The complicated and changeable underwater environment increases the difficulty of pattern recognition for robotic fish swimming gaits. Aiming at this question, environment sensing and pattern recognition using an artificial lateral system are investigated in this work. Imitating lateral line of real fish in nature, a novel artificial lateral line system for robotic fish is designed in this pape...

Objective: Soil temperature serves as a key variable in hydrological investigations to determine soil moisture content as well as hydrological balance in watersheds. The ingoing research aims to shed lights on potential of artificial neural networks (ANNs) and Neuro-Fuzzy inference system (ANFIS) to simulate soil temperature at 5-100 cm depths. To satisfy this end, climatic and...

Shear wave velocity (Vs) data are key information for petrophysical, geophysical and geomechanical studies. Although compressional wave velocity (Vp) measurements exist in almost all wells, shear wave velocity is not recorded for most of elderly wells due to lack of technologic tools. Furthermore, measurement of shear wave velocity is to some extent costly. This study proposes a novel methodolo...

Here we describe a reliable method for isolating genes that are differentially expressed in two cell populations. The method is a combination of subtractive hybridization and PCR. Among many improvements to previously described methods is the incorporation of a new technology into the procedure which sterilizes(inactivates) PCR amplicons, and thereby overcomes the limitation of similar procedur...

We extend the subtractive imaging method to label-free second harmonic generation (SHG) microscopy to enhance the spatial resolution and contrast. This method is based on the intensity difference between two images obtained with circularly polarized Gaussian and doughnut-shaped beams, respectively. By characterizing the intensity and polarization distributions of the two focused beams, we verif...

On the basis of chaotic features frequency hopping signal, band prediction for signal can enhance interference effect greatly. However, poor accuracy often limits its development in military field. Therefore, sake enhancing this paper studies radial function (RBF) neural network model based on gradient descent method and improved particle swarm optimization algorithm, respectively. The former u...

ontology is the main infrastructure of the semantic web which provides facilities for integration, searching and sharing of information on the web. development of ontologies as the basis of semantic web and their heterogeneities have led to the existence of ontology matching. by emerging large-scale ontologies in real domain, the ontology matching systems faced with some problem like memory con...

In this paper we introduce an advanced mean field method to correct the inherent bias of conventional subtractive interference cancellation in Code Division Multiple Access (CDMA). In simulations, we get a performance quite close to that of the individual optimal exponential complexity detector and significant improvements over current state-of-the-art subtractive interference cancellation in a...

In this study, an efficient method is introduced to predict the stability of soil-structure interaction (SSI) system subject to earthquake loads. In the procedure of the nonlinear dynamic analysis, a number of structures collapse and then lose their stability. The prediction of failure probability is considered as stability criterion. In order to achieve this purpose, a modified adaptive neuro ...

This work presents an approach on high-level semantic feature detection in video sequences. Keyframes are selected to represent the visual content of the shots. Then, low-level feature extraction is performed on the keyframes and a feature vector including color and texture features is formed. A region thesaurus that contains all the high-level features is constructed using a subtractive cluste...