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Sexing is a difficult task for most birds (especially ornamental birds) involving expensive, state-of-the-art equipment and experiments. An intelligent fowl sexing system was developed based on data mining methods to distinguish hen from cock hatchlings. The vocalization of one-day-old hatchlings was captured by a microphone and a sound card. To obtain more accurate information from the recordings, time-domain sound signals were converted into the frequency domain and the time-frequency domain using Fourier transform and discrete wavelet transform, respectively. During data-mining from signals of these three domains, 25 statistical features were extracted. The Improved Distance Evaluation (IDE) method was used to select the best features and also to reduce the classifier's input dimensions. Fowls’ sound signals were classified by Support Vector Machine (SVM) with a Gaussian Radial Basis Function (GRBF). This classifier identified and classified cocks and hens based on the selected features from time, frequency and time-frequency domains. The highest accuracy of the SVM at time, frequency and time-frequency domains was 68.51, 70.37 and 90.74 percent, respectively. Results showed that the proposed system can successfully distinguish between Hen and Cock hatchlings. The results further suggest that signal processing and feature selection methods can maximize the classification accuracy.

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Measuring the vital signs of human body, such as oxygen saturation, blood pressure, and heart rate is the greatest and basic stage of the diagnosis of various diseases, especially cardiovascular diseases. Various methods have been developed to measure these signs. In general, these methods are divided into invasive and non-invasive categories. Due to less damages of non-invasive methods, more attention has been paid to them in recent decades. Using mobile phone is one of the most important non-invasive approaches because of being common and accessible among people. In this article, after studying Photoplethysmographic methods and expressing theories related to this method, imaging photoplethysmography (IPPG) is used to measure heart rate. Regarding two proposed algorithms based on furies transfer and peak detection, implementation of these algorithms was done, using a camera and LED of smart phone on 20 people. Next, the heart was calculated. Finally, a comparison was made between the two methods, the results of which show that peak detection method has less error than furies transfer method.

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Nowadays, by converting the cheap and commercial low-valued fish into value-added products such as fish sausages, as well as the application of novel ohmic heating method to cook more uniform, faster compared to other thermal severe methods and with minimal processing can play an important role in producing a safe and nutritious product. Therefore, the purpose of this study is to investigate some microbial and chemical characteristics of (Saurida tumbil) greater lizardfish sausage heated by emerging ohmic heating method and formulation optimization was performed by response surface methodology -central composite design (RSM-CCD) by considering KCl (0.7- 2.3 %), Soy Oil ( 4-14 %) and Isolated Soy Protein (0.2-1.8%). Optimization of 20 fish sausage formulation produced by ohmic heating was done by response surface methodology using Design Expert software version 11 and the relationship between the independent variables and the five responses was investigated. KCl has been shown an inhibitory effect on samples total plate count level. The interaction effect of soybean oil and soy protein isolate had a significant effect on pH changes. Increasing soybean oil percentage caused a little increase and subsequently reduction of pH and increasing soy protein isolate led to a significant decrease in pH. Furthermore, higher amount of KCl and soy protein isolate reduced the amount of cooking loss. In addition increase of soy bean oil percentage caused reduction and increase of soy protein isolate lead to increase of water holding capacity. Based on the results of formulation optimization in fish sausages with formulations containing 2% potassium chloride, 6% soybean oil and 1.5% soy protein isolate can increase water holding capacity, the lowest microbial load and the lowest peroxide value, cooking loss and optimized pH.
 

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Additives analysis plays important role in food quality control and has a great impact on public health. Therefore, rapid detection of these compounds in food samples is important in food safety. In this study, reduced graphene oxide /Fe₃O₄ nanocomposite (rG-Fe₃O₄-NC) was synthesized in the presence of sour lemon peel extract as a reducer and stabilizer agent in aqueous solution. For the first time multivariate optimization based on rotatable central composite design (RCCD) coupled with response surface methodology (RSM) was used to optimize effective experimental variables for fabrication of electrode. An experimental design has been used to examine and optimize the impacts of diverse experimental parameters like the pH and concentration of the nanocomposite in rG-Fe₃O₄-NC. The optimal conditions were pH: 6 and the concentration of the nanocomposite: 8%. The synthesized nanocomposites were characterized by TEM and XRD techniques. The rGO modified carbon paste electrode (rG-Fe₃O₄-NC/CPE) was used as a highly sensitive electrochemical sensor for the detection of vanillin. Interference of vitamin B₂, methionine, valine, glycine and KBR, KCl and glucose were checked in the presence of 25 µM vanillin at surface of rG-Fe₃O₄-NC/CPE with acceptable error 5%. Results confirmed that 500-folde of above compounds have not any important interference in monitoring process of 25 µM vanillin. The vanillin sensor showed linear range between 01 nM – 250 μM and a low detection limit of 0.3 nM. Finally, the rG-Fe₃O₄-NC/CPE was successfully used for determining vanillin in food samples. Therefore, this sensor can be used in food industry to the online determination of vanillin in flavored milks and ice cream.

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The use of nanotechnology in the food industry provides facilities such as encapsulation, targeted transfer of plant compounds and extracts without unfavourable sensitive effects. In this study, the essential oil (EO) of Santalum album (Santalum album linn.) was used to prepare a nanoemulsion. The nanoemulsion characteristics were evaluated and the data was optimized. To conduct the research, Design-Expert 12, statistical method of response surface, Central composite design with variables such as ultrasound frequency (25-31 kHz), ultrasound duration (10-20 sec.), and Santalum album EO (1%-10%) were used. After extraction of EO and identification of its effective compounds; percentage of antioxidant activity, viscosity, color indexes and the particle size of nanoemulsions tests were done. After optimization, stability test was performed on the optimized sample. The optimization results showed that with 5.5% Santalum album EO, ultrasound frequency of 28 KHZ, ultrasound duration of 15 seconds a nanoemulsion having optimum characteristics can be produced. After repeating the experiments for the obtained point, resulted in production of a nanoemulstion having particle size of 230 nm, the viscosity of 3.10 mPa.s, the brightness index of 78, the whiteness index of 58, and the antioxidant activity of 70%. It is believed these nanoemulsions have the potential to be used in the cosmetics, pharmaceutical and food industries.
 

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Grain design is the most important part of a solid rocket motor. The aim of this study is finocyl grain design based on predetermined objective function with respect to ballistic curves in order to satisfy various thrust performance requirements through an innovative design approach using a genetic algorithm optimization method. The classical sampling method has been used for design space-filling. The level set method has been used for simulating the evolution of the burning surface in the propellant grain. An algorithm has been developed beside the level set code that prepares the initial grain configuration using Pro/Engineer software to export generated models to level set code. The lumped method has been used to perform internal ballistic analysis. Two meta-models are used to surrogate the level set method in the optimization design loop. The first method is based on adaptive basis function construction and the second method is based on the artificial neural network. In order to validate the proposed algorithm, a grain finosyl sample has been investigated. The results show that both grain design method reduced the design time significantly and this algorithm can be used in designing of any grain configuration. In addition, data have more accuracy in grain design based on the artificial neural network, so this method is the more effective and practical method to grain burn-back training.

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Drop vortex is utilized to convey sewage across elevation change in steep catchments. This structure is generally used when the elevation difference is more than 5 m. Since the air and water flow are extensively combined in these structures and the sewage flow might contain detergent and foam producing materials, foam could produce in some parts of drop vortex. This phenomenon could affect vortex airflow and reduce drop vortex hydraulic performance. In this investigation, the effects of Foam Producing Flow (FPF) on vortex air discharge were studied by a scaled model and statistical Design of Experiment (DoE) methodology. Effects of Concentration Number, detergent type, and Froude Number on the dependent variable, air discharge to water discharge ratio, were studied by 33 full-factorial design and 63 runs. Analysis of the results revealed that all design factors had meaningful effects on vortex air discharge and it decreases by the increase of Concentration and Froude Number. Moreover, it was illuminated that foam formation could boost air discharge by 82% and in some conditions could reduce it more than 64%.

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The RCC construction method is one of the alternative methods in constructing concrete and earth dams. RCC is a kind of concrete which is pressed with roller, and after being compacted with roller, it is changed to a concrete like normal concrete .Primarily, using RCC in dam construction was developed to obtain the concrete structural properties and a construction method similar to earth dams. In RCC mix design, compressibility, non-segregation, maintaining the consistency of the fresh concrete, limiting the permeability, and achieving the proper bonding among the layers is required for efficiency .A qualitatively and quantitatively wide range of materials are used for constructing RCC mixtures in different dam projects. Therefore،Primarily the RCC aimed to obtain the conventional concrete properties and the construction procedure similar to earth dams. The quality and accessibility to materials to produce RCC should satisfy the structural and durability requirements. Therefore, the proper ratio of roller compacted concrete Mixture is an important step in achieving an economical and durable concrete.  This study aims to investigate the effects of various factors on the dam RCC Mixture Design (a case study of Javeh dam in the West of Iran), which optimum Mixture Design was developed as a laboratory research while observing all technical requirements and finally it was conducted as a test pad application. Javeh Reservoir Dam is located in a distance of 40 km southwest of Sanandaj, Kurdistan and 6 km from the downstream of Gaveh Roud and Qeshlaq River intersection. The dam is made of RCC. The properties of RCC in fresh and hardened conditions are of particular importance. Technical and economic advantages of RCC dams depend on the suitability of the mix design. Therefore, by an appropriate mix design, we can investigate the effect of RCC composite materials on the strength properties of RCC in terms of compressive strength, efficiency and non-separation characteristics of aggregates and their ratios in an optimal mix design. RCC must have sufficient efficiency to achieve the desired density according to the method and facilities. The efficiency of the new mix of RCC is entirely influenced by the amount of paste in the RCC mix. The paste contains the materials finer than #200 sieve including cement, pozzolan, water, filler of the aggregates and air bubbles. From the results, the total cementitious materials used in the optimum laboratory Mixture Design is 125 kg/m3. In addition, the ratio of Paste to mortar was about 5% higher than the minimum recommended in the RCC instruction given in the manual of the US Army Corps of Engineers. The compressive strength of roller concrete is affected by factors such as the amount of aggregates, the quality of fine grains, the quality of cement materials, grade density and content of mixed moisture. Considering that artificial neural networks are among the modeling methods that have shown great power to adapt to engineering problems, the models for predicting the compressive strength of this type of 180-day concrete is discussed based on the actual results from laboratory Mixture Design by neural networks modeling. The values of correlation coefficients in each of the models made in this study were close to the value of 1, which indicates the appropriate accuracy of the models.
 

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Iranian famous drinking yoghurt type, named Doogh, is a fermented dairy beverage and constituts an important part of daily beverage consumption in Iran. Doogh is commonly produced from mixing of yoghurt, drinking water, salt, and essence of aromatic vegetables such as thyme, mint, and oregano. In the present work, the effects of Quince seed mucilage [Qm: 0-0.1% (w/w)], Guar gum [Gg: 0-0.2% (w/w)] and storage time (1-21 days) on the physicochemical (pH, acidity and viscosity) and sensory properties of Doogh were studied. The Doogh was stored at 4°C for 21 days to be evaluated. Quince seed mucilage and guar gum were added to Doogh based on a Central Composite Design (CCD). The Response Surface Method (RSM) was applied to find out the optimum conditions and interaction between different factors. Three factors including Doogh storage time and added percentages of Qm and Gg were investigated. The results showed that the optimum condition of factors was different based on response. Based on viscosity of the Doogh, the first day of Doogh production and 0.1% (w/w) of Qm and 0.2% (w/w) of Gg were the best condition.

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According to the vital role that bridges play in transportation system and also communications of a society, monitoring their structural safety and keeping theme in service is crucial. Numerous methods have been proposed for detecting probable damages in bridges. Unfortunately most of them are based on comparison between the response of bridge in an intact and damaged state. Therefore intact state response must be known. However, not always it’s true in practice. So proposing a method which can determine and localize damages without prior knowledge of intact state is necessary. Such a method which was proposed by Sun et al. is studied carefully. Through the aforementioned method, the dynamic displacement response of a simply supported beam was decomposed into a dynamic component and a quasi-static component. Using Maxwell-Betti law of reciprocal deflection, the quasi-static component was attributed to the static deflection of the beam. Later damage which is defined by loss of stiffness, could be localized based on the abrupt changes in the static deflection curvature as it is related to bending moment and flexural stiffness of a beam. It is found out that the decomposition approach proposed by Sun et al. is restricted to fact that only one mode of oscillation must be dominant and also the natural frequency of motion must be determined through experimental measuring. Another limitation is that the abrupt changes in the curvature diagram cannot be related to damage essentially as curvature is also affected by the bending moment. In this study two modifications were proposed to get more accurate results in localizing the imposed damages. The first modification is the use of EMD method in order to decompose the displacement response into its intrinsic mode functions. Hence the aforementioned method could be used in real bridge displacement responses as higher modes corporations can also be determined and extracted through EMD process and finally the quasi-static component is determined as the residue of EMD algorithm. Also the ambient noise may be decomposed from the original signal, improving the method to work in real situations. The second modification is creating an imaginary constant moment length in the beam by the use of super position principle. So sudden increase in the curvature diagram is essentially a damage. Different scenarios of damage were studied and both methods have been used to detect damage in each scenario. Results show a great improvement in detection and localization of damage using the improved algorithm rather than the original proposed method. Eventually a five span real bridge model was taken into study. The improved damaged detection method could clearly determine the longitudinal position of the damage.

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