Sharif Digital Repository

Concept drift, change in the underlying distribution that data points come from, is an inevitable phenomenon in data streams. Due to increase in the number of data streams' applications such as network intrusion detection, weather forecasting, and detection of unconventional behavior in financial transactions; numerous researches have recently been conducted in the area of concept drift detection. An ideal method for concept drift detection should be able to rapidly and correctly identify changes in the underlying distribution of data points and adapt its model as quickly as possible while the memory and processing time is limited. In this paper, we propose a novel explicit method based on... 

Data stream classification is one of the most challenging areas in the machine learning. In this paper, we focus on three major challenges namely infinite length, concept-drift and concept-evolution. Infinite length causes the inability to store all instances. Concept-drift is the change in the underlying concept and occurs in almost every data stream. Concept-evolution, in fact, is the arrival of novel classes and is an undeniable phenomenon in most real world data streams. There are lots of researches about data stream classification, but most of them focus on the first two challenges and ignore the last one. In this paper, we propose new method based on ensembles whose classifiers use... 

We have entered the era of networked communications where concepts such as big data and social networks are emerging. The explosion and profusion of available data in a broad range of application domains cause data streams to become an inevitable part of the most real-world applications. In the classification of data streams, there are four major challenges: infinite length, concept drift, recurring and evolving concepts. This paper proposes a novel method to address the mentioned challenges with a focus on the last one. Unlike the existing methods for detection of evolving concepts, we cast joint classification and detection of evolving concepts into optimizing an objective function by... 

We have entered the era of networked communications where concepts such as big data and social networks are emerging. The explosion and profusion of available data in a broad range of application domains cause data streams to become an inevitable part of the most real-world applications. In the classification of data streams, there are four major challenges: infinite length, concept drift, recurring and evolving concepts. This paper proposes a novel method to address the mentioned challenges with a focus on the last one. Unlike the existing methods for detection of evolving concepts, we cast joint classification and detection of evolving concepts into optimizing an objective function by... 

Most of the supervised classification algorithms are proposed to classify newly seen instances based on their learned label space. However, in the case of data streams, conceptevolution is inevitable. In this paper we propose a support vector based approach for classification beyond the learned label space in data streams with regard to other challenges in data streams like concept-drift and infinite-length. We maintain the boundaries of observed classes through the stream by utilizing a support vector based method (SVDD). Newly arrived instances located outside these boundaries will be analyzed by constructing neighborhood graph to detect the emergence of a class beyond the learned label... 

We investigate large wireless networks subject to security constraints. In contrast to point-to-point, interferencelimited communications considered in prior works, we propose active cooperative relaying-based schemes. We consider a network with nl legitimate nodes, ne eavesdroppers, and path loss exponent α ≥ 2. As long as n2e (log(ne))γ = o(nl ), for some positive γ , we show that one can obtain unbounded secure aggregate rate. This means zero-cost secure communication, given fixed total power constraint for the entire network. We achieve this result through: 1) the source using Wyner randomized encoder and a serial (multi-stage) block Markov scheme, to cooperate with the relays and 2) the... 

Investigating the impact of geological uncertainty (i.e., spatial distribution of fractures) on reservoir performance may aid management decisions. The conventional approach to address this is to build a number of possible reservoir models, upscale them, and then run flow simulations. The problem with this approach is that it is computationally very expensive. In this study, we use another approach based on the permeability contrasts that control the flow, called percolation approach. This assumes that the permeability disorder of a rock can be simplified to either permeable or impermeable. The advantage is that by using some universal laws from percolation theory, the effect of the complex... 

Recently, a new class of binary codes for overloaded CDMA systems are proposed that not only has the ability of errorless communication but also suitable for detecting active users. These codes are called COWDA. In [1], a Maximum Likelihood (ML) decoder is proposed for this class of codes. Although the proposed scheme for coding/decoding shows impressive performance, the decoder can be significantly improved. In this paper, by assuming practical conditions for the traffic in the system, we suggest and prove an algorithm that increases the performance of the decoder several orders of magnitude (the Bit-Error-Rate (BER) is divided by a factor of about 400 in some E b/N0's). The algorithm... 

In this paper we present new methods to estimate the effective permeability (keff) of heterogeneous porous media with a wide distribution of permeabilities and various underlying structures, using percolation concepts. We first set a threshold permeability (kth) on the permeability density function and use standard algorithms from percolation theory to check whether the high permeable grid blocks (i.e., those with permeability higher than kth) with occupied fraction of “p” first forms a cluster connecting two opposite sides of the system in the direction of the flow (high permeability flow pathway). Then we estimate the effective permeability of the heterogeneous porous media in different... 

It has long been understood that flow behavior in heterogeneous porous media is largely controlled by the continuity of permeability contrasts. With this in mind, we are looking in new methods for a fast estimation of the effective permeability which concentrates on the properties of the percolating cluster. From percolation concepts we use a threshold permeability value (Kth) by which the gridblocks with the highest permeability values connect two opposite side of the system in the direction of the flow. Those methods can be applied to heterogeneous media of a range of permeabilities distribution and various underlying structures. We use power law relations and weighted power averages that... 

Indium tin oxide (ITO) thin films have been deposited using RF sputtering technique at different pressures, RF powers, and substrate temperatures. Variations in surface morphology, optical properties, and film resistances were measured and analyzed. It is shown that a very low value of sheet resistance (1.96 ω/sq.) can be achieved with suitable arrangement of the deposition experiments. First, at constant RF power, deposition at different pressure values is done, and the condition for achieving minimum sheet resistance (26.43 ω/sq.) is found. In the next step, different values of RF powers are tried, while keeping the pressure fixed on the previously found minimum point (1-2 Pa). Finally,... 

Seven different types of gasification-based coal conversion processes for producing mainly electricity and in some cases hydrogen (H2), with and without carbon dioxide (CO2) capture, were compared on a consistent basis through simulation studies. The flowsheet for each process was developed in a chemical process simulation tool "Aspen Plus". The pressure swing adsorption (PSA), physical absorption (Selexol), and chemical looping combustion (CLC) technologies were separately analyzed for processes with CO2 capture. The performances of the above three capture technologies were compared with respect to energetic and exergetic efficiencies, and the level of CO2 emission. The effect of air... 

Single-crystal hydroxyapatite (HAp) nanorods and nanogranules have been synthesized successfully by a mechanochemical process using two distinct experimental procedures. The experimental outcomes are characterized by transmission electron microscopy (TEM), and powder X-ray diffraction (XRD) techniques. In this work, the feasibility of using polymeric milling media to prepare hydroxyapatite nanoparticles is described. The resulting hydroxyapatite powder exhibits an average size of about 20 to 23 nm. Final results indicate that the proposed synthesis strategy provides a facile pathway to obtain single-crystal HAp with high quality and suitable morphology. © 2008 Elsevier B.V. All rights... 

Migration to the cloud has been a popular topic in industry and academia in recent years. Despite many benefits that the cloud presents, such as high availability and scalability, most of the on-premise application architectures are not ready to fully exploit the benefits of this environment, and adapting them to this environment is a non-trivial task. Microservices have appeared recently as novel architectural styles that are native to the cloud. These cloud-native architectures can facilitate migrating on-premise architectures to fully benefit from the cloud environments because non-functional attributes, like scalability, are inherent in this style. The existing approaches on cloud... 

Estimating available hydrocarbon to be produced during secondary oil recovery is an ongoing activity in field development. The primary plan is normally scheduled during early stage of field's life through master development plan studies. During this period, due to the lake of certain data, estimation of the field efficiency is usually based on rules of thumb and not detailed field characterization. Hence, there is a great motivation to produce simpler physically-based methodologies. The minimum necessity inputs of percolation approach make it a useful tool for foration performance prediction. This approach enables us to attain a better assessment of the efficiency of secondary recovery... 

Development of reliable and accurate models to estimate carbon dioxide–brine interfacial tension (IFT) is necessary, since its experimental measurement is time-consuming and requires expensive experimental apparatus as well as complicated interpretation procedure. In the current study, feed forward artificial neural network is used for estimation of CO2–brine IFT based on data from published literature which consists of a number of carbon dioxide–brine interfacial tension data covering broad ranges of temperature, total salinity, mole fractions of impure components and pressure. Trial-and-error method is utilized to optimize the artificial neural network topology in order to enhance its... 

In the present study a finite difference method has been developed to model the transient fluid flow and heat transfer. A single fluid has been selected for modeling of mold filling and The SOLA-VOF 3D technique was modified to increase the accuracy of simulation of filling phenomena for shape castings. The model was then evaluated with the experimental methods. Refereeing to the experimental and simulation results a good consistency and the accuracy of the suggested model are confirmed. © 2005 Published by Elsevier B.V  

In the casting process, as a mould is filled with molten metal, air escapes through the vents. Air pressure in the mould cavity has serious effects upon the filling behaviour such as surface profile of the molten metal and filling time. In this project a computational model was developed for calculation of air pressure during the mould filling. A 3D single phase code based on the SOLA-VOF algorithm was used for the prediction of the fluid flow. The ideal gas assumption, conservation of mass equation and Bernoulli law were used for the calculation of air pressure. A new algorithm was developed to interpolate air pressure on the surface cells. The creation of air pressure was correlated with... 

In this paper, we report our evaluation of the strength of random number generator and RSA key-pair generator of some commercially available constrained hardware modules, i.e., tokens and smart cards. That was motivated after recent related attacks to RSA public keys, which are generated by constrained network devices and smart cards, and turned out to be insecure due to low-quality randomness. Those attacks are mostly computing pair-wise GCD between the moduli in public keys, and resulted in breaking several thousands of these keys. Our results show that most of the tested hardware modules behave well. However, some have abnormal or weak random generators which seem to be unsuitable for... 

In continuum mechanics, the constitutive models are usually based on the Cauchy-Born (CB) hypothesis which seeks the intrinsic characteristics of the material via the atomistic information and it is valid in small deformation. The main purpose of this paper is to investigate the temperature effect on the stability and size-dependency of Cauchy-Born hypothesis. Three-dimensional temperature-related Cauchy-Born formulations are developed for crystalline structure and the stability and size-dependency of temperature-related Cauchy-Born hypothesis are investigated by means of direct comparison between atomistic and continuous mediums. In order to control the temperature effect, the Nose-Hoover...