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The methodology of community detection can be divided into two principles: imposing a network model on a given graph, or optimizing a designed objective function. The former provides guarantees on theoretical detectability but falls short when the graph is inconsistent with the underlying model. The latter is model-free but fails to provide quality assurance for the detected communities. In this paper,...
In this article, a new method is presented in order to increase node dispersion on RRTs. This approach allows for a better environment representation, reducing the amount of nodes in the tree. The proposed RRT differs from Classic RRT by an insertion of a new node-tree connection method. The proposed affixing rule uses a tree whose edges are of variable length, which more rapidly explores the environment's...
Background: An increasing research effort has devoted to just-in-time (JIT) defect prediction. A recent study by Yang et al. at FSE'16 leveraged individual change metrics to build unsupervised JIT defect prediction model. They found that many unsupervised models performed similarly to or better than the state-of-the-art supervised models in effort-aware JIT defect prediction. Goal: In Yang et al.'s...
The prevalence of bridging defects makes bridging fault models important to consider during fault simulation and test generation. The large number of bridging faults that can be defined for a circuit led to the development of procedures for selecting subsets of bridging faults that are likely to occur based on the circuit layout, and hard-to-detect bridging faults whose coverage provides a more effective...
Understanding where people look in images is an important problem in computer vision. Despite significant research, it remains unclear to what extent human fixations can be predicted by low-level (contrast) compared to highlevel (presence of objects) image features. Here we address this problem by introducing two novel models that use different feature spaces but the same readout architecture. The...
Resource selection and task placement for distributed execution poses conceptual and implementation difficulties. Although resource selection and task placement are at the core of many tools and workflow systems, the methods are ad hoc rather than being based on models. Consequently, partial and non-interoperable implementations proliferate. We address both the conceptual and implementation difficulties...
This paper presents a design methodology with uncertainty quantification to estimate the required margin for two main design variables in a modular multilevel converter (MMC). In this methodology, the minimum required design margins are calculated by quantifying all sources of uncertainty in the modeling and simulation of MMCs. To this end, an enhanced modeling framework is presented to take into...
In this letter, a novel no reference image quality metric is developed, a set of ten features are extracted from each distorted image, then Relevance Vector Machine algorithm (RVM) is utilized to learn the mapping between the combined features and human opinion scores, experiments are conducted on the LIVE databases. The performance of the proposed metric is compared with some existing NR metrics...
In this paper we propose event goodput, i.e., the fraction of events which may be successfully managed by a system, as a relevant metric to describe the performance of battery powered real-time sensor networks. Unlike other performance metrics as response, completion, maximum lateness times, all representing fundamental, but different, figures of merit for the description of the behavior of real-time...
Riding on the waves of deep neural networks, deep metric learning has achieved promising results in various tasks by using triplet network or Siamese network. Though the basic goal of making images from the same category closer than the ones from different categories is intuitive, it is hard to optimize the objective directly due to the quadratic or cubic sample size. Hard example mining is widely...
To bridge the gap between humans and machines in image understanding and describing, we need further insight into how people describe a perceived scene. In this paper, we study the agreement between bottom-up saliency-based visual attention and object referrals in scene description constructs. We investigate the properties of human-written descriptions and machine-generated ones. We then propose a...
Cyber attacks are a critical threat to government infrastructure, commercial enterprises and personal devices. When belligerents attack cyber systems, they need to spread laterally to reach high value targets and communicate with their command and control sites. Intuitively, a layered defense including intrusion detection systems will limit the adversary's exploitation of the target. We apply lessons...
The paper provides the mathematical model describing the movement of different kinds of avalanche snow mass and its interaction with obstacles based on the modified method of particle dynamics. Further, the authors introduce their algorithm to calculate avalanche impact on buildings and structures; this algorithm underlies a computer program that allows you to set the basic parameters of a building,...
When using formal verification on critical software, an important question involves whether we have we specified enough properties for a given implementation model. To address this question, coverage metrics for property-based formal verification have been proposed. Existing metrics are usually based on mutation, where the implementation model is repeatedly modified and re-analyzed to determine whether...
In recent studies, researchers have developed various computation offloading frameworks for bringing cloud services closer to the user via edge networks. Specifically, an edge device needs to offload computationally intensive tasks because of energy and processing constraints. These constraints present the challenge of identifying which edge nodes should receive tasks to reduce overall resource consumption...
With the growing adoption of cloud computing for business systems, the efforts to keep those environments secure are also increasing. Virtualization infrastructures are key to support such systems, but engineers lack means to help them in selecting the best solutions according to their security requirements. The goal of this work is to define and develop a benchmarking approach to assess and compare...
This paper considers an orthogonal frequency division multiplexing system where the Effective Exponential SNR Mapping (EESM) is applied. We first present an approximate model in which the subcarriers grouped into one block are assumed to have the same channel coefficient and, subcarriers in different blocks have independent and identically distributed channel coefficients. Then, we present an algorithm...
Advancements over the last decade in video acquisition and display technologies lead to a continuous increase of video content resolution. These aspects combined with the shift towards cloud multimedia services and the underway adoption of High Efficiency Video Coding standards (HEVC) create a lot of interest for Super-Resolution (SR) and video enhancing techniques. Recent works showed that proximal...
This paper proposes an estimation method for the latent variable Rasch model based on the method of least squares which allows a continuous data set using. The research suggests the application of original approaches within the method for the solution of some applied problems. The authors explain how to use it for task assignment and work organization, decision-making under certainty and the securities...
Reducing carbon dioxide emissions is an important issue for the environment. The amine-based carbon capture system is a complex system with high energy consumption, and the system needs to be operated flexibly in a wide range. Therefore, advanced control technology is required and an appropriate model is a necessary condition for controller design. To this end, this paper investigates the nonlinearity...
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