Volume 11 | Issue 1 |

 Abstract

Chronic Kidney Disease (CKD) is a global health issue with a high morbidity and mortality rate, as well as a risk factor for other diseases. Because there are no clear symptoms in the early stages of CKD, patients frequently miss the condition. Early identification of CKD allows patients to obtain timely treatment to slow the disease's progression. Because of their fast and precise recognition performance, machine learning models can successfully assist doctors in achieving this goal. In this proposed work, we suggest a machine learning methodology for diagnosing CKD in the early stages and to test the performance of proposed ML algorithms, we collected the CKD data set from the KAGGLE website, which contains a substantial number of missing values. Normally the dataset may contain some missing values and in order to fill those missing values we try to assume mean value with written type string. If these missing values are not identified then the outcome may be inappropriate. By conducting various experiments on our proposed dataset by taking the four machine learning algorithms (Logistic Regression, SVM, Random Forest Classifier, Decision Tree Classifier),we finally came to an conclusion that random forest outperforms the other machine learning models in terms of accuracy.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Chronic Kidney Disease, Logistic Regression, SVM, Random Forest Classifier, Decision Tree Classifier.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cold War, India and Russian relation, Science and Techonology

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

education, work participation, gap, below potential, life-determining decisions.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

People, Features, Script, Price, Promotion, Place, Purchase Intention, Movie Marketing

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Caste, Dalit, Upper-caste, untouchability ,Manusmriti,Caste discriminations, Identity Crisis,Autobiography,An outsider, Marginalization.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

One of India's most important economic contributors is the fashion industry. However, this industry produces a significant amount of pre-and post-production waste. This industry enthusiastically designs or updates the designs of clothing to satisfy consumer demands for fashion products, resulting in sizeable amounts of fabric waste being generated during the manufacturing process. The effort will be most effective, according to practitioners and academics, when made during the designing, pattern-making, and cutting phases in order to minimize waste. Students, researchers, and practitioners in the global fashion industry who are interested in the concerns of waste pre-production and its impact on the environment have studied and practiced the notion of zero waste fashion design, also known as zero waste fashion design. The procedures to develop garments using cutting fabric waste during the pattern making and cutting process are referred to as zero waste fashion design. The purpose of this study is to look into how the concept of zero waste fashion design can be implemented in the design and production of clothing. How different manipulation techniques and methods can also be used to develop zero waste garments.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Apparel, Manipulation, Zero Waste, Upcycling, Fashion Design.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

If you believe you can reduce the amount of food waste by analysing food waste for each individual and awarding Offer bonuses and prizes through reports generated by system. Wasting food is common among students today at university, hostels and at work. This creates great demand Due to future groceries, it may lead to food shortages future generations. Because food waste disposal is a long process. The paper has mainly focused on measuring food waste Offer rewards to users viewing real-time Everyone's Food Waste on Screens and Websites Reference to the future. This study is primarily focused on monitoring. Food loss for everyone. Our model proposes and creates it produce results in parallel, User about the amount of extra food each time. this helps Analyse and generate a list of users who fall into non-food groups Waste standards and reward their noble deeds. We can do it Automate processes manually or over the internet Things as central tools. Uses RFID sensors for monitoring personal waste. Can only be opened with RFID A map provided by the government. It basically automates how to determine the amount of local food waste.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

RFID, Iot,Ardunio Wins Motor, Motor Driver, Wi-Fi Module,Cloud Computing, Mysql Database,Servomotor

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Jigsaw Strategy, Education, Co-operative learning.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Capital is the engine of economic development and this statement is gaining importance in recent times. Traditionally, the various sources of capital for developing countries were either the demand of their output by industrial countries or foreign aid or loans from foreign banks. Today, foreign direct Investment is considered to be the major source of funds which may contribute in increasing the growth of service sector in developing countries. FDI is playing a growing role in the service sector development.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Capital, Globalisation, Tertiary, Growth, Sector

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Creative Commons Attribution 4.0 and The Open Definition