Blockchain Enabled Reparations in Smart Buildings Cyber Physical System

Blockchain technology is evolving across the globe and is being looked upon as a definite part of the future. Blockchain is often associated with bitcoin and finance’s domain. But over the last decade, this backend technology to bitcoin has spread its association in almost all domains that we can think of. Further to this, smart contracts are making the blockchain ecosystem better. Other evolving technologies like Internet-of-things, Industrial Internet-of things, Cyber physical systems are also making their onset on the global platform. Smart buildings link Internet of-things connectivity, sensors and the cloud to remotely supervise and assure efficient heating- air conditioning, lighting and security systems etc to improve efficiency and overall sustainability. The global buildings sector over the next 40 years is expected to add 230 billion square meters of fresh construction, i.e., adding the equivalent of Paris every week. Thus integrating these technologies right at the onset, before they grow in isolation, is a coveted need today. This paper proposes a prototype to simulate architecture and discusses how blockchain-enabled smart buildings can further expedite automation, security and transparency. For an apprehension purpose, the paper focuses on smart contracts enabled repairs and service in smart buildings

Study of Sericulture & Cocoon Production in Janjgir- Champa Diistrict of Chhattisgarh (India)

Sericulture is a growing business for rural development since it integrates well with farming practices and has the ability to produce lucrative income all year round. It boasts affordable startup costs and offers jobs all year round. Sericulture, a cottage and small-scale industry, is a labor-intensive, economically appealing, and environmentally friendly form of agriculture. Per square meter of land, sericulture produces a lot of work and cash. Sericulture offers many opportunities for improving human resource employability and can successfully slow down population migration to cities. When compared to other crop operations in terms of generating money, sericulture is the most lucrative. The cultivation of mulberries, the generation of silkworm seeds, the rearing of silkworms, the reeling and weaving of silk, the collecting of byproducts, and their processing are all aspects of the sericulture industry that generate a significant amount of work and, consequently, a source of income for rural and tribal people. Sericulture is recognized as a thriving rural sector primarily because it offers families and labor year-round, remunerative employment, and also guarantees periodic income even with tiny land holdings

Use of Modular Neural Network for Heart Disease

The medical field is very versatile field and one of the interested research areas for the scientist. It deals with many medical disease problems starting with the diagnosis of the disease, preventing from the disease and treatment for the disease. There are various types of medical disease and accordingly various types of treatment methods. In this paper we mostly concern about the diagnosis of the heart disease. Mainly two types of the diagnosis method are used one is manual and other is automatic diagnosis which consists of diagnosis of disease with the help of intelligent expert system. In this paper the modular neural network is used to diagnosis the heart disease. The attributes are divided and given to the two neural network models Backpropagation Neural Network (BPNN) and Radial Basis Function Neural Network (RBFNN) for training and testing. The two integration techniques are used two integrate the results and provide the final training accuracy and testing accuracy. The modular neural network with probabilistic product method gave an accuracy of 87.02% over training data and 85.88% over testing accuracy and with probabilistic product method gave an accuracy of 89.72% over training data and 84.70% over testing accuracy, which was experimentally determined to be better than monolithic neural networks

Automated home waste segregation and management system

Waste management is a massive issue in India, most of the present systems cannot manage waste on a scalable level, thus creating pressure on the ecosystem. Before the elimination of waste, segregation needs to be done to manage individual types of waste. Hence taken the same approach to solving the problem, which most of the present-day systems fail to do. The goal is to segregate the garbage generated in individual households into solid, liquid, biodegradable, non-biodegradable, combustible, and non-combustible, using many subsystems that involve electro pneumatics, compression, and storage. Image processing techniques will further advocate the process. The desired system will further reduce the waste of an in-built pulverizer. After conducting in-depth research on the present solutions for the urban waste processing chain, the level of complexity increases as the waste goes further along the chain and, in the end, the only option left is incineration was figured out. The solution allows endpoints of the chain to process different types of garbage in a more organized fashion. Municipal solid waste (MSW) is solid waste that results from municipal community, commercial, institutional, and recreational activities. This paper aims to segregate the MSW generated by households into biodegradable, non-biodegradable, combustible, and non-combustible

Studies of genetic variability, heritability and genetic advance in balsam (Impatiens balsamina L.)

A field experiment was carried out with 34 genotypes of Balsam (Impatiens balsamina L.) to assess the variability, heritability and genetic advance with an objective to identify superior genotypes for further crop improvement programme. The experiment was conducted during rainy season 2014 at the Horticulture Research Farm, Department of Horticulture, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi. These genotypes show significant variation at 5% level of significance for different characters under study. Highest range of variation was reported with the number of flowers/plant (109-221). The phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) was maximum for seed yield/plant, i.e. 29.02 and  26.34 while, minimum in case of length of leaf, i.e.  8.35 and 6.48, respectively. High heritability was observed for all the characters except plant height, width of leaves and duration of flowering. Maximum heritability was recorded for duration of flowering (90.68%) and minimum was observed in width of leaf (30.04). High heritability (h2 = 90.64) with high genetic advance (GA= 71.36) as percentage of mean was observed for number of flowers/plant, which indicated that additive gene effects were more important for that trait. High genetic advance as per cent of mean was observed for number of flowers/plant (71.36) however, lowest for floral bud diameter (0.11) which indicates the preponderance of additive genes and selection will be effective for improvement of these traits

Physico-chemical attributes and organoleptic assessment of guava (Psidium guajava L.) cultivars grown in eastern Uttar Pradesh

A study was conducted to evaluate the different guava cultivars for their physico-chemical composition and organoleptic assessment during the year 2012-2013. Results of study indicated that Gorakh Bilas Pasand cultivar proved to be superior on the basis of physical characters (Length-7.64 cm, Breadth-7.79 cm , Weight-240.60 g, Number of seeds per fruit-251 etc.) followed by Lucknow-49. However, Lucknow-49 was found noteworthy in respect of chemical composition (TSS-13.00 oBrix, Acidity-0.50%, pH-5.86, Vitamin C-300.36 mg/100g etc). In organoleptic assessment, it was found that ‘liked very much’ rating was provided by consumer to Lucknow-49. On the basis of overall findings, it was concluded that ‘Lucknow-49’ was superior in most of characters studied and might be one of the promising cultivars for quality fruits under eastern Uttar Pradesh conditions