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Bidirectional model transformations (Bx) are considered as one of the cornerstones of model-driven engineering paradigm. Bx re-establishes the consistency between the source and target models, when they are evolved independently. Recently, a large number of approaches for Bx are proposed, each with different capabilities and characteristics. Among them is a novel Bx approach, called EVL+trace, which...
In recent years, social networks developed in terms of diversities, capabilities and users. Therefore, researchers in different fields have been attracted to these kind of networks. Trust management between users in these kind of networks is one of the most important research topics. In this article a new model for evaluating trust between users in social networks based on subjective logic is presented...
Microscopic images of blood are very important among the various medical images. One of the most important applications is to diagnosis blood disorders and its types like blood cancer. The main issue to diagnosis blood cancers is white blood globule either mature or not. There are many problem during using image processing to investigate white blood Cell can be mentioned as non-uniformity of colors,...
Clustering is a powerful approach for data analysis and its aim is to group objects based on their similarities. Density peaks clustering is a recently introduced clustering method with the advantages of doesn't need any predefined parameters and neither any iterative process. In this paper, a novel density peaks clustering method called IDPC is proposed. The proposed method consists of two major...
Crowdsourcing allows us to utilize non-expert annotators in learning concept instead of using reference model. In machine learning domain, there are many papers which addressed this problem by assuming independency between annotators. While this assumption does not hold in real world's problems. In this paper we propose a hierarchical framework to model dependency between annotators. This cooperation...
Implementing an automatic algorithm for classification of retinal vessel landmarks as bifurcation and crossovers will help the experts to analyze retinal images and detect the abnormalities of vascular topology in less time. It also can be used as the initial step of an automatic vessel classification system which is worthwhile in automatic screening programs. In this paper, we proposed a graph based...
In this paper a cordic based Application-Specific Instruction-set Processor(ASIP) for Two dimensional Discrete Fourier Transform(DFT) and Discrete Cosine Transform(DCT) is proposed. Today, DFT performs an important role in digital signal processing, and DCT algorithm is suitable for image compression applications. Using cordic method inside these two signal processing algorithms reduces the number...
Biometrics can provide more privacy and reliability to recognize a person, based on physiological information or bio-signals of him which is specific and inherent of that person and cannot be disguised by other individuals. Photoplethysmogram (PPG) is often considered as one of the non-invasive easy to access bio-signals of human being that is replete with information about cardiac activity, respiration,...
Cloud computing is a new way to address a wide range of resource needs. Cloud environment provides a framework for dynamic and saleable use of services. It provides access to computing and data storage resources on a pay per usage model. Although there are many known advantages for cloud, security is still one of its most challenging issues. Intrusion detection systems are a common security tool which...
One of the most common disorders in children with cleft palate is hypernasality that survives also after operation. To solve this problem, it is required to set many speech therapy sessions. Therefore, assessment of hypernasality is fundamental for speech therapists and could be done either by a nasometer equipment or an expert speech therapist. Recently speech processing methods are introduced as...
One of the main challenges in Grid systems is designing an adaptive, scalable, and model-independent method for job scheduling to achieve a desirable degree of load balancing and system efficiency. Centralized job scheduling methods have some drawbacks, such as single point of failure and lack of scalability. Moreover, decentralized methods require a coordination mechanism with limited communications...
Recently, new Fuzzy Decision Tree (FDT) approaches have been developed for doing classification tasks. In this paper, one of these FDTs is adapted for performing the imbalanced classification tasks. First, our proposed method utilizes k-means algorithm to cluster the majority class samples into some clusters. Then, each cluster is labeled as a new class and thereby the binary imbalanced classification...
The present paper proposes an unsupervised feature learning method for POLSAR image classification. The proposed method includes two steps. In these two steps, features are created and learned from scratch. The first is to learn dictionaries and encode features using scatter matrices. The dictionary is learned using a set of vectors that are known as hierarchical matching pursuit (HMP). The dictionary...
Computer networks consist of several assets such as hardware, software, and data sources. These assets have often some vulnerabilities which can be exploited by attackers that violate security policies in the network. Considering the limited budget, the network administrator should analyze and prioritize these vulnerabilities to be able to efficiently protect a network by mitigating the most risky...
Understanding software behavior by analyzing its execution traces is an important enabler for many software engineering tasks. In Model-Driven Development (MDD), dynamic analysis methods are often used to analyze executable models to enable the understanding of software behavior in early stages of the development process. An execution trace of a model can provide information to help reason about executable...
Many machine learning problems such as speech recognition, gesture recognition, and handwriting recognition are concerned with simultaneous segmentation and labeling of sequence data. Latent-dynamic conditional random field (LDCRF) is a well-known discriminative method that has been successfully used for this task. However, LDCRF can only be trained with pre-segmented data sequences in which the label...
As Voice over Internet Protocol (VoIP) or internet telephony became so popular, it has faced more security threats in comparison with traditional Public Switched Telephone Network (PSTN). Using IP-based infrastructures like public internet and signaling protocols such as Session Initiation Protocol (SIP), have been subjected this technology to various kinds of attacks. Denial of Service (DoS) attack,...
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