Narrow Results

Nowadays, almost all of the enterprises are facing resources and materials with multimodal format. For example, textual information can be mixed with visual scenes, and visual information can be also mixed with textual scenarios. As a result, such information fusion among multimodal materials costs a large amount of human labors in daily management affairs. To deal with such issue, this paper introduces deep learning to characterize gap between vision and texts, and proposes a deep learning-based multimodal resource reconstruction scheme via awareness of table document, so as to facilitate digital enterprise management. A deep neural network is developed to construct a method to automatically extract table texts from images, so that multimodal information fusion can be realized. This can reduce much human labor in recognizing textual characteristics from visual scenarios, which can further facilitate the resource dispatching activities in the process of digital enterprise management. Some experiments are also conducted upon the basis of real-world data set, and proper results are obtained to prove that the proposal is endowed with considerable efficiency.

Restricting the analysis to general 2×2 coordination games, this article shows how under certain conditions, it is highly likely that individuals coordinate on a (pay-off) efficient through risk inferior convention. This contrasts with other equilibrium refinement criteria, such as risk dominance or stochastic stability. Here it is assumed that players are situated on a toroidal regular lattice, interact only locally and, in each period, imitate the last period's most successful player in their neighborhood. If the set of observable players by an individual and the set that he interacts with are both identical and small, pay-off dominance plays the major role in defining the long-term convention. As the latter set of players increases, a risk dominant but pay-off inferior convention becomes more likely. The model also shows that the interaction of two player types in a nonsymmetric game potentially leads to nonegalitarian conventions.

Rectangular concrete-filled steel tubular (RCFST) columns can be designed to have unequal wall thickness to maximize their resistance to combined axial and uniaxial bending loads. However, there is very little published research on their local–global interaction buckling behavior. This paper presents an efficient fiber-based simulation model for analyzing the inelastic interaction buckling of eccentrically loaded RCFST slender columns with unequal wall thickness. The model considers the progressive local–global interaction buckling, distributed plasticity, concrete cracking and crushing, second-order effects, and geometric imperfections. The mathematical model is programmed to compute not only the axial load–displacement responses but also the interaction curves of axial load and moment of slender RCFST columns. The simulation modeling is validated by experimentally measured data. The validated computer model is used to parametrically study the interaction local–global buckling responses of RCFST columns while the range analysis is conducted to identify the relative significance of key parameters. It is demonstrated that the proposed computer model accurately simulates experimentally measured responses. Hence, it can be used with confidence in practice to analyze and design RCFST slender columns fabricated with steel plates of unequal thickness. The existing design standard AS/NZS 2327:2017 provides acceptable strength predictions of RCFST slender columns and beam-columns while the procedure specified in Eurocode 4 overestimates their capacities.

The Internet today offers primarily a best-effort service. Research and technology development efforts are currently underway to allow the provisioning of better than best-effort quality of service assurances. In this article, we develop a spot pricing framework for expected bandwidth guaranteed Internet service contracts on a single domain. A nonlinear pricing model that maximizes the total surplus with cost constraints forms the basis for the framework. The spot price process is obtained for different demand profiles of the customer-base and demand arrival characteristics. Simulation modeling and analysis is employed to implement the pricing framework and analyze the price process under different market conditions and changes due to network failures. The framework when implemented at access or exchange points of different service provider domains will provide assured bandwidth for inter-domain traffic.

Simulation technique has been employed to predict rice yield of Kandhamal plateaus in Orissa (India) using the data of previous years. Preliminary simulation model has been developed. The test for uniformity and independence has been conducted using Kolmogrov–smironov test and auto-correlation test, respectively. The result obtained has been subjected to testing of hypothesis by using two sided test. Data for five years (1995 to 2000) are used for model validation and the sample size is increased to 12 years i.e., from 1995 to 2007 for prediction up to 2012. Sensitivity analysis is conducted by changing the parameters within feasible limits to find out the effect on the model.

Nowadays, verification and validation activities have become the prominent parameters to check the acceptability of a simulation model by the users for the intended purpose. This review paper aims to identify and analyze the recent development and challenges of simulation model verification and validation. To achieve this objective, a systematic review of the literature was carried out which mainly consisted of the methodological development of verification and validation process paralleled with simulation model development. Initially, a cumulative total of 980 records was found sourced from Google Scholar via an advanced search method, Science Direct, Web of science and from Scopus. Through a rigorous screening process about 72 sources or publications were included for analysis. The verification and validation techniques that have been developed so far were classified into five categories methodologically. From intensive analysis, it is found that researchers extensively scrutinize the traditional methods and graphical/ statistical tools, escalating interest in data-driven and automation techniques, and limited focus on agent-based and hybrid models. Though agent-based and hybrid models are increasingly vital in the realm of complex system simulations, their verification and validation processes remain relatively under-explored. Though reasonable efforts have been exerted on the verification and validation methods development, still academicians and researchers agreed on the lack of verification and validation methodology for the recently developed simulation model paradigms such as agent-based and hybrid models, autonomous robotics models, high fidelity and data-driven models, and real-time prediction models such as digital twins. As a challenge of verification and validation processes, lack of universal methodologies, lack of reliable real-world data for validation, inaccuracy of real-world data for the intended purpose, different world views by different individuals, and the rapid growth and complexity of simulation modeling are identified as the hindering factors of verification and validation process.

Mathematical modeling and computer simulation of grain drying are the major emphasis of grain drying research in China Agricultural University. In this paper research on simulation of mixed flow grain dryers had been accomplished. Mathematical model of MFGD had been established. The developed software had been used in analysis, design and optimization of mixed flow grain dryers. Effect of air temperature, air flow rate, size and location of air duct on the drying rate and energy consumption was discussed and analyzed. Experimental research was carried out to validate the simulation results. Emphasis was put on the Influence of air duct size distribution and number of rows on the performance of mixed flow grain dryer.

After reading this chapter, you should have a general understanding of how river basin models are developed and how they are used within the field of international water resources. You should also have gained a basic understanding of some of the ways in which countries have attempted to use river basin models.

Supply chain information is crucial in supporting supply chain management (SCM) and decision making. Computer simulation is an applicable approach for modeling supply chain system, which includes a great deal of complicated and uncertain elements. This chapter focuses on introducing a simulation approach to model supply chain business processes, especially information flow, material flow and capital flow, and explaining how to use simulation results to support supply chain decisions.

Aiming at the typical structure of military aircraft avionics systems, this paper presents a design of the airborne embedded training system. In this paper, the design requirements of embedded training system are discussed, which lay the groundwork for the improvement of the airborne embedded training system design plan. The overall architecture of airborne embedded training system is designed in details. The Arena simulation software is used to simulate the integration process between airborne embedded training system and other avionics systems. The evaluation of quota system of training is formulated. VC++6.0 is used to make simulation for performance evaluation process.

The increase of renewable energy exploitation is a current topic in the energy field. One of the main obstacles to the use of renewable energy in the global energetic mix is represented by the fluctuating nature of renewable power sources, since power fluctuations are cause of stress for the electric grid. A possibility to widely exploit renewable sources is the implementation of a “smart grid”, consisting in an interconnection of several smart-nodes. To reduce the stochastic effect of the renewable energy source it is possible to equip the nodes an energy storage managed in order to smooth the power peaks. In this regard, a dynamic analysis was carried out in order to integrate the renewable sources with the electric grid. This work presents a simulation model of a smart node consisting in a user power profile, a photovoltaic panel and a battery. Tests were worked out in different node configurations, in order to evaluate the incidence on the energy flows and on the grid distortion factor. Simulations were repeated by implementing the system with an algorithm for home automation in order to exploit intelligently the energy from the renewable source. This algorithm allows to synchronizethe operation of certain loads to the sun irradiation power.

Based on MTF optical system modeling and ZEMAX ray tracing system to simulate the original image. Setting up the actual optical path, established the MTF simulation model and ZEMAX simulation model according to the actual optical path, analysis to simulate image. Analysis the difference between the two kinds of modeling method on the image, and evaluate modeling methods. Appling two modeling methods to real remote sensing images to simulate the degraded images. The results show that, modeling based on ZEMAX ray tracing is more realistic to reflect the change in optical system on image, as a result, it's more suitable for remote sensing image simulation.