Volume 12 | Issue 5 |

 Abstract

This study explores how consumer perceptions influence the market demand for tribal products in the Nilgiris District, focusing on consumer awareness and perceived quality. Given the economic and cultural importance of these products, understanding the factors that drive consumer behavior is critical. The research employs a descriptive design and utilizes convenience sampling to collect data from 107 respondents through structured questionnaires, supplemented by secondary data for comprehensive coverage. Findings indicate a significant relationship between consumer perceptions and market demand, highlighted by the strong influence of perceived quality on purchasing decisions. Specifically, consumer awareness of tribal products, while high, showed a lesser direct impact on market demand compared to the perceived quality, which was strongly correlated with purchase behavior. This suggests that enhancing the perceived quality of tribal products could significantly boost market demand. Based on these findings, the study recommends intensifying marketing efforts to increase consumer awareness and highlight the unique aspects of tribal products through various media. Moreover, standardizing quality control measures could improve the consistency and overall perception of quality, further driving market demand. Ultimately, this research underscores the need for strategies that not only focus on enhancing product visibility but also on maintaining high quality to meet consumer expectations effectively. The conclusion drawn is that by addressing these key factors, there can be a substantial improvement in market demand for tribal products, benefiting the local economy and supporting the sustainability of tribal communities.

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 Keywords

Tribal Products, Consumer Perceptions, Market Demand, Nilgiris District, Cultural Significance

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT Weaning is the process of giving an infant other foods and liquids with breast milk after the age of 6 months as breast milk alone is not sufficient to meet the nutritional requirements of growing baby. It is the process by which the infant gradually becomes habituated to adult diet. Under nutrition remains one of the most common causes of morbidity and mortality among children globally, which is directly or indirectly related to knowledge of months regarding weaning. The present "A Descriptive study to assess the level of knowledge Regarding Weaning Among Nursing Mothers in Pediatric OPD of SMIH Patel Nagar, Dehradun, Uttarakhand with a view to develop informational booklet.'' AIM: To assess the level of knowledge Regarding Weaning Among Nursing Mothers in Pediatric OPD of SMIH Patel Nagar, Dehradun, Uttarakhand OBJECTIVE OF THE STUDY 1. To assess the level of knowledge regarding weaning among nursing mothers. 2. To find the association between level of knowledge of nursing mothers with their socio -demographic variables. METHODOLOGY The nature of the study was non-experimental. The study was conducted in Pediatric OPD SMIH, Patel Nagar, Dehradun; the research design use for the study was Non- Experimental descriptive research design. Total 49 nursing mothers were selected through purposive sampling technique and data was collected using self structured knowledge questionnaires in pediatric OPD in Shri Mahant Indiresh hospital Dehradun, Uttarakhand.The data collected for to assess the level of knowledge regarding Weaning among Nursing Mothers. RESULT The analysis revealed that mothers of infant (28.75%) had good knowledge, (67.57%) had average and (4.08%) had poor knowledge regarding weaning. There was no significant association found between knowledge score of nursing mothers regarding weaning with their socio demographic variables. CONCLUSION: It can concluded that most of the mothers had average level of knowledge regarding weaning.

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 Keywords

Knowledge,Weaning ,Nursing Mothers

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Abstract Indian English Literature paved way for many writers to create their own space of words and self expression. Self expression of emotions and feelings has created the genre of confession through the renowned female writer Kamala Das. Holding the ancestral traditional values and the modern equations of society Kamala Das made her writings more unique. This paper is an analysis of how Kamala portrayed herself being tackled in the clutches color in My Story.

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Keywords: Discrimination, color, humiliation, self expression, authority

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This study introduces an innovative approach to Flood Damage Assessment (FDA) by integrating advanced technologies, including Remote Sensing (RS), Geographic Information System (GIS), and a state-of-the-art neural network architecture. A custom-designed Convolutional Neural Network (CNN), incorporating a UNET with ResNet-34 as a backbone pretrained on the CIFAR-10 ImageNet model, plays a pivotal role in achieving accurate flood mapping. The utilization of transfer learning enhances the model's ability to discern intricate patterns from high-resolution satellite imagery, addressing challenges in complex landscapes. The proposed methodology, validated with diverse datasets from real-world flood events, demonstrates the effectiveness of the integrated neural network in improving disaster management strategies. This research significantly contributes to advancing flood damage assessment methodologies, showcasing the synergy of RS, GIS, and cutting-edge CNN architectures for timely and accurate disaster response and recovery.

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 Keywords

Flood Damage Assessment, Remote Sensing, Geographic Information System, Convolutional Neural Network, Transfer Learning, Satellite Imagery, Disaster Management.

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Creative Commons Attribution 4.0 and The Open Definition

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Orange peel, Osmotic dehydration, Water loss, Solid gain .

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Creative Commons Attribution 4.0 and The Open Definition

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As a foundational technology in the security net environment, detection of network intrusions has a great deal of attention and use. Network Intrusion Detection (NID) still has difficulties when it comes to installing on devices with limited resources, despite the tremendous efforts of research & advanced technologies. We provide a lightweight detection of intrusions technique based on knowledge of extraction is called Lightweight Neural Network (LNet), which strikes the balance between efficiency and accuracy by concurrently lowering computing costs and model storage. To be more precise, we stack DeepMax blocks to create the LNet after carefully designing the DeepMax blocks to extract compressed representation effectively. Additionally, in order to compensate for the lightweight network's performance decrease, we apply batchwise knowledge of oneself distillation to regularise training consistency. Our suggested Lightweight Neural Network (LNN) and XGboost methodology is shown to be successful on Allflowmeter_Hikari datasets through experiments

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Explainable Artificial Intelligence for Cyber Security

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Logistics especially cargo handling and import exports highly depend on internal and external transportation chains which are usually handled by human drivers and overseers or in recent developments by partially automated vehicles which has disadvantage of free thinking. Our project "intelligent carrier" is primarily aimed to automate cargo and luggage handling in airports at an affordable price such that it can also be implemented by storage handlers etc. This carrier follows prefixed and subsidiary paths for intelligent path selection and added ability to avoid obstacles. This robot is completely developed to be controlled by an external processing centre which is able to control multiple robot units. Its complete function is to position an airplane on its arrival and allot a robot carrier which travels along the mapped path with intelligent obstacle avoidance to reach predestined position based on closeness to the anchor location.

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 Keywords

carrier, anchor, processing center

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Film-forming gels containing povidone iodine can create a protective barrier over the wound, promoting a moist environment conducive to healing while preventing infection. The experimental work done to carry out organoleptic properties, UV spectroscopy, FTIR study and melting point determination for drug determination and then trial batches were prepared for determining the concentration and selection various polymers. Based on that factorial batches were prepared and evaluation is performed. The povidone iodine gel was prepared using different ratios of PVA and PVP K-30, PEG 400 used as a plasticizer. Formulations (F1-F9) were prepared and evaluated for their physicochemical properties. Based on that 32 full factorial designs were applied to optimize the final formulation and check the impact of independent variables. The optimized (F6) Formulation (Ratio of PVA: PVP K-30 and PEG 400) exhibited % drug release 93.59% in 360 minutes. F6 formulation found stable for 1 month during stability study.

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 Keywords

Film forming gel, povidone iodine, antiseptic, wound healing.

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A wide spectrum of vitamin deficiencies can show one or more visually distinguishable symptoms and indications that appear in multiple locations in the human body. The application provides individuals with the capability to diagnose their possible vitamin deficiencies without the need to provide blood samples through the analysis of photos taken of their eyes, lips, tongue, and nails. This process is implemented using the deep learning based CNN algorithm. Here we have considered the dataset of eyes, lips, tongue and lips. Once after the consideration of dataset, the pre-processing is performed and then CNN algorithm is used to train the data. Once after the training, model is saved and the testing is performed using the dataset.

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-Vitamin deficiency, deep learning, CNN, dataset

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In the contemporary landscape, both insurance companies and customers (insurers) are increasingly motivated to secure the most advantageous deals, particularly in the realm of health insurance where the need for coverage is of paramount concern. Customers, in particular, exhibit a heightened sense of caution when evaluating health insurance options. Fuzzy logic is a computational approach that deals with uncertainty and imprecision, has emerged as a versatile solution across various real-world domains such as electronics, computer science, finance and medical science. This study offers a comprehensive exploration of the application of fuzzy sets methodologies within the field of actuarial science, focusing on health insurance risk assessment. It delves into the foundational mathematics underpinning fuzzy sets, providing a quick overview of their development and utilization. Moreover, the study demonstrates how fuzzy logic models can be effectively constructed and refined to adapt to changing rules and incorporate supplementary data, thus enhancing their predictive accuracy and practical utility. Here a model is presented, which is based on fuzzy expert system that will help the insurance companies to find out predictive modeling of health insurance premiums for cardiac patients using Fuzzy Inference Techniques. Through the application of fuzzy logic techniques, the study aims to derive actionable insights that can inform more informed decision-making processes in the realm of health insurance.

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 Keywords

Health insurance, Decision-making, Risk assessment, Predictive modeling, Policy evaluation.

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Creative Commons Attribution 4.0 and The Open Definition