616 research outputs found
Complexity of pattern classes and Lipschitz property
Rademacher and Gaussian complexities are successfully used in learning theory for measuring the capacity of the class of functions to be learned. One of the most important properties for these complexities is their Lipschitz property: a composition of a class of functions with a fixed Lipschitz function may increase its complexity by at most twice the Lipschitz constant. The proof of this property is non-trivial (in contrast to the other properties) and it is believed that the proof in the Gaussian case is conceptually more difficult then the one for the Rademacher case. In this paper we give a detailed prove of the Lipschitz property for the Rademacher case and generalize the same idea to an arbitrary complexity (including the Gaussian). We also discuss a related topic about the Rademacher complexity of a class consisting of all the Lipschitz functions with a given Lipschitz constant. We show that the complexity is surprisingly low in the one-dimensional case. The question for higher dimensions remains open
Classifying Crises-Information Relevancy with Semantics
Social media platforms have become key portals for sharing and consuming information during crisis situations. However, humanitarian organisations and affected communities often struggle to sieve through the large volumes of data that are typically shared on such platforms during crises to determine which posts are truly relevant to the crisis, and which are not. Previous work on automatically classifying crisis information was mostly focused on using statistical features. However,
such approaches tend to be inappropriate when processing data on a type of crisis that the model was not trained on, such as processing information about a train crash, whereas the classifier was trained on floods, earthquakes, and typhoons. In such cases, the model will need to be retrained, which is costly and time-consuming. In this paper, we explore the impact of semantics in classifying Twitter posts across same, and different, types of crises. We experiment with 26 crisis events, using a hybrid system that combines statistical features with various semantic features extracted from external knowledge bases. We show that adding semantic features has no noticeable benefit over statistical features when classifying same-type crises, whereas it enhances the classifier performance by up to 7.2% when classifying information about a new type of crisis
Cross-Lingual Classification of Crisis Data
Many citizens nowadays flock to social media during crises to share or acquire the latest information about the event. Due to the sheer volume of data typically circulated during such events, it is necessary to be able to efficiently filter out irrelevant posts, thus focusing attention on the posts that are truly relevant to the crisis. Current methods for classifying the relevance of posts to a crisis or set of crises typically struggle to deal with posts in different languages, and it is not viable during rapidly evolving crisis situations to train new models for each language. In this paper we test statistical and semantic classification approaches on cross-lingual datasets from 30 crisis events, consisting of posts written mainly in English, Spanish, and Italian. We experiment with scenarios where the model is trained on one language and tested on another, and where the data is translated to a single language. We show that the addition of semantic features extracted from external knowledge bases improve accuracy over a purely statistical model
Right for the Right Reason: Training Agnostic Networks
We consider the problem of a neural network being requested to classify
images (or other inputs) without making implicit use of a "protected concept",
that is a concept that should not play any role in the decision of the network.
Typically these concepts include information such as gender or race, or other
contextual information such as image backgrounds that might be implicitly
reflected in unknown correlations with other variables, making it insufficient
to simply remove them from the input features. In other words, making accurate
predictions is not good enough if those predictions rely on information that
should not be used: predictive performance is not the only important metric for
learning systems. We apply a method developed in the context of domain
adaptation to address this problem of "being right for the right reason", where
we request a classifier to make a decision in a way that is entirely 'agnostic'
to a given protected concept (e.g. gender, race, background etc.), even if this
could be implicitly reflected in other attributes via unknown correlations.
After defining the concept of an 'agnostic model', we demonstrate how the
Domain-Adversarial Neural Network can remove unwanted information from a model
using a gradient reversal layer.Comment: Author's original versio
Applying Machine Learning to Catalogue Matching in Astrophysics
We present the results of applying automated machine learning techniques to
the problem of matching different object catalogues in astrophysics. In this
study we take two partially matched catalogues where one of the two catalogues
has a large positional uncertainty. The two catalogues we used here were taken
from the HI Parkes All Sky Survey (HIPASS), and SuperCOSMOS optical survey.
Previous work had matched 44% (1887 objects) of HIPASS to the SuperCOSMOS
catalogue.
A supervised learning algorithm was then applied to construct a model of the
matched portion of our catalogue. Validation of the model shows that we
achieved a good classification performance (99.12% correct).
Applying this model, to the unmatched portion of the catalogue found 1209 new
matches. This increases the catalogue size from 1887 matched objects to 3096.
The combination of these procedures yields a catalogue that is 72% matched.Comment: 8 Pages, 5 Figure
Towards Emotion Recognition: A Persistent Entropy Application
Emotion recognition and classification is a very active area of research. In
this paper, we present a first approach to emotion classification using
persistent entropy and support vector machines. A topology-based model is
applied to obtain a single real number from each raw signal. These data are
used as input of a support vector machine to classify signals into 8 different
emotions (calm, happy, sad, angry, fearful, disgust and surprised)
Effects Of High Pressure Homogenization On The Activity, Stability, Kinetics And Three-dimensional Conformation Of A Glucose Oxidase Produced By Aspergillus Niger
High pressure homogenization (HPH) is a non-thermal method, which has been employed to change the activity and stability of biotechnologically relevant enzymes. This work investigated how HPH affects the structural and functional characteristics of a glucose oxidase (GO) from Aspergillus niger. The enzyme was homogenized at 75 and 150 MPa and the effects were evaluated with respect to the enzyme activity, stability, kinetic parameters and molecular structure. The enzyme showed a pH-dependent response to the HPH treatment, with reduction or maintenance of activity at pH 4.5-6.0 and a remarkable activity increase (30-300%) at pH 6.5 in all tested temperatures (15, 50 and 75°C). The enzyme thermal tolerance was reduced due to HPH treatment and the storage for 24 h at high temperatures (50 and 75°C) also caused a reduction of activity. Interestingly, at lower temperatures (15°C) the activity levels were slightly higher than that observed for native enzyme or at least maintained. These effects of HPH treatment on function and stability of GO were further investigated by spectroscopic methods. Both fluorescence and circular dichroism revealed conformational changes in the molecular structure of the enzyme that might be associated with the distinct functional and stability behavior of GO. © 2014 Tribst et al.97Bankar, S.B., Bule, M.V., Singhal, R.S., Ananthanarayan, L., Glucose oxidase - An overview (2009) Biotechnol Adv, 27 (4), pp. 489-501Whitaker, J.R., (2003) Handbook of Food Enzymology, p. 1108. , New York: Marcel Dekker IncorporatedWohlfahrt, G., Witt, S., Hendle, J., Schomburg, D., Kalisz, H.M., Hecht, H.-J., 1.8 and 1.9 Â resolution structures of the Penicillium amagasakiense and Aspergillus niger glucose oxidases as a basis for modelling substrate complexes (1999) Acta Crystallographica Section D: Biological Crystallography, 55 (5), pp. 969-977. , DOI 10.1107/S0907444999003431Leskovac, V., Trivic, S., Wohlfahrt, G., Kandrac, J., Pericin, D., Glucose oxidase from Aspergillus niger: The mechanism of action with molecular oxygen, quinones, and one-electron acceptors (2005) International Journal of Biochemistry and Cell Biology, 37 (4), pp. 731-750. , DOI 10.1016/j.biocel.2004.10.014Fiedurek, J., Gromada, A., Screening and mutagenesis of molds for improvement of the simultaneous production of catalase and glucose oxidase (1997) Enzyme and Microbial Technology, 20 (5), pp. 344-347. , DOI 10.1016/S0141-0229(96)00148-2, PII S0141022996001482Pluschkell, S., Hellmuth, K., Rinas, U., Kinetics of glucose oxidase excretion by recombinant Aspergillus niger (1996) Biotechnology and Bioengineering, 51 (2), pp. 215-220. , DOI 10.1002/(SICI)1097-0290(19960720)51:2<215::AIDLacroix, N., Fliss, I., Makhlouf, J., Inactivation of pectin methylesterase and stabilization of opalescence in orange juice by dynamic high pressure (2005) Food Research International, 38 (5), pp. 569-576. , DOI 10.1016/j.foodres.2004.11.010, PII S0963996904002716Tribst, A.A.L., Franchi, M.A., Cristianini, M., Ultra-high pressure homogenization treatment combined with lysozyme for controlling Lactobacillus brevis contamination in model system (2008) Innov Food Sci Emerg Technol, 9 (3), pp. 265-271Tribst, A.A.L., Franchi, M.A., De Massaguer, P.R., Cristianini, M., Quality of mango nectar processed by high-pressure homogenization with optimized heat treatment (2011) J Food Sci, 76 (2), pp. M106-M110Franchi, M.A., Tribst, A.A.L., Cristianini, M., Effects of High Pressure Homogenization on Beer Quality Attributes (2011) J Inst Brew, 117 (2), pp. 195-198Tribst, A.A.L., Franchi, M.A., Cristianini, M., De Massaguer, P.R., Inactivation of Aspergillus niger in mango nectar by high-pressure homogenization combined with heat shock (2009) J Food Sci, 74 (9), pp. M509-M514Augusto, P.E.D., Ibarz, A., Cristianini, M., Effect of high pressure homogenization (HPH) on the rheological properties of a fruit juice serum model (2012) J. Food Eng, 111 (2), pp. 474-477Augusto, P.E.D., Ibarz, A., Cristianini, M., Effect of high pressure homogenization (HPH) on the rheological properties of tomato juice: Time-dependent and steady-state shear (2012) J Food Eng, 111 (4), pp. 570-579Welti-Chanes, J., Ochoa-Velasco, C.E., Guerrero-Béltran, J.A., High-pressure homogenization of orange juice to inactivate pectinmethylesterase (2009) Innov Food Sci Emerg Technol, 10 (4), pp. 457-462Liu, W., Liu, J., Liu, C., Zhong, Y., Liu, W., Activation and conformational changes of mushroom polyphenoloxidase by high pressure microfluidization treatment (2009) Innov Food Sci Emerg Technol, 10 (2), pp. 142-147Liu, W., Liu, J., Xie, M., Liu, C., Liu, W., Characterization and high-pressure microfluidization-induced activation of polyphenoloxidase from Chinese pear (Pyrus pyrifolia Nakai) (2009) J Agric Food Chem, 57, pp. 5376-5380Tribst, A.A.L., Cristianini, M., High pressure homogenization of a fungi α-amylase (2012) Innov Food Sci Emerg Technol, 3, pp. 107-111Tribst, A.A.L., Cristianini, M., Increasing fungi amyloglucosidase activity by high pressure homogenization (2012) Innov Food Sci Emerg Technol, 16, pp. 21-25Tribst, A.A.L., Cristianini, M., Changes in Commercial Glucose Oxidase Activity by High Pressure Homogenization (2012) Innov Food Sci Emerg Technol, 16, pp. 355-360Tribst, A.A.L., Augusto, P.E.D., Cristianini, M., The effect of the high pressure homogenisation on the activity and stability of a commercial neutral protease from Bacillus subtilis (2012) Int J Food Sci Technol, 47 (4), pp. 716-722Tribst, A.A.L., Augusto, P.E.D., Cristianini, M., The effect of high pressure homogenization on the activity of a commercial β-Galactosidase (2012) J Ind Microbiol Biotechnol, 39 (11), pp. 1587-1596Tribst, A.A.L., Augusto, P.E.D., Cristianini, M., Changes in enzyme activity by multiple passes on high pressure homogenizer (2013) Innov Food Sci Emerg Technol, 18, pp. 83-88Leite Jr., B.R.D.C., Tribst, A.A.L., Cristianini, M., Proteolytic and milk-clotting activities of calf rennet processed by high pressure homogenization and the influence on the rheological behavior of the milk coagulation process (2014) Innov Food Sci Emerg Technol, 21, pp. 44-49Liu, W., Zhang, Z.-Q., Liu, C., Xie, M., Tu, Z., The effect of dynamic high-pressure microfluidization on the activity, stability and conformation of trypsin (2010) Food Chem, 123, pp. 616-621Miller, G.L., Use of dinitro salicylic acid reagent for determination of reducing sugar (1959) Anal Chem, 31, pp. 426-428Takács, E., Grolmusz, V.K., Vértessy, B.G., A tradeoff between protein stability and conformational mobility in homotrimeric dUTPases (2004) FEBS Letters, 566 (1-3), pp. 48-54Whitmore, L., Wallace, B.A., Protein secondary structure analyses from circular dichroism spectroscopy: Methods and reference databases (2008) Biopolymers, 89 (5), pp. 392-400Vertessy, B.G., Flexible glycine rich motif of Escherichia coli deoxyuridine triphosphate nucleotidohydrolase is important for functional but not for structural integrity of the enzyme (1997) Proteins: Structure, Function and Genetics, 28 (4), pp. 568-579Yanari, S., Bovey, F.A., Interpretation of the ultraviolet spectral changes of proteins (1960) J Biol Chem, 235 (10), pp. 2828-12825Vivian, J.T., Callis, P.R., Mechanisms of tryptophan fluorescence shifts in proteins (2001) Biophysical Journal, 80 (5), pp. 2093-2109Hecht, H.J., Kalisz, H.M., Hendle, J., Schmid, R.D., Schomburg, D., Crystal structure of glucose oxidase from Aspergillus niger refined at 2.3 A reslution (1993) Journal of Molecular Biology, 229 (1), pp. 153-172. , DOI 10.1006/jmbi.1993.1015Woody, R.W., Theory of Circular dichroism of Proteins (1996) Circular Dichroism and the Conformational Analysis of Biomolecules, pp. 25-30. , Fasman GD (ed) New York: Plenum Press PublisherLuo, D.H., Zhao, Q.Z., Zhao, M.M., Yang, B., Long, X.T., Effects of limited proteolysis and high-pressure homogenisation on structural and functional characteristics of glycinin (2010) Food Chem, 122, pp. 25-3
Automatic detection of limb prominences in 304 A EUV images
A new algorithm for automatic detection of prominences on the solar limb in 304 A EUV images is presented, and results of its application to SOHO/EIT data discussed. The detection is based on the method of moments combined with a
classifier analysis aimed at discriminating between limb prominences, active regions, and the quiet corona. This classifier analysis is based on a Support Vector Machine (SVM). Using a set of 12 moments of the radial intensity profiles, the algorithm performs well in discriminating between the above three categories of limb structures, with a misclassification rate of 7%. Pixels detected as belonging to a prominence are then used as starting point to reconstruct the whole prominence by morphological image processing techniques. It is planned that a catalogue of limb prominences identified in SOHO and STEREO data using this method will be made publicly available to the scientific community
Aiding first incident responders using a decision support system based on live drone feeds
In case of a dangerous incident, such as a fire, a collision or an earthquake, a lot of contextual data is available for the first incident responders when handling this incident. Based on this data, a commander on scene or dispatchers need to make split-second decisions to get a good overview on the situation and to avoid further injuries or risks. Therefore, we propose a decision support system that can aid incident responders on scene in prioritizing the rescue efforts that need to be addressed. The system collects relevant data from a custom designed drone by detecting objects such as firefighters, fires, victims, fuel tanks, etc. The drone autonomously observes the incident area, and based on the detected information it proposes a prioritized based action list on e.g. urgency or danger to incident responders
SocialLink: exploiting graph embeddings to link DBpedia entities to Twitter profiles
SocialLink is a project designed to match social media profiles on Twitter to corresponding entities in DBpedia. Built to bridge the vibrant Twitter social media world and the Linked Open Data cloud, SocialLink enables knowledge transfer between the two, both assisting Semantic Web practitioners in better harvesting the vast amounts of information available on Twitter and allowing leveraging of DBpedia data for social media analysis tasks. In this paper, we further extend the original SocialLink approach by exploiting graph-based features based on both DBpedia and Twitter, represented as graph embeddings learned from vast amounts of unlabeled data. The introduction of such new features required to redesign our deep neural network-based candidate selection algorithm and, as a result, we experimentally demonstrate a significant improvement of the performances of SocialLink
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