Models of biochemical networks are frequently complex and high-dimensional. Reduction methods that preserve important dynamical properties are therefore essential for their study. Interactions in biochemical networks are frequently modeled using Hill functions ([Formula: see text]). Reduced ODEs and Boolean approximations of such model networks have been studied extensively when the exponent [F...

Uncovering community structures is important for understanding networks. Currently, several nonnegative matrix factorization algorithms have been proposed for discovering community structure in complex networks. However, these algorithms exhibit some drawbacks, such as unstable results and inefficient running times. In view of the problems, a novel approach that utilizes an initialized Bayesian...

In much of the current literature on supply chain management, supply networks are recognized as a system. In this paper, we take this observation to the next level by arguing the need to recognize supply networks as a complex adaptive system (CAS). We propose that many supply networks emerge rather than result from purposeful design by a singular entity. Most supply chain management literature ...

Abstract In large biomolecular systems such as protein complexes, there are huge numbers of combinations inter-residue interactions whose comprehensive analyses often beyond the intuitive processing by researchers. Here we propose a computational method to allow for systematic analysis these based on fragment molecular orbital calculations, in which inter-fragment interaction energies comprehen...

Face is an important biometric feature for personal identification. This paper describes a new face verification methods based on singular value decomposition and RBF neural networks. The proposed method utilizes the positive samples and negative samples learning ability of RBF neural networks to improve singular values based face verification. Experiment results show that the novel face verifi...

The particle size control of drug is one of the most important factors affecting the efficiency of the nano-drug production in confined liquid impinging jets. In the present research, for this investigation the confined liquid impinging jet was used to produce nanoparticles of Carbamazepine. The effects of several parameters such as concentration, solution and anti-solvent flow rate and solvent...

Abstract Complex networks, which constitute the main subject of network science, have been wide and extensively adopted for representing, characterizing, modeling an ample range structures phenomena from both theoretical applied perspectives. The present work describes application real-valued Jaccard coincidence similarity indices translating generic datasets into networks. More specifically, t...