Sharif Digital Repository

Measurements and sensing implementations impose certain cost in sensor networks. The sensor selection cost optimisation is the problem of minimising the sensing cost of monitoring a physical (or cyber-physical) system. Consider a given set of sensors tracking states of a dynamical system for estimation purposes. For each sensor assume different costs to measure different (realisable) states. The idea is to assign sensors to measure states such that the global cost is minimised. The number and selection of sensor measurements need to ensure the observability to track the dynamic state of the system with bounded estimation error. The main question we address is how to select the state... 

Natural and biodegradable polymers are of particular interest as green sources with low-cost and environmentally friendly features, and have been widely used for polymer composite development. The term “Green Composites” refers to polymer/filler systems in which polymer, filler, or sometimes both components are green in view of sources from which they are yielded or their biodegradability. Natural fibers obtained from plants, animals, and/or geological processes are a big class of green sources widely applied in green composite development. There has also been continued research on recycling of green composite as well as developing hybrid systems for advanced applications. In view of their... 

Natural and biodegradable polymers are of particular interest as green sources with low-cost and environmentally friendly features, and have been widely used for polymer composite development. The term “Green Composites” refers to polymer/filler systems in which polymer, filler, or sometimes both components are green in view of sources from which they are yielded or their biodegradability. Natural fibers obtained from plants, animals, and/or geological processes are a big class of green sources widely applied in green composite development. There has also been continued research on recycling of green composite as well as developing hybrid systems for advanced applications. In view of their... 

Recently it has been shown that network coding can highly improve the network throughput in the communication systems and specifically increase the downloading performance in P2P networks. This paper presents a new live streaming system for GIA-based P2P networks. In the proposed system the traditional GIA protocol is improved for an efficient use in multimedia applications. We introduce a new mesh-pull layered video streaming framework for GIA-based systems and employ random network coding to improve the network performance. Random network coding algorithm enables each peer to send a single encoded video chunk instead of multiple video blocks toward the destination node and save its... 

Understanding the impact of network clustering and small-world properties on epidemic spread can be crucial in developing effective strategies for managing and controlling infectious diseases. Particularly in this work, we study the impact of these network features on targeted intervention (e.g., self-isolation and quarantine). The targeted individuals for self-isolation are based on centrality measures and node influence metrics. Compared to our previous works on scale-free networks, small-world networks are considered in this paper. Small-world networks resemble real-world social and human networks. In this type of network, most nodes are not directly connected but can be reached through a... 

Advancements in nanotechnology have resulted in the introduction of several nonviral delivery vectors for the nontoxic, efficient delivery of encapsulated mRNA-based vaccines. Lipid- and polymer-based nanoparticles (NP) have proven to be the most potent delivery systems, providing increased delivery efficiency and protection of mRNA molecules from degradation. Here, the authors provide an overview of the recent studies carried out using lipid NPs and their functionalized forms, polymeric and lipid-polymer hybrid nanocarriers utilized mainly for the encapsulation of mRNAs for gene and immune therapeutic applications. A microfluidic system as a prevalent methodology for the preparation of NPs... 

In this work, a green synthesis method was designed and practiced to develop bioactive and biocompatible carbon-based nanocomposites biomaterials. ZnO nanoparticles were synthesized in assistance of leaf extracts and added to a composite nanostructure composed of the reduced graphene oxide (rGO) and multi-walled carbon nanotubes (MWCNT). The resulting green nanocomposite revealed ability to make π-π interactions, hydrogen bonding, and van der Waals interactions with the doxorubicin (DOX). Then, the surface morphology of the synthesized nanocomposite was investigated, and the interrelationship between the surface morphology, relative cell viability, and drug uptake and release behavior were... 

In this work, a green synthesis method was designed and practiced to develop bioactive and biocompatible carbon-based nanocomposites biomaterials. ZnO nanoparticles were synthesized in assistance of leaf extracts and added to a composite nanostructure composed of the reduced graphene oxide (rGO) and multi-walled carbon nanotubes (MWCNT). The resulting green nanocomposite revealed ability to make π-π interactions, hydrogen bonding, and van der Waals interactions with the doxorubicin (DOX). Then, the surface morphology of the synthesized nanocomposite was investigated, and the interrelationship between the surface morphology, relative cell viability, and drug uptake and release behavior were... 

In this paper, we propose a Gaussian Process Regression (GPR) framework for concealment of corrupted motion vectors in predictive video coding of packet video systems. The problem of estimating the lost motion vectors is modelled as a kernel construction problem in a Bayesian framework. First, to describe the similarity between the neighboring motion vectors, a kernel function is defined. Then the parameters of the kernel function is estimated as the coefficients of a linear Bayesian estimator. The experimental results verify the superiority of the proposed algorithm over the conventional and state of the art motion vector concealment methods. Moreover, noticeable improvements on both... 

When the number of labeled data is not sufficient, Semi-Supervised Learning (SSL) methods utilize unlabeled data to enhance classification. Recently, many SSL methods have been developed based on the manifold assumption in a batch mode. However, when data arrive sequentially and in large quantities, both computation and storage limitations become a bottleneck. In this paper, we present a new semi-supervised coarse graining (CG) algorithm to reduce the required number of data points for preserving the manifold structure. First, an equivalent formulation of Label Propagation (LP) is derived. Then a novel spectral view of the Harmonic Solution (HS) is proposed. Finally an algorithm to reduce... 

Effects of introducing two monovacancies in bilayer graphene are investigated by using spin-polarized density functional theory. Each layer of bilayer graphene has a monovacancy. Two different classifications are studied, namely, AA and AB. In AA category, vacancies in upper layer and lower layer are chosen from the same sublattices (A or B). However, in AB category, vacancies are selected from the different sublattices (A and B). Two different structures of every classification are examined in order to investigate the effects of two monovacancies on structural, electronic, and magnetic properties of bilayer graphene. Structural optimization reveals that introducing a monovacancy in every... 

The aim of this paper is introducing coding scheme that can potentially achieve the sum rate-distortion bound of Gaussian IMTSC/CEO problem with arbitrary number of encoders. No previous work has been reported on code design for the IMTSC/CEO problem with the number of encoders greater than two. In this paper the framework of Slepian-Wolf coded quantization is extended to the case with the number of encoders greater than two. On the other hand, we apply the approach to the case of unequal levels of the observation noise at the encoders. Encoding process consists of trellis coded quantization (TCQ) and LDPC codes. The proposed framework can be easily used for any number of active encoders... 

We propose a new nonblind multiresolution watermarking method for still images based on the contourlet transform (CT). In our approach, the watermark is a grayscale image which is embedded into the highest frequency subband of the host image in its contourlet domain. We demonstrate that in comparison to other methods, this method enables us to embed more amounts of data into the directional subbands of the host image without degrading its perceptibility. The experimental results show robustness against several common watermarking attacks such as compression, adding noise, filtering, and geometrical transformations. Since the proposed approach can embed considerable payload, while providing... 

Power and bandwidth constraints are two major challenges in wireless sensor networks. Since a considerable amount of energy in sensor networks is consumed for data transmission, compression techniques may prolong the life of such networks. Moreover, with fewer bits to transmit, the network can cope better with the problem of inadequate bandwidth. In this paper, we consider an image sensor network and propose a paradigm based on the principles of Distributed Source Coding (DSC) for efficient compression. Our method relies on high correlation between the sensor nodes. The algorithm consists of two phases: the Training Phase and the Main Phase. In the Training Phase an aggregation node or a... 

In this paper, we propose a new multiresolution watermarking method for still images based on the Contourlet Transform (CT). In our algorithm, the watermark is a grayscale image which is embedded into the host image in its contourlet domain. We demonstrate that in comparison with other methods, the proposed method enables us to embed more amount of data into the host image without degrading its perceptual quality. The experimental results show robustness against several common watermarking attacks such as compression, adding noise, and filtering. ©2009 IEEE  

Social networks are getting closer to our real physical world. People share the exact location and time of their check-ins and are influenced by their friends. Modeling the spatio-temporal behavior of users in social networks is of great importance for predicting the future behavior of users, controlling the users’ movements, and finding the latent influence network. It is observed that users have periodic patterns in their movements. Also, they are influenced by the locations that their close friends recently visited. Leveraging these two observations, we propose a probabilistic model based on a doubly stochastic point process with a periodic-decaying kernel for the time of check-ins and a... 

Community detection in social networks has become a popular topic of research during the last decade. There exist a variety of algorithms for modularizing the network graph into different communities. However, they mostly assume that partial or complete information of the network graphs are available that is not feasible in many cases. In this article, we focus on detecting communities by exploiting their diffusion information. To this end, we utilize the Conditional Random Fields (CRF) to discover the community structures. The proposed method, community diffusion (CoDi), does not require any prior knowledge about the network structure or specific properties of communities. Furthermore, in... 

In this paper, we propose a new peer-to-peer (P2P) video streaming protocol which presents an implementation of network coding with a new caching mechanism. It employs a push-pull mechanism for sending the video chunks between peers. More specifically, this push-pull mechanism gives priority to the video chunks according to their video layers. The video base layer is transmitted through a pushing mechanism while the enhancement layers employ a pulling mechanism. Moreover, in the network coding algorithm of this protocol, we introduce a caching mechanism to improve the network's performance as well as the video streaming quality. The comprehensive simulations show that the proposed protocol... 

Substantial terms have been recognized on the associated risk elements, comorbidities as well as, putative pathophysiological processes of Alzheimer disease and related dementias (ADRDs) as well as, type 2 diabetes mellitus (T2DM), a few from greatest important disease from the moments. Very much is considered regarding the biology and chemistry of each predicament, nevertheless T2DM and ADRDs are an actually similar pattern developing from the similar origins of maturing or synergistic conditions connected by aggressive patho-corporeal terms and continues to be ambiguous. In this depth-critique article, we aimed to investigate all possibilities and represented a novel and applicable... 

Substantial terms have been recognized on the associated risk elements, comorbidities as well as, putative pathophysiological processes of Alzheimer disease and related dementias (ADRDs) as well as, type 2 diabetes mellitus (T2DM), a few from greatest important disease from the moments. Very much is considered regarding the biology and chemistry of each predicament, nevertheless T2DM and ADRDs are an actually similar pattern developing from the similar origins of maturing or synergistic conditions connected by aggressive patho-corporeal terms and continues to be ambiguous. In this depth-critique article, we aimed to investigate all possibilities and represented a novel and applicable...