Cited and citing pattern of Indian Journal of Pure and Applied Mathematics: An evaluation

This paper examines the cited and citing pattern of Indian Journal of Pure and Applied Mathematics (IJPAM) in terms of source, authorship, subject diversity, accessibility, citation-age, quantity & citing-life. This study is based on the data collected from 5 Volumes, consisting of 30 issues, carrying 171 articles, citing 2754 references from 575 citing sources of IJPAM published from 2009 to 2013. Whereas for collecting cited references, every published article from the official website of the journal namely Indian National Science Academy (INSA) was downloaded, for citing references, Google Scholar and Scopus both were explored to recognize the maximum number of citing sources during October 2017.The study revealed that journal articles are the most cited references, whereas citing references are mostly from the journals of foreign origin. Majority of cited articles are available in non-open access form, though the citations came from both, open and non-open journals. Joint authorship was found to be predominant, in both cited-citing references

Impact of Scholarly Output on NIRF Ranking: A Study of Top 15 NITs

The study aims to analyze the sub-parameters Combined metric for Publications (PU) of NIRF ranking parameter Research and Professional Practice and impact of various publications\u27 parameter on it. The study investigates the scientific research productivity and authors productivity of the top 15 National Institutional Ranking Framework (NIRF) ranked in the engineering category National Institute of Technology in 2021. For this purpose, the data were collected from the NIRF website and Scopus database. The study is focused on analyzing the total number of research publications of these institutions and the authors with the highest number of papers published, their publications and the citations received by them. The study also discussed the collaboration of authors having the highest number of papers published with other co-authors

Novel Method for Denoising Medical Image Using 2nd Level Discrete Wavelet Transform and Bilinear Filter

Medical imaging is one of the crucial subfields in the world of science and technology. There must be genuine image quality of medical images as it is used to diagnose diverse types of illness and in medical image we cannot settlement or compromise in quality because it provide us important data of patients and if quality compromised then severe effects may come into existence which definitely harmful for patients. Developing a significant denoising method plays a crucial role in image processing. In this research paper, image is first decomposed using filter into eight subbands using 3D DWT and bilateral filter technique and in this process we got approximation coefficient using DWT and once again DWT technique used on approximation coefficient image then we applied bilateral filter and the detail coefficients are subjected to Wavelet Thresholding. After that there is requirement of image reconstructed and this process is executed by inverse wavelet transform (IDWT) of the resultant coefficients and then it is filtered using bilateral filter. In our research work two types of images are considered which are MRI images and Ultrasound images. In this work IDWT process carried out two times that is why our research work known as 2 level DWT process. In this process finally two parameters are calculated PSNR and MSE

Effective Approach for Extracting Noise from Digital Image and Real Time Data using Filtering Technique

Digital image are made out of pixels and we know pixel is the smallest component of a picture. Every pixel speaks to the dark level for highly contrasting photographs at a solitary point in the image, so a pixel can be spoken to by a small speck of particular shading. In an image pixel having intensity in range of 0-255 and if pixel having intensity zero it means black and having intensity 255 it means white and in between them then considered as gray level. There are various types of images and various types of noises occurred and to remove them diverse filters are available and every filter are having own advantage and disadvantages and suitable for a particular types of noised which it can remove efficiently. In our research work our main target is to fetch out salt and pepper noise. In base paper at two levels of S&P noise filter is used to denoise the image to get various parameters. But in our research work salt and pepper noise at various levels targeted and removed efficiently with parameters PSNR, MSE and IEF. Noise is random in nature and it can be mixed with image anywhere therefore diverse noise models were studied deeply. Restoration efficiency was checked by PSNR and mean square error (MSE) into considerations

Social Media: An Interactive Educational Tool for Better Understanding of Educational Concepts and Make Them More Memorable

The topic “Social media:An Interactive Educational Tool for better understanding of Educational concepts and make them more memorable.As social media sites continue to grow in popularity, it is our premise that technology is a vital part in today’s student success equation.“Social media: an innovative education tool†was undertaken to study the relevance and importance of social media which is an in-thing among the educational sector. In an era, where the global is the word to define common platform for the people around the world to share and exchange their beliefs, culture, traditions, knowledge, views, etc. The study concludes that our education system needs change and social media should be widely utilized for the educational purposes. It is mainly used for the purpose of making presentations followed by assignment updates, better research and connectivity.Now a day’s Social media is an ingrained part of today’s society. Our students are constantly on Instagram, Facebook, Twitter, and likely many sites we’re not hip enough to know about, So if you want to bring the “real world†into the classroom, consider integrating social media into your lessons.When used carefully, social media can be a useful tool rather than a distraction. A recent Edutopia blog post argues that using social media not only brings current technology to the classroom, but it also Helps Bridge the digital divide among lower-income students. Why should they be left behind as technology continues to march forward?Education-based sites such as Edmodo, Edublog, and Kidblog provide alternative social media sites for posting status updates and announcements, blogging, and micro blogging. But even the commercialized sites can be useful for demonstrating social media to students

Impact of covid 19 on Libraries: a selective review of literature

Education is the unstoppable procedure. Covid 19 has effected in every sectors. Education sector has been badly affected. Almost all educational institutes has been closed during pandemic. Library is also a part of an educational institution. In the present study authors studied the corona positive and negative effects of corona that had an impact on libraries. For the study author used descriptive research method. Data was collected from various article, webinar, and reports etc. Authors found the positive effects on libraries like digitization, remote access service, use social media and connect too many people etc. Negative impacts are decreasing use of print resources, financial crises, impact on health and many more

Structure based prediction of a novel GPR120 antagonist based on pharmacophore screening and molecular dynamics simulations

The G-protein coupled receptor, GPR120, has ubiquitous expression and multifaceted roles in modulating metabolic and anti-inflammatory processes. Recent implications of its role in cancer progression have presented GPR120 as an attractive oncogenic drug target. GPR120 gene knockdown in breast cancer studies revealed a role of GPR120-induced chemoresistance in epirubicin and cisplatin-induced DNA damage in tumour cells. Higher expression and activation levels of GPR120 is also reported to promote tumour angiogenesis and cell migration in colorectal cancer. Some agonists targeting GPR120 have been reported, such as TUG891 and Compound39, but to date development of small-molecule inhibitors of GPR120 is limited. Herein, following homology modelling of the receptor a pharmacophore hypothesis was derived from 300 ns all-atomic molecular dynamics (MD) simulations on apo, TUG891-bound and Compound39-bound GPR120S (short isoform) receptor models embedded in a water solvated lipid bilayer system. We performed comparative MD analysis on protein–ligand interactions between the two agonist and apo simulations on the stability of the “ionic lock” – a Class A GPCRs characteristic of receptor activation and inactivation. The detailed analysis predicted that ligand interactions with W277 and N313 are critical to conserve the “ionic-lock” conformation (R136 of Helix 3) and prevent GPR120S receptor activation. The results led to generation of a W277 and N313 focused pharmacophore hypothesis and the screening of the ZINC15 database using ZINCPharmer through the structure-based pharmacophore. 100 ns all-atomic molecular dynamics (MD) simulations were performed on 9 small molecules identified and Cpd 9, (2-hydroxy-N-{4-[(6-hydroxy-2-methylpyrimidin-4-yl) amino] phenyl} benzamide) was predicted to be a small-molecule GPR120S antagonist. The conformational results from the collective all-atomic MD analysis provided structural information for further identification and optimisation of novel druggable inhibitors of GPR120S using this rational design approach, which could have future potential for anti-cancer drug development studies

Analysis of ECG Signal Using WP-HH Transform

This paper introduces a method of ECG signal de noising using Hilbert Huang and Wavelet Packet Transform. Both HHT and WPT are signal processing method. Wavelet Packet transforms is used to decompose the electrocardiogram signal into a set of narrow band signals. Later the suitable threshold value is selected for each decomposed components. For those components for which wavelet coefficients are larger than the threshold value, HHT is applied. This method removes the noise as well as base line wonder effect from ECG signal and reduces the computing quantities and the decomposition layers of EMD. Paper includes features extraction method using ECG signal (IF, mean frequency, phase) which are useful to discriminate normal and abnormal signal. The simulation result indicates the proposed method is very effective as compared to other methods

Recognition and Classification of Leaf Disease in Potato Plants

Farming is one of the most important lifelines of the country. A nation’s growth majorly depends on how advanced and effective their agricultural practices are in improving the crop yield. When a crop is grown many at times, farmers are unable to identify the health and wellbeing of the plant; they only recognize the problems when it becomes too late hence losing out on that year's expected yield. In this study, we have introduced a recognition and classification technique which is able to detect any ailments that the plant is suffering from at an early stage itself thus enabling the farmers to do the needful at a recoverable stage itself. To make the system as user-friendly as possible, we have provided a feature where the farmers are able to assess the health of the plant by providing a picture of the potato plants’ leaf

A text Ontology Method based on mining Develop D –MATRIX

In this issue, we demonstrate a text mining method of ontology based on the development and updating of a D-matrix naturally extraction of a large number of verbatim repairs (written in unstructured text) collected during the analysis stages. dependence (D) Fault - Matrix is a systematic demonstrative model is used to capture data symptomatic level progressive elimination system including dependencies between observable symptoms and failure modes associated with a frame. Matrix is a time D-long process. The development of D-matrix from first standards and update using the domain information is a concentrated work. In addition, increased D-die time for the disclosure of new symptoms and failure modes observed for the first race is a difficult task. In this methodology, we first develop the fault diagnosis ontology includes concepts and relationships regularly seen in fault diagnosis field. Then we use text mining algorithm that make use of this ontology to distinguish basic items, such as coins, symptoms, failure modes, and conditions of the unstructured text verbatim repair. The proposed technique is tools like a prototype tool and accepted using real - life information collected from cars space