Mohammad Alishahi
@fiau.ac.ir
Department of computer engineering
Fariman branch, Islamic Azad university, Fariman Iran
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Mohammad Reza Aalami, Mahdi Zarif, Mohammad Alishahi, Ali Asghar Shojaei, and Hamed Heydari Doostabad
Institution of Engineering and Technology (IET)
MohammadHossien Alishahi, Paul Fortier, Wanming Hao, Xingwang Li, and Ming Zeng
Institute of Electrical and Electronics Engineers (IEEE)
Mohammad Eydi, Mohammad Alishahi, and Mahdi Zarif
Institution of Engineering and Technology (IET)
Arghavan Irankhah, Sahar Rezazadeh Saatlou, Mohammad Hossein Yaghmaee, Sara Ershadi-Nasab, and Mohammad Alishahi
IEEE
Nowadays, power companies are trying to monitor energy consumption to provide demand response. Energy management and scheduling are possible through short-term load forecasting. Energy supply stability and efficiency depend on accurate forecasting, which balances demand and supply. In this paper, a novel hourly energy prediction method is introduced. A new parallel deep learning network is presented based on CNN and GRU networks. Firstly, some features are extracted from the dataset during pre-processing. Then, the CNN models extract more information from these features in two parallel paths. Afterward, Bi-GRU networks are used to observe the extracted features from previous layers in both two directions to learn long dependency patterns. The real-world data collected by Mashhad energy distribution company is used to evaluate the proposed method. The results demonstrate that the proposed method reached the lowest values containing 49.04, 34.37, and 3.81 for RMSE, MAE, and MAPE metrics in comparison with existing methods.
Leili Mortazavi, Mohammad Alishahi, Ameneh Rajabi Darbandiolya, and Amir Mohammad Nazemi
IEEE
The demand of users and the increase of devices connected to cellular networks has increased accordingly, since the advent of different generations of mobile phones and the communication between people through mobile phones. Over the years, researchers and mobile operators have come to the conclusion that current technologies do not meet the needs of users. Therefore, to meet the needs of users, the number of micro-cells is increasing sharply, but with this volume of increase, mobile operators are facing the challenge of energy consumption. Using the cell shutdown approach, key and very useful solutions can be provided to optimize energy consumption in mobile cellular networks. In the cell shutdown method, shutting down a number of cells, moving them to an adjacent cell, without compromising the quality of service and reducing the covered areas, is a requirement of this approach. This paper simulates a solution to reduce energy consumption in base stations by clustering and selecting a base station based on the annealing algorithm. The simulation results show that the proposed model, compared to the model that is performed only with respect to the node Euclidean distance to the base station, has improved an operational power of more than 5%, a power consumption of more than 2% and a network lifetime of more than 3%. While the average of inactive base stations in the proposed model has been up to 8% higher.
Mostafa Farhadi Moghadam, Mahdi Nikooghadam, Maytham Azhar Baqer Al Jabban, Mohammad Alishahi, Leili Mortazavi, and Amirhossein Mohajerzadeh
Institute of Electrical and Electronics Engineers (IEEE)
Wireless sensor networks (WSN) consist of a large number of resource-constrained sensor nodes, different types of controls, and gateway nodes. these kinds of networks are used as control systems and remote monitoring in industries such as health care, defense, agriculture, and disaster management. Due to the widespread use of wireless sensor networks, valuable information is exchanged between network entities such as sensors, gates, users, etc. in an unsafe channel, and the presence of important and sensitive information in the network increases the importance of security issues. In this article, we analyzed Majid Alotaibi schema and identify some security breaches in this article. We have also described a security attack against the proposed protocol based on security problems. In addition, to address the security issues of M. Alotaibi proposed protocol, we have introduced a mutual authentication and key agreement protocol based on ECDH (elliptic-curve Diffie–Hellman). We have implemented our own method using the Scyther tool, manually reviewed its security features and also compared it with other methods.
Zahra Izadi-Ghodousi, Mahsa Hosseinpour, Fatemeh Safaei, Amir Hossein Mohajerzadeh, and Mohammad Alishahi
Springer Science and Business Media LLC
In this paper we have considered an efficient adapted Unscented Kalman Filter based target tracking in directional wireless sensor networks while observations are noise-corrupted. In directional sensor networks, sensors are able to observe the target only in specified (and certainly changeable) directions. Also, sensor nodes are capable of measuring the bearings (relative angle to the target). To make target tracking efficient, first, we use scheduling algorithm which determines the sensor nodes activity. Also coverage is a challenge that we will discuss in this paper as well. Sensor nodes activation algorithm directly affects the target areas coverage. Second, we use time series to predict the motion of the target. Using ARIMA, in each step of target position estimation, an area will be predicted where the target would be there with high probability. Third, we use a version of UKF, which is adjusted to the requirements of the target tracking application, to determine the position of the target with desired precision. Fourth, a routing algorithm called as C-RPL is used to perform the communications between sensor nodes in each step. Simulation results approve that the proposed efficient target tracking algorithm achieves its goals.
Mohammad Alishahi, Mohammad Hossein Yaghmaee Moghaddam, and Hamid Reza Pourreza
Springer Science and Business Media LLC
Routing Protocol for Low Power and Lossy Network (RPL) is standardized and known as the primary solution for the last mile communication network in the smart grid. Various applications with different requirements are rapidly developed in the smart grid. The need to provide Quality of Service (QoS) for such a communication network is inevitable. In this paper, we use the benefits of virtualization and software-defined networking to present a virtual version of the RPL protocol which we name OMC-RPL (Optimized Multi-Class RPL). We present an SDN-enabled architecture consisting of a central controller and some SDN nodes. This implementation reduces the complexity and controls interactions to distribute the network states and other related information in the network. The proposed SDN-enabled architecture consists of different components including Network Link Discovery, Topology Manager, and Virtual Routing. OMC-RPL utilizes a holistic objective function including distinctive metrics related to QoS, and supports the data classification which is an essential requirement in this context. The proposed objective function considers different numbers of traffic classes by using weighting parameters. An optimization algorithm determines the best values of these coefficients. OMC-RPL is evaluated in different aspects. Simulation results show that the new idea significantly decreases both the end-to-end delay and packet loss which are the important factors of QoS. The virtualization idea is also investigated, which results in less message exchange.
Mohammad Alishahi, Mostafa Farhadi, Sina Jafari, Mina Taghavi, Hamid Moosavi, and Amirhossein Mohajerzadeh
IEEE
The population growth influences the need for electric power. But the existing power grid is not fully qualified to resolve this need. For providing a suitable power grid that is match with today's needs, smart grid has been proposed. Smart grid includes advanced metering infrastructure (AMI), communication network, etc. alongside traditional power grid to deliver the electric power to the customers. One of the most important parts of smart grid is the communication link between smart meters and the control center. Since smart grid's performance relies on real time data communication, reliable and secure communications for transporting the real time data is crucial. Smart grid communication network consists of HAN (home area network), BAN (building area network), NAN (neighbor area network) and WAN (Wide area network). This paper proposes an efficient and secure infrastructure for communication in a smart grid focusing on two networks, HAN and NAN. Using Elliptic Curve Cryptography (ECC) a key agreement scheme is built up that contains two phases, pre-deployment and key agreement. The proposed scheme is cost efficient in using operators and transmitting messages for agreement on a session key for safe data transmission.
Guohong Wu, Yoshiyuki Ono, and Mohammad Alishahi
IEEE
This paper presents an experimental study with a pilot hybrid microgrid system that is proposed and implemented in Tagajo campus of Tohoku Gakuin University, Japan. The developed microgrid system is designed to be able to supply power to both DC and AC loads simultaneously by renewable power sources such as PV and wind power generations, etc. Meanwhile, in case that the renewable power is insufficient to supply both these loads, a diesel generator is automatically actuated as backup power source. For the purpose of power balance and voltage stabilization, two types of energy storage devices with different response characteristics and cost, which are secondary battery and EDLC (Electrical Double-layer Capacitor) respectively, are introduced into this system. In this work, a coordinated control strategy for these energy storages were proposed and verified by a series of experimental studies with the developed hybrid microgrid system. The purpose of the experimental study addressed in this paper is to confirm the islanded operation properties of this system for stable power supply to both AC and DC loads, even in case with considerable power fluctuation of renewable sources and significant power change in loads. As a result of this study, it is illustrated that the developed hybrid microgrid and its control systems can work properly and resiliently as being designed.
Mohammad Alishahi and Mostafa Majidpour
IEEE
According to the growth of different projects and research in the transportation field and also connected, automated and intelligent vehicles the use of effective protocols and standardization is a growing necessity in this context. In this paper we customized an existing internet standard which is called RPL (Routing Protocol for Low Power and Lossy Networks) for connected vehicles. RPL is flexible and has special specifications such as supporting many low power and lossy nodes, different traffics and self-healing. We believe customized RPL could be suitable for connected vehicles. Our proposed RPL with respect to the Quality of Service (QoS) parameters and the simulation results with different scenarios prove our claims.
M. Alishahi, S.S. Khorasani, M.H. Yaghmaee, and M. Zabihi
Institution of Engineering and Technology
Nowadays, the increasing demands and inadequate technology in electricity industry lead us to make it smart. To achieve this goal, the quality of service is very important for critical applications like teleprotection. Since the allowed delay for these kinds of applications are about milliseconds, having latency in packet delivery will cause serious damages. In this paper, we try to identify the verity of IF-based applications in Mashhad Electric Energy Distribution Company (MEEDC) and prioritize them based on their importance and traffic features such as allowed delay, arrival rate and packet size. After that we want to find an appropriate aggregation point for their traffics to analyse the input queue of the routers. By doing this we will be able to calculate the minimum required bandwidth for the egress link and according to the available communication network we can make decision whether the egress link is adequate or not. If not we can guarantee the QoS for critical applications. (4 pages)
Mahmoud Houshmand and Mohammad Alishahi
IEEE
There are some elements such as competition among companies and changes in demands which result in changes of customers' behaviors. Therefore, paying no attention to these changes may lead to a reduction in company benefits and loss of customers. Since data and their analyses determine the activities and decision makings of companies, data quality is of paramount in analyzing them because misinformation leads to wrong decision making. Since data mining has been designed to find out multi repetition patterns, it can be used to improve the product sales violations by sales people and increase the quality of data. Most of data mining models available try to find patterns in one table, but the fact is that standard database is of more applications because they are normalized and the data are scattered in more than one table. This situation calls for a new method to discover the data and interpret them. This paper tries to discuss this issue as the Multi-Relational Data Mining (MRDM). In fact, this MRDM is used to improve product sales and categories. This method, indeed, enables us to extract the knowledge beyond several tables in standard database and compare data with the extracted patterns. There is a method to measure and evaluate data from some tables in the database with the approach of MRDM.
Homa Foroughi, Mohamad Alishah, Hamidreza Pourreza, and Maryam Shahinfar
Springer Netherlands
Video Surveillance is an omnipresent topic when it comes to enhancing security and safety in the intelligent home environments. In this paper we propose a novel method to detect various posture-based events in a typical elderly monitoring application in a home surveillance scenario. These events include normal daily life activities, abnormal behaviors and unusual events. Due to the fact that falling and its physical-psychological consequences in the elderly are a major health hazard, we monitor human activities with a particular interest to the problem of fall detection. Combination of best-fit approximated ellipse around the human body, horizontal and vertical velocities of movement and temporal changes of centroid point, would provide a useful cue for detection of different behaviors. Extracted feature vectors are finally fed to a fuzzy multiclass support vector machine for precise classification of motions and determination of a fall event. Reliable recognition rate of experimental results underlines satisfactory performance of our system.
Fatemeh Ghorbanpour Alizamini, Mir Mohsen Pedram, Mohammad Alishahi, and Kambiz Badie
IEEE
The activities and decisions of organizations and companies are based on data and the information obtained from data analysis. Data quality plays a crucial role in data analysis, because the incorrect data leads to wrong decisions. Nowadays, improving the data quality manually is very difficult and in many cases is impossible as data quality is one of the complicated and non-structured concepts and data refinement process can not be done without the help of professional domain experts, and detection and correction of errors require a thorough knowledge in the related domain of the data. Thus, the necessity of using (semi-)automatic methods is discussed to find data defects and errors and solve them. Because data mining methods are designed to discover interesting patterns in datasets, we can use them efficiently to improve different dimensions of data quality. In this paper, a new method is presented to measure the accuracy dimension of data quality using fuzzy association rules. Finally, Experimental results of the proposed method show the effectiveness of the proposed method to find incorrect values in datasets.
Mohamad Alishahi, Mehdi Ravakhah, Baharak Shakeriaski, and Mahmud Naghibzade
IEEE
One of the most effective ways to extract knowledge from large information resources is applying data mining methods. Since the amount of information on the Internet is exploding, using XML documents is common as they have many advantages. Knowledge extraction from XML documents is a way to provide more utilizable results. XCLS is one of the most efficient algorithms for XML documents clustering. In this paper we represent a new algorithm for clustering XML documents. This algorithm is an improvement over XCLS algorithm which tries to obviate its problems. We implemented both algorithms and evaluated their clustering quality and running time on the same data sets. In both cases, it is shown that the performance of the new algorithm is better.