In this paper, modular neural network (MNN) inversion has been applied for the parameters approximation of the gravity anomaly causative target. The trained neural network is used for estimating the amplitude coefficient and depths to the top and bottom of a finite vertical cylinder source. The results of the applied neural network method are compared with the results of the least-squares stand...

The use of Saccharomyces cerevisiae mnn mutants has facilitated the study of the epitopes recognized by antisera against several antigenic factors of the genus Candida (Candida Check; Iatron Laboratories, Tokyo, Japan). We have taken advantage of the very well characterized structure of the mannans of the different mnn mutants to compare their reactivities with the factor antisera used in the i...

This paper proposes the Mesh Neural Network (MNN), a novel architecture which allows neurons to be connected in any topology, efficiently route information. In MNNs, information is propagated between throughout state transition function. State and error gradients are then directly computed from updates without backward computation. The MNN propagation schema formalized derived tensor algebra. p...

There is significant interest worldwide to identify new antiferromagnetic materials suitable for device applications. Key requirements such are: relatively high magnetocrystalline anisotropy constant, low cost, corrosion resistance and the ability induce a large exchange bias, i.e., loop shift, when grown adjacent ferromagnetic layer. In this article, review of recent developments on novel mate...

The title complex, [Mn(C(5)O(5))(C(12)H(8)N(2))(2)], lies across a crystallographic twofold axis which passes through the Mn atom and bisects the croconate ligand. The two 1,10-phenanthroline (phen) ligands are arranged in a propeller manner and the local mol-ecular geometry of the MnN(4)O(2) unit is severely distorted octa-hedral. This may be inter-preted as a structural perturbation of the Mn...

We study the mixing time of a Markov chain Mnn on permutations that performs nearest neighbor transpositions in the non-uniform setting, a problem arising in the context of self-organizing lists. We are given “positively biased” probabilities {pi,j ≥ 1/2} for all i < j and let pj,i = 1− pi,j . In each step, the chain Mnn chooses two adjacent elements k, and ` and exchanges their positions with ...

In a mobile network environment, a Mobile Router (MR) has multiple communication interfaces to the Internet. It switches between or simultaneously uses these interfaces, causing network conditions within the MR to change. If the network conditions were shared with between nodes behind the MR (MNN) and their correspondent nodes (CN), it would be possible for applications to change its behavior a...

In this paper, a Multi-Negotiation Network (MNN) and a MultiNegotiation Influence Diagram (MNID) are proposed to optimally handle Multiple Related Negotiations (MRN) in a multi-agent system. Most popular, state-of-theart approaches perform MRN sequentially. However, a sequential procedure may not optimally execute MRN in terms of maximizing the global outcome, and may even lead to unnecessary l...

This paper examines neutrality, understood as a necessary requirement for law’s legitimacy. In the conventional, liberal formulation of it, law must neither favor nor depend on any particular conception good. Taking into consideration critique that principle neutrality has received, from within liberalism well rival perspectives, authors search an alternative. The proposed solution is Model Neu...

This paper presents an empirical evaluation of a number of recently developed Automatic Target Recognition algorithms for Forward-Looking Infrared (FLIR) imagery using a large database of real FLIR images. The algorithms evaluated are based on convolutional neural networks (CNN), principal component analysis (PCA), linear discriminant analysis (LDA), learning vector quantization (LVQ), modular ...