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Balajee, R. M.
- Context Based Android Application Administrative Access Control (CBAA-AAC) for Smart Phones
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1 Department of Computer Science and Engineering, Annapoorana Engineering College, IN
1 Department of Computer Science and Engineering, Annapoorana Engineering College, IN
Source
ICTACT Journal on Soft Computing, Vol 6, No 4 (2016), Pagination: 1308-1313Abstract
Android applications in smart phones are generally towards provide greater flexibility and convince for users. Considering the fact that the Android applications are having privilege to access data and resources in mobile after it gets installed (one time permission provided by end user on the time installation), these application may also lead to issues in security for the user data as well as issues relate smart phone with peripheral environment. A practical example for an issue which relates smart phone with peripheral environment can be even an Android smart phone application of a college student use camera resource to capture photos of R&D cell and transfer without user or organization permission. The security of the organization and user should be prevented by providing an adoptable solution. The proposed concept of CBAA-AAC (Context Based Android Application Administrative Access Control) is used to control the privileges of any Android application over a corresponding longitude and latitude by the organization administrator. In this way, administrator is able to block malicious application of every individual smart phone which can have activity towards utilizing services and resources that may affect the security of the organization, such an move is must for assuring security of any organization and educational institutions while they allow users to "bring their own smart phones/mobile devices" into the campus.Keywords
Android Application, Administrative Access Control, Smart Phones and Organization Administrator.
- A Survey on Machine Learning Algorithms and Finding the Best Out there for the Considered seven Medical Data Sets Scenario
Abstract Views :156 |
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Authors
Affiliations
1 Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Avadi, Chennai, IN
1 Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Avadi, Chennai, IN
Source
Research Journal of Pharmacy and Technology, Vol 12, No 6 (2019), Pagination: 3059-3062Abstract
Today, researchers are focusing on many machine learning algorithms in general over the data’s available. Each and every algorithm will have certain characteristics and we need to test it on specific data set to say about its efficiency in particular. Each and every Algorithm efficiency will get varies according to the data set’s nature. Research based on medical science will be much useful to society in critical situations, so we are taking seven medical data sets scenario for our research work. A detailed survey over variety of machine learning algorithms like SVM, Naïve Bayes, Dession Tree, Random Forecast, K-Means Clustering, Partition Algorithm, Bayesian Algorithm, Hierarchical Algorithm, Missing Values, Low Variance, Principal Component Analysis, Rough Set Theory, etc, over the seven medical data sets scenario which is taken to study and the results will be made on the aspect, which algorithms are good for what kind of medical records.Keywords
Machine Learning Algorithms, SVM, Naïve Bayes, Dession Tree, Random Forecast, K-Means Clustering, Partition Algorithm, Bayesian Algorithm, Hierarchical Algorithm, Missing Values, Low Variance, Principal Component Analysis, Rough Set Theory, Seven Medical Data Sets Scenario.References
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