Volume 12 | Issue 5

 Abstract

Introduction: Employee engagement plays a vital role in the success of any organization. Within this context, human resources managers are crucial in designing strategies to promote employee engagement. Methodology: This study employs a qualitative phenomenological research design to explore the lived experiences of human resources managers in promoting employee engagement within their organizations. The study involves conducting in-depth interviews with ten human resources managers across various industries. The central question guiding this research is: "What strategies do Human Resource Managers use to promote a culture of engagement within their organizations?" Data was gathered through twenty-five semi-structured interviews and analyzed using an inductive approach to develop themes. Results: This study identified three emerging themes: Performance Management, Talent Management, and Team Management. The findings reveal that Performance Management involves using surveillance methods to provide feedback during and after appraisals. Talent Management includes implementing motivational factors to boost team morale, recognizing and appreciating employees, and providing professional education for employee growth. Team Management involves fostering teamwork, where individuals share ideas and skills to achieve shared objectives, thus promoting communication and cooperation within the workplace. Discussion: The three themes are crucial for human resource managers in promoting employee engagement because they collectively contribute to fostering a positive work environment, enhancing employee satisfaction, and ultimately improving organizational performance. Recommendations: This research paper contributes to the existing literature on employee engagement and therefore recommends that future researchers conduct related studies of employee engagement exploring other variables such as productivity, employee well-being, and satisfaction. The human resource managers can also use this paper to effectively promote employee engagement and foster a culture of open communication and collaboration to manage talent and performance within their team.

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Collaborating, Communication, Employee Engagement, Monitoring, Feedback, Recognition, Organization, Performance

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"Evaluating Marketed Metformin Hydrochloride (500mg) Tablets: A Comparative In-Vitro Approach", aims to assess the quality and performance of various commercially available Metformin hydrochloride tablets through in-vitro testing methods. By comparing different brands or formulations, the project seeks to identify potential differences in drug release profiles, dissolution rates, and other critical parameters that may impact therapeutic effectiveness and patient outcomes. This research contributes valuable insights to pharmaceutical quality control and assists healthcare professionals in making informed decisions regarding medication selection and management for patients with diabetes or other conditions treated with Metformin.

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Metformin hydrochloride, In-vitro Study

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Artificial Intelligence (AI) is becoming more common in our lives, including in College/Universities. A study asked 38 people about how AI affects learning and thinking. It found that AI is most useful for tasks like studying for exams, problem-solving, and doing assignments. People see both good and bad sides to AI. Some like how it personalizes learning and helps to solve problems, but others worry it might make people lazy or less creative. Still, many think AI can help students learn independently by giving quick help, organizing thoughts, and improving problem-solving skills. People see AI as a tool to help, it cannot replace a human intelligence. It might even help with language skills and encourage creative thinking. Some worries include losing jobs, less creativity, and not having real-life experiences. But most don't think AI makes us worse at decision-making or less active. Overall, people believe AI helps us think better, find new solutions, and teach better. People have different opinions about trusting AI answers compared to answers from friends or teachers. This study shows that AI in education has both good and bad sides, and we need to think carefully about how we use it.

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THE IMPACT OF AI ON COLLEGE STUDENT'S INTELLECTUAL DEVELOPMENT

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While the retail grocery industry in India is one of the fastest-growing, retail businesses in the country compete with one another for the limited consumer base. The E grocery retailers ought to be able to draw in customers and use marketing to interact with them. The retailers of E-grocery should be able to draw in customers and engage with them through marketing since it focuses on finding multiple organizational variables that impact the notion of lean marketing readiness: Lean awareness, Lean principles, Knowledge on lead deadly wastes .Lean tools and techniques, Perception on lean, implementation benefits, Perception on lean implementation. The aim of the study was to determine the factors contributing to the lean awareness and to understand perceptions of retailers on lean thinking which can help to progress the further research. The study helps retailers of e grocery marts to understand and develop ways to adopt the Lean marketing strategies in turn can produce value for the customers through the optimization of the resources and create a steady workflow based on real customers' demands

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retail businesses, Lean awareness, Perception on lean, lean implementation, variables, factors

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A potentially effective method of bypassing the barrier between the blood and the brain and delivering medicinal substances straight to the brain is the nose-to-brain medication delivery system. The state-of-the-art in nose-to-brain medication delivery systems is thoroughly reviewed in this paper, with an emphasis on recent developments, difficulties, and potential future directions. The nasal route has several benefits for delivering drugs to the brain, such as a rich blood supply, a wide surface area, and the ability to bypass first-pass metabolism. To improve medication transport through the nasal passages to the brain, a number of approaches have been investigated, such as the use of mucoadhesive formulations, nasal irrigation methods, and nanocarriers. The efficiency & targeting abilities of nose to brain delivery systems are significantly enhanced by nanotechnology. medications may be delivered continuously and with regulated release thanks to nanocarriers including liposomes, nanoparticles, and nano emulsions, which also increase the medications' bioavailability and therapeutic effectiveness. By limiting systemic adverse effects, surface modification approaches enable tailored delivery to certain brain areas. By maintaining longer contact with the nasal mucosa and facilitating absorption into the systemic circulation or direct transfer to the brain, mucoadhesive formulations improve medication retention in the nasal cavity. Mucoadhesive systems based on polymers, such hydrogels and microspheres, have shown potential in enhancing medication absorption and retention. Nasal irrigation methods provide a non-invasive and patient-friendly way to administer medication. These methods include nasal sprays and nebulizers. By administering medications in an aerosolized form, these devices enable quick absorption through the nasal epithelium and direct delivery of the medication to the brain through the olfactory and trigeminal pathways. Even with great advancements, there are still a number of issues with nose-to-brain medication administration that need to be resolved, such as the removal of nasal mucociliary cells, the breakdown of enzymes, and architectural obstructions in the nasal canal. In addition, a thorough assessment of the long-term impacts on the nasal mucosa and the safety profile of nanocarriers is required. Neap-to-brain medication delivery devices are particularly promising for treating Parkinson's disease, Alzheimer's disease, and brain tumors, among other neurological conditions. To fully realize the promise of this novel technique in clinical practice, more study is needed to overcome current obstacles and optimize delivery strategies.

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Nose-to-brain drug delivery, Blood-brain barrier, Nanotechnology, Nanocarriers, Nasal irrigation techniques, Controlled release, Sustained delivery, Surface modification, olfactory and trigeminal nerve

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Within cloud environments, Searchable Encryption (SE) serves as a vital tool for protecting data while maintaining its accessibility. The Cipher text-Policy Attribute-Based Keyword Search (CP-ABKS) relies on Ciphertext-Policy Attribute-Based Encryption (CP-ABE) to allow for keyword retrieval and precise access control. However, existing CP-ABKS setups face challenges due to their dependence on a single attribute authority for user certificate validation and secret key distribution. This reliance leads to performance bottlenecks in distributed cloud setups. To address this issue, our research introduces a secure Multi-authority CP-ABKS (MABKS) system. This system aims to overcome these limitations and reduce computational and storage overhead on resource-constrained devices within cloud infrastructures. Additionally, enhancements have been made to the MABKS system to enable the detection of fraudulent attribute authorities and facilitate attribute updates

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Cipher text-Policy Attribute-Based Encryption, MABKS, , Multi-authority CP-ABKS

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In the realm of machine learning, the Extreme Learning Machine (ELM) excels in classification and regression but falters with imbalanced data. To address this, we introduce OWA-ELM, an enhanced ELM algorithm with output weight adjustment. OWA-ELM strategically adjusts connection weights to favor minority classes, improving their classification accuracy without compromising majority class performance. Furthermore, we integrate OWA-ELM with the deep learning SMOTE algorithm to automatically synthesize similar data, addressing data imbalance more effectively. Our extended OWA-ELM with SMOTE outperforms other algorithms, achieving higher FSCOREs and demonstrating superior classification performance on imbalanced datasets.

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Imbalanced Data, OWA-ELM

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Ayurveda is the Oldest Medical System which Utilizes Different Surgical and Para-Surgical Interventions for Treating Disorders; Wide Description is Available in Ayurvedic Classics Regarding Various Surgical Instruments (Yantra) Used in Different Branches of Ayurveda for Carrying out Clinical Examination; Medical and Operative Procedures. Surgical Instruments Such as Forceps, Dilators, Speculums, Needles, Lancets etc. are Similar to the 101 Yantras Mentioned in Ayurveda as Swastika Yantra, Samdansha Yantra, Nadi Yantra, Shalaka Yantra, etc. to Perform Various Procedures, Use of Blunt Instruments are Described in Detail. Most of the Modern Surgical Instruments are only Slight Modifications of the Instruments Used by Ancient Hindu Surgeons. In this Article we have Discussed about those Yantras (Blunt Instruments) Which are Mentioned In Ayurveda and their Counterparts in Modern Surgical Practice.

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Ayurveda, Yantra, Modern Surgical Instruments

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This project aims to enhance water quality monitoring by leveraging machine learning for improved accuracy and efficiency. It utilizes data collection, visualization, and pollution detection. A key feature is a web-based application that presents data interactively and generates comprehensive reports, aiding in timely decision-making. This system underscores the potential of technology in addressing environmental challenges and advocates for its wider application in resource management. The project serves as a testament to the power of technological innovation in preserving the environment.

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Water Quality, Quality Monitoring, Water, Machine Learning, Water Pollution

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The importance of security in the authentication process as well as the increase in threat level posed by such malware has attracted many researchers to the field. Many attacks are successful in accessing social network accounts since the current password-based authentication paradigms are not efficient and robust enough as well as vulnerable to automated attacks. The traditional two-factor authentication mechanisms are not applicable to online social networks because physical token or biometric data cannot be easily used to log into users' profiles. The selection process ensures that each user's password is unique and virtually impossible to guess or replicate by an attacker. The system will be designed with user-friendliness in mind, offering an intuitive and engaging interface for symbol selection. The goal is to create a secure and memorable authentication system that mitigates the risk of unauthorized access.

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Keywords: Graphical Password, Shoulder Surfing, Authentication Scheme, Passwords, Graphical Authentication, Password Attacks.

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Effective soil management is essential for maximizing agricultural productivity and ensuring sustainable food production. This project presents an integrated Soil Fertility Measurement and Automatic Spraying System designed to streamline soil management practices and optimize soil conditions in real-time. The system utilizes sensors to measure key soil parameters such as moisture content and NPK values, providing farmers with valuable insights into soil fertility levels. The measured data is displayed on an LCD screen, enabling farmers to make informed decisions about crop management practices. Further-more, the system incorporates an automated spraying mechanism controlled by water pumps driven by an L298 module. When soil parameters deviate from optimal levels, the system activates the spraying system to adjust soil conditions, ensuring that crops receive the necessary moisture and nutrients for healthy growth. By combining soil parameter measurement with automated spraying capabilities, the proposed system offers a comprehensive solution for enhancing agricultural productivity and sustainability. Real-time monitoring of soil fertility levels allows for timely inter-ventions to maintain optimal growing conditions, resulting in improved crop yields and re-source efficiency. The integration of sensor technology and automation reduces the reliance on manual labor and streamlines soil management processes, enabling farmers to achieve higher yields while minimizing environmental impact. Overall, the Soil Fertility Measurement and Automatic Spraying System represent a significant advancement in soil management practices, with the potential to revolutionize agricultural productivity and con-tribute to global food security efforts.

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Arduino UNO, Soil Moisture Sensor, NPK Sensor, L298 Motor Driver

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The healthcare industry struggles to find and keep skilled workers who can adapt to patient care needs. This mixed-methods study examines the complex dynamics of healthcare workforce issues using a comprehensive literature review and primary survey data analysis. Primary data analysis can illuminate demographics, job satisfaction, and how workforce issues affect patient care and organisational performance. Healthcare personnel span many ages and genders, according to the findings. There is a strong pattern showing how many factors make a happy workplace. Clear advancement paths, a decent work-life balance, and supportive coworkers are examples. The results suggest that business culture, leadership styles, and personal preferences affect healthcare worker retention. The study shows that workforce issues greatly impact patient care and organisational effectiveness. Exhaustion and burnout increase personnel shortages, which threaten quality care. Patient safety and organisational productivity are affected across healthcare facilities. Such findings emphasise the need for targeted healthcare worker shortage relief and resilience strategies. This study adds to healthcare worker dynamics knowledge by giving empirical facts and practical insights. Its detailed synthesis of primary survey data and secondary literature help map workforce management and planning for health care organisations, legislators, and others. Impacts extend beyond academia and affect healthcare personnel acquisition, retention, and development strategies. This report urges the healthcare industry to collaborate to overcome its workforce crisis. These findings and ideas can help healthcare companies develop workplaces that encourage employee health and satisfaction while providing excellent, person-centered care.

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Healthcare workforce, workforce challenges, job satisfaction, patient care outcomes, organizational performance, mixed-methods approach, recruitment, retention, workforce resilience, healthcare management.

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In this study, we present an enhanced version of the DenseNet deep neural network model tailored specifically for tuberculosis (TB) detection using chest X-ray images. Leveraging the inherent advantages of DenseNet's densely connected layers, we propose novel architectural modifications and optimization strategies to improve both the model's performance and efficiency. Through extensive experimentation on a diverse dataset, we demonstrate significant enhancements in sensitivity, specificity, and overall accuracy compared to existing methods. Our improved DenseNet model exhibits robustness in detecting TB manifestations in chest X-ray images, holding promise for enhancing diagnostic capabilities in clinical settings

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Convolutional neural network, deep learning, tuberculosis, chest X-ray, and disease diagnosis.

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Rice varietal identification plays a crucial role in agricultural research, food safety, and quality control. In recent years, deep learning techniques, particularly Convolutional Neural Networks (CNNs), have emerged as powerful tools for image classification tasks, including the identification of different rice varieties. This paper presents a comprehensive approach to leveraging CNNs for accurate rice varietal identification. The methodology begins with data collection and preparation, involving the assembly of a diverse dataset encompassing various rice varieties under different lighting conditions and backgrounds. Supervised learning is employed, with images labelled according to their corresponding rice variety. Preprocessing techniques such as normalization and augmentation are applied to enhance dataset robustness. Next, a suitable CNN architecture is designed, drawing upon established models like sequential, or developing custom architectures tailored to the task. Emphasis is placed on maintaining spatial information and handling input images of varying sizes effectively. Techniques such as batch normalization, dropout, and appropriate activation functions are incorporated to enhance model generalization and prevent overfitting. The model is then trained on the prepared dataset, with careful consideration given to training-validation-test set splits and hyperparameter tuning. Various optimization algorithms such as stochastic gradient descent (SGD) and Adam are explored to optimize model parameters while preventing overfitting through regularization techniques.

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Rice varietal identification, Deep learning, CNNs, Supervised learning, Data collection, preparation, CNN architecture

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Transmission shafts constitute pivotal components in mechanical systems, responsible for transferring power from the engine to various mechanisms. The integrity and longevity of these systems hinge on the robustness of transmission shafts, necessitating comprehensive stress analysis. This paper presents an in-depth exploration into stress analysis methodologies applied to transmission shafts. Analytical, numerical, and experimental approaches are scrutinized, with a focus on their efficacy, limitations, and advancements. Material properties, geometric configurations, loading conditions, and manufacturing intricacies are dissected to discern their influence on shaft behavior. Through this comprehensive examination, this paper endeavors to contribute to the advancement of transmission shaft design, ensuring reliability and performance across diverse engineering applications.

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This paper presents an in-depth exploration into stress analysis methodologies applied to transmission shafts

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For decades, farmers have been using biological or chemical fertilizers to enhance crop production and soil fertility. They also play a crucial role in meeting food requirement. To meet the demand for fertilizers, the fertilizer industry emerged in India. The Indian fertilizer industry, established in 1906, has consistently accelerated its growth over the years. Every nutrient requirement of the soil is either fulfilled domestically or imported to meet demands. This industry encompasses private, public, and cooperative sectors, each making significant and collaborative contributions to the agricultural and economic development of India. This study primarily focused on the distinctive contribution of cooperative sector in conventional form of fertilizer and development of Nano fertilizer, which effectively alleviate logistical burdens.

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Fertilizer, Indian Fertilizer industry, Nano fertilizer, Cooperative sector, Public sector, Private sector

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ABSTRACT Background Unintentional and irrational usage of oral/parenteral steroids is the root cause of chronic iatrogenic cushing's syndrome. Case presentation Here, we present a iatrogenic cushing's syndrome case which is caused by longterm exposue to both parenteral and oral intake of steroids. Conclusion An evidence of constant use of over-the-counter medications is required to identify the source of exogenous glucocorticoids in iatrogenic Cushing's syndrome.

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Cushing's syndrome, steroids, cortisol

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This research paper proposal delves into the significant role played by Amar Singh Jhabal in the Gurdwara Reform Movement, a crucial chapter in Sikh history during the early 20th century. He was born on 1888 in Punjab, India and his evolution from a police sub-inspector to a prominent leader underscores his unwavering commitment to Sikh rights and religious freedom. This proposal provides an overview of Amar Singh Jhabal's background, education, and his instrumental involvement in various aspects of the Gurdwara Reform Movement. It emphasizes his vocal opposition to the confiscation of kirpans, his efforts in mobilizing the Sikh community, and his advocacy for reform in the Gurdwara management. His personal sacrifices, including imprisonment, and his pivotal contributions to the enactment of the Sikh Gurdwara Act, 1925, a landmark achievement for the Sikh community in their quest for religious autonomy and Gurdwara management under the Shiromani Gurdwara Parbhandhak Committee. His enduring legacy in Sikh history and his integral role in the broader struggle for civil and religious liberties in India.

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Akhand Path, Gurdwara, Gur Asthan, Kirpan, Central Sikh League, Tankhaiya, Gurdwara Guru Kotha, Guru ka Bagh Morcha, Gurmata,

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The importance of artificial intelligence (AI) in forming public relations (PR) strategies within digital marketing has grown in the age of digital transformation. In order to better understand AI's revolutionary impact on audience engagement, content development, data analytics, and crisis management, this study examines the various effects of AI on PR tactics. The way PR professionals engage with audiences has changed dramatically with the introduction of AI technology. Artificial Intelligence (AI) facilitates more meaningful and focused contact with customers by using complex algorithms. PR professionals may examine enormous volumes of data to determine audience preferences, attitudes, and behaviors by utilizing machine learning algorithms. This allows them to create customized message that appeals to particular groups of people. The importance of artificial intelligence (AI) in forming public relations (PR) strategies within digital marketing has grown in the age of digital transformation. In order to better understand AI's revolutionary impact on audience engagement, content development, data analytics, and crisis management, this study examines the various effects of AI on PR tactics. The way PR professionals engage with audiences has changed dramatically with the introduction of AI technology. Artificial Intelligence (AI) facilitates more meaningful and focused contact with customers by using complex algorithms. PR professionals may examine enormous volumes of data to determine audience preferences, attitudes, and behaviors by utilizing machine learning algorithms. This allows them to create customized message that appeals to particular groups of people. Furthermore, in the PR industry, AI technologies have completely changed crisis management tactics. Organizations may protect their brand and sustain stakeholder trust by promptly identifying and addressing potential crises with real-time monitoring systems that are equipped with AI-driven sentiment analysis. PR experts can determine the importance of a crisis, pinpoint important stakeholders, and adjust their communication plans by using sentiment analysis of news stories and social media conversations. Nevertheless, there are moral and legal issues with using AI into PR tactics. Ethical rules and careful thought are necessary for addressing concerns related to data privacy, algorithmic bias, and the legitimacy of content created by artificial intelligence. PR pros need to be on the lookout for ways to ensure accountability, equity, and transparency in their AI-driven projects as the technology develops.

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Keywords: Artificial Intelligence (AI), Machine learning (ML), Digital Marketing (DM)

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Creative Commons Attribution 4.0 and The Open Definition