Search results for: S. Behzadi
6 Metrics and Methods for Improving Resilience in Agribusiness Supply Chains
Authors: Golnar Behzadi, Michael O'Sullivan, Tava Olsen, Abraham Zhang
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By definition, increasing supply chain resilience improves the supply chain’s ability to return to normal, or to an even more desirable situation, quickly and efficiently after being hit by a disruption. This is especially critical in agribusiness supply chains where the products are perishable and have a short life-cycle. In this paper, we propose a resilience metric to capture and improve the recovery process in terms of both performance and time, of an agribusiness supply chain following either supply or demand-side disruption. We build a model that determines optimal supply chain recovery planning decisions and selects the best resilient strategies that minimize the loss of profit during the recovery time window. The model is formulated as a two-stage stochastic mixed-integer linear programming problem and solved with a branch-and-cut algorithm. The results show that the optimal recovery schedule is highly dependent on the duration of the time-window allowed for recovery. In addition, the profit loss during recovery is reduced by utilizing the proposed resilient actions.Keywords: agribusiness supply chain, recovery, resilience metric, risk management
Procedia PDF Downloads 3975 Obtaining Constants of Johnson-Cook Material Model Using a Combined Experimental, Numerical Simulation and Optimization Method
Authors: F. Rahimi Dehgolan, M. Behzadi, J. Fathi Sola
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In this article, the Johnson-Cook material model’s constants for structural steel ST.37 have been determined by a method which integrates experimental tests, numerical simulation, and optimization. In the first step, a quasi-static test was carried out on a plain specimen. Next, the constants were calculated for it by minimizing the difference between the results acquired from the experiment and numerical simulation. Then, a quasi-static tension test was performed on three notched specimens with different notch radii. At last, in order to verify the results, they were used in numerical simulation of notched specimens and it was observed that experimental and simulation results are in good agreement. Changing the diameter size of the plain specimen in the necking area was set as the objective function in the optimization step. For final validation of the proposed method, diameter variation was considered as a parameter and its sensitivity to a change in any of the model constants was examined and the results were completely corroborating.Keywords: constants, Johnson-Cook material model, notched specimens, quasi-static test, sensitivity
Procedia PDF Downloads 3114 Methaheuristic Bat Algorithm in Training of Feed-Forward Neural Network for Stock Price Prediction
Authors: Marjan Golmaryami, Marzieh Behzadi
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Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange
Procedia PDF Downloads 5493 Assessing the Correlation between miR-141 Expression, Common K-Ras Gene Mutations, and Their Impact on Prognosis in Colorectal Cancer Tissue of Iranian Patients
Authors: Shima Behzadi
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Background: In many human malignant tumors, microRNA expression is aberrant. This study investigates miR-141 as a prognostic marker in colorectal cancer with K-Ras mutation. Materials and methods: In this case-control study, 100 patients, mostly over the age of 50, who were diagnosed with colorectal cancer were selected. The pathology department of the Mostoufi Pathobiology and Genetics Laboratory in Tehran confirmed the presence of colorectal cancer in samples of paraffin-embedded colon tissue. The case group was composed of patients with codon 12 and 13 mutations in exon 2 of the K-Ras gene, while tumor samples of individuals without these mutations in exon 2 of the K-Ras gene were selected as the control group, with patient consent. The changes in the expression of miR-141 were examined in both groups. Results: The study found that 20% of the patients tested positive for codon 12 mutation, and 10% of patients had codon 13 mutation. As a result, in 30 cases, there was a higher level of miR-141 expression. The miR-141 gene expression level in K-Ras positive tumor samples was 1.5 times higher than its expression level in K-Ras negative samples. This increase in expression was statistically significant, with a p-value of less than 0.001, indicating that the observed results are highly statistically significant. Conclusion: The study revealed that the incidence of typical K-Ras gene mutations among the colorectal cancer patients in the sample matches the national average in Iran. Additionally, the expression of miR-141 can serve as a useful biomarker to aid in the prognosis of colorectal cancer.Keywords: colorectal cancer, K-Ras gene, miR-141 marker, real time PCR, electrophoresis
Procedia PDF Downloads 462 Coastal Water Quality Assessment in Hormozgan Province: Implications for Sustainable Marine Ecosystems and Aquaculture in the Persian Gulf
Authors: Sharareh Khodami, Mohammad Seddiq Mortazavi, Seyedeh Laili Mohebbi-Nozar, Fereshteh Saraji, S. Behzadi, Gholam Ali Akbarzadeh, Mitra Naemi
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Water quality is a critical driver of healthy marine ecosystems and a cornerstone of the blue economy, particularly fisheries. The coastal waters of Hormozgan Province, located in the northern Persian Gulf and Gulf of Oman, are increasingly threatened by wastewater discharges from industrial, urban, and agricultural activities. This study evaluates the spatial and temporal patterns of coastal water quality over two decades (2001–2021), drawing on a comprehensive dataset from 200 sampling stations along the province’s shoreline. Key environmental parameters -temperature, dissolved oxygen, salinity, turbidity, chlorophyll-a, nitrate, nitrite, ammonium, and phosphate- were analyzed. Using geographic information systems (GIS), spatial distributions were mapped, and a water quality index (WQI) was derived to classify overall water quality conditions. The WQI values ranged from weak to excellent, reflecting notable spatial variability. The interquartile range (IQR) method was applied to determine acceptable parameter ranges and establish early-warning thresholds for management. Zones were categorized into “caution” and “action” areas, guiding targeted interventions. Results highlight the significant impacts of sustained nutrient loading, particularly from nitrate and phosphate linked to anthropogenic sources, on coastal ecosystem health. These findings underscore the urgent need for stringent nutrient management policies to protect marine ecosystems, ensuring the long-term sustainability of fisheries and other marine resources in this region.Keywords: coastal area, Hormozgan, Persian Gulf, water quality
Procedia PDF Downloads 11 Inflation and Deflation of Aircraft's Tire with Intelligent Tire Pressure Regulation System
Authors: Masoud Mirzaee, Ghobad Behzadi Pour
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An aircraft tire is designed to tolerate extremely heavy loads for a short duration. The number of tires increases with the weight of the aircraft, as it is needed to be distributed more evenly. Generally, aircraft tires work at high pressure, up to 200 psi (14 bar; 1,400 kPa) for airliners and higher for business jets. Tire assemblies for most aircraft categories provide a recommendation of compressed nitrogen that supports the aircraft’s weight on the ground, including a mechanism for controlling the aircraft during taxi, takeoff; landing; and traction for braking. Accurate tire pressure is a key factor that enables tire assemblies to perform reliably under high static and dynamic loads. Concerning ambient temperature change, considering the condition in which the temperature between the origin and destination airport was different, tire pressure should be adjusted and inflated to the specified operating pressure at the colder airport. This adjustment superseding the normal tire over an inflation limit of 5 percent at constant ambient temperature is required because the inflation pressure remains constant to support the load of a specified aircraft configuration. On the other hand, without this adjustment, a tire assembly would be significantly under/over-inflated at the destination. Due to an increase of human errors in the aviation industry, exorbitant costs are imposed on the airlines for providing consumable parts such as aircraft tires. The existence of an intelligent system to adjust the aircraft tire pressure based on weight, load, temperature, and weather conditions of origin and destination airports, could have a significant effect on reducing the aircraft maintenance costs, aircraft fuel and further improving the environmental issues related to the air pollution. An intelligent tire pressure regulation system (ITPRS) contains a processing computer, a nitrogen bottle with 1800 psi, and distribution lines. Nitrogen bottle’s inlet and outlet valves are installed in the main wheel landing gear’s area and are connected through nitrogen lines to main wheels and nose wheels assy. Controlling and monitoring of nitrogen will be performed by a computer, which is adjusted according to the calculations of received parameters, including the temperature of origin and destination airport, the weight of cargo loads and passengers, fuel quantity, and wind direction. Correct tire inflation and deflation are essential in assuring that tires can withstand the centrifugal forces and heat of normal operations, with an adequate margin of safety for unusual operating conditions such as rejected takeoff and hard landings. ITPRS will increase the performance of the aircraft in all phases of takeoff, landing, and taxi. Moreover, this system will reduce human errors, consumption materials, and stresses imposed on the aircraft body.Keywords: avionic system, improve efficiency, ITPRS, human error, reduced cost, tire pressure
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