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151.
Seyed Ali Modarres Najafabadi József Kövecses Jorge Angeles 《Multibody System Dynamics》2008,20(2):163-176
This paper outlines a novel approach to the modeling and analysis of impact involving multibody systems. This approach is
based on an analysis of energy absorption and restitution during impact, using a decomposition of the kinetic energy, which
decouples the parts associated with the spaces of admissible and constrained motions of the underlying unilateral constraints.
Such a decomposition turns out to be useful in the analysis of energy dissipation during impact, and leads to a generalized
definition of the energetic coefficient of restitution, which targets particularly collisions in multibody systems. The applicability
of the approach reported is investigated by conducting an experimental study on a robotic testbed. It is shown that impact
between multibody systems is considerably affected not only by the local dynamics characteristics of the interacting bodies,
but also the configuration of the whole multibody system. The results reported here show that our decomposition can offer
a sound characterization of impact in several problems of multibody systems. 相似文献
152.
Salman A. Al‐Shami Md Rawi Che Salmah Siti Azizah Mohd Nor Abu Hassan Ahmad Nur Adibah Mohd Ishadi Hamady Dieng 《河流研究与利用》2013,29(9):1195-1204
Rapid industrialization and urbanization has led to increasing input of chemical contaminants into the aquatic environment of Malaysia. Despite the threat civilization poses to the biota, there are still very few relevant studies on ecotoxicological testing of river ecosystems. To overcome this knowledge gap, we examined lethal and genotoxic effects of sediments from different rivers of the northern Malaysia against Chironomus kiiensis, a group well represented in the aquatic fauna of this region. We exposed the larvae to sediments from Selama River (SR), Permatang Rawa River (PRR) and Kilang Ubi River (KUR) at various durations (0, 6, 12, 24 and 48 h). The larval mortality was monitored, whereas DNA damage in survivors' cells was determined using the comet assay. Pollution level indexed by the amounts of heavy metals and other organic contaminants in the sediment showed progressive increases from SR to PRR to KUR. Highly polluted sediments (PRR to KUR) were detrimental to C. kiiensis larvae, most of which did not survive following exposure for long periods. DNA analyses revealed greater damages in nuclei derived from larvae maintained on polluted sediments, in particular, those from KUR. The effects on the genomic material of C. kiiensis larvae occurred in a time‐dependent manner, with damage level increasing as exposure time progressed. Our results highlight the genotoxic properties of polluted sediments. More importantly, this study showed that C. kiiensis larvae could respond to different levels of pollution with respect to exposure time. It is concluded that C. kiiensis larvae is a potential candidate for river ecotoxicological monitoring. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
153.
Kamarulzaman Kamarudin Syed Muhammad Mamduh Ali Yeon Md Shakaff Shaharil Mad Saad Ammar Zakaria Abu Hassan Abdullah 《仪器科学与技术》2013,41(1):74-88
Characterization and calibration of gas sensor is a complex problem due to the dynamic behavior of gases and the limitations of current technology. This article reports a flexible, robust, and autonomous integrated system that is able to perform characterization on metal oxide-based gas sensors in dynamic environments. The system controls the concentration and flow of the relevant gases into the gas chamber and simultaneously measuring the sensor response. This feature allows the characterization of the sensor under continuous dynamic flow of gases similar to conditions on a robot or flow pipes. Several experiments have been performed on the system using hydrogen sulfide. The results provide information on the general characteristics of the sensor as well as its sensitivity. The noise levels were studied with different reference voltages. Overall, the results verify that the system is reliable and able to produce repeatable measurements. 相似文献
154.
ABSTRACT In this paper, the finite element technique used in the analysis and design of water distribution networks will be presented. The method was applied successfully to the solution of three different networks. In order to demonstrate the feasibility of the approach and to show some merits and demerits of the finite element method, a comparison was made on a digital computer with the standard Hardy Cross method. In all cases the finite element method was shown to provide superior performance. Moreover, the programmes were run on three different machines [Wang vs 100, Apple IIe, and IBM micro-computer] to show the effect of increasing storage capacity, machine accuracy, and time saving. 相似文献
155.
Alasl MK Khosravi M Hosseini M Pazuki GR Nezakati Esmail Zadeh R 《Water science and technology》2012,66(9):1962-1967
Physico-chemical water quality parameters and nutrient levels such as water temperature, turbidity, saturated oxygen, dissolved oxygen, pH, chlorophyll-a, salinity, conductivity, total nitrogen and total phosphorus, were measured from April to September 2011 in the Karaj dam area, Iran. Total nitrogen in water was modelled using an artificial neural network system. In the proposed system, water temperature, depth, saturated oxygen, dissolved oxygen, pH, chlorophyll-a, salinity, turbidity and conductivity were considered as input data, and the total nitrogen in water was considered as output. The weights and biases for various systems were obtained by the quick propagation, batch back propagation, incremental back propagation, genetic and Levenberg-Marquardt algorithms. The proposed system uses 144 experimental data points; 70% of the experimental data are randomly selected for training the network and 30% of the data are used for testing. The best network topology was obtained as (9-5-1) using the quick propagation method with tangent transform function. The average absolute deviation percentages (AAD%) are 2.329 and 2.301 for training and testing processes, respectively. It is emphasized that the results of the artificial neural network (ANN) model are compatible with the experimental data. 相似文献
156.
Ata Allah Taleizadeh Seyed Taghi Akhavan Niaki Seyed Mohammad Haji Seyedjavadi 《Journal of Manufacturing Systems》2012
In this paper, a multiproduct inventory control problem is considered in which the periods between two replenishments of the products are assumed independent random variables, and increasing and decreasing functions are assumed to model the dynamic demands of each product. Furthermore, the quantities of the orders are assumed integer-type, space and budget are constraints, the service-level is a chance-constraint, and that the partial back-ordering policy is taken into account for the shortages. The costs of the problem are holding, purchasing, and shortage. We show the model of this problem is an integer nonlinear programming type and to solve it, a harmony search approach is used. At the end, three numerical examples of different sizes are given to demonstrate the applicability of the proposed methodology in real world inventory control problems, to validate the results obtained, and to compare its performances with the ones of both a genetic and a particle swarm optimization algorithms. 相似文献
157.
Seyed Jafar Sadjadi Seyed Ahmad Yazdian Kamran Shahanaghi 《Computers & Industrial Engineering》2012,62(1):349-358
In the classical economic production quantity (EPQ) problem demand is considered to be known in advance. However, in the real-world, demand of a product is a function of factors such as product’s price, its quality, and marketing expenditures for promoting the product. Quality level of the product and specifications of the adopted manufacturing process also affect the unit product’s cost. Therefore, in this paper we consider a profit maximizing firm who wants to jointly determine the optimal lot-sizing, pricing, and marketing decisions along with manufacturing requirements in terms of flexibility and reliability of the process. Geometric programming (GP) technique is proposed to address the resulting nonlinear optimization problem. Using recent advances in optimization techniques we are able to optimally solve the developed, highly nonlinear, mathematical model. Finally, using numerical examples, we illustrate the solution approach and analyze the solution under different conditions. 相似文献
158.
159.
Moussa Sofiane Karoui Yannick Deville Shahram Hosseini Abdelaziz Ouamri 《Pattern recognition》2012,45(12):4263-4278
Remote sensing has become an unavoidable tool for better managing our environment, generally by realizing maps of land cover using classification techniques. Traditional classification techniques assign only one class (e.g., water, soil, grass) to each pixel of remote sensing images. However, the area covered by one pixel contains more than one surface component and results in the mixture of these surface components. In such situations, classical classification is not acceptable for many major applications, such as environmental monitoring, agriculture, mineral exploration and mining, etc. Most methods proposed for treating this problem have been developed for hyperspectral images. On the contrary, there are very few automatic techniques suited to multispectral images. In this paper, we propose new unsupervised spatial methods (called 2D-Corr-NLS and 2D-Corr-NMF) in order to unmix each pixel of a multispectral image for better recognizing the surface components constituting the observed scene. These methods are related to the blind source separation (BSS) problem, and are based on sparse component analysis (SCA), clustering and non-negativity constraints. Our approach consists in first identifying the mixing matrix involved in this BSS problem, by using the first stage of a spatial correlation-based SCA method with very limited source sparsity constraints, combined with clustering. Non-negative least squares (NLS) or non-negative matrix factorization (NMF) methods are then used to extract spatial sources. An important advantage of our proposed methods is their applicability to the possibly globally underdetermined, but locally (over)determined BSS model in multispectral remote sensing images. Experiments based on realistic synthetic mixtures and real multispectral images collected by the Landsat ETM+ and the Formosat-2 sensors are performed to evaluate the performance of the proposed approach. We also show that our methods significantly outperform the sequential maximum angle convex cone (SMACC) method. 相似文献
160.