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The increasing availability of texts generated in many aria and online information has necessitated intensive research in the area of automatic text coherence identification within the Natural Language Processing (NLP) community. Over the past two decades, the problem has been addressed from many different perspectives, in varying domains and using various paradigms such as text summarization, text...
One of the main aims of molecular biology is to understand regulatory relationships between the cellular components. Most of the methods developed to extract gene regulatory relationship from time-delayed gene expression data are not sensitive to non-linearity and non-monotonicity of the cellular system. Here we present four various time-lagged correlation methods including Pearson, Spearman, Kendall...
Ad-hoc networks consist of collections of wireless mobile nodes. Due to mobility, there exists frequent link breakage, packet loss, and need for route discovery. OLSR is proactive routing protocol that is developed for mobile ad-hoc networks. OLSR reduces the network traffic by flooding control packets efficiently and reducing unnecessary and redundant control packets. OLSR reduces the overhead of...
As the number of researcher increases, the amount of information related to research activities grows rapidly. As a result, the management of this information for better retrieval and analysis has become an important issue. Many data models abroad and within Iran have been developed to address this issue. In this paper, after comparing some of these models, a new ontology based data model is proposed...
Proper recognition of microscopic sperm cells in video images is an important step in diagnosis and treatment of male infertility. The small sizes of the sperm cells make their segmentation and detection an important stage in the microscopic images analysis. Histogram-based thresholding schemes are one of the common approaches for this purpose. This paper proposes a non-linear amplitude compression...
This paper presents an approach to a closed-class authorship attribution (AA) problem. It is based on language modeling for classification and called modified language modeling. Modified language modeling aims to offer a solution for AA problem by Combinations of both bigram words weighting and Unigram words weighting. It makes the relation between unseen text and training documents clearer with giving...
The study of embedded structure of communities in social and information networks is an extensive studies in this domain and vast variety of community detection methods have been proposed. In this paper we proposed a distributed approach for local and overlapping community detection based on the game theory. In our method, each node is a player and there is an iterative cycle in which players can...
Human recognition through walking styles is among the newest of biometric methods. By using this biometric, individuals can be identified, distantly, even at low visibility. Our aim is to provide such ability for a computer system. In other words, we intend to extract appropriate features through processing video images that can reflect individuals' identity. In order to set up such a system, we have...
Nowadays, cryptography is one of the common security mechanisms. Cryptography algorithms are used to make secure data transmission over unsecured networks. Vital applications are required to techniques that encrypt/decrypt big data at the appropriate time, because the data should be encrypted/decrypted are variable size and usually the size of them is large. In this paper, for the mentioned requirements,...
In this paper a method for multiple human detection in the image has been presented. This method uses differential evolution (DE) algorithm to improve window position detection speed and HOG-LBP algorithm for feature extraction. Fitness function for DE algorithm is SVM and in the final state, a postprocessing on detected windows by DE algorithm is performed. This method has been tested on INRIA datasets...
M-commerce has gained so much attention in recent years. M-commerce was originally coined in 1997 by Kevin Duffey at the launch of the Global Mobile Commerce Forum to mean “delivery of electronic commerce capabilities directly into the customer's hand, anywhere, via wireless technology”. This portable form of commerce is of so much benefit for the stakeholders including the organizations and end-users...
One of the most important challenges in social network models is dissimilarity of proposed models with real networks. In this article we proposed a new small world model generator based on binary trees that simulate family and human ties. In reality family such as father, children, and grandchildren makes a path between grandfather and grandchildren. We used this property to adopt effective parameters...
Consistency is one of the key challenges in replicated distributed systems (DSs). Data centric and client centric are two main categories of consistency models. Monotonic read (MR) is one of the client centric consistency models that guarantees consistency from view point of a single client in terms of access to replicated data store. This consistency model guarantees that when a process reads a value...
Super-peer network is a type of peer-to-peer networks. In a super-peer network, a super-peer is a peer that has more ability than other peers have and is responsible for some of the tasks of network management. Since different peers vary in terms of capability, selecting a super-peer is a challenge problem. Gradient topology is a type of super-peer networks. Because of dynamicity of peers, adaptive...
Technological developments alongside VLSI achievements enable mobile devices to be equipped with multiple radio interfaces which is known as multihoming. On the other hand, the combination of various wireless access technologies, known as Next Generation Wireless Networks (NGWNs) has been introduced to provide continuous connection to mobile devices in any time and location. Cognitive radio networks...
Workflows are visualized in different ways. In most cases real workflows deviates from hand-made models and they can be plotted as a graphical diagram. Displaying Graphical diagrams with large amounts of data is difficult; because we are limited to two-dimensional computer screens or papers. In some cases it is essential to transform workflows to reduced ones, especially with reducing visualization...
Recently Recurrent Neural Networks (RNNs) have shown impressive performance in sequence classification tasks. In this paper we apply Long Short-Term Memory (LSTM) network on Persian phoneme recognition. For years Hidden Markov Model (HMM) was the dominant technique in speech recognition system but after introducing LSTM, RNNs outperformed HHM-based methods. We apply LSTM and deep LSTM on FARSDAT speech...
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