| 1. |
- Wittek, Peter, et al.
(författare)
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Digital Preservation in Grids and Clouds : A Middleware Approach
- 2012
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Ingår i: Journal of Grid Computing. - : Springer. - 1570-7873 .- 1572-9184. ; 10:1, s. 133-149
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Tidskriftsartikel (refereegranskat)abstract
- Digital preservation is the persistent archiving of digital assets for future access and reuse, irrespective of the underlying platform and software solutions. Existing preservation systems have a strong focus on grids, but the advent of cloud technologies offers an attractive option. We describe a middleware system that enables a flexible choice between a grid and a cloud for ad-hoc computations that arise during the execution of a preservation workflow and also for archiving digital objects. The choice between different infrastructures remains open during the lifecycle of the archive, ensuring a smooth switch between different solutions to accommodate the changing requirements of the organization that needs its digital assets preserved. We also offer insights on the costs, running times, and organizational issues of cloud computing, proving that the cloud alternative is particularly attractive for smaller organizations without access to a grid or with limited IT infrastructure.
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| 2. |
- Darányi, Sándor, 1951-, et al.
(författare)
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A Potential Surface Underlying Meaning?
- 2015
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Machine learning algorithms utilizing gradient descent to identify concepts or more general learnables hint at a so-far ignored possibility, namely that local and global minima represent any vocabulary as a landscape against which evaluation of the results can take place. A simple example to illustrate this idea would be a potential surface underlying gravitation. However, to construct a gravitation-based representation of, e.g., word meaning, only the distance between localized items is a given in the vector space, whereas the equivalents of mass or charge are unknown in semantics. Clearly, the working hypothesis that physical fields could be a useful metaphor to study word and sentence meaning is an option but our current representations are incomplete in this respect.For a starter, consider that an RBF kernel has the capacity to generate a potential surface and hence create the impression of gravity, providing one with distance-based decay of interaction strength, plus a scalar scaling factor for the interaction, but of course no term masses. We are working on an experiment design to change that. Therefore, with certain mechanisms in neural networks that could host such quasi-physical fields, a novel approach to the modeling of mind content seems plausible, subject to scrutiny.Work in progress in another direction of the same idea indicates that by using certain algorithms, already emerged vs. still emerging content is clearly distinguishable, in line with Aristotle’s Metaphysics. The implications are that a model completed by “term mass” or “term charge” would enable the computation of the specific work equivalent of sentences or documents, and that via replacing semantics by other modalities, vector fields of more general symbolic content could exist as well. Also, the perceived hypersurface generated by the dynamics of language use may be a step toward more advanced models, for example addressing the Hamiltonian of expanding semantic systems, or the relationship between reaction paths in quantum chemistry vs. sentence construction by gradient descent.
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| 3. |
- Darányi, Sándor, et al.
(författare)
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A Physical Metaphor to Study Semantic Drift
- 2016
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Ingår i: Proceedings of SuCCESS-16, 1st International Workshop on Semantic Change & Evolving Semantics. - 9781450321389
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Konferensbidrag (refereegranskat)abstract
- In accessibility tests for digital preservation, over time we experience drifts of localized and labelled content in statistical models of evolving semantics represented as a vector field. This articulates the need to detect, measure, interpret and model outcomes of knowledge dynamics. To this end we employ a high-performance machine learning algorithm for the training of extremely large emergent self-organizing maps for exploratory data analysis. The working hypothesis we present here is that the dynamics of semantic drifts can be modeled on a relaxed version of Newtonian mechanics called social mechanics. By using term distances as a measure of semantic relatedness vs. their PageRank values indicating social importance and applied as variable ‘term mass’, gravitation as a metaphor to express changes in the semantic content of a vector field lends a new perspective for experimentation. From ‘term gravitation’ over time, one can compute its generating potential whose fluctuations manifest modifications in pairwise term similarity vs. social importance, thereby updating Osgood’s semantic differential. The dataset examined is the public catalog metadata of Tate Galleries, London.
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| 4. |
- Gao, Shi Chao, et al.
(författare)
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Data-driven estimation of blood pressure using photoplethysmographic signals
- 2016
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Ingår i: Proceedings of EMBC-16, 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - : IEEE. - 9781457702204
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Konferensbidrag (refereegranskat)abstract
- Noninvasive measurement of blood pressure by optical methods receives considerable interest, but the complexity of the measurement and the difficulty of adjusting parameters restrict applications. We develop a method for estimating the systolic and diastolic blood pressure using a single-point optical recording of a photoplethysmographic (PPG) signal. The estimation is data-driven, we use automated machine learning algorithms instead of mathematical models. Combining supervised learning with a discrete wavelet transform, the method is insensitive to minor irregularities in the PPG waveform, hence both pulse oximeters and smartphone cameras can record the signal. We evaluate the accuracy of the estimation on 78 samples from 65 subjects (40 male, 25 female, age 29±7) with no history of cardiovascular disease. The estimate for systolic blood pressure has a mean error 4.9±4.9 mm Hg, and 4.3±3.7 mm Hg for diastolic blood pressure when using the oximeter-obtained PPG. The same values are 5.1±4.3 mm Hg and 4.6±4.3 mm Hg when using the phone-obtained PPG, comparing with A&D UA-767PBT result as gold standard. The simplicity of the method encourages ambulatory measurement, and given the ease of sharing the measured data, we expect a shift to data-oriented approaches deriving insight from ubiquitous mobile devices that will yield more accurate machine learning models in monitoring blood pressure.
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| 5. |
- Kontopoulos, Efstratios, et al.
(författare)
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Studying the Cohesion Evolution of Genes Related to Chronic Lymphocytic Leukemia Using Semantic Similarity in Gene Ontology and Self-Organizing Maps
- 2016
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Ingår i: Proceedings of SWAT4LS-16, 9th International Conference on Semantic Web Applications and Tools for Life Sciences.
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Konferensbidrag (refereegranskat)abstract
- A significant body of work on biomedical text mining is aimed at uncovering meaningful associations between biological entities, including genes. This has the potential to offer new insights for research, uncovering hidden links between genes involved in critical pathways and processes. Recently, high-throughput studies have started to unravel the genetic landscape of chronic lymphocytic leukemia (CLL), the most common adult leukemia. CLL displays remarkable clinical heterogeneity, likely reflecting its underlying biological heterogeneity which, despite all progress, still remains insufficiently characterized and understood. This paper deploys an ontology-based semantic similarity combined with self-organizing maps for studying the temporal evolution of cohesion among CLL-related genes and the extracted information. Three consecutive time periods are considered and groups of genes are derived therein. Our preliminary results indicated that our proposed gene groupings are meaningful and that the temporal dimension indeed impacted the gene cohesion, leaving a lot of room for further promising investigations.
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| 6. |
- Meroño Peñuela, Albert, et al.
(författare)
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Visualizing the Drift of Linked Open Data Using Self-Organizing Maps
- 2016
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Ingår i: Proceedings of Drift-a-LOD Workshop at the 20th International Conference on Knowledge Engineering and Knowledge Management.
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Konferensbidrag (refereegranskat)abstract
- The urge for evolving the Web into a globally shared dataspace has turned the Linked Open Data (LOD) cloud into a massive platform containing 100 billion machine-readable statements. Several factors hamper a historical study of the evolution of the LOD cloud, and hence forecasting its future: its ever-growing scale, which makes a global analysis difficult; its Web-distributed nature, which challenges the analysis of its data; and the scarcity of regular and time-stamped archival dumps. Recently, a scalable implementation of self-organizing maps (SOM) has been developed to visualize the local topology of high-dimensional data. We use this methodology to address scalability issues, and the Dynamic Linked Data Observatory, a regular biweekly, centralized sample of the LOD cloud, as a time-stamped collection. We visualize the drift of Linked Datasets between 2012 and 2016, finding that datasets with high availability, high vocabulary reuse, and modeling with commonly used terms in the LOD cloud are better traceable across time.
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| 7. |
- Wittek, Peter
(författare)
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High-Performance Dynamic Quantum Clustering on Graphics Processors
- 2013
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Ingår i: Journal of Computational Physics. - : Academic Press. - 0021-9991 .- 1090-2716. ; 233, s. 262-
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Tidskriftsartikel (refereegranskat)abstract
- Clustering methods in machine learning may benefit from borrowing metaphors from physics. Dynamic quantum clustering associates a Gaussian wave packet with the multidimensional data points and regards them as eigenfunctions of the Schrödinger equation. The clustering structure emerges by letting the system evolve and the visual nature of the algorithm has been shown to be useful in a range of applications. Furthermore, the method only uses matrix operations, which readily lend themselves to parallelization. In this paper, we develop an implementation on graphics hardware and investigate how this approach can accelerate the computations. We achieve a speedup of up to two magnitudes over a multicore CPU implementation, which proves that quantum-like methods and acceleration by graphics processing units have a great relevance to machine learning.
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| 8. |
- Wittek, Peter, et al.
(författare)
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Military Reconstructive Simulation in the Cloud to Aid Battlefield Excavations
- 2012
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Konferensbidrag (refereegranskat)abstract
- Archaeological studies on battlefields may see great benefits from simulated military engagements: simulations help testing hypotheses based on historical data and may also help with validating methodologies used on the site. Such methods, however, require high-performance computing expertise and considerable computational power. With the emergence of on-demand computing instances in the cloud, distributed computations have become available to technically every organization or individual. This puts large-scale battlefield simulations within the reach of archaeologists, and the cloud paradigm also lowers the required technological expertise, potentially leading to a more widespread adoption of such simulation methods.
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| 9. |
- Wittek, Peter, et al.
(författare)
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Monitoring Term Drift Based on SemanticConsistency in an Evolving Vector Field
- 2015
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Ingår i: Proceedings of IJCNN-15.
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Konferensbidrag (refereegranskat)abstract
- Based on the Aristotelian concept of potentialityvs. actuality allowing for the study of energy and dynamics inlanguage, we propose a field approach to lexical analysis. Fallingback on the distributional hypothesis to statistically model wordmeaning, we used evolving fields as a metaphor to express timedependentchanges in a vector space model by a combinationof random indexing and evolving self-organizing maps (ESOM).To monitor semantic drifts within the observation period, anexperiment was carried out on the term space of a collection of12.8 million Amazon book reviews. For evaluation, the semanticconsistency of ESOM term clusters was compared with theirrespective neighbourhoods in WordNet, and contrasted withdistances among term vectors by random indexing. We found thatat 0.05 level of significance, the terms in the clusters showed a highlevel of semantic consistency. Tracking the drift of distributionalpatterns in the term space across time periods, we found thatconsistency decreased, but not at a statistically significant level.Our method is highly scalable, with interpretations in philosophy.
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| 10. |
- Wittek, Peter, et al.
(författare)
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Risk and Ambiguity in Information Seeking : Eye Gaze Patterns Reveal Contextual Behaviour in Dealing with Uncertainty
- 2016
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Ingår i: Frontiers in Psychology. - : Frontiers Media SA. - 1664-1078. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Information foraging connects optimal foraging theory in ecology with how humans search for information. The theory suggests that, following an information scent, the information seeker must optimize the tradeoff between exploration by repeated steps in the search space vs. exploitation, using the resources encountered. We conjecture that this tradeoff characterizes how a user deals with uncertainty and its two aspects, risk and ambiguity in economic theory. Risk is related to the perceived quality of the actually visited patch of information, and can be reduced by exploiting and understanding the patch to a better extent. Ambiguity, on the other hand, is the opportunity cost of having higher quality patches elsewhere in the search space. The aforementioned tradeoff depends on many attributes, including traits of the user: at the two extreme ends of the spectrum, analytic and wholistic searchers employ entirely different strategies. The former type focuses on exploitation first, interspersed with bouts of exploration, whereas the latter type prefers to explore the search space first and consume later. Based on an eye-tracking study of experts’ interactions with novel search interfaces in the biomedical domain, we demonstrate that perceived risk shifts the balance between exploration and exploitation in either type of users, tilting it against vs. in favour of ambiguity minimization. Since the pattern of behaviour in information foraging is quintessentially sequential, risk and ambiguity minimization cannot happen simultaneously, leading to a fundamental limit on how good such a tradeoff can be. This in turn connects information seeking with the emergent field of quantum decision theory.
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