An Overview of Pulses Production in India: Retrospect and Prospects of the Future Food with an Application of Hybrid Models.

Forecasts are valuable to countries to make informed business decisions and develop data-driven strategies. The production of pulses is an integral part of agricultural diversification initiatives because it offers promising economic opportunities to reduce rural poverty and unemployment in developing countries. Pulses are the cheapest source of protein needed for human health. India's pulses production guidelines must be based on accurate and best forecast models. Comparing classical statistical and machine learning models based on different scientific data series is the subject of high-level research today. This study focused on the forecasting behaviour of pulses production for India, Karnataka, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh. The data series was split into a training dataset (1950-2014) and a testing dataset (2015-2019) for model building and validation purposes, respectively. ARIMA, NNAR and hybrid models were used and compared on training and validation datasets based on goodness of fit (RMSE, MAE and MASE). This research demonstrates that due to the diverse agricultural conditions across different provinces in India, there is no single model that can accurately predict pulse production in all regions. This study's highest accuracy model is ARIMA. ARIMA outperforms NNAR, a machine learning model. Pulse production in India, Rajasthan, and Madhya Pradesh will expand by 26.11%, 12.62%, and 0.51% from 2020 to 2030, whereas it would decline by - 6.5%, - 6.21%, and - 6.76 per cent in Karnataka, Maharashtra, and Uttar Pradesh, respectively. The current forecast results could allow policymakers to develop more aggressive food security and sustainability plans and better Indian pulses production policies in the future.

Prospect of Bioactive Curcumin Nanoemulsion as Effective Agency to Improve Milk Based Soft Cheese by Using Ultrasound Encapsulation Approach.

The aim of this paper was to determine the effect of stabilized curcumin nanoemulsions (CUNE) as a food additive capable of directionally acting to inhibit molecules involved in dairy products' quality and digestibility, especially cheese. The objects were cheeses made from the milk of higher grades with addition of a CUNE and a control sample. The cheeses were studied using a scanning electron microscope (SEM) in terms of organoleptic properties, such as appearance, taste, and aroma. The results show that the addition of CUNEs improved the organoleptic properties compared to the control cheese by 150% and improved its shelf life. The SEM study shows that formulation with CUNE promotes the uniform distribution of porosity. The CUNE-based cheese shows a better sensory evaluation compared to the emulsion without curcumin. CUNE-processed cheese provided better antioxidant and antimicrobial analysis than the control sample and offers added value to the dairy sector.

Parallel multigrid method for solving inverse problems.

We considered in this work the linear operator equation and used the Landweber iterative method as an iterative solver. After that, we used the multigrid method as an optimization method for obtaining an approximation solution with a highly accurate and fast process. A new parallel algorithm for the multigrid process has been developed. The proposed algorithm is based on a V-cycle mixed with the two-grid method. This modification of the V-cycle provides for parallel computing for each level. A coarse grid operator with a residual right-hand side vector for each coarse grid is provided. This parallel algorithm is used to accelerate and enhance computation for the solution of the iteration method in solving the inverse ill-posed problems. The necessary cost-time computation for all stages and processes for the parallel V-cycle algorithm has been done. A numerical experiment on solving the IVP (initial value problem) for the heat equation showed that the new parallel algorithm is much more efficient than the sequential method.•The study of iteration algorithms and mathematical experiments reveals a slow rate of convergence.•The Multigrid method is often used to speed up the rate of convergence of iterative methods, which is an effective method of solving large systems of linear algebra equations.•The approximation solution for the linear algebra equations was found by using the parallel method with the multigrid method.

Case-Study-Based Overview of Methods and Technical Solutions of Analog and Digital Transmission in Measurement and Control Ship Systems.

The purpose of this article is to provide an overview of possible solutions to improve the performance of measurement and control processes in maritime engineering applications. This improvement can be basically provided by adopting techniques to enhance the reliability of measurement/control systems based on the 4-20 mA analogue standard. This aspect will be discussed through a Simscape Simulink model illustrating methods of noise and ground loops elimination for pressure measurement of a 4-20 mA current loop in the tank level measurement system on a bulk carrier commercial ship. Alternatively, improved measurement and control processes can be rendered by utilizing smart transmitters based on wired hybrid analogue-digital (Highway Addressable Remote Transducer (HART)), wired digital (Foundation Fieldbus (FF)) or wireless (wireless HART) communication protocols. A brief theoretical description of these protocols will be presented in this article. As an example of using smart transmitters, a simulation-based case study will analyze the possible options to implement non-intrinsically safe as well as intrinsically safe FF models for the tank level measurement system on a bulk carrier commercial ship. Conclusions obtained through analysis of the simulation results will characterize the behavior of FF segments in safe as well as explosive hazardous areas, highlighting the characteristics of field barriers and segment protectors used in conjunction with the HPTC (High-Power Trunk Concept) intrinsically safe model.

State of the art in total pulse production in major states of India using ARIMA techniques.

Pulses are staple protein-rich food for Indian vegetarians, and India is one of the largest producers in the world. The present investigation is an attempt to study the trend in the production of total pulses in India using the autoregressive integrated moving average (ARIMA) method. For stochastic trend estimation, yearly data were used for the period from 1961 to 2019. On the basis of the performance of several goodness of model fit criteria, the most suitable ARIMA model is chosen to capture the trend of pulse production. Forecasting for the 10 years from 2020 to 2029 is done, and it is observed that India has the highest forecast value (31.03302 million tonnes) in 2029. This study will play an important role in determining the gap between production of and demand for pulses in the future.