Search results for "Network science"
showing 10 items of 103 documents
Trend Following with Momentum Versus Moving Average: A Tale of Differences
2018
Despite the ever-growing interest in trend following and a series of publications in academic journals, there is still a great shortage of theoretical results on the properties of trend following rules. Our paper fills this gap by comparing and contrasting the two most popular trend following rules, the Momentum (MOM) and Moving Average (MA) rules, from a theoretical perspective. Our approach is based on the return-based formulation of trading rules and modelling the price trends by an autoregressive return process. We provide theoretical results on the similarity between various trend following rules and the forecast accuracy of trading rules. Our results show that the similarity between t…
Comparison of wine discrimination with orthonasal and retronasal profilings. Application to Burgundy Pinot Noir wines
1999
Two sensory spaces, corresponding to the same wine sample profiled by nose (BN) and profiled by mouth (BM), were compared. The similarity between the two maps of product differences were measured by multivariate analysis, showing a good agreement and comparable product discrimination by the panel in the two modes, slightly in favor of BN discrimination. The superiority of one particular mode was not established from the comparison of individual performances BN versus BM, but differences between panelists and between descriptor use were found. Two-way canonical variate analysis of BN minus BM scores was also performed: the results revealed that panelists had higher influence than products in…
Integrating user preference to similarity queries over medical images datasets
2010
International audience; Large amounts of images from medical exams are being stored in databases, so developing retrieval techniques is an important research problem. Retrieval based on the image visual content is usually better than using textual descriptions, as they seldom gives every nuances that the user may be interested in. Content-based image retrieval employs the similarity among images for retrieval. However, similarity is evaluated using numeric methods, and they often orders the images by similarity in a way rather distinct from the user's intention. In this paper, we propose a technique to allow expressing the user's preference over attributes associated to the images, so simil…
Inference of Spatiotemporal Processes over Graphs via Kernel Kriged Kalman Filtering
2018
Inference of space-time signals evolving over graphs emerges naturally in a number of network science related applications. A frequently encountered challenge pertains to reconstructing such dynamic processes given their values over a subset of vertices and time instants. The present paper develops a graph-aware kernel-based kriged Kalman filtering approach that leverages the spatio-temporal dynamics to allow for efficient online reconstruction, while also coping with dynamically evolving network topologies. Laplacian kernels are employed to perform kriging over the graph when spatial second-order statistics are unknown, as is often the case. Numerical tests with synthetic and real data ill…
Combining similarity measures in content-based image retrieval
2008
The purpose of content based image retrieval (CBIR) systems is to allow users to retrieve pictures from large image repositories. In a CBIR system, an image is usually represented as a set of low level descriptors from which a series of underlying similarity or distance functions are used to conveniently drive the different types of queries. Recent work deals with combination of distances or scores from different and usually independent representations in an attempt to induce high level semantics from the low level descriptors of the images. Choosing the best method to combine these results requires a careful analysis and, in most cases, the use of ad-hoc strategies. Combination based on or…
An ab initio softness metric to measure the similarity between all pairs of amino acids
2010
Abstract The search for quantitative index of similarity between molecular moeties is important for its applications in pharmacology. Similarity is also an important concept in computational biology to measure the exchangeability of an amino acid by another in a protein sequence. In the present work, a distance between two molecules based on local and global softnesses of their fragments is defined. The method proposed is general and could be applied to any molecular library. It is first applied to compute the distance between the 190 pairs of different amino acids in their neutral states. Two amino acids belonging to the one of the biochemical class (aliphatic, sulfur-containing, acidic, ……
Social network analysis approaches to study crime
2022
Social Network Analysis (SNA) studies groups of individuals and can be applied in a lot of areas such us organizational studies, psychology, economics, information science and criminology. One of the most important results of SNA has been the definition of a set of centrality measures (e.g., degree, closeness, betweenness, or clustering coefficient) which can be used to identify the most influential people with respect to their network of relationships. The main problem with computing centrality metrics on social networks is the typical big size of the data. From the computational point of view, SNA represents social networks as graphs composed of a set of nodes connected by another set of …
Fuzzy Systems Based on Multispecies PSO Method in Spatial Analysis
2012
We present a method by using the hierarchical cluster-based Multispecies particle swarm optimization to generate a fuzzy system of Takagi-Sugeno-Kang type encapsulated in a geographical information system considered as environmental decision support for spatial analysis. We consider a spatial area partitioned in subzones: the data measured in each subzone are used to extract a fuzzy rule set of above mentioned type. We adopt a similarity index (greater than a specific threshold) for comparing fuzzy systems generated for adjacent subzones.
Can Avatar Appearance Influence Physical Activity? User-Avatar Similarity and Proteus Effects on Cardiac Frequency and Step Counts
2020
This study combined user-avatar similarity and Proteus effect predictions to incentivize physical activity. 305 participants ran while wearing accelerometers and a heart rate monitor. They were randomly assigned to onscreen motion-capturing avatars displaying either participant or stranger faces dressed in sports or formal clothes. Participants assigned to avatars displaying their own face showed increased cardiac frequency compared with those exposed to avatars with a stranger's face. Relative to the remaining conditions, participants assigned to avatars with their own face also wearing sports clothes showed increased cardiac frequency but participants assigned to avatars with a stranger's…
Community detection-based deep neural network architectures: A fully automated framework based on Likert-scale data
2020
[EN] Deep neural networks (DNNs) have emerged as a state-of-the-art tool in very different research fields due to its adaptive power to the decision space since they do not presuppose any linear relationship between data. Some of the main disadvantages of these trending models are that the choice of the network underlying architecture profoundly influences the performance of the model and that the architecture design requires prior knowledge of the field of study. The use of questionnaires is hugely extended in social/behavioral sciences. The main contribution of this work is to automate the process of a DNN architecture design by using an agglomerative hierarchical algorithm that mimics th…