Development of an integrated model for airflow in building spaces

In building energy simulation, an integrated modelling of airflow in the building needed. Therefore, in this paper two approaches are used for building energy simulation: zonal network for modelling of the building segments and Computational Fluid Dynamics (CFD) for modelling of the airflow. It is noted that a synchronize solution process is needed for the building and the CFD equation-sets. For this purpose an iterative procedure is used to corresponding solution of these equations.     

Optimum loading of machines in a flexible manufacturing system using a mixed-integer linear mathematical programming model and genetic algorithm

Machine loading problem in a flexible manufacturing system (FMS) encompasses various types of flexibility aspects pertaining to part selection and operation assignments. The evolution of flexible manufacturing systems offers great potential for increasing flexibility by ensuring both cost-effectiveness and customized manufacturing at the same time. This paper proposes a linear mathematical programming model with both continuous and zero-one variables for job selection and operation allocation problems in an FMS to maximize profitability and utilization of system. The proposed model assigns operations to different machines considering capacity of machines, batch-sizes, processing time of operations, machine costs, tool requirements, and capacity of tool magazine. A genetic algorithm (GA) is then proposed to solve the formulated problem. Performance of the proposed GA is evaluated based on some benchmark problems adopted from the literature. A statistical test is conducted which implies that the proposed algorithm is robust in finding near-optimal solutions. Comparison of the results with those published in the literature indicates supremacy of the solutions obtained by the proposed algorithm for attempted model.     

Determining Flow Friction Factor in Irrigation Pipes Using Data Mining and Artificial Intelligence Approaches

The implicit Colebrook–White equation has been widely used to estimate the friction factor for turbulent fluid in irrigation pipes. A fast, accurate, and robust resolution of the Colebrook–White equation is, in particular, necessary for scientific intensive computations. In this study, the performance of some artificial intelligence approaches, including gene expression programming (GEP), which is a variant of genetic programming (GP); adaptive neurofuzzy inference system (ANFIS); and artificial neural network (ANN) has been compared to the M5 model tree, which is a data mining technique and, to most available approximations, is based on root mean squared error (RMSE), mean absolute error (MAE) and correlation coefficient (R). Results show that Serghides and Buzzelli approximations with RMSE (0.00002), MAE (0.00001), and R (0.99999) values had the best performances. Among the data mining and artificial intelligence approaches, the GEP with RMSE (0.00032), MAE (0.00026), and R (0.99953) values performed better. However, all 20 explicit approximations except Wood, Churchill (full range of turbulence including laminar regime) and Rau and Kumar estimated the friction factor more accurately than the GEP.     

Nonisothermal crystallization behavior and mechanical properties of PEEK/SCF/nano-SiO2 composites

Nonisothermal crystallization of hybrid PEEK composites reinforced with short carbon fibers (SCF) and nano-SiO₂ (1, 1.5 and 2 wt%) was investigated using DSC. Composites were fabricated by melt-mixing process at 400 °C. The Size of the nanoparticles was 13 nm. Samples were cooled from 410 °C to 25 °C with cooling rates of 10, 30, 50 and 70 °C min⁻¹. The onset, peak and end crystallization temperatures were investigated as well as absolute crystallization percentage and crystallization time. Avrami, Ozawa and Ozawa–Avrami equations were fitted to the data in order to investigate the crystallization kinetics. Mechanical behaviors of the composites were examined using nanoindentation and nanoscratching. DSC results revealed that absolute crystallization percentage increases in PEEK/SCF/1%SiO₂ and PEEK/SCF/1.5%SiO₂ samples compared to PEEK/SCF, however it decreases by adding more nano-SiO₂. Ozawa–Avrami is proved to be the best model for describing crystallization behavior of the composites while Avrami equation was suitable for describing a part of the crystallization process. The Avrami and Ozawa–Avrami constants were calculated. Besides, adding SCFs and nano-SiO₂ into PEEK results in a significant decrease in plasticity index, while increases the resistance to plastic deformation of the composite.     

Simulation of energy saving in Iranian buildings using integrative modelling for insulation

According to one survey on energy consumption in Iran, commercial and building sector consume more energy than any other economic sectors. For example, about 38% of total energy that consumed in year 2001 has been used for space heating. Insulation in external walls of buildings has an important role to reduce the environmental effects on indoor space condition. Therefore, always using insulation is an alternative to avoid from the energy loss. In this paper, the effects of the using of a proper insulation on the energy saving in Iranian buildings are studied. For this purpose, an integrative modelling is used for simulation of the energy consumption in buildings. It is shown that energy consumption per square meter of buildings can be reduced up to 35.2% when insulation is used for external walls.     

Convenient method for preparation of a new absorbent based on biofunctionalized graphene oxide hydrogels using nitrene chemistry and click reaction

A new graphene oxide (GO)-based hydrogel was synthesized through cross-linking of biofunctionalized graphene oxide nanosheets by di-alkyne polyethylene glycol as cross-linking agent. In this respect, nitrene chemistry as a convenient and straightforward protocol was developed for biofunctionalization of GO using an azido-starch as an eco-friendly, biodegradable and cost-effective material. In the next step, 1,3-dipolar cycloaddition chemistry, a green and highly efficient approach was utilized in cross-linking of functionalized GO by PEG through click reaction between remaining azido groups of starch on the surface of GO sheets and terminal alkyne groups of polyethylene glycol. Formation of aziridine and triazole rings during functionalization and cross-linking in this method could evidently improve biological activities of the obtained hydrogel compared to the conventional methods. The antibacterial activity of the new compounds was explored. The synthesized hydrogel showed antibacterial properties against Gram-positive and Gram-negative bacteria due to the presence of triazole rings. Also, the resulting hydrogel exhibited high dye removal efficiency and it can be utilized in water treatment effectively. The adsorption kinetics was analyzed through the effects of adsorption time and the dye concentration on the adsorption capacity. Kinetic data were accurately described by a pseudo-second-order model.     

A regression modelling approach for optimizing segmentation scale parameters to extract buildings of different sizes

Multiresolution segmentation (MRS) is one of the most commonly used image segmentation algorithms in the remote-sensing community. This algorithm has three user-defined parameters: scale, shape, and compactness. The scale parameter (SP) is the most crucial one in determining the average size of the image segments generated. Since setting this parameter typically requires a trial-and-error process, automatically estimating it can expedite the segmentation process. However, most of automatic approaches are still iterative and can lead to a time-consuming process. In this article, we propose a new, non-iterative framework for estimating the SP with an emphasis on extracting individual urban buildings. The basis of the proposed method is to investigate the feasibility of associating the size of urban buildings with a corresponding ‘optimal’ (or at least reasonable) SP using an explicit mathematical equation. Using the proposed method, these two variables are related to each other by constructing a mathematical (regression) model. In this framework, the independent variables were chosen to be the typical size of buildings in a given urban area and the spatial resolution of the image under consideration; and the dependent variable was chosen to be the corresponding optimal SP. To assess the potential of the proposed approach, two regression models that yielded explicit equations (i.e. degree-2 polynomial (DP), and regression tree (RT)) were employed. In addition, as a sophisticated and versatile nonlinear model, support vector regression (SVR) was utilized to further measure the performances of DP and RT models compared with it. According to the comparisons, the DP model was selected as a representative of the proposed approach. In the end, to evaluate the proposed methodology, we also compared the results derived from the DP model with those derived from the Estimation of Scale Parameter (ESP) tool. Based on our experiments, not only did the DP model produce acceptable results, but also it outperformed ESP tool in this study for extracting individual urban buildings.     

An intelligent multimedia information system for multimodal content extraction and querying

Multimedia Tools and Applications - This paper introduces an intelligent multimedia information system, which exploits machine learning and database technologies. The system extracts semantic...     

Modeling and Analyzing of Millimeter Wave Heterogeneous Cellular Networks by Poisson Hole Process

Wireless Personal Communications - In this paper, a novel Poisson hole process (PHP) modeling of wireless networks is proposed. Contrary to the prior PHP models with circular-shaped holes, we...     

Physico-chemical properties investigation of cisplatin loaded polybutyladipate (PBA) nanoparticles prepared by w/o/w

cis-Diamminedichloroplatinum(II) (cisplatin) is used against different kinds of cancers. Unfortunately, because of the severe side-effects like nephrotoxicity, ototoxicity, etc., they are administered in small doses at low concentrations. The purpose of this work is to improve injectional controlled release (ICR) of cisplatin that releases drug in the extended temporal periods. In order to access this aim, biodegradable polymeric nanoparticles containing cisplatin as anticancer drug of various ranges from 71 to 661 nm were prepared by a w/o/w double emulsion solvent evaporation technique. Influences of process parameters such as solvent removal technique, type and concentration of polymer, volume of oil phase, volume of external aqueous phase, concentration of stabilizer, drug concentration in the internal and external aqueous phases and power of sonication on morphology, characteristics of the nanoparticles and release profile were investigated. Morphology of the nanoparticles was studied by transmission electron microscopy (TEM) and scanning electron microscopy (SEM) and the images indicated that spherical shape of the nanoparticles can be tailored to rod-like shape by changing the reaction parameters. Size of the nanoparticles decreased as polymer concentration decreases. Volume of oil phase, power of sonication and drug concentration in the internal water phase affected the size of nanoparticles. Drug release profiles indicate that polymer concentration in the oil phase and stabilizer concentration in the external water phase have critical role in the drug release process from the nanoparticles. The in-vitro release of the encapsulated drug was observed by using the diffusion models of release from a sphere carrier and the release pattern was shown to be a complex process.