Automatic fire detection based on soft computing techniques: review from 2000 to 2010

Automatic fire detection system is a system that is capable of assessing environmental factors and their effects on the environment as well as predicting the occurrence of fire in the early stages and even before the outbreak. There are two perspectives in fire detection: fire detection in forests or jungles and fire detection in occupied or residential areas. Automatic fire detection has attracted increased attention due to its importance in decreasing fire damage. There are many studies that have considered appropriate techniques for early fire detection. In recent years researches have been studying technical developments in this field aimed at exploiting wireless communications networks, detection systems and fire prediction systems design. In this paper the automatic fire detection researches using intelligent techniques from 2000 to 2010 is reviewed. We could classify researches to four categories: fire detectors, reduce false alarms systems, fire data analysis and fire predictors. We also classify the intelligent techniques outlined in the researches for each category.     

A PSO-based model to increase the accuracy of software development effort estimation

Development effort is one of the most important metrics that must be estimated in order to design the plan of a project. The uncertainty and complexity of software projects make the process of effort estimation difficult and ambiguous. Analogy-based estimation (ABE) is the most common method in this area because it is quite straightforward and practical, relying on comparison between new projects and completed projects to estimate the development effort. Despite many advantages, ABE is unable to produce accurate estimates when the importance level of project features is not the same or the relationship among features is difficult to determine. In such situations, efficient feature weighting can be a solution to improve the performance of ABE. This paper proposes a hybrid estimation model based on a combination of a particle swarm optimization (PSO) algorithm and ABE to increase the accuracy of software development effort estimation. This combination leads to accurate identification of projects that are similar, based on optimizing the performance of the similarity function in ABE. A framework is presented in which the appropriate weights are allocated to project features so that the most accurate estimates are achieved. The suggested model is flexible enough to be used in different datasets including categorical and non-categorical project features. Three real data sets are employed to evaluate the proposed model, and the results are compared with other estimation models. The promising results show that a combination of PSO and ABE could significantly improve the performance of existing estimation models.     

Removal of Acid Orange 7 and Remazol Black 5 reactive dyes from aqueous solutions using a novel biosorbent

This study utilizes canola stalks (CS), an agro-residue, as a biosorbent to remove two different dyes, namely Acid Orange 7 (AO7) and Remozol Black 5 (RB5) from aqueous solutions. The effects of operational parameters on the efficiency of dye removal including pH, adsorbent mass, initial dye concentration and contact time have been investigated. For both tested dyes, the maximum absorption capacity was reached at initial pH 2.5 and 120 min contact time. The results showed that the absorption of both dyes depended on the pH of milieu, temperature, dye and CS concentrations. Freundlich and Langmuir models were used to analyze the obtained experimental data. The isotherms are found to be linear over the entire concentration range for both dyes. The highest value of linear correlation coefficients for AO7 (0.9926) and RB5 (0.9882) showed that the Langmuir is the best model to fit the experimental data. Kinetic study of absorption was done applying the pseudo first-order and the pseudo second-order equations. Absorption of both dyes could be well predicted by the pseudo second-order equation. The obtained results are very promising since: (i) high levels of dye removal (> 90%) were achieved with low contact times biosorbent/dye (less than 20 min contact); and (ii) the whole CS can be successfully used as biosorbent of AO7 and RB5 dyes in aqueous solution without needing any chemical modifications.     

Analysis and Assessment of Hydrochemical Characteristics of Maragheh-Bonab Plain Aquifer,Northwest of Iran

The present study aims at assessing the hydrochemistry of the groundwater system of the Maragheh-Bonab Plain located in the East Azarbaijan Province, northwest of Iran. The groundwater is used mainly for drinking, agriculture and industry. The study also discusses the issue of the industrial untreated wastewater discharge to the Plain aquifer that is a high Ca-Cl water type with TDS value of about 150 g/L. The hydrogeochemical study is conducted by collecting and analyzing the groundwater samples from July and September of 2013. The studied system contains three major groundwater types, namely Ca–Mg–HCO₃, Na–Cl, and non-dominant water, based on the analysis of the major ions. The main processes contributing to chemical compositions in the groundwater are the dissolution along the flow path, dedolomitisation, ion exchange reactions, and the mixing with wastewater. According to the computed water quality index (WQI) ranging from 25.45 to 194.35, the groundwater in the plain can be categorized into “excellent water”, “good water”, and “poor water”. There is a resemblance between the spatial distribution of the WQI and hydrochemical water types in the Piper diagram. The “excellent” quality water broadly coincides with the Ca-Mg-HCO₃ water type. The “poor” water matches with the Na–Cl water type, and the “good” quality water coincides with blended water. The results indicate that this aquifer suffers from intense human activities which are forcing the aquifer into a critical condition.     

Measuring effect of the blooming of chemical curatives on the rate of cyclic fatigue crack growth in natural rubber filled with a silanized silica nanofiller

Two rubber compounds with different amounts of chemical curatives were prepared by mixing natural rubber with a high loading of a sulfur‐bearing silanized precipitated amorphous white silica nanofiller. The chemical bonding between the filler and rubber was optimized via the tetrasulfane groups of the silane by adding a sulfenamide accelerator and zinc oxide. The rubber compounds were cured and stored at ambient temperature for 65 days before they were tested. One compound showed extensive blooming as a function of storage time. Thin tensile strips of the rubber vulcanizates containing an edge crack were repeatedly stressed at constant strain amplitude and test frequency at ambient temperature and crack length c was measured as a function of the number of cycles n. The cut growth per cycle, dc/dn, was calculated and plotted against the tearing energy, T. The blooming of the chemical curatives increased dc/dn by up to an order of magnitude at a constant T. This was due to the reagglomeration of the chemical curatives in the rubber and also within a thin layer approximately 15 to 20 μm in size beneath the rubber surface. Under repeated stressing, cracks grew through the relatively weak agglomerated areas in the rubber and this caused the rate of crack growth to increase at a constant T. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Modeling and Optimization of Microwave Osmotic Dehydration of Apple Cylinders Under Continuous-Flow Spray Mode Processing Conditions

The objective of this study was to model and optimize the mass transfer behavior during microwave osmotic dehydration of apple cylinders under continuous-flow spray mode processing conditions. Data needed for the model development and optimization were obtained using a central composite rotatable experimental design involving sucrose concentration (33.3–66.8°B), temperature (33.3–66.8 °C), flow rate (2,120–3,480 ml/min), and contact times (5–55 min); and the response variables were moisture loss, solids gain, and weight loss. Mass transfer kinetics was evaluated based on the empirical Azuara model and the conventional diffusion model. Diffusivities of both moisture loss (D _m) and solids gain (D _s) obtained from the diffusion model were related to sucrose concentration, temperature, and flow rate. Optimization was evaluated using a desirability function model which could be used with several imposed constraints. The optimum conditions obtained depended on the imposed constraints. A set of constraints involving maximizing moisture loss and weight reduction while keeping the solids gain below 3.5% gave the following optimal conditions: a 30-min osmotic treatment at 65°B, 60 °C, and 2,800 ml/min flow rate yielding a moisture loss of 40.9%, weight reduction of 37.7%, with a solids gain of 3.32%.     

Synthesis and Characterization of Polycarbonate/TiO2 Ultrafiltration Membranes: Critical Flux Determination

A novel polycarbonate (PC) membrane was modified with titanium dioxide via nonsolvent-induced phase separation method to improve its hydrophilicity and antifouling properties in a submerged membrane system for the removal of humic acid (HA) both with and without polyaluminum chloride (PAC) coagulant. The effect of TiO₂ additive on the morphology and performance of the nanocomposite membranes was studied by atomic force microscopy, field emission scanning electron microscopy, energy dispersive X-ray, mechanical properties, water contact angle, porosity, pure water flux, rejection tests, and antifouling parameters. The obtained results revealed that a higher critical flux was achieved by the PC/TiO₂ nanocomposite membrane. The flux recovery ratio of the neat PC membrane increased with the addition of TiO₂ nanoparticles and without PAC coagulant. HA removal for the PC nanocomposite membrane was higher than that of the neat PC membrane with and without PAC coagulant.     

A visible-light-active BiFeO<Subscript>3</Subscript>/ZnS nanocomposite for photocatalytic conversion of greenhouse gases

Given the changes in environmental conditions in the world, photocatalytic conversion of greenhouse gases is of great interest today. Our aim was to increase the photocatalytic efficiency of BiFeO₃/ZnS (p-n heterojunction photocatalyst) by varying the molar ratio of ZnS to perovskite structure of BiFeO₃ using hydrothermal synthesis. The results of X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), FT-IR spectroscopy showed the small crystal size and suitable distribution of ZnS particles on the BiFeO₃ structure. The results of UV-visible, and photoluminescence (PL) spectroscopy analyses showed the good behavior of p-n heterostructure in absorption of visible light and lowering electron-hole recombination. The best visible light photocatalytic efficiency of CO₂ reduction, 24.8%, was obtained by an equimolar ratio of BiFeO₃/ZnS.     

Optimizing the setup of a flatbed color scanner for color measurement using full factorial design

The application of flatbed color scanners for the measurement of color in various industries, especially textile industry, has received a great deal of attention. The initial setup of a scanner and the investigation of factors with a significant effect on scanner outputs are necessary to measure a reliable color using the scanner. In the present study, the setup of a flatbed color scanner was optimized using a full factorial design technique. Three factors, including the scanning position on the glass surface of the scanner (A), cutting size of an image in pixels (B), and bit depth (C), at different levels as input factors, and signal‐to‐noise ratio and variance of the scanned image as the responses were considered for the evaluation of the reliability of the scanner color measurement. The results of analyzing the factorial design indicate that each of the three factors played a significant role in the scanner setup for the color measurement so that factor A demonstrated the most significant impact on the responses.     

Optimisation study of gum extraction from Basil seeds (Ocimum basilicum L.)

Basil seed ( Ocimum basilicum L.) is cultivated in large quantities in different regions of Iran. This seed has reasonable amounts of gum with good functional properties which is comparable with commercial food hydrocolloids. A central composite rotatable design was applied to evaluate the effects of temperature, pH and water/seed ratio on the yield, apparent viscosity and protein content of water-extracted Basil seed gum. All of the variables significantly ( P  < 0.05) affected the extraction yield, whereas the effect of water/seed ratio on apparent viscosity and the effects of pH and water/seed ratio on protein content were not significant ( P  > 0.05). Numerical optimisation determined the optimum extraction conditions based on the highest yield and viscosity and the lowest protein content as being temperature 68.71 °C, pH 8.09 and water/seed ratio 65.98:1. Power law model well described non-Newtonian pseudoplastic behaviour of BSG. Flow behaviour index ( n ) and consistency index ( K ) of 1% crude and pure BSG samples were 0.306, 0.283 and 17.46, 20.22 Pa s ⁿ , respectively.