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AMA, Agricultural Mechanization in Asia, Africa and Latin America

AMA, Agricultural Mechanization in Asia, Africa and Latin America (AMA) (issn: 00845841) is a peer reviewed journal first published online after indexing scopus in 1982. AMA is published by Farm Machinery Industrial Research Corp and Shin-Norinsha Co. AMA publishes every subjects of general engineering and agricultural engineering.

Submission Deadline
01 Feb 2022 (Vol - 53 , Issue- 02 )
Upcoming Publication
31 Jan 2022 (Vol - 53 , Issue 01 )

Aim and Scope :

AMA, Agricultural Mechanization in Asia, Africa and Latin America

AMA, Agricultural Mechanization in Asia, Africa and Latin America (ISSN: 00845841) is a peer-reviewed journal. The journal covers Agricultural and Biological Sciences and all sort of engineering topic. the journal's scopes are in the following fields but not limited to:

Azerbaijan Medical Journal Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Agricultural and Biological Sciences
Electrical Engineering and Telecommunication
Electronic Engineering
Computer Science & Engineering
Civil and architectural engineering
Mechanical and Materials Engineering
Transportation Engineering
Industrial Engineering
Industrial and Commercial Design
Information Engineering
Chemical Engineering
Food Engineering

Analysis of Transmission Ratios for Helical Worm Gearbox Reducer to Obtain Minimum Mass of Gearbox

Paper ID- AMA-29-08-2021-10661

Gearbox have the capability of transmitting and adjusting an input motion from a prime mover to drive system. Due to this capability, they are is very widely used and is an indispensable part in industry. In this paper, the analysis of optimum transmission ratio (u2) of helical worm gearbox reducer, based on the objective function of minimizing gearbox mass, are discussed. The resulting optimization problem is solved using the Design of Experiment technique. A plan of a simulation experiment is generated to serve for finding a regression model to calculate the optimum ratio. Analysis of the results received showed that besides the influence of process parameters, their interactions also have significant effects on the response u2.

Analysis on the Entropy Characters of Population Diversity and Strong Convergence (a.s.) in Gene Expression Programming

Paper ID- AMA-29-08-2021-10660

BS-GEP (Gene Expression Programming (GEP) based on Block Strategy) is an improved GEP in time series prediction proposed in our previous work, in which the population is divided into several blocks according to the individual fitness of each generation and the mutation operators are reset differently in each block to guarantee the population diversity. To confirm the influence of our opinion on population diver- sity, and eventually reveal the evolutionary direction of the population diversity, by employing Shannon entropy to measure diversity, the entropy characters of gene-bit mutation are investigated theoretically, and the features of diversity in the evolution are analyzed. It is shown that the entropy of gene sequences adjusts with the mutation rate in BS-GEP, so that the population diversity tends to its maximum swiftly and then lower gently. Thus BS-GEP maintains more rich population diversity than the stand- ard GEP. In addition, to verify convergence of BS-GEP is not weaker than of GEP, which is proved as Strong Convergence in Probability, martingale theory is adopted to demonstrate BS-GEP with Almost Everywhere Strong Convergence (a.s.) in its Markov chain analysis, to complement the convergence theory of BS-GEP.

Determining Optimum Partial Gear Ratios of Two-Stage Helical Gearboxes with First Stage Double Gear Sets to Achieve Minimum Cost

Paper ID- AMA-28-08-2021-10659

In the design of the reducer, the transmission ratio is one of the most important parameters because it is directly related to the volume, size, and cost of the reducer. In this work, we recommend a method to find the optimum gear ratio u1 of the two-stage helical gearbox with the first- stage double gear set to achieve the minimum cost. Whereby, a simulation experiment designed and performed by an optimization program with the goal of minimum cost. Ten input variables were considered to find their influence on the optimal u1. In the end, the proposed regression model is confirmed by determining the deviation between the experiment and response u1 through the residual evaluation distribution.

Inhibition of glycation and multiple marker analysis using extracts of Nanorrhinum ramosissimum (Wall.) Betsche: An under investigated plant species

Paper ID- AMA-28-08-2021-10658

Glycation leads to subsequent production of advanced oxidative protein products and glycation end products that contribute immensely in manifesting various diabetic complications. Bioactive molecules from medicinal plant sources with antiglycation properties can significantly check these alterations. Nanorrhinum ramosissimum, a traditionally acclaimed medicinal herb that has been used in the Indian indigenous systems of medicine and treatment and has been known for curing diabetes. In the present study, aqueous shoot extract of field and in vitro regenerated N. Ramosissimum was used for estimation of antiglycation potential. Inhibition of glycation was analyzed by estimating different antiglycation markers (fructosamine, protein carbonyl group, thiol group, amino group and advanced oxidation protein products) at multiple stages by co-incubation of plant extracts with bovine serum albumin-methylglyoxal glycation model. The plant extracts displayed significant antiglycation potential at all stages. The present study might be able to draw the attention of different researchers and medical practitioners towards wider acceptability of this valuable medicinal plant N. Ramosissimum so that it could further be explored and subsequently utilized in combating pathogenic complications associated with diabetes.

Standardization of Rugose Spiralling Whitefly field level images for Artificial Intelligence application on Coconut gardens

Paper ID- AMA-28-08-2021-10657

Coconut is referred as the tree of heaven, as it provides various products to the people. Coconut is grown in over 86 countries in the world with a production of 54 billion coconuts every year. Aleurodicus rugioperculatus Martin (Hemiptera: Aleyrodidae), commonly known as the Rugose Spiralling Whitefly (RSW), is commonly observed on coconut palm. The invasive pest RWS causes stress to coconut plant by removing nutrient and water and also produces honeydew which causes heavy loss to the coconut gardens. There is a need for early identification of RSW with the field level images using Artificial Intelligence. The images are collected from the field at three levels, 1. healthy leaflets 2. RSW infestation leaflets and 3. Scooty mould leaflets, of which the images are standardized by using Artificial Intelligence application, Random Forest Classifier is used to classify the images and it is an early warning system for better management of coconut gardens.