Clustering is unsupervised classification of patterns into groups. Neural networks are very useful tools for performing clustering. In this paper, we propose a new model for using artificial neural networks to perform clustering tasks on remotely sensed imagery. This model generates self-organizing maps (SOM) based on remotely sensed imagery and such related data as yield, nitrate, and moisture...

Soil moisture is one of the most important key physical parameters in hydrological and environmental processes. During the past decade, remote sensing measurements have been widely used to provide mean surface soil moisture on a large spatial scale because conventional ground based measurements are not always available and require more time and cost. However, very few studies have been conducte...

The 2010 Julius H. Comroe, Jr., Lecture of the American Physiological Society focuses on evolving ideas in chemoreception for CO₂/pH in terms of what is "sensed," where it is sensed, and how the sensed information is used physiologically. Chemoreception is viewed as involving neurons (and glia) at many sites within the hindbrain, including, but not limited to, the retrotrapezoid nucleus, the me...

We thank Dr Bhargava for careful reading of our article [1]. As highlighted by Dr Bhargava, Non Competitive Atrial Pacing (NCAP) algorithm is designed to prevent atrial arrhythmias by preventing atrial pacing within 300msec after a sensed atrial event in the post ventricular atrial refractory period (PVARP). The varying AV delays and fixed interval of 300msec between sensed atrial event (AR) in...

Image registration is a basic and important process for multi-sensor or multi-temporal remote sensing. In this letter, a new feature-based method named shape context is proposed for airborne multi-sensor image matching. This method has been found to be robust in handwritten digit and object recognition, and it is now introduced into remote sensing image matching after some adjustments. In the p...

Association rule mining is one of the most important problems of data mining. Since remotely sensed data contains huge amounts of information, it’s a very potent area to discover useful rules. Compared to traditional Market “basket data”, remote sensed imagery has specific characteristics and also presents specific difficulties. Two problems need to be solved to apply association rule mining on...

Fuzzy methods in remote sensing have received growing interest for their particular value in situations where the geographical phenomena are inherently fuzzy. A fuzzy approach is investigated for the classi® cation of sub-urban land cover from remote sensing imagery and the evaluation of classi® cation accuracy. Under the fuzzy strategy, fuzziness, intrinsic to both remotely sensed data and gro...

We consider a set of primary channels that operate in an unslotted fashion, switching activity at random times. A secondary user senses the primary channels searching for transmission opportunities. If a channel is sensed to be free, the secondary terminal transmits, and if sensed to be busy, the secondary transmitter remains silent. We solve the problem of determining the optimal time after wh...

Spectrum resources are facing huge demands and cognitive radio (CR) can improve the spectrum utilization. Recently, power spectral density (PSD) map is defined to enable the CR to reuse the frequency resources regarding to the area. For this reason, the sensed PSDs are fused by a Fusion Center (FC) which the sensed PSDs are collected by the distributed sensors in the area. But, for a given zone...