Browsing by Author "Chaudhary, Ramesh Kumar"

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    Cultural hybridity in Pawal Cowan’s an Orphanin history
    (2016) Chaudhary, Ramesh Kumar; Raj Kumar Baral
    Available in fulltext
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    Use of Drinking Water and its Impacts on the Health of Students
    (Faculty of Health Education, 2017) Chaudhary, Ramesh Kumar
    This thesis is entitled "Use of Drinking Water and its Impacts on the health of Students". The objectives of this study were to find out the condition of drinking water in community schools and to find out the impacts of drinking water on on health of the students of community schools. The research design adopted for the present study was descriptive design. Pakali HSS and Bha.Si. HSS School were selected by the purposive sampling method. The total students of Pakali HSS were 964 and Bha.Si. HSS were 526 and 165 students from Pakali HSS and 85 students from Bha.Si. HSS from the secondary level were selected by the purposive sampling method as the respondents. The questionnaire and observation checklist were tools to collect data in schools. The main source of drinking water of 91.6 percent respondents was tubewell, 3.6 percent respondents was tap and 4.8 percent respondents was others. Maximum respondents (96.8 percent) replied that polluted water causes communicable diseases and 3.2 percent doesn't. Cent percent respondents washed their water pot daily. Eighteight percent respondents used some methods to purify drinking water, out of them 61.82 percent used filtering, 34.54 percent boiling, 1.82 percent chemical and 1.82 percent used other methods. 54 percent respondents replied that arsenic of source of drinking water of the schools had been tested and 46 percent replied it had not been. Fourtyeight percent respondents replied that drinking water of the schools has smell and 52 percent replied it did not. Fiftythree point six percent respondents replied that orientation programs of drinking water were conducted and 46.4 percent replied were not. 16.8 percent respondents used tanks, 7.2 percent used jars, 62.4 percent used jugs and 13.6 percent used other things for storing drinking water. After using toilet 1.2 percent respondents used only water, 96.8 percent used water and soap, 1.6 percent used water and kharani and 0.4 percent used other things. Most of the respondents (99.2 percent) replied that they washed hands before eating food and 0.8 percent did not wash. In conclusion, more respondents had positive thinking about drinking water and they did hygienic health practice. Some respondents had felt problem in drinking water of community schools.
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    Valorization of Native American Cultural Uniqueness in Erdrich's The Porcupine Year
    (Department of English, 2016) Chaudhary, Ramesh Kumar
    The present thesis entitled "Valorization of Native American Cultural Uniqueness in Louise Erdrich's The Porcupine Year" invites readers to understand Native American culture and tradition. In order to unearth the issue, the researcher brings forth the various cultural practices that help to prove the Native American cultural uniqueness. Besides, the researcher presents the representation of Native American people and their culture referring various scholars on Native American life. Oral traditions, myth making, traditional healing and curing, spirituality, religious supremacy, hunting and fishing are some of the characteristics features of Native American culture and tradition which have been valorized as distinct and unique among Native American society. Moreover, the culture is the only thing that establishes each native with distinct rubric called Native Americans. Besides, this research attempts to foreground the distinct rituals and traditions of Native Americans which have been made subversive in the past.
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    Word Embedding Based Feature Extraction for Nepali News Classification
    (Department of Computer Science and Information Technology, 2019) Chaudhary, Ramesh Kumar
    A major challenge in topic classification (TC) is the high dimensionality of the feature space. Therefore, feature extraction (FE) plays a vital role in topic classification in particular and text mining in general. FE based on cosine similarity score is commonly used to reduce the dimensionality of datasets with tens or hundreds of thousands of features, which can be impossible to process further. In this study, TF-IDF (Term Frequency Inverse Document Frequency) term weighting is used to extract features. Selecting relevant features and determining how to encode them for a learning machine method have a vast impact on the learning machine methods ability to extract a good model. Count based feature extraction methods is compared with word to vector feature extraction techniques for Nepali news classification. The results show good classification performance when using the feature extraction techniques based on word to vector for less number of classes and drastically decrease the performance for large sample size. On the other hand result of classification count based technique shows consistent nearly performance for any number of classes. The overall performance of the TF-IDF (Term Frequency Inverse Document Frequency) is far better than both word to vector techniques.