2,302 research outputs found
Faster subsequence recognition in compressed strings
Computation on compressed strings is one of the key approaches to processing
massive data sets. We consider local subsequence recognition problems on
strings compressed by straight-line programs (SLP), which is closely related to
Lempel--Ziv compression. For an SLP-compressed text of length , and an
uncompressed pattern of length , C{\'e}gielski et al. gave an algorithm for
local subsequence recognition running in time . We improve
the running time to . Our algorithm can also be used to
compute the longest common subsequence between a compressed text and an
uncompressed pattern in time ; the same problem with a
compressed pattern is known to be NP-hard
Improved Approximate String Matching and Regular Expression Matching on Ziv-Lempel Compressed Texts
We study the approximate string matching and regular expression matching
problem for the case when the text to be searched is compressed with the
Ziv-Lempel adaptive dictionary compression schemes. We present a time-space
trade-off that leads to algorithms improving the previously known complexities
for both problems. In particular, we significantly improve the space bounds,
which in practical applications are likely to be a bottleneck
A response to “Trends in tropical tree growth: re-analysis confirms earlier findings”
We recently demonstrated that growth trends from tree rings from Van der Sleen et al. (2015) and Groenendijk et al. (2015) are affected by demographic biases. In particular, clustered age distributions led to a negative bias in their growth trends. In a response, they challenge our analysis and present an alternative correction approach. We here show that their arguments are incorrect and based on misunderstanding of our analysis, and that their alternative approach does not work
A Faster Implementation of Online Run-Length Burrows-Wheeler Transform
Run-length encoding Burrows-Wheeler Transformed strings, resulting in
Run-Length BWT (RLBWT), is a powerful tool for processing highly repetitive
strings. We propose a new algorithm for online RLBWT working in run-compressed
space, which runs in time and bits of space, where
is the length of input string received so far and is the number of runs
in the BWT of the reversed . We improve the state-of-the-art algorithm for
online RLBWT in terms of empirical construction time. Adopting the dynamic list
for maintaining a total order, we can replace rank queries in a dynamic wavelet
tree on a run-length compressed string by the direct comparison of labels in a
dynamic list. The empirical result for various benchmarks show the efficiency
of our algorithm, especially for highly repetitive strings.Comment: In Proc. IWOCA201
Exploring ecosystem markets for the delivery of public goods in the UK
Environmental restoration and conservation challenges go beyond what can be financed publicly. There are significant opportunities for private investment in the delivery of public goods, benefitting both commercial organisations whose business relies on ecosystem services, as well as landowners, land managers and the general public. Thus, public-private financing of natural capital improvement presents an opportunity to increase the availability of funding for payments for ecosystem services that provide environmental and societal benefits. Though public-private partnerships for the financing of ecosystem services is in its infancy in the UK.
This new report explores the voluntary ecosystem services market in the UK. This is achieved by developing an understanding of how key actors (schemes, stakeholder engagement initiatives, trading platforms and supporting modelling tools) operate, and by identifying possible synergies, examples of good practice and challenges to implementation. Topics covered include, understanding how the identified actors account for the social distribution of ecosystem services, how values are attributed to ecosystem services, and the legal obligations linked to ventures’ operation
The role of community acceptance in planning outcomes for onshore wind and solar farms: An energy justice analysis
The deployment of renewable technologies as part of climate mitigation strategies have provoked a range of responses from various actors, bringing public acceptance to the forefront of energy debates. A key example is the reaction of communities when renewable projects are proposed in their local areas. This paper analyses the effect that community acceptance has had on planning applications for onshore wind and solar farms in Great Britain between 1990 and 2017. It does this by compiling a set of indicators for community acceptance and testing their association with planning outcomes using binomial logistic regression. It identifies 12 variables with statistically significant effects: 4 for onshore wind, 4 for solar farms, and 4 spanning both. For both technologies, the visibility of a project, its installed capacity, the social deprivation of the area, and the year of the application are significant. The paper draws conclusions from these results for community acceptance and energy justice, and discusses the implications for energy decision-making
Using social media, machine learning and natural language processing to map multiple recreational beneficiaries
Information and numbers on the use and appreciation of nature are valuable information for protected area (PA) managers. A promising direction is the utilisation of social media, such as the photo-sharing website Flickr. Here we demonstrate a novel approach, borrowing techniques from machine learning (image analysis), natural language processing (Latent Semantic Analysis (LSA)) and self-organising maps (SOM), to collect and interpret >20,000 photos from the Camargue region in Southern France. From the perspective of Cultural Ecosystem Services (CES), we assessed the relationship between the use of the Camargue delta and the presence of natural elements by consulting local managers. Clustering algorithms applied to results of the LSA data revealed six distinct user groups, which included those interested in nature, ornithology, religious pilgrimage, general tourists and aviation enthusiasts. For each group, we produced high-resolution spatial and seasonal maps, which matched known recreational attractions and annual festivals in the Camargue. The accuracy of the group identification, and the spatial and temporal patterns of photo activity, in the Camargue delta were evaluated by local managers of the Camargue regional park. This study demonstrates how PA managers can harness social-media to monitor recreation and improve their management decision making
Practical Evaluation of Lempel-Ziv-78 and Lempel-Ziv-Welch Tries
We present the first thorough practical study of the Lempel-Ziv-78 and the
Lempel-Ziv-Welch computation based on trie data structures. With a careful
selection of trie representations we can beat well-tuned popular trie data
structures like Judy, m-Bonsai or Cedar
Landscape aesthetics: Spatial modelling and mapping using social media images and machine learning
Cultural ecosystem services such as aesthetic value are highly context-specific and often present difficulties in their assessment. Here we present a case study in the northern English Protected Area of the Yorkshire Dales National Park. Utilising publicly available images, paired-comparison surveys, probability modelling, machine-learning based text annotations, natural language processing and regression analysis, we developed a spatial model to predict and map landscape aesthetics across the whole site. The predictive model found eighteen significant variables, including the positive role of rural areas, mountainous landforms and vegetation for aesthetic value. Finally, we demonstrate the potential of our approach to varying size datasets and partial paired-comparison matrices, finding a very good agreement with only 20% of paired comparisons. This study demonstrates the use of freely available data and mostly open source tools to ascertain landscape aesthetic value in a large Protected Area
Dynamic Fluctuation Phenomena in Double Membrane Films
Dynamics of double membrane films is investigated in the long-wavelength
limit including the overdamped squeezing mode. We demonstrate that thermal
fluctuations essentially modify the character of the mode due to its nonlinear
coupling to the transversal shear hydrodynamic mode. The corresponding Green
function acquires as a function of the frequency a cut along the imaginary
semi-axis. Fluctuations lead to increasing the attenuation of the squeezing
mode it becomes larger than the `bare' value.Comment: 7 pages, Revte
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