pinecone/core-2020-05-10-deduplication huggingface dataset:
A Review and comparison of service E-Contract Architecture Metamodels

© Springer International Publishing Switzerland 2015. An adaptive service e-contract is an electronic agreement which is required to enable adaptive or agile service sourcing and pro- visioning. There are a number of e-contract metamodels that can be used to create a context specific adaptive service e-contract. The chal- lenge is which one to choose and adopt for adaptive services. This paper presents a review and comparison of well-known e-contract metamod- els using the architecture theory. The architecture theory allows the analysis of the e-contract metamodels using a three-dimension analyt- ical lens: structure, behavior and technology. The results of this paper highlight the metamodels structural, behavioral and technological differ- ences and similarities. This paper will help researchers and practitioners to observe the existing e-contract metamodels are appropriate to the adaptive services or if thwhetherere is a need to merge and integrate the concepts of these metamodels to propose a new unifying adaptive service e-contract metamodel. This paper is limited to the number of compared metamodels
Extending local features with contextual information in graph kernels

Graph kernels are usually defined in terms of simpler kernels over local
substructures of the original graphs. Different kernels consider different
types of substructures. However, in some cases they have similar predictive
performances, probably because the substructures can be interpreted as
approximations of the subgraphs they induce. In this paper, we propose to
associate to each feature a piece of information about the context in which the
feature appears in the graph. A substructure appearing in two different graphs
will match only if it appears with the same context in both graphs. We propose
a kernel based on this idea that considers trees as substructures, and where
the contexts are features too. The kernel is inspired from the framework in
[6], even if it is not part of it. We give an efficient algorithm for computing
the kernel and show promising results on real-world graph classification
datasets.Comment: To appear in ICONIP 201
A Cortically-Inspired Model for Bioacoustics Recognition

Wavelet transforms have shown superior performance in auditory recognition tasks compared to the more commonly used Mel-Frequency Cepstral Coefficients, and offer the ability to more closely model the frequency response behaviour of the cochlear basilar membrane. In this paper we evaluate a gammatone wavelet as a preprocessor for the Hierarchical Temporal Memory (HTM) model of the neocortex as part of the broader development of a biologically motivated approach to sound recognition. Specifically, we apply for the first time, a gammatone/equivalent rectangular bandwidth wavelet transform in conjunction with the HTM’s Spatial Pooler to recognise frog calls, bird songs and insect sounds. Our audio feature detection results show that wavelets perform considerably better than MFCCs on our selected datasets but that combining wavelets with HTM does not produce further improvements. This outcome raises questions concerning the degree of match to the biology required for an effective HTM-based model of audition.Griffith Sciences, School of Information and Communication TechnologyFull Tex
A multichannel Deep Belief Network for the classification of EEG data

© Springer International Publishing Switzerland 2015. Deep learning, and in particular Deep Belief Network (DBN), has recently witnessed increased attention from researchers as a new classification platform. It has been successfully applied to a number of classification problems, such as image classification, speech recognition and natural language processing. However, deep learning has not been fully explored in electroencephalogram (EEG) classification. We propose in this paper three implementations of DBNs to classify multichannel EEG data based on different channel fusion levels. In order to evaluate the proposed method, we used EEG data that has been recorded to study the modulatory effect of transcranial direct current stimulation. One of the proposed DBNs produced very promising results when compared to three well-established classifiers; which are Support Vec- tor Machine (SVM), Linear Discriminant Analysis (LDA) and Extreme Learning Machine (ELM)
A Medical Image Steganography Method Based on Integer Wavelet Transform and Overlapping Edge Detection

Recently, there has been an increased interest in the transmission of digital medical images for e-health services. However, existing implementations of this service do not pay much attention to the confidentiality and protection of patients’ information. In this paper, we present a new medical image steganography technique for protecting patients’ confidential information through the embedding of this information in the image itself while maintaining high quality of the image as well as high embedding capacity. This technique divides the cover image into two areas, the Region of Interest (ROI) and the Region of Non-Interest (RONI), by performing Otsu’s method and then encloses ROI pixels in a rectangular shape according to the binary pixel intensities. In order to improve the security, the Electronic Patient Records (EPR) is embedded in the high frequency sub-bands of the wavelet transform domain of the RONI pixels. An edge detection method is proposed using overlapping blocks to identify and classify the edge regions. Then, it embeds two secret bits into three coefficient bits by performing an XOR operation to minimize the difference between the cover and stego images. The experimental results indicate that the proposed method provides a good compromise between security, embedding capacity and visual quality of the stego image
A comparative analysis of scalable and context-aware trust management approaches for internet of things

© Springer International Publishing Switzerland 2015. The Internet of Things - IoT - is a new paradigm in technology that allows most physical ‘things’ to contact each other. Trust between IoT devices is a critical factor. Trust in the IoT environment can be modeled using various approaches, such as confidence level and reputation parameters. Furthermore, trust is an important element in engineering reliable and scalable networks. In this paper, we survey scalable and context-aware trust management for IoT from three perspectives. First, we present an overview of the IoT and the importance of trust in relation to it, and then we provide an in-depth trust/reliable management protocol for the IoT and evaluate comparable trust management protocols. We also investigate a scalable solution for trust management in the IoT and provide a comparative evaluation of existing trust solutions. We then pre-sent a context-aware assessment for the IoT and compare the different trust solutions. Lastly, we give a full comparative analysis of trust/reliability management in the IoT. Our results are drawn from this comparative analysis, and directions for future research are outlined
An efficient shortest path routing algorithm in the data centre network DPillar.

DPillar has recently been proposed as a server-centric data centre network and is combinatorially related to the well-known wrapped butterfly network. We explain the relationship between DPillar and the wrapped butterfly network before proving a symmetry property of DPillar. We use this symmetry property to establish a single-path routing algorithm for DPillar that computes a shortest path and has time complexity O(klog(n))O(klog⁡(n)), where k parameterizes the dimension of DPillar and n the number of ports in its switches. Moreover, our algorithm is trivial to implement, being essentially a conditional clause of numeric tests, and improves significantly upon a routing algorithm earlier employed for DPillar. A secondary and important effect of our work is that it emphasises that data centre networks are amenable to a closer combinatorial scrutiny that can significantly improve their computational efficiency and performance
Algorithms for Replica Placement in High-Availability Storage

A new model of causal failure is presented and used to solve a novel replica
placement problem in data centers. The model describes dependencies among
system components as a directed graph. A replica placement is defined as a
subset of vertices in such a graph. A criterion for optimizing replica
placements is formalized and explained. In this work, the optimization goal is
to avoid choosing placements in which a single failure event is likely to wipe
out multiple replicas. Using this criterion, a fast algorithm is given for the
scenario in which the dependency model is a tree. The main contribution of the
paper is an $O(n + \rho \log \rho)$ dynamic programming algorithm for placing
$\rho$ replicas on a tree with $n$ vertices. This algorithm exhibits the
interesting property that only two subproblems need to be recursively
considered at each stage. An $O(n^2 \rho)$ greedy algorithm is also briefly
reported.Comment: 22 pages, 7 figures, 4 algorithm listing
Animal Protection Law in Australia: Bound by History

This chapter examines changing attitudes to the treatment of animals in nineteenth century Britain, tracing the effects of change through to the first British animal protection legislation in 1822, and beyond to the law of the Australian colonies. By the early part of the twentieth century a number of key facets of animal protection regulation were established: the adoption of the generic ‘no unnecessary suffering’ standard in assessing the extent of cruelty to animals allowed; the use of exemptions from the generic prohibition against cruelty; the imposition of duties to provide for the needs of an animal; and the establishment of one of the key institutional actors in the animal protection field, the RSPCA. As well, the Australian colonies faithfully reproduced an understanding of domesticated animals as personal property. Analysis of the development of animal protection law in Queensland provides a “representative sample” of the adoption of animal protection law in the States and Territories more broadly. In Queensland, as in other similar jurisdictions, the question remains whether the present day animal protection regulatory framework amounts, in essence, to a nineteenth century answer to twenty-first century concerns.Arts, Education & Law Group, School of LawFull Tex
Secure set-based policy checking and its application to password registration

Policies are the corner stones of today's computer systems. They define secure states and safe operations. A common problem with policies is that their enforcement is often in con ict with user privacy. In order to check the satisfiability of a policy, a server usually needs to collect from a client some information which may be private. In this work we introduce the notion of secure set-based policy checking (SPC) that allows the server to verify policies while preserving the client's privacy. SPC is a generic protocol that can be applied in many policy-based systems. As an example, we show how to use SPC to build a password registration protocol so that a server can check whether a client's password is compliant with its password policy without seeing the password. We also analyse SPC and the password registration protocol and provide security proofs. To demonstrate the practicality of the proposed primitives, we report performance evaluation results based on a prototype implementation of the password registration protoco
Cluster Dependent Classifiers for Online\ud
Signature Verification

In this paper, the applicability of notion of cluster dependent classifier for online signature verification is investigated. For every writer, by the use of a number of training samples, a representative is selected based on minimum average distance criteria (centroid) across all the samples of that writer. Later k-means clustering algorithm is employed to cluster the writers based on the chosen representatives. To select a suitable classifier for a writer, the equal error rate (EER) is estimated using each of the classifier for every writer in a cluster. The classifier which gives the lowest EER for a writer is selected to be the suitable classifier for that writer. Once the classifier for each writer in a cluster is decided, the classifier which has been selected for a maximum number of writers in that cluster is decided to be the classifier for all writers of that cluster. During verification, the authenticity of the query signature is decided using the same classifier which has been selected for the cluster to which the claimed writer belongs. In comparison with the existing works on online signature verification, which use a common classifier for all writers during verification, our work is based on the usage of a classifier which is cluster dependent. On the other hand our intuition is to recommend to use a same classifier for all and only those writers who have some common characteristics and to use different classifiers for writers of different characteristics. To demonstrate the efficacy of our model, extensive experiments are carried out on the MCYT online signature dataset (DB1) consisting signatures of 100 individuals. The outcome of the experiments being indicative of increased performance with the adaption of cluster dependent classifier seems to open up a new avenue for further investigation on a reasonably large dataset
Discrete Geodesics and Cellular Automata

International audienceThis paper proposes a dynamical notion of discrete geodesics, understood as straightest trajectories in discretized curved spacetime. The notion is generic, as it is formulated in terms of a general deviation function, but readily specializes to metric spaces such as discretized pseudo-riemannian manifolds. It is effective: an algorithm for computing these geodesics naturally follows, which allows numerical validation—as shown by computing the perihelion shift of a Mercury-like planet. It is consistent, in the continuum limit, with the standard notion of timelike geodesics in a pseudo-riemannian manifold. Whether the algorithm fits within the framework of cellular automata is discussed at length
Optimal Torus Exploration by Oblivious Robots

International audienceWe consider autonomous robots that are endowed with motion actuators and visibility sensors. The robots we consider are weak, i.e., they are anonymous, uniform, unable to explicitly communicate, and oblivious (they do not remember any of their past actions). In this paper, we propose an optimal (w.r.t. the number of robots) solution for the terminating exploration of a torus-shaped network by a team of $k$ such robots. In more details, we first show that it is impossible to explore a simple torus of arbitrary size with (strictly) less than four robots, even if the algorithm is probabilistic. If the algorithm is required to be deterministic, four robots are also insufficient. This negative result implies that the only way to obtain an optimal algorithm (w.r.t. the number of robots participating to the algorithm) is to make use of probabilities. Then, we propose a probabilistic algorithm that uses four robots to explore all simple tori of size $\ell \times L$, where $7 \leq \ell \leq L$. Hence, in such tori, four robots are necessary and sufficient to solve the (probabilistic) terminating exploration. As a torus can be seen as a 2-dimensional ring, our result shows, perhaps surprisingly, that increasing the number of possible symmetries in the network (due to increasing dimensions) does not come at an extra cost w.r.t. the number of robots that are necessary to solve the problem
Fisheye Consistency: Keeping Data in Synch in a Georeplicated World

International audienceOver the last thirty years, numerous consistency conditions for repli-cated data have been proposed and implemented. Popular examples include linearizability (or atomicity), sequential consistency, causal consistency, and eventual consistency. These conditions are usually defined independently from the computing entities (nodes) that manipulate the replicated data; i.e., they do not take into account how computing entities might be linked to one another, or geographically distributed. To address this lack, as a first contribution, this paper introduces the notion of proximity graph between computing nodes. If two nodes are connected in this graph, their operations must satisfy a strong consistency condition, while the operations invoked by other nodes are allowed to satisfy a weaker condition. The second contribution exploits this graph to provide a generic approach to the hybridization of data consistency conditions within the same system. We illustrate this approach on sequential consistency and causal consistency, and present a model in which all data operations are causally consistent, while operations by neighboring processes in the proximity graph are sequentially consistent. The third contribution of the paper is the design and the proof of a distributed algorithm based on this proximity graph, which combines sequential consistency and causal consistency (the resulting condition is called fisheye consistency). In doing so the paper provides a generic provably correct solution of direct relevance to modern georeplicated systems
Efficient state-based CRDTs by delta-mutation

CRDTs are distributed data types that make eventual consistency of a distributed object possible and non ad-hoc. Specifically, state-based CRDTs ensure convergence through disseminating the entire state, that may be large, and merging it to other replicas; whereas operation-based CRDTs disseminate operations (i.e., small states) assuming an exactly-once reliable dissemination layer. We introduce Delta State Conflict-Free Replicated Datatypes (δ-CRDT) that can achieve the best of both worlds: small messages with an incremental nature, disseminated over unreliable communication channels. This is achieved by defining δ-mutators to return a delta-state, typically with a much smaller size than the full state, that is joined to both: local and remote states. We introduce the δ-CRDT framework, and we explain it through establishing a correspondence to current state-based CRDTs. In addition, we present an anti-entropy algorithm that ensures causal consistency, and two δ-CRDT specifications of well-known replicated datatypes.This work is co-financed by the North Portugal Regional Operational Programme (ON.2, O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF), within project NORTE07-0124-FEDER-000058; and by EU FP7 SyncFree project (609551)
Avoiding Ultraviolet Divergence by Means of Interior-Boundary Conditions

We describe here a novel way of defining Hamiltonians for quantum field
theories (QFTs), based on the particle-position representation of the state
vector and involving a condition on the state vector that we call an
"interior-boundary condition." At least for some QFTs (and, we hope, for many),
this approach leads to a well-defined, self-adjoint Hamiltonian without the
need for an ultraviolet cut-off or renormalization.Comment: 18 pages LaTeX, 2 figures; presentation given at the conference
  "Quantum Mathematical Physics" in Regensburg (Germany), Sept. 29-Oct. 2, 2014
  (http://www.uni-regensburg.de/Fakultaeten/nat_Fak_I/qft2014/index.html
Super Riemann Surfaces and the Super Conformal Action Functional

Riemann surfaces are two-dimensional manifolds with a conformal class of
metrics. It is well known that the harmonic action functional and harmonic maps
are tools to study the moduli space of Riemann surfaces. Super Riemann surfaces
are an analogue of Riemann surfaces in the world of super geometry. After a
short introduction to super differential geometry we will compare Riemann
surfaces and super Riemann surfaces. We will see that super Riemann surfaces
can be viewed as Riemann surfaces with an additional field, the gravitino. An
extension of the harmonic action functional to super Riemann surfaces is
presented and applications to the moduli space of super Riemann surfaces are
considered.Comment: To appear in "Quantum Mathematical Physics", Conference Proceedings,
  Regensburg 201
Local Thermal Equilibrium States in Relativistic Quantum Field Theory

It is well-known that thermal equilibrium states in quantum statistical
mechanics and quantum field theory can be described in a mathematically
rigorous manner by means of the so-called Kubo-Martin-Schwinger (KMS)
condition, which is based on certain analyticity and periodicity properties of
correlation functions. On the other hand, the characterization of
non-equilibrium states which only locally have thermal properties still
constitutes a challenge in quantum field theory. We discuss a recent proposal
for characterization of such states by a generalized KMS condition. The
connection of this proposal to a proposal by D. Buchholz, I. Ojima and H.-J.
Roos for characterizing local thermal equilibrium states in quantum field
theory is discussed.Comment: 14 pp., version as appeared in "Quantum Mathematical Physics", with
  one reference updated, "Quantum Mathematical Physics", eds. Felix Finster et
  al. (Proceedings of the conference "Quantum Mathematical Physics - A Bridge
  between Mathematics and Physics", Regensburg 2014), Birkh\"auser (2016
Integrating Time-Series Data in Large-Scale Discrete Cell-Based Models

International audienceIn this work we propose an automatic way of generating and verifying formal hybrid models of signaling and transcriptional events, gathered in large-scale regulatory networks.This is done by integrating temporal and stochastic aspects of the expression of some biological components. The hybrid approach lies in the fact that measurements take into account both times of lengthening phases and discrete switches between them. The model proposed is based on a real case study of keratinocytes differentiation, in which gene time-series data was generated upon Calcium stimulation. To achieve this we rely on the Process Hitting (PH) formalism that was designed to consider large-scale system analysis. We first propose an automatic way of detecting and translating biological motifs from the Pathway Interaction Database to the PH formalism. Then, we propose a way of estimating temporal and stochas-tic parameters from time-series expression data of action on the PH. Simulations emphasize the interest of synchronizing concurrent events
Model-Based Whole-Genome Analysis of DNA Methylation Fidelity

We consider the problem of understanding how DNA methylation fidelity, i.e. the preservation of methylated sites in the genome, varies across the genome and across different cell types. Our approach uses a stochastic model of DNA methylation across generations and trains it using data obtained through next generation sequencing. By training the model locally, i.e. learning its parameters based on observations in a specific genomic region, we can compare how DNA methylation fidelity varies genome-wide. In the paper, we focus on the computational challenges to scale parameter estimation to the whole-genome level, and present two methods to achieve this goal, one based on moment-based approximation and one based on simulation. We extensively tested our methods on synthetic data and on a first batch of experimental data