Ahmad Banakar

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Papers by Ahmad Banakar

Diagnosing the spores of tomato fungal diseases using microscopic image processing and machine learning

Multimedia tools and applications, Jan 25, 2024

Comparison of the cumulative exergy demand of phase change and reverse osmosis desalination plants with environmental impacts approach

Desalination

Ohmic Heating of Aloe vera Gel: Electrical Conductivity and Energy Efficiency

Iranian Journal of Chemistry & Chemical Engineering-international English Edition, Oct 1, 2018

Ohmic heating is defined as a process which alternating electric current is passed through food w... more Ohmic heating is defined as a process which alternating electric current is passed through food with the primary purpose of heating it due to the electrical resistance and can be specially applied as an alternative heating method. In this research, Aloe vera gel concentrates having 0.5-2% soluble solids were ohmically heated up to 60°C by using four different voltage gradients (30-60 V/cm). The dependence of electrical conductivity on temperature, voltage gradient, and concentration were obtained. Results indicated that there was a linear relationship between temperature and electrical conductivity. The range of the electrical conductivity was 0.45 to1.20 S/m, which was dependent on the concentration and voltage gradient, although the effect of concentration was very higher than voltage gradient. The ohmic heating System Performance Coefficients (SPCs) were calculated by using the energies given to the system and taken by the Aloe vera gel samples and were in the range of 0.67-0.89 and the highest SPC (0.89) was observed at 0.5 % and 30 V/cm.

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Development and performance evaluation of a photovoltaic-powered induction cooker (PV-IC): An approach for promoting clean production in rural areas

Cleaner engineering and technology, Feb 1, 2022

A feature selection method using slime mould optimization algorithm in order to diagnose plant leaf diseases

Design, manufacturing and evaluation of a solar heating system with Fresnel concentrator for greenhouse

مجله علوم و فنون کشتهای گلخانهای, Jun 1, 2016

Energy consumption is very high in greenhouses mainly due to off-season production. The main sour... more Energy consumption is very high in greenhouses mainly due to off-season production. The main source of its energy supply is fossil fuels. Due to the disadvantages of fossil fuels consumption and preventive laws in the incoming years, study on reducing consumption and replacing a part of them with renewable energy is essential. In this research, a solar heating system, equipped with a concentrator and Fresnel lens, adjustable to all regions in Iran, was designed and manufactured in Faculty of Agriculture, Tarbiat Modares University. Thermal heating requirement of a cucumber greenhouse was calculated and then solar heating system and thermal storage system were designed and manufactured. For more energy saving, besides insulation of the reservoir tank with an elastomeric layer, cupper tubes and paraffin was used. Then, behavior of the system was evaluated under three thermal conditions of 35, 50 and 65°C. The results of variations of water temperature in the tank showed that mean descending rate of temperature, with a higher initial temperature, has been faster in the tank as compared to the tank with lower initial temperature. But, with proper volume and insulation and use of phase-change materials, particularly in the melting point range of paraffin, temperature in the tank remains constant and the cooling process is slower. Therefore solar heating system and thermal tank with suitable volume and insulation can be used for heating the greenhouses.

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Evaluation of a pre-heating system for solar desalination system with linear Fresnel lens

Journal of Renewable and Sustainable Energy, Sep 1, 2017

Freshwater supply is currently exacerbated in most parts of the world. Freshwater production tech... more Freshwater supply is currently exacerbated in most parts of the world. Freshwater production technologies require spending considerable costs and energy. In this study, a solar collector with a Fresnel lens was developed and evaluated as the collector unit. This collector was designed with a cavity collector and multi-tube absorber arrangement for using preheated water required by water stills. Experiments were conducted from mid-May to mid-June, 2014. Thermal evaluations were conducted at three flow rates (100, 200, and 400 ml/min), resulting in the maximum thermal efficiencies of 75.7%, 81.1%, and 88.2% and minimum thermal efficiencies of 66.5%, 70.4%, and 73.7%, respectively. The maximum output temperatures for the studied flow rates (100, 200, and 400 ml/min) were 96, 77, and 63 C, respectively. Maximum and minimum heats absorbed at three flow rates (100, 200, and 400 ml/min) were 636.

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Local recurrent sigmoidal–wavelet neurons in feed-forward neural network for forecasting of dynamic systems: Theory

Applied Soft Computing, Mar 1, 2012

In this paper different structure of the neurons in the hidden layer of a feed-forward network, f... more In this paper different structure of the neurons in the hidden layer of a feed-forward network, for forecasting of the dynamic systems, are proposed. Each neuron in the network is a combination of the sigmoidal activation function (SAF) and wavelet activation function (WAF). The output of the hidden neuron is the product of the output from these two activation functions. A delay element is used to feedback the output of the sigmoidal and the wavelet activation function to each other. This arrangement leads to proposed five possible configurations of recurrent neurons. Besides proposing these neuron models, the presented paper tries to compare the performance of wavelet function with sigmoid function. To guarantee the stability and the convergence of the learning process, upper bound for the learning rates has been investigated using the Lyapunov stability theorem. A two-phase adaptive learning rate ensures this upper bound. Universal approximation property of the feed-forward network with the proposed neurons has also been investigated. Finally, the applicability and comparison of the proposed recurrent networks has been weathered on two benchmark problem catering different types of dynamical systems.

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Design, development and performance evaluation of an automatic control system for rice whitening machine based on computer vision and fuzzy logic

Computers and Electronics in Agriculture, Jun 1, 2016

An automatic control system was developed for controlling rice whitening machine.The system was d... more An automatic control system was developed for controlling rice whitening machine.The system was designed based on machine vision and fuzzy logic techniques.The developed system had a high accuracy in controlling of the whitening machine.Performance speed of the system was satisfactorily higher than human operator.Decisions made by the system resulted in a good improvement in the quality of product. The objective of this study was developing an intelligent automatic control system (ACS) based on machine vision and fuzzy logic techniques to control the performance of rice whitening machines. The developed ACS consisted of two main parts, namely hardware (including sampling unit, kernel singulation unit, image capturing unit, processor (computer), discharge pressure control unit and data acquisition unit), and software (including image processing, fuzzy inference and central control units). Two important qualitative indices, degree of milling and percentage of broken kernels, were considered as input variables and the level of pressure on the discharge section of the whitening machine was selected as the output variable in the fuzzy inference unit. Results of the evaluations indicated that the developed ACS had 89.2% accuracy in determining the desired working conditions for the whitening machine. The total time of each monitoring round was, on the average, equal to 14.73s, of which 6.4s was devoted to kernel sampling and transporting the samples into the imaging chamber, 7.33s for taking three images from the kernels, processing the captured images and executing the fuzzy inference process, and the remaining 1.5s for making the adjustments in the level of pressure in the mechanism. Based on this information and in contrast to the corresponding time spent by the human operator to perform a similar process, it was revealed that the performance speed of the ACS was, on average, 31.3% higher than that of the human operator. Evaluation of the samples obtained from the discharge section of the rice whitening machine at different stages of the control process showed that the decisions made by the developed ACS during the control process resulted in a satisfactory improvement in the quality of the output product.

An Intelligent Procedure for the Detection and Classification of Chickens Infected by Clostridium Perfringens Based on their Vocalization

Brazilian Journal of Poultry Science, Dec 1, 2015

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Artificial wavelet neural network and its application in neuro-fuzzy models

Applied Soft Computing, Sep 1, 2008

In the proposed work, two types of artificial neural networks are proposed by using well-known ad... more In the proposed work, two types of artificial neural networks are proposed by using well-known advantages and valuable features of wavelets and sigmoidal activation functions. Two neurons are derived by adding and multiplying the outputs of the wavelet and the sigmoidal activation functions. These neurons in a feed-forward single hidden layer network result summation wavelet neural network (SWNN) and multiplication

A hybrid intelligent approach based on computer vision and fuzzy logic for quality measurement of milled rice

Measurement, Apr 1, 2015

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Comparison of environmental impact on various desalination technologies

Desalination, Feb 1, 2023

Remaining useful life (RUL) prediction of internal combustion engine timing belt based on vibration signals and artificial neural network

Neural Computing and Applications, Nov 20, 2020

Timing belt rupture, which can develop quickly and cause severe harm to various engine components... more Timing belt rupture, which can develop quickly and cause severe harm to various engine components, usually occurs unexpectedly and without prior warning signs. Due to the rapid occurrence of timing belt rupture, fault diagnosis strategies are not indeed efficient. In this paper, a vibration-based intelligent method has been proposed to predict the remaining useful life (RUL) of the timing belt using data mining techniques and multi-layer perceptron neural network (MLP-NN). To achieve this goal, two categories of experimental tests were designed and carried out on the timing belt, namely, fault thresholding (FT) and accelerated life (AL) tests. FT test was performed by comparing the defect-free belt vibration signals with those of a faulty belt to determine the failure threshold. This is while, in the AL test, the engine was continuously run with a defect-free timing belt until initiation of rupture or damage was detected. Four feature functions, regarded as timing belt health indicators, were applied to the collected vibration signals, namely, energy, impulse factor, root mean square, and FM4. The extracted features were then fed to the MLP-NN to predict the timing belt RUL by continuously comparing the feature values and the failure threshold. The results showed that the proposed method is able to predict the timing belt RUL with an accuracy of 90%. In addition, data predicted by the MLP-NN showed high correlation with the actual measured data, which emphasizes the robustness and precision of the proposed method for timing belt RUL prediction. Keywords Life prediction Á Neural networks (NN) Á Data mining Á Fault diagnosis and prognosis Á Timing belt Á Engine life test Á Validation tests Á Internal combustion (IC) engine

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Potential Applications of Computer Vision in Quality Inspection of Rice: A Review

Food Engineering Reviews, Jan 7, 2015

Among the cereals, rice is the major foodstuff for a large part of the world's population. Due to... more Among the cereals, rice is the major foodstuff for a large part of the world's population. Due to its tremendous importance in the global market, its qualitative economic aspects during processing have always been attended by producers. As the most delicate of the cereals, rice needs the utmost care during post-harvest handling and processing, because in most cases, it is consumed as whole kernel. The growing demand for production of rice with high-quality and safety standards has increased the need for its accurate, fast and objective quality monitoring. Computer vision techniques, as novel technologies, can provide an automated, nondestructive and cost-effective way to achieve these requirements. In recent years, various studies have been conducted to evaluate rice qualitative features based on computer vision techniques. This paper presents the theoretical and technical principles of computer vision for nondestructive quality assessment of rice combined with a review of the recent achievements and applications for quality inspection and monitoring of the product.

format_quoteHead rice yield (HRY) is crucial, representing the weight percentage of intact kernels and determined by their principal dimensions during milling processes.format_quote

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Reducing Energy Consumption in a Poultry Farm by Designing and Optimizing the Solar Heating/Photovoltaic System

Sustainability, Mar 31, 2023

A solar heating system is designed to reduce energy consumption in a poultry farm. According to t... more A solar heating system is designed to reduce energy consumption in a poultry farm. According to the physics and conditions of the indoor environment of the poultry building and the effect of the poultry weather conditions, the amount of 1.37 × 10 8 kJ/h during the year energy is required for heating. Then, by using double-glazed windows and insulation for the exterior walls of the building in the building architecture section, the amount of energy consumption is drastically reduced, and the required annual gas consumption is equal to 11,833 m 3 . The surface required for the collector is recommended to supply 50% of the energy from the sun with the rest from the hybrid system. The results showed that 26 m 2 of a solar collector with an optimal slope of 45 degrees, and a tank volume of 440 L and a pump discharge of 1700 kg/h are required to provide 100% of energy. To receive the maximum amount of solar energy (maximum solar fraction (SF)), a collector surface equal to 30 m 2 is required. However, when the economic point of view is considered, the collector surface equivalent to 26 m 2 is recommended. To establish a balance, that is, 50% of the energy from the auxiliary system and the rest from the solar system, between the use of solar energy and the use of the auxiliary system, a collector area of 16 m 2 is needed. Based on this, 60 photovoltaic modules, which are 10 cells in series in 6 parallel circuits, is the most optimal mode.

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A New Artificial Neural Network and its Application in Wavelet Neural Network and Wavelet Neuro-Fuzzy Case study: Time Series Prediction

The approximation of general continuous functions by nonlinear network is very useful for system ... more The approximation of general continuous functions by nonlinear network is very useful for system modeling and identification. Therefore, different type of networks and their combinations have developed. In present paper a wavelet neural network is used and a linear regression of inputs is used as a wavelet weight, also this model is applied in wavelet neuro-fuzzy model

Input Selection for TSK Fuzzy Model based on Modified Mountain Clustering

System identification plays a principal role in input-output data analysis, such that a better re... more System identification plays a principal role in input-output data analysis, such that a better result can be obtained from better model. System identification includes two parts: structure identification and parameter identification. In structure identification, input variables and input-output relations are found. This paper tries to find best input candidate for a TSK fuzzy identification model based on modified mountain clustering

An Investigation of Energy Consumption, Solar Fraction and Hybrid Photovoltaic–Thermal Solar Dryer Parameters in Drying of Chamomile Flower

International Journal of Food Engineering, Dec 1, 2014

In this research, drying of a medicinal plant (chamomile) in a hybrid photovoltaic-thermal solar ... more In this research, drying of a medicinal plant (chamomile) in a hybrid photovoltaic-thermal solar dryer with and without heat pump was investigated. The experiments were performed at three air speeds (0.5, 1, and 1.5 m/s), three levels of air temperature (40, 50, and 60°C), with and without using a heat pump. Results of analysis indicated that adding a heat pump to the photovoltaic solar dryer decreases drying time, energy consumption, and required specific energy. Solar energy fraction increased with decreasing air temperature and velocity. Analysis of the dryer-related parameters showed that the maximum and minimum thermal efficiencies were 33.8 and 16.4%, respectively, both in the no-heat-pump mode while with the heat pump, its maximum and minimum values were 38.4 and 19.7%, respectively. Moreover, the highest and lowest electrical efficiencies for the no-heat-pump mode were 13.4 and 9.1%, respectively; while using the heat pump, its maximum and minimum values were 14.1 and 10.4%, respectively. Results of analyzing the dryer's coefficient of performance for drying chamomile showed that the highest and lowest coefficients of performance were 3.41 and 1.82, respectively. Eleven mathematical models were tested, and Page's model was selected as the best for describing the drying behavior of chamomile flower.

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Parameter identification of TSK neuro-fuzzy models

Fuzzy Sets and Systems, Sep 1, 2011

In the framework of the TSK neuro-fuzzy model a combination of the two well-known identification ... more In the framework of the TSK neuro-fuzzy model a combination of the two well-known identification methods are employed for parameter estimation of the neuro-fuzzy inference system, namely the series–parallel and the parallel configurations. The presented paper proposes two new possible configurations for identifying the parameters of the TSK neuro-fuzzy model using the combinations of these two existing configurations. One of

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