Sharif Digital Repository

Network survivability is one of the main design challenges in wireless sensor networks (WSN). Survivability is the ability of the network to provide essential services in the presence of attacks and/or failures, and recover full service in a timely manner. To the best knowledge of us, survivability for WSN has never been studied considering failure effects on network. We consider the network survivability as a composite measure consisting of both network failure duration and failure impact on the network. In this paper we model network survivability in steady state. In this state, network is affected by predicted failures. This modeling is based on network connectivity and coverage, when an... 

In this paper we introduce a preprocessing method to reduce noise effects in noise prone environments. Prototype based clustering algorithms are sensitive to noise because the effect of noisy data are as same as effect of true data and this affects on calculation of clusters center and then reduces accuracy. Therefore, these algorithms can not be applied in noise-prone environments and if this is applied there, we can not trust to the results. To overcome such problems we reduce and in some cases eliminate the noisy data. Also a part of our method is applied on the source of generated data in a network. Then noisy data that the number of them is high in noisy environments are eliminated and... 

Support vector machines (SVMs) were used as a novel learning machine in the authentication of the origin of salmon. SVMs have the advantage of relying on a well-developed theory and have already proved to be successful in a number of practical applications. This paper provides a new and effective method for the discrimination between wild and farm salmon and eliminates the possibility of fraud through misrepresentation of the country of origin of salmon. The method requires a very simple sample preparation of the fish oils extracted from the white muscle of salmon samples. 1H NMR spectroscopic analysis provides data that is very informative for analysing the fatty acid constituents of the... 

To the best knowledge of us, survivability for WSN has never been studied considering failure affects on network. We perceive the network survivability as a composite measure consisting of both network failure duration and failure impact on the network. In this paper we will study network survivability in unstably state: in this state, network is affected by the failures that occur temporarily and instantly also may occur several times. In other words, the main characteristics of these failures are their frequency and being temporary. In this paper we will propose a survivability model for network in unstable state that is based on network availability. This availability model, presents... 

Most of clustered models in wireless sensor networks use a double-layered structure. In these structures a node is considered as cluster-head and has the responsibility of gathering information of environment. Static attribute is the main disadvantage of these clustering method. because as traffic rises in environment as time passes, cluster-head nodes energy and its close nodes, is consumed rapidly and so these nodes that has important role in data gathering, are break down. This issue is considered as age decrease in network life time and finally, network death. In this paper, a new three-layered dynamic model is introduced that its main goal is to increase network life time. The dynamic... 

The learning vector quantization (LVQ) neural network is a useful tool for pattern recognition. Based on the network weights obtained from the training set, prediction can be made for the unknown objects. In this paper, discrimination of wines based on 2D NMR spectra is performed using LVQ neural networks with orthogonal signal correction (OSC). OSC has been proposed as a data preprocessing method that removes from X information not correlated to Y. Moreover, the partial least squares discriminant analysis (PLS-DA) method has also been used to treat the same data set. It has been found that the OSC-LVQ neural networks method gives slightly better prediction results than OSC-PLS-DA © 2005... 

Learning a foreign language encompasses a process of trial and error that can lead to the progression of the learner's interlanguage, meaning that the learners make use of their language knowledge that receives feedback and brings about progress through diagnosis of the problems and being corrected by the teacher. Therefore, there exists a need to analyze the underlying reasons causing the students to remain taciturn with a low willingness to communicate (WTC) during a language class. There has been much work done investigating the role of the learner's stable personal characteristics (traits) along with their situational changes at a specific time (states) that influence the student's... 

Accurate system identification (SI) is essential for flight controller design of unmanned aerial vehicles and microaerial vehicles (MAVs). SI can be performed either in frequency or time domain using flight test data. As flight testing is often costly and may even lead to catastrophic events before some flight stability analysis is at hand, a low-cost 5 degree-of-freedom free motion platform (FMP) is designed and used for initial identification of MAVs via wind tunnel testing. A typical MAV is constructed as a test case and equipped with inertial sensors for testing and validation purposes. The proposed FMP allows for both rotational as well as translational motions that in turn provide for... 

Using 3-D scanned data to analyze and extract pore network plays a vital role in investigation of porous media's characteristics. In this paper, a new simple method is developed to detect pores and throats for analyzing the connectivity and permeability of the network. This automated method utilizes some of the common and well-known image processing functions which are widely accessible by researchers and this has led to an easy algorithm implementation. In this method, after polishing and quality control of images, using city-block distance function and watershed segmentation algorithm, pores and throats are detected and 3-D network is produced. This method can also be applied on 2-D images... 

In this paper, we try to recognize and distinguish different groups of arrhythmia using novel features which have been obtained from the heart rate's phase space in recent years. For this purpose, we used Triangular Phase Space Mapping (TPSM) and Parabolic Phase Space Mapping (PPSM). For recognition, we used three groups of 15 subjects using the Physionet database (Arrhythmia, Congestive Heart Failure (CHF), and Atrial Fibrillation (AF)) with Normal Sinus Rhythm (NSR). The obtained features discriminate arrhythmia from NSR by p