Journal of Optimization in Soft Computing
Volume:1 Issue: 1, Autumn 2023

With the development of information technology, electronic health (e-health) systems are used as a common approach to recording patients' medical data. Given that medical information is an essential asset of individuals and the health system, there are severe concerns about secure sharing and preserving this information's privacy. In this paper, we propose a new identity-based encryption (IBE) method by bilinear pairings to ensure the confidentiality of patients' data and their privacy in cloud health systems; in this way, this plan also provides authentication for users using challenge-response mechanisms. In addition, the proposed scheme, using blockchain techniques, ensures integrity and precise access control for shared data. The correctness of the proposed protocol is verified, and its security is formally proven in the standard model. The implementation of our scheme is performed in Java, and the results show that the proposed scheme reduces the computational overhead compared to previous similar methods.

Wireless sensor networks (WSNs) are the safest and most widely used existing networks, which are used for monitoring and controlling the environment and obtaining environmental information in order to make appropriate decisions in different environments. One of the very important features of wireless sensor networks is their lifetime. Two important factors come to mind to increase the lifetime of networks: These factors are maintaining the coverage of the network and reducing the energy consumption of sensor nodes simultaneously with the uniform consumption of energy by all of them. Clustering, as the optimal method of data collection, is used to reduce energy consumption and maintain the coverage of the network in wireless sensor networks. In clustered networks, each node transmits acquired data to the cluster head to which it belongs. After a cluster head collects all the data from all member nodes, it transmits the data to the base station (sink). Given that fuzzy logic is a good alternative for complex mathematical systems, in this study, a fuzzy logic-based trust model uses the clustering method in wireless sensor networks. In this way, cluster-head sensors are elected from among sensors with high reliability with the help of fuzzy rules. As a result, the best and most trusted sensors will be selected as the cluster heads. The simulation results in MATLAB software show that in this way, in comparison with K-Means, FCM, subtractive clustering, and multi-objective fuzzy clustering protocols, the energy consumption in clustered nodes will decrease and the network’s lifetime will increase.

Medical image registration plays an important role in many clinical applications, including the detection and diagnosis of diseases, planning of therapy, guidance of interventions. Multimodal medical image registration is the process of overlapping two or more images taken from the same scene by different modalities and different sensors. Intensity-based methods are widely used in multimodal medical image registration, these techniques register different modality images that have the same content by optimal transformation. The estimation of the optimal transformation requires the optimization of a similarity metric between the images. Recently, various optimization algorithms have been presented that the selection of appropriate optimization algorithms is very important in determining the optimal transformation parameter. The Social Spider Optimization (SSO) algorithm is one of the meta-heuristic methods that prevents premature convergence. In this paper, medical image registration technique is suggested based on the SSO algorithm. The Mutual Information (MI), Normalization of Mutual Information (NMI), and Sum of Squared Differences (SSD) are used separately as cost function (objective function) and the performance of each of these functions is checked in multimodal medical image registration. The simulation results on Brain Web data set affirm the suggested method outperforms classical registration methods in terms of convergence rate, execution time.

  Among variable speed wind turbines the use of doubly-fed induction generator based wind turbines are very common. However, due to their stator direct connection to the grid, they are very sensitive to grid faults. This paper analyzes the low voltage ride-through (LVRT) capability enhancement under the three-phase balanced grid fault. Therefore the variations of 5 parameters during balanced grid fault are Analyzed. These parameters are stator voltage, rotor current, stator current, rotor speed, and the DC link voltage. To improve the LVRT capability an enhanced demagnetization control method is proposed. This method shortens the natural stator current time constant and approximately immunes the system against parameter variations as shown in simulation results. To show the effectiveness of the proposed method, the results are compared with one of the best previous demagnetization control methods.

In this article, we will examine the problems related to routing and positioning with real variables and examine the related questions. These engineering, inventory and optimization decisions are made in a multi-layered supply chain system, including suppliers, warehouses and different buyers. We are looking for new ways to manage location and routing efficiently and effectively. In order to increase efficiency and achieve optimal results, exploratory and meta-heuristic methods have been used. In meta-heuristic techniques, a combination technique is usually used to increase performance. Therefore, this review article examines meta-heuristic methods and analysis of location problems using different quantities. It also examines the advantages and disadvantages of each method to optimally solve these problems in order to introduce practical and efficient methods