Open Access Original Research Article

Study of Acoustic Waves in a Teaching Classroom using Finite Element Method

C. A. Wilson Bárcenas, J. M. Horta Rangel, M. A. Pérez Lara y Hernández, J. B. Hernández Zaragoza, M. L. Pérez Rea, L. F. Pérez Moreno

Current Journal of Applied Science and Technology, Page 65-75
DOI: 10.9734/cjast/2021/v40i2031464

Aims: To understand the behavior of acoustic waves in a specific classroom in order to get a configuration of panels and ceilings configuration to improve reception and clarity of internal sounds. This was possible by the modification of the properties of the enclosure, sush as the absorption coefficients of internal surfaces. The analysis was carried out through the implementation of a model by using Finite Element Method.

Study Design: The acoustic behavior that enclosure for academic use require is discussed, indicating that it is common to find deficiencies in the acoustic architecture of enclosures, and the risks that this causes to cognitive and academic development, as a consequence of low understanding.

Place and Duration of Study: Graduate Engineering Department, Universidad Autónoma de Querétaro, between August 2020 and June 2021.

Methodology: The problem is solved by applying the finite element method. This implies that the essential concepts for the understanding of this subject are reviewed, such as; acoustic physics, mechanics of the continuous medium and finite element method.

Results: After multiple analized scenarios, it was observed that while there is an absorption greater than the surface, the material of the panel or ceiling is not relevant. On the other hand, the size and surface where is located the panels turned out to be more relevant parameters.

Conclusion: Considering the proposed alternatives, an increase in the Sound Pressure Level and a uniform distribution can be observed. The use of computational tools help to understand the behavior and distribution of acoustic waves in the classroom, which can provide an overview of different adaptations.

Open Access Original Research Article

Binary Logistic Regression Analysis on Predicting Academics Performance

E. K. Akinyemi, O. A. Ogunleye, H.O Olaoye, J. Brakoru

Current Journal of Applied Science and Technology, Page 1-6
DOI: 10.9734/cjast/2021/v40i2031458

This paper considers the application of logistic regression model to predict academics performance of students. The choice of this model becomes imperative as a result of dichotomous relationship existing in the model (either pass or fail). 100 students from the four department where engaged in the study. Statistical package for social scientist (SPSS) was used for the analysis. The results show that monthly allowance of students, and study time of the students were significant predictors. While gender and educational level of parent were insignificant predictors. The fitness of the model was assessed using Hosmer and Lemeshow test, split-sample approach and other supplementary indices to validate the model. The fitted model indicated that fitted binary logistic regression model could be used to predict the future performance of students.

Open Access Original Research Article

Facial Expression Recognition Using Python Using CNN Model

Akash Kumar, Athira B. Nair, Swarnaprabha Jena, Debaraj Rana, Subrat Kumar Pradhan

Current Journal of Applied Science and Technology, Page 7-16
DOI: 10.9734/cjast/2021/v40i2031459

Facial expressions are a vital part of human life. Each day has a number of instances and all instances include numerous amounts of communication. Every communication expressed with emotion tells us about the state of the person. The interpersonal as well as security purposes are solved through facial expressions. The mischievous intention of a person can be caught by his expressions.

The human mind can capture visual information faster. So, a machine recognizing it will be a challenge. As the saying goes- “A picture is worth a thousand words”- only when it is represented well. A machine being able to detect the atmosphere by the means of expression is less of a manual work.

This paper detects the faces, extract the features as well classify them into different categories which ultimately lead to expression recognition. We evaluate our proposed method with the dataset which we used and the recall of angry, fear, happy, neutral, sad, and surprise is 60%, 31%, 84%, 22%, 57% and 58% respectively and the f1-score is 51% 35%, 82%, 25%, 51% and 64% respectively. Experimental results demonstrate the competitive classification of our proposed system.

Open Access Original Research Article

A Hybrid Prediction Model of Kernel Principal Component Analysis, Support Vector Regression and Teaching Learning Based Optimization Techniques

Mohammed Siddique, Tumbanath Samantara, Siba Prasad Mishra

Current Journal of Applied Science and Technology, Page 17-25
DOI: 10.9734/cjast/2021/v40i2031460

Forecasting of stock market is considered as one of the most decisive and critical tasks for the data scientists in financial domain. Stock market is one of exciting and demanding monetary activities for individual investors, and financial analysts. The stock market is an inter-connected important economic international business. Prediction of stock price has become a crucial issue for stock investors and brokers. The stock market is able to influence the day to day life of the common people. The stock price is based on the state of market stability. As the dormant high noises in the data impair the performance, reducing the noise would be competent while constructing the forecasting model. To achieve this task, integration of kernel principal component analysis, support vector machine with teaching learning based optimization algorithm is proposed in this research work. Kernel principal component analysis is able to remove the unnecessary and unrelated factors, and reduces the dimension of input variables and time complexity. The feasibility and efficiency of this proposed hybrid model has been applied to forecast the daily open prices of stock index of a leading Company. The performance of the proposed approach is evaluated with 3543 daily transactional (13th December 2001 to 4th December 2020) stocks price data from Bombay Stock Exchange (BSE). Empirical results show that the proposed model enhances the performance of the prediction model and can be used for taking better decision and more accurate predictions for financial investors.

Open Access Original Research Article

Effects of Fermented Maize Residue on the Physicochemical and Nutritional Properties of Cookies

Owuno Friday, Kiin-Kabari David Barine, Akusu Monday

Current Journal of Applied Science and Technology, Page 26-33
DOI: 10.9734/cjast/2021/v40i2031461

Fermented maize residue, a by-product of the production of fermented starch, a local weaning food and breakfast cereal for adults in Nigeria and West Africa was dried, milled into flour and utilized as a fibre source in cookies production at 0 – 30% levels of substitution.  The effects of the addition of the fermented maize residue on the physical, sensory and nutritional properties on the cookie sample were investigated.  Results showed spread ratio values decreased with residue flour addition, ash content and protein content and carbohydrate also showed a decrease.  The crude fibre content increased with levels of replacement.  The result of sensory evaluation showed equal preference among the samples.  Invitro-protein digestibility showed a decrease with fermented maize residue addition. Addition of fermented maize residue to cookie production can be a viable way of utilizing the fibre rich fermented maize residue

Open Access Original Research Article

Genetic Components and Diversity Analysis in Indian Mustard [Brassica juncea (Linn.) Czern & Coss] Based on Different Morpho-physiological Traits

Chitralekha Shyam, M. K. Tripathi, Sushma Tiwari, Niraj Tripathi

Current Journal of Applied Science and Technology, Page 34-57
DOI: 10.9734/cjast/2021/v40i2031462

Aim: Indian mustard [Brassica juncea (Linn.)] is the third vital oilseed crop in the world which contributes 28.6% in the production of oilseeds. Genetic diversity assessment plays a fundamental role in the preservation and improvement of the targeted plant species.

Study Design: In the present investigation, 196 Indian mustard genotypes including checks were grown in the field and evaluated based on different morpho-physiological traits.

Place and Duration of the Study: All the genotypes were grown in randomized block design with two replications in Rabi 2016-17 and 2017-18 at the experimental field of Department of Genetics & Plant Breeding, College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior, M.P., India.

Methodology: The study was conducted to record different morphological and physiological traits that play a major role in differentiating the targeted genotypes.

Results: Based on the present study, the highest genotypic and phenotypic coefficients of disparity were documented for seed yield per plant tracked by harvest index and numbers of silique per plant. Maximum heritability and genetic advance were documented for seed yield per plot tracked by harvest index, biological yield per plot, days to 50% flowering, length of the main raceme, numbers of silique per plant, seed yield per plant, numbers of seeds per silique, 1000-seed weight and numbers of silique per the main raceme.

Conclusions: In principal component analysis, 15 principal components were evidenced while cluster analysis gave 16 clusters. The highest inter-cluster distance was evidenced between cluster 9 and cluster 16 which suggests that the hybridization scheme considering parents from these clusters is supposed to be given a higher occurrence of better-wanted combination(s) for expansion of beneficial genetic stocks.

Open Access Original Research Article

Correlation Studies in Ashwagandha [Withania somnifera (L.) Dunal]

Babulal Dhaka, Amit Dadheech, N. K. Padiwal, Raju Ram Choudhary

Current Journal of Applied Science and Technology, Page 58-64
DOI: 10.9734/cjast/2021/v40i2031463

In the present study entitled “Variability and Correlation Studies in Ashwagandha [Withania somnifera (L.) Dunal]”, 74 genotypes along with three standard checks viz., JA-20 (Jawahar Asgandh-20), JA-134 (Jawahar Asgandh-134) and RVA-100 were evaluated in augmented RBD design during late kharif 2019-20 at the Instructional Farm, Rajasthan College of Agriculture, Maharana Pratap University of Agriculture and Technology, Udaipur (Rajasthan).

The observations were recorded on ten randomly selected competitive plants for fifteen characters, viz. days to 50% flowering, days to 75 per cent maturity, plant height, number of primary branches per plant, number of secondary branches per plant, leaf area index, root length, root diameter in collar region, fresh root yield per plant, dry root yield per plant, fresh plant weight per plant, dry plant weight per plant, 100 seed weight, harvest index and total alkaloid. Analysis of variance, correlation coefficient and path analysis were performed for the mean data.

The dry root yield per plant exhibited significant and positive correlation with dry plant weight, fresh root yield and harvest index at both genotypic and phenotypic level. While with, root diameter in collar region at genotypic level and fresh plant weight at phenotypic level. Positive and significant correlation among dry root yield per plant and contributing characters would help in indirect selection for dry root yield per plant in the crop like ashwagandha where economic part (dry root yield per plant) remain underground up till uprooting.

Open Access Original Research Article

Cryopreservation of Arecanut (Areca catechu L.) Embryogenic Calli by V Cryo-plate Method

Kilingar Subrahmanya Muralikrishna, Kalathil Kundanchery Sajini, Pulikuthi Kavya, Krishna Prakash, Abdulla Abdulla Sabana, Muliyar Krishna Rajesh, Anitha Karun

Current Journal of Applied Science and Technology, Page 76-82
DOI: 10.9734/cjast/2021/v40i2031465

Aims: Arecanut, a perennial palm species of Arecaceae family, has huge commercial value, and is grown mainly for its masticatory nuts. The ever-increasing demand for uniform quality plantlets from growers necessitates putting in place In vitro mass multiplication and other crop improvement programmes. The present study was carried out to standardize the procedure for cryopreservation of embryogenic calli of arecanut, derived from immature inflorescence cultures, by vitrification based cryo-plate technique.

Study Design: Completely randomized design (CRD) with three replications.

Place and Duration of Study: ICAR-Central Plantation Crops Research Institute, Kerala, India during 2019.

Methodology: The embryogenic calli were precultured in Eeuwen's Y3 basal medium supplemented with sucrose (0.2, 0.3 and 0.4 M) for three days. Explants were affixed on cryo-plates and later dehydrated using plant vitrification solution 3 (PVS3) for 30 min. Cryoplates were inserted in cryovials and cryopreserved. Explants with no cryostorage served as control. Explants were rewarmed quickly in a water bath (40ºC) for 2 min and treated with unloading solution and cultured on recovery medium.

Results: The results showed 8-10 % recovery of embryogenic calli that resulted in normal plantlet production. The clonal fidelity studies, using Start Codon Targeted (SCoT) marker, showed no variation of cryopreserved calli in comparison to the original calli.

Conclusion: This preliminary study demonstrated the successful use of vitrification (V) cryo-plate technique in cryopreservation of embryogenic calli of arecanut. With better recovery percentage, the optimal concentration of sucrose in the preculture medium was found to be 0.3 M. Desiccation in PVS3 solution for 30 min had no adverse effect.