V. Rajalakshmi ¹, G. S. Anandha Mala ²

Affiliations
1 Sathyabama University, Chennai, Tamil Nadu, IN
2 Department of Computer Science and Engineering, St. Joseph’s College of Engineering, Chennai, Tamil Nadu, IN

Abstract

As there are new techniques growing to reveal the hidden information on data, the threat towards those data also increases. Therefore, privacy preservation in data mining is an emerging research area which develops various algorithms to anonymize the data provided for data mining. The existing methodology handles the tradeoff between utility and privacy of data in a more expensive way in terms of execution time. In this paper, a simple Anonymization technique using subclustering is specified which achieves maximum privacy and also utility with minimum execution time. The methodology is explained with algorithm and the results are compared with the baseline method.

Keywords

Anonymization, Clustering, Isometric Transformation, Privacy Preservation

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R. Gayathri ¹, V. Rajalakshmi ¹

Affiliations
1 Department of Information Technology, Sathyabama University, Rajiv Gandhi Road, Jeppiaar Nagar, Chennai - 600119, Tamil Nadu, IN

Abstract

Objectives: To bridge the vocabulary gap between health seekers and providers to provide believable and accurate solutions to the health seekers for patients to solve issues over medical assistance records. Method: The proposed scheme consists of two mutually reinforced components, namely, local mining and global learning. The local mining technique is using some of the particular medical records for explaining the overall benefit and conclusion regarding particular health mapping by authentication terminology. The database of local Mining is getting update through the data of global learning, which collects the related medical data. This attempt is a particular pair of Q&A independently over the concept of medical extraction from pairing it through Q&A and maps it through the terminologies of authentication. Findings: In this research work a novel scheme is proposed which will be able to code the medical records with corpus-aware terminologies. As the first of its kind on automatically coding the community generated health data using concept entropy impurity approach to comparatively detect and normalize the medical concepts locally, which naturally construct a corpus-aware terminology vocabulary with the help of external knowledge. Also it builds a novel global learning model to collaboratively enhance the local coding results. This model seamlessly integrates various heterogeneous information cues. For making a communication or connection between the gaps, it is being described over here about the label of Question and Answer by joining and utilizing the approaches of global learning and local mining. Applications: The procedure can be used to build an efficient web portal for health seekers. The effectiveness of the system is being increased by experts question and answering

Keywords

Corpus Aware Terminology, Global Learning, Health Care, Health Seekers, Local Mining, Semantic Approach

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D. Dhayalan ¹, K. Divya Bharathi ¹, S. Radhika ¹, V. Rajalakshmi ¹

Affiliations
1 Department of MCA, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Chennai - 600 062, Tamil Nadu, IN

Abstract

Objectives: This paper discusses about the importance of the effective intelligence among human and artificial devices. Nowadays more and more human activities will be carried by artificial agents and devices, which overcome our Imagination. Methods: This paper gives a theoretical application to develop the personality of mentally challenged person by feeding Artificial Instructions into their brain by using the fMRI (functional Magnetic Resonance Imaging) concept in the reverse manner which is used in the mind reading system. Findings: The instructions will get fed into the brain by means of computer system and then it passes to the Temporal lobes of the human brain.Temporal lobes were used to speak, make decision, think and analyse. The instructions will get decoded into brain instruction by the different signals of the fMRI. Applications/Improvements: This work may bring changes in the life of mentally challenged ones and accidental victims.

Keywords

Artificial Instructions, fMRI Technology, Functional Imaging, Human Brain

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