Azo Dye Decolorization in Sole Biocatalyzed Electrolysis System (BES) and Coupled with Anaerobic Sequencing Batch Reactor (ASBR-BES) in Operation with Ideal Synthetic Wastewater and Domestic Wastewater

Bakhshi Roghaye,Talebbeydokhti Nasser,Salari Marjan 한국화학공학회 2024 Korean Journal of Chemical Engineering Vol.41 No.3

In practice, various waste streams may be available to drive biocatalyzed electrolysis systems (BESs) for azo dyes decolorization, which can aff ect how BES is employed to achieve superior performance. This work examined the performance of BES and coupling it with an anaerobic sequencing batch reactor (ASBR-BES) in operation with ideal synthetic wastewater (SW) and domestic wastewater (DW) to remove acid orange 7 (AO7). Within 10 h, ASBR-BES-SW showed an acceptable AO7 removal effi ciency (94% ± 0.6%) higher than BES-SW. However, in applying DW, BES achieved 5.3% higher decolorization effi ciency compared to ASBR-BES (79.3% ± 0.7%) in 26 h, which was enhanced to 95.5% ± 0.4% by reducing the electrode spacing to 1 cm. Higher reductant usage ratio and more residual chemical oxygen demand were achieved in SW than DW. Coulombic effi ciencies on AO7 reduction and COD oxidation were evaluated to investigate the contribution of removal processes. Also, variations of electrical conductivity, temperature, pH, and current density during a cycle were examined.

The Effect of Exchange and Correlation on Properties of Carbon Nanotube Structure: A DFT study

Bakhshi, K.,Mollaamin, F.,Monajjemi, M. Korean Chemical Society 2011 대한화학회지 Vol.55 No.1

전자구조의 계산에서 교환과 상관 효과에 대한 기술을 개선하기 위해서는 교환-상관범함수에 대한 개념을 명확히 하는 것이 바람직하다. 이 목적을 성취하기 위해서는 많은 그룹의 물질에 대하여 다른 이론 방법을 적용할 필요가 있다. 본 연구에서는 탄소나노튜브의 고리와 바구니 내원자들의 밀도전하를 연구하기 위하여 혼성 밀도함수 이론(DFT) 계산을 수행하였다. 핵-핵 에너지, 전자-핵 에너지와 운동에너지에 대한 교환 및 상호작용을 관찰하였으며, B3P86, B3PW91, B1B96, BLYP와 B3LYP 수준에서 계산하였다. As an aid towards improving the treatment of exchange and correlation effects in electronic structure calculations, it is desirable to have a clear picture of concepts of exchange-correlation functionals in computational calculations. For achieving this aim, it is necessary to perform different theoretical methods for many groups of materials. We have performed hybrid density functional theory (DFT) methods to investigate the density charges of atoms in rings and cages of carbon nanotube. DFT methods are engaged and compared their results. We have also been inclined to see the impression of exchange and correlation on nuclearnuclear energy and electron-nuclear energy and kinetic energy. With due attention to existence methods, B3P86, B3PW91, B1B96, BLYP and B3LYP have used in this work.

The Effect of Exchange and Correlation on Properties of Carbon Nanotube Structure: A DFT study

K. Bakhshi,F. Mollaamin,M. Monajjemi 대한화학회 2011 대한화학회지 Vol.55 No.1

As an aid towards improving the treatment of exchange and correlation effects in electronic structure calculations,it is desirable to have a clear picture of concepts of exchange-correlation functionals in computational calculations. For achieving this aim, it is necessary to perform different theoretical methods for many groups of materials. We have performed hybrid density functional theory (DFT) methods to investigate the density charges of atoms in rings and cages of carbon nanotube. DFT methods are engaged and compared their results. We have also been inclined to see the impression of exchange and correlation on nuclearnuclear energy and electron-nuclear energy and kinetic energy. With due attention to existence methods, B3P86, B3PW91, B1B96,BLYP and B3LYP have used in this work.

Effect of hydrophobic modification on the structure and rheology of aqueous and brine solutions of scleroglucan polymer

Maryam Bakhshi,Mozhdeh Ozeiri,Alireza Sharif,Jamal Aalaie 한국화학공학회 2017 Korean Journal of Chemical Engineering Vol.34 No.3

Amphiphilic scleroglucans were synthesized by grafting hydrophobic stearate groups in various densities onto the polysaccharide under its triple-helix conformation. Furthermore, a polyelectrolyte was obtained by attaching ionic-sulfonic groups to the hydrophobically modified scleroglucan. Rheological measurements demonstrated the role of grafted stearates in helix-coil transition of scleroglucan and in reducing the viscosity of scleroglucan in pure aqueous and brine solutions. Nevertheless, grafting the ionic-sulfonic groups caused a substantial recovery of the lost viscosity, especially in brine solution at 90 oC, while keeping the amphiphilic character of the hydrophobically modified scleroglucan. Additionally, the hydrophobic modification altered the adsorption behavior of scleroglucan on oil-reservoir rock surfaces: the higher the grafting density, the greater the adsorption amount. However, the polyelectrolyte sample showed the lowest adsorption among all modified samples. Finally, the modified scleroglucans are promising candidates for enhanced oil recovery applications.

$(α,β)_T$-fuzzy $H_vMV$-ideals

Mahmood Bakhshi 원광대학교 기초자연과학연구소 2017 ANNALS OF FUZZY MATHEMATICS AND INFORMATICS Vol.13 No.1

In this paper, based on the concepts of belongingness and quasi-coincidence, new types of fuzzy $H_vMV$-ideals with respect to a t-norm are introduced. Some properties, characterizations and equivalent conditions are given. The connections among them are obtained, as well.

FUZZY FRACTIONAL CONFORMABLE LAPLACE TRANSFORMS

( Negar Bakhshi Sadabadi ),( Fariba Maheri ) 호남수학회 2021 호남수학학술지 Vol.43 No.2

In this paper, we define a fractional conformable fuzzy Laplace transform and prove some related theorems. Also by using this transform we solve some fuzzy fractional differential equations.

Presenting a Hybrid Scheme of Machine Learning Combined with Metaheuristic Optimizers for Predicting Final Cost and Time of Project

Reza Bakhshi,Sina Fard Moradinia,Rasool Jani,Ramin Vafaei Poor 대한토목학회 2022 KSCE JOURNAL OF CIVIL ENGINEERING Vol.26 No.8

A primary task to a project manager is to ensure that the project proceeds timely and on the budget. Earned value management (EVM) is the most common method to evaluate and further predict a project in terms of time and cost. Because of poor accuracy in forecasting different durations, the application of the EVM for schedule performance prediction has been limited. Therefore, in this paper, the Kalman filter was used to analyze the data and compare the results with those of a few hybrid machine learning (HML) techniques. The innovation of this study comes in the face of the prediction of the project time and cost by efficient machine learning algorithms based on some directly measurable variables. For this purpose, 398 data points from five different dam projects were used to predict two output variables by hybrid schemes of multilayer perceptron (MLP) algorithm combined with the genetic algorithm (GA) and particle swarm optimization (PSO), herein referred to as MLP-GA and MLP-PSO, respectively. Four input variables, namely earned schedule (month), earned value ($), actual progress (%), and actual cost (%), were considered for time prediction, and the time (month) was considered as an input variable for cost prediction. The results showed that early warnings for the risk of delay in project schedule and cost were generated in months 1 and 8 by the MLP-PSO, months 1 and 11 by the MLP-GA, and rather months 7 and NV (no value) for the Kalman filter, indicating the fast operation coupled with high accuracy of the HML algorithms, as compared to the Kalman filter. In addition, the two HML algorithms were compared based on statistical error indices to determine the best one. After reviewing the results, the MLP-PSO was found to outperform the MLP-GA in terms of convergence rate and accuracy. To the best of our knowledge, none of the previous studies have used the proposed hybrid algorithms (MELM-PSO and MELM-GA) for forecasting, simultaneously, the time and cost as two critical parameters in the project management, indicating the novelty of our research.

An Efficient Approach in Face Recognition for Invariant Faces using SIFT, SURF and PCA

Yukti Bakhshi,Sukhvir Kaur,Prince Verma 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.5

This paper presents an efficient algorithm based on SIFT (Scale Invariant Feature Transform), SURF (Speeded up Robust Features) and PCA. The method applies the SIFT and SURF algorithm in the detection and description for image features for a particular image and then applying PCA to the image for the better performance in matching in terms of rotation, expression and pose. The SURF technique is fast and robust interest point detector which is used in many computer vision applications. The basic process of face recognition system and improvement in matching the invariant faces is described in this paper. Performance can be seen on the basis of Recognition rate and Computation time. Image Processing Toolbox under MATLAB Software is used for the implementation of this proposed work.

The Within-tree Variation in Wood Density and Mechanical Properties and Their Relationship in Juniperus polycarpos

Kiaei, Majid,Bakhshi, Reza,Saffari, Mohsen,Golkari, Sadegh Institute of Forest Science 2015 Journal of Forest Science Vol.31 No.4

The variations of wood density and mechanical properties of Juniperus polycarpos trees were studied in a natural forest in Iran. Sample disks were taken from each tree to examine wood density and mechanical properties (MOE and MOR) from pith to bark at breast height, 50%, and 75% of total tree height. The analysis of variance (ANOVA) indicated that radial position and height significantly affected all wood properties. The wood density, MOE and MOR were decreased along horizontal position from the pith to the bark and vertical direction from base upwards. Regression analysis showed that modulus of elasticity (MOE) and modulus of rupture (MOR) had a positive correlation with wood density.

Artificial Neural Network for Prediction of Distant Metastasis in Colorectal Cancer

Biglarian, Akbar,Bakhshi, Enayatollah,Gohari, Mahmood Reza,Khodabakhshi, Reza Asian Pacific Journal of Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.3

Background and Objectives: Artificial neural networks (ANNs) are flexible and nonlinear models which can be used by clinical oncologists in medical research as decision making tools. This study aimed to predict distant metastasis (DM) of colorectal cancer (CRC) patients using an ANN model. Methods: The data of this study were gathered from 1219 registered CRC patients at the Research Center for Gastroenterology and Liver Disease of Shahid Beheshti University of Medical Sciences, Tehran, Iran (January 2002 and October 2007). For prediction of DM in CRC patients, neural network (NN) and logistic regression (LR) models were used. Then, the concordance index (C index) and the area under receiver operating characteristic curve (AUROC) were used for comparison of neural network and logistic regression models. Data analysis was performed with R 2.14.1 software. Results: The C indices of ANN and LR models for colon cancer data were calculated to be 0.812 and 0.779, respectively. Based on testing dataset, the AUROC for ANN and LR models were 0.82 and 0.77, respectively. This means that the accuracy of ANN prediction was better than for LR prediction. Conclusion: The ANN model is a suitable method for predicting DM and in that case is suggested as a good classifier that usefulness to treatment goals.