Secure Two-Party Computation of Squared Euclidean Distances in the Presence of Malicious Adversaries

Author(s):  
Marc Mouffron ◽  
Frederic Rousseau ◽  
Huafei Zhu
Keyword(s):  
2021 ◽  
pp. 102986492110015
Author(s):  
Lindsey Reymore

This paper offers a series of characterizations of prototypical musical timbres, called Timbre Trait Profiles, for 34 musical instruments common in Western orchestras and wind ensembles. These profiles represent the results of a study in which 243 musician participants imagined the sounds of various instruments and used the 20-dimensional model of musical instrument timbre qualia proposed by Reymore and Huron (2020) to rate their auditory image of each instrument. The rating means are visualized through radar plots, which provide timbral-linguistic thumbprints, and are summarized through snapshot profiles, which catalog the six highest- and three lowest-rated descriptors. The Euclidean distances among instruments offer a quantitative operationalization of semantic distances; these distances are illustrated through hierarchical clustering and multidimensional scaling. Exploratory Factor Analysis is used to analyze the latent structure of the rating data. Finally, results are used to assess Reymore and Huron’s 20-dimensional timbre qualia model, suggesting that the model is highly reliable. It is anticipated that the Timbre Trait Profiles can be applied in future perceptual/cognitive research on timbre and orchestration, in music theoretical analysis for both close readings and corpus studies, and in orchestration pedagogy.


2021 ◽  
pp. 1-1
Author(s):  
Rahmad Sadli ◽  
Mohamed Afkir ◽  
Abdenour Hadid ◽  
Atika Rivenq ◽  
Abdelmalik Taleb-Ahmed

2018 ◽  
Vol 12 (2) ◽  
pp. 21-29 ◽  
Author(s):  
Anoop Mayampurath ◽  
Christopher Ward ◽  
John Fahrenbach ◽  
Cynthia LaFond ◽  
Michael Howell ◽  
...  

Objective: To investigate whether a patient’s proximity to the nurse’s station or ward entrance at time of admission was associated with increased risk of adverse outcomes. Method: We conducted a retrospective cohort study of consecutive adult inpatients to 13 medical–surgical wards at an academic hospital from 2009 to 2013. Proximity of admission room to the nurse’s station and to the ward entrance was measured using Euclidean distances. Outcomes of interest include development of critical illness (defined as cardiac arrests or transfer to an intensive care unit), inhospital mortality, and increase in length of stay (LOS). Results: Of the 83,635 admissions, 4,129 developed critical illness and 1,316 died. The median LOS was 3 days. After adjusting for admission severity of illness, ward, shift, and year, we found no relationship between proximity at admission to nurse’s station our outcomes. However, patients admitted to end of the ward had higher risk of developing critical illness (odds ratio [ OR] = 1.15, 95% confidence interval [CI] = [1.08, 1.23]), mortality ( OR = 1.16, 95% CI [1.03, 1.33]), and a higher LOS (13-hr increase, 95% CI [10, 15] hours) compared to patients admitted closer to the ward entrance. Similar results were observed in sensitivity analyses adjusting for isolation room patients and considering patients without room transfers in the first 48 hr. Conclusions: Our study suggests that being away from the nurse’s station did not increase the risk of these adverse events in ward patients, but being farther from the ward entrance was associated with increase in risk of adverse outcomes. Patient safety can be improved by recognizing this additional risk factor.


2021 ◽  
Vol 19 (1) ◽  
pp. e0401
Author(s):  
Marcos P. G. Rezende ◽  
Julio C. Souza ◽  
Carlos H. M. Malhado ◽  
Paulo L. S. Carneiro ◽  
Johnny I. M. Araujo ◽  
...  

Aim of study: Sports involving horses have notable financial importance. Breeds are evaluated to find the best-suited ones for a specific sport category. Phenotypic diversity using biometric markers was evaluated for Quarter Horse (QH), Arabic (AR), English Thoroughbred (ET), and Brazilian Equestrian (BE) horse breeds.Area of study: Mato Grosso do Sul-Brazil.Material and methods: Lengths, widths, and circumference measures of 268 horses were collected. These measures were used to estimate conformation indexes. The size-free canonical discriminant analysis was used to remove the size effect on the animal's shape. The similarity among breeds (by sex) was evaluated employing multivariate analysis (canonical analysis, MANOVA, principal components, Euclidean distances, and grouping through complete linkage), considering all linear measures and conformation indexes (included in the analysis of principal components).Main results: Four canonical variables (CANs), each one representing an equation to interpret the morpho-functionality of breeds “sustentation”, “structure”, “frame”, and “equilibrium”, were retained. The breeds presented differences when the CANs were simultaneously considered. Differences mainly were the size and the thickness of the body as well as the ability of the animal to move. ET, QH, and BE demonstrate a well-defined biometric profile. These three breeds clustered separately from AR breed.Research highlights: Canonical variables allow to verify the functional aptitudes since the responses were close to conformation indices commonly used as horse skill estimators. The implementation of these variables as selection criteria in horse breeding programs require further studies in larger populations of horses for a confirmation of the present results.


2021 ◽  
Vol 14 (2) ◽  
pp. 26
Author(s):  
Na Li ◽  
Lianguan Huang ◽  
Yanling Li ◽  
Meng Sun

In recent years, with the development of the Internet, the data on the network presents an outbreak trend. Big data mining aims at obtaining useful information through data processing, such as clustering, clarifying and so on. Clustering is an important branch of big data mining and it is popular because of its simplicity. A new trend for clients who lack of storage and computational resources is to outsource the data and clustering task to the public cloud platforms. However, as datasets used for clustering may contain some sensitive information (e.g., identity information, health information), simply outsourcing them to the cloud platforms can't protect the privacy. So clients tend to encrypt their databases before uploading to the cloud for clustering. In this paper, we focus on privacy protection and efficiency promotion with respect to k-means clustering, and we propose a new privacy-preserving multi-user outsourced k-means clustering algorithm which is based on locality sensitive hashing (LSH). In this algorithm, we use a Paillier cryptosystem encrypting databases, and combine LSH to prune off some unnecessary computations during the clustering. That is, we don't need to compute the Euclidean distances between each data record and each clustering center. Finally, the theoretical and experimental results show that our algorithm is more efficient than most existing privacy-preserving k-means clustering.


2021 ◽  
Vol 15 ◽  
Author(s):  
Paolo Finotelli ◽  
Carlo Piccardi ◽  
Edie Miglio ◽  
Paolo Dulio

In this paper, we propose a graphlet-based topological algorithm for the investigation of the brain network at resting state (RS). To this aim, we model the brain as a graph, where (labeled) nodes correspond to specific cerebral areas and links are weighted connections determined by the intensity of the functional magnetic resonance imaging (fMRI). Then, we select a number of working graphlets, namely, connected and non-isomorphic induced subgraphs. We compute, for each labeled node, its Graphlet Degree Vector (GDV), which allows us to associate a GDV matrix to each one of the 133 subjects of the considered sample, reporting how many times each node of the atlas “touches” the independent orbits defined by the graphlet set. We focus on the 56 independent columns (i.e., non-redundant orbits) of the GDV matrices. By aggregating their count all over the 133 subjects and then by sorting each column independently, we obtain a sorted node table, whose top-level entries highlight the nodes (i.e., brain regions) most frequently touching each of the 56 independent graphlet orbits. Then, by pairwise comparing the columns of the sorted node table in the top-k entries for various values of k, we identify sets of nodes that are consistently involved with high frequency in the 56 independent graphlet orbits all over the 133 subjects. It turns out that these sets consist of labeled nodes directly belonging to the default mode network (DMN) or strongly interacting with it at the RS, indicating that graphlet analysis provides a viable tool for the topological characterization of such brain regions. We finally provide a validation of the graphlet approach by testing its power in catching network differences. To this aim, we encode in a Graphlet Correlation Matrix (GCM) the network information associated with each subject then construct a subject-to-subject Graphlet Correlation Distance (GCD) matrix based on the Euclidean distances between all possible pairs of GCM. The analysis of the clusters induced by the GCD matrix shows a clear separation of the subjects in two groups, whose relationship with the subject characteristics is investigated.


2012 ◽  
Vol 10 (2) ◽  
pp. 417-424 ◽  
Author(s):  
Nara Tadini Junqueira ◽  
Cecília Gontijo Leal ◽  
Carlos Bernardo Mascarenhas Alves ◽  
Paulo Santos Pompeu

The rio das Velhas, located in central Minas Gerais State (Brazil), is a major tributary of the rio São Francisco. Despite several anthropogenic pressures, this basin supports more than 115 fish species. The aim of this study was to compare the morphological space occupied by fish assemblages in four regions (headwaters, upper, middle, and lower course) along the channel of the rio das Velhas. We try to answer the following question: Is there a change in the morphological organization of the fish along the longitudinal gradient of the river? Individuals from 67 species, collected at several sites in the basin from 1999 to 2008, were measured for 11 morphological attributes related to swimming behavior and habitat use. Through the graphs, the first two dimensions of the PCA suggest that the morphological volume occupied by the headwaters region is smaller than the other sections, because of the low richness of the site. However, morphological hypervolumes of the four reaches analyzed by Euclidean distances were not statistically different. The results indicated that only the density of morphological types increases along the rio das Velhas, and there is no difference between the headwaters and upper courses. Therefore, in order to use functional groups related to the morphology of the species as tools to take measures for the conservation and revitalization of the rio das Velhas, it is necessary analyze the density of species within these groups, as well as their composition.


Networks ◽  
1978 ◽  
Vol 8 (4) ◽  
pp. 297-314 ◽  
Author(s):  
B. L. Golden ◽  
M. Ball

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