A Neural Network Approach to Identify Hyperspectral Image Content

A Hyperspectral is the imaging technique that contains very large dimension data with the hundreds of channels. Meanwhile, the Hyperspectral Images (HISs) delivers the complete knowledge of imaging; therefore applying a classification algorithm is very important tool for practical uses. The HSIs are always having a large number of correlated and redundant feature, which causes the decrement in the classification accuracy; moreover, the features redundancy come up with some extra burden of computation that without adding any beneficial information to the classification accuracy. In this study, an unsupervised based Band Selection Algorithm (BSA) is considered with the Linear Projection (LP) that depends upon the metric-band similarities. Afterwards Monogenetic Binary Feature (MBF) has consider to perform the ‘texture analysis’ of the HSI, where three operational component represents the monogenetic signal such as; phase, amplitude and orientation. In post processing classification stage, feature-mapping function can provide important information, which help to adopt the Kernel based Neural Network (KNN) to optimize the generalization ability. However, an alternative method of multiclass application can be adopt through KNN, if we consider the multi-output nodes instead of taking single-output node

eDify: Enhancing Teaching and Learning Process by Using Video Streaming Server

The study investigates the nature and degree of influence of the range of application usability variables on the learning experience of the students at a specific institution of higher education institution in Oman. The study was carried out via eDify implementation encompassing the usability variables and learning experience of the students. Literature does little to suggest the aforementioned relationship in the context of the Omani higher education. The current study would reveal the variables that are critical to effective technology-based learning of the students. The implications generated through the study would allow the institution involved in the study to effectively implement the variables required for enhanced teaching and learning. The methodology used in the study is divided into an exploratory and the main research. Principal component analysis and a range of regression analyses are conducted to test the relationships between the independent and the dependent variable, “learning experience”. Results suggest that the usability variables have both positive and significant effects on the dependent variable of the learning experience. One usability variable that stands out more than others is the usage of mobile media