Volume 12 | Issue 5 |

 Abstract

The banking system claims that everyone's primary source of income comes from loans. A bank's primary source of revenue is, therefore, loans. One of the greatest threats to a bank's viability and profitability in today's cutthroat market is the difficulty of accurately assessing the risk associated with a loan application. Many individuals visit different banks every day to seek for loans. Every applicant does not get approval. Most banks utilize their risk assessment and credit scoring systems to determine whether or not to approve a customer's loan application. Getting a loan approved is a tedious process for bank employees. A more efficient, accurate, and quick loan approval procedure is possible with the use of modern technologies like machine learning models. Predicting whether or not a borrower will get a loan is an important yet long-standing problem for the financial services sector. Historically, banks and other lenders relied on manual processes and subjective criteria to evaluate loan applications, which often led to inconsistent decisions and increased risk of loan defaults. With the rise of ML algorithm, there is now an opportunity to create more accurate and reliable predictive models that can help financial institutions make better lending decisions. This research uses ML techniques to identify trends in a shared dataset of loan-eligible individuals. The dataset is prepared by performing exploratory data analysis and data balancing. The explored algorithms include Cat Boost, Gradient boosting and XGBoost. Preprocessing data, selecting features, balancing data, training and testing, classification, and comparing performance using accuracy and precision as classification metrics are the main goals of the project. Recall and f1-score. Following Gradient Boost Classifier (86.39%) and XGBoost (84.61%), the results reveal that Cat Boost Classifier had the greatest accuracy at 88.16%. The findings show that ML algorithms have the ability to make loan approvals better and decrease the likelihood of defaults.

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 Keywords

Machine Learning

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Nurse's burnout is a universal phenomenon characterized by a reduction in nurse's energy that indicate in emotional exhaustion, demotivation, and feeling of frustration and may lead to reduction in work competence. This study was conducted to assess the level of burnout among nurses and coping strategies they use to prevent burnout on work place in the government and private hospital of district Mohali (Punjab). A quantitative approach with comparative research design was adopted for the study.60 nurses (30 from government and 30 from private hospital) were selected through non- probability convenient sampling technique. Study shows that majority of nurses (86.7% in government and 90 % in private hospital) were having moderate prevalence of Burnout Syndrome and majority of nurses (86.7% in government and 96.7% in private hospital)were using the coping strategies to prevent the burnout syndrome on their work place as well as at home. There was no significant association found between the variables of the study using chi square (p= <0.05).

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 Keywords

Nurses, Burnout, Prevalence, Coping Strategies

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 Abstract

The mattress industry has undergone significant transformations in recent years, influenced by various factors such as technological advancements, consumer preferences, economic conditions, and global market dynamics. This study aims to provide a comprehensive analysis of the trends observed in the mattress industry over the past five years, shedding light on key developments and their implications for industry players. Through a combination of qualitative and quantitative research methods, this study examines several pivotal trends shaping the mattress industry. Firstly, it explores the growing demand for innovative mattress technologies, including memory foam, hybrid constructions, and adjustable bases, driven by consumers' increasing emphasis on comfort, support, and sleep quality. Additionally, the rise of eco-friendly materials and sustainable manufacturing practices reflects a broader societal shift towards environmental consciousness, influencing both product design and marketing strategies. Moreover, the expansion of online mattress retailers and direct-to-consumer models has disrupted traditional distribution channels, offering consumers greater convenience, competitive pricing, and extensive product options. This shift towards e-commerce is accompanied by a focus on personalized shopping experiences, augmented reality tools, and hassle-free return policies, catering to the evolving preferences of digitally-savvy consumers. Furthermore, the study delves into the impact of demographic trends, such as an aging population and the rise of urbanization, on mattress sales and product innovation. Changes in lifestyle patterns, including an increased emphasis on wellness and self-care, have also fueled demand for premium mattresses and sleep accessories, creating opportunities for market segmentation and niche players. Lastly, the study examines the effects of macroeconomic factors, such as fluctuations in raw material prices and currency exchange rates, on the profitability and competitiveness of mattress manufacturers and retailers. It also discusses the implications of regulatory developments, safety standards, and industry consolidation on market dynamics and competitive landscape.

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 Keywords

Mattress industry, Trends Analysis, Market dynamics, Technological advancements, Consumer preferences, Economic conditions, Global market, Innovation Sustainable practices, E-commerce, Direct-to-consumer, Demographic trends, Lifestyle patterns, Premium mattresses.

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The shift towards health-conscious consumption patterns has become a prominent trend in recent years, profoundly impacting food preferences globally. This study delves into the dynamics of this transformation, examining the drivers, implications, and manifestations of changing food preferences among consumers. Through a comprehensive review of existing literature and empirical research, this paper identifies key factors influencing health-conscious consumption behaviors, including nutritional awareness, lifestyle changes, socio-cultural influences, and marketing strategies. Moreover, it explores the consequences of these shifts on various stakeholders, such as food industries, public health policies, and environmental sustainability. By synthesizing insights from diverse disciplines, this study contributes to a nuanced understanding of the complex interplay between health considerations and food choices in contemporary society. The findings underscore the need for targeted interventions and strategic initiatives to promote healthier food options and foster sustainable consumption practices.

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From a social, ethical, political, and technical perspective, this research delves at the far-reaching consequences of deepfake technology powered by artificial intelligence (AD). Concerns over the integrity of information ecosystems & the loss of faith in visual and aural evidence have been raised by the potential for deepfakes, synthetic media made using powerful machine learning algorithms, to fool audiences and influence public opinion. This study seeks to address the challenges posed by deepfakes by conducting a thorough investigation into their creation and dissemination, assessing their societal and ethical implications, and identifying potential mitigation strategies along with regulatory frameworks. The study's overarching goal is to help policymakers, technologists, or the public better comprehend deepfake technology so that they can make educated decisions about how to respond to the potential threats it poses and how to limit the damage it can do.

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Keywords: Deepfake technology, artificial intelligence, synthetic media, misinformation, trust, ethics, regulation.

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The dissertation investigates the intricate relationship between childhood trauma and adult mental health outcomes, aiming to shed light on the enduring impact of early adverse experiences on psychological well-being. Utilizing a quantitative research methodology, the study employs validated measures to assess childhood trauma experiences and adult mental health problems, including depression, anxiety, PTSD, substance use disorders, borderline personality disorder, and disassociate disorders. By analyzing data collected through questionnaires, the research explores the prevalence of mental health problems among individuals with a history of childhood trauma, identifying key risk factors and pathways linking early adversity to adult psychiatric disorders. The findings underscore the importance of trauma-informed interventions and early intervention strategies to address the complex needs of individuals affected by childhood trauma and promote resilience and recovery.

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 Keywords

childhood trauma, adult mental health, depression, anxiety, PTSD, substance abuse, borderline personality disorder, disassociate disorders, trauma-informed care.

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This research paper investigates the synergies between Human Resources (HR) and Marketing functions in utilizing social media platforms for attracting and hiring talent. In the contemporary digital landscape, social media has emerged as a pivotal tool for organizations to showcase their employer brand, engage with potential candidates, and streamline the recruitment process. By conducting a comparative analysis of HR and Marketing collaborations on platforms such as LinkedIn, Twitter, Facebook, and Instagram, this study aims to uncover effective strategies for talent acquisition and retention. The research explores how joint efforts between HR and Marketing departments can leverage social media's reach, engagement capabilities, and brand positioning to attract top talent and create a compelling employer value proposition.

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 Keywords

HR and Marketing Collaboration, Talent Acquisition, Social Media Recruiting, Employer Branding, Digital Recruitment Strategies, Integrated Marketing Communications, Social Media Marketing for HR, Recruitment Marketing, Cross-functional Collaboration, Employee Value Proposition (EVP), Social Recruiting, Brand Advocacy, Candidate Engagement, Online Talent Attraction, HR Marketing Integration, Social Media Campaigns for Hiring, Employer Brand Strategy, Talent Pipeline Development, Recruitment Analy

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 Abstract

People are sociable animals. To succeed in life, we require the company of others, and the quality of our relationships has a profound effect on our happiness and mental health. Maintaining social connections with others can reduce stress, anxiety, and depression; increase self-esteem; bring comfort and joy; avoid loneliness; and even lengthen one's life. Conversely, having few close social ties can be extremely harmful to your mental and emotional well-being. According to data from 2021, people spend an average of 142 minutes a day on social media platforms worldwide. That is more than two hours a day spent absorbing information that may influence our opinions, mental health, and general mood in a favourable or unfavourable way. Therefore, it is critical that we figure out how to make sure that there is a tonne of optimism in our news feeds. In essence, the amount of time we spend on social media greatly influences how we are affected by it. Being social beings, humans may spend more time interacting with one another in the modern world over a brief Facebook post or in response to a "story." Even while digital communication offers advantages, it is crucial that we develop relationships through face-to-face conversation. Overusing our phones to experience life can have a seriously negative impact on our mental health. In light of this, it's imperative that we reevaluate our online behaviours in order to move towards a more positive mindset and way of life. Social pressures and developmental obstacles can be present throughout childhood and adolescence. Social media can exacerbate mental health conditions such as anxiety, sadness, bullying, and low self-esteem in certain children. It may be tempting to just take away your child's phone or other gadget if you're concerned about how they're using social media. However, that can lead to more issues by cutting off your youngster from their peers and the advantages of social media. Alternatively, there exist alternative methods to assist your child in utilising Facebook, Instagram, and additional sites responsibly.

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 Keywords

mental health and happiness, prevent loneliness, global average time, digital communication, developmental challenges.

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During COVID-19, quick advancements were made in the field of vaccines, which brought about the growth of several controversies about the safety of vaccines. Under the shadow of those controversies, we hypothesize that those who took vaccines could be higher risk takers and more pro-social as they took the vaccine decision to protect themselves and others. This study helps us determine "The Risk-taking Behaviour, Prosocial Behaviour, and Vaccination Hesitancy among Adults Who Took the Second and Booster Dose of the COVID-19 Vaccine". Purposive sampling was used to collect responses from 313 persons aged 18 to 40 on the vaccination hesitancy scale, prosocialness scale, and risk-taking scale, respectively. We conducted descriptive statistics, Spearman's correlation, the Mann-Whitney U test, and regression analysis. Results showed that there was no significant relationship between vaccine hesitancy and various doses of vaccines, and also no relationship between vaccine hesitancy and prosociality among adults who took multiple doses of vaccines; Interestingly, there was a negative relationship between vaccine hesitancy and risk-taking behaviour among adults who took various doses of vaccines. There was a negative relationship between vaccine hesitancy and the first dose; there is no significant relationship between vaccine hesitancy and subsequent vaccine doses.

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 Keywords

COVID-19, Vaccine Hesitancy, Prosocial Behaviour, Risk Taking, Second Dose and Booster Dose

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This research investigates the impact of AI technologies on news production processes, focusing on efficiency and accuracy enhancements. It examines the speed of news generation, reduction of human errors, and real-world applications of AI in content creation. Ethical implications of AI integration in journalism are critically explored, including biases, transparency issues, and accountability concerns. The study proposes guidelines for responsible AI use in editorial decision-making. Additionally, it analyzes how AI-generated content affects audience engagement and consumption patterns, identifying emerging trends and providing insights for news organizations. Methodologically, it employs a mix of quantitative (survey, content analysis) and qualitative (literature review, comparative analysis) approaches to contribute fresh insights to the transformative role of AI in automated journalism. The research not only explores the current landscape but also projects future user experiences with AI-generated news, offering valuable recommendations for navigating this evolving intersection of artificial intelligence and journalism.

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 Keywords

Artificial Intelligence, Automated Journalism, News Generation, Indian Media, Global Media Trends

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