A virtual workspace for hybrid multidimensional scaling algorithms

In visualising multidimensional data, it is well known that different types of algorithms to process them. Data sets might be distinguished according to volume, variable types and distribution, and each of these characteristics imposes constraints upon the choice of applicable algorithms for their visualization. Previous work has shown that a hybrid algorithmic approach can be successful in addressing the impact of data volume on the feasibility of multidimensional scaling (MDS). This suggests that hybrid combinations of appropriate algorithms might also successfully address other characteristics of data. This paper presents a system and framework in which a user can easily explore hybrid algorithms and the data flowing through them. Visual programming and a novel algorithmic architecture let the user semi-automatically define data flows and the co-ordination of multiple views

A visual workspace for constructing hybrid MDS algorithms and coordinating multiple views

Data can be distinguished according to volume, variable types and distribution, and each of these characteristics imposes constraints upon the choice of applicable algorithms for their visualisation. This has led to an abundance of often disparate algorithmic techniques. Previous work has shown that a hybrid algorithmic approach can be successful in addressing the impact of data volume on the feasibility of multidimensional scaling (MDS). This paper presents a system and framework in which a user can easily explore algorithms as well as their hybrid conjunctions and the data flowing through them. Visual programming and a novel algorithmic architecture let the user semi-automatically define data flows and the co-ordination of multiple views of algorithmic and visualisation components. We propose that our approach has two main benefits: significant improvements in run times of MDS algorithms can be achieved, and intermediate views of the data and the visualisation program structure can provide greater insight and control over the visualisation process

Visualisation techniques for users and designers of layout algorithms

Visualisation systems consisting of a set of components through which data and interaction commands flow have been explored by a number of researchers. Such hybrid and multistage algorithms can be used to reduce overall computation time, and to provide views of the data that show intermediate results and the outputs of complementary algorithms. In this paper we present work on expanding the range and variety of such components, with two new techniques for analysing and controlling the performance of visualisation processes. While the techniques presented are quite different, they are unified within HIVE: a visualisation system based upon a data-flow model and visual programming. Embodied within this system is a framework for weaving together our visualisation components to better afford insight into data and also deepen understanding of the process of the data's visualisation. We describe the new components and offer short case studies of their application. We demonstrate that both analysts and visualisation designers can benefit from a rich set of components and integrated tools for profiling performance

A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

The need to analyze large amounts of multivariate data raises the fundamental problem of dimensionality reduction which is defined as a process of mapping data from high-dimensional space into low-dimensional. One of the most popular methods for handling this problem is multidimensional scaling. Due to the technological advances, the dimensionality of the input data as well as the amount of processed data is increasing steadily but the requirement of processing these data within a reasonable time frame still remains an open problem. Recent development in graphics hardware allows to perform generic parallel computations on powerful hardware and provides an opportunity to solve many time-constrained problems in both graphical and non-graphical domain. The purpose of this survey is to describe and analyze recent implementations of multidimensional scaling algorithms on graphics processing units and present the applicability of these algorithms on such architectures based on the experimental results which show a decrease of execution time for multi-level approaches

Visualizing Profiles of Large Datasets of Weighted and Mixed Data

This work provides a procedure with which to construct and visualize profiles, i.e., groups of individuals with similar characteristics, for weighted and mixed data by combining two classical multivariate techniques, multidimensional scaling (MDS) and the k-prototypes clustering algorithm. The well-known drawback of classical MDS in large datasets is circumvented by selecting a small random sample of the dataset, whose individuals are clustered by means of an adapted version of the k-prototypes algorithm and mapped via classical MDS. Gower’s interpolation formula is used to project remaining individuals onto the previous configuration. In all the process, Gower’s distance is used to measure the proximity between individuals. The methodology is illustrated on a real dataset, obtained from the Survey of Health, Ageing and Retirement in Europe (SHARE), which was carried out in 19 countries and represents over 124 million aged individuals in Europe. The performance of the method was evaluated through a simulation study, whose results point out that the new proposal solves the high computational cost of the classical MDS with low error.This research was funded by the Spanish Ministry of Economy and Competitiveness, grant number MTM2014-56535-R; and the V Regional Plan for Scientific Research and Technological Innovation 2016-2020 of the Community of Madrid, an agreement with Universidad Carlos III de Madrid in the action of "Excellence for University Professors.

The Energy Landscape, Folding Pathways and the Kinetics of a Knotted Protein

The folding pathway and rate coefficients of the folding of a knotted protein are calculated for a potential energy function with minimal energetic frustration. A kinetic transition network is constructed using the discrete path sampling approach, and the resulting potential energy surface is visualized by constructing disconnectivity graphs. Owing to topological constraints, the low-lying portion of the landscape consists of three distinct regions, corresponding to the native knotted state and to configurations where either the N- or C-terminus is not yet folded into the knot. The fastest folding pathways from denatured states exhibit early formation of the N-terminus portion of the knot and a rate-determining step where the C-terminus is incorporated. The low-lying minima with the N-terminus knotted and the C-terminus free therefore constitute an off-pathway intermediate for this model. The insertion of both the N- and C-termini into the knot occur late in the folding process, creating large energy barriers that are the rate limiting steps in the folding process. When compared to other protein folding proteins of a similar length, this system folds over six orders of magnitude more slowly.Comment: 19 page

Coordinating views for data visualisation and algorithmic profiling

A number of researchers have designed visualisation systems that consist of multiple components, through which data and interaction commands flow. Such multistage (hybrid) models can be used to reduce algorithmic complexity, and to open up intermediate stages of algorithms for inspection and steering. In this paper, we present work on aiding the developer and the user of such algorithms through the application of interactive visualisation techniques. We present a set of tools designed to profile the performance of other visualisation components, and provide further functionality for the exploration of high dimensional data sets. Case studies are provided, illustrating the application of the profiling modules to a number of data sets. Through this work we are exploring ways in which techniques traditionally used to prepare for visualisation runs, and to retrospectively analyse them, can find new uses within the context of a multi-component visualisation system

Mercury concentration and speciation in coastal rainwater

Mercury exists in mainly two oxidation states in the atmosphere, Hg0 and Hg(II). Inorganic divalent mercury, Hg(II), has a greater solubility; therefore is in higher concentration in rainwater, than Hg0. The toxic species, methylmercury is an organic form of Hg(II) and is present in low concentration. Mercury is released into the atmosphere by natural and anthropogenic sources. Rainwater is thought to be a main removal mechanism for atmospheric mercury. The concentration and speciation of mercury were determined in rainwater from Wilmington, NC, from September 1, 2003 to September 30, 2005. Volume weighted averages for total Hg in unfiltered rainwater, total dissolved Hg, particulate Hg, dissolved gaseous Hg (Hg0) and methyl-Hg were 52.9 ± 4.7 pM, 40.6 ± 4.0 pM, 13.7± 1.5 pM, 4.3 ± 0.9 pM and 1.1 ± 0.1 pM, respectively. All mercury species were present in all seasons with no significant difference in concentrations between summer and winter, except dissolved gaseous mercury concentration was higher in the winter, with a higher ratio of Hg(II)/Hg(0) in summer relative to winter events. Diurnal variation was seen where Hg(II) decreased during the day into the night, suggesting photochemical reduction of Hg(II). All Hg concentrations were higher in continental storms relative to coastal rain events. Both total mercury species (UFHg and TDHg) were positively correlated with particulate mercury. Total mercury species were washed out of the atmosphere by rainwater with lower concentrations for larger rain events. A weak positive correlation was observed between TDHg and NO3 -, TDHg and SO4 2-, DGHg and Cl-, and Hgpart and DOC. The photochemistry of mercury from Wilmington was also investigated. UFHg, TDHg, and DGHg were generally produced upon irradiation of rainwater samples by simulated sunlight. Particulate Hg concentrations generally declined upon irradiation and MMHg concentrations showed no pattern, in some instances, increasing, decreasing or remaining the same. Positive correlation was observed between, production of UFHg and Hgpart and a negative correlation was observed between production of TDHg and Hgpart. Continental events increased in Hgpart while decreasing in TDHg, whereas coastal events increased in TDHg while decreasing in Hgpart after irradiation. Seasonal differences between Hg species were similar with an increase in TDHg and DGHg, while decreasing in Hgpart and greater changes were observed during the winter. Diurnal variations of Hg(II)/Hg(0) ratio increased during the afternoon and decreased there after. Atmospheric global inputs by natural and anthropogenic sources, 4.1 x 106 kg or 2.0 x 107 mol per year, were in good agreement with calculated total flux of mercury removed via wet deposition, 3.8 x 106 kg or 1.9 x 107 mol per year, suggesting that essentially all mercury released into the atmosphere is removed via rain

Changes in the distribution and density of Florida Bay macrophytes: 1995-2004

Benthic macrophyte cover and distribution data have been collected in ten basins within Florida Bay since 1995 as part of the Florida Bay Fisheries Habitat Assessment Program (FHAP). A weighted average for the most prevalent macrophytes during each sampling event since spring 1995 was calculated. Results indicate that the three most common seagrasses observed in Florida Bay, Thalassia testudinum, Halodule wrightii, and Syringodium filiforme, have increased in distribution since 1995. Halodule wrightii and Syringodium filiforme exhibited an increase in both frequency and cover at the bay-scale, an occurrence driven by their dramatic increases in the western-most FHAP study basins: Johnson and Rabbit Key Basins. Acetabularia, Batophora, Halimeda, and Penicillus also exhibited increases in both frequency and cover since spring 1995. The drift Rhodophytes increased in density and distribution between spring 1995 and spring 1998, but did not increase further after that time. Batophora proved to be the most ubiquitous macroalgae throughout Florida Bay and Acetabularia and the drift Rhodophytes showed the strongest seasonal fluctuations, as they were both much more abundant and widespread during spring samplings. Spearman rank order correlation analysis of the Braun-Blanquet cover data showed that Thalassia was generally negatively correlated to all other macrophytes, while Halodule, Halophila, and Syringodium were positively correlated to one another on most occasions. These seagrasses fluctuated between positive and negative correlations with the macroalgae, and as a group, the macroalgae were positively correlated with one another on most occasions, although exceptions did apply. Non-metric multidimensional scaling was used to create ordination plots of the ~ 315 sample stations. Density overlays were used in conjunction with these ordination plots, and together these showed that total seagrass cover and total macroalgal cover were generally mutually exclusive. Spearman rank order correlation analysis was further used to determine if this spatial separation of the two macrophyte groups was statistically significant at the bay-scale, and it was found that 11 of the 18 bi-annual sampling events yielded a statistically significant negative correlation between total seagrass cover and total macroalgae cover. Canonical Correspondence Analysis (CCA) was used to determine which, if any, of the environmental/physical variables, collected as part of the FHAP data set, had a significant effect on macrophyte distribution within Florida Bay. Significance of these effects was determined using Monte Carlo Permutation Tests. CCA showed that depth and visibility were the initial driving forces in macrophyte distribution. During fall 2000, however, a spike in salinity was observed and by spring 2001 this became the most significant variable affecting macrophyte distribution, and it remained so, along with depth, throughout the duration of FHAP