Number 1 Volume 5

Open Access Article

1 - A New Method to Improve Energy Consumption in Wireless Camera Sensor Networks
javad bayat Shiva Karimi

Introduction: In the development of wireless camera sensor networks, there are unique challenges such as the need for high bandwidth, low latency for processing, high energy consumption, and real-time control. Each wireless camera sensor node is able to process image da More

Introduction: In the development of wireless camera sensor networks, there are unique challenges such as the need for high bandwidth, low latency for processing, high energy consumption, and real-time control. Each wireless camera sensor node is able to process image data locally and extract suitable data and cooperate with other cameras based on the desired application. In these networks, high bandwidth is demanded to transmit visual data, and high volume calculations in these networks must be possible with low power. In this article, a new model based on Harris‘s Hawk optimization algorithm is proposed to improve energy consumption in wireless camera sensor networks. The optimization algorithm of Harris‘s Hawk is one of the meta-heuristic algorithms that was invented in 2019. Method: Harris‘s Hawk optimization algorithm was used to form optimal clustering. Each vector generated in Harris‘s Hawk optimization algorithm is calculated based on the fitness function and the most optimal vectors are selected for clustering. In the proposed model, factors such as intra-cluster distance and extra-cluster distance, and energy consumption have been considered. Results: Evaluations in the environment of 150×150 m2 and 300×300 m2 with a different number of nodes show that the proposed model has better efficiency compared to PADT and genetic algorithm (GA). Discussion: In wireless camera sensor networks, the imbalance of energy consumption among nodes is an effective factor in the network lifetime. In order to balance the energy consumption among nodes, clustering algorithms have been proposed for uniform energy distribution. In this paper, we proposed a new model for clustering camera sensor nodes based on Harris‘s Hawk optimization algorithm. In the proposed model, we paid attention to parameters such as intra-cluster distance, extra-cluster distance, and residual energy of sensor nodes. The cluster quality criterion is based on the intra-cluster distance, which depends on the position of the cluster head in the clusters. In the proposed model, because the distance criterion is taken into account and the distance of non-cluster nodes with the cluster head node is evaluated and the closest nodes to the cluster head are selected. Manuscript profile

Open Access Article

2 - A Trust-based Recommender System Using an Improved Particle Swarm Optimization Algorithm
Sajad Ahmadian Mohammad Hossein Olyaee

Introduction: Recommender systems are intelligent tools to help users find their desired information among a large number of choices based on their previous preferences in a way faster than search engines. One of the main challenges in recommender systems is the sparsit More

Introduction: Recommender systems are intelligent tools to help users find their desired information among a large number of choices based on their previous preferences in a way faster than search engines. One of the main challenges in recommender systems is the sparsity of the user-item rating matrix. This means that users mainly tend to express their opinions about a few items, leading to a large portion of the user-item rating matrix being empty. Trust-based recommender systems aim to alleviate the sparsity problem using trust relationships between users. Trust relationships can be used to calculate similarity values between users and determine the nearest neighbors set for the target user. However, the efficiency of trust-based recommender systems depends on the correct selection of neighboring users for the target user based on the similarity values between users. Method: In this paper, a novel trust-based recommender system is proposed based on an improved particle swarm optimization algorithm. To this end, first, the similarity values between users are calculated based on the user-item rating matrix and trust relationships. Then, the improved particle swarm optimization algorithm is used to optimally weight the neighboring users of the target user. The main purpose of this algorithm is to assign an optimal weight to each user in the nearest neighbor set of the target user to predict the unknown items accurately. After the optimal weighting of neighboring users, unknown ratings are predicted for the target user. Results: The proposed method is evaluated on a standard dataset in terms of mean absolute error, root mean square error, and rate coverage metrics. Experimental results demonstrate the high efficiency of the proposed method compared to other methods. Discussion: We use the genetic algorithms operators and chaos-based asexual reproduction optimization algorithm to improve the original version of the particle swarm optimization algorithm. The genetic algorithms operators increase the exploration mechanism of the particle swarm optimization algorithm, leading to a decline in the probability of tapping into local optima. Moreover, the chaos-based asexual reproduction optimization algorithm is applied to the best solution to further search the area around the best solution. Manuscript profile

Open Access Article

3 - Identification and ranking of factors influencing the attraction of health tourists by hospitals based on the Lassol communication model using the fuzzy TOPSIS technique.
maryam amiri ali mohamad sharifi mazid abadi shahnaz hashemi

Introduction: In the tourism industry, health tourism is a relatively emerging field of knowledge that can create a dynamic multi-disciplinary economic activity by integrating businesses in the fields of medicine, health, tourism and media. For the development of health More

Introduction: In the tourism industry, health tourism is a relatively emerging field of knowledge that can create a dynamic multi-disciplinary economic activity by integrating businesses in the fields of medicine, health, tourism and media. For the development of health tourism, the coordination and cooperation of different organizations and departments is needed, and on the other hand, its promotion and development by the media is of great importance. Method: Although relatively significant and extensive researches have been conducted on the nature of health tourism, but the issue of recognizing the role of modern media in attracting health tourists and using this opportunity by hospitals has been neglected, which is addressed in the present study. Accordingly, in this research, first by studying the subject literature and reviewing the background, 73 related components were identified and classified based on Laswell's communication model. The mentioned list was provided to the experts through a semi-open questionnaire in order to identify and rank the effective factors. Results: The results of the ranking of the options with the TOPSIS fuzzy technique showed that in the audience category, the variables focusing on health tourists from Muslim and neighboring countries are the most important. In the message type category, honesty variables have the highest importance. In the layer of the message transmitter, the variables of the Ministry of Health are the most important. Also, in the category of communication channels, the variables of strong and large content production in different Iranian and foreign sites are of the highest importance. Discussion: One of the most important factors that makes traveling to Iran attractive and choosing it among different destinations is the low cost of traveling to Iran. It should be said that this component is more attractive for the neighbors than for the western tourists. Also, the facilitation of travel is one of the factors that is directly effective in domestic tourism. Considering the level of per capita income and different deciles of income in the country and neighboring countries, it is necessary to provide facilities that all classes can travel, and this is about the neighboring countries. M is true. Among other issues that have a direct impact on travel to Iran from different countries, especially neighboring countries, is the possibility for easy and worry-free financial exchanges with Iran, because due to international sanctions, many incoming tourists Currency inside the country is a problem are faced to the extent that this factor is considered as one of the restrictions of travel to the country. In this regard, both the government and hospitals should look for conditions for easy exchange through various financial instruments. Manuscript profile

Open Access Article

4 - An Online group feature selection algorithm using mutual information
maryam rahmaninia sondos bahadori

Introduction: In the area of big data, the dimension of data in many fields are increasing dramatically. To deal with the high dimensions of training data, online feature selection algorithms are considered as very important issue in data mining. Recently, online featur More

Introduction: In the area of big data, the dimension of data in many fields are increasing dramatically. To deal with the high dimensions of training data, online feature selection algorithms are considered as very important issue in data mining. Recently, online feature selection methods have attracted a lot of attention from researchers. These algorithms deal with the process of selecting important and efficient features and removing redundant features without any pre-knowledge of the set of features. Despite all the progress in this field, there are still many challenges related to these algorithms. Among these challenges, we can mention scalability, minimum size of selected features, sufficient accuracy and execution time. On the other hand, in many real-world applications, features are entered into the dataset in groups and sequentially. Although many online feature selection algorithms have been presented so far, but none of them have been able to find trade of between these criteria. Method: In this paper, we propose a group online feature selection method with feature stream using two new measures of redundancy and relevancy using mutual information theory. Mutual information can compute linear and non-linear dependency between the variables. With the proposed method, we try to create a better tradeoff between all the challenges. Results: In order to show the effectiveness of the proposed online group feature selection method, a number of experiments have been conducted on six large multi-label training data sets named ALLAML, colon, SMK-CAN-187, credit-g, sonar and breast-cancer in different applications and 3 online group feature selection algorithms named FNE_OGSFS، Group-SAOLA and OGSFS which are presented recently. Also, 3 evaluation criteria including average accuracy using KNN (k - nearest neighborhood (, SVM (Support Vector Machine) and NB (Naïve Bayesian) classifiers, number of selected features and executing time were used as criteria for comparing the proposed method. According to the obtained results, the proposed algorithm has obtained better results in almost of cases compared to other algorithms which it shows the efficiency of the proposed method. Discussion: In this paper, we will show that proposed online group feature selection method will achieve better performance by considering label group dependency between the new arrival features. Manuscript profile

Open Access Article

5 - Sampled-Data Flocking of Multi-Agent Systems Under the Cyber-Attack Problem
سحر یزدانی

Introduction: Flocking is a type of collective behavior which is observed in the nature. In the design of a flocking algorithm, it should be ensured connectivity of agents’ network and the collision avoidance, and velocities convergence of agents to that of virtual lead More

Introduction: Flocking is a type of collective behavior which is observed in the nature. In the design of a flocking algorithm, it should be ensured connectivity of agents’ network and the collision avoidance, and velocities convergence of agents to that of virtual leader. In practice due to the limitations in the measurement and control units, it is often impossible to ensure the continuity of information. Thus, the study of the flocking problem under the sampled data frameworks is indispensable. However, to the best of the authors’ knowledge, there are very few works on the sampled-data flocking. On the other hand, in many practical applications, the multi-agent systems are controlled through some communication networks. The transmitted data among agents could be easily exploited by adversaries due to the open network links among sensors, controllers and actuators. Since in practice often the attacks are capable to destroy a number of edges within the network or cause to collide among agents, the study of networked system under the cyber-attacks is very important. In the cyber-attacks, successful but recoverable attacks have attracted more attention. Successful attacks refer to a class of attacks by which the network is broken dow n into a group of isolated clusters. Recoverable attacks refer to a class of attacks that the network can recover from after a period of time. In this paper, we study the sampled-data flocking of multi-agent systems under the successful but recoverable network attacks. Method: Here, defining a new discrete-time energy function we prove the asymptotic velocity convergence of agents to the velocity of virtual leader. Then, through the upper bound of the energy function, we find an upper bound for the sampling period such that the connectivity of network is preserved and collision is avoided, and also, the velocity convergence is ensured. After that, we modify the algorithm for application in cyber-attacks. Results: We show that under our proposed sampled-data algorithm, no link is lost from initial network, no collision is occurred among agents, and the velocity convergence of agents to that of virtual leader is ensured. Also, demonstrate the proposed algorithm is applicable for the flocking under the attack problem. Manuscript profile

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