Artificial neural networks have proven to be an attractive mathematical tool to represent complex relationships in many branches of hydrology. Due to this attractive feature, neural networks are increasingly being applied in subsurface modeling where intricate physical processes and lack of detailed field data prevail. In this paper, a methodology using modular neural networks (MNN) is proposed...

Mental nerve neuropathy (MNN) or "numb chin syndrome" is a rare neurologic symptom most often associated with malignancy. Patients typically develop paresthesia or numbness localized to the chin and lower lip and will often seek care at their local emergency department. Pain and expansion of the lower jaw may also be present. We report a case of MNN associated with a metastatic lesion in the ma...

A sandwich-structured flexible supercapacitor electrode has been developed based on MnO2 nanonest (MNN) modified ionic liquid (IL) functionalized graphene paper (GP), which is fabricated by functionalizing graphene nanosheets with an amine-terminated IL (i.e., 1-(3-aminopropyl)-3-methylimidazolium bromide) to form freestanding IL functionalized GP (IL-GP), and then modifying IL-GP with a unique...

We describe in this paper the evolution of modular neural networks using hierarchical genetic algorithms for pattern recognition. Modular Neural Networks (MNN) have shown significant learning improvement over single Neural Networks (NN). For this reason, the use of MNN for pattern recognition is well justified. However, network topology design of MNN is at least an order of magnitude more diffi...

Purpose Exposure to various stressors, including psychological, metabolic, and immune, in the perinatal period induces long-lasting effects in physiological function and increase the risk of metabolic disorders in later life. In the present study, sexual maturation and sexual behavior were assessed in prenatally undernourished mature male rats. Methods All the pregnant rats were divided into ...

The use of \global neural networks" (as the back propagation neural network) and \clustering neural networks" (as the radial basis function neural network) leads each other to diierent advantages and inconvenients. The combination of the desirable features ot those two neural ways of computation is achieved by the use of Modular Neural Networks (MNN). In addition, a considerable advantage can e...

Morphological Neural Networks (MNN) have been proposed as associative memories (with its two cases: autoassociative and heteroassociative). In this paper we are involved with Heteroassociative MNN (HMNN). We propose their use for selflocalization in a vision-based navigation framework for mobile robots. HMNN can be trained in a single computation step. Their storage capacity bound is the dimens...

F rom an evolutionary perspective, facial expressions of fear convey highly recognizable emotional signals that serve adaptive functions by promoting survival and reproductive success (1). Current theories of how the brain interprets facial expressions of fear implicate the mirror neuron network (MNN) in echoing the emotional states of others by internal simulation (2,3). Originally discovered ...

To better support forest sustainable management, this paper explores the technical framework for forest health assessment, and then focuses on how to better execute the evaluation part of this technical framework. Modular neural networks (MNN) have been shown to be more efficient for classification problems than the conventional monolithic artificial neural network. Therefore, this was used in ...

The inorganic layered crystal (ILC) MoS2 in low dimensions is considered as one of the most promising and efficient semiconductors. To enable the magnetism and keep intrinsic crystal structures, we carried out a first-principles study of the magnetic and semiconductive monolayer MoS2 adsorbed with the Mnn (n = 1-4) clusters, and bilayer MoS2 intercalated with the same clusters. Geometric optimi...