OpenRaiser/Intern-Atlas huggingface dataset:
Evolution of Online User Behavior During a Social Upheaval
Venue: arXiv cs.SI 2014
Year: 2014

Social media represent powerful tools of mass communication and information diffusion. They played a pivotal role during recent social uprisings and political mobilizations across the world. Here we present a study of the Gezi Park movement in Turkey through the lens of Twitter. We analyze over 2.3 million tweets produced during the 25 days of protest occurred between May and June 2013. We first characterize the spatio-temporal nature of the conversation about the Gezi Park demonstrations, showing that similarity in trends of discussion mirrors geographic cues. We then describe the characteristics of the users involved in this conversation and what roles they played. We study how roles and individual influence evolved during the period of the upheaval. This analysis reveals that the conversation becomes more democratic as events unfold, with a redistribution of influence over time in the user population. We conclude by observing how the online and offline worlds are tightly intertwined, showing that exogenous events, such as political speeches or police actions, affect social media conversations and trigger changes in individual behavior.
Securing Medical Images by Watermarking Using DWT DCT and SVD
Venue: arXiv cs.MM 2014
Year: 2014

Telemedicine is well known application where enormous amount of medical data need to be transferred securely over network and manipulate effectively. Security of digital data, especially medical images, becomes important for many reasons such as confidentiality, authentication and integrity. Digital watermarking has emerged as a advanced technology to enhance the security of digital images. The insertion of watermark in medical images can authenticate it and guarantee its integrity. The watermark must be generally hidden does not affect the quality of the medical image. In this paper, we propose blind watermarking based on Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD), we compare the performance of this technique with watermarking based DWT and SVD. The proposed method DWT, DCT and SVD comparatively better than DWT and SVD method.
Repairable Block Failure Resilient Codes
Venue: arXiv cs.IT 2014
Year: 2014

In large scale distributed storage systems (DSS) deployed in cloud computing, correlated failures resulting in simultaneous failure (or, unavailability) of blocks of nodes are common. In such scenarios, the stored data or a content of a failed node can only be reconstructed from the available live nodes belonging to available blocks. To analyze the resilience of the system against such block failures, this work introduces the framework of Block Failure Resilient (BFR) codes, wherein the data (e.g., file in DSS) can be decoded by reading out from a same number of codeword symbols (nodes) from each available blocks of the underlying codeword. Further, repairable BFR codes are introduced, wherein any codeword symbol in a failed block can be repaired by contacting to remaining blocks in the system. Motivated from regenerating codes, file size bounds for repairable BFR codes are derived, trade-off between per node storage and repair bandwidth is analyzed, and BFR-MSR and BFR-MBR points are derived. Explicit codes achieving these two operating points for a wide set of parameters are constructed by utilizing combinatorial designs, wherein the codewords of the underlying outer codes are distributed to BFR codeword symbols according to projective planes.
Diversity versus Multiplexing at Finite Blocklength
Venue: arXiv cs.IT 2014
Year: 2014

A finite blocklenth analysis of the diversity-multiplexing tradeoff is presented, based on nonasymptotic bounds on the maximum channel coding rate of multiple-antenna block-memoryless Rayleigh-fading channels.The bounds in this paper allow one to numerically assess for which packet size, number of antennas, and degree of channel selectivity, diversity-exploiting schemes are close to optimal, and when instead the available spatial degrees of freedom should be used to provide spatial multiplexing. This finite blocklength view on the diversity-multiplexing tradeoff provides insights on the design of delay-sensitive ultra-reliable communication links.
Order-Independent Texture Synthesis
Venue: arXiv cs.GR 2014
Year: 2014

Search-based texture synthesis algorithms are sensitive to the order in which texture samples are generated; different synthesis orders yield different textures. Unfortunately, most polygon rasterizers and ray tracers do not guarantee the order with which surfaces are sampled. To circumvent this problem, textures are synthesized beforehand at some maximum resolution and rendered using texture mapping. We describe a search-based texture synthesis algorithm in which samples can be generated in arbitrary order, yet the resulting texture remains identical. The key to our algorithm is a pyramidal representation in which each texture sample depends only on a fixed number of neighboring samples at each level of the pyramid. The bottom (coarsest) level of the pyramid consists of a noise image, which is small and predetermined. When a sample is requested by the renderer, all samples on which it depends are generated at once. Using this approach, samples can be generated in any order. To make the algorithm efficient, we propose storing texture samples and their dependents in a pyramidal cache. Although the first few samples are expensive to generate, there is substantial reuse, so subsequent samples cost less. Fortunately, most rendering algorithms exhibit good coherence, so cache reuse is high.
Comparison of SVM Optimization Techniques in the Primal
Venue: arXiv cs.LG 2014
Year: 2014

This paper examines the efficacy of different optimization techniques in a primal formulation of a support vector machine (SVM). Three main techniques are compared. The dataset used to compare all three techniques was the Sentiment Analysis on Movie Reviews dataset, from kaggle.com.
Social Technologies for Developing Collective Intelligence in Networked Society
Venue: arXiv cs.SI 2014
Year: 2014

The scientific problem in our project is defined as a question: how social technologies could contribute to the development of smart and inclusive society? The subject of our research are networked projects (virtual CI systems) which include collective decision making tools and innovation mechanisms allowing and encouraging individual and team creativity, entrepreneurship, online collaboration, new forms of self-regulation and self-governance, self-configuration of communities by considering these projects as being catalyst for emergence of CI. The answers to these theoretical questions could have huge practical implications by influencing more reasonable and sophisticated application of social technologies in practice.
Performance Analysis of Ad-Hoc Routing in Clustered Multi-hop Wireless Networks
Venue: arXiv cs.IT 2014
Year: 2014

This paper analyzes the performance of clustered decode-and-forward multi-hop relaying (CDFMR) wireless Rayleigh fading networks, and sheds light on their design principles for energy and spectral efficiency. The focus is on a general performance analysis (over all SNR range) of heterogeneous wireless networks with possibly different numbers of relays in clusters of various separations. For clustered multi-hop relaying systems, ad-hoc routing is known as an efficient decentralized routing algorithm which selects the best relay node on a hop-by-hop basis using local channel state information. In this article, we combine ad-hoc routing and cooperative diversity in CDFMR systems, and we derive (i) a closed-form expression for the probability distribution of the end-to-end SNR at the destination node; (ii) the system symbol error rate (SER) performance for a wide class of modulation schemes; and (iii) exact analytical expressions for the system ergodic capacity, the outage probability and the achievable probability of the SNR (power) gain. We also provide simple analytical asymptotic expressions for SER and the outage probability in high SNR regime. Simulation results are provided to validate the correctness of the presented analyses.
The Mythical Swing Voter
Venue: arXiv cs.SI 2014
Year: 2014

The only acceptable form of polling in the multi-billion dollar survey research field utilizes representative samples. We argue that with proper statistical adjustment, non-representative polling can provide accurate predictions, and often in a much more timely and cost-effective fashion. We demonstrate this by applying multilevel regression and post-stratification (MRP) to a 2012 election survey on the Xbox gaming platform. Not only do the transformed top-line projections from this data closely trend standard indicators, but we use the unique nature of the data's size and panel to answer a meaningful political puzzle. We find that reported swings in public opinion polls are generally not due to actual shifts in vote intention, but rather are the result of temporary periods of relatively low response rates among supporters of the reportedly slumping candidate. This work shows great promise for using non-representative polling to measure public opinion and the first product of this new polling technique raises the possibility that decades of large, reported swings in public opinion-including the perennial "convention bounce"-are mostly artifacts of sampling bias.
Social diffusion and global drift in adaptive social networks
Venue: arXiv cs.SI 2014
Year: 2014

Social contagion has been studied in various contexts. Many instances of social contagion can be modeled as an infection process where a specific state (adoption of product, fad, knowledge, behavior, etc.) spreads from individual to individual through links between them. In the meantime, other forms of social contagion may better be understood as a diffusion process where the state of an individual tends to assimilate with the social norm (i.e., local average state) within his/her neighborhood. Unlike infection scenarios where influence is nonlinear, unidirectional, fast, and potentially disruptive, social diffusion is linear, bidirectional, gradual, and converging. The distance between an individual's state and his/her neighbors' average state always decreases, and thus a homogeneous global state is guaranteed to be the network's stable equilibrium state in the long run. This does not sound as intriguing or exciting as infection dynamics, which might be why there are very few studies on mathematical models of social diffusion processes. Here, this study attempts to shed new light on an unrecognized characteristic of social diffusion, i.e., non-trivial drift it can cause to the network's global average state. Although somewhat counterintuitive, such global drift is indeed possible because, unlike physical diffusion processes, social diffusion processes are not conservational. In what follows, a mathematical model of social diffusion will be presented to explain the mechanism of this phenomenon, and some possible collective actions for influencing the direction of global drift will be proposed. The relevance of social diffusion to individual and collective improvement will be discussed briefly, with an emphasis on educational applications.
On control of discrete-time state-dependent jump linear systems with probabilistic constraints: A receding horizon approach
Venue: arXiv cs.SY 2014
Year: 2014

In this article, we consider a receding horizon control of discrete-time state-dependent jump linear systems, particular kind of stochastic switching systems, subject to possibly unbounded random disturbances and probabilistic state constraints. Due to a nature of the dynamical system and the constraints, we consider a one-step receding horizon. Using inverse cumulative distribution function, we convert the probabilistic state constraints to deterministic constraints, and obtain a tractable deterministic receding horizon control problem. We consider the receding control law to have a linear state-feedback and an admissible offset term. We ensure mean square boundedness of the state variable via solving linear matrix inequalities off-line, and solve the receding horizon control problem on-line with control offset terms. We illustrate the overall approach applied on a macroeconomic system.
Robust Precoding for Network MIMO with Hierarchical CSIT
Venue: arXiv cs.IT 2014
Year: 2014

In this work, we consider a wireless network with K cooperating transmitters (TXs) serving jointly K receivers (RXs). Due to the practical limitations of the backhaul network, it is relevant to consider a setting where each TX receives its own imperfect estimate of the multi-user channel state, denoted as the distributed channel state information (CSI) setting. We focus in this work on a particular distributed CSI configuration called hierarchical CSI configuration in which the TXs can be ordered by increasing level of CSI. This scenario is particularly relevant for future networks with heterogeneous backhaul where the TXs connected with a weak backhaul link will receive only a coarse estimate while the TXs with a stronger backhaul will have a more accurate CSI. In that scenario, we formulate the optimal precoding as a team decision problem. Solving optimally this problem is extremely challenging such that we propose a heuristic approach allowing to obtain a simple, yet efficient and practical, precoding algorithm. The proposed precoding algorithm exploits the hierarchical structure of the CSI to make the transmission more robust to the imperfect CSI knowledge at the TXs.
Recommending Items in Social Tagging Systems Using Tag and Time Information
Venue: arXiv cs.IR 2014
Year: 2014

In this work we present a novel item recommendation approach that aims at improving Collaborative Filtering (CF) in social tagging systems using the information about tags and time. Our algorithm follows a two-step approach, where in the first step a potentially interesting candidate item-set is found using user-based CF and in the second step this candidate item-set is ranked using item-based CF. Within this ranking step we integrate the information of tag usage and time using the Base-Level Learning (BLL) equation coming from human memory theory that is used to determine the reuse-probability of words and tags using a power-law forgetting function. As the results of our extensive evaluation conducted on data-sets gathered from three social tagging systems (BibSonomy, CiteULike and MovieLens) show, the usage of tag-based and time information via the BLL equation also helps to improve the ranking and recommendation process of items and thus, can be used to realize an effective item recommender that outperforms two alternative algorithms which also exploit time and tag-based information.
Subjective and Objective Quality Assessment of Image: A Survey
Venue: arXiv cs.MM 2014
Year: 2014

With the increasing demand for image-based applications, the efficient and reliable evaluation of image quality has increased in importance. Measuring the image quality is of fundamental importance for numerous image processing applications, where the goal of image quality assessment (IQA) methods is to automatically evaluate the quality of images in agreement with human quality judgments. Numerous IQA methods have been proposed over the past years to fulfill this goal. In this paper, a survey of the quality assessment methods for conventional image signals, as well as the newly emerged ones, which includes the high dynamic range (HDR) and 3-D images, is presented. A comprehensive explanation of the subjective and objective IQA and their classification is provided. Six widely used subjective quality datasets, and performance measures are reviewed. Emphasis is given to the full-reference image quality assessment (FR-IQA) methods, and 9 often-used quality measures (including mean squared error (MSE), structural similarity index (SSIM), multi-scale structural similarity index (MS-SSIM), visual information fidelity (VIF), most apparent distortion (MAD), feature similarity measure (FSIM), feature similarity measure for color images (FSIMC), dynamic range independent measure (DRIM), and tone-mapped images quality index (TMQI)) are carefully described, and their performance and computation time on four subjective quality datasets are evaluated. Furthermore, a brief introduction to 3-D IQA is provided and the issues related to this area of research are reviewed.
Regional Pilot Study to Evaluate e-Readiness and Local e-Government Services
Venue: arXiv cs.CY 2014
Year: 2014

The concept of local e-Government has become a key factor for delivering services in an efficient, cost effective, transparent and convenient way, in circumstances where a) citizens do not have enough time available to communicate with local authorities in order to perform their responsibilities and needs, and b) information and communication technologies significantly facilitate administrative procedures and citizens-government interaction. This paper aims to identify e-services that local authorities provide, and to investigate their readiness for delivering these services. A pilot research has been conducted to identify the offer of e-services by local authorities, along with e-readiness in municipalities of the Pelagonia region in the Republic of Macedonia. The survey was carried out by means of structured interview questions based on a modified model proposed by Partnership on Measuring ICT for Development - web analysis of municipal websites in the region has been conducted, as well. The study reveals uneven distribution according to the age group of users, lack of reliability and confidence for processing the needs and requests electronically by a large part of the population, and improperly developed set of ICT tools by local governments for providing a variety of services that can be fully processed electronically.
Navigating Robot Swarms Using Collective Intelligence Learned from Golden Shiner Fish
Venue: arXiv cs.NE 2014
Year: 2014

Navigating networked robot swarms often requires knowing where to go, sensing the environment, and path-planning based on the destination and barriers in the environment. Such a process is computationally intensive. Moreover, as the network scales up, the computational load increases quadratically, or even exponentially. Unlike these man-made systems, most biological systems scale linearly in complexity. Furthermore, the scale of a biological swarm can even enable collective intelligence. One example comes from observations of golden shiner fish. Golden shiners naturally prefer darkness and school together. Each individual golden shiner does not know where the darkness is. Neither does it sense the light gradients in the environment. However, by moving together as a school, they always end up in the shady area. We apply such collective intelligence learned from golden shiner fish to navigating robot swarms. Each individual robot's dynamic is based on the gold shiners' movement strategy---a random walk with its speed modulated by the light intensity and its direction affected by its neighbors. The theoretical analysis and simulation results show that our method 1) promises to navigate a robot swarm with little situational knowledge, 2) simplifies control and decision-making for each individual robot, 3) requires minimal or even no information exchange within the swarm, and 4) is highly distributed, adaptive, and robust.
Toward Software Measurement and Quality Analysis of MARF and GIPSY Case Studies a Team 13 SOEN6611-S14 Project Report
Venue: arXiv cs.SE 2014
Year: 2014

It is no longer a debate that quality is an essential requirement in any software product, especially in a highly competitive market and a context of mission critical product. To obtain better product quality, software metrics are the only reliable indicators provided to assess and measure this attribute of a software product. Several metrics have been elaborated but none of them were really convenient in an object oriented ecosystem. However, the MOOD metrics have proven their efficiency in gauging the software quality at system level, while CK Metrics measure the quality of software at class level . These metrics, well suited for Object-Oriented design, allow measuring object oriented design properties such as coupling, cohesion, encapsulation, Inheritance and polymorphism. The goal of the present study is using the mentioned metrics to assess the quality of two different case studies, MARF and GIPSY. For this purpose, different tools such as McCabe, Logiscope and, JDeodorant have been used to measure the quality of these projects by implementing in different manners the metrics composing the CK and MOOD suite metrics, whilst MARFCAT has been used to detect vulnerable code files in both case studies. The present study puts the light on the strengths of these tools to measure the quality of proven and largely researched software products.
A betweenness structure entropy of complex networks
Venue: arXiv cs.SI 2014
Year: 2014

The structure entropy is an important index to illuminate the structure property of the complex network. Most of the existing structure entropies are based on the degree distribution of the complex network. But the structure entropy based on the degree can not illustrate the structure property of the weighted networks. In order to study the structure property of the weighted networks, a new structure entropy of the complex networks based on the betweenness is proposed in this paper. Comparing with the existing structure entropy, the proposed method is more reasonable to describe the structure property of the complex weighted networks.
Differential privacy for counting queries: can Bayes estimation help uncover the true value?
Venue: arXiv cs.DB 2014
Year: 2014

Differential privacy is achieved by the introduction of Laplacian noise in the response to a query, establishing a precise trade-off between the level of differential privacy and the accuracy of the database response (via the amount of noise introduced). Multiple queries may improve the accuracy but erode the privacy budget. We examine the case where we submit just a single counting query. We show that even in that case a Bayesian approach may be used to improve the accuracy for the same amount of noise injected, if we know the size of the database and the probability of a positive response to the query.
Effect of node mobility on AOMDV protocol in MANET
Venue: arXiv cs.NI 2014
Year: 2014

In this paper, we have analyzed the effect of node mobility on the performance of AOMDV multipath routing protocol. This routing protocol in ad hoc network has been analyzed with random way point mobility model only. This is not sufficient to evaluate the behavior of a routing protocol. Therefore, in this paper, we have considered Random waypoint, Random Direction and Probabilistic Random Walk mobility Model for performance analysis of AOMDV protocol. The result reveals that packet delivery ratio decreases with the increasing node mobility for all mobility models. Also, average end-to-end delay is also vary with varying node speed, initially upto 20 nodes in all mobility models delay is minimum.