words chosen do not solve attribute relevancy and could not classify the positive and negative usage of uncertain terms. In order to address these problems, normal discriminant piecewise regressive (NDPR) sentiment classification technique is introduced. NDPR technique perform three processes, namely, pre-processing, feature extraction and classification to improve the accuracy level through forming classes (i.e., positive, neutral and negative) based on the extracted words from user review comments. Initially, NDPR technique performs the data pre-processing task for stemming and removing the stop words from review statements to reduce the file size that in turn improves the efficiency. After that, normal discriminant feature extraction process is carried out in NDPR technique to extract the opinion word from the review statements sent by reviewers. The related opinion words are systematized for their semantic equivalence of sentiment based on extracted word. This helps to reduce the time consumption to extract the opinions from reviewers. Finally, piecewise regressive sentiment classification (PRSC) process is carried out in NDPR technique to analyse the semantic opinion words for evaluating the sentiment class label. The sentiment class labels are categorized into positive, neutral and negative sentiments with the user review comments. This in turn helps to reduce the time consumption to extract the opinions from reviewers and to improve the review detection accuracy. The performance evaluation of NDPR technique is carried out with standard benchmark datasets of consumer product and services reviews extracted. The parameters used in evaluation are number of customer review words, accuracy, time complexity (TC) and false positive rate. Experimental analysis shows that NDPR technique reduces the time to extract the opinions from reviewers and false positive rate.