نشریه مهندسی برق و مهندسی کامپیوتر ایران
سال هفدهم شماره 1 (پیاپی 50، بهار 1398)

Today, the continuous changes in customer requirements are the main challenges faced by enterprises. Service-oriented architecture is considered as a practical solution to solve this problem for service-oriented enterprises. In the service-oriented architecture, selection and composition of services to quickly respond to complex customer requirements is available to service-oriented enterprises. Enterprises use ready-to-use and outsourced services to respond more quickly to the complex and changing needs of customers. One of the emerging technologies in this area is web services. By expanding the desire of enterprises to use web services, overtime web services providers increased. For this reason, Web services with the same functionality and different qualities were expanded. Therefore, the issue of choosing a web service with the best quality for enterprises is important. On the other hand, enterprises with only one web service cannot meet the complex requirements of customers; therefore, they need to composite multiple web services together. In addition, with the increase of web services with different functions, correlation, dependency and conflict between Web services also expand in their composition. But so far, there is no way to choose the best web services based on the quality of service(QoS) and also their composition does not violate the dependency, conflict and correlation between web services. In this paper, we try to make use of previous methods that consider dependency or conflict or correlation in simple modes of web services composition. We will improve all these methods in a comprehensive approach and support complex situations that may arise from the composition of web services and find the suitable composite web service by considering dependency, conflict, and correlation between Web services.

The detection of outliers is a task in data mining and machine learning and it’s an important step in data preprocessing. In this paper, in order to detect proximity-based outliers, a non-parametric method is proposed called NPOD. The proposed method is a combination of distance-based and density-based methods and has the ability to detect outliers in both local and global scenarios. This method does not require to determine any parameters of neighborhood radius, the threshold of existing points in the neighborhood radius, and the nearest neighbor parameters. In order to detect outliers, a new method of scoring is presented. Experimental results on the UCI datasets show that this algorithm, in spite of being non-parametric, has comparable results with previous methods. Also in some cases, it has the best performance.

Image annotation systems are responsible for describing the content of the images by assigning tags to them. The purpose of this research is to improve the accuracy and speed of image annotation system. Recently, with the growing of images, the image annotation process is based on the basics of images instead of themselves. One of these new methods is the implementation of the non-negative matrix algorithm (NMF) on the features of the images. In the proposed method, for the first time, in order to increase the speed and efficiency of the7 system, we use a method that called the block principal pivoting for the NMF solution. This method has ability to add online new class of data to its knowledge and knowledge learning in a compact form. Moreover, the ability to train based on received data without having to be re-processed. In the training phase, the matrix of the coefficients and the base of the input images are obtained using the Block Principal Pivoting method. Then, at the test phase for the input image, by extracted features of the image and the coefficients obtained from the training phase, the coefficient of belonging to the test image is calculated to each of the classes of training images. Then, this coefficient while searching among the teaching images for assigning the label to test image increases the accuracy of the algorithm. This search is done by the KNN method on the base of the images. To test the proposed method, we used two databases Corel5K and real animal data (derived from 500px) and, finally, compared with existing methods, which we found in the Corel5K database at a precision of 50.20 and real data was 62.89. Precision have been increased considerably.

In one-way quantum computation model (1WQC), the quantum correlations in an entangled state, called a cluster state or graph state, are used to perform universal quantum computations using single-qubit measurements. In 1WQC, the computations are shown by measurement patterns or simply patterns. The synthesis problem in the 1WQC model is defined as extracting the pattern from a given arbitrary unitary matrix. The important criteria in evaluating measurement patterns in the 1WQC model, are the size, the depth and the number of entanglements of the pattern. In this paper, a new approach is proposed to synthesize controlled-unitary U gates where U is a single-qubit gate. To this end, for the first time, the idea of applying the extended measurement calculus, which utilizes the measurements in different Bloch sphere planes, is used in the synthesis of the 1WQC model. Some optimizations are proposed for this method and a new approach is presented to synthesize controlled-U gates for the 1WQC model which improves the evaluation criteria of size, depth and the number of entanglements in this model as compared to the best previous result by 9.1%, 30% and 18.1%, respectively.

Wireless sensor networks (WSNs) are one of the useful and attractive technologies that have received much attention in recent years. These networks have been used in a variety of applications, due to their ease of use and inexpensive deployment. Due to the criticality of most applications of these networks, security is considered as one of the essential parameters of the quality of service (QoS), and thus Intrusion Detection System (IDS) is considered as a fundamental requirement for security in these networks. This paper provides a trust-based IDS to protect the WSN against all network layer and routing attacks based on the features extracted from them. Through simulations, the proposed IDS has been evaluated with all performance criteria. The results show that the proposed IDS, in comparison with existing works, which often focuses on a specific attack, covers all network layer and routing attacks in WSNs, and also, due to high detection accuracy, low false alarms rate, and low energy consumption is considered as a desirable and lightweight IDS for WSNs.

In this paper, a new method of identity-based encryption is first presented, and it is shown that there is less computational overhead than previous methods. In this regard, the proposed identity-based encryption method is simulated, and the results are compared with the superior representatives of the identity-based encryption. Then, a cloud-based electronic health system (EHS) is proposed using the re-encryption proxy and the identity-based encryption method presented in this paper. In addition to providing confidentiality and enhancing accessibility, the system has a lower running time in the phases of setup, private key generation, encryption, re-encryption key generation, and decryption — this resulting in lower costs and overhead of the cryptographic process in the Electronics health system.

Since the advent of cryptographic chips, the side channel attacks have become a serious threat to cryptographic algorithms and security systems. The side channel attacks use weaknesses in the chip implementation instead of using the computational weaknesses of the algorithms. The scan chain that is widely used in the chip test is one of these side channels. To avoid an attack using a scan chain, one can remove the scan chain after the construction test, but this method makes it impossible to test the post-construction and updating the circuit. Therefore, in addition to preserving the testability of the scan chain, it is necessary to look for a method to prevent the side channel attacks. In this article, a method is proposed to identify the attacker and prevent his scan-based attacks. In this way, by the user authorization, the corresponding output will be generated and the attacker's access to sensitive information is prevented. The proposed method, with an area overhead of less than 1%, power overhead around 1% and a negligible delay overhead retains testability and can prevent differential and signature-based scan attacks better than previous state-of-the-art techniques.

Path planning of mobile robot is one of the most important topics in mobile robotic discussion. The aim of this study is to find a continuous path from an initial position to the final target; So that, it should be free of collision and optimal or near to optimal. Since path planning problem of robot is one type of optimization problems, the evolutionary algorithms can be used to solve this problem. Nowadays, clonal selection algorithm is frequently used to solve the problems because of having valuable computational characteristics. But very little attempts have been done in the field of using this method to solve robot path planning problem. Few accomplished attempts are actually a kind of improved genetic algorithm. In this research, an efficient method for robot path planning in the presence of obstacles is designed using all the features of the clonal selection algorithm. The proposed method is evaluated in various environments with different runs in terms of the proposed path length criteria and the number of generations needed to generate the path. Based on the results of experiments, the proposed method shows better performance than the genetic algorithm in all environments and all the evaluation parameters. Especially, by increasing the number of obstacles vertices and also concave obstacles, the proposed method shows much more efficient performance than the genetic algorithm. Also, comparing the performance of the proposed method with the BPSO algorithm (presented in another study) indicates the superiority of path planning algorithm based on the clonal selection.