Search results for "Article Subject"
showing 10 items of 698 documents
Mathematical Modeling and Parameters Estimation of Car Crash Using Eigensystem Realization Algorithm and Curve-Fitting Approaches
2013
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/262196 Open Access An eigensystem realization algorithm (ERA) approach for estimating the structural system matrices is proposed in this paper using the measurements of acceleration data available from the real crash test. A mathematical model that represents the real vehicle frontal crash scenario is presented. The model's structure is a double-spring-mass-damper system, whereby the front mass represents the vehicle-chassis and the rear mass represents the passenger compartment. The physical parameters of the model are estimated using cu…
Weather Derivatives and Stochastic Modelling of Temperature
2011
We propose a continuous-time autoregressive model for the temperature dynamics with volatility being the product of a seasonal function and a stochastic process. We use the Barndorff-Nielsen and Shephard model for the stochastic volatility. The proposed temperature dynamics is flexible enough to model temperature data accurately, and at the same time being analytically tractable. Futures prices for commonly traded contracts at the Chicago Mercantile Exchange on indices like cooling- and heating-degree days and cumulative average temperatures are computed, as well as option prices on them.
Hölder Continuity up to the Boundary of Minimizers for Some Integral Functionals with Degenerate Integrands
2007
We study qualitative properties of minimizers for a class of integral functionals, defined in a weighted space. In particular we obtain Hölder regularity up to the boundary for the minimizers of an integral functional of high order by using an interior local regularity result and a modified Moser method with special test function.
A Knowledge Management and Decision Support Model for Enterprises
2011
We propose a novel knowledge management system (KMS) for enterprises. Our system exploits two different approaches for knowledge representation and reasoning: a document-based approach based on data-driven creation of a semantic space and an ontology-based model. Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty. Copyright © 2011 Patrizia Ribino et al.
Advanced stochastic control systems with engineering applications
2014
1 School of Astronautics, Harbin Institute of Technology, Harbin, Heilongjiang, China 2 School of Electrical and Electronic Engineering, The University of Adelaide, SA 5005, Australia 3 Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway 4 Institute of Automation and Complex Systems, University of Duisburg-Essen, Duisburg, Germany 5 College of Automation, Chongqing University, Chongqing 400044, China
Information Sharing and Channel Construction of Supply Chain under Asymmetric Demand Information
2014
Information sharing and marketing channel building have become an important problem of supply chain management theory and practice. The research of information sharing focused on traditional channel of supply chain between upstream and downstream enterprises; however, the research ignores the behavior of information sharing with potential entrants and composite structure characteristics about traditional marketing channel with the direct channel. This paper uses the model to research the effects brought about sharing demand information with potential entrants and building marketing channel, which reveals information sharing and channel building mechanism in the supply chain. The study found…
Internet of Things with Deep Learning-Based Face Recognition Approach for Authentication in Control Medical Systems
2022
Internet of Things (IoT) with deep learning (DL) is drastically growing and plays a significant role in many applications, including medical and healthcare systems. It can help users in this field get an advantage in terms of enhanced touchless authentication, especially in spreading infectious diseases like coronavirus disease 2019 (COVID-19). Even though there is a number of available security systems, they suffer from one or more of issues, such as identity fraud, loss of keys and passwords, or spreading diseases through touch authentication tools. To overcome these issues, IoT-based intelligent control medical authentication systems using DL models are proposed to enhance the security f…
Effect of Opuntia ficus-indica Mucilage Edible Coating in Combination with Ascorbic Acid, on Strawberry Fruit Quality during Cold Storage
2021
Strawberry fruit is a nonclimacteric fruit and is one of the most consumed berries in the world. It is characterized by high levels of vitamin C, folate, vitamin E, β-carotene, and phenolic constituents as well asanthocyanins that are strictly related to health benefits. Strawberries are highly perishable fruit with a very short postharvest life due to their susceptibility to mechanical injury, rapid texture softening, physiological disorders, and infection caused by several pathogens (yeast and mold) that can rapidly reduce fruit quality. The aim of the present study was to evaluate the effect of the application of Opuntia ficus-indica mucilage in combination with ascorbic acid, as edible …
Distributed Data Clustering via Opinion Dynamics
2015
We provide a distributed method to partition a large set of data in clusters, characterized by small in-group and large out-group distances. We assume a wireless sensors network in which each sensor is given a large set of data and the objective is to provide a way to group the sensors in homogeneous clusters by information type. In previous literature, the desired number of clusters must be specified a priori by the user. In our approach, the clusters are constrained to have centroids with a distance at least ε between them and the number of desired clusters is not specified. Although traditional algorithms fail to solve the problem with this constraint, it can help obtain a better cluste…
On the Cryptanalysis of Two Cryptographic Algorithms That Utilize Chaotic Neural Networks
2015
This paper deals with the security and efficiency issues of two cipher algorithms which utilize the principles of Chaotic Neural Networks (CNNs). The two algorithms that we consider are (1) the CNN-Hash, which is a one-way hash function based on the Piece-Wise Linear Chaotic Map (PWLCM) and the One-Way Coupled Map Lattice (OCML), and (2) the Delayed CNN-Based Encryption (DCBE), which is an encryption algorithm based on the delayed CNN. Although both of these cipher algorithms have their own salient characteristics, our analysis shows that, unfortunately, the CNN-Hash is not secure because it is neither Second-Preimage resistant nor collision resistant. Indeed, one can find a collision with …