Application of photoelectro-fenton process modified with porous cathode electrode in removing resistant organic compounds from aquatic solutions: modeling, toxicity and kinetics

Reza Ali Fallahzadeh,Mohammad Hassan Ehrampoush,Mohsen Nabi Meybodi,Mohammad Taghi Ghaneian,Arash Dalvand,Fariborz Omidi,Mohammad Hossein Salmani,Hossien Fallahzadeh,Amir Hossein Mahvi 한국화학공학회 2020 Korean Journal of Chemical Engineering Vol.37 No.6

The presence of antibiotics in the environment as persistent micropollutants, due to their widespread consumption, has increased the concerns about the harmful effects of these compounds on human and animal health. Advanced oxidation processes are one of the most effective methods to remove these types of organic pollutants. In this study, amoxicillin (AMX) removal in a modified photoelectro-Fenton (PEF) reactor in which porous stainless steel was used as a cathode electrode, and the ability of air injection into its center to produce H2O2 was investigated. A graphite anode electrode equipped with iron rings was used to increase the electrochemical reaction surface and produce iron ions. The effect of current density, time, and electrolyte concentration on AMX removal efficiency was evaluated by Box-Behnken design method. Subsequently, the effect of AMX concentration variable and pH on removal efficiency was investigated. Finally, the chemical oxygen demand (COD) removal efficiency, toxicity, and effluent activity from the PEF reactor were investigated. The results showed that the modified photoelectro-Fenton process could have efficiency of 99% to remove AMX, in 20min using current density of 36 mA/cm2 and 16mM/L electrolyte concentration. Reducing pH and AMX concentration increased the removal efficiency. The PEF process can completely remove the COD in 58 min. Also, toxicity studies indicated an effective reduction in the effluent. This modified reactor improves the efficiency of the PEF process, which, in addition to the 99% removal of AMX, provides a proper function for COD removal, reducing the toxicity properties of the effluent.

Application of photo-electro oxidation process for amoxicillin removal from aqueous solution: Modeling and toxicity evaluation

Reza Ali Fallahzadeh,Amir Hossein Mahvi,Mohsen Nabi Meybodi,Mohammad Taghi Ghaneian,Arash Dalvand,Mohammad Hossein Salmani,Hossien Fallahzadeh,Mohammad Hassan Ehrampoush 한국화학공학회 2019 Korean Journal of Chemical Engineering Vol.36 No.5

The recent increase in the global consumption of antibiotics has led to faster entry of these pollutants into the environment as well as an increase in public concern about its impact on ecosystem and human health. Generally, due to high toxicity of antibiotics, biological methods are not used to treat these pollutants; therefore, advanced oxidation processes are recommended to treat and reduce the toxicity of the wastewater. In this study, we evaluated the efficacy of photo-oxidation (P) and electro-oxidation (E) processes in the removal of amoxicillin (AMX) from wastewater, either as integrated or separate processes. Moreover, the effect of variables, including current density (2-100 mA/cm2), reaction time (2-120 min), and electrolyte concentration (100-1,000mg/l) on antibiotic removal efficiency were investigated by Box Behnken design under response surface methodology, and optimal conditions were determined for pollutant removal. Then, the effect of AMX concentration and pH variables on the removal efficiency was investigated. The COD removal efficiency was also evaluated under optimal conditions, and eventually the toxicity and bioavailability of the effluent from the combined Photo-Electro oxidation process (PE) were examined. The optimal conditions for variables, including current density, reaction time, and electrolyte concentration for removal efficiency of 62.4%, were 94 mA/cm2, 95 min and 997mg/l, respectively. Investigating the Amoxicillin and pH variables showed that by reducing the contaminant concentration and pH, the antibiotic removal efficiency increased. The toxicity and bioavailability of the final effluent show the reduction of both parameters in the PE reactor effluent. The PE process can provide an appropriate function to reduce the toxicity and antibacterial properties of effluent by removing more than 60% of amoxicillin and 30% of COD from wastewater.

An Efficient Scheduling Method for Grid Systems Based on a Hierarchical Stochastic Petri Net

Mohammad Shojafar,Zahra Pooranian,Jemal H. Abawajy,Mohammad Reza Meybodi 한국정보과학회 2013 Journal of Computing Science and Engineering Vol.7 No.1

This paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min.

An Efficient Scheduling Method for Grid Systems Based on a Hierarchical Stochastic Petri Net

Shojafar, Mohammad,Pooranian, Zahra,Abawajy, Jemal H.,Meybodi, Mohammad Reza Korean Institute of Information Scientists and Eng 2013 Journal of Computing Science and Engineering Vol.7 No.1

This paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min.

Cellular goore game with application to finding maximum clique in social networks

Khomami Mohammad Mehdi Daliri,Meybodi Mohammad Reza,Ameri Reyhaneh 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.3

The goore game (GG) is a model for collective decision making under uncertainty, which can be used as a tool for stochastic optimization of a discrete variable function. The GG has a fascinating property that can be resolved in a distributed manner with no intercommunication between the players. The game has found applications in many network applications, including sensor networks, quality-of-service routing, and social networks. In this paper, we introduce an extension of GG called cellular goore game (CGG) for the first time. The CGG is a network of GGs. In this network, each node (or subset of nodes in the network) plays the rule of referees, each of which participates in a GG with its neighboring players (voters) at any time. Like in GG, each player independently selects its optimal action between two available actions based on their gains and losses received from its adjacent referee. Players in CGG know nothing about how other players are playing or even how/why they are rewarded/penalized. The potential of the CGG is shown by providing an algorithm for finding a maximum clique in social networks. Our research provides the first-time study of the CGG for finding a maximum clique in graphs. The performance of the CGG-based algorithm for finding maximum clique is studied on the standard clique benchmark called DIMACS by several experiments. The obtained result shows that the CGG-based algorithm is superior to the existing algorithms in terms of finding maximum clique size and time.

A Precise Algorithm for Detecting Malicious Sybil Nodes in Mobile Wireless Sensor Networks

Mojtaba Jamshidi,Aso Mohammad Darwesh,Augustyn Lorenc,Milad Ranjbari,Mohammad Reza Meybodi 대한전자공학회 2018 IEIE Transactions on Smart Processing & Computing Vol.7 No.6

A Sybil attack, where a malicious node creates multiple fake or captured identities, is one of the most well-known attacks against wireless sensor networks (WSNs). This attack can leave devastating effects on operational and routing protocols, such as voting, data aggregation, resource allocation, and misbehavior detection. In this paper, a simple and precise algorithm for detecting Sybil attacks in mobile WSNs is proposed. Considering the rapid growth of Internet of Things (IoTs) devices and WSNs’ popularity, the threat from this attack is serious. The main underlying idea of the proposed algorithm is to use neighbors’ information and observer nodes to detect Sybil nodes during the network lifetime. In the proposed algorithm, some observer nodes first walk the network and record necessary information about other nodes. Each observer node then uses this collected information to detect Sybil nodes. The proposed algorithm is compared with other algorithms according to criteria including memory, communication, and computation overhead. Also, the proposed algorithm is implemented with the J-SIM simulator, and its performance is compared in a series of experiments with other algorithms using the criteria of true- and falsedetection rates. The simulation results indicate that the proposed algorithm can detect 100% of the Sybil nodes, so its false-detection rate is 0%, regarding the study assumptions.

A Lightweight Algorithm against Replica Node Attack in Mobile Wireless Sensor Networks using Learning Agents

Mojtaba Jamshidi,Shokooh Sheikh Abooli Poor,Nooruldeen Nasih Qader,Mehdi Esnaashari,Mohammad Reza Meybodi 대한전자공학회 2019 IEIE Transactions on Smart Processing & Computing Vol.8 No.1

The node replication attack is considered one of the most dangerous attacks against wireless sensor networks (WSNs). In this attack, an adversary captures one or more normal nodes of the network, extracts its key materials, generates several replicas, and deploys them in the network. In this paper, we propose a novel, intelligent, and lightweight algorithm using learning agents and watchdog nodes (WNs) to detect replica nodes in mobile WSNs. In the proposed algorithm, there are a few WNs, each one equipped with a learning agent that monitors the network traffic and nodes’ movements to identify potential replica nodes in the network. We use the fact that the number of times that a replica node meets a WN is probably more than that of a normal node during a specific monitoring interval of the network. The proposed algorithm is simulated using the J-SIM simulator, and its performance is evaluated in terms of replica node–detection probability and false detection probability through experiments. Experiment results show that the proposed algorithm can detect 100% of the replica nodes, while its false detection probability is less than 0.01.

DSLA: Defending against Selective Forwarding Attack in Wireless Sensor Networks using Learning Automaton

Mojtaba Jamshidi,Mehdi Esnaashari,Shahin Ghasemi,Nooruldeen Nasih Qader,Mohammad Reza Meybodi 대한전자공학회 2020 IEIE Transactions on Smart Processing & Computing Vol.9 No.1

Selective forwarding attacks (SFAs) can harm the mission of critical applications such as military surveillance and forest fire monitoring. In these attacks, malicious nodes behave like normal nodes most of the time, but selectively drop sensitive packets, such as a packet that reports on the movement of opposing forces, and therefore, detection of this kind of attack is hard. In this paper, a fully distributed, dynamic, intelligent, lightweight algorithm based on learning automata is proposed in order to defend against the selective forwarding attack. In this algorithm, an overhearing mechanism, along with the learning automata model, is used to select secure routes for forwarding packets in a multi-hop routing algorithm. Each node is equipped with a learning automaton, which helps the node select the next hop for forwarding its data towards the base station. The proposed algorithm is simulated using J-SIM. Simulation results show the superiority of the proposed algorithm over existing algorithms, such as the single path forwarding algorithm, the multi-hop acknowledge–based algorithm, the multi-data–flow algorithm, the multi-path algorithm, and the neighbor watch system–based algorithm, in packet delivery rate, packet drop rate by malicious nodes, communications overhead, and energy consumption.