Sharif Digital Repository

TiO2 nanoparticles supported on activated carbon (AC) and multiwalled carbon nanotubes (MWCNTs) were prepared by the sol–gel method using ultrasonic irradiation. All the prepared samples were calcined at different temperatures and characterized by X-ray diffraction, nitrogen adsorption/desorption isotherms, scanning electron microscopy, transmission electron microscopy and diffuse reflectance spectroscopy. The effects of size and type of carbon on the morphology and photocatalytic activity of the resulting hybrid materials were investigated. The results showed that a decrease in the size of the carbon led to a decrease in size of TiO2 nanoparticles. Both AC and MWCNTs retarded the... 

TiO2 nanoparticles supported on activated carbon (AC) and multiwalled carbon nanotubes (MWCNTs) were prepared by the sol-gel method using ultrasonic irradiation. All the prepared samples were calcined at different temperatures and characterized by X-ray diffraction, nitrogen adsorption/desorption isotherms, scanning electron microscopy, transmission electron microscopy and diffuse reflectance spectroscopy. The effects of size and type of carbon on the morphology and photocatalytic activity of the resulting hybrid materials were investigated. The results showed that a decrease in the size of the carbon led to a decrease in size of TiO2 nanoparticles. Both AC and MWCNTs retarded the... 

Diffusive molecular communications (DiMC) have recently gained attention as a candidate for nano- to micro- and macro-scale communications due to its simplicity and energy efficiency. As signal propagation is solely enabled by Brownian motion mechanics, DiMC faces severe inter-symbol interference (ISI), which limits reliable and high data-rate communications. Herein, recent literature on DiMC performance enhancement strategies is surveyed; key research directions are identified. Signaling design and associated design constraints are presented. Studies on fundamental information theoretic limits of DiMC channel are reviewed. Classical and novel transceiver designs are discussed with an... 

Diffusive molecular communications (DiMC) have recently gained attention as a candidate for nano- to micro- and macro-scale communications due to its simplicity and energy efficiency. As signal propagation is solely enabled by Brownian motion mechanics, DiMC faces severe inter-symbol interference (ISI), which limits reliable and high data-rate communications. Herein, recent literature on DiMC performance enhancement strategies is surveyed; key research directions are identified. Signaling design and associated design constraints are presented. Studies on fundamental information theoretic limits of DiMC channel are reviewed. Classical and novel transceiver designs are discussed with an... 

Users in social networks whose posts stay at the top of their followers' feeds the longest time are more likely to be noticed. Can we design an online algorithm to help them decide when to post to stay at the top? In this paper, we address this question as a novel optimal control problem for jump stochastic differential equations. For a wide variety of feed dynamics, we show that the optimal broadcasting intensity for any user is surprisingly simple - it is given by the position of her most recent post on each of her follower's feeds. As a consequence, we are able to develop a simple and highly efficient online algorithm, RedQueen, to sample the optimal times for the user to post.... 

User engagement in online social networking depends critically on the level of social activity in the corresponding platform-the number of online actions, such as posts, shares or replies, taken by their users. Can we design data-driven algorithms to increase social activity? At a user level, such algorithms may increase activity by helping users decide when to take an action to be more likely to be noticed by their peers. At a network level, they may increase activity by incentivizing a few influential users to take more actions, which in turn will trigger additional actions by other users. In this paper, we model social activity using the framework of marked temporal point processes,... 

In this paper, a simple memory limited transmitter for molecular communication is proposed, in which information is encoded in the diffusion rate of the molecules. Taking advantage of memory, the proposed transmitter reduces the ISI problem by properly adjusting its diffusion rate. The error probability of the proposed scheme is derived and the result is compared with the lower bound on error probability of the optimum transmitter. It is shown that the performance of introduced transmitter is near optimal (under certain simplifications). Simplicity is the key feature of the presented communication system: the transmitter follows a simple rule, the receiver is a simple threshold decoder and... 

In this paper, a simple memory limited transmitter for molecular communication is proposed, in which information is encoded in the emission rate of the molecules. Taking advantage of memory, the proposed transmitter reduces the ISI problem by properly adjusting its emission rate, which can be interpreted as water-filling on the expected interference. The error probability of the proposed scheme is derived and the result is compared with the error probability of the optimal transmitter obtained by dynamic programming methods. Furthermore, for the special case of channel with one symbol memory, a tight lower bound on error probability is derived. Numerical results show that the performance of... 

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... 

Nanonetworking indicates new solutions for many applications in biomedical and industrial fields. In this paper, we examine the diffusion-based molecular communication for information transmission in nano-networks. Design of practical decoders for resource-limited nano-networks requires an understanding the fundamental performance limits of memory-limited decoders. While some existing works in the literature do consider decoders with limited memory, to best of our knowledge, the tradeoff between memory and probability of error has not been studied in the literature. In this paper we make a first step by studying this tradeoff for a particular molecular communication channel between two... 

In this paper, a diffusion-based molecular communication channel between two nano-machines is considered. The effect of the amount of memory on performance is characterized, and a simple memory-limited decoder is proposed; its performance is shown to be close to that of the best possible decoder (without any restrictions on the computational complexity or its functional form), using genie-aided upper bounds. This effect is adapted to the case of Molecular Concentration Shift Keying; it is shown that a four-bit memory achieves nearly the same performance as infinite memory for all of the examples considered. A general class of threshold decoders is considered and shown to be suboptimal for a... 

The LTI-Poisson model is a natural extension of the conventional memoryless Poisson channel to include memory, and can model the ISI effect in diffusion based molecular communication networks. In this paper, we exploit prior art on linear ISI channels to provide a computable finite-letter characterization of the capacity of single-hop LTI-Poisson networks. Then we find more explicit single-letter lower and upper bounds on the capacity in the point to point case. Further, an approach for bounding mutual information in the low SNR regime using the symmetrized KL divergence is introduced and its applicability for Poisson channels is demonstrated. This leads to a non-trivial upper bound on the... 

This paper presents a robust tracking approach to handle challenges such as occlusion and appearance change. Here, the target is partitioned into a number of patches. Then, the appearance of each patch is modeled using a dictionary composed of corresponding target patches in previous frames. In each frame, the target is found among a set of candidates generated by a particle filter, via a likelihood measure that is shown to be proportional to the sum of patch-reconstruction errors of each candidate. Since the target's appearance often changes slowly in a video sequence, it is assumed that the target in the current frame and the best candidates of a small number of previous frames, belong to... 

Semisupervised hyperspectral unmixing finds the ratio of spectral library members in the mixture of hyperspectral pixels to find the proportion of pure materials in a natural scene. The two main challenges are noise in observed spectral vectors and high mutual coherence of spectral libraries. To tackle these challenges, we propose a probabilistic sparse regression method for linear hyperspectral unmixing, which utilizes the implicit relations of neighboring pixels. We partition the hyperspectral image into rectangular patches. The sparse coefficients of pixels in each patch are assumed to be generated from a Laplacian scale mixture model with the same latent variables. These latent variables... 

In real world social networks, there are multiple cascades which are rarely independent. They usually compete or cooperate with each other. Motivated by the reinforcement theory in sociology we leverage the fact that adoption of a user to any behavior is modeled by the aggregation of behaviors of its neighbors. We use a multidimensional marked Hawkes process to model users product adoption and consequently spread of cascades in social networks. The resulting inference problem is proved to be convex and is solved in parallel by using the barrier method. The advantage of the proposed model is twofold; it models correlated cascades and also learns the latent diffusion network. Experimental... 

Using multiple antennas at the transmit and receive sides of a passive radar brings both the benefits of MIMO radar and passive radar. However one of the obstacles arisen in such configuration is the receive antennas placement in proper positions so that the radar performance is improved. Here we just consider the case of positioning one receiver among multiple illuminators of opportunity. Indeed it is a start for the solution of optimizing the geometry of the multiple receivers in a passive radar