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Thakur, R. S.
- From Chief Editor's Desk
Authors
Source
Journal of Pharmaceutical Research, Vol 14, No Special Ed (2015), Pagination: 13-22Abstract
No Abstract.- Solid-Self Emulsifying Drug Delivery System:Formulation Techniques and Dosage Forms
Authors
1 Department of Pharmaceutics, Krupanidhi College of Pharmacy, #12/1, Chikkabellandur, Carmelaram post, Bangalore-560 035, IN
2 Department of Formulation and Development, Janssen-Cliag-Johnson and Johnson, Mumbai-400 080, Maharashtra, IN
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Journal of Pharmaceutical Research, Vol 10, No 3 (2011), Pagination: 87-93Abstract
The drug substance administered by any route must possess some aqueous solubility for systemic absorption. For this purpose, solubility is one of the most important parameter to achieve desired concentration of drug in systemic circulation for therapeutic response. However, more than 40% of new chemical entities exhibit poor aqueous solubility and present a major challenge to modern drug delivery system, because of their low bioavailability. Self-emulsifying drug delivery systems (SEDDS) are usually used to improve the bioavailability of hydrophobic drugs. Conventional SEDDS, however, are mostly prepared in a liquid form, which can produce some disadvantages. Accordingly, solid SEDDS (S-SEDDS), prepared by solidification of liquid/semisolid self emulsifying (SE) ingredients into powders, have gained popularity. This article gives an overview of the recent advances in the study of S-SEDDS, especially the related solidification techniques and the development of solid SE dosage forms. Finally, the existing problems and the possible future research directions in this field are pointed out.Keywords
Solid-Self Emulsifying System, Solidification Techniques, Self Emulsifying, Recent Advances and Future Aspects.- Rule Based Recommendation System for Performance Improvement in Engineering Institutions
Authors
1 M.G.C.G.V., Chitrakoot, Satna, M.P., IN
2 M.A.N.I.T., Bhopal, IN
Source
Data Mining and Knowledge Engineering, Vol 8, No 1 (2016), Pagination: 11-14Abstract
Higher education plays an important role in economy of any nation countries like India need a good higher education to face the challenges of this new era. Manifold growth has been found in the higher education in India in last decade. But there is need to focus more on our education system. The paper aims at the use of data mining techniques for improving the efficiency of higher educational institutions. The association rule mining Techniques can be applied to higher education processes, to help improve student's performance of an institution. This paper contains a methodology to examine the performance of engineering graduate student based on their continuous evaluation and locality. We present an approach based on association rule mining techniques to identify the strategies for improving the performance of students.Keywords
Association Rule Mining, Recommendation System Educational Data Mining, Knowledge Representation, Higher Education System.- Model for Link Prediction in Social Network by Genetic Algorithm Approach
Authors
1 Department of Computer Application, Maulana Ajad National Institute of Technology, Bhopal, M.P., IN
Source
Data Mining and Knowledge Engineering, Vol 7, No 5 (2015), Pagination: 191-196Abstract
Social networking sites are increasing their features day by day to gain the attention of users. There are lots of research works in this field. Out of many research areas this paper focuses on link prediction using soft computing technique. We used various features of social network and applied genetic algorithm to predict links. Selection of features to build chromosome is main task in genetic algorithm. Number of runs will get different chromosomes i.e. shown in results. Normalization of features is also done depending upon their priority. Results show that with the increase in dataset size chances of correct prediction increases.Keywords
Social Network, Link Prediction, Genetic Algorithm.- Multidimensional Database Model for Web Content Mining
Authors
1 Department of Computer Applications, Maulana Azad National Institute of Technology, Bhopal, M.P., IN
Source
Data Mining and Knowledge Engineering, Vol 5, No 3 (2013), Pagination: 109-112Abstract
With increase in network technologies and number of users working on the network, attempts are being made to discover the useful knowledge from the secondary data. For retrieving knowledge large number of models, techniques and methods are evolving continuously in the area of web content mining. These techniques are becoming very critical for effective management of web sites in the variety of domains such as business, education and e-learning. Based on the prediction approach the user browsing behaviors can be guessed and this information can be utilized for building of proper web sites. This paper proposes star schema for web contents mining from the complex data which is multidimensional in nature. Further the association among web contents is explored using multidimensional ARM approach to know the surfing behavior of web users. At the end Performance computation of proposed work has been discussed, which shows improvement in the gain and implementation explains well the significance of multidimensional association rule in web content data. The paper also compares pros and cons with the traditional state of art approaches.Keywords
Web Content Mining, Data Mining, Pattern Discovery.- Karnaugh Map Model for Mining Association Relationships in Web Content Data:Hypertext
Authors
1 Department of Computer Applications, Maulana Azad National Institute of Technology, Bhopal, M.P, IN
2 Department of Mathematics, Maulana Azad National Institute of Technology, Bhopal, M.P, IN
Source
Data Mining and Knowledge Engineering, Vol 4, No 11 (2012), Pagination: 579-587Abstract
Web content mining refers to description and discovery of useful information from the web contents/data/documents. Hypertext is one of the most common web content data that has hyperlinks in addition to text. These are modeled with multiple levels of details depending on the application. In this paper Karnaugh map model for multilevel association rule mining has been developed to investigate association relationships among hypertexts of a web site. Karnaugh map model needs single scan of data and stores the information in the form of frequency. Model adopts progressively deepening approach for finding large text sets by utilizing karnaugh map logic for finding frequent text sets at each level of abstraction. Frequent texts sets are generated by the karnaugh map model are used to discover strong association relationships among hypertexts at different levels of abstraction. Further the rules are categorized under three categories and their behavior is studied across the level of abstractions.Keywords
Karnaugh Map Model, Multilevel Association Rules, Association Relationships, Frequent Text Set.- Analysis of Student Performance Using Mining Technique:A Review
Authors
1 Department of Computer Sc. & Engg, Govt. Mahatma Gandhi Chitrakoot Gramodaya Vishwavidyalaya, Chitrakoot, Satna M.P., IN
2 Maulana Azad National Institute of Technology, Bhopal, IN
3 Govt. Mahatma Gandhi Chitrakoot Gramodaya Vishwavidyalaya, Chitrakoot, Satna M.P., IN
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Artificial Intelligent Systems and Machine Learning, Vol 8, No 3 (2016), Pagination: 94-97Abstract
Today's higher education is one of the needs of any students for growing his life.One of the biggest challenges with higher education is thatinstitutions would like to know, which students will enroll in which course, and which students will need more assistance in particular subject and what efforts should be taken for weak students.Data mining is one of the powerful tools to extract knowledge from large educational database and it can be used for decision making in educational system.
In this paper data mining techniques such as clustering,Association, Rule mining etc. based work is analyzed which will give direction to the educational institution for improving performances of their students. This review also helps to researchers for choosing appropriate data mining techniques to analyzed student data.
Keywords
Educational Data Mining, Association Rule Mining, Classification, Clustering, Soft Computing.- A Review and Performance Prediction of Students’ Using Association Rule Mining based Approach
Authors
Source
Data Mining and Knowledge Engineering, Vol 8, No 8 (2016), Pagination: 252-259Abstract
For the last few decades’ education data mining has become one among foremost promising research areas. The only objective of this area is to explore data mining methods in order to analyze the student performance as well as impart the quality education for enhancing the performance of educational institutes. Data mining is the core part of the knowledge discovery process which is used to extract meaningful information from raw data. However, the various data mining techniques are proposed for achieving the most effective quality results. An Association Rule Mining (ARM) one of the well-known and popular data mining techniques which has been used extensively for educational perspective. In this study, higher education institute i.e. Government Girls College (GGC) data are considered and various attributes regarding student performance are analyzed for study purpose. Therefore, the various experiments based on support and confidence measures like 2%, 4%, 10%, 20% and 40% are conducted to generate interesting rules. The major objective of this research study is to find the weaker students as well as those students who have bright performance in schooling level but could not be performed well on current semester exams due to certain reasons. However, teachers as well as parents can give particular attention to those students, whether they will perform better in the next semester or exams.Keywords
Apriori Algorithm, Association Rule Mining, Confidence, Education Data Mining, Preprocessing, Prediction, Support, Weka 3.7.- Long Term and Short Term Investment Strategy for Predicting the Performance of BSE using MLP Model
Authors
1 Department of Computer Applications, S.A.T.I., Vidisha - 464001, Madhya Pradesh, IN
2 Department of Applied Math’s and Computer Science, S.A.T.I., Vidisha - 464001, Madhya Pradesh, IN
3 Department of Computer Applications, M.A.N.I.T., Bhopal - 462003, Madhya Pradesh, IN
Source
Indian Journal of Science and Technology, Vol 8, No 22 (2015), Pagination:Abstract
Background/Objectives: Now a day’s stock market has great influence in the daily life of people. The biggest problem of stock market is that it holds large uncertainties which are directly related to their long term and short term investment. The key objective of researchers in this area is to strengthen economy as well as profit maximization on individual share. Methods/Statistical Analysis: This study, adopted a most popular back propagation training algorithm for predicting the performance of Bombay Stock Exchange of India based on long term and short term basis. In this study, 3500 samples of nine different companies are considered are divided 60% for training, 20% for validation and remaining 20% for testing task. In the initial phase the data underwent five phases which includes variable selection, data preprocessing, training dataset, prediction and evaluation. However the research evaluated through MATLAB tool which consists of training performance, error rate, and output prices. After getting the output from various evaluations made on stock dataset. Findings: It is shown by experimental results the method has given more accurate prediction results. Besides, it takes less training time and epochs for prediction task. It is also found that long term investment also has more successive returns over short term investment. Applications/Improvements: In the present study back propagation method is employed for long term and short term prediction. The different experimental results are carried out on stock data sets. It is also observed by study for long span of time small scale and medium scale companies like HCL and Ambuja Cement have better performance compared to large scale companies like TCS. In contrast, short span of time large scale companies like TCS also have better performance.Keywords
BSE, Long Term Investment, Multi Layer Perceptron, Prediction, Short Term Investment- Multidimensional Association Rules Extraction in Smoking Habits Database
Authors
1 MP Bhoj University, Bhopal, IN
2 MaNIT, Bhopal, MP, IN
3 Geetanjali Girls College, Bhopal, MP, IN