Fuzzy clustering of data mining: A survey paper
Clustering is the main and essentially used method for the automatic information taking out from huge amounts of data. Its task is recognize groups, its called clusters, of indistinguishable objects in a data set. Clustering methods is used in broad area, including database shopping, web inspect, information acceptance, bio technology, and broad others. whenever, if clustering methods is used on real data , a problem that often produce up is that absent values shown in the data sets. For established clustering methods were developed to inspect complete data, there is a need for data clustering method pickup incomplete data. Proceed towards recommend in the literature for modify the clustering algorithms to incomplete data effort better on data set with similer scattered clusters. In this thesis we are description a new proceed towards for suitable for a new use the fuzzy c-means clustering algorithm to incomplete data that takesget hold the scatters of clusters into statement. In this experiment on made by human being and real data sets with various scattered clusters .we show that our proceed out accomplish the another clustering techniq for defective data. ,We explain various cluster reliability functions and modify them to defective data according to the “present-case” proceed it. We inspect the original and the modify cluster reliability functions using the separate results of various artificial and real data produce by various fuzzy clustering algorithms for imperfect data. Therefore both the clustering algorithms and the cluster reliability functions are modify to inperfect data, we should target are finding the factor that is searching for determining the optimal number of clusters on defected data: the modify of the clustering algorithms, the modify of the cluster reliable functions, or the miss of information in the data self. In this research , we present that our capacity are capable to right check the clusters nearly situated to every other and cluster within broad density substance .
Published by: Shivani Singh, Dr. A. K. Singh
Author: Shivani Singh
Paper ID: V5I3-1896
Paper Status: published
Published: June 14, 2019
Air pollution data analysis using ARIMA model
This work addresses the prediction of the possible amount of air pollution in the atmosphere. Initially, we convert the raw data of pollutants to a standard that is AQI (Air Quality Index) then we carry out Exploratory data analysis such as seasonal pollution analysis, correlation matrix to find out the relation between various factors contributing to air pollution, box plots to find out a summary of a particular factor, etc. Further, we build models for prediction and forecasting future values. Forecasting consists of taking models to fit on historical information/data and using it to predict future observations. We bui1d two models subjected for this purpose namely, Multiple linear regression model and ARIMA (Auto-Regressive Integrated Moving Averages) model. We use the results obtained in exploratory analysis to find the dependent variables for AQI and build a Multiple linear regression model to predict future values. ARIMA model is used for forecasting our pollution time series to predict future values based on the parameters found using the auto-correlation function.
Published by: Amogh Mudholkar, Akash S., Ajay C., Gowramma G. S.
Author: Amogh Mudholkar
Paper ID: V5I3-1880
Paper Status: published
Published: June 14, 2019
Association of herbal plant in Rheumatoid Arthritis studies using in silico approach
Arthritis is inflammation or degeneration of joints. There are more than 100 different types of arthritis most common types of inflammatory arthritis include Juvenile rheumatoid arthritis (in children’s), Rheumatoid Arthritis (RA) (in adults), Psoriatic arthritis, gout, osteoarthritis, gonococcal Arthritis, etc. Rheumatoid Arthritis (RA) is an autoimmune disease. It is also a systemic disease which means it affects the whole body. People with Rheumatoid Arthritis (RA) have a higher risk of some other conditions such as heart disease, obesity, depression, anxiety, high blood pressure, diabetes, etc. No one knows the definite cause of this disease, but there is researcher’s evidence that genetics, environmental and stochastic factors are involved. There are various drugs therapies and treatments are available to suppress Rheumatoid Arthritis (RA) and there is a need for an alternative approach to avoid unnecessary side effects and high cost. Therefore, phytochemicals are used which include anti-inflammatory properties. Thus, the present study is aimed for finding phytochemical which is Stigmasterol showing higher binding affinity towards the target receptors those are 4JJ7, 6E28, 5GJH, 4FKL, 4EK4, 3CZF, 5NI9, 4RI5, 5BXU and 5N86 using molecular docking approach to find out potential drug molecule against protein causes inflammation. Tools used for molecular docking were GROMACS 5.1.1 for protein optimization, AutoDock 4.2.6 software for docking & Discovery Studio for visualization. Stigmasterol was ranked top among various docking conformations showing highest binding affinity with the target. Therefore it could be an alternative treatment method for rheumatic disorders. Plants like Glycine max (soybean), Physostigma venenosum (calabar bean), Brassica napus (rapeseed) comprise of this phytochemical. Further studies can confirm the usage of this phytochemical and plants for suppressing inflammation via inflammation
Published by: Aparna Hiren Patil Kose, Priyanka Patel, Samiksha Wani
Author: Aparna Hiren Patil Kose
Paper ID: V5I3-1875
Paper Status: published
Published: June 14, 2019
Organisation climate and job satisfaction: A study in Action Ispat and Power Limited Jharsuguda (Odisha)
Abstract The purpose of this study is to analyze the importance and impact of different organizational climate dimensions in terms of employee’s satisfaction, employee motivation and performance in Action Ispat & Power (P) Ltd Jharsuguda of Odisha. The research on the effect of organizational climate on job satisfaction in Steel & Power companies in Odisha is essential, notably in terms of specific business environment which dwells in a transition era under complicated political and economic systems. The result of the study shows that there exists a significant relationship between organizational climate and job satisfaction among employees. The findings also revealed that job satisfaction under different categories of employees does not differ. The analysis and tests also revealed that there is no significant difference between organizational culture and the general health of the employees. The satisfaction level of employees on factors actors like opportunity for personal development and growth , participation in decision making , flexibility and freedom of job , relationship with colleagues, employer-employee relationship, measures for increasing morale , attitude of superiors, support from superiors ,cooperation from subordinates, staff strength, chance of attunement of goals and ambitions and communication system and flow of information in the organizations are at the positive side. This paper presents the comprehensive diagnosis of organizational climate and job satisfaction indices of Steel & Power business, the factors causing the dissatisfaction & suggestions to improve them
Published by: Lekh Ram Bhati, Dr. Jyotirmayee Choudhary
Author: Lekh Ram Bhati
Paper ID: V5I3-1855
Paper Status: published
Published: June 14, 2019
Knowledge regarding issues in reproductive health among adolescent girls
A descriptive study with cross sectional survey approach was under taken to assess the knowledge regarding issues in reproductive health among adolescent girls in selected village, Salem. Semi-structured interview schedule was used to collect the data from 100 adolescent girls and collected data was analyzed by inferential statistics. It can be concluded that from the present study adolescent girls had average knowledge regarding issues in reproductive health.
Published by: A. Thenmozhi, Dr. V. Selvanayaki
Author: A. Thenmozhi
Paper ID: V5I3-1851
Paper Status: published
Published: June 14, 2019
Pattern discovery tool and technique of web
In the last years with the development of Internet technology the enhancement of the World Wide Web grows up all expectations. More information is extant in different formats and retrieving content has become a very hard task. One possible approach to solve the issue is Web Usage Mining (WUM). Web mining is the petition of data mining on web data and web usage mining is a vital component of web mining. The aim of web usage mining is to perceive the demeanor of web site users using the process of data mining of web data and Web usage mining is to perceive the demeanor of web site users through the process of data mining of web Access data. knowledge obtained from web usage mining can be used to enhance web creation, introduce personalization service and facilitate more dominant browsing the vital an application of web mining extracting the secret knowledge in the log dossier of a web server recognizing more interests of web clients, searching customer behavior while at the site are normally referred as the application of web usage mining. In this paper, we provide an updated focused review on apart pattern discovery methods of web usage mining.
Published by: Pratap Lal, Dr. Ajeet Kumar Singh
Author: Pratap Lal
Paper ID: V5I3-1849
Paper Status: published
Published: June 14, 2019
