From the Desk of the Editor-in-Chief….

EduSkills is an organisation which is making serious efforts to fill the gap between Academia and Industry thus helping the Institutions to produce Industry ready digital workforce in India following the mission of working holistically on 3Es of Education, Employment and Entrepreneurship. I had the opportunity of some association with Eduskills and have been impressed by their contribution to the furtherance of relevant quality technical education in the Country.

Another step was conceived by them to bring out a Quality Journal and requested me to be the Editor-in-Chief, to which I happily agreed as my humble bit to support their efforts. To take care of the broad-based requirements, we decided to name the journal as ‘International Journal of Innovation in Multidisciplinary Scientific Research.’ I have great pleasure in forwarding this inaugural Issue to our esteemed readers.

Innovation is everyone’s business. The prime necessity of innovation is to bring the desired growth in both social and economic sectors by value addition through appropriate modifications in the performance behaviour of different parameters of growth. An innovation pre-supposes rationality at least minimally. Oue quest for a universal growth theory leads us to a highly multidisciplinary approach. The very first paper here is therefore, ’Science of Innovation’.

The second paper proposes a ‘Modified Binary Jaya Optimization Algorithm’, which has been used for the feature selection in the domain of supervised machine learning. The key feature of the proposed algorithm is design of a new filter with a Lévy-flight based update mechanism using mutual information coefficient. In the third paper titled “An improved Decision Tree Algorithm for Text Classification and Visualisation”, a fundamental hypothesis has been explained that for big data, the term ‘Machine Learning ‘must be reinvented as existing methods prove inadequate. A decision tree merging process is suggested with an Optimistic Decision Tree Algorithm and its efficacy is proved using Simulation Studies.

The fourth paper ‘Inverse Cooking Recipe Generation from Food Images using Hybrid Approaches’ develops an interesting interdisciplinary system that creates recipes from food pictures using deep learning techniques. The developed system analyses the food images to identify the ingredients, etc which is then translated into a recipe by using NLP.

The fifth paper ‘A New Pollination Based Optimization Algorithm and its Application to Paddy Disease Detection’ very interestingly derives its concept from the resource optimization strategy applied by the plants for maximal pollination success. Plants lure pollinators through sharp coloured floral display and fragrance. Authors have successfully modelled this process into a multi-population, unconstrained global optimization algorithm which was validated by demonstrating that it could successfully detect rice plant diseases to an accuracy of 99.37%. 

The next two papers describe interesting applications of Image Processing. The paper ‘Kidney Stone Detection using Fuzzy C- means Clustering’ describes a computer aided system using MATLAB for detection of kidney stones. Automating this process, the possibility of human error is significantly reduced. The use of hierarchical clustering is shown to be very effective in the process. The next paper ‘Early Prediction of Breast Cancer Risks Using Convolutional Neural Network’ makes a useful contribution for the health care professionals in increasing the precision and effectiveness of Cancer diagnosis. The paper concludes that the proposed CNN Model is giving an accuracy near 85%.

The next paper titled ‘A Novel Smart Resilient Protective System Design’ emphasises on implementing the safe and economical protective earthing system taking into account the dynamic dependency of soil parameters. The optimum design of these parameters if done manually is very tedious and also lacks accuracy to a large extent. The developed system is efficient and much more accurate.

The last paper ‘Estimation of Vegetation Index over the State of Sikkim’ makes use of recently introduced GEE Platform which facilitates data processing without the need of downloading remote sensing data to the user’s system. The developed method can be very helpful for overall sustainability studies in sectors like forests, agriculture, biodiversity, etc.

I requested the eminent academic researchers Prof Prabhat Ranjan, Prof Ramesh Chandra, Prof R K Sinha and Prof Mini Thomas to be with me on the Advisory Committee for the Journal and they all spontaneously agreed. I am grateful for their acceptance which will certainly propel us to elevate the level of the Journal. I also would thank all members of the Editorial Board and Reviewers.

The suggestions for improvement are solicited and will be certainly considered for the benefit of the readers.

Prof K K Aggarwal