In this paper we have studied some affine connexions in a Hsu-structure manifold. Certain theorems have also been proved, which are of great geometrical importance

Transformer is a static device, which converts power from one level to another level. The aim of the proposed work is to protect the transformer under overload condition by load sharing. Due to over load on transformer, the efficiency drops and winding get overheated and may get burnt. Thus, by sharing load on transformer, the transformer is protected. This will be done by connecting another transformer in parallel through a microcontroller on the other hand through the Arduino. The both controllers compare the load on the first transformer with the reference value. When the load exceeds the reference value, the second transformer will share the remaining load. If the load exceeds the rating of both transformers, then system is going to be shut down. Whenever the sharing of load on transformer occurs, the operator gets message through the GSM. An IOT is also used to inform the control station about sharing load. This arrangement will provide proper maintenance facility for both transformers. Hence, temperature of both transformers, load shared to another transformer along with timing are recorded. These can fetch about a year of records.  All these make system very efficient and reliable.

Pedestrian detection and tracking are widely applied to intelligent video surveillance, intelligent transportation. We select OpenCV as the development tool for implementation of pedestrian detection, tracking, counting and risk warning in a video segment. We introduce a low-dimensional soft- output SVM pedestrian classifier to implement precise pedestrian detection. Experiments indicate that the system has high recognition accuracy and can operate in real time. The concept can be used for the maintaining Hygienic saving the memory of data base and count the number of people passes in the fame. This is done under the Digital Image processing. We use the concept of Feature Extraction and Feature Selection. This paper of the project will undergo under many methods like Deep Neural network, Convolution Neural network, MNSIT, HOG and YULU etc. The paper is based on the project which used concepts  as  Machine Learning, Deep Learning and code is written  in Python.

Packaging waste forms a significant part of municipal solid waste and has caused increasing environmental concerns, resulting in tightening of regulations aimed at reducing the amount of waste generated. Among other material, a wide range of plastics are still used in packaging applications by producers from both organized and unorganized sectors and traders of various products even though it is being banned in a phased manner by the Indian Government. These are virtually non-biodegradable, and some are difficult to recycle or reuse due to being made of complex composites having varying levels of contamination. In our vicinity, such packaging material is observed to litter the environment in every nook and corner, around our residences, on the roads and everywhere. Recently, significant progress has been made in the development of biodegradable plastics, largely from renewable natural resources, to produce biodegradable material with similar functionality to that of plastics. This study focuses on understanding the level of awareness about plastic ban and the potential for the use of biodegradable packaging material so as to contain the planet from further deterioration and to restore its heritage to the best of our capabilities.

In a very short span, Covid-19 has spread all over the world and caused lot of devastation. The pandemic is revamping the style of our healthcare systems. Healthcare organizations need to quickly adapt to the situation using modern technologies. This paper focuses on the use of Artificial intelligence to track, trace and predict the outbreak at greater speeds and also various challenges that need to be overcome for the further advance of the field and to implement the change. Research and medical trails on the development of drugs and vaccines are also conducted quickly and effectively with AI as the algorithm can give results on different trail runs than to do all the manual research. The aim of the article is to review the role of Artificial Intelligence in combating the pandemic at present and also its potential for the future outbreaks. With the support of modern technologies like AI it is possible to reduce the impact of future pandemic explosions or at least we can be more than ready.

‘HOME’, a word which can sum up our entire world, a certain place which is supposedly intended to make us feel safe, but what if it doesn’t? Violence in any form is entirely despicable and repugnant but much worse when it happens to an innocent woman who misconstrues it to be love. Domestic violence is REAL. As per 2011 census, the percentage of people residing in urban areas in India is 31.16%, rest is a rural sector. Majority of times, such misogynistic mind set of a man having power over a woman or he having every right to hit her can be more prevalent in the rural areas compared to the urban ones. This can in turn encourage domestic violence and it is about time we stand together and eradicate it entirely from our country. We need to know that there can be a soul victimized, mentally ruptured and torn, for not everything is supposed to be ‘happy’ behind those ‘happy homes’.  This research article elucidates the nature of domestic violence, India’s efforts to eradicate domestic violence, changes needed and expected outcome.

The World Health Organization (WHO) has declared global emergency due to the pandemic outbreak of coronavirus. Rising incidents of COVID-19 among majority of the countries is an increasing concern to all of our heaths. It is important that we all know about this deadly virus and its behavior to hence prevent us from acquiring it.The purpose of this paper is to investigate about the COVID-19 and to prepare a futuristic model to prevent such outbreaks. Using graphical analysis and mathematical modeling this study analyzed the trends of COVID-19 in all the provinces of China, where the virus originated from. The obtained results are compared and we get a definitive value of the number of confirmed, cured and death cases so far in China. It was found that the COVID-19 disease has an 80% recovery rate. It is likely to affect older people and persons with chronic illness.  A unique similarity was observed between COVID-19 and SARS [Severe Acute Respiratory Syndrome], which had an outbreak in 2003. This study definitely answers questions regarding the symptoms of the disease and how it spreads. It also gives a clear image of the number of people witnessing it. This disease still does not have a definitive cure. Further studies are needed to establish the same