Nowadays, the speed up development and use of digital devices such as smartphones have put people at risk internet crimes. The evidence present crimes in a computer file can be easily unreachable by changing prefix or other algorithms. In more complex cases, either divided into different parts that has information about type are deleted, where fragment recognition issue is discussed. known file...

In this paper a diagnostic model based on Naive Bayes developed to diagnose erytemato squamous diseases. The hybrid feature selection method, named IGSBFS (Information Gain and Sequential Backward Floating Search), combines the advantages of filters and wrappers to select the optimal feature subset from the original feature set. In IGSBFS, Information Gain acts as filters to remove redundant fe...

Nitrate leaching losses from arable lands into groundwater were a main driver in designating Vulnerable Zones (NVZs) according to the Nitrates Directive, with view enhancing their water quality. Despite this, developing common strategies for effective quality control these areas remains challenge European Union. This paper evaluates performance of Random Forest (RF) machine learning algorithm c...

Multi-channel Gabor filters (MGFs) and Markov random fields (MRFs) are two common methods for texture analysis. This paper investigates their integration through a novel algorithm using the neighborhood-oscillating tabu search (NOTS) for high-resolution image classification. The NOTS algorithm fuses the texture features extracted by MGF and MRF. This algorithm has been compared with classical m...

A large number of algorithms have been proposed for feature subset selection. Our experimental results show that the sequential forward oating selection (SFFS) algorithm, proposed by Pudil et al., dominates the other algorithms tested. We study the problem of choosing an optimal feature set for land use classi cation based on SAR satellite images using four di erent texture models. Pooling feat...

This paper focuses on enhancing the effectiveness of filter feature selection models from two aspects. First, feature-searching engine is modified based on optimization theory. Second, a point injection strategy is designed to improve the regularization capability of feature selection. The second topic is important, because overfitting is usually experienced. To evaluate the proposed strategies...

Floating-point division is generally regarded as a low frequency, high latency operation in typical floating-point applications.So due to this not much development had taken place in this field. But nowadays floating point divider has become indispensable and increasingly important in many modern applications. Most of the previous implementation required much larger area and latencies. In this ...