Volume 13 | Issue 6 |

 Abstract

The present study examines the impact of organizational climate on organization performance, focusing on leading IT firms in India i.e., Tata Consultancy Services, Infosys, Wipro, HCL, and Tech Mahindra. The research explores key organizational climate factors including work environment, job satisfaction, communication, employee commitment, training, decision-making, and work-life balance and their influence on overall productivity and employee engagement. The findings aim to provide insights into best practices for fostering a conducive organizational climate that enhances efficiency and competitiveness.

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 Keywords

Organizational Climate, Organizational Performance, Work Environment, Employee relationship, communication, etc.

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As the automotive industry shifts its focus toward software-defined vehicles, the need for faster and reliable software development continues to grow. However, traditional methods show their limitations. The rise of Generative Artificial Intelligence (GenAI), particularly Large Language Models (LLMs), introduces new opportunities to automate automotive software development tasks such as requirement analysis and code generation. However, due to the complexity of automotive systems, where software components must interact with each other seamlessly, challenges remain in software integration and system-level validation. In this paper, we propose to combine GenAI with model-driven engineering to automate automotive software development. Our approach uses LLMs to convert free-text requirements into event chain descriptions and to generate platform-independent software components that realize the required functionality. At the same time, formal models are created based on event chain descriptions to support system validation and the generation of integration code for integrating generated software components in the whole vehicle system through middleware. This approach increases development automation while enabling formal analysis to improve system reliability. As a proof of concept, we used GPT-4o to implement our method and tested it in the CARLA simulation environment with ROS2 middleware. We evaluated the system in a simple Autonomous Emergency Braking scenario.

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 Keywords

LLM- Large Language Models, Eclipse Modelling Framework (EMF), Autonomous Emergency Braking (AEB).

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 Abstract

T h e a p p r o a c h o f p r e d i c t i v e m a i n t e n a n c e , a l s o k n o w n a s P d M , r e p r e s e n t s a n e f f i c i e n t m e t h o d o l o g y f o r m a n a g i n g a s s e t m a i n t e n a n c e p r o g r a m s . P r e d i c t i o n s r e g a r d i n g e q u i p m e n t b r e a k d o w n s c a n b e d e r i v e d t h r o u g h d a t a - c e n t r i c a n a l y t i c a l t e c h n i q u e s t o o p t i m i z e m a i n t e n a n c e o p e r a t i o n s . I n s u c h s c e n a r i o s , v a l u a b l e i n f o r m a t i o n i s u t i l i z e d t o a n t i c i p a t e a n d p r e v e n t p o t e n t i a l i s s u e . The goal is to identify specific patterns and correlations that will aid in failure prediction and, eventually, prevention. In the the manufacturing sector, equipment is frequently used without a specified maintenance schedule. Due to unforeseen failures, this practice usually causes unplanned downtime. To prevent unplanned equipment stoppages, scheduled maintenance involves checking the manufacturing equipment's condition at predetermined intervals and replacing any defective parts.Conversely, this results in more extended periods that the equipment is not operating and higher maintenance costs. Predictive maintenance (PdM) techniques are becoming more and more important as a result of Industry 4.0 and smart systems, which can save downtime costs and boost industrial equipment availability (utilization rate). By making the most of component usable lives, through PdM organization have the opportunity to implement ecofriendly production methods. This paper use Index Terms: Random Forest Regression, LSTM, Industry 4.O, Predictive Maintenance (PdM)

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AIML

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The study explores the level of social awareness among slum dwellers about education and health in the greater Guwahati area of Kamrup district, Assam. Social awareness refers to an individual's consciousness about societal issues, including legal rights, health, hygiene, and education. The study emphasizes that a significant section of the slum population lacks basic awareness regarding free and compulsory education, health practices, and hygiene, resulting in persistent health problems and educational neglect. A sample of 100 respondents, including 60 males and 40 females, was selected through random sampling to assess their awareness levels. The findings aim to highlight the urgent need for educational interventions and health awareness programs to improve the quality of life in slum communities.

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Social Awareness, Slum Dwellers, Education, Health, Hygiene

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Geopolymer concrete, known for its sustainable properties and high strength, has emerged as a viable alternative to traditional Portland cement concrete. However, the prediction of cracks and the recognition of their patterns in geopolymer concrete beams remain critical challenges that impact structural integrity and durability. This review paper explores various machine learning techniques employed in the analysis of crack formation and pattern recognition in geopolymer concrete. We systematically evaluate the effectiveness of different algorithms, including supervised and unsupervised learning methods, and their applications in crack detection and classification. Additionally, we highlight the integration of image processing techniques and sensor data in enhancing predictive accuracy. The findings indicate that machine learning models significantly improve the understanding of crack behavior in geopolymer concrete, facilitating proactive maintenance strategies. This paper concludes with recommendations for future research directions, emphasizing the need for more comprehensive datasets and the exploration of hybrid machine learning models to advance the field.

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Geopolymer concrete, crack prediction, pattern recognition, machine learning, structural integrity, image processing, predictive maintenance, supervised learning, unsupervised learning, sensor data, hybrid models.

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Creative Commons Attribution 4.0 and The Open Definition

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Women cannot be differentiated based on their roles; they are creators. Unfortunately, these creators often do not receive the recognition they deserve. When we talk about their roles, we must acknowledge that throughout life, progress is possible primarily because of women. Women can also be categorized based on the localities in which they live. For instance, women in rural areas are often seen solely as housewives, with their roles confined to nurturing families. This perspective reduces their potential for becoming independent, self-sufficient decision-makers. While they create the future by raising the next generation, they are not recognized as masters of their own destinies. Women have both social and economic roles that are essential for community development. They play a crucial part in rural industrialization by contributing their time, effort, and knowledge. Notably, women possess strong financial management skills; they know how to save, where to spend, and how much to allocate for each need. With women's support, men can make informed decisions at the right time and take calculated risks. Additionally, women often innovate by starting businesses that cater to local needs, such as handicrafts, organic farming, and food processing. This entrepreneurial spirit fosters economic growth and improves their communities. This research paper discusses the significant contributions of women to rural industrialization and emphasizes their essential role in creating sustainable development.

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Keywords: Rural Industrialization, Economic Empowerment, Community Development, Entrepreneurship, Sustainable Development,

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The last few years have witnessed a rapid increase in the popularity of herbal and natural cures, thus leading to growing interest in plant-based models for dermatological applications. This present investigation deals with the formulation and evaluation of a herbal topical gel containing extracts of the well-known plants Calendula officinalis and Aloe vera gel with anti-inflammatory, antimicrobial, antioxidant, and wound-healing properties. Thus, the prime objective was directed at developing stable and effective herbal gels for topical application to promote skin healing and enhance dermal health. The Aqueous extraction method was used to prepare the Calendula officinalis plant extract where else Aloe vera gel was freshly prepared using mature leaves. Using Carbopol 940 as the gelling agent and combining it with glycerin as a humectant, different formulations of gel types were done. The formulations prepared were then subjected to a physicochemical parameter evaluation regarding pH, spreadability, viscosity, homogeneity, extrudability, and skin irritation. Of all formulations tested, the optimized gel has shown interesting pH, close to skin pH, good spreadability, and high extrudability without visible signs of phase separation or microbial growth. In addition, in vitro antimicrobial activity was carried out using the well diffusion method against common skin pathogens such as Staphylococcus aureus and Escherichia coli, with zones of inhibition observed to be promising. No irritation or adverse reactions were reported.

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Calendula Officinalis, Aloe vera, Topical Formulation, Wound Healing, Anti-inflammatory activity, Aqueous extraction,

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This study investigates the crucial relationship between brand awareness and its subsequent impact on sales performance. The research explores how varying levels of brand recognition familiarity and recall influence consumer purchasing decisions. A quantitative approach was employed utilizing surveys and sales data analysis to assess the correlation between brand awareness metrics and actual sales figures. The investigation focuses on examining consumer perceptions and brand associations. The research seeks to determine the extent to which increased brand awareness translates into tangible sales growth. Furthermore the study analyzes the effectiveness of different marketing strategies in building and sustaining brand awareness. The impact of digital marketing social media presence and traditional advertising methods are considered. The analysis identifies key drivers of brand awareness and their relative contribution to sales uplift. The findings reveal a significant positive correlation between heightened brand awareness and increased sales revenue. The results demonstrate that brands with greater visibility and positive consumer perception tend to achieve higher sales volumes. The research suggests that strategic investments in brand building activities are essential for achieving sustainable business growth. The study contributes to the understanding of brand equity and its financial implications. The research offers practical insights for marketers seeking to optimize their brand strategies and improve sales performance. The implications of the research extend to businesses of all sizes seeking to leverage brand awareness for competitive advantage. The study acknowledges limitations such as the specific industry focus and the reliance on survey data. Future research directions include exploring the long-term effects of brand awareness campaigns and the influence of brand reputation on consumer loyalty.

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Brand awareness, Sales performance, Brand reputation, competitive advantage

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Water is requisite for chow of life. It is a bounded resource. Human utilize both forms of water, Surface water and Groundwater. But groundwater resources are foremost for drinking water needs and agriculture in Bihar. The state government has carried out a multipurpose scheme JAL-JEEVAN-HARIYALI MISSION (JJHM) to nurture groundwater conservation in all districts of Bihar. This program has inspired schools to harvest rainwater within their outskirts in Kaimur district. Not only the new creation of water bodies but also the identification and rejuvenation of conventional water bodies; Wells, Ponds, Tanks and Ahar Pyne is going on and some water bodies have been completed in the study area. This mission has not been completed yet so work is going on. This approach will enhance the potential for groundwater recharge. This study is based on secondary data. These are sources; National Compilation on Dynamic Ground Water Resources of India, 2022 and JJHM Annual Report FY 2022-23. This scheme plays a remarkable role in assuring sustainable water management in Kaimur. by elevating rainwater harvesting and reviving conventional water sources, the Bihar government is working to conserve invaluable groundwater resources for future generations.

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Groundwater Conservation, Groundwater Extraction, Groundwater Resource, JAL-JEEVAN-HARIYALI MISSION(JJHM), Rainwater Harvesting

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Nanotechnology is revolutionizing the field of medicine, offering innovative solutions for drug delivery, diagnostics, and treatment. By leveraging nanoscale materials and structures, researchers are developing highly targeted and efficient therapies that minimize side effects and enhance patient outcomes. Nanoparticles are being used to deliver drugs directly to diseased cells, improving the precision of treatments for conditions such as cancer, cardiovascular diseases, and neurodegenerative disorders. In diagnostics, nanotechnology enables early detection of diseases through advanced imaging techniques and biosensors with unparalleled sensitivity. This seminar explores the applications of nanotechnology in medicine, focusing on its role in personalized medicine, nanotheranostics (a combination of therapy and diagnostics), and the development of biocompatible nanomaterials. Additionally, it addresses the challenges of clinical translation, including regulatory hurdles, safety concerns, and scalability. By understanding these advancements, healthcare professionals, researchers, and policymakers can harness nanotechnology to shape the future of medicine and improve global health outcomes.

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Nanomedicine, Targeted Drug Delivery, Diagnostic Nanoparticles, Biosensors, Personalized Medicine, Biomedical Nanotechnology ________________________

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