This paper studies three techniques for outliers detection in the context of Wireless Sensor Networks, including a machine learning technique, a Principal Component Analysis-based methodology and an univariate statistics-based approach. The first methodology is based on a Least Squares-Support Vector Machine technique, together with a sliding window learning. A modification to this approach is ...

In this paper, Independent Component Analysis is considered for blind suppression of interference caused by bit-pulsed jamming in a direct sequence spread spectrum communication system. A framework for applying blind techniques to the jammer mitigation problem was earlier introduced in [1]. However, the scheme proposed there is based on second-order statistics only, and has serious practical li...

According to cognitive load theory, instructions can impose three types of cognitive load on the learner: intrinsic load, extraneous load, and germane load. Proper measurement of the different types of cognitive load can help us understand why the effectiveness and efficiency of learning environments may differ as a function of instructional formats and learner characteristics. In this article,...

since the birth of multi–spectral imaging techniques, there has been a tendency to consider and process this new type of data as a set of parallel gray–scale images, instead of an ensemble of an n–d realization. although, even now, some researchers make the same assumption, it is proved that using vector geometries leads to better results. in this paper, first a method is proposed to extract th...

as widespread deserts is located in west and southwest of iran plateau, dust storms form due to west andsouthwest systems over syria or iraq as well as arabian peninsula. these systems severely affect west and southwestregions. sometimes the fine dusts transmit to central, north east, and east regions. in this study for investigating dustysynoptical patterns, meteorological data at 5 synoptic s...

background: in order to check the practicality of classification of universities of medical sciences (umss) based on their infrastructures, and scientific contributions, this study explored the most appropriate indicators to measure the size and productivity of umss. methods: in the first phase, we approached a group of experts who had a deep experience in the management of umss and in the mini...

In this paper, we introduce a new method for steganalysis of grey-scale images. First, we analyzed the effect of various steganographic processes on the statistical properties of the image. So we extracted the optimal features from the images, which have high ability in make differentiated between two groups of normal and stego images. In this method, high order statistics in discrete wavelet t...

A receiver transforms correlated channel state information (CSI) to an uncorrelated sparse CSI vector by using a principal component analysis (PCA), and feeds it back to a transmitter. The PCA extracts essential information from the CSI without redundancy that arises from the highly correlated antennas. The transmitter then recovers the original CSI through the inverse transformation of the fee...

While it is now generally accepted that independent component analysis (ICA) is a good tool for isolating both artifacts and cognition-related processes in EEG data, there is little definite proof that data preprocessed using ICA is more effective than artifact rejection on raw channel data, especially when more subtle signal processing methods are used to detect artifacts. Here we applied five...