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A machine vision-intelligent modelling based technique for in-line bell pepper sorting

Information Processing in Agriculture 2023年第4期10卷 491-503页

作者： Khaled Mohi-Alden mahmoud omid mahmoud Soltani Firouz Amin Nasiri Department of Agricultural Machinery Engineering Faculty of Agricultural Engineering and TechnologyUniversity of TehranIran Department of Biosystems Engineering and Soil Science University of TennesseeKnoxvilleTN 37996USA

The uniformity of appearance attributes of bell peppers is significant for consumers and food *** automate the sorting process of bell peppers and improve the packaging quality of this crop by detecting and separating the not likable low-color bell peppers,developing an appropriate sorting system would be of high importance and *** to standards and export needs,the bell pepper should be graded based on maturity levels and size to five *** research has been aimed to develop a machine vision-based system equipped with an intelligent modelling approach for in-line sorting bell peppers into desirable and undesirable samples,with the ability to predict the maturity level and the size of the desirable bell *** perceptron(MLP)artificial neural networks(ANNs)as the nonlinear modelswere designed for that *** modelswere trained and evaluated through five-fold cross-validation *** optimum MLP classifier was compared with a linear discriminant analysis(LDA)*** results showed that the MLP outperforms the LDA *** processing time to classify each captured image was estimated as 0.2 s/sample,which is fast enough for in-line ***,the optimum MLP model was integrated with a machine vision-based sorting machine,and the developed system was evaluated in the in-line *** performance parameters,including accuracy,precision,sensitivity,and specificity,were 93.2%,86.4%,84%,and 95.7%,*** total sorting rate of the bell pepper was also measured as approximately 3000 samples/h.

关键词： Bell pepper Sorting Image processing Machine vision Multilayer perceptron Linear discriminant analysis

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Dielectric spectroscopy coupled with artificial neural network for classification and quantification of sesame oil adulteration

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Information Processing in Agriculture 2022年第2期9卷 233-242页

作者： mahmoud Soltani Firouz mahmoud omid Mehrdad Babaei Mahdi Rashvand Department of Agricultural Machinery Engineering Faculty of Agricultural Engineering and TechnologyUniversity of TehranKarajIran Machine Design and Mechatronics Department Institute of MechanicsIranian Research Organization for Science and TechnologyTehranIran

Adulteration using cheap vegetable oils into expensive oils such as sesame oil is a considerable challenge in the edible oil market. To discriminate pure and adulterated sesame oilwith sunflower and canola oils (commonly used as an adulterant to the high-price oils),dielectric spectroscopy was applied in the range of 40 kHz–20 MHz. The principal component analysis (PCA) plots were able to distinguish the pure sesame oil, while it was impossible to separate the adulterated oils based on the kind of adulteration. The correlationbased feature selection (CFS) method was used to select the more relevant dielectric datawithin the spectrum and to reduce the dimensionality of the input vector belongs to theartificial neural network (ANN). The ANN classifier with topology of 19-5-4 structureshowed a perfect accuracy of 100% in detecting the authentic and the adulterated sesameoil. The regression ANN with the topology of 15-5-1, 21-8-1 and 10-11-1 were the mostrobust models in quantifying the amount of adulteration in sesame oil generated by sun-flower oil, canola oil and sunflower + canola oils, with R2Test of 1, 1 and 0.999 9, *** proposed technique is a powerful and simple method to detect and quantify adulteration of sesame oil. The novelty of this research is capability of used system for authentication of adulterated sesame oil using low frequency. Furthermore, the developed systemhas a good capability for other types of sesame oil adulterations as well as to detect adulteration in other expensive edible oils.

关键词： Adulteration Artificial neural network Chemometrics Sesame oil Correlation-based feature selection Principal component analysis

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Fault diagnosis of tractor auxiliary gearbox using vibration analysis and random forest classifier

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Information Processing in Agriculture 2022年第1期9卷 60-67页

作者： Mohammad Hosseinpour-Zarnaq mahmoud omid Ebrahim Biabani-Aghdam Department of Agricultural Machinery Engineering Faculty of Agricultural Engineering and TechnologyUniversity of TehranKarajIran Biosystems Engineering Department Tarbiat Modares UniversityTehranIran

Accurate detection of mechanical components faults is an essential step for reduction of repair cost,human injury probability and loss of *** intelligent fault diagno-sis systems in tractor could prevent secondary damage,thereby avoiding heavy *** this study,fault diagnosis of tractor auxiliary gearbox is *** signals of healthy and faulty pinions gear under three different operational conditions(Rotational speeds of 600 RPM,1350 RPM and 2000 RPM)were collected,and discrete wave-let transform(DWT)was used as signal *** statistical features were calcu-lated from collected ***-based feature selection(CFS)method was used to find the best *** forest(RF)and multilayer perceptron(MLP)neural net-works were employed to classify the *** overall accuracy of RF classifier without using feature selection were 86.25%,at 600 *** corresponding values of RF trained with the optimal 6 features by using CFS was 92.5%.The best results obtained at 1350 RPM,since the detection accuracy was 95%.The results of this study demonstrated the effectiveness and feasibility of the proposed method for fault diagnosis of tractor auxiliary gearbox.

关键词： Gearbox Fault diagnosis Vibration analysis Discrete wavelet transform Feature selection Random forest

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Design,development and evaluation of an online grading system for peeled pistachios equipped with machine vision technology and support vector machine

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Information Processing in Agriculture 2017年第4期4卷 333-341页

作者： Hosein Nouri-Ahmadabadi mahmoud omid Seyed Saeid Mohtasebi mahmoud Soltani Firouz Department of Agricultural Machinery Engineering Faculty of Agricultural Engineering and TechnologyUniversity of TehranKarajIran

In this study,an intelligent system based on combined machine vision(MV)and Support Vector Machine(SVM)was developed for sorting of peeled pistachio kernels and *** system was composed of conveyor belt,lighting box,camera,processing unit and sorting unit.A color CCD camera was used to capture *** images were digitalized by a capture card and transferred to a personal computer for further ***,images were converted from RGB color space to HSV color *** segmentation of the acquired images,H-component in the HSV color space and Otsu thresholding method were applied.A feature vector containing 30 color features was extracted from the captured images.A feature selection method based on sensitivity analysis was carried out to select superior *** selected features were presented to SVM *** SVM models having a different kernel function were developed and *** SVM model having cubic polynomial kernel function and 38 support vectors achieved the best accuracy(99.17%)and then was selected to use in online decision-making unit of the *** launching the online system,it was found that limiting factors of the system capacity were related to the hardware parts of the system(conveyor belt and pneumatic valves used in the sorting unit).The limiting factors led to a distance of 8 mm between the *** overall accuracy and capacity of the sorter were obtained 94.33% and 22.74 kg/h,respectively.

关键词： Pistachio kernel Sorting Machine vision Sensitivity analysis Support vector machine

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Optimized design of a linear vibrating screen based on efficiency maximisation and mesh wear minimisation employing discrete element method

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Particuology 2024年第7期90卷 307-322页

作者： omid Afsari Kamyar Hashemnia School of Mechanical Engineering Shiraz UniversityMolla Sadra St.ShirazIran

This article investigates the combined effect and the order of influence of feed rate,inclination angle,vibration amplitude,frequency,and angle on the efficiency and mesh wear rate of a linear vibrating screen,as well as the average velocity,and mass of the accumulated *** discrete element modeling simulations were conducted using LIGGGHTS open-source code to analyze particles *** Taguchi method was employed to evaluate the combined effect of the ***,the simulation results were analyzed using analysis of *** optimal values of the parameters for maximising efficiency and minimising mesh wear were determined using grey relational *** results indicated that the most effective parameters on screening efficiency and average velocity of particles were the inclination angle,vibration angle,frequency,amplitude,and feed rate,*** most influential parameters on screen mesh wear rate were feed rate,inclination angle,vibration angle,frequency,and amplitude,respectively.

关键词： Discrete element modeling Granular material Taguchi method Vibrating screen Wear

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Development of an intelligent system based on ANFIS for predicting wheat grain yield on the basis of energy inputs

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Information Processing in Agriculture 2014年第1期1卷 14-22页

作者： Benyamin Khoshnevisan Shahin Rafiee mahmoud omid Hossein Mousazadeh Department of Agricultural Machinery Engineering Faculty of Agricultural Engineering and TechnologyUniversity of TehranKarajIran

Energy is regarded as one of the most important elements in agricultural *** the last decades energy consumption in agriculture has increased,so finding the relationship between energy consumption and crop yields in agricultural production can help to achieve sustainable *** this study several adaptive neuro-fuzzy inference system(ANFIS)models were evaluated to predict wheat grain yield on the basis of energy ***,artificial neural networks(ANNs)were developed and the obtained results were compared with ANFIS *** the best ANFIS structure gained in this study,R,RMSE and MAPE were calculated as 0.976,0.046 and 0.4,*** developed ANN was a multilayer perceptron(MLP)with eleven neurons in the input layer,two hidden layers with 32 and 10 neurons and one neuron(wheat grain yield)in the output *** the best ANN model,R,RMSE and MAPE were computed as 0.92,0.9 and 0.1,*** results illustrated that ANFIS model can predict the yield more precisely than ANN.

关键词： Wheat yield Energy consumption Prediction ANFIS ANN

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Tensile strength and failure behavior of rock-mortar interfaces: Direct and indirect measurements

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第1期16卷 41-55页

作者： Ghasem Shams Patrice Rivard omid Moradian Civil Engineering and Building Engineering Department Universitéde SherbrookeSherbrookeQuébecCanada Department of Earth Sciences Swiss Federal Institute of Technology(ETH)ZurichSwitzerland Department of Civil and Environmental Engineering Colorado School of MinesGoldenCOUSA

The tensile strength at the rock-concrete interface is one of the crucial factors controlling the failure mechanisms of structures,such as concrete gravity *** the critical importance of the failure mechanism and tensile strength of rock-concrete interfaces,understanding of these factors remains very *** study investigated the tensile strength and fracturing processes at rock-mortar interfaces subjected to direct and indirect tensile *** image correlation(DIC)and acoustic emission(AE)techniques were used to monitor the failure mechanisms of specimens subjected to direct tension and indirect loading(Brazilian tests).The results indicated that the direct tensile strength of the rock-mortar specimens was lower than their indirect tensile strength,with a direct/indirect tensile strength ratio of 65%.DIC strain field data and moment tensor inversions(MTI)of AE events indicated that a significant number of shear microcracks occurred in the specimens subjected to the Brazilian *** presence of these shear microcracks,which require more energy to break,resulted in a higher tensile strength during the Brazilian *** contrast,microcracks were predominantly tensile in specimens subjected to direct tension,leading to a lower tensile *** monitoring of the cracking processes in the rock-mortar interfaces revealed that they show AE precursors before failure under the Brazilian test,whereas they show a minimal number of AE events before failure under direct *** to different microcracking mechanisms,specimens tested under Brazilian tests showed lower roughness with flatter fracture surfaces than those tested under direct tension with jagged and rough fracture *** results of this study shed light on better understanding the micromechanics of damage in the rock-concrete interfaces for a safer design of engineering structures.

关键词： Rock-mortar Rock-concrete Moment tensor inversion(MTI) Acoustic emission(AE) Digital image correlation(DIC) Tensile strength Direct tensile test Brazilian test

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Bearing capacity of circular footings on multi-layered sand-waste tire shreds reinforced with geogrids

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第3期16卷 1085-1094页

作者： mahmoud Ghazavi Ehsan Khosroshahi Faculty of Civil Engineering K.N.Toosi University of TechnologyTehranIran

The presence of waste tires poses an environmental challenge as they occupy a significant amount of land and are expensive to dispose in ***,reusing waste tires can address this issue when waste tires are used in geotechnical *** determine the viability of this approach,laboratoryscale tests were conducted to investigate load-bearing capacity of circular footings on sand-tire shred(STS)mixtures with shredded waste tire contents of 5%e15%by weight and three different widths of *** investigation focused on analyzing the thickness of layers composed of STS mixtures,the soil cap,and the impact of geogrids on bearing *** results indicate that a specific mixture of sand and tire shreds provides the highest footing-bearing *** addition,the optimal shred content and size were found to be 10%by weight and 2 cm×10 cm,***,for a given tire shred width,a particular length provides the largest bearing *** results agree well with that of previous research conducted by the first author and his colleagues in direct shear and California bearing ratio(CBR)*** primary finding of this research is that the use of two-layered STS mixtures reinforced by geogrids significantly enhances the bearing capacity.

关键词： Geogrid Sand Waste tire shred Bearing capacity Waste tire shred optimization Tire shred aspect ratio

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Laboratory study of a hydronic concrete deck heated externally in a controlled sub-freezing environment

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Energy and Built Environment 2024年第1期5卷 9-23页

作者： Mark Hurley omid Habibzadeh-Bigdarvish Gang Lei Xinbao Yu Department of Civil Engineering University of Texas at ArlingtonTX 76019United States

Geothermal heating of bridge decks is a reliable and sustainable method for bridge de-icing that has been in-creasing in demand since conventional de-icing methods were proved to be environmentally *** research on geothermal heating of bridge decks relied on hydronic pipes embedded inside of bridge decks,which are confined to newly constructed *** existing bridges,a newly devised method for external heating has been recently tested under limited laboratory conditions to determine its overall *** study explores laboratory heating tests of a concrete slab with a thickness representing a typical concrete bridge *** slab was equipped with a simulated geothermal bridge de-icing system and tested inside a freezer subjected to sub-freezing controlled *** winter scenarios were applied to the system to determine its heat-ing performance and how feasible it will be for the system to be transferred to the field.A prediction equation was developed to estimate the total energy reserves required to permit de-icing,and statistical analysis was performed and validated with test *** slab surface heat flux was estimated to range from 27 W/m^(2) K to 73 W/m^(2) K from the heating *** externally-heated deck can be designed with the developed prediction equation for snow melting.

关键词： Thermal demands Bridge deck de-icing Attached hydronic loops Heated bridge deck Heat flux analysis

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Revealing connectivity in residential Architecture: An algorithmic approach to extracting adjacency matrices from floor plans

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Frontiers of Architectural Research 2024年第2期13卷 370-386页

作者： Mohammad Amin Moradi omid Mohammadrashidi Navid Niazkar Morteza Rahbar School of Architecture and Engineering University College of RouzbahanMazandaranIran School of Architecture Islamic Azad UniversitySafaDasht CampusTehranIran A.James Clark School of Engineering University of MarylandCollege ParkMDUSA School of Architecture and Environmental Design Iran University of Science and TechnologyTehranIran

In today's world, various approaches and parameters exist for designing a plan and determining its spatial, placement. Hence, various modes for identifying crucial locations can be explored when an architectural plan is designed in different dimensions. While designing all these modes takes considerable time, there are numerous potential applications for artificial intelligence (AI) in this domain. This study aims to compute and use an adjacency matrix to generate architectural residential plans. Additionally, it develops a plan generation algorithm in Rhinoceros software, utilizing the Grasshopper plugin to create a dataset of architectural plans. In the following step, the data was entered into a neural network to identify the architectural plan's type, furniture, icons, and use of spaces, which was achieved using YOLOv4, EfficientDet, YOLOv5, DetectoRS, and RetinaNet. The algorithm's execution, testing, and training were conducted using Darknet and PyTorch. The research dataset comprises 12,000 plans, with 70% employed in the training phase and 30% in the testing phase. The network was appropriately trained practically and precisely in relation to an average precision (AP) resulting of 91.50%. After detecting the types of space use, the main research algorithm has been designed and coded, which includes determining the adjacency matrix of architectural plan spaces in seven stages. All research processes were conducted in Python, including dataset preparation, network object detection, and adjacency matrix algorithm design. Finally, the adjacency matrix is given to the input of the proposed plan generator network, which consequently, based on the resulting adjacency, obtains different placement modes for spaces and furniture.

关键词： Algorithm design Adjacency matrix Generate floor plan Detection plan

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