Informatics Publishing Limited

E. Swathipriya ¹, N. Subha ¹, B. Gomathy ¹

Affiliations
1 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN

Abstract

In recent times, Breast cancer has become one of the common disease among women. Few of the important ischolar_main causes for breast cancer is urbanization and adoption of modernized culture. Most of the cancer cases are diagnosed only during the last phase of the disease and thus early detection of the disease has become a crucial task. This paper analysis the performance of four classification algorithms on a breast cancer dataset and speculates the ideal one. Based on the accuracy, appropriate algorithm is chosen and the useful information thus obtained as an outcome is used for breast cancer Diagnosis. During the prediction process Rapid miner 6.0 tool is used to apply data mining algorithms on the cancer dataset.

Keywords

Classifier, Decision Tree, Entropy, Information Gain, Linear Regression, Pruning, Support Vector Machine.

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S. M. Ramesh ¹, A. Shanmugam ¹, B. Gomathy ²

Affiliations
1 Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, Satthyamangalam-638401, IN
2 Department of Computer Science Engineering, Bannari Amman Institute of Technology, Satthyamangalam-638401, IN

Abstract

The SPIHT image compression algorithm is modified for application to large images with limited processor memory. The sub band decomposition coefficients are partitioned into small tree-preserving spatial blocks which are each independently coded using the SPIHT algorithm. The bit streams for each spatial block are assembled into a single final bit stream through one of two packetization schemes. The final bit stream can be embedded in fidelity with a small expense in rate. SPIHT encoding and decoding of the spatial blocks can be done in parallel for real-time video compression.

Keywords

Decomposition, SPIHT Algorithm, Packetization, Sub-Bitstream.

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M. P. Sruthi ¹, S. Sinthiya ¹, B. Gomathy ¹

Affiliations
1 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN

Abstract

Personal data leads to a trend that data owners adopt to remotely outsource their data to clouds for the enjoyment of the high-quality revival and storage service without worrying the load of local data management and maintenance. However, protected share and search for the outsourced data is a challenging task, which may easily incur the leakage of sensible personal information. Efficient data sharing and searching with security is of essential importance. This paper, for the first time, introduces a searchable attribute-based proxy re-encryption system. When we compare to existing systems only aiding both searchable attribute-based functionality and attribute-based proxy re-encryption, our new primitive supports both abilities and gives flexible keyword update service. Particularly, the system enables a data owner to efficiently share his data to a named group of users matching a sharing policy and the data will maintain its searchable property but also the respective search keyword can be uploaded after the data sharing. The new mechanism is suitable to many real-world applications, such as electronic health record systems. It is proved that chosen cipher text is secure in the random oracle model. To achieve fine-grained and efficient scalable data access control for PHRs, we grease attribute based encryption (ABE) techniques to encode each patient's PHR file. The highest degree of patient privacy is assured simultaneously by using multi-authority ABE. Our scheme enables dynamic modification of access policies and file attributes, guide adequate on-demand user/attribute revocation and break-glass access based on emergency scenarios. Extensive detailed and empirical results are presented which shows the security, scalability and efficiency of proposed scheme.

Keywords

Patient, Records, Sharing, Attribute Based Encryption.

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M. Priyanka ¹, N. Subha ¹, B. Gomathy ¹

Affiliations
1 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN

Abstract

Data mining is the practice of extracting the useful information from the frequently occurring patterns in the observational datasets available. In data mining, classification is the process of bringing out the models called classifiers to predict the class labels. This paper gives a comprehensive review of the classification techniques in data mining such as Support Vector Machine (SVM), Decision tree and Linear Regression.

Keywords

Classification, Datasets, Decision Tree, Linear Regression, SVM.

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S. Sinthiya ¹, A. Udayadhara ¹, B. Gomathy ¹

Affiliations
1 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN

Abstract

The electronic prescription system provides web based services to physicians, pharmacies and administrators. In this application, when a patient enters the hospital the patient id is saved on the database server. After checking the patient health the prescribed medicines will be sent to the subscribed pharmacy by the doctor. The medicines will be retrieved from the hospital server. The medicine and quantity will be retrieved in the pharmacy and the prescribed details can be printed in the pharmacy.

Keywords

Database Server, Patient, Doctor.

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T. Nagamani ¹, B. Gomathy ²

Affiliations
1 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN
2 Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, IN

Abstract

For greater flexibility, from local to commercial public cloud, data owners are stimulated to farm out their complex data management systems in cloud. Before outsourcing, Sensitive data has to be encrypted to protect data privacy which obsoletes traditional data exploitation based on plaintext keyword search. Thus, the main objective is enabling an encrypted cloud data search service. So, it is very important to allow multi-keyword query for the search service, while considering the large number of data users and documents in cloud, thus cloud computing is the long dreamed vision of computing as a utility, where cloud customers can vaguely store their data into the cloud so as to enjoy the on-demand high-quality applications and services from a shared pool of configurable computing resources.  Similarity ranking to meet the efficient data retrieval need. Related works are mainly focus on single keyword search or Boolean keyword search, and seldom differentiate the search results. Here, it is proposed a basic MRSE scheme using secure inner product computation, and then radically improve it by getting the different privacy requirements.

Keywords

Boolean Keyword, Cloud, Coordinate Matching, Encryption, Keyword Search, Information Retrieval, Ranked Search.

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