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Owing to the black-box nature of services, selecting a trustworthy service that best fits users' requirements is greatly critical in service-oriented computing. Once a set of services fulfilling users' functional requirements are founded, one of these services invoked by the users depends mostly on the Quality of Services (QoS), particularly security, trust, and reputation. This paper proposes a trust...
Existing incentive schemes for peer-to-peer (P2P) file-sharing are rate-based, giving room for strategic peers to benefit from manipulative behaviors so as to treat honest peers unfairly. Specifically, strategic peers can achieve high performance by providing high upload rates which are useless to the system. On the other hand, honest peers suffer from getting low download rates even if they devote...
This article describes a system which performs a measurement task by controlling water level in an evaporation measuring setup. This measurement is inherently digital and the intelligent controller performs noise reduction and disturbance compensation. This measurement is based on oversampling for better noise shaping and increase in measurement accuracy. The proposed structure is implemented and...
With the rapid development of wireless networks, the solution for degradation of Transmission Control Protocol (TCP) over wireless networks becomes more and more significant because of the software reusability. In order to improve the performance of TCP protocol, several studies have been proposed in different directions. Some of them attempt to find a suitable path for TCP transmission. Expected...
The ultimate goal of distance metric learning is to use discriminative information to keep data samples in the same class close, and those in different classes separate. Local distance metric methods can preserve discriminative information by considering neighborhood influence. We propose a discriminative distance metric approach by maximizing local pair wise constraints. Based on the local learning...
Cloud computing brings new service models that offer users more flexibility and better resource control promising to improve the user's satisfaction in terms of Quality of Service. However, current cloud solutions, in particular above the Infrastructure-as-a-Service layer, don't provide automated solutions that address the Quality of Service users may want for their applications. In this paper we...
Security management requires quantitative security metrics in order to effectively distribute limited resources and justify investments into security. The problem is not only to select the right security metrics but also to be sure that the selected metrics correctly represent security strength. In this paper, we tackle the problem of formal analysis of different quantitative security metrics. We...
In online social networks, social influence of a user reflects his or her reputation or importance in the whole network or to a personalized user. Social influence analysis can be used in many real applications, such as link prediction, friend recommendation and personalized searching. Personalized Page Rank, which ranks nodes according to the probabilities that a random walk starting from a personalized...
Recommendation systems are popular information filtering tools that help people find what they want. Accuracy is the most widely used metric for evaluating recommendation systems. Recently, many research works have focused on new measurements beyond the accuracy of recommendation systems. In this paper, we propose a neighbor diversification collaborative filtering algorithm to improve the recommendation...
Social networks have brought a whole new era of staying connected with family, friends and even strangers. This enables us in finding similar kind of people around us or locating who is important for us. Indirectly it measures the relations with whom we have connected through social metrics e.g. Centrality, similarity etc. The same concept can be applied for efficient routing in disconnected networks...
This paper proposes a new image smoothing method invariant to affine transformation. In the field of image processing and recognition, Gaussian filtering is a common procedure for image smoothing. However Gaussian filtering is not affine invariant. This paper proposes a new method for image smoothing that is invariant under such affine transformation that does not change the area of any region in...
In this paper we consider certain gradient and Hamiltonian flows on adjoint orbits that generalize the Toda lattice flow. The Toda lattice can be shown to be a gradient flow on a suitable orbit. Here we discuss related gradient flows and consider the generalization of the Toda lattice flow to the Toda rigid body flow.
Identifying the patient-zero of an epidemic outbreak, locating the person who started a rumor in a social network, finding the computer that initiated the spreading of a computer virus in a network- these are all applications of localizing the source of diffusion in a network. Since most of the networks of interest are very large, we are usually able to observe only a part of the network. In this...
This paper presents a new comparison framework, with the view to help researchers in selecting the most appropriate illumination compensation algorithm to serve as a preprocessing step in computer vision applications. The main objective of this framework is to reveal the positive and negative characteristics of the algorithms, rather than providing a single metric to rank their overall performance...
Most Internet routing protocols have one of two algorithms lurking at their core — either Dijkstra's algorithm in the case of link-state protocols or a distributed Bellman-Ford algorithm in the case of distance-vector or path-vector protocols. When computing simple shortest paths these protocols can be modified to utilize all best paths with a combination of next-hop sets and Equal Cost Multi-Path...
In many cases of new actuation of compliant controlled or bio-inspired joint driven robot, a global identification of electrical and mechanical coupled dynamics is required. This paper proposes a technique which mixes a closed loop output error method with the inverse dynamic identification model method which allows using linear least-squares technique to estimate the parameters. A first approach...
In our previous work, we proposed to use a vehicle network for data gathering, i.e. as an urban sensor. In this paper, we aim at understanding the theoretical limits of data gathering in a time slotted wireless network in terms of maximum service rate per node and end to end packet delivery ratio. The capacity of wireless networks has been widely studied and boundaries for that capacity expressed...
The purpose of full reference image quality indices like Mean Square Error (MSE) or SSIM is to predict the judgement of human observers in subjective quality assessment tasks. More advanced indices like SSIM or VIF are, however, rarely metrics in the strict sense, i.e. they don't define a distance between pairs of images that would describe how far these images are related. It was shown in a recent...
Multiple-shot person re-identification tackles the problem to build the correspondences between sets of human images obtained from distributed cameras. It is challenging due to large within-class variations and small between-class differences, caused by the changing of human appearance and environment. Existing methods for addressing this issue include designing the representation to capture the within-set...
In this paper we describe an objective smoothness assessment method for volume data. The metric can predict the extent of the difference in smoothness between a reference model, which may not be of perfect quality, and a distorted version. The proposed metric is based on the wavelet characterization of Besov function spaces. The comparison of Besov norm between two models can resolve the global and...
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