Papers by mehdi sadeghzadeh
Social Science Research Network, 2018
Recent studies on oil market demonstrate endogeneity of oil price by modeling it as a function of... more Recent studies on oil market demonstrate endogeneity of oil price by modeling it as a function of consumption and precautionary demands and producers' supply. However, studies analysing the effect of oil price uncertainty on investment, do not disentangle uncertainties raised by underlying components playing a role in oil market. Accordingly, this study investigates the relationship between investment and uncertainty for a panel of U.S. firms operating in oil and gas industry with a new approach. We decompose oil price volatility to be driven by structural shocks that are recognized in oil market literature, over and above other determinants, to study whether investment uncertainty relationship depends on the drivers of uncertainty. Our findings suggest that oil market uncertainty lowers investment only when it is caused by global consumption demand shocks. Stock market uncertainty is found to have a negative effect on investment with a year of delay. The results suggest no positive relation between irreversible investment and uncertainty, but interestingly, positive relation exists for reversible investment. This finding is in line with the option theory of investment and implies that irreversibility effect of increased uncertainty dominates the traditional convexity effect.
2013 International Conference on Computing, Networking and Communications (ICNC), 2013
Cell collaboration, also known as downlink network MIMO, has been proved to suppress the adverse ... more Cell collaboration, also known as downlink network MIMO, has been proved to suppress the adverse effects of inter-cell interference (ICI), and as a result, to improve the performance of cell edge users. In this paper, we propose a novel clustered linear precoding scheme applicable to network MIMO systems using only partial channel state information (CSI) to enhance the quality of service and the edge user throughput. More specifically, by using a novel block diagonalization (BD) method, we first construct the precoding matrices that jointly eliminate ICI and maximize the sum-rate for a given input covariance matrix. Assuming per-BTS power constraints (PBPCs), optimal allocation schemes are further developed to optimize the sum-rate. Numerical results show that the proposed method can achieve a similar sum-rate to that of the BD with full CSI knowledge. More importantly, such a benefit can be obtained by using a small cluster size without the need of global optimization. The comparison in terms of the average signalto-interference-plus-noise ratio (SINR) between the proposed technique using partial CSI and that with full CSI is also made. It is then revealed that there is no difference in SINR, and as a consequence, the BER performance, between the two schemes.
IEEE Transactions on Vehicular Technology, Jun 1, 2019
In this paper, we propose regularized block diagonalization (RBD) precoding using artificial nois... more In this paper, we propose regularized block diagonalization (RBD) precoding using artificial noise (AN) for physical layer security in downlink multi-user MIMO wireless networks. We derive secrecy sum rate and asymptotic secrecy sum rate for the proposed scheme. The optimum power allocation for legitimate users and the AN signal are derived in closed form for optimal asymptotic secrecy sum rate. Our analysis shows that to achieve best performance, it is more efficient to degrade the performance of the eavesdropper than improving legitimate users’ rates. We also study the impact of error in channel estimation on the system and derive closed-form SINR and secrecy sum-rate expressions for this case. Simulations show that the secrecy sum rate of RBD precoding outperforms the secrecy sum rate of regularized channel inversion by 0.5 bits/s/Hz. We also show that in the presence of channel estimation error, our approximate closed forms for secrecy sum rate are very closed to the actual secrecy sum rate over a wide range of SNR and channel estimation error values.
Nowadays, the use of social networks has developed widely. When people publish too much private i... more Nowadays, the use of social networks has developed widely. When people publish too much private information about themselves in these networks, their information may be attacked by an adversary, so there is a need to protect the privacy of people on these networks. One of the methods of preserving private information is k-anonymization. Anonymization is encountered with the challenge of data loss. A method is needed that ensures data anonymization while the utility is also well preserved. In this research, we try to create a proper model for data privacy and utility preservation by combining a graph cut clustering method and an artificial bee colony optimization algorithm. Two datasets are used in this research, which are Ca-GrQc including 5242 nodes and 14496 edges, and Polbooks containing 105 nodes and 441 edges. Three measures are used to evaluate this model, including, Transitivity, APL, and ACC. Finally, based results it can be declared proposed method, is a proper method for preserving privacy in social networks.
In this research, an investigation on the genetic algorithm efficiency to determine the optimal a... more In this research, an investigation on the genetic algorithm efficiency to determine the optimal air distribution in the ventilation networks and the optimal fan performance and required pressure drop for the regulator doors is carried out. The objective function of the model is the minimization of energy consumption.
In recent years, speech recognition has become one of the most important areas of research. The c... more In recent years, speech recognition has become one of the most important areas of research. The current system has been used to extract features from Mel-frequency cestrum coefficient (MFCC) if the signal is degraded by noise, it cannot create a system with high ability of recognition. In this paper we present an approach in which the speech recognition systems will be capable to do the recognition operations with higher capability. To achieve this goal we create the speech recognition by combining MFCC and analysis–modification–synthesis (AMS) methods and multiply it in input noise signal. Three experiment were investigated, in the first experiment, sub-bands weighted and non-weighted are studied, In a second experiment, the input signal was compared with the sum sub-bands weighted in the third trial, we compared the all of the band input signal with the whole band input signal, and the reconstructed weight signal was multiplied. The results showed that we can improve the reconstructed weighted signal by multiplying it in the input signal and also the ratio of the sum of the weighted sub-bands to the duration of the multiplication of all of the input signal bands by the reconstructed weighted signal had a lower mean squared error (MSE) value.
Decision Science Letters, 2014
Today, the world facing with huge flood of data and the recent advances in computer technology ha... more Today, the world facing with huge flood of data and the recent advances in computer technology have provided the capability to process significant amount of data. On the other hand, analyzing the information requires resources that most institutions do not have, independently. To handle such circumstances, grid computing has emerged as an important research area where the calculation of distributed computing and clustering are different. In this study, we propose a grid computing architecture as a set of protocols that use the cumulative knowledge of computers, networks, databases and scientific instruments based on the implementation of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique. The results of the implementation of the proposed algorithm on grid systems indicate the superiority of the proposed approach in terms of validation criteria scheduling algorithms, such as task completion time and the performance compared with some alternative method.
Research Square (Research Square), Jun 16, 2022
This paper proposes a new method to solve the problem of foraging in swarm robotics. This researc... more This paper proposes a new method to solve the problem of foraging in swarm robotics. This research approach is inspired by the collective behaviours of some species of bats that communicate the location of food or nests to other group using sound signals. A mechanism has been established a mechanism for more effective communication between agents. Within the framework of a self-organizing system without a central controller and through coordination mechanisms in individuals, we propose a way to prevent overcrowding at the point of exploitation and continue exploration. In this research, homogeneous agents, independently, with limited perception and processing ability, can determine and change their role in the group, and according to their role, they perform various tasks and cooperate and interact with other agents, and change and determine the roles of the agents according to rules, social or threshold time is done according to a probabilistic model. We tested the proposed method in a simulation environment and showed the performance of a group of individual agents with minimal cognitive and processing abilities.
GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017
We analyze asymptotic performance of regularized block diagonalization (RBD) precoding along with... more We analyze asymptotic performance of regularized block diagonalization (RBD) precoding along with artificial noise (AN) used for physical layer security in downlink multi-user wireless networks. We derive the secrecy and asymptotic secrecy sum-rates for this scheme. We also derive closed form expressions for the asymptotic power allocation to the AN signal and legitimate users. Simulations show RBD precoding outperform regularized channel inversion (RCI) in terms of secrecy sum-rate with a margin of 0.5 bits/s/Hz.
The routing problem is a multi-objective optimization problem with a set of constraints. An ideal... more The routing problem is a multi-objective optimization problem with a set of constraints. An ideal routing algorithm should strive to find an optimum path for packet transmission within a specified time so as to satisfy the Quality of Service (QoS). This paper presents a method based on non-dominated sorting genetic algorithm-II (NSGA-II) for solving routing problem in computer networks that consider simultaneously three criteria: cost, delay and delay jitter. This method based on the current network conditions, instead of finding one optimal path for transmitting data packets to a destination, finds several optimal paths; so the proposed method fulfills the QoS requirements and uses effectively of network resources. The results obtained by proposed method are compared with NSGA algorithm. Experimental results show that this method has better performance and higher efficiency than NSGA algorithm and finds optimal paths for leading packets in single simulation run.
Today, due to fundamental advances in the field of integrated circuit design, wireless communicat... more Today, due to fundamental advances in the field of integrated circuit design, wireless communications and sensor design, wireless sensor networks are highly regarded researchers in various industries. Increased lifetime in wireless sensor networks, without having the ability to replace and recharge the batteries, the issue has become a challenge for researchers. In this regard, many algorithms and methods are provided. In some cases, the problem of increasing energy consumption in the nodes level examined, in others the problem at the network level and have provided techniques for routing and reduce consumption. In this paper routing methods to reduce energy consumption and function of each is checked and then ALO meta-heuristic algorithm role in the global clustering and network with mobile base stations to reduce energy consumption is expressed.
Int. Arab J. Inf. Technol., 2019
One of the most challengeable problems in pattern recognition domain is financial time series for... more One of the most challengeable problems in pattern recognition domain is financial time series forecasting which aims to exactly estimate the cost value variations of a particular object in future. One of the best well-known financial time series prediction methods is Neural Network (NN) but it suffers from parameter tuning such as number of neuron in hidden layer, learning rate and number of periods that should be forecasted. To solve the problem, this paper proposes a new metaheuristic-based parameter tuning scheme which is based on Harmony Search (HS). To improve the exploration and exploitation rates of HS, the control parameters of HS are adapted during the generations. Evaluation of the proposed method on several financial times series datasets shows the efficiency of the improved HS on parameter setting of NN for time series prediction.
International Journal of Robotics and Automation, 2016
With the growth of network complexity, it is very common to find firewall policies with thousands... more With the growth of network complexity, it is very common to find firewall policies with thousands of rules. Modern firewall rulebase are growing in size and complexity at an exponential rate. As changes add up, the firewall rule base gets more complex. Firewall rulebase works on first-match principle. As a result, there exists scope of improvement in firewall performance, if highest utilized rule is brought ahead in rulebase. This will facilitate earlier matching and hence less firewall resource utilization. However, this should be done carefully without compromising overall firewall security or without loss of semantic integrity. In this paper, authors have proposed framework for rulebase reordering based on traffic conditions. To evaluate the performance of approach, authors further carried out performance testing on OpenBSD PF firewall by reordering rulebase under laboratory traffic. Results obtained indicate 9.57% improvement in firewall throughput and 11.9% improvement in concurrent connections after rulebase is reordered based on traffic conditions.
The ad hoc network is a system of network elements that combine to form a network requiring littl... more The ad hoc network is a system of network elements that combine to form a network requiring little or no planning. This may not be feasible as nodes can enter and leave the network. In such networks, each node can receive the packet (host) and the packet sender (router) to act. The goal of routing is finding paths that meet the needs of the network and effectively use network resources. This paper presents a method for QoS routing in ad hoc networks based on ant colony optimization (ACO) algorithm and fuzzy logic. The advantages of this method flexibility and routing are based on several criteria. The results show that the proposed method in comparison with the algorithm IACA has better performance, higher efficiency and greater throughput. Therefore, the combination of ant algorithm with Fuzzy Logic due to its simplicity fuzzy computing is appropriate for QoS routing.
Razavi International Journal of Medicine, 2021
Background and Objectives: Nowadays, attracting tourists and keeping them in a competitive enviro... more Background and Objectives: Nowadays, attracting tourists and keeping them in a competitive environment, especially in the health tourist industry, has a high priority. Given the different behaviors of health tourists, analyzing their behavior is important.Methodology: This research is applied in terms of purpose and descriptive method. Data mining methods and powerful Python tools have been used to analyze the data. The combined method of clustering algorithm and communication rules have been used to identify the pattern of tourist behavior.Results: After analyzing the data, the motivation of foreign tourists to travel to Iran was determined and the selected destination was prioritized based on importance and according to the behaviors and different needs of health tourists, different travel packages were designed.Conclusion: By analyzing the behavior of tourists and clustering them according to the type of behavior in each cluster, it is possible to achieve strategies tailored to t...
Razavi International Journal of Medicine, 2021
Background and Objectives: Today, increasing consumer desire for health tourism has led to a grea... more Background and Objectives: Today, increasing consumer desire for health tourism has led to a greater understanding of the behavioral patterns of tourists. It becomes clear that intervention in that process is necessary to achieve the desired results. The development of tourism services at a specific time is essential for the target market and meeting the needs of tourists to succeed in the tourism market. Methodology: In this article, a Quantitative and qualitative method has been used. In the qualitative method, 50 people were interviewed and in the quantitative part, 156 questionnaires were distributed, and finally, its validity and reliability were examined. SmartPLS2 software has been used for modeling and data analysis. Results: After analyzing the data, the effective factors in tourists' decision to choose Iran as a health tourism destination were examined. By focusing on the obtained factors, the needs of health tourists can be met and more motivation can be created. Conc...
Nowadays, we live in web area. The area through which the formation of various social network, ne... more Nowadays, we live in web area. The area through which the formation of various social network, new communicative and informing methods are introduced to the widespread social communications. A social network is a social structure which is made out of individuals and meanwhile, by the pass of time, the analyzing these social network will gain increasing primacy. In this research, one of the parameters of social network analysis called edge betweenness centrality is introduced. Edge betweenness is an edge to compute the shortest paths between pair of nodes in the network that passes through it most frequently. In this research, to detect the communities through edge betweenness centrality algorithm, a method is introduced in such a way that each edge by receiving one fuzzy membership degree in the interval [1,0] the measure of its effect on the network will be different. One of the features of this algorithm that makes it distinguished from others is the application of fuzzy logic to ...
Uploads
Papers by mehdi sadeghzadeh