Volume 11 | Issue 4 |

 Abstract

Rainfall is of utmost importance in agriculture, but predicting it accurately has become a significant challenge in recent times. Accurate forecasts of precipitation provide valuable insights in advance, enabling individuals to take necessary precautions and devise better crop strategies. The impact of global warming on nature and humanity has accelerated changes in climatic conditions, resulting in adverse effects such as flooding and drought. As a result, accurately predicting rainfall has become one of the best techniques to understand the climate. However, forecasting precipitation is a demanding and uncertain task that significantly impacts human society. Precise and timely predictions can proactively mitigate potential human and financial losses. To address this issue, a series of experiments were conducted using prevalent machine learning methods to construct models that anticipate whether it will rain the following day based on weather data for that day in major Australian cities. The outcomes offer a comparison of diverse evaluation metrics of these machine learning approaches and their capability to predict precipitation by scrutinizing the weather data. The study aims to provide accurate climate descriptions to clients from various domains such as agriculture, research, power generation, etc., to comprehend the need for climate transformation and its parameters, such as temperature, humidity, precipitation, and wind speed, which ultimately lead to rainfall predictions. It is essential to note that predicting rainfall is a challenging task that also depends on geographic location.

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 Keywords

rainfall prediction, machine learning, dataset, visualization, classifiers, model evaluation

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The article discusses the impact of GST on the FMCG industry in India. It highlights the changes in supply chain management, logistics, pricing of goods and services, compliance challenges, and the government's initiatives to support the industry. The article also examines the impact of GST on consumer behavior and demand, as well as the challenges faced by small and medium-sized FMCG businesses. Additionally, the article provides predictions and future outlook for the FMCG industry under GST, such as increased compliance, adoption of technology, consolidation of the industry, and increased exports. Overall, the article concludes that the implementation of GST has had a positive impact on the FMCG industry, promoting growth, innovation, and competitiveness, and contributing to the Indian economy.

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 Keywords

GST (Goods and Service Tax),FMCG (Fast Moving Consumer Goods) Industry, Logistics, Pricing, Compliance challenges, Consumer behaviour, Government initiatives.

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Food, according to Indian culture is the source of sustenance for the entire creation. Food is considered to be very sacred and is treated as God.Strict restrictions were placed in Indian culture regarding dietary patterns as it is believed that the food affects one's physical as well as mental and emotional health of individuals. In the current time,the effect of food and its influence on mind is neglected. Due to availability of packed, processed and ready to eat foods in plenty, children's eating patterns are adversely affected. Current day children prefer to eat processed, junk foods than freshly available foods and home - made foods. These eating patterns have lead to ill health, obesity, depression, psychosomatic problems etc. The problems faced due to faulty eating behaviours can be corrected with the ancient Indian wisdom on yogic diet. The current study made an attempt to review the effect of yogic diet prescribed by Indian culture to mitigate food related problems among children. Keywords: Yogic diet, types of food in Indian culture Food, according to Indian culture is the source of sustenance for the entire creation. Food is considered to be very sacred and is treated as God.Strict restrictions were placed in Indian culture regarding dietary patterns as it is believed that the food affects one's physical as well as mental and emotional health of individuals. In the current time,the effect of food and its influence on mind is neglected. Due to availability of packed, processed and ready to eat foods in plenty, children's eating patterns are adversely affected. Current day children prefer to eat processed, junk foods than freshly available foods and home - made foods. These eating patterns have lead to ill health, obesity, depression, psychosomatic problems etc. The problems faced due to faulty eating behaviours can be corrected with the ancient Indian wisdom on yogic diet. The current study made an attempt to review the effect of yogic diet prescribed by Indian culture to mitigate food related problems among children. Keywords: Yogic diet, types of food in Indian culture Food, according to Indian culture is the source of sustenance for the entire creation. Food is considered to be very sacred and is treated as God.Strict restrictions were placed in Indian culture regarding dietary patterns as it is believed that the food affects one's physical as well as mental and emotional health of individuals. In the current time,the effect of food and its influence on mind is neglected. Due to availability of packed, processed and ready to eat foods in plenty, children's eating patterns are adversely affected. Current day children prefer to eat processed, junk foods than freshly available foods and home - made foods. These eating patterns have lead to ill health, obesity, depression, psychosomatic problems etc. The problems faced due to faulty eating behaviours can be corrected with the ancient Indian wisdom on yogic diet. The current study made an attempt to review the effect of yogic diet prescribed by Indian culture to mitigate food related problems among children. Keywords: Yogic diet, types of food in Indian culture

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Yogic diet, types of food in Indian culture

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After the COVID-19 virus was introduced to the world, the WHO declared a global pandemic. It affected over 150 countries. To minimize the spread of the virus, schools, offices, and markets were temporarily closed. During the pandemic, many of the lecture sessions were conducted on-line, which caused a surprise for the teaching fraternity and the stack holders. It is with this background the researchers have made an attempt to study the willingness of the Faculty members to teach online Post-pandemic with special emphasis on Faculty in Private engineering colleges in Bangalore. The study was conducted among 144 Faculty members using a mixed-method approach to collect and analyze qualitative and quantitative data. The various phases of the study included: literature search, review, problem formulation, data collection, and analysis. Using SPSS .24 software the collected data was analyzed and the statistical tools applied were Cross Tabulation, Chi-Square tests, Correlation Method and Garrett Ranking Method. Majority of the Teaching Faculty contacted for this survey expressed their readiness to teach online Post-pandemic. This research also highlights two important issues that Teaching Faculty face: Lack of Equipment and Erratic/Unstable Internet Connection. Hence, the respective managements should pay attention to these issues on a priority basis to provide quality teaching to the teaching community.

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COVID-19, pandemic, teaching fraternity, stack holders, Post-pandemic

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Women are the pillars of society. Though their contribution to the social, political and economical plethora is not given priorities, their contribution to the household activities can't be denied by anyone. Due to the existing gender roles in the society, women are always expected to be within the four walls of their own homes. Perhaps, this results in more inclination of women towards the environment. Because women rely on the environment for their household chores- starting from cooking to relaxing. Women are the best collectors of natural resources. They depend on natural resources such as water, trees, land etc for their household chores. Hence, the loss of the environment directly impacts the lives of women. Forest is considered one of the most important natural resources and it becomes mandatory to preserve and conserve it. It is important for maintaining the ecology and women play a very vital role in its protection. The destruction of the environment mostly affects women as they are the most attached to the environment. Women are the active agents of conservation and restoration of the environment . Globally researchers have been trying their level best to link gender equality with a balanced environment and to portray how degrading environmental situations can result in the enhancement of men- women gap as well as refusal to women's rights. For example, countries with more women in their parliaments are likely to set aside protected land and ratify environmental treaties. The main reason behind examining the issue of women and environment is to show the role of women in the development of a balanced sustainable environment. For example, in India women are seen to be attached to a forest.environment sometimes for household chores and sometimes due to their mother's kind of love. This paper tries to show the relationship between women and the environment, various environmental movements etc.

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Environment, Women, Environment conservation, Environment restoration

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Creative Commons Attribution 4.0 and The Open Definition

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This paper explores the use of k-means clustering as a powerful technique for customer segmentation in marketing. The strengths and limitations of k-means clustering are discussed, as well as the factors that affect the accuracy and effectiveness of segmentation using this technique. The paper also highlights the importance of data preprocessing, feature selection, and clustering evaluation in achieving robust and insightful customer segmentation. In conclusion, the paper provides recommendations for future research directions and practical implications for businesses seeking to use k-means clustering for customer segmentation.

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Customer Segmentation, K-means Clustering Algorithm, Marketing Strategy, Data Mining, Machine Learning, Customer Behaviour, Consumer Profiling, Customer Analytics.

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Abstract All human life events are Profession. When man began to use knowledge to increase his power, he became an industrial scientist. The Sangam period was a period of great influence in industrial development. Neythal and Marutham during the Sangam period, the productivity of the land shows his industrial prowess. It is because of this that there are reports of professional skills in the literature. Thiruvalluvar Human Society describes the skills that development can achieve. This article examines professional skills among them.

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???????? (Hard Skill), ????????? (Soft Skill), ??????????? ???????? (Professional Skills), ?????????? ?????, (Management Skills), ???? (Virtue).

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This research suggests a visibility detection approach based on the identification of the taillight signals of the previous vehicle using vehicle pictures. We first construct the system for picture enhancement before identifying the vehicle from the enhanced image. We are building a system that primarily serves as a means of vehicle identification without using the taillights. The other is to recognize moving vehicles using taillight segmentation. Utilising a YOLOv2 detector network, automobiles are detected in this work. The enormous variety in picture appearance and imaging interference mean that even though numerous automated detection approaches, including those based on image processing techniques, have been developed, the detection performance can still be improved.

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 Keywords

: Atmospheric haze removal, Image Processing, YOLOV2, MATLAB

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Background: The digestive system is impacted by gastrointestinal tract (GI) illnesses, and conventional diagnosis calls for invasive treatments. Large datasets can be used to train deep learning models to accurately predict and diagnose GI tract diseases, allowing for early detection, fewer invasive procedures, and better patient outcomes. Methods: We gather and preprocess a sizable dataset to build a deep learning model for predicting gastrointestinal tract illness. Meaningful data is extracted using feature extraction techniques, and an appropriate deep learning model is chosen and trained on the preprocessed data. Lastly, performance measures are used to assess the trained model on a validation dataset. Findings: High accuracy rates have been reached for disorders including colon cancer, inflammatory bowel disease, and Crohn's disease, demonstrating the potential of deep learning models for the prognosis of gastrointestinal tract diseases. Improved patient outcomes and lower healthcare costs can result from the adoption of non-invasive techniques for early detection and diagnosis. The models must be validated in clinical situations through more study. Novelty and applications: A innovative and non-invasive method of diagnostics is the application of deep learning models for the prognosis of gastrointestinal tract disorders. The use of this technology has the potential to completely transform the area of gastroenterology by enabling early identification and individualised treatment strategies. It can also lower medical expenses and enhance patient outcomes.

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 Keywords

Gastrointestinaltract,Data set,Crohn's disease,Detection,Gastroenterology.

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In this Project, a tentative design of a cloud-based Stroke prediction system had been proposed to detect impending Stroke using Machine learning techniques. For the accurate detection of the Stroke, an efficient machine learning technique should be used which had been derived from a distinctive analysis among several machine learning algorithms. The proposed algorithm was validated using two widely used open-access database, where 10-fold cross-validation is applied in order to analyze the performance of Stroke detection. An accuracy level of 97.53% accuracy was found from the ML algorithm along with sensitivity and specificity of 97.50% and 94.94%respectively. Moreover, to monitor the Stroke patient round-the-clock by his/her caretaker/doctor, a real-time patient monitoring system was developed and presented using Arduino, capable of sensing some real-time parameters such as body temperature, blood pressure, Blood flow, Heartbeat, Oxygen level. With the help of different decision-making algorithms decisions can be made easily and fast and according to its people can have access to the database. The main advantage of our system is it automatically generate the require prescription based on the vital parameters of the human.

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 Keywords

Machine learning techniques, learning algorithms and Nursing workflow

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Creative Commons Attribution 4.0 and The Open Definition