Hybrid Approach to English-Hindi Name Entity Transliteration

Machine translation (MT) research in Indian languages is still in its infancy. Not much work has been done in proper transliteration of name entities in this domain. In this paper we address this issue. We have used English-Hindi language pair for our experiments and have used a hybrid approach. At first we have processed English words using a rule based approach which extracts individual phonemes from the words and then we have applied statistical approach which converts the English into its equivalent Hindi phoneme and in turn the corresponding Hindi word. Through this approach we have attained 83.40% accuracy.Comment: Proceedings of IEEE Students' Conference on Electrical, Electronics and Computer Sciences 201

Detection of Brain Tumor in MRI Image through Fuzzy-Based Approach

The process of accurate detection of edges of MRI images of a brain is always a challenging but interesting problem. Accurate detection is very important and critical for the generation of correct diagnosis. The major problem that comes across while analyzing MRI images of a brain is inaccurate data. The process of segmentation of brain MRI image involves the problem of searching anatomical regions of interest, which can help radiologists to extract shapes, appearance, and other structural features for diagnosis of diseases or treatment evaluation. The brain image segmentation is composed of many stages. During the last few years, preprocessing algorithms, techniques, and operators have emerged as a powerful tool for efficient extraction of regions of interest, performing basic algebraic operations on images, enhancing specific image features, and reducing data on both resolution and brightness. Edge detection is one of the techniques of image segmentation. Here from image segmentation, tumor is located. Finally, we try to retrieve tumor from MRI image of a brain in the form of edge more accurately and efficiently, by enhancing the performance of diffe rent kinds of edge detectors using fuzzy approach

Classifier-Based Text Simplification for Improved Machine Translation

Machine Translation is one of the research fields of Computational Linguistics. The objective of many MT Researchers is to develop an MT System that produce good quality and high accuracy output translations and which also covers maximum language pairs. As internet and Globalization is increasing day by day, we need a way that improves the quality of translation. For this reason, we have developed a Classifier based Text Simplification Model for English-Hindi Machine Translation Systems. We have used support vector machines and Na\"ive Bayes Classifier to develop this model. We have also evaluated the performance of these classifiers.Comment: In Proceedings of International Conference on Advances in Computer Engineering and Applications 201

Experiential versus Traditional Pedagogy: A study of primary school in Delhi NCR

The Indian education system has been struggling with forming a foundational sense of numeracy among children. The draft of the Indian National Education Policy (NEP) that was released in early June 2019 makes a very clear statement about the "severe learning crisis." The long policy document states that there are a significant number of children in elementary school who don't have the basic reading and math skills and recommends a "pedagogical shift" to change this. Therefore, the research will focus on understanding whether a pedagogical shift from traditional pedagogy to experiential pedagogy will lead to better learning outcomes among primary school students. Using a pre- and post-test, we divided forty students (n = 40) from grade one into two groups. The first group experienced traditional pedagogy, while the second group experienced experiential pedagogy. Using SPSS 19, a t-test was administered. The result indicates students in experiential learning have better pre-test scores than students in traditional learning. The outcome stipulates that experiential learning provides holistic learning with better understanding that students can connect to their live

Social empowerment through green fashion

https://kent-islandora.s3.us-east-2.amazonaws.com/node/12113/77225-thumbnail.jpgClothes reflect the personality of individuals and can be used as an identity of a group, community, family, region and even country. Khadi is one such cloth that had played a key role in the freedom struggle of India and thus, has been referred to as the \u27Fabric of Indian Independence\u27. Khadi fabric has historical significance for bringing about extensive rural empowerment. Khadi has become the invaluable asset of heritage providing respectable means of livelihood to huge human resource especially rural women. In this paper an attempt is made to focus on various environment friendly methods and processes involved in the manufacturing, production and other developments taking place in khadi fabric. Purposive sampling technique was used for collecting the data. Semi-structured interview and observation techniques were used for data collection. Detailed information about raw material manufacturing processes, utilization of energy and water during manufacturing of cotton khadi from yarn to fabric was sought. Information was obtained with respect to waste management, by-products of the manufacturing process, nature of air pollutants and toxic substances if any produced during manufacturing process. Results of the study confirms that khadi is handspun and handwoven in the natural environment using natural fibers and it is considered 100% natural. It does not rely on electric units and the manufacturing processes do not generate toxic waste products. Production of khadi consumes less water and energy as compared to water and energy consumed in a conventional textile mill. In the rural India khadi production meets the twin objectives of green production and employment creation. Total employment in khadi sector during 2018-19 has registered at 5 lakh persons.</p

Sovereign ratings: Determinants and policy implications for India

This paper studies sovereign rating models of Moody's, Standard & Poor's (S&P) and Fitch to identify important determinants of sovereign ratings. Ordered logit and probit are employed to check for robustness of empirical results. We found that Moody's model is most reliable (it has the highest rate of correct predictions for sample countries). Further, the sovereign ratings are robust to the choice of estimation procedures. Economic strength, inflation and governance indicators are found to be important determinants of sovereign ratings followed by fiscal strength, domestic political risk and size of banking system. The paper provides key policy suggestions for India to improve its ratings. Keywords: Sovereign ratings, Credit rating agencies, Factor analysis, Ordered logit and probit, Economic factors, Governance indicator

Development of Field Deployable Sensor for Detection of Pesticide From Food Chain

The use of pesticides in agriculture field remains a serious issue related to public health. This necessitates the need to develop a low cost/portable, sensitive and selective bio-sensing platform for detection of pesticides in food chain. In this work a low-cost biosensing platform for ultrasensitive detection of chlorpyrifos (CPF) is developed. Electrochemical micro Paper Analytical Device (ElPAD) is fabricated by conventional screen-printing technology. Metal Organic Framework (Z1200 MOF) having zinc metal and imidazole ligand is used as a transducing element which facilitates biocompatible matrix for Acetylcholinesterase (AChE) enzyme immobilization. The limit of detection for CPF is found be 3 ng/L with sensitivity 0.521 kY/ng L-1/mm2. The sensor required 100lL of reagent and was tested with a linear concentration range of 10 ng/L to 1000 ng/L with response time of 5s. The sensor is further integrated with portable electronics based on Arduino microcontroller and Artificial Intelligence (AI) which provided economical, portable and user-friendly sensing platform. The stability of the sensor was 30 days. The developed sensor was also tested with real samples and the sensor response is in agreement with conventional technique

A Novel Phenanthridionone Based Scaffold As a Potential Inhibitor of the BRD2 Bromodomain: Crystal Structure of the Complex

<div><p>Bromodomain containing proteins recognize the level of histone acetylation and regulate epigenetically controlled processes like gene transcription and chromatin modification. The BET (<u>b</u>romodomain and <u>e</u>xtra-<u>t</u>erminal) family proteins, which are transcriptional co-regulators, have been implicated in the pathogenesis of cancer, neurodegenerative disorders, and defects in embryonic stem cell differentiation. Inhibitors selectively targeting the BET bromodomains can pave the path for new drug discovery against several forms of major diseases. By a rational structure-based approach, we have identified a new inhibitor (NSC127133) of the second bromodomain (BD2) of the BET family protein BRD2 using the NCI Diversity Set III library. A high-resolution crystal structure of the BRD2-BD2 in complex with this compound and in <i>apo</i>- form is refined to 0.91 and 0.94 Å, respectively. The compound, which is a phenanthridinone derivative, binds well to the acetyl-lysine binding pocket of BD2 and displays significant hydrophobic and hydrophilic interactions. Moreover, the atomic resolution data obtained in this study allowed us to visualize certain structural features of BD2 which remained unobserved so far. We propose that the discovered compound may be a potential molecule to develop a new library for inhibiting the BRD2-BD2 function.</p></div

Insights into the crystal structure of BRD2-BD2 – phenanthridinone complex and theoretical studies on phenanthridinone analogs

<p>Bromodomain and extra-terminal family proteins recognize the acetylated histone code on chromatin and participate in downstream processes like DNA replication, modification, and repair. As part of epigenetic approaches, BRD2 and BRD4 were identified as putative targets, for the management of chronic diseases. We have recently reported the discovery of a new scaffold of the phenanthridinone-based inhibitor (L10) of the second bromodomain of BRD2 (BRD2-BD2). Here, we present the crystal structure of the BRD2-BD2, refined to 1.4 Å resolution, in complex with β-mercaptoethanol (a component of the protein buffer). The β-mercaptoethanol covalently links to C425 of BD2 in the acetyl-lysine binding pocket, to form a modified cysteine mercaptoethanol (CME). The CME modification significantly hinders the entry of ligands into the BD2 binding pocket, suggesting that β-mercaptoethanol should be removed during protein production process. Next, to confirm whether phenanthridionone scaffold is a new inhibitor family of BRD2-BD2, we have determined the crystal structure of BD2 in complex with 6(5H)-Phenanthridinone (a core moiety of L10), refined to 1.28 Å resolution. It confirmed that the phenanthridinone molecule, unambiguously, binds to BD2. Moreover, we performed molecular docking and molecular dynamic studies on selected phenanthridinone analogs. The predicted L10 analogs are stable with essential hydrophobic and hydrophilic interactions with BD2 during molecular dynamic simulations. We propose that the predicted phenanthridinone analogs may be potential molecules for inhibiting the BD2 function of acetylated histone recognition.</p

Data reduction and refinement statistics of the <i>apo-</i>form of BRD2-BD2 and <i>BD2-L10</i> structures.

<p>Data reduction and refinement statistics of the <i>apo-</i>form of BRD2-BD2 and <i>BD2-L10</i> structures.</p