Sharif Digital Repository

A novel method is proposed in the scope of image segmentation that solves this problem by breaking it into two main blocks. The first block's functionality is a method to anticipate the color basis of each segment in segmented images. One of the challenges of image segmentation is the inappropriate distribution of colors in the RGB color space. To determine the color of each segment, after mapping the input image onto the HSI color space, the image colors are classified into some clusters by exploiting the K-Means. Then, the list of cluster centers is winnowed down to a short list of colors based on a set of criteria. The second block of the proposed method defines how each pixel of the... 

Sludge handling is a common issue in all biological wastewater treatment methods. In this study, sonication technique as a state-of-the-art technology has been applied to a continuous MBBR system with the aim of sludge reduction. A novel configuration of MBBR with an additional recycle stream of sonicated sludge was used as the experimental setup. Based on exposed energy and sludge disruption performance, optimized sonication density and exposure time were obtained 1.5 W/mL and 15 min, respectively. This condition provided 42.2% increase in soluble COD as a result of sludge disintegration. Our results revealed that the performance of MBBR and excess sludge reduction were affected by... 

Due to reliability and performance considerations, employing multiple software-defined networking (SDN) controllers is known as a promising technique in Wireless Sensor Networks (WSNs). Nevertheless, employing multiple controllers increases the inter-controller synchronization overhead. Therefore, optimal placement of SDN controllers to optimize the performance of a WSN, subject to the maximum number of controllers, determined based on the synchronization overhead, is a challenging research problem. In this paper, we first formulate this research problem as an optimization problem, then to address the optimization problem, we propose the Cuckoo Placement of Controllers (Cuckoo-PC) algorithm.... 

Mixed-criticality systems are introduced due to industrial interest to integrate different types of functionalities with varying importance into a common and shared computing platform. Low-energy consumption is vital in mixed-criticality systems due to their ever-increasing computation requirements and the fact that they are mostly supplied with batteries. In case when high-criticality tasks overrun in such systems, low-criticality tasks can be whether ignored or degraded to assure high-criticality tasks timeliness. We propose a novel energy management method (called Stretch), which lowers the energy consumption of mixed-criticality systems with the cost of degrading service level of... 

Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest items to users that might be interesting for them. Recent studies illustrate that incorporating social trust in Matrix Factorization methods demonstrably improves accuracy of rating prediction. Such approaches mainly use the trust scores explicitly expressed by users. However, it is often challenging to have users provide explicit trust scores of each other. There exist quite a few works, which propose Trust Metrics to compute and predict trust scores between users based on their interactions. In this paper, first we present how social relation can be extracted from users'... 

Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest items to users that might be interesting for them. Recent studies illustrate that incorporating social trust in Matrix Factorization methods demonstrably improves accuracy of rating prediction. Such approaches mainly use the trust scores explicitly expressed by users. However, it is often challenging to have users provide explicit trust scores of each other. There exist quite a few works, which propose Trust Metrics to compute and predict trust scores between users based on their interactions. In this paper, first we present how social relation can be extracted from users'... 

Online media play an important role in information societies by providing a convenient infrastructure for different processes. Information diffusion that is a fundamental process taking place on social and information networks has been investigated in many studies. Research on information diffusion in these networks faces two main challenges: (1) In most cases, diffusion takes place on an underlying network, which is latent and its structure is unknown. (2) This latent network is not fixed and changes over time. In this article, we investigate the diffusion network extraction (DNE) problem when the underlying network is dynamic and latent. We model the diffusion behavior (existence... 

Visual attributes are great means of describing images or scenes, in a way both humans and computers understand. In order to establish a correspondence between images and to be able to compare the strength of each property between images, relative attributes were introduced. However, since their introduction, hand-crafted and engineered features were used to learn increasingly complex models for the problem of relative attributes. This limits the applicability of those methods for more realistic cases. We introduce a deep neural network architecture for the task of relative attribute prediction. A convolutional neural network (ConvNet) is adopted to learn the features by including an... 

Classification of video events based on frame-level descriptors is a common approach to video recognition. In the meanwhile, proper encoding of the frame-level descriptors is vital to the whole event classification procedure. While there are some pretty efficient video descriptor encoding methods, temporal ordering of the descriptors is often ignored in these encoding algorithms. In this paper, we show that by taking into account the temporal inter-frame dependencies and tracking the chronological order of video sub-events, accuracy of event recognition is further improved. First, the frame-level descriptors are extracted using convolutional neural networks (CNNs) pre-trained on ImageNet,... 

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... 

This paper proposes an efficient mechanism that mitigates crosstalk faults in Network-on-Chips (NoCs). This is done by using a Packet Manipulating mechanism called PAM for reliable data transfer of NoCs. PAM investigates the transitions of a packet to minimize the forbidden transition patterns appearing during the flit traversal in NoCs. To do this, the content of a packet is manipulated using three different manipulating mechanisms. In other words, PAM manipulates the content of packet in three manipulating modes including: vertical, horizontal and diagonal modes. Then, comparing the transitions of these manipulating mechanisms, a packet with minimum numbers of transitions is selected to be... 

Data traversal in Network-on-Chips (NoCs) is threated by crosstalk fault seriously. Crosstalk fault leads to mutual influence between adjacent wires of NoCs and as a result endangers the reliability of data in NoCs. Crosstalk fault is strongly dependent on the transition patterns appearing on the wires of NoCs. Among these transitions, Triplet Opposite Directions (TODs) impose the worse crosstalk effects to the wires of NoCs. This paper proposes an efficient numerical-based coding mechanism called Summation-based-Subtracted-Added-Penultimate (S2AP) which alleviates crosstalk faults. This is done by completely removing TODs which are the main source of crosstalk faults in the channels of... 

Inter-wire coupling capacitances can lead to crosstalk fault that is strongly dependent on the transition patterns appearing on the wires. These transition patterns can cause mutual influences between adjacent wires of NoCs and as a result threaten the reliability of data transfer seriously. To increase the reliability of NoCs against the crosstalk fault, Forbidden Pattern Free (FPFs) codes are used. To generate FPF codes, numerical systems are among the overhead-efficient mechanisms. The algorithms of numerical systems have direct effect on the amounts of the codec overheads including power consumption, area occupation and performance of NoCs. To find an overhead-efficient numerical system,... 

With technology scaling, crosstalk fault has become a serious problem in reliable data transfer through Network on Chip (NoC) channels. The effects of crosstalk fault depend on transition patterns appearing on the wires of NoC channels. Among these patterns, Triplet Opposite Direction (TOD) imposes the worst crosstalk effects. Crosstalk Avoidance Codes (CACs) are the overhead-efficient mechanisms to tackle TODs. The main problem of CACs is their high imposed overheads to NoC routers. To solve this problem, this paper proposes an overhead-efficient coding mechanism called Penultimate-Subtracted Fibonacci (PS-Fibo) to alleviate crosstalk faults in NoC wires. PS-Fibo coding mechanism benefits... 

Appearances of specific transition patterns during data transfer in bus lines of modern high-performance computing systems, such as communicating structures of accelerators for deep convolutional neural networks, commercial Network on Chips, and memories, can lead to crosstalk faults. With the shrinkage of technology size, crosstalk faults occurrence boosts and leads to degradation of reliability and performance, as well as the increasing power consumption of lines. One effective way to alleviate crosstalk faults is to avoid the appearance of these specific transition patterns by using numerical-based crosstalk avoidance codes (CACs). However, a serious problem with numerical-based CACs is... 

In this article, we look at early, recent, and state-of-the-art methods for registration of medical images using a range of high-performance computing (HPC) architectures including symmetric multiprocessing (SMP), massively multiprocessing (MMP), and architectures with distributed memory (DM), and nonuniform memory access (NUMA). The article is designed to be self-sufficient. We will take the time to define and describe concepts of interest, albeit briefly, in the context of image registration and HPC. We provide an overview of the registration problem and its main components in the section "Registration." Our main focus will be HPC-related aspects, and we will highlight relevant issues as... 

Given a social network modeled as a weighted graph GG, the influence maximization problem seeks kk vertices to become initially influenced, to maximize the expected number of influenced nodes under a particular diffusion model. The influence maximization problem has been proven to be NP-hard, and most proposed solutions to the problem are approximate greedy algorithms, which can guarantee a tunable approximation ratio for their results with respect to the optimal solution. The state-of-the-art algorithms are based on Reverse Influence Sampling (RIS) technique, which can offer both computational efficiency and non-trivial (1-1/e-ϵ)-approximation ratio guarantee for any epsilon >0ϵ>0.... 

This paper introduces a novel coding scheme based on the diffusion map framework. The idea is to run a t-step random walk on the data graph to capture the similarity of a data point to the codebook atoms. By doing this we exploit local similarities extracted from the data structure to obtain a global similarity which takes into account the nonlinear structure of the data. Unlike the locality-based and sparse coding methods, the proposed coding varies smoothly with respect to the underlying manifold. We extend the above transductive approach to an inductive variant which is of great interest for large scale datasets. We also present a method for codebook generation by coarse graining the data... 

A state-of-the-art algorithm for perspective projection reconstruction of non-rigid surfaces from single-view and realistic videos is proposed. It overcomes the limitations arising from the usage of orthographic camera model and also the complexity and non-linearity issues of perspective projection equation. Unlike traditional non-rigid structure-from-motion (NRSfM) methods, which have been studied only on synthetic datasets and controlled lab environments that require some prior constraints (such as manually segmented objects, limited rotations and occlusions, and full-length trajectories); the proposed method can be used in realistic video sequences. In addition, contrary to previous... 

A state-of-the-art algorithm for perspective projection reconstruction of non-rigid surfaces from single-view and realistic videos is proposed. It overcomes the limitations arising from the usage of orthographic camera model and also the complexity and non-linearity issues of perspective projection equation. Unlike traditional non-rigid structure-from-motion (NRSfM) methods, which have been studied only on synthetic datasets and controlled lab environments that require some prior constraints (such as manually segmented objects, limited rotations and occlusions, and full-length trajectories); the proposed method can be used in realistic video sequences. In addition, contrary to previous...