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Regrasping is the process of adjusting the position and orientation of an object in one's hand. The study of robotic regrasping has generally been limited to use of theoretical analytical models and cases with little uncertainty. Analytical models and simulations have so far proven unable to capture the complexity of the real world. Empirical statistical models are more promising, but collecting good...
Several stakeholders are increasingly interested in operational risks and their impact on key business projects such as outsourcing projects. To guide stakeholders and project managers to take decisions related to the outsourcing of one or multiple activities, we propose a decision support system for classifying organizational risks, as example of operational risks, into different risk categories...
The secure integration of renewable generation into modern power systems requires an appropriate assessment of the security of the system in real-time. The uncertainty associated with renewable power makes it impossible to tackle this problem via a brute-force approach, i.e. it is not possible to run detailed online static or dynamic simulations for all possible security problems and realizations...
The design of path allegiance metric (PAM) based routing protocol leverages upon a trust management framework proposed in our earlier works. The PAM routing protocol strives to provide data plane security in mobile ad hoc network and its working is based upon the belief, disbelief and uncertainty components of the trust management framework which assigns a trust metric based upon the packet forwarding...
In the context of swift development of P2P e-commerce, it is critical to defending both customers and sellers from being victimized by probable deception stemming from uncertainties, vagueness and ambiguities that characterize the interactions amongst unfamiliar dealers. Accordingly, credit standing concerning each business partaker plays a decisive part in preventing fraud in P2P transactions and...
The Carbon Capture Simulation Initiative (CCSI) project has developed and deployed scientific infrastructure called the CCSI Toolset. The CCSI Toolset provides state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants...
Because of coexistence of aleatory uncertainty and epistemic uncertainty in engineering design, we represented a method of unifying aleatory uncertainty and epistemic uncertainty, and that is to quantifying probability uncertainty for structures of evidence theory (D-S theory), thereafter this method will provide theory foundation for uncertainty quantification of complex machinery. Probability density...
The use of prior distributions is often a controversial topic in Bayesian inference. Informative priors are often avoided at all costs. However, when prior information is available informative priors are an appropriate way of introducing this information into the model. Furthermore, informative priors, when used properly and creatively, can provide solutions to computational issues and improve modeling...
In this paper, we propose a Skyline service selection approach based on QoS prediction. We first consider the QoS history records as time series and predict the QoS values by using Autoregressive Integrated Moving Average (ARIMA) model to provide more accurate QoS attributes values. And then we calculate the uncertainty of the prediction result by adopting an improved Coefficient of Variation. In...
The principal goal of this contribution is to present two different approaches to description and robust stability analysis of continuous-time fractional order uncertain systems. The first approach uses fractional order models with parametric uncertainty and robust stability of corresponding closed-loop control systems is investigated by using the value set concept in combination with the zero exclusion...
Robust Unit Commitment (UC) model has been intensively investigated as an effective approach to hedge against randomness and risks. All existing robust UC formulations consider uncertainties in demand and/or cost. We observe that, nevertheless, a power system could be seriously affected by surrounding temperature and there is a strong relationship among the efficiency of gas generators, demand and...
The computational method and model of Module of Modeling of Computational Systemic Mind Under Uncertainty is oriented on use as plug-in in systems of Artificial Intelligence, which are characterized by the ability to be self-organized and to operate computationally, intellectually, autonomously, systemically and continuously real time, under uncertainty, in inhomogeneous subject areas, in unknown...
Power system operators have traditionally addressed system uncertainty through the scheduling of operating reserves. These reserves are excess capacity, either online or offline, that can quickly be used to address unforeseen events in the load profile. As renewable energy resources, namely wind and solar, new techniques are being developed to address the uncertainty introduced from these sources...
Two usually distinct paradigms exist to model uncertainties. The stochastic one deals with random uncertainties. Strong assumptions about their probability distributions are often made, especially when online computation is required. For instance, assuming independent Gaussian distributions is common practice when using standard versions of the famous Kalman Filter. Though efficient to deal with measurement...
We study the spectrum allocation problem in flexgrid optical networks under demand uncertainty. Using elastic spectrum allocation the slots assigned to a lightpath can be changed under different restrictions without service disruption. We study five different technologies to manage these changes. It is shown that the two least efficient models are less computational demanding than the other variants...
Visual Background Extractor (ViBe) is a video moving object detection method with simple implementation and fast speed. ViBe uses a detection threshold (neighborhood size) to judge whether a pixel belongs to the background or the foreground. However, in some complicated scenes, the belongingness of the pixels is ambiguous. One cannot well perform the object detection using the ViBe with a single threshold,...
Noradrenaline participates in the neuromodulation of brain activity to modify the trade-off between exploration and exploitation when sensory contingencies have changed. Accordingly, attentional models of noradrenaline acting on sensory representations have been proposed. In this paper, we explore another possible action of this neuromodulator in the decision making process and report simulation results...
This paper presents a mathematical analysis of the impact of key-point detection errors on the similarity of local image descriptors that are based on histogram of gradients. First, we derive a closed-form expression for the 𝐿p distance between two descriptors, for general translation, scale and orientation detection errors. Second, we introduce a detailed analysis for the special case where translation...
Influence diagrams is getting extensively applied as rule acquisition in economics, business, and military fields, in traditional influence diagrams, computational models of dependence relations are established by probability distribution, which has good performance in deterministic information system. However, information systems(IS) in real world usually are uncertain or approximate, such as IS...
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