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Search Results: 1 - 10 of 226735 matches for " Linda Gerencsér "
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Identification of Behaviour in Freely Moving Dogs (Canis familiaris) Using Inertial Sensors
Linda Gerencsér, Gábor Vásárhelyi, Máté Nagy, Tamas Vicsek, Adam Miklósi
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0077814
Abstract: Monitoring and describing the physical movements and body postures of animals is one of the most fundamental tasks of ethology. The more precise the observations are the more sophisticated the interpretations can be about the biology of a certain individual or species. Animal-borne data loggers have recently contributed much to the collection of motion-data from individuals, however, the problem of translating these measurements to distinct behavioural categories to create an ethogram is not overcome yet. The objective of the present study was to develop a “behaviour tracker”: a system composed of a multiple sensor data-logger device (with a tri-axial accelerometer and a tri-axial gyroscope) and a supervised learning algorithm as means of automated identification of the behaviour of freely moving dogs. We collected parallel sensor measurements and video recordings of each of our subjects (Belgian Malinois, N=12; Labrador Retrievers, N=12) that were guided through a predetermined series of standard activities. Seven behavioural categories (lay, sit, stand, walk, trot, gallop, canter) were pre-defined and each video recording was tagged accordingly. Evaluation of the measurements was performed by support vector machine (SVM) classification. During the analysis we used different combinations of independent measurements for training and validation (belonging to the same or different individuals or using different training data size) to determine the robustness of the application. We reached an overall accuracy of above 90% perfect identification of all the defined seven categories of behaviour when both training and validation data belonged to the same individual, and over 80% perfect recognition rate using a generalized training data set of multiple subjects. Our results indicate that the present method provides a good model for an easily applicable, fast, automatic behaviour classification system that can be trained with arbitrary motion patterns and potentially be applied to a wide range of species and situations.
Mixing times of Markov chains on a cycle with additional long range connections
Balázs Gerencsér
Mathematics , 2014,
Abstract: We develop Markov chain mixing time estimates for a class of Markov chains with restricted transitions. We assume transitions may occur along a cycle of $n$ nodes and on $n^\gamma$ additional edges, where $\gamma < 1$. We find that the mixing times of reversible Markov chains properly interpolate between the mixing times of the cycle with no added edges and of the cycle with $cn$ added edges (which is in turn a Small World Network model). In the case of non-reversible Markov-chains, a considerable gap remains between lower and upper bounds, but simulations give hope to experience a significant speedup compared to the reversible case.
On the boundedness of solutions of SPDEs
Konstantinos Dareiotis,Máté Gerencsér
Mathematics , 2013,
Abstract: In this paper estimates for the uniform norm of solutions of parabolic SPDEs are derived. The result is obtained through iteration techniques, motivated by the work of Moser in deterministic settings. As an application of the main result, solvability of a class of semilinear SPDEs is derived.
Improved mixing rates of directed cycles by added connection
Balázs Gerencsér,Julien Hendrickx
Mathematics , 2015,
Abstract: We provide bounds on the mixing rate of a Markov chain whose mixing properties are improved by a combination of adding long distance edges and introducing non-reversibility. Our model is built on a cycle graph and involves selecting a sublinear number of nodes and adding all edges connecting them. We show that there is a square factor improvement of the mixing rate compared to the reversible version of the Markov chain. Our result suggests that the combination of the two techniques is a promising concept in a more general setting.
A weak Harnack inequality for stochastic partial differential equations
Konstantinos Dareiotis,Máté Gerencsér
Mathematics , 2015,
Abstract: We consider linear stochastic partial differential equations under minimal assumptions: the coefficients are merely bounded and measurable and satisfy the stochastic parabolicity condition. We derive local supremum estimates with a stochastic adaptation of De Giorgi's iteration and establish a weak Harnack inequality for the solutions. The latter is then used to obtain pointwise almost sure continuity.
Push sum with transmission failures
Balázs Gerencsér,Julien M. Hendrickx
Computer Science , 2015,
Abstract: The push-sum algorithm allows distributed computing of the average on a directed graph, and is particularly relevant when one is restricted to one-way and/or asynchronous communications. We investigate its behavior in the presence of unreliable communication channels where messages can be lost. We show that convergence still holds, and analyze the error of the final common value we get for the essential case of two nodes, both theoretically and numerically. We compare this error performance with that of the standard consensus algorithm. For the multi-node case, we deduce fundamental properties that implicitly describe the distribution of the final value obtained.
Identification of Finite Dimensional Lévy Systems in Financial Mathematics
L. Gerencsér,M. Mánfay
Statistics , 2013,
Abstract: L\'evy processes are widely used in financial mathematics to model return data. Price processes are then defined as a corresponding geometric L\'evy process, implying the fact that returns are independent. In this paper we propose an alternative class of models allowing to describe dependence between return data. Technically such an alternative model class is obtained by considering finite dimensional linear stochastic SISO systems driven by a L\'evy process. In this paper we consider a discrete-time version of this model, focusing on the problem of identifying the dynamics and the noise characteristics of such a so-called L\'evy system. The special feature of this problem is that the characteristic function (c.f.) of the driving noise is explicitly known, possibly up to a few unknown parameters. We develop and analyze a variety of novel identification methods by adapting the so-called empirical characteristic function method (ECF) originally devised for estimating parameters of c.f.-s from i.i.d. samples. Precise characterization of the errors of these estimators will be given, and their asymptotic covariance matrices will be obtained. Their potential to outperform the prediction error method in estimating the system parameters will also be demonstrated.
Effect of adult weight and CT-based selection on the performances of growing rabbits
Zsolt Szendr?,Zsolt Matics,Zsolt Gerencsér,Márió Lengyel
Italian Journal of Animal Science , 2010, DOI: 10.4081/ijas.2009.s3.237
Abstract: The aim of the study was to compare the productive performance of different genotypes. Maternal (M; n=32, adult weight /AW/ 4.0-4.5kg, selected for number of kits born alive), Pannon White (P; n=32, AW: 4.3-4.8kg), and Large body line (L; n=32, AW: 4.8- 5.4kg) (P and L were selected for carcass traits based on CT /Computer tomography/data) rabbits were analysed. Average daily gain between 5-11wk of age, body weight at 11wk of age and feed intake were significantly (P<0.001) highest for L rabbits. For M, P and L rabbits, the following values were observed: average daily gain=38.6, 43.1 and 47.4g/d; body weight=2458, 2667 and 2949g; feed intake=115, 121 and 138g/d, respectively. Mortality of growing rabbits was unaffected by genotype. It can be concluded that production traits were mainly affected by the adult weight of the genotypes.
Light colour preference of growing rabbits
Zsolt Gerencsér,Zsolt Matics,István Nagy,Zsolt Szendr?
Italian Journal of Animal Science , 2010, DOI: 10.4081/ijas.2009.s3.205
Abstract: The objective of the experiment was to evaluate the light colour preference of growing rabbits placed in a free-choice cage. The experiment was carried out on 128 Pannon White growing rabbits weaned at the age of 5 weeks and placed into blocks (2m2) of four cages. The rabbits could move freely among the four cages (0.5m2 each) through swing doors. The cages differed only in the colour of the light applied (white, yellow, green or blue). The lighting schedule was 16L: 8D. From 6 until 10 weeks of age, infrared video recording was performed once a week (24 hours). The number of rabbits in each cage was counted every 15 minutes. Feed consumption was measured weekly. Between 6 and 10 weeks of age the rabbits significantly preferred white light (28.0%). The preference order was the following: yellow (26.3%), blue (23.4%) and green (22.3%) (P<0.001). No significant differences were recorded in the feed consumption among the cages. In conclusion, the cage preference of the rabbits was slightly affected by the light colour.
Effect of adult weight and CT-based selection on rabbit meat quality
Antonella Dalle Zotte,Barbara Fornasier,Zsolt Matics,Zsolt Gerencsér
Italian Journal of Animal Science , 2010, DOI: 10.4081/ijas.2009.s3.243
Abstract: This study compared the meat quality of different genotypes. Maternal (M; adult weight/AW/=4.0-4.5kg; selected for the number of kits born alive), Pannon White (P; AW=4.3-4.8kg) and Large type (L; AW=4.8-5.4kg) rabbits were analysed. P and L genotypes were selected for carcass traits based on CT/Computer tomography/data. Rabbits were slaughtered at 11wk of age and hindleg (HL) meat and M. Longissimus dorsi (LD) were analysed for proximate composition and fatty acid (FA) profile. Proximate composition was unaffected by the selection programme, even though the meat of P rabbits was leaner and had higher ash content (P<0.10). The LD meat of P rabbits exhibited significantly lower MUFA contents compared to M and L rabbits (25.4 vs 28.0 vs 27.7%; P<0.01) and higher PUFA content compared to M rabbits (31.9 vs 24.9%; P<0.05). This study revealed that long-term CT-based selection is effective in increasing meat leanness and PUFA content.
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