In this paper, a new mathematical model is proposed for cellular manufacturing system considering the queuing based theory. Also machine breakdown and operator assignment problems are taken into account. To evaluate t...
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In this paper, a new mathematical model is proposed for cellular manufacturing system considering the queuing based theory. Also machine breakdown and operator assignment problems are taken into account. To evaluate the performance of proposed model, 4 numerical examples are generated randomly and solved using GAMS. Experimental results verify the applicability of proposed model in every industrial plant which implements a CMS. Also the sensitivity analysis of proposed numerical examples implies that optimal operator assignment solution has significant impact on the overall system efficiency.
This paper describes the mathematical modeling of the optimal power flow problem. The purpose is to optimize the power flow for a whole day, for a system in which several distributed generators (DGs) have been added. ...
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This paper describes the mathematical modeling of the optimal power flow problem. The purpose is to optimize the power flow for a whole day, for a system in which several distributed generators (DGs) have been added. There are two objective functions which are minimized, the generation cost and the total power losses of the system, while satisfying equality and inequality constraints. The optimization is performed for different DGs and load scale factors. The other generators from the system have a 1 scale factor.
This paper describes the simulation of a distributed generation system with storage technologies. The simulation is performed using a SCADA software for a distributed generation system, considering the generation cost...
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This paper describes the simulation of a distributed generation system with storage technologies. The simulation is performed using a SCADA software for a distributed generation system, considering the generation cost, the load and the availability of the system's generating units. Also, a storage unit is added to the system. An overview of the storage technologies is also presented.
This paper introduces a novel arterial blood pressure (ABP) signal model that generates statistically accurate synthetic signals with known characteristics. Using parameter identification from real ABP signals to form...
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This paper introduces a novel arterial blood pressure (ABP) signal model that generates statistically accurate synthetic signals with known characteristics. Using parameter identification from real ABP signals to form base parameter templates, our model applies stochastic processes to modulate cardiac cycle period and shape. A real-time control component modulates model parameters between cycle boundaries to emulate properties of real cardiovascular signals, such as arrhythmia, ectopic beats, resonances in the heart-rate variability spectrum, and respiratory cycle modulation of ABP signal amplitude. We present several examples to illustrate the capability of the proposed model.
The purpose of this paper is to measure the sustainability of corporate through using the relationship of major shareholder using complex system. As a result of case study, we can find two types of meaningful network....
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The purpose of this paper is to measure the sustainability of corporate through using the relationship of major shareholder using complex system. As a result of case study, we can find two types of meaningful network. First type is the clustering according to connectivity among major shareholders. Second Type is the network according to corporate group. First type shows small world network and characteristics of corporate group such like business style, decision making speed and owner risk. Second type shows scale-free network and investment preference according flowing power law in stock market. Third type is the clustering according to industry sector of stock focusing on Information Technology.
In this paper, a practical approach for the consideration of single pile and pile group installation effects in clay is presented using some novel procedures implemented in the finite element (FE) software package PLA...
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In this paper, a practical approach for the consideration of single pile and pile group installation effects in clay is presented using some novel procedures implemented in the finite element (FE) software package PLAXIS 2D. Data reported at a soft ciay site at Islais Creek, San Francisco are used to provide calibration for the constitutive model and to validate initial predictions of single pile installation effects. A short parametric study was then undertaken to examine the influence of a number of pile/soil parameters on the soil stresses generated around a single pile after installation and subsequent consoJidation. In addition, a new simplified method is proposed to consider group installation effects over-and-above those associated with an equivalent single pile involving the volumetric expansion of tunnels within a plane-strain framework. Remarkably, results show that the installation of additional group piles has a negligible influence after consolidation.
A new technology of low-frequency modulation of the arc current in MAG and MIG welding is presented. The technology provides control of thermal and crystallization processes, stabilizes the time of formation and cryst...
A new technology of low-frequency modulation of the arc current in MAG and MIG welding is presented. The technology provides control of thermal and crystallization processes, stabilizes the time of formation and crystallization of the weld pool. Conducting theoretical studies allowed formulating the basic criteria for obtaining strong permanent joints for high-duty structures, providing conditions for more equilibrium structure of the deposited metal and the smaller width of the HAZ. The stabilization of time of the formation and crystallization of the weld pool improves the formation of the weld and increases productivity in welding thin sheet metal.
Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning o...
ISBN:
(数字)9781627054478
Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli. In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances defined into knowledge bases. The aim of these measures is to assess the similarity or relatedness of such semantic entities by taking into account their semantics, i.e. their meaning---intuitively, the words tea and coffee, which both refer to stimulating beverage, will be estimated to be more semantically similar than the words toffee (confection) and coffee, despite that the last pair has a higher syntactic similarity. The two state-of-the-art approaches for estimating and quantifying semantic similarities/relatedness of semantic entities are presented in detail: the first one relies on corpora analysis and is based on Natural Language Processing techniques and semantic models while the second is based on more or less formal, computer-readable and workable forms of knowledge such as semantic networks, thesauri or ontologies. Semantic measures are widely used today to compare units of language, concepts, instances or even resources indexed by them (e.g., documents, genes). They are central elements of a large variety of Natural Language Processing applications and knowledge-based treatments, and have therefore naturally been subject to intensive and interdisciplinary research efforts during last decades. Beyond a simple inventory and categorization of existing measures, the aim of this monograph is to convey novices as well as researchers of these domains toward a better unders
Converting waste plastic into marketable hydrocarbons is a promising way to protect the environment and earn financial gain. While several kinetic studies have examined the cracking of waste plastic, they are often ov...
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Converting waste plastic into marketable hydrocarbons is a promising way to protect the environment and earn financial gain. While several kinetic studies have examined the cracking of waste plastic, they are often oversimplified or inappropriate for designing an industrial reactor. This work proves the necessity of using isoconversional methods by using Differential Scanning Calorimetry (DSC). DSC verified that cracking of waste plastic involves the production of several intermediates, indicating that the kinetics is more complex and requires further studies. Several isoconversional methods such as Friedman, Ozawa, Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS) and model-free were applied to estimate the apparent activation energy and frequency factor of thermal cracking of high-density polyethylene (HDPE) using non-isothermal and isothermal Thermogravimetric Analysis (TGA). The determined kinetic parameters from each method were evaluated against the experimental data. In order to overcome the failures and shortages engaged with the employed methods, a new isothermal isoconversional model was proposed and good matching results were observed.
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