GRAY COLOR CONVERSION USING CLASSIFICATION METHOD

There are various methods of gray conversion of RGB color images. They are calculated by three functions, Grayscale function, the Desaturate function, and the value component of the HSV option of the Decompose function. By converting this method we found the gray color image but when trying the reverse it is not same as actual images. That is due to the function that produces same value for different color and when reversing there is conflict between choosing one of them. Here I want to introduce a function using Classification method that produces different values of gray color for a range of RGB color images so the nearly reverse is possible

On certain subclasses of analytic functions associated with the Carlson–Shaffer operator

The object of the present paper is to solve Fekete-Szego problem and determine the sharp upper bound to the second Hankel determinant for a certain class $R^{\lambda}(a,c,A,B)$ of analytic functions in the unit disk. We also investigate several majorization properties for functions belonging to a subclass $\widetilde {R}^{\lambda}(a,c, A,B)$ of $R^{\lambda}(a,c,A,B)$ and related function classes. Relevant connections of the main results obtained here with those given by earlier workers on the subject are pointed out

Assessment of adverse event following immunization and its co-relates among COVID-19 vaccine recipient in Bundelkhand region of Uttar Pradesh: A cross-sectional study

Background: The COVID-19 pandemic is a global emergency. AEFIs reporting and assessment should be done with high priority as they could change the benefit-risk profile of the vaccine. Objective: To assess adverse effects after COVID-19 vaccination. Methods: This cross-sectional study conducted among 605 heath functionaries taken part from January 2021 to March 2021. Results: The most common AEFI reported was pain at injection site (51.9%). Gender, previous COVID status and perception before vaccination were significantly associated with AEFI. Conclusion: There was no serious adverse event after vaccination. COVID vaccine has a good safety profile

Factors associated with low birth weight among deliveries at a tertiary healthcare hospital in Bundelkhand region of Uttar Pradesh

Background: Low birth weight (LBW) is an important factor of infant morbidity and mortality in developing countries. Approximately 20.5 million new-borns, i.e., an estimated 15% of all babies are born with LBW globally. Various factors such as maternal age, education, parity, gestation period, nutritional status and socioeconomic status influence the of birth weight of baby. Objectives of the study to find out the prevalence of LBW babies and their determinants.Methods: This was a hospital based cross-sectional study. The data has been taken from the period of 1st January 2019 to 15th February 2020.Results: 223 mothers and their newborn babies were included in the study. The 55 infants (24.6 %) were LBW (<2500 g) babies. From binary logistic regression analyses of each variable with LBW; gender {0.430 (0.230-0.804), p=0.007}, religion OR={3.477 (1.178-10.264), p=0.018}, education of mother OR={2.051 (1.009- 4.170), p=0.044}, occupation of father OR={1.991 (1.008-3.933), p=0.045}, mode of delivery OR={1.880 (1.004-3.519), p=0.047} and duration of pregnancy OR={6.286 (2.895-13.648), p<0.001} were found to have significant association.Conclusions: The study assessed the variables of LBW in Bundelkhand region of Uttar Pradesh. The study showed that teenage mothers are at a higher risk of having a low-birth-weight baby. It is important to strengthen health education, capacity building, spreading awareness for marriage after twenty along with diagnosing and treating any type of medical or gynaecological conditions resulting premature babies

Chemical composition and antimicrobial activity of the essential oil of Desmostachya bipinnata linn.

The present study describes the phytochemical profile and antibacterial activity of Desmostachya bipinnata. The sample of essential oil was obtained from the aerial parts of the plant by hydrodistillation and analyzed by GC–MS. From the 16 compounds representing 99.97% of the oils: camphene (16.79%), isobornyl acetate (9.92%), tricyclene (4.30%), (+,-) trans-2,6-gamma-Irone (2.21%), Caryophyllene diepoxide (12.29%) , β-eudesmol (11.16%) Eseroline (25.15%) and Calarene (3.48%) appear as the main components. The oil also contained smaller percentages of Diphenyliodinium bromide, 1.limenone, 2-cyclohexene-1-one and 8-nitro-12-tridecanolide. Furthermore, an antibacterial study of the oil was evaluated using agar diffusion and broth dilution methods. The antibacterial studies showed that the oil had significant inhibitory effect against all four bacteria strains included in the study. Results, suggest potential antibacterial activity of the essential oil of Desmostachya bipinnata, which may find its application in future research for the therapy, food and pharmaceutical industry.Keywords: Desmostachya bipinnata, Essential oil, Antimicrobial activity, GC-MS

Multi-Intent Detection in User Provided Annotations for Programming by Examples Systems

In mapping enterprise applications, data mapping remains a fundamental part of integration development, but its time consuming. An increasing number of applications lack naming standards, and nested field structures further add complexity for the integration developers. Once the mapping is done, data transformation is the next challenge for the users since each application expects data to be in a certain format. Also, while building integration flow, developers need to understand the format of the source and target data field and come up with transformation program that can change data from source to target format. The problem of automatic generation of a transformation program through program synthesis paradigm from some specifications has been studied since the early days of Artificial Intelligence (AI). Programming by Example (PBE) is one such kind of technique that targets automatic inferencing of a computer program to accomplish a format or string conversion task from user-provided input and output samples. To learn the correct intent, a diverse set of samples from the user is required. However, there is a possibility that the user fails to provide a diverse set of samples. This can lead to multiple intents or ambiguity in the input and output samples. Hence, PBE systems can get confused in generating the correct intent program. In this paper, we propose a deep neural network based ambiguity prediction model, which analyzes the input-output strings and maps them to a different set of properties responsible for multiple intent. Users can analyze these properties and accordingly can provide new samples or modify existing samples which can help in building a better PBE system for mapping enterprise applications

Design and development of a machine vision system using artificial neural network-based algorithm for automated coal characterization

Coal is heterogeneous in nature, and thus the characterization of coal is essential before its use for a specific purpose. Thus, the current study aims to develop a machine vision system for automated coal characterizations. The model was calibrated using 80 image samples that are captured for different coal samples in different angles. All the images were captured in RGB color space and converted into five other color spaces (HSI, CMYK, Lab, xyz, Gray) for feature extraction. The intensity component image of HSI color space was further transformed into four frequency components (discrete cosine transform, discrete wavelet transform, discrete Fourier transform, and Gabor filter) for the texture features extraction. A total of 280 image features was extracted and optimized using a step-wise linear regression-based algorithm for model development. The datasets of the optimized features were used as an input for the model, and their respective coal characteristics (analyzed in the laboratory) were used as outputs of the model. The R-squared values were found to be 0.89, 0.92, 0.92, and 0.84, respectively, for fixed carbon, ash content, volatile matter, and moisture content. The performance of the proposed artificial neural network model was also compared with the performances of performances of Gaussian process regression, support vector regression, and radial basis neural network models. The study demonstrates the potential of the machine vision system in automated coal characterization

On a Subclass of Analytic Functions Related to a Hyperbola

The object of the present investigation is to solve Fekete-Szegö problem and determine the sharp upper bound to the second Hankel determinant for a new class ℛ̃(a,c,ρ) of analytic functions in the unit disk. We also obtain a sufficient condition for an analytic function to be in this class

A Critical Review on Go-Ghrita, Shata Dhouta Ghrita and Sahasra Dhouta Ghrita

Traditional medical system has always played an important role in the maintenance of health of mankind. Modern medicine has been drawing inputs from these traditional systems since their very beginning. Samskara in Ayurveda, is a process of transformation of inherent attributes of a substance. This is created by dilution, application of heat, cleansing, churning, storing in a specific place, maturing, flavoring, impregnation, preservation, container etc. Ancient scholars considered that Ghrita is able to perform multiple actions if processed accordingly. On the base of this, many Samskaras are employed for Ghrita and subsequently various pharmacological actions are observed. Shatadhouta Ghrita and Sahsradhouta Ghrita are also an outcome of that keen observation. Shatadhouta Ghrita and Sahasradhouta Ghrita are two Ayurvedic preparations, which are prepared by washing cow ghee for hundred and thousand times respectively. They are considered as best alleviators of Pitta Dosha and burning sensation, in the treatments of wound healing. On the basis of detailed literary review, it was understood that, Shatadhouta Ghrita and Sahasradhouta Ghrita should be prepared by pressure washing of Ghrita with water. These preparations are indicated for Dahashamana action. Both of them have the properties as that of oil in water kind of emulsion

PERFORMANCE AND A NEW 2-D ANALYTICAL MODELING OF A DUAL-HALO DUAL-DIELECTRIC TRIPLE-MATERIAL SURROUNDING-GATE-ALL-AROUND (DH-DD-TM-SGAA) MOSFET

This proposed work covers the effect of dual halo structure with dual dielectric. A 2-D analytical model for potential distribution, threshold voltage, electric field and sub-threshold swing has been described through the Poisson’s equation solution for a novel structure known as dual-halo dual-dielectric triple-material surrounding-gate MOSFET to diminish short channel effects. The new device has been incorporated with Dual halo near the source and drain sides, while the electrode at the gate incorporates three dissimilar work function metals. A relative estimation of short channel effects (SCEs) for DHDD-TM-SG, triple-material surrounding-gate (TM-SG) and single-halo triplematerial surrounding-gate (SH-TM-SG) MOSFETs has also been carried out in terms of threshold-voltage-roll-off, drain induced barrier lowering, hot carrier effects, and also sub-threshold swing. The proposed novel structure significantly reduces the SCEs. Therefore, DH-DD-TM-SG MOSFETs have superior performance than TM-SG and SH-TM-SG MOSFETs. The efficiency of the Dual halo-doped device is investigated. The proposed model demonstrates its validity by a comparing the simulated results from already published devices obtained by using TCAD Silvaco