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Network centrality reflects node importance in networks, which is a challenging problem in social network analysis. Based on Fuzzy Set and MYCIN theory, this paper proposes a novel node centrality measuring method and models n-monkeys dataset, where n is 20. Initially, we created monkeys relationship graph and generated relationship matrix based on the monkeys' encountering times in a specific time...
Within the context of road estimation, the present paper addresses the problem of the fusion of several sources with different reliabilities. Thereby, reliability represents a higher-level uncertainty. This problem arises in automated driving and ADAS due to changing environmental conditions, e.g., road type or visibility of lane markings. Thus, we present an online sensor reliability assessment and...
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...
This paper gives an overview of the calorimetric systems used to determine the losses of converters and motors, introduces the standards in the scope of the topic briefly, and highlights the problems associated with the loss determination of high efficiency devices. The calorimeters are classified in four categories based on chamber configuration. Information about previously published calorimeters...
This paper describes the design and setup of different measuring systems for the calibration of commercial voltage and current transformer test sets for non-conventional instrument transformers. The calibration systems are recently developed at the national metrology institutes VSL, PTB, METAS and TUBITAK within the frame of the European project “FUTURE GRID — Non-conventional voltage and current...
The problem of measuring the contrast of image elements (objects and background) for complex monochrome images is considered in this paper. A new method for measuring the contrast of image elements is proposed on the basis of analytical assessments of the contrast of the corresponding elements of the initial and inverted images. The new definitions for weighted and relative contrast of image elements...
In this article control-based reduction of gantry crane elastic swinging in the trolley travel direction is concerned. As acceleration forces of the trolley are often the reason of these vibrations, they can be utilized in an appropriate damping strategy. For an elastic crane a dynamic model is derived applying the finite element method (FEM). This approach results in a high order state-space model,...
Belief reliability is a new reliability metric considering both aleatory uncertainty and epistemic uncertainty. This paper will give a case study of belief reliability theory, focusing on the reliability evaluation of a quad redundant servo system. In the case study, the belief reliabilities of four components are first evaluated by estimating design margin, aleatory uncertainty factor, and epistemic...
Fuzzy rough technique is a mathematical tool to deal with fuzzy and rough knowledge, which could reduce the redundant objects and attributes by keeping the information invariant. In the existing researches on fuzzy rough sets, all the attributes are assumed to have the same weights for the decision. Actually different attributes may play different roles on the decision. As a result, we introduce weights...
The advent of widely available photo collections covering broad geographic areas has spurred significant advances in large-scale urban scene modeling. While much emphasis has been placed on reconstruction and visualization, the utility of such models extends well beyond. Specifically, these models should support a wide variety of reasoning tasks (or queries), and thus enable advanced scene study....
This paper presents a novel framework for assessing the physical consistency between two terrestrial Essential Climate Variables (ECVs) products retrieved from Earth Observation at global scale. The proposed methodology assesses the level of temporal and spatial agreement between them using multitemporal data. This is based on the analysis of their temporal changes taking into account their associated...
We present a method for improving high-insertion-loss measurements with a calibrated vector network analyzer (VNA) requiring only two additional pieces of hardware. By utilizing an amplifier and an attenuator, and measuring wave-parameters rather than scattering-parameters, we are able to increase the dynamic range of our measurements while decreasing uncertainties due to the noise floor of the VNA...
A variety of end-user devices involving keypoint-based mapping systems are about to hit the market e.g. as part of smartphones, cars, robotic platforms, or virtual and augmented reality applications. Thus, the generated map data requires automated evaluation procedures that do not require experienced personnel or ground truth knowledge of the underlying environment. A particularly important question...
This paper presents a risk assessment algorithm for automatic lane change maneuvers on highways. It is capable of reliably assessing a given highway situation in terms of the possibility of collisions and robustly giving a recommendation for lane changes. The algorithm infers potential collision risks of observed vehicles based on Bayesian networks considering uncertainties of its input data. It utilizes...
This paper proposes a systematic procedure for the selection of controller design points in a linearized gain scheduling control context. The pointwise gap metric is first used to cluster linear systems obtained over the nonlinear system's operating space into a relatively small number of sectors. For each sector a suitable controller design point is provided. Existence of a linear controller stabilizing...
This paper studies linear set-dynamics driven by random convex compact sets (RCCSs), where the parameter matrix evolves according to an underlying Markovian random process taking values in a finite set. We derive dynamics of the expectations of the associated reach sets. We establish that such expectations evolve according to coupled deterministic set-dynamics. We provide sufficient conditions for...
There are two major challenges to the personalized recommendation method, one is the sparseness of characteristic attribute, the other is the excessive reliance on scoring data. To solve above problems, a personalized recommendation algorithm (PRM-Grey) based on grey theory is presented. Firstly, the nearest neighbor matrix formed through the similarity between the characteristic matrix rows. Then,...
Active learning has been widely used to select the most informative data for labeling in classification tasks, except for time series classification. The main challenge of active learning in time series classification is to evaluate the informativeness of a time series instance. Specifically, many informativeness metrics have been proposed for traditional active learning, however, none of them is...
Much prior work has studied cache replacement, but a large gap remains between theory and practice. The design of many practical policies is guided by the optimal policy, Belady's MIN. However, MIN assumes perfect knowledge of the future that is unavailable in practice, and the obvious generalizationsof MIN are suboptimal with imperfect information. What, then, is the right metric for practical cache...
Fault attack becomes a serious threat to system security and requires to be evaluated in the design stage. Existing methods usually ignore the intrinsic uncertainty in attack process and suffer from low scalability. In this paper, we develop a general framework to evaluate system vulnerability against fault attack. A holistic model for fault injection is incorporated to capture the probabilistic nature...
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