Intro
Preface
Organization
Contents
Type 2 Diabetes Prediction from the Weighted Data
1 Introduction
2 Materials and Methods
2.1 Missing Values Replacement
2.2 Normalization
2.3 Feature Extraction
2.4 N2PS
2.5 Weighted Value
2.6 Prediction Model
2.7 Accuracy
2.8 Procedure of the Proposed Work
3 Experimental Results
4 Conclusion
References
Harnessing Energy of M-ary Hopfield Neural Network for Connectionist Temporal Sequence Decoding
1 Introduction
2 Hopfield Network Based Formulations
2.1 Basic Hopfield Network for Static Patterns

2.2 M-ary Hopfield Network for Static Patterns
2.3 Hopfield Based Network for Sequence Storage and Retrieval
3 M-ary HNN for Sequence Storage and Retrieval
3.1 Dual Weight Learning
3.2 Isolated Sequence Retrieval from M-ary HNN
4 Connected Temporal Sequence Decoding Using Extended M-ary HNN
4.1 Model
4.2 Decoding Process
5 Dataset and Experiments
5.1 Scenario-A
5.2 Scenario-B
6 Conclusions
References
Integrative Analysis of miRNA-mRNA Expression Data to Identify miRNA-Targets for Oral Cancer
1 Introduction
2 Background Study
3 Materials and Methods

3.1 Dataset Used
3.2 Proposed Model
4 Results
5 Conclusion
References
Compact Associative Classification for Up and Down Regulated Genes Using Supervised Discretization and Clustering
1 Introduction
2 Literature Review
3 Proposed Method
3.1 Data Normalization
3.2 Selection of Up and Down Regulated Genes
3.3 Discretization
3.4 Associative Classifier
3.5 Clustering Class Association Rules
3.6 Pseudo Algorithm
4 Results and Discussion
5 Conclusion and Future Work
References

Assessment of Brain Tumor in Flair MRI Slice with Joint Thresholding and Segmentation
1 Introduction
2 Related Research
3 Methodology
3.1 BRATS2015 Database
3.2 Tri-Level Thresholding
3.3 Automatic Segmentation
3.4 Performance Evaluation
4 Result and Discussion
5 Conclusion
References
Mayfly-Algorithm Selected Features for Classification of Breast Histology Images into Benign/Malignant Class
1 Introduction
2 Related Research
3 Methodology
3.1 Image Database
3.2 Feature Extraction
3.3 Feature Selection
3.4 Classification and Validation

4 Result and Discussion
5 Conclusion
References
Recent Trends in Human Re-identification Techniques - A Comparative Study
1 Introduction
2 Methodologies for Human Re-identification
2.1 Feature Representation
2.2 Distance Metric Learning Methodologies
3 Performance Analysis
3.1 Comparative Analysis
4 Conclusion
References
Automatic Segmentation of Handwritten Devanagari Word Documents Enabling Accurate Recognition
1 Introduction
2 Brief Overview of Devanagari Script
3 Proposed Method
3.1 Identification and Segmentation of Shiroreakha [14]