Informatics Publishing Limited

Mahesh Goel ¹, S. C. Anand ², Virendera Singh ², Ajay Verma ², Naresh Sharma ²

Affiliations
1 Department of Oral and Maxillofacial Surgery Postgraduate Institute of Dental Sciences Rohtak - 124001 (Haryana), IN
2 Department of Oral and Maxillofacial Surgery Postgraduate Institute of Dental Sciences Rohtak - 124001 (Haryana), IN

Abstract

Aim: The aim of this study was to portray lag screw and position screw utility and accuracy in various situations in bony fractures, osteotomy fragments, placement of costochondral and sternoclavicular split grafts and also in reconstruction with bone grafts. Material and Methods: This prospective study includes 30 numbers of patients of mandibular fractures, jaw deformity and TMJ ankylosis. All cases were treated by using lag screws except in two cases in which positional screws were used to stabilize osteotomized fragments. These cases were selected randomly from patients attending the outdoor patient department of oral and maxillofacial surgery at PGIDS, Rohtak, irrespective of age, sex and caste and socioeconomic status. Results: This study comprised 30 numbers of cases which were evaluated clinically as well as radiologically. The measured parameters were further analyzed statistically. The number of cases and its distribution shows that major part of the use of lag screws were in the body of mandibular fracture which are 10 out of 30 while the immobilization of CCG/ SCG are eleven in number. It was observed that use of lag screw with definite protocol give the maximum compressive osteosynthesis. In spite of careful use of the laid down technique the complication of various types were encountered. Conclusion: It is apparent that a lag screw osteosynthesis with its ability of compression is a versatile internal rigid fixation and can be utilized in various surgical procedures for fixation of bony fragments. It is extremely technique sensitive procedure in spite of minimal requirement of armamentarium.

Keywords

Lag and Position Screw, Internal Fixation, Osteosynthesis

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Ajay Verma ¹, Prabhat Kumar Guru ², Mukesh Kumar Pandey ¹

Affiliations
1 Indira Gandhi Krishi Vishwavidyalaya, Raipur, Chhattisgarh, IN
2 National Academy of Agricultural Research Management, Rajendranagar, Hyderabad, A.P., IN

Abstract

Every day, millions of agricultural workers are exposed to noise at work and all the risks this can entail. The World Health Organization (WHO) states "noise-induced hearing loss is insidious, permanent and irreparable". By using power tiller, more than the permissible exposure limit to noise may cause serious health problems to the agricultural workers. This paper examines the noise propagation of popular and most commonly used power tillers having a power rating of 11kW, 9.5kW and 4.4 kW. It was observed that all three power tillers produced the noise above 93 dB(A) in the working zone of the operator. The density of noise contour and SPL is proportional to the engine rpm or load. The working radius around PT-I, PT-II and PT-III of 3.5 m, 2 m and 5.6 m was found noisy [>90 dB(A)] and not suitable to work 8 h per day as per recommendation of ISO and OSHA. The permissible duration of exposure to noise for operator for PT-I, PT-II and PT-III varies from 7.8 h to 3.6 h, 13 h to 5.1 h and 5.3h to 2.1h, respectively for different engine rpm.

Keywords

Noise Propagation, Power Tiller, Noise Contours, Agricultural Workers.

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Parmanand ¹, Ajay Verma ², P. D. Verma ¹, Prabhat Kumar Guru ³

Affiliations
1 Krishi Vigyan Kendra, Bhatapara (C.G.), IN
2 Department of Farm Machinery and Power Engineering, Indira Gandhi Krishi Vishwavidyalaya, Raipur (C.G.), IN
3 Division of Crop Production, ICAR-Central Rice Research Institute, Cuttack (Odisha), IN

Abstract

This paper deals with the development of a pedal operated millet thresher. Millet is one of the oldest human foods and believed to be the first domesticated cereal grain. Millets are important food for sustaining tribal population in Bastar region of Chhattisgarh. Available evidence suggests that the mode of threshing finger millet is by traditional method like beating with sticks, rubbing and trampling finger-heads under bullocks feet or men feet. Traditional method is time wasting, energy sapping and often the grains are broken. Pedal operation is the most efficient way of utilizing power from human muscles. Keeping this thing in mind, pedal operated thresher for minor millets with spike-tooth type threshing cylinder was designed, fabricated and tested. This machine basically consists of four major components: feeding, threshing (consisting of threshing cylinder, concave and cylinder casing), cleaning and power transmission mechanism. The developed millet thresher has the ability to winnow the premature grains and leaves, which are often lighter, thus, leaving aside the massy grains that, will be collected. It is beneficial for farmers with reduced time of operation, reduction in breakage of the grains and separation of the stalk from the grains. The machine is economically viable can be used by farmers easily.

Keywords

Finger Millet Thresher, Spike-Tooth Type Threshing Cylinder, Pedal Operated Thresher.

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Ratna Sanyal ¹, Dhwaj Raj ¹, Divanshu Kumar Gupta ¹, Ajay Verma ¹

Affiliations
1 Indian Institute of Information Technology, Allahabad, Deoghat, Jhalwa, Allahabad – 211 012, Uttar Pradesh, IN

Abstract

This paper describes the Digital Library Workflow and Repository Management system (DLworm) to manage the repositories and to automate the workflow for digital library at any institution/organization. After a detailed and comprehensive analysis of the steps involved in maintaining a digital library system, a concrete model has been developed and tested. DLworm supports most of the functionalities required for such a large repository. DLworm is intended to formulate a fault tolerant system providing integrated environment for all users involved in the processes of maintaining and accessing a digital library. DLworm is a flexible and extensible system supporting phonetic matching for search queries. DLworm uses a three level hierarchy for maintaining the data in the repositories. We describe briefly the architecture that is robust and fulfils the demand for long term preservation of digital data. This article illustrates mechanisms for process management that makes DLworm highly efficient and user friendly.

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Preeti Trivedi ¹, Ajay Verma ²

Affiliations
1 G.S. Institute of Technology and Science, Indore, M.P., IN
2 Department of Electronics and Instrumentation, IET, DAVV, Indore, M.P., IN

Abstract

A software defined radio adopts a fully reconfigurable front end and is believed to be the right answer to realize 3G/4G mobile systems. This paper will give a review of different   ADC architecture used in SDR mobile receiver with different parameter of ADC. In an ideal software radio, the data conversion    process   occurs   immediately   after the antenna in the receiver chain. This paper also presents a multi-standard reconfigurable   modulator, which are able to support the predictable standards of fourth generation of mobile communication systems (4G). The down conversion process is entirely in the digital domain. The proper selection of data converters, both analog to digital converters and digital to analog converters (DACs) is one of the most challenging steps in designing software radio. Different types of ADCs are discussed here.

Keywords

Analog to Digital Converter (ADC), Intermediate Frequency (IF),Software Defined Radio (SDR), SNR, Radio Frequency (RF).

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Ajay Verma ¹, V. Kumar ¹, A. S. Kharab ¹, G. P. Singh ¹

Affiliations
1 Statistics and Computer Center, ICAR-Indian Institute of Wheat and Barley Research, Karnal (Haryana), IN

Abstract

The present study was carried out to identify malt barley genotypes with high yield and stability across eight different environments, using non-parametric statistical measures. Descriptive statistics MR, SD and CV identified DWRB147, DWRB150 and RD2943 stable genotypes. BH902 and PL890 were identified as unstable genotypes by CMR CSD and CCV. Non-parametric measures selected DWRB147 and DWRB150 as the stable genotypes and BH902 and PL890 unstable genotypes. Significant tests for S_i ¹ and S_i ² were based on sum of Z_i ¹ and Z_i ² measures and sum of Z_i ¹ was greater than critical value confirmed significant differences among the twenty genotypes. Results of the NP_i ², NP_i ³ and NP_i ⁴were similar for unstable performance of BH902, DWRB150 and DWRB147. Biplot analysis of PCA1 and PCA2 accounting for 70.08 per cent showed three distinguish groups among non-parametric measures. Clustering by Ward’s hierarchical method expressed four clusters by using the squared Euclidean distance as dissimilarity measure.

Keywords

Non-Parametric Measurements, Rank Correlation, Biplot Analysis, Hierarchical Clustering.

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Ajay Verma ¹, V. Kumar ¹, A. S. Kharab ¹, G. P. Singh ¹

Affiliations
1 Statistics and Computer Center, ICAR- Indian Institute of Wheat and Barley Research, Karnal (Haryana), IN

Abstract

Genotypes G5, G8, G3, G21 and G18 had achieved higher yields besides b_i > 1.0. G21 and G3 identified as appropriate one, because had higher yield value than the mean, bi values near 1.0 and low S²_di. Lower values (W²_i) resulted for G12, G5, G2, G21 while higher for G5, G3 and G14. Genotypes G12 followed by G2, G20, and G7 had the smallest environmental variance (S²_xi). Smaller values of (CV_i) considered G12, G2, G20, and G10 of stable performance. α² _i measure pointed out G12, G7 and G2 with smallest values. Desirable lower P_i values reflected by G18, G5, G21, and G4 while GAI values identified G18, G11, G4 G10 as desirable genotypes. S_i ⁽¹⁾ and S_i⁽²⁾ showed lower values of G12, G2 and G7 genotypes. Significant tests of S_i ⁽¹⁾ and S_i⁽²⁾ proved the highly significant difference in ranks among the 21 genotypes grown in 8 environments. Genotypes G12, G2, and G7 had the lower S_i⁽³⁾ and S_i⁽⁶⁾ values. Yield of genotypes had significant negative correlation with bi, S_i⁽²⁾, S_i⁽³⁾, S_i⁽⁶⁾, NP_i ⁽²⁾, NP_i⁽³⁾, NP_i⁽⁴⁾ and significant positive correlation with GAI, P_i and Rank Sum. Hierarchical cluster analysis classified genotypes into three clusters as largest cluster included genotypes with more than average yield along with high yielders G18, G11, G3, G5, G21 and unstable performance indicated by non parametric measures. Biplot analysis while considering first two significant principal components grouped the parametric and non parametric measures into four groups. The smaller group consisted of b_i and S² _di and adjacent to group of non parametric measures S_i⁽²⁾, S_i⁽⁶⁾, NP_i⁽²⁾, NP_i⁽³⁾ and NP_i⁽⁴⁾.

Keywords

Barley, Parametric, Non-Parametric Measures, Biplot Analysis, Hierarchical Clustering.

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Ajay Verma ¹, G. P. Singh ¹

Affiliations
1 ICAR-Indian Institute of Wheat and Barley Research, Karnal (Haryana), IN

Abstract

Rank based measures of stability had been compared for wheat genotypes evualated in Central Zone of the country as per the BLUP and BLUE of yield values. Measures based on ranks of BLUP of original yield for 2016-17, S_i^s measures identified G3, G7, G4 as stable genotypes. Corrected yield measures CS_i^s selected G4, G7, G3 for stable performance. Values of NP_i^(s) identified G1, G6 as of undesirable types. Association analysis observed positive correlations of S_i^s, with others and themselves. Positive relationships also exhibited by CS_i^s and NP_i^(s) values to other measures. Biplot analysis exhibited cluster of S_i⁶ , S_i³ , CV, NP_i⁽²⁾, NP_i⁽³⁾, NP_i⁽⁴⁾ and CS_i⁷. Larger cluster comprised of NP_i⁽¹⁾ CCV, CSD S_i¹, S_i², S_i⁴, S_i ⁵, S_i⁷ , CS_i ¹, CS_i², CS_i ³, CS_i ⁴, CS_i ⁵, CS_i⁶ measures. Based on BLUE’s of genotypes yield, measures S_is found G3, G7, G4 as the stable genotypes, however G1, G2 would express unstable performance. CS_i^s identified G7, G3, G6 as opposed to G3, G5, G7 genotypes as by values NP_i^(s). Positive correlations exhibited by S_isexcept of negative with CMR, CMed, Z1 and Z2 values. Ranks of genotypes as per values of CS_i^s and NP_i^(s) measures expressed direct relationship with most of the measures. Biplot analysis observed large cluster comprised of CCV, CSD, NP_i⁽¹⁾, S_i¹, S_i², S_i⁴,CS_i¹, CS_i², CS_i ³, CS_i⁴, CS_i⁵, CS_i⁶, CS_i⁷ measures. Second year of study (2017-18) as per BLUP’s seen, S_i^s settled for G6, G5, G3 genotypes. While NP_i^(s) settled for G6, G3,G5 as genotypes of stable performance. Highly significant negative correlation of yield observed with most of the measures MR, CV, Med, S_i³, S_i⁶ ,CMR,NP_i⁽²⁾, NP_i⁽³⁾, NP_i⁽⁴⁾. Biplot analysis as per first two significant components (accounted for 88.7 %) marked larger cluster contains CS_i^s with NP_i⁽¹⁾, S_i¹, S_i2 S_i⁴, S_i5 S_i⁷ ,SD, CSD measures. S_is rank based measures as per BLUE’s of genotypes pointed towards G5,G4, G6, G1 whereas G6, G5, G1,G3 by CS_i^s values. Wheat genotypes G1,G2, G3,G5 settled by least values of NP_i^(s) . Direct relationships portraited by S_i^s, CS_i^s and NP_i^(s) with others. Larger cluster grouped NP_i^(s), CV, CCV, Z1, Z2, Yield, GAI, CS_i⁵, CS_i6 measures.

Keywords

Blup, Blue, S_i^(s), CS_i ^(s), NP_i^(s), Co-efficient Of Concordance, Biplot Analysis.

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Ajay Verma ¹, Manisha Jain ¹, Vinod Bhatt ²

Affiliations
1 Division of Mathematics (SASL), VIT Bhopal University, Kothrikalan, Sehore, M. P., IN
2 Division of Languages (SASL), VIT Bhopal University, Kothrikalan, Sehore, M. P., IN

Abstract

This paper offers a picture of disability based on census 2011, India. As per Census 2011 India, We examine the impact of demographic factors on attitudes towards students with disabilities versus non-disabled students in government and private Technical and non-technical educational institutions in India. Andrew Fisher's formula is used to determine the sample size for our investigation. Hypothesis testing has been done by using a t-test and chi-square test for comparison between the variables. Descriptive statistics are used to represent the graphical representation of the data set. This study will be helpful to know the mind-set of disabled v/s no- disabled students. At the end of the study, results were discussed with the help of graphs and tables by using Statistical Package for the Social Sciences (SPSS) and Microsoft excel.

Keywords

Disability, Behaviour, Demographic Data, Educational Level.

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