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Conditioning And Preconditioning Of The Model Error Formulation:  (P)

*Dr. Rajeev Kumar and **Gurpreet Kaur

*Assistant Professor, Department of Mathematics, OPJS University, Churu, Rajasthan (India)

**Research Scholar, Department of Mathematics, OPJS University, Churu, Rajasthan (India)

Email: shargun500@gmail.com; Contact No. +91-9996347359

Abstract: The theorems in this section extend the work of Haben et al. [41] on the condition number of the standard 3DVAR and 4DVAR systems. We briefly discussed and compared J (p) to the conventional sc4DVAR approach (2.8) in Section 5.1.2 using the lower and upper bounds derived in [41] and the bounds we have derived in Theorem 5.1.2. In sc4DVAR, ^S is the only error variance ratio, which means if the observations are accurate and/or the background error variance is large then the condition number of the of Hessian of the sc4DVAR problem would rise. The assumptions become more specific with each theorem. The first theorem assumes general correlation structures for the background, observation and model errors while assuming there are fewer observations than the dimension of state space. The second theorem derives bounds that are more specific to a particular class of covariance and model matrices, whereas the final theorem is specific to the advection equation. We then take the preconditioned Hessian of objective function J (p) and bound its condition number. We then show the improvement in overall conditioning and minimisation iteration rates of the preconditioned problem compared to the original problem.

[Kumar, R. and Kaur, G. Conditioning And Preconditioning Of The Model Error Formulation:  (P). Rep Opinion 2020;12(3):1-4]. ISSN 1553-9873 (print); ISSN 2375-7205 (online). http://www.sciencepub.net/report. 1. doi:10.7537/marsroj120320.01.

Keywords: Solution, Prediction, Assumption

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COVID-19 Research Literatures

Mark Herbert

World Development Institute

39-06 Main Street, Flushing, Queens, New York 1354, USA, ma708090@gmail.com

Abstract: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus is mainly spread during close contact and via respiratory droplets that are produced when a person talks, coughs, or sneezes. Respiratory droplets may be produced during breathing, however, current research indicates that the virus is not considered airborne. People may also contract COVID-19 by touching a contaminated surface (Fomite) and then inadvertently transfer the pathogen to a mucous membrane (such as the eyes, nose, or mouth). It is most contagious when people are symptomatic, although spread may be possible before symptoms appear. The virus can live on surfaces up to 72 hours. Time from exposure to onset of symptoms is generally between two and fourteen days, with an average of five days. The standard method of diagnosis is by reverse transcription polymerase chain reaction (rRT-PCR) from a nasopharyngeal swab. The infection can also be diagnosed from a combination of symptoms, risk factors and a chest CT scan showing features of pneumonia. This article introduces recent research reports as references in the related studies.

[Mark Herbert. COVID-19 Research Literatures. Rep Opinion 2020;12(3):5-73]. ISSN 1553-9873 (print); ISSN 2375-7205 (online). http://www.sciencepub.net/report. 2. doi:10.7537/marsroj120320.02.

Key words: Coronavirus disease 2019 (COVID-19); life; research; literature

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Study On The Parameters Related To The Interactive Intent Estimation Model

*Prof. Rajeev Yadav and **Mrs. Kanta

* Professor, Department of Computer Science, OPJS University, Churu, Rajasthan (India)

**Research Scholar, Department of Computer Science, OPJS University, Churu, Rajasthan (India)

Email: kkantarana@gmail.com

Abstract: The user relevance-feedback (URF) is imposed in the system via labeling the result objects with positive or negative intent. The award or penalty is incorporated into the system as URF and supplied to 'Current Intent Estimation' module. Similarly, pseudo relevance feedback (PRF) identifies top-k result objects from each window in top-n and retains them in next/future iterations. This module estimates the relevance estimate for the 'In-search' context, and also evaluates the implicit co-relations with 'Pre-search' context. The co-relations are employed to predict the futuristic data objects. The proposed system 'IIM', adapted query terms proximities and notions of relevance-feedback to emphasis the significance of the diverse context of user search into retrieval framework and eventually steered the implicit data exploration. An ideal exploratory search system accommodates implicit and explicit relevance measures for the proactive search intent estimation. Hence, the proposed framework steers both key drivers of exploratory information-seeking, i.e. focused-search based on DT and QT measures and exploratory-browsing based on URF and PRF, eventually to support the user-centric information-seeking. In YmalDB and uRank employed PRF based intent estimation on automatic clustered data objects, AIDE apply URF based object classification to model data retrieval strategy. The Intent Radar adapts URF to model the revised intent and PRF, though primarily rely on the 'Pre-search' based intent. A brief comparison among the counterparts and the proposed system is presented in Table 1.1, along with information-seeking parameters. The summary of visual features, e.g., Visual Accomplishment and Visual Implications, to assist the user information-seeking on the proposed system and other four ESS is given in Annexure-D. The assessment of the designed system 'IIM', equivalent ES systems are employed system and presented in the next research, on the predefined potential search trails.

[Yadav, R. and Kanta. Study On The Parameters Related To The Interactive Intent Estimation Model. Rep Opinion 2020;12(3):74-83]. ISSN 1553-9873 (print); ISSN 2375-7205 (online). http://www.sciencepub.net/report. 3. doi:10.7537/marsroj120320.03.

Keywords: interactive, intent, estimation, model

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Reliability and validity of The MATRICS Consensus Cognitive Battery (MCCB): A systematic review

Tingting Li, Huilan Xu, Wei Liu

Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha Hunan, China, 410078

Abstract: This paper summarized and analyzed domestic and foreign literatures related to the reliability and validity of The MATRICS Consensus Cognitive Battery published in the past to provide a basis for better use of this tool.

[Tingting Li, Huilan Xu, Wei Liu. Reliability and validity of The MATRICS Consensus Cognitive Battery (MCCB): A systematic review. Rep Opinion 2020;12(3):84-88]. ISSN 1553-9873 (print); ISSN 2375-7205 (online). http://www.sciencepub.net/report. 4. doi:10.7537/marsroj120320.04.

Key words：MATRICS Consensus Cognitive Battery; Reliability; Validity; Cognitive; Psychopath

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Solution Pattern Of Almost Λ-Statistical Convergence And Its Application

*Dr. Rajeev Kumar and **Neeru Gupta

*Assistant Professor, Department of Mathematics, OPJS University, Churu, Rajasthan (India)

**Research Scholar, Department of Mathematics, OPJS University, Churu, Rajasthan (India)

Contact No. +91-9468317544; Email: godugupta@gmail.com

Abstract: In this paper we study one more extension of the concept of statistical convergence namely almost λ-statistical convergence. In section 1.2 we discuss some inclusion relations between almost λ-statistical convergence, strong almost (V,λ)-summability and strong almost convergence. Further in section 1.3 we study the necessary and sufficient condition for an almost statistically convergent sequence to be almost λ-statistically convergent. Let s be the set of all real or complex sequences and let l_∞, c and c₀ denote the Banach spaces of bounded, convergent and null sequences x = {ξ_k} respectively normed by ||x|| = |ξ_k|. Suppose D is the shift operator on i.e. D ({ξ_k}) = {ξ_k+1}.

[Kumar, R. and Gupta, N. Solution Pattern Of Almost Λ-Statistical Convergence And Its Application. Rep Opinion 2020;12(3):89-93]. ISSN 1553-9873 (print); ISSN 2375-7205 (online). http://www.sciencepub.net/report. 5. doi:10.7537/marsroj120320.05.

Keywords: Solution, Pattern, Λ-Statistical, Convergence

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Review Of Literature Of Knnya Gurukula On Women Education In Haryana (India)

Dr. Jayveer Singh and Mrs. Sumita

*Associate Professor, Department of History, OPJS University, Churu, Rajasthan (India)

**Research Scholar, Department of History, OPJS University, Churu, Rajasthan (India)

e-mail: drravinder2013@gmail.com

Abstract: It is extremely important part of any research as it shows what other researchers have already done and what other investigators are doing contemporarily. In other words, it basically helps the investigators to find various research gaps. It provides insight to investigate about use of methodology. Thus, it provides a critical review and appraisal of the related studies and shows how the related studies contribute towards advancing the present knowledge regarding the specific area under investigation. In order to critically understand and examine the area of research, the investigator went through the available published and unpublished thesis, research reports, text books & conceptual papers, and several other related literatures on women’s education, which provided a clearer insight into the problems and direction for an appropriate methodology. The investigator has examined different literature from books, thesis, research works and survey reports.

[Singh, J. and Sumita. Review Of Literature Of Knnya Gurukula On Women Education In Haryana (India). Rep Opinion 2020;12(3):94-98]. ISSN 1553-9873 (print); ISSN 2375-7205 (online). http://www.sciencepub.net/report. 6. doi:10.7537/marsroj120320.06.

Keywords: Review, Literature, Kanya, Gurukul, Haryana, India

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The Trinity Of Nature, Man And God In Poetry Of Rabindranath Tagore

*Dr. Nitendra Singh and ** Sakshi Antil

*Associate Professor, Department of English, OPJS University, Churu, Rajasthan (India)

**Research Scholar, Department of English, OPJS University, Churu, Rajasthan (India)

Email: sakshi.dipsight@gmail.com

Abstract: Tagore's poems on God, Nature, and Man are bound together by the individual chord of love and by Tagore's 'Vedantic Advaita'. The three major themes can be fruitfully termed Godscape, Naturescape and Manscape and their common bond as Lovescape. The poems making the bed-rock of Tagore's thoughts, feelings and visionary concepts not only teach humankind to live in harmony fulfilling God's purpose in creating the universe, Nature, and Man, but also reveal that every atom of this cosmos is His manifestation. The overall message is that man should have a compassionate heart and serving hands, to know His presence in all the objects of nature and in all human beings. Love for God, for Nature, and for Man is the towering theme of Tagore's poetry. He has sung in praise of God and Love; and he has vouchsafed that life and world have purpose. Men have to go on lighting lamps where there is 4 darkness. God has created man in this universe to dispel darkness; he is not to be enveloped in it. He has to fulfil his duty to God, to Nature, and to his own self.

[Singh, N. and Antil, S. The Trinity Of Nature, Man And God In Poetry Of Rabindranath Tagore. Rep Opinion 2020;12(3):99-103]. ISSN 1553-9873 (print); ISSN 2375-7205 (online). http://www.sciencepub.net/report. 7. doi:10.7537/marsroj120320.07.

Keywords: Trinity, Literature, Rabindernath Tagore, Poetry.

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Social Network as the Tool for Commercializing Media Content

Kamoliddin Tursunpulatovich Beknazarov

PhD doctoral student of University of Journalism and Mass Communication of the Republic of Uzbekistan, Tashkent, Uzbekistan

k.beknazarov@gmail.com

Abstract: The article describe the feature of the Internet in front of other communication channels is that communication is possible both with Internet users (interpersonal interaction), and with the information provided (machine interaction), development of the interactivity of the Internet, users have the opportunity to use audio-visual channels for transmitting information through the Internet.

[Beknazarov K.T. Social Network as the Tool for Commercializing Media Content. Rep Opinion 2020;12(3):104-107]. ISSN 1553-9873 (print); ISSN 2375-7205 (online). http://www.sciencepub.net/report. 8. doi:10.7537/marsroj120320.08.

Keywords: internet, communication, news channel, public

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