Search results for "Network science"

Structural Analogies in Annelid Erythrocruorins

1986

Erythrocruorins from many annelid species have been studied by many authors. In spite of the great similarity of most physicochemical properties and of the electron-micrographs of these proteins, some debated experimental data divide the scientific community, e.g. the Mr of the whole molecule (ranging from 2,500 to 4,1000 kDa) and, in consequence, the Mr of the 1/12 molecules, the Mr and number of the smallest covalently bound subunits and the Mr and number of the globin-like monomers (1).

Family Reciprocity and Caring Relationships in Ageing Societies

2010

The legal balance between liberty and equality

2021

The paper explores the specific legal balance between liberty and equality, distinguishing it from political theories and constitutional settings, where they are often considered in opposition. In order to find the specific legal balance between liberty and equality, and after identifying some of their relevant meanings for the purpose, it becomes necessary to focus on the rule of law, and to examine the relationship between liberty and equality in its different versions. Once the core meaning of the rule of law in terms of liberty and equality is enucleated, it is possible to consider extending it to the international field.

New Trends in Graph Mining

2010

Searching for repeated features characterizing biological data is fundamental in computational biology. When biological networks are under analysis, the presence of repeated modules across the same network (or several distinct ones) is shown to be very relevant. Indeed, several studies prove that biological networks can be often understood in terms of coalitions of basic repeated building blocks, often referred to as network motifs.This work provides a review of the main techniques proposed for motif extraction from biological networks. In particular, main intrinsic difficulties related to the problem are pointed out, along with solutions proposed in the literature to overcome them. Open ch…

Perceptual similarity between color images using fuzzy metrics

2016

A method to measure the similarity between color images is proposed.Correlation among the color image channels is taken into account.Proposed similarity measure is based on fuzzy metrics because of their advantages.The proposal matches well with the perceptual visual similarity between color images. In many applications of the computer vision field measuring the similarity between (color) images is of paramount importance. However, the commonly used pixelwise similarity measures such as Mean Absolute Error, Peak Signal to Noise Ratio, Mean Squared Error or Normalized Color Difference do not match well with perceptual similarity. Recently, it has been proposed a method for gray-scale image s…

New structural parameters of fullerenes for principal component analysis

2003

The Kekule structure count and the permanent of the adjacency matrix of fullerenes are related to structural parameters involving the presence of contiguous pentagons p, q, r, q/p and r/p, where p is the number of edges common to two pentagons, q is the number of vertices common to three pentagons and r is the number of pairs of nonadjacent pentagons adjacent to another common pentagon. The cluster analysis of the structural parameters allows classification these parameters. Principal component analysis (PCA) of the structural parameters and the cluster analyses of the fullerenes permit their classification. PCA clearly distinguishes five classes of fullerenes. The cluster analysis of fulle…

A Similarity Evaluation Technique for Cooperative Problem Solving with a Group of Agents

1999

Evaluation of distance or similarity is very important in cooperative problem solving with a group of agents. Distance between problems is used by agents to recognize nearest solved problems for a new problem, distance between solutions is necessary to compare and evaluate the solutions made by different agents, and distance between agents is useful to evaluate weights of the agents to be able to integrate them by weighted voting. The goal of this paper is to develop a similarity evaluation technique to be used for cooperative problem solving with a group of agents. Virtual training environment used for this goal is represented by predicates that define relationships within three sets: prob…

SCCF Parameter and Similarity Measure Optimization and Evaluation

2019

Neighborhood-based Collaborative Filtering (CF) is one of the most successful and widely used recommendation approaches; however, it suffers from major flaws especially under sparse environments. Traditional similarity measures used by neighborhood-based CF to find similar users or items are not suitable in sparse datasets. Sparse Subspace Clustering and common liking rate in CF (SCCF), a recently published research, proposed a tunable similarity measure oriented towards sparse datasets; however, its performance can be maximized and requires further analysis and investigation. In this paper, we propose and evaluate the performance of a new tuning mechanism, using the Mean Absolute Error (MA…

Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.

2007

Abstract Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rath…

Least-squares community extraction in feature-rich networks using similarity data

2021

We explore a doubly-greedy approach to the issue of community detection in feature-rich networks. According to this approach, both the network and feature data are straightforwardly recovered from the underlying unknown non-overlapping communities, supplied with a center in the feature space and intensity weight(s) over the network each. Our least-squares additive criterion allows us to search for communities one-by-one and to find each community by adding entities one by one. A focus of this paper is that the feature-space data part is converted into a similarity matrix format. The similarity/link values can be used in either of two modes: (a) as measured in the same scale so that one may …