Volume 13 | Issue 1 |

 Abstract

Like other major industries, the manufacturing sector has undergone a corporate transformation in response to the demands of a more competitive and international business environment. One of the most crucial factors to take into account throughout the move is soft skills. Workers that receive this training acquire a competitive advantage in terms of delivering efficient assistance. In the post-liberalization age, the Indian public and private sectors are facing a number of challenges in maintaining and growing their clientele. Among the challenges include identifying a financially viable solution for customer interactions, innovation, human resources, and financial inclusion. This study looks at how employee performance in the public and commercial sectors is affected by soft skill training. The respondents for this study were employees of certain commercial and public sector bank branches in Pune. Employee performance during job performance is positively impacted by soft skill training. A structured questionnaire was used to collect data for the study, and SPSS 25.0 was used for analysis.

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 Keywords

Soft Skills, Training, Business Environment, Employee performance, Manufacturing sector.

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Creative Commons Attribution 4.0 and The Open Definition

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Digital learning is one of the most powerful change that is revolutonarized the Education.It has Enabled today's learning to be more knowledge seekers.Digital tools were once used to promote products ,but today it has gone far beyond in leverage Essential knowledge systems. Especially in institutes and higher learning digital platform leverage knowledge system is creative and exchaning and Intelect.Digital learning is facilitating students to captilizen time,place and place. It allows to use wide range of practices in virtual learning in Higher Eduicational Institutes.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital learning ,knowledge needs,virtual tools.

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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The role of Human Resource (HR) managers in talent acquisition has undergone a significant transformation in response to dynamic workforce trends, technological advancements, and organizational demands. This paper explores the evolving role of HR managers in talent acquisition, focusing on their strategic involvement, innovative practices, and the challenges they face in attracting and retaining top talent. Through a comprehensive analysis of literature, this study highlights the need for adaptive strategies, technological integration, and a candidate-centric approach in modern HR practices. The findings emphasize the importance of HR managers as strategic partners in driving organizational success by building a competitive and skilled workforce.

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Human Resource Management, Talent Acquisition, Strategic HR, Workforce Trends, Recruitment Technology, Candidate Experience

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: Introduction- Centuries over centuries human societies have overcome all the barriers in communicating within or outside the community. Communication as per its modern definition and understanding stands as the backbone for interpersonal, social and professional development. As the human civilisation has walked into new millennium, we have developed different tools and modes of communication. In today's digital Fastrack social media tools platforms have promptly come up as most widely used channels for mass and individual communication. Social media tools have not only made communication more spontaneous but also more convenient in terms of frequency of active participation in communication, be it informal or formal setting. Social media tools also have shortened the communication gap between formal and informal modes. In the modern era free flow communication between the different parties, have seen tremendous feed in terms of technological modes. These ultra-modern tools of communication have not only made communication faster but also time saving as compared to ancient time.

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Creative Commons Attribution 4.0 and The Open Definition

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: Social media, Formal & Informal Communication, Communication Tools

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Creative Commons Attribution 4.0 and The Open Definition

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Recycling is already a significant work for all countries. Among the work needed for recycling, garbage classification is the most fundamental step to enable cost efficient recycling. Segregation of garbage is also a primary concern in many nations across the world. Even though we are in the modern era, many people still do not know how to distinguish between organic and recyclable waste. It is because of this that the world is facing a major crisis of waste disposal. Population growth and the acceleration of urbanization have led to a sharp increase in municipal solid waste production, and researchers have sought to use advanced technology to solve this problem. Machine learning (ML) algorithms are good at modelling complex nonlinear processes and have been gradually adopted to promote solid waste management and help of the sustainable development of the environment in the past few years. In this paper, we attempt to classify the garbage waste object in images and classify it into seven categories that are cardboard, paper, glass, metal, plastic (mainly domestic waste), e-waste and medical waste. The proposed approaches are simulated and evaluated based on image processing and machine learning. The models we used include multi-kernel support vector machines (SVM) and random forest (RF). The model works in 80-20% training and testing pattern that provides the 86.01% of accuracy for the testing.

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garbage classification, image processing, machine learning, support vector machine.

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Creative Commons Attribution 4.0 and The Open Definition

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Polycystic kidney disease (PKD) is an autosomal dominant disorder. It is a multisystem and progressive disease with cysts formation and kidney enlargement along with other organ involvement (e.g., liver, pancreas, spleen). Cystic kidneys are common causes of end-stage renal disease, both in children and in adults. In the adult population, it is the most frequent genetic cause of renal failure, with 6% to 8% of patients on dialysis in the US. By the age of 60 years, 50% of them need renal replacement therapy. Cysts may be detected in childhood or in utero, but clinical manifestations appear in the third or fourth decade of life. Enlarging cysts destroy the structure of nephrons, ultimately resulting in the loss of renal function. Eventually, ADPKD develops into end-stage renal disease. Currently, there is no effective drug therapy that can be safely used clinically. The conventional approach of management includes dialysis and renal transplantation, which are not affordable by Indian population mainly due to economic reasons. Therefore, exploration of a safe and alternative therapy is needed, which proves to be helpful in reducing the requirement of dialysis and in postponing the renal transplantation. It is a case of Polycystic kidney disease (PKD) which is correlated with Mutravaha Stotodushtijanya Vyadhi. A patient 46 year old presented in the OPD with Complaints of loss of weight, loss of Appetite, fatigue and also brought the RFT report which showed high creatinine, and high blood urea. After clinical examination, she was treated with oral medication for 3 months. She had relief in symptoms and also improvement in RFT reports.

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PKD, Cysts, Mutra vaha Srotas, Medo Dushti, Vrukka Roga

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The objective of the present study was to investigate the risk taking behavior basis on locale and educational level (under graduate). There were 200 students as a sample of the present study. The respondents were equally divided into two groups male 100 and female 100. Each group was also divided into different college student. They were purposively selected from different degree College of District Prayagraj. Demographic and personal information sheet of risk taking behavior scale was used for data collection. The obtained data were analyzed through t-test. Results showed that effect of locale was statistically significant in risk-taking behavior and male students have higher score of risk-taking behavior in comparison to their female counterpart. The result also showed that the effect of educational level was statistically significant in risk-taking behavior and undergraduate score student.

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Creative Commons Attribution 4.0 and The Open Definition

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Male, Female, T test, Prayagraj

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Creative Commons Attribution 4.0 and The Open Definition

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"Study to assess the effectiveness of aerobic exercise regarding obesity among adolescent girls in selected schools of Jabalpur city" The research approach adopted for this study was a pre- experimental evaluative research approach in nature. A Pre- experimental one group pre-test and post-test design was used to evaluate the effectiveness of aerobic exercise on obesity among adolescents in selected school of Jabalpur, Madhya Pradesh. The sample consisted of 60 adolescents (11-16 years) students, who are available at the time of study. Non-probability purposive sampling method was used for the selection of samples. The instrument for the data collection was BMI classification to perceived level of BMI and teaching aerobic exercise. The data obtained was analyzed by using descriptive and inferential statistics in terms of frequency, percentage, mean, standard deviation, paired t-test and chi-square test. Socio-demographic variables: majority (61.6%) belonged to 13 - 14 years, (68.33%) was from 10th standard, (85%)lived in home,(66.66%) lived in nuclear family, (65%) family monthly income was from 10,001/-to above, (56.66%) no information about obesity, (68.33%) of "NO" obese in the family, (61.66%) of three times meal schedule, (41.66%) of mixed food consumed,(36.66%) of once a week frequency of spicy food consumption, (76.66%) 8 hours sleep pattern and (73.33%) no exercise by their own. The mean post-test perceived level of BMI is significantly less than the mean pre-test perceived level of BMI that is23.65 inpre-testand21.59 in post-test with paired t-value=2.59 at P =0.05 level of significance. The results of major findings indicated that adolescent (11-16 years) students had decreased the perceived level of BMI. Aerobic exercise was found to be a very effective method of providing information regarding reducing obesity among adolescents. There was significant association between the pre-test perceived level of BMI and demographic variables such as age, education, residence, type of family, total family monthly income, type of food consumed, sources of prior information about obesity, anybody obese in the family, meal schedule, frequency of spicy food consumption, sleep pattern within 24 hours, exercise schedule estimated by chi-square test. The study concluded that the aerobic exercise on perceived BMI level was an effective method for reducing obesity to adolescent age group(11-16 years) to enhance their knowledge regarding reducing obesity through aerobic exercise.

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 Keywords

Obesity, Adolescent age, M.P

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Creative Commons Attribution 4.0 and The Open Definition

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Stress disorders are a rather common occurrence among business sector workers. As people's job and lifestyles change, we can observe an increase in stress among working employees. Even while many business sectors offer a range of mental health programs and attempt to lessen stress-related problems in the workplace, the disorder is still very much alive and well. In this paper, we will apply two machine learning techniques to ascertain the level of stress experienced by corporate sector employees and attempt to identify the problems that contribute to the stress levels. Following the completion of data preprocessing and cleaning, we will use two machine learning approaches (SVM and Random Forest). Our trained model's accuracy was examined and evaluated in detail. Using these two machine learning techniques, it is discovered that the primary factors that lead to stress problems are an employee's sex, family background, and ease of access to health benefits at work. Because of these outcomes, corporate sectors can now reduce stress and create a very welcoming workplace for their personnel. In order to determine if an employee is in a relaxed or stressed state, the author uses social media datasets, such as tweets, where employees can express their opinions. However, manually assessing these opinions may require a significant amount of human labor. Therefore, we are utilizing machine learning techniques, and the results of our experiment indicate that these algorithms have an accuracy of over 80% in detecting stress.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Employee Stress, Machine Learning, Support Vector Machine, Random Forest Algorithm

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Creative Commons Attribution 4.0 and The Open Definition