Tabu search based algorithms for bandwidth-delay-constrained least-cost multicast routing

The advent of various real-time multimedia applications in high-speed networks creates a need for quality of service (QoS) based multicast routing. The Steiner tree problem, is a well-known NP-complete problem, provides the mathematical structure behind multicast communications. Two important QoS constraints are the bandwidth constraint and the end-to-end delay constraint. In this paper, we propose various algorithms to solve the bandwidth-delay-constrained least-cost multicast routing problem based on Tabu Search (TS), addressing issues of the selected initial solution and move type as two major building blocks in short-term memory version of Tabu Search and longer-term memory with associated intensification and diversification strategies as advanced Tabu Search techniques. We evaluate the performance and efficiency of the proposed TS-based algorithms in comparison with other existing TS-based algorithms and heuristics on a variety of random generated networks with regard to total tree cost. Finally we identify the most efficient algorithm uncovered by our testing.     

Modeling and validation of a photocatalytic oxidation reactor for indoor environment applications

Modern building ventilation design must take into account the health, safety and comfort of the occupants, as well as energy consumption and the environment. The system needs to protect occupants against chemical contaminants from numerous internal sources—office equipment, furniture, building materials, appliances, as well as intentional release. A promising technology which has great potential in this respect is UV photocatalytic oxidation (UV-PCO). Designing a UV-PCO system for a building requires full understanding of its performance, which strongly depends on the UV intensity field, types and concentration levels of reactants, oxygen and moisture levels, temperature, reflectance of duct surfaces, system configuration, orientation, air stream characteristics like temperature, humidity, air velocity and mixing, just to mention a few.This paper reports the development of a mathematical model for predicting the performance of a honeycomb monolith PCO reactor used in building mechanical ventilation systems. The model is validated by comparing its prediction with experimental data and with the prediction made by an existing model. The influence of several kinetic parameters such as airflow rate, pollutant inlet concentration, light intensity, humidity and catalyst deactivation has been investigated. The developed model can be used as a practical tool to simulate and optimize a UV-PCO system for application in building mechanical ventilation system.     

Computational fluid dynamics modeling of immobilized photocatalytic reactors for water treatment

A computational fluid dynamics (CFD) model for the simulation of immobilized photocatalytic reactors used for water treatment was developed and evaluated experimentally. The model integrated hydrodynamics, species mass transport, chemical reaction kinetics, and irradiance distribution within the reactor. The experimental evaluation was performed using various configurations of annular reactors and ultraviolet lamp sizes over a wide range of hydrodynamic conditions (350 < Re < 11,000). The evaluation showed that the developed CFD model was able to successfully predict the photocatalytic degradation rate of a model pollutant in the analyzed reactors. In terms of hydrodynamic models, the results demonstrated that the laminar model performs well for systems under laminar flow conditions, whereas the Abe‐Kondoh‐Nagano low Reynolds number and the Reynolds stress turbulence models give accurate predictions for photoreactors under transitional or turbulent flow regimes. The performed analysis confirmed that degradation rates of organic contaminants in immobilized photocatalytic reactors are strongly limited by external mass transfer; as a consequence, the degradation prediction capability of the CFD model is largely determined by the external mass transfer prediction performance of the hydrodynamic models used. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

Application of transfer functions to model water injection in hydrocarbon reservoir

Water flooding is one of the most economical methods to increase oil recovery. In order to improve the ultimate oil recovery during waterflooding, it is essential to provide an accurate forecast of reservoir performance. Hence, various methods have been utilized to simulate reservoirs. Although grid-based simulation is the most common and accurate method, time-consuming computation and the demand for large quantities of data restrict the use of this method. Sometimes, a quick overview of reservoir performance is sufficient or all required data are not accessible. Therefore, in this study a fast simulator is introduced to provide a quick overview with the minimum amount of data.A new method is presented to forecast the performance of water injection based on Transfer Function (TF). In this approach, it is assumed that a reservoir consists of a combination of TFs. The order and arrangement of TFs are chosen based on the physical conditions of the reservoir which are ascertained by examining several cases. The selected arrangement and orders can be extended to any other reservoirs. Injection and production rates act as input and output signals to these TFs, respectively. After analyzing input and output signals, the unknown parameters of TFs are calculated. Subsequently, it is possible to predict reservoir performance.Four different cases are employed to validate the derived equation. The results reveal a good agreement with those obtained from the common grid-based simulators. In addition, it has been demonstrated that the TF parameters depend on the characteristics and the pattern of different sections of the reservoir.This approach is a quick way to forecast waterflooding performance and can be a new window for the future of fast simulators. It provides the prediction with higher certainty in comparison with the other fast simulators. Furthermore, the only requirements for the method are injection and production rates. The analytical solution of the method enables its utilization in finding optimum rates for water injection in a short period of time. The method also presents some key parameters such as well connectivity. The use of the model is limited to situations when a rapid estimation is looked for and/or adequate data is not accessible.     

Modeling the combined conduction—Air infiltration through diffusive building envelope

This paper presents a comprehensive study of the thermal performance of the diffusive building envelope. As the infiltration air moves through the building envelope, it exchanges heat with the solid matrix. The temperature profile in the building envelope deviates from that of pure conduction, because of the heat exchange between infiltrated air and solid matrix. Numerical study was carried out to determine the contribution of air infiltration to the heat gain/loss through the diffusive building envelope. The model validation process was carried out at two different levels: inter-model comparison; validation with experimental data. At the inter-model level, the infiltration heat exchange efficiency of a wall was compared with the infiltration heat exchange efficiency predicted by an existing model in the literature. The results show good agreement between two models. The second level of validation compares the model's prediction with the existing experimental data. The results confirm that there are excellent agreement between prediction made by the numerical model and the experimental data.     

Measurement of diffusion coefficients of VOCs for building materials: review and development of a calculation procedure

The measurement and prediction of building material emission rates have been the subject of intensive research over the past decade, resulting in the development of advanced sensory and chemical analysis measurement techniques as well as the development of analytical and numerical models. One of the important input parameters for these models is the diffusion coefficient. Several experimental techniques have been applied to estimate the diffusion coefficient. An extensive literature review of the techniques used to measure this coefficient was carried out, for building materials exposed to volatile organic compounds (VOC). This paper reviews these techniques; it also analyses the results and discusses the possible causes of difference in the reported data. It was noted that the discrepancy between the different results was mainly because of the assumptions made in and the techniques used to analyze the data. For a given technique, the results show that there can be a difference of up to 700% in the reported data. Moreover, the paper proposes what is referred to as the mass exchanger method, to calculate diffusion coefficients considering both diffusion and convection. The results obtained by this mass exchanger method were compared with those obtained by the existing method considering only diffusion. It was demonstrated that, for porous materials, the convection resistance could not be ignored when compared with the diffusion resistance.     

Customer oriented enterprise IT architecture framework

Due to the rapid expansion and complexity of mechanisms, technologies, systems, processes and communications in organizations, governance and management has become something beyond the control of hardware and software systems and include integration and convergence of all components of an organization. Enterprise architecture (EA) by breaking down the organization’s systems to its components and determining the relationship between them in different layers offers an appropriate solution for understanding and investigating relationships and processes of organizations which develop strategies and information technology plans. This paper proposes a conceptual model for enterprise IT architecture. For this purpose, conceptual and reference models of enterprise architecture are investigated and key concepts of them are described. By identifying dimensions of reviewed models, key dimensions of the proposed model are extracted and by using Shannon’s entropy, weight and priority of each dimension is determined. In order to determine building blocks of each dimension, a mapping has been established between customer and functional requirements by using axiomatic method and relations between customer and functional requirements has been validated by experts’ opinions using Quality Function Development (QFD) method. Proposed model has been described by determining goals, components and relations. Then the model is validated by surveying experts. Finally an Iranian telecommunication enterprise is selected for a case study and the model is tested there and promoting solutions are proposed to improve the status of the organization for implementing the model.     

Modeling and physical interpretation of photocatalytic oxidation efficiency in indoor air applications

Volatile organic compounds (VOCs) are the major pollutants in indoor air, which significantly impact indoor air quality (IAQ). As a promising technique to remove VOCs, photocatalytic oxidation (PCO) takes the advantages of oxidation of a large range of VOCs with low energy consumption. In this study, the mass transports and reaction mechanism involved in the PCO process have been studied. In addition, the kinetic models of PCO on the different conditions of elementary reactions have been critically reviewed. Moreover, the factors that may affect the efficiency of PCO were interpreted based on the established fundamental mechanism of PCO. Some recommendations were made for future work to improve the efficiency of PCO system for building applications.     

Performance evaluation of 67 denoising filters in ultrasound images: A systematic comparison analysis

Noise corrupts ultrasound images and degrades spatial and contrast resolutions. Hence, it is challenging to characterize the lesions precisely using ultrasound images. The present study aims to evaluate 67 denoising filters and select the best one for ultrasound image denoising. Seven test images were synthesized to evaluate the performance of filters at three different noise levels. Eleven full-reference quantitative image quality metrics (IQMs) were employed to evaluate the performance of the filters. A new filter evaluation method, Rank Analysis, was introduced and utilized at each noise level. The ten best filters with the smallest mean rank in all noise levels were defined for further analysis on real ultrasound images. The Rank Analysis was also employed for real ultrasound images, and filters were evaluated based on 14 IQMs (11 full-reference and three no-reference). Finally, the best filter was defined using the repeated measures analysis statistical test. According to the Rank Analysis results, the Spatial correlation (SCorr) filter obtained the best results with the mean rank scores±SD of 1 ± 0, which was significantly better than the other nine filters (p < 0.001). The second-best results were achieved by three filters, Bitonic, most homogeneous neighborhood, and Lee diffusion (p < 0.05). We concluded that SCorr is the best filter for ultrasound image denoising. It can be used in the pre-processing step before segmentation and diagnostic procedures. In addition, a new filter evaluation method, Rank Analysis, was introduced in this study, which is easy to use, fast, and provides reliable results. So, it can be used to evaluate newly developed filters in the future studies.