Volume 12 | Issue 4

 Abstract

Hospitals and healthcare centers are facing problems in distributing medicines to patients. The nurses are primarily employed to administer and distribute medicines to the patients. Nurses are trained to do this job, however, there is always the risk of errors in medication distribution due to the load of patients or long hours of work. This fatigue of nurses brings in the threat of the wrong administration of medicines and puts patient's health at risk. This work presents a simple distribution system for dispensing medicine to the right patients. The designed system caters to hospitals or elderly care centers providing an innovative and functional medicine serving tray with a sliding mechanism. The design used various sensors and wireless communication techniques for dispensing the medicines. The design prototype is a medicine dispensing tray that helps dispense the right medicine dose to the patients non-invasively and safely

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 Keywords

Medicine distribution, Medicine dispensing tray, Sliding mechanism

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Transgender individuals have long been marginalized and misunderstood within society, facing discrimination, violence, and systemic barriers to healthcare, employment, and legal recognition. This article seeks to shed light on the experiences of transgender individuals, exploring the complexities of gender identity, the challenges they encounter, and the importance of fostering inclusivity and support. Drawing upon research, personal narratives, and advocacy efforts, we examine the social, cultural, and political factors shaping transgender experiences, as well as the strides made towards transgender rights and visibility. By promoting understanding, empathy, and ally ship, this article aims to contribute to a more compassionate and equitable society where all individuals, regardless of gender identity, are affirmed, respected, and celebrated for their authentic selves.

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Transgender, Gender Identity, Discrimination, Inclusivity, Advocacy, Rights, Ally ship, Solidarity.

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This Paper is aimed at analyzing the customer expectation and perception of Union Bank of India Service Quality. Banks play a significant role in the economic development and growth. They are the pillars of the economic system of the country. In the paper, we analyzing the service quality of specification bank that is Union Bank to find out the gap between customer expectation and perception thought the SERVQUAL model. The Study includes mainly 5 dimensions i.e., Responsiveness, Assurance, Reliability, Tangibility and Empathy. This research gives useful information to specific bank where they are lacking, where improvement and focus needed.

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 Keywords

SERVQUAL, Service Quality, Customer Satisfaction, Banking Sector and Union Bank of India.

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 Abstract

Elementary education forms the foundation of the entire education system for several reasons. Elementary education focuses on teaching basic skills like reading, writing, and arithmetic. These skills are essential for all further learning across subjects. Elementary education fosters the development of critical thinking and problem-solving skills, which are crucial for success in higher education and beyond. Children gain social skills, teamwork, and effective communication during their elementary school years. e-resources have become an integral part of the education system in general, as well as a valuable resource for teachers and students. Use of e-resources in elementary education plays an important role in shaping the future of the students.

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eResources, Elementary Education

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The government of India's flagship initiative, the Pradhan Mantri Mudra Yojana, was launched in 2015 and aims to finance the unfunded while encouraging an entrepreneurial culture in the nation. People who enjoy being entrepreneurs and have the potential to benefit from the market are eligible for loans without the need for collateral under this scheme. Many women who were unable to take the initiative, because they lacked collateral, have benefited from this scheme by being able to pursue a career in business. With the PMMY initiative, women were able to start businesses without the need for collateral and obtain loans, which improved their potential and entrepreneurship abilities. A business needs to be proficient in a variety of talents in order to succeed, including social skills, business management, and decision-making abilities. This empirical study assesses the impact of Mudra Yojana on women entrepreneurship. A qualitative analysis of data gathered on different parameters using the Likert scale has been done in the study to assess the impact of PMMY on women entrepreneurship. Exploratory Factor Analysis has been used in the study.

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 Keywords

PMMY, Women Entrepreneurs, Business Management Skills, Decision-Making Skills, Social Skills, Likert Scale, Exploratory Factor Analysis

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Small and medium-sized businesses, or MSMEs, are important drivers of economic expansion and job creation, particularly in developing nations like India. Most SME failures in India can be attributed to their lack of accounting knowledge and skills, which leads to the preparation of no-cost and management accounting records. In India, MSMEs still experience a high failure rate. This study intends to investigate the cost and management accounting procedures of sixty MSMEs in the Udaipur district, comprising twenty-four micro, twenty-four small, and twelve medium-sized companies. The study examined the various cost and management accounting practices used by MSMEs. The study discovered that MSMEs' cost and management accounting practices are very limited and it was revealed that some people did not keep cost and management accounting records because they did not believe the business was large enough to warrant explicit record-keeping. Findings show that there is no significant difference between C&M practices based on size and other demographics such as respondent gender, education qualification, industry type, investment, and number of employees.

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Micro, Small and Medium Sized enterprises (MSMEs), Cost and management accounting practices, Lack of accounting knowledge

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This dissertation explores the impact of social media, e-commerce, and m-commerce platforms on the smartphone buying behavior of Generation Z. As digital natives, Generation Z's purchasing decisions are significantly influenced by online platforms. This study aims to identify the key factors on these platforms that affect their smartphone purchasing decisions. A quantitative research approach was adopted, with data collected through an online survey distributed to a stratified random sample of Generation Z individuals. The survey was composed of questions on social media usage, mobile commerce (m-commerce) technology, buying patterns concerning smartphones, and the determinants of purchase decision. The data was analyzed using statistical techniques including frequency distribution tables and a Chi-Square test. The findings provide valuable insights into Generation Z's smartphone buying behavior and the role of digital platforms in shaping these behaviors. The outcomes of this analysis have substantive implications to smartphone companies as it helps them to know how Gen Z is purchasing, thus mapping their marketing strategies. This research contributes to the academic field of Marketing and Consumer Behavior by providing a comprehensive analysis of Generation Z's smartphone buying behavior in the context of digital platforms.

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Generation Z, Behavior, Purchase, Smartphone

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 Abstract

The monitor model in SLA distinguishes between language learning and language acquisition as acquisition is natural and subconscious while learning is conscious knowledge of the rules of the language. Comprehensible input and low level of affective filter ensure language acquisition. Competence acquired through acquisition is the tacit knowledge of the language system whereas competence acquired through learning acts as a monitor or editor of language use. The monitor model also explains the role of cognitive and metacognitive factors that impact second language learning and their implications for language teaching and learning in SLA context.

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SLA, ESL, EFL, learning, acquisition, hypothesis, monitor, affective-filter, cognitive, metacognitive, metalinguistic, tacit, morpheme, predictable, lateralization, input

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Abstract: Education has always been seen as a tool for bringing about societal change. It is impossible to achieve this goal without first enhancing classroom procedures. Teaching is an activity that is planned and carried out with the goal of achieving many different goals, including behavioral changes in the students. Teachers that are effective are aware of how their pupils think and learn. "The key takeaway is that students can acquire social skills and academic knowledge, but they can also learn how to develop into integrated individuals who engage with the outside world, benefit from it, and contribute in return." (Weil, Joyce, and Calhoun, 2009).Without the ability to collaborate with others, engage in democratic processes, and exhibit empathy, a student's education is not complete. Communication researchers need to understand the ideas of the self and self-concept. Theorists began to acknowledge the part that individuals play in communication in the 1970s and 1980s. One mechanism that has been recognized as providing regularity to interpersonal communication is the self-concept. Studies have looked into a variety of topics, including ethnic identities, technology use and self-perception, communication anxiety at the individual level, and the function of speech in the formation of one's self-concept. According to this research and theory, communication and information processing are mediated by factors pertaining to the self and self-concept. The information processing approach places a strong emphasis on how kids manage, track, and plan with information. The thought and memory processes are at the heart of this strategy. The information-processing approach holds that children acquire progressively more complicated knowledge and abilities as a result of their ever-growing capacity to process information (Halford, 2008).Through improving the processing of self-relevant information, improving the retrieval of pertinent information, and influencing information interpretations, self-concept plays a significant role in information processing. "Self" is a more inclusive construct that encompasses ideas of agency and consciousness in addition to identification, relationships, roles, personality, and the physical body. The term "self-concept" describes a person's sense of self or the collection of beliefs they have about themselves, such as their sense of self-worth or self-evaluation. Differing responses in social contexts can be explained by different characteristics and self-concepts.

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Self-Concept, Information Processing Approach, Physics.

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As per the modern principles of white analytical chemistry (WAC), it is imperative to refrain from utilizing organic solvents that are carcinogenic and teratogenic in order to safeguard both the environment and analysts. A innovative idea for evaluating analytical techniques based on their economical effectiveness, greenness, and validation efficiency is white analytical chemistry. As a result, the reverse-phase high-pressure liquid chromatography (RP-HPLC) method for the simultaneous analysis was developed and validated using a WAC. In the field of chemistry, environmental protection as well as individual health and safety are being given more weight these days. As a result, there are more published studies explaining how to follow green guidelines, heed environmental agencies' recommendations, and handle chemicals more cleanly. Even the concept of "analytical quality-by-design" has been put up to highlight the importance of analytical chemistry in this industry's quality control system. But in theory, every sector of the chemical industry has a quality system, with a significant emphasis on chemical analysis and the corresponding quality control system. With time, more green chemistry ideas will find their way into the manufacturing of chemicals, such as minimizing waste output, using less materials and energy, and incorporating analytical measurements into large-scale quality-control operations. Green chemistry concepts will be included into QbD for a specific industry as a result of their integration with analytical chemistry. In this present research review article, a general introduction to green chemistry is explained using analytical quality by design approach.

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White analytical chemistry(WAC), Green chemistry ,Reverse phase liquid chromatography(RP-HPLC), Analytical quality by design(aQBD)

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This study investigates investor perceptions of money-back policies provided by particular life insurance providers. With a growing focus on financial security and various investing opinions, the study provides insight into the preferences, attitudes, and decision-making factors influencing investors for these money-back insurance products. The research explores demographic trends, policy features, returns, and level of satisfaction among investors. This study's factors include premium, quality service, bonus, transparency, trust, and risk. In this study, purposive sampling is used to collect 350 respondents and analysed using percentage analysis, Chi-square analysis, Correlation, Regression analysis, and ANOVA. Results indicated that the money-back policies influence the investor attitude. The percentage of male and female is 57.4% and 42.6%, in the occupation status 59.7% of the respondents are in the category of private employees. Recommendations include money-back policies improved customer service, and transparency in policy and premium structure to enhance customer satisfaction.

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Life Insurance, Money-Back policy, Bonus, Premium, Level of satisfaction.

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Solar energy, such as photovoltaic or solar thermal energy, powers thermoelectric cooling (TEC) solar refrigerators. The Peltier effect is the basis for the thermoelectric module refrigerator's operation. The use of TEC modules in an industry has grown significantly in recent years. They have been using solar refrigeration, which is well known for being an environmentally benign and energy-efficient substitute for the traditional vapor compression technique. The design of TEC solar refrigeration with thermoelectric heating and cooling is presented in this study. The purpose of this work is to develop a different, environmentally friendly refrigeration cycle that can achieve the same temperature as a typical conventional refrigerator. The realm of refrigeration is expanded by the design and production of such a refrigerator. The solar refrigeration system that is being suggested

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Keyword: Thermo-Electric Module, Peltier Effect, Solar Energy, Refrigeration, Oven system.

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There have been tremendous advancements in technology that have led to an increase in the needs of people. This, in turn, has led to more loan approval requests in the banking sector. Some attributes are considered to check loan status while selecting an applicant for loan approval. Banks are facing a serious challenge when it comes to evaluating loan applications and mitigating the risks associated with borrowers potentially defaulting on their loans. This process is particularly laborious for banks, as they must thoroughly verify each individual's loan eligibility. This paper proposes utilizing machine learning models with Ensemble Learning Techniques to determine the viability of granting individual loan requests. By using this approach, it is possible to enhance the accuracy with which suitable candidates are selected from an existing list. Therefore, this process can be used to address the aforementioned concerns surrounding loan approval processes. The model is helpful to both bank staff and applicants as it drastically reduces the time taken to sanction the loan

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 Keywords

Loan Status, Loan Lending, Decision Tree, Random Forest, Machine Learning

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 Abstract

KISHORO ME MANSHIK TNAV KI STHITI KA ADHYAYAN

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KISHORO ME MANSHIK TNAV KI STHITI KA ADHYAYAN

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Skin diseases afflict millions worldwide, requiring expertise and advanced instruments for accurate diagnosis due to limited visual resolution in skin images. Laser and Photonics-based medical technology aids quick and precise diagnosis, yet equipment is scarce and costly. Deep learning techniques facilitate early detection of skin diseases, minimizing reliance on human labor. Feature extraction is pivotal in skin disease classification, with deep learning algorithms automating this process. The adoption of CNN algorithms has notably reduced manual labor in feature extraction and data reconstruction. Achieving a 70% accuracy rate in skin disease classification is feasible through CNN algorithms.

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Skin diseases Convolutional Neural Network (CNN) Medical image analysis, Feature extraction, Image processing, Skin lesion detection, Deep learning, Image classification, Image classification

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Abstract: In the realm of programming languages, Python and Java stand as two giants, each with strengths and weaknesses. This research paper presents a comparative analysis to guide beginners in their choice between Python and Java. The study delves into various aspects including syntax, ease of learning, community support, performance, versatility, and ecosystem. Through an extensive review of existing literature and practical experiments, this paper examines the suitability of Python and Java for beginners, considering factors such as readability, simplicity, and availability of learning resources. Additionally, the performance disparities between the two languages are investigated, shedding light on scenarios where one language might be more advantageous over the other. Furthermore, this paper explores the ecosystems surrounding Python and Java, encompassing libraries, frameworks, and tools available for development. The comparative analysis includes discussions on the applicability of each language in different domains such as web development, data science, and software engineering. Ultimately, this research aims to provide beginners with valuable insights to make an informed decision when choosing between Python and Java as their first programming language. By highlighting the strengths and weaknesses of each language, this paper serves as a comprehensive guide for newcomers embarking on their journey into the world of programming.

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Comparative analysis, Python, Java, beginners, programming languages, syntax, learning curve, performance, ecosystem, versatility, decision-making.

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With more than 1.3 billion people living in India, the country's health care system still has a ways to go before it can adequately serve this sizable population with dependable and reasonably priced medical treatment. Telemedicine is one of the growing technologies that might facilitate access to medical services for the rural population. Since medical images take up a lot of storage space and transmission time is a bottleneck for real-time telemedicine requirements, developing algorithms and implementing them on VLSIs is crucial for processing images and videos quickly. In this work, fast and robust algorithms and their VLSI architectures have been designed for medical image compression supporting both 2D and 3D medical images.

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DWT, IDWT, SPHIT, MATLAB, FPGA, Telemedicine, FFT Analysis.

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: Natural dye, Avocado Dye, Coconut Husk Dye, Bamboo fabric.

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Heartbeat level prediction is crucial for assessing cardiovascular health and diagnosing related conditions. In this study, we conduct a comparative analysis of machine learning algorithms including Support Vector Machine (SVM), Random Forest, Linear Regression, and k-Nearest Neighbors (KNN) for predicting heartbeat levels. Each algorithm is trained and evaluated using a comprehensive dataset comprising features such as chest pain type, resting blood pressure, serum cholesterol level, fasting blood sugar, resting electrocardiographic results, and maximum heart rate achieved. Standard performance metrics including accuracy, precision, recall, F1 score, and confusion matrix are employed to assess the predictive capabilities of the models. Through this comparative analysis, we aim to identify the most effective algorithm for accurate heartbeat level prediction, considering the trade-offs between computational complexity, interpretability, and predictive performance. The findings of this study contribute to the advancement of machine learning applications in cardiovascular health monitoring and diagnosis. This meticulous approach culminates in the section of the optimal machine learning algorithm for heart beat level prediction, offering insights into cardiovascular health with precision and efficacy.The finding aim to identify the most effective algorithm for heart rate prediction, providing insights for practical health care applications.

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Heartbeat level prediction, Machine learning algorithms, Support Vector Machine (SVM), Random Forest, Linear Regression, k-Nearest Neighbors (KNN), Comparative analysis, Performance metrics, Accuracy, Precision, Recall, F1 score, Confusion matrix.

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Anemia refers to a decrease in the total number of circulating red cells with decrease in hemoglobin when compared with normal for that age group and gender. Iron deficiency (ID) is one of the most common micronutrient deficiencies worldwide and it is designated as a reduction of total body iron. Object To detect the prevalence of anemia in young adult females. How to control the iron deficiency in adult female. Method A prospective study was undertaken among age varies from 17 to 28 years subject in Anand Gujarat. CBC and peripheral smear were noted. Result Subject were classified based on severity of iron deficiency anemia. We found that adult females associated with iron deficiency anemia in which two categories mild (32%) and moderate (27%). Conclusion As per the study females were more prone to iron deficiency anemia

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 Keywords

anemia, iron deficiency, severity, Iron

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