Adopt Agile Methodology for Building Wealth Management Platform Building

Agile software development is becoming very important software development methodology in the IT world because it is iterative and its agility. This research shows how the agile methodology helps to deploy the project smoothly by saving time and money. This research also shows the benefits of adopting agile than following traditional procedure. The result of the research would help to adopt and implement the agile methodology and would help to achieve the business goals

Content-based Image Retrieval by Spatial Similarity

Similarity-based retrieval of images is an important task in image databases. Most of the user's queries are on retrieving those database images that are spatially similar to a query image. In defence strategies, one wants to know a number of armoured vehicles, such as battle tanks, portable missile launching vehicles, etc. moving towards it, so that one can decide counter strategy. Content-based spatial similarity retrieval of images can be used to locate spatial relationship of various objects in a specific area from the aerial photographs and to retrieve images similar to the query image from image database. A content-based image retrieval system that efficiently and effectively retrieves information from a defence image database along with the architecture for retrieving images by spatial similarity is presented. A robust algorithm SIMdef for retrieval by spatial similarity is proposed that utilises both directional and topological relations for computing similarity between images, retrieves similar images and recognises images even after they undergo modelling transformations (translation, scale and rotation). A case study for some of the common objects, used in defence applications using SIMdef algorithm, has been done

A Review of Current Research Trends in Power-Electronic Innovations in Cyber-Physical Systems.

In this paper, a broad overview of the current research trends in power-electronic innovations in cyber-physical systems (CPSs) is presented. The recent advances in semiconductor device technologies, control architectures, and communication methodologies have enabled researchers to develop integrated smart CPSs that can cater to the emerging requirements of smart grids, renewable energy, electric vehicles, trains, ships, internet of things (IoTs), etc. The topics presented in this paper include novel power-distribution architectures, protection techniques considering large renewable integration in smart grids, wireless charging in electric vehicles, simultaneous power and information transmission, multi-hop network-based coordination, power technologies for renewable energy and smart transformer, CPS reliability, transactive smart railway grid, and real-time simulation of shipboard power systems. It is anticipated that the research trends presented in this paper will provide a timely and useful overview to the power-electronics researchers with broad applications in CPSs.post-print2.019 K

The measurement of the concentration and distribution of ceratocystis paradox a (De seynes) moreau in soil

A baiting technique making use of sugar-cane discs was used to estimate the concentration, and presence of aggregations, of spores of Ceratocystis paradoxa in the soil. The technique was based on the probability of infection from small samples of soil. A concentration of six spores per gram of soil was readily detected. A number of sugar-cane fields were surveyed. The equivalent random con centration of spores varied from 0 to 148 per gram of soil for samples taken 4-8 in. below the soil surface. The greatest concentrations of spores were at 3-6 or 6-10 in. depths

Hybrid Vehicle: A New Era of Transportation

With arrival of the 21st century the human civilization has come across new problems. The problems they have never faced before and the seeds of these problems were sown a long time ago. It was the dependency of humans on the fossil fuel that led us to the problems like Global Warming, Climate change and energy crisis. But as said necessity is the mother of all invention. With the problems and the lack of fossil fuel the hunt for new source of energy began. With all the green sources of energy discovered the fact was clear that we know to convert most of them into electrical energy. So a new system of transport had to be developed that uses electrical energy. Here in this paper we will have a look on the history of the transportation, the need for the electrical vehicles, their working, the innovations and their impact around the globe along with the challenges they will face ahead. The paper will also discuss the working and function of “Electrical Vehicles” and “Plug in Hybrid Vehicles”. The paper will conclude the advantages and disadvantage of hybrid and electrical vehicles, regenerative braking, Hydrogen fuel cell, types of propulsion system and how it will change our way of living in the futur

Modeling structure property relationships with Kernel recursive least squares

Motivation: Modeling structure property relationships accurately is a challenging task and newly developed kernel based methods may provide the accuracy for building these relationships. Method: Kernelized variant of traditional recursive least squares algorithm is used to model two QSPR datasets. Results: All the datasets showed a good correlation between actual and predicted values of boiling points with root mean squared errors (RMSEs) comparable to other conventional methods. For the datasets from Espinosa et al., KRLS showed good prediction statistics with R value in the range of 0.97-0.99 and S value in the range 5.5- 8 as compared to multiple linear regression (MLR) with R value in the range 0.85-0.88 and S value in the range 22-26. For the dataset from Trinajstiu et al., KRLS performed consistently well with R values lying in the range of 0.95-0.99 and S in the range of 5-10 as compared to MLR with R values in the range of 0.7-0.85 and S in the range of 25-30. Conclusions: The KRLS method works better when more number of variables from the dataset are included as against other methods such as support vector learning or lazy learning technique which works better for smaller number of reduced relevant variables from the dataset