Titlebook: IT Convergence and Security 2017; Volume 1 Kuinam J. Kim,Hyuncheol Kim,Nakhoon Baek Conference proceedings 2018 Springer Nature Singapore P

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An Improved SVM-T-RFE Based on Intensity-Dependent Normalization for Feature Selection in Gene Exprehod of measuring gene expression. Since RNA-seq generate a huge amount of data they have been struggling to overcome the lack of computational methods to exploit the enormous RNA-seq Big-Data. In most of cases, those methods have not been adequate for feature scaling scheme on RNA-seq Big-Data. So,

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Heavy Rainfall Forecasting Model Using Artificial Neural Network for Flood Prone Areacountries. Although to predict the trend of precipitation is a difficult task, there are many approaches exist using time series analysis and machine learning techniques to provide an alternative way to reduce impact of flood cause by heavy precipitation event. This study applied an Artificial Neura

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I-Vector Extraction Using Speaker Relevancy for Short Duration Speaker Recognitioned system, the frame-level point-wise mutual information is utilized to directly modify the Baum-Welch statistics in order to extract a robust i-vector. Furthermore, a method for computing the frame-level speaker relevancy using deep neural network (DNN) analogous to the DNN used in robust automatic

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A Recommended Replacement Algorithm for the Scalable Asynchronous Cache Consistency Schemeleviate their associated problems. These challenges are inherited from the mobile environment because of low bandwidth, limited battery power, and mobile disconnectedness. Many caching techniques were presented in literature; however, Scalable Asynchronous Cache Consistency Scheme (SACCS) that prove

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Multiple Constraints Satisfaction-Based Reliable Localization for Mobile Underwater Sensor Networksrks (UWSNs). In a typical application, e.g. the ocean battlefields, the localization process has been no doubt constantly restricted by several kinds of uncertainty, which lead to obvious degradation of localization reliability and accuracy, e.g. the confidence of reference information, the mobility

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A Comparison of Model Validation Techniques for Audio-Visual Speech Recognition systems. As ASR that uses only speech can be contaminated by environmental noise, in some applications it may improve performance to employ Audio-Visual Speech Recognition (AVSR), in which recognition uses both audio information and mouth movements obtained from a video recording of the speaker’s f

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Multi-focus Image Fusion Based on Non-subsampled Shearlet Transform and Sparse Representationsed on sparse representation and non-subsampled shearlet transform (NSST). Firstly, the source images are decomposed to low- and high-frequency coefficients by NSST. The sparse representation is then adopted to fuse the low-frequency coefficients. For the high-frequency coefficients, a maximum sum-m