Numerical Solutions for Heat Transfer of An Unsteady Cavity with Viscous Heating

The mechanism of viscous heating of a Newtonian fluid filled inside a cavity under the effect of an external applied force on the top lid is evaluated numerically in this exploration. The investigation is carried out by assuming a two-dimensional laminar in-compressible fluid flow subject to Neumann boundary conditions throughout the numerical iterations in a transient analysis. All the walls of the square cavity are perfectly insulated and the top moving lid produces a constant finite heat flux even though the fluid flow attains the steady-state condition. The objective is to examine the effects of viscous heating in the fully insulated lid-driven cavity under no-slip and free-slip Neumann boundary conditions coupled with variations in Reynolds and Prandtl numbers. The partial differential equations of time-dependent vorticity-stream function and thermal energy are discretized and solved using a self-developed finite difference code in MATLAB^® environment. Time dependence of fluid thermodynamics is envisaged through contour and image plots. A commercial simulation software, Ansys Fluent^® utilizing a finite element code is employed to verify the finite difference results produced. Although the effect of viscous heating is very minimal, Neumann no-slip and free-slip boundary conditions are able to trap the heat inside the fully insulated cavity as the heat flux is constantly supplied at the top lid. A lower Reynolds number and a greater Prandtl number with free-slip effects reduce temperature distribution in the cavity with a faster velocity than in the no-slip condition as the free-slip behaves as a lubricant.     

An Intelligent Graph Edit Distance-Based Approach for Finding Business Process Similarities

There are numerous application areas of computing similarity between process models. It includes finding similar models from a repository, controlling redundancy of process models, and finding corresponding activities between a pair of process models. The similarity between two process models is computed based on their similarity between labels, structures, and execution behaviors. Several attempts have been made to develop similarity techniques between activity labels, as well as their execution behavior. However, a notable problem with the process model similarity is that two process models can also be similar if there is a structural variation between them. However, neither a benchmark dataset exists for the structural similarity between process models nor there exist an effective technique to compute structural similarity. To that end, we have developed a large collection of process models in which structural changes are handcrafted while preserving the semantics of the models. Furthermore, we have used a machine learning-based approach to compute the similarity between a pair of process models having structural and label differences. Finally, we have evaluated the proposed approach using our generated collection of process models.     

Heterogeneous Cubic Multidimensional Integrated Circuit for Water and Food Security in Fish Farming Ponds

Among major food production sectors, world aquaculture shows the highest growth rate, providing more than 50% of the global seafood market. However, water pollution in fish farming ponds is regarded as the leading cause of fish death and financial losses in the market. Here, an Internet of Things system based on a cubic multidimensional integration of circuit (MD‐IC) is demonstrated for water and food security applications in fish farming ponds. Both faces of the silicon substrate are used for thin‐film‐based device fabrication. The devices are interconnected via through‐silicon‐vias, resulting in a bifacial complementary metal‐oxide‐semiconductor‐compatible electronics system. The demonstrated cubic MD‐IC is a complete, small, and lightweight system that can be easily deployed by farmers with no need for specialists. The system integrates on its outer sides simultaneous air and water quality monitoring devices (temperature, electrical conductivity, ammonia, and pH sensors), solar cells for energy‐harvesting, and antenna for real‐time data‐transfer, while data‐management circuitry and a solid‐state battery are integrated on its internal faces. Microfluidic cooling technology is used for thermal management in the MD‐IC. Finally, a biofriendly polymeric encapsulation is used to waterproof the embedded electronics, improve the mechanical robustness, and allow the system to float on the surface of the water.     

A genetic algorithm approach to solving the anti-covering location problem

Abstract: In this paper we address the problem of locating a maximum weighted number of facilities such that no two are within a specified distance from each other. A natural process of evolution approach, more specifically a genetic algorithm, is proposed to solve this problem. It is shown that through the use of a commercially available spreadsheet-based genetic algorithm software package, the decision-maker with a fundamental knowledge of spreadsheets can easily set up and solve this optimization problem. Also, we report on our extensive computational experience using three different data sets.     

Machine learning and directional switching median-based filter for highly corrupted images

In this paper, two-stage machine learning-based noise detection scheme has been proposed for identification of salt-and- pepper impulse noise which gives excellent detection results for highly corrupted images. In the first stage, a window of size $3\times 3$ is taken from image and some other features of this window are used as input to neural network. This scheme has distinction of having very low missed detection (MD) and false positives rates. In the second stage, decision tree-based algorithm (J48) is applied on some well-known statistical parameters to generate rules for noise detection. These noise detection methods give promising results for identification of noise from highly corrupted images. A modified version of switching median filter (directional weighted switching median filter) is proposed for noise removal. Performance of noise detector is measured using MD and false alarm FA. Filtering results are compared with state-of-the-art noise removal techniques in terms of peak signal-to-noise ratio and structural similarity index measure. Extensive experiments are performed to show that the proposed technique gives better results than state-of-the-art noise detection and filtering methods.     

Dynamic integral sliding mode for MIMO uncertain nonlinear systems

In this paper the authors propose a novel sliding mode control methodology for Multi-Input and Multi-Output (MIMO) uncertain nonlinear systems. The proposed approach synthesizes dynamic sliding mode and integral sliding mode control strategies into dynamic integral sliding mode. The new control laws establish sliding mode without reaching phase with the use of an integral sliding manifold. Consequently, robustness against uncertainties increases from the very beginning of the process. Furthermore, the control laws considerably alleviate chattering along the switching manifold. In addition, the performance of the controller boost up in the presence of uncertainties. A comprehensive comparative analysis carried out with dynamic sliding mode control and integral sliding mode control demonstrates superiority of the newly designed control law. A chatter free regulation control of two uncertain nonlinear systems with improved performance in the presence of uncertainties ensures the robustness of the proposed dynamic integral sliding mode controller.     

Elastic caching solutions for content dissemination services of ip-based internet technologies prospective

Multimedia Tools and Applications - The Information-Centric Networking (ICN) provides a new data dissemination Internet paradigm to support the communication services that will meet the...     

The impact of team task and job engagement on the transfer of tacit knowledge in e-business virtual teams

This research focuses on the initiative to integrate team task and job engagement as related to the transfer of tacit knowledge. The aim of this study is to investigate if team task and job involvement enhances the overall work efficiency through transfer of tacit knowledge between e-business virtual teams. We develop a model that is based on the relationship between tacit degree of knowledge, job engagement, team tasks, and their effect on knowledge transfer. The conceptual model is validated with the data collected from a survey. The results indicate that the tacit knowledge does not have a positive effect on team tasks and job engagement, and the team tasks and job engagement have a significant positive effect on knowledge transfer. In addition, the study found that team tasks and job engagement have mediating effects in the process of tacit knowledge transfer. Also, we discuss the theoretical and practical implications and contributions of this study.     

Solving a class of facility location problems using genetic algorithms

Locating p facilities to serve a number of customers is a problem in many areas of business. The problem is to determine p facility locations such that the weighted average distance traveled from all the demand points to their nearest facility sites is minimized. A variant of the p-median problem is one in which a maximum distance constraint is imposed between the demand point and its nearest facility location, also known as the p-median problem with maximum distance constraint. In this paper, we apply a fairly new methodology known as genetic algorithms to solve a relatively large sized constrained version of the p -median problem. We present our computational experience on the use of genetic algorithms for solving the constrained version of the p-median problem using two different data sets. Our comparative experimental experience shows that this solution procedure performs quite well compared with the results obtained from existing techniques.