Sharif Digital Repository

Fused Deposition Modeling with Polypropylene filament was employed to make a lap joint between Polypropylene and pre-punched Al-Mg alloy sheets, in the form of bonds between the polymeric substrate and the additive part and mechanical lock between the additive part and aluminum base sheet. Effects of the joint interface area (hole diameter of 5–13 mm) and preheating of the substrates (room temperature, 50 and 90℃) were investigated on the mechanical properties of the joints. Peak load in the tensile-shear and cross-tension tests increased with enhancement of the joint interface area (up to ˜280 N and ˜160 N, respectively). Higher joint strength in the tensile-shear test compared to the... 

In today's competitive world, having an effective business intelligent (BI) system for monitoring and evaluation of industrial and product oriented organizations is vital. A perfect BI must help managers not only to speed up his decision making process; but also to increase quality of their decision. But how? One of the main specifications of an effective BI system is providing managers by correct format of information and at the correct time. Critical Success Factors (CSFs) are a kind of significant factors that must be considered in attaining an organization's goal; and key performance indicators (KPIs) are a type of quantitative and measurable CSF; and one character of an effective BI is... 

In the past few years, Iranian universities have embarked to use e-learning tools and technologies to extend and improve their educational services. After a few years of conducting e-learning programs a debate took place within the executives and managers of the e-learning institutes concerning which activities are of the most influence on the learning progress of online students. This research is aimed to investigate the impact of a number of e-learning activities on the students' learning development. The results show that participation in virtual classroom sessions has the most substantial impact on the students' final grades. This paper presents the process of applying data mining... 

The diffusion phenomenon has a remarkable impact on Online Social Networks (OSNs). Gathering diffusion data over these large networks encounters many challenges which can be alleviated by adopting a suitable sampling approach. The contributions of this paper is twofold. First we study the sampling approaches over diffusion networks, and for the first time, classify these approaches into two categories, (1) Structure-based Sampling (SBS), and (2) Diffusion-based Sampling (DBS). The dependency of the former approach to topological features of the network, and unavailability of real diffusion paths in the latter, converts the problem of choosing an appropriate sampling approach to a trade-off.... 

Al6063 powder was subjected to severe plastic deformation via high-energy mechanical milling to prepare ultrafine-grained (UFG) aluminium alloy. Uniaxial compression test at various temperatures between 300 and 450 °C and strain rates between 0.01 and 1 s-1 was carried out to evaluate hot workability of the material. Microstructural studies were performed by EBSD and TEM. The average activation energy and strain rate sensitivity of the hot deformation process were determined to be 280 kJ mol-1 and 0.05, respectively. The deformation temperature and applied strain rate significantly affected the grain structure of UFG Al alloy. A finer grain structure was obtained at lower temperatures and... 

The charge ratio of cosmic muons has important information in both "the atmospheric neutrinos anomaly" and "the hadronic interactions". We measured the muon charge ratio (Rμ = N μ+/Nμ-) in the cosmic rays flux at the momenta range 0.76-1.60 GeV/c at Sharif University of Technology in Tehran (35°43′N, 51°20′E) and 1200 m above sea level (890 gcm -2) by using a cosmic ray telescope. We used the delayed coincidence method based on reduced mean life time of negative muon due to nuclear capture in matter. By finding Rμ in different time intervals, we indicated 3 week time interval is proper to obtain Rμ and in this time interval, Rμ = 1.18±0.03. So we compared the experimental data to predictions... 

There are many works on annealing process of SPDed bulk metals but there are limited works on annealing process of SPDed sheets. Therefore, in this study the annealing response after constrained groove pressing (CGP) of low carbon steel sheets has been investigated. These sheets are subjected to severe plastic deformation at room temperature by CGP method up to three passes. Nano-structured low carbon steel sheets produced by severe plastic deformation are annealed at temperature range of 100 to 600 °C for 20 min. The microstructural changes after deformation and annealing are studied by optical microscopy. The effects of CGP strain and annealing temperature on microstructure, strength and... 

In order to be more precise to find primary cosmic particles directions, nowadays detectors and data analysis for studying secondary particles in extensive air showers have an ongoing progress and water Cherenkov detector is considered as a secondary particle detector. Our aim in this paper is to optimize the size and the inner surface characteristic of a cylindrical water Cherenkov tank with one PMT. By comparing simulation outputs with experiments results, we show that the diffusing inner surface is more practical than the reflective inner surface and we conclude that the optimum height for a diffusing tank with a diameter of 45cm is 60cm  

Crack detection by Piezoelectric Wafer Active Sensors (PWAS) is one of the emerging methods of Non-destructive Evaluation (NDE). These sensors can assess the health state of the structure in far filed through the analyzing the high frequency Lamb wave propagation. As PWAS is the essential part of this method, simulation and modeling of these sensors and their interaction with the host structure, strongly affect the accuracy of results. In this study, unlike the previous works, in which some certain areas of the host structure were considered as a sensor and actuator, the direct simulation of electro-mechanical interaction of the PWAS and the host structure is modeled among modeling the PWAS... 

Data stream clustering has attracted a huge attention in recent years. Many one-pass and evolving algorithms have been developed in this field but feature selection and its influence on clustering solution has not been addressed by these algorithms. In this paper we explain a feature-based clustering method for streaming data. Our method establishes a ranking between features based on their appropriateness in terms of clustering compactness and separateness. Then, it uses an automatic algorithm to identify unimportant features and remove them from feature set. These two steps take place continuously during lifetime of clustering task. © 2009 IEEE  

Many real-world systems and applications such as World Wide Web, and social interactions can be modeled as networks of interacting nodes. However, in many cases, one encounters the situation where the pattern of the node-to-node interactions (i.e., edges) or the structure of a network is unknown. We address this issue by studying the Network Reconstruction Problem: Given a network with missing edges, how is it possible to uncover the network structure based on certain observable quantities extracted from partial measurements? We propose a novel framework called CS-NetRec based on a newly emerged paradigm in sparse signal recovery called Compressive Sensing (CS). The results demonstrate that... 

Introducing a suitable model for a structure to understand its behavior under different conditions of loading is very important. Mathematical modeling is the simulation of a physical structure or physical process by means of suitable analytical or numerical construct. One of suitable methods for finding deflection of a beam under different forms of loading is Finite Element Method (FEM). In this paper we find deflection of a beam using FEM based on Euler-Bernoulli and Timoshenko theory. © 2009 IEEE  

A new scenario for simultaneously generating a secret key and two private keys among three Terminals in the presence of an external eavesdropper is considered. Terminals 1, 2 and 3 intend to share a common secret key concealed from the external eavesdropper (Terminal 4) and simultaneously, each of Terminals 1 and 2 intends to share a private key with Terminal 3 while keeping it concealed from each other and from Terminal 4. All four Terminals observe i.i.d. outputs of correlated sources and there is a public channel from Terminal 3 to Terminals 1 and 2. An inner bound of the secret key-private keys capacity region is derived and the single letter capacity regions are obtained for some... 

In this paper, we introduce a new version of the shortest path problem appeared in many applications. In this problem, there is a start point s, an end point t, an ordered sequence =(S0 = s, S1,...,S k, Sk+1 = t) of sets of polygons, and an ordered sequence =(F0,...,Fk) of simple polygons named fences in such that each fence Fi contains polygons of Si and Si+1. The goal is to find a path of minimum possible length from s to t which orderly touches the sets of polygons of in at least one point supporting the fences constraints. This is the general version of the previously answered Touring Polygons Problem (TPP). We prove that this problem is NP-Hard and propose a precision sensitive FPTAS... 

Treebanks are not large enough to reliably model precise lexical phenomena. This deficiency provokes attachment errors in the parsers trained on such data. We propose in this paper to compute lexical affinities, on large corpora, for specific lexico-syntactic configurations that are hard to disambiguate and introduce the new information in a parser. Experiments on the French Treebank showed a relative decrease of the error rate of 7.1% Labeled Accuracy Score yielding the best parsing results on this treebank  

This paper introduces an incremental local learning algorithm inspired by learning in neurobiological systems. This algorithm has no training phase and learns the world during operation, in a lifetime manner. It is a semi-supervised algorithm which combines soft competitive learning in input space and linear regression with recursive update in output space. This method is also robust to negative interference and compromises bias-variance dilemma. These qualities make the learning method a good nonlinear function approximator having possible applications in neuro-robotic systems. Some simulations illustrate the effectiveness of the proposed algorithm in function approximation, time-series... 

Many real-time systems are in fact isochronal, where both early and late responses are harmful to the system or lead to lower quality of service. Real-time task scheduling problems proved that are NP-hard problems. Therefore, it is necessary to apply a heuristic search strategy on these problems. In this paper, a multi-objective genetic algorithm is proposed for static task scheduling in non-overloaded isochronal soft real-time systems. Its objective is to maximize the total utility of jobs. Simulation results indicate that genetic algorithm could be a suitable heuristic search strategy for task scheduling in isochronal soft real-time systems. © 2009 IEEE  

In this study, clustering based method for activation detection in functional magnetic resonance imaging (fMRI) is employed. Moreover, some features are obtained by fitting two models namely FIR filter and Gamma function, to hemodynamic response function (HRF). After applying clustering methods (that require number of clusters as an input) to feature space, our simulations show that number of clusters can affect activation detection significantly. Therefore a newly proposed clustering algorithm namely evolving neural gas (ENG) that gives optimal number of clusters is exploited. In addition to ENG, the result of four clustering algorithms namely k-means, fuzzy C-means, neural gas, and clara... 

In this study the properties of muscle synergies, arising from optimal feedback control are investigated. Three different tasks namely reaching, via-point, and hitting are performed using optimization of corresponding cost functions. Then by applying non-negative matrix factorization method to a dataset of muscle tensions, synchronous muscle synergies are obtained. In this way, different muscle patterns can be generated by linear combination of these basis vectors with non-negative time-varying scaling coefficients. According to our simulations some of obtained muscle synergies are shared between tasks and some of them are specific for one task. This finding is also in agreement with the... 

The assessment of the hypnotic state of the brain is crucial to the process of an operation under general anaesthesia. A noninvasive method of quantifying depth of anaesthesia is through analysis of electroencephalogram (EEG). Among number of works done in the field, no single algorithm has been found exhibiting a precise measure in all of the hypnotic states. One can categorise algorithms as either a state-quantifier or a trend measure. State-quantifier algorithms can discriminate between different hypnotic states such as awake, light sedation, deep anaesthesia, etc. On the other hand, trend measure algorithms are employed to specify the short-term changes in hypnotic brain conditions,...