OpenRaiser/Intern-Atlas huggingface dataset:
IT based social media impacts on Indonesian general legislative elections 2014
Venue: arXiv cs.CY 2014
Year: 2014

The information technology applications in cyberspace (the internet) are currently dominated by social media. The author investigates and explores the advantages of social media implementation of any political party in Indonesian general legislative elections 2014. There are twelve national political parties participating in the election as contestants plus three local political parties in Aceh. In this research, author focus on national political parties only. The author visited, analyzed, and learnt the social media used by the contestants. Those social media are : 1) Facebook, 2) Twitter, and 3) YouTube. Author also compares the popularity of political parties on social media with the results of a real count. Then Author can discuss : 1) the impact of social media on political parties, 2) social media as a brand of political parties, 3) social media as political presentation, and 4) social media as virtual society. The results of this study indicate that Facebook is still a social media application that received high attention by the voters on a campaign of political parties. Indonesian's legislative elections won by parties that are using social media as part of their campaigns.
Smart city analysis using spatial data and predicting the sustainability
Venue: arXiv cs.CY 2014
Year: 2014

Smart city [1] planning is crucial as it should balance among resources and the needs of the city .It allows to achieve good eco-friendly industries, there by supporting both the nature and the stake holders. Setting up an industry is a difficult problem, because it should optimize the resources and allocating it in an effective manner. Weighted sum approach [2] uses the spatial data for finding appropriate places to set up the industry based on the weight assigned to each constraint. The user can predict the possible places in the search space, where the industry can be set with low time complexity using spatial data. Diversity being introduced by using multipoint crossover and mutation operations. It will help to bring exploration in the search space, thereby bring the diversity factor into the solution space. The prediction approach will help to avoid the human exploitation on nature for resources. This in turn helps the investors to maximize the Return on Investment (ROI).
Pilot Decontamination in CMT-based Massive MIMO Networks
Venue: arXiv cs.IT 2014
Year: 2014

Pilot contamination problem in massive MIMO networks operating in time-division duplex (TDD) mode can limit their expected capacity to a great extent. This paper addresses this problem in cosine modulated multitone (CMT) based massive MIMO networks; taking advantage of their so-called blind equalization property. We extend and apply the blind equalization technique from single antenna case to multi-cellular massive MIMO systems and show that it can remove the channel estimation errors (due to pilot contamination effect) without any need for cooperation between different cells or transmission of additional training information. Our numerical results advocate the efficacy of the proposed blind technique in improving the channel estimation accuracy and removal of the residual channel estimation errors caused by the users of the other cells.
Application Specific Cache Simulation Analysis for Application Specific Instruction set Processor
Venue: arXiv cs.AR 2014
Year: 2014

An Efficient Simulation of application specific instruction-set processors (ASIP) is a challenging onus in the area of VLSI design. This paper reconnoiters the possibility of use of ASIP simulators for ASIP Simulation. This proposed study allow as the simulation of the cache memory design with various ASIP simulators like Simple scalar and VEX. In this paper we have implemented the memory configuration according to desire application. These simulators performs the cache related results such as cache name, sets, cache associativity, cache block size, cache replacement policy according to specific application.
Twitter and Polls: Analyzing and estimating political orientation of Twitter users in India General #Elections2014
Venue: arXiv cs.SI 2014
Year: 2014

This year (2014) in the month of May, the tenure of the 15th Lok Sabha was to end and the elections to the 543 parliamentary seats were to be held. A whooping $5 billion were spent on these elections, which made us stand second only to the US Presidential elections in terms of money spent. Swelling number of Internet users and Online Social Media (OSM) users could effect 3-4% of urban population votes as per a report of IAMAI (Internet & Mobile Association of India). Our count of tweets related to elections from September 2013 to May 2014, was close to 18.21 million. We analyzed the complete dataset and found that the activity on Twitter peaked during important events. It was evident from our data that the political behavior of the politicians affected their followers count. Yet another aim of our work was to find an efficient way to classify the political orientation of the users on Twitter. We used four different techniques: two were based on the content of the tweets, one on the user based features and another based on community detection algorithm on the retweet and user mention networks. We found that the community detection algorithm worked best. We built a portal to show the analysis of the tweets of the last 24 hours. To the best of our knowledge, this is the first academic pursuit to analyze the elections data and classify the users in the India General Elections 2014.
Pushdown flow analysis with abstract garbage collection
Venue: arXiv cs.PL 2014
Year: 2014

In the static analysis of functional programs, pushdown flow analysis and abstract garbage collection push the boundaries of what we can learn about programs statically. This work illuminates and poses solutions to theoretical and practical challenges that stand in the way of combining the power of these techniques. Pushdown flow analysis grants unbounded yet computable polyvariance to the analysis of return-flow in higher-order programs. Abstract garbage collection grants unbounded polyvariance to abstract addresses which become unreachable between invocations of the abstract contexts in which they were created. Pushdown analysis solves the problem of precisely analyzing recursion in higher-order languages; abstract garbage collection is essential in solving the "stickiness" problem. Alone, our benchmarks demonstrate that each method can reduce analysis times and boost precision by orders of magnitude. We combine these methods. The challenge in marrying these techniques is not subtle: computing the reachable control states of a pushdown system relies on limiting access during transition to the top of the stack; abstract garbage collection, on the other hand, needs full access to the entire stack to compute a root set, just as concrete collection does. Conditional pushdown systems were developed for just such a conundrum, but existing methods are ill-suited for the dynamic nature of garbage collection. We show fully precise and approximate solutions to the feasible paths problem for pushdown garbage-collecting control-flow analysis. Experiments reveal synergistic interplay between garbage collection and pushdown techniques, and the fusion demonstrates "better-than-both-worlds" precision.
Optimizing the Social Cost of Congestion Games by Imposing Variable Delays
Venue: arXiv cs.GT 2014
Year: 2014

We describe a new coordination mechanism for non-atomic congestion games that leads to a (selfish) social cost which is arbitrarily close to the non-selfish optimal. This mechanism does not incur any additional extra cost, like tolls, which are usually differentiated from the social cost as expressed in terms of delays only.
Implementation of Tic-Tac-Toe Game in LabVIEW
Venue: arXiv cs.OH 2014
Year: 2014

Tic-Tac-Toe game can be played by two players where the square block (3 x 3) can be filled with a cross (X) or a circle (O). The game will toggle between the players by giving the chance for each player to mark their move. When one of the players make a combination of 3 same markers in a horizontal, vertical or diagonal line the program will display which player has won, whether X or O. In this paper, we implement a 3x3 tic-tac-toe game in LabVIEW. The game is designed so that two players can play tic-tac-toe using LabVIEW software. The program will contain a display function and a select function to place the symbol as well as toggle between the symbols allowing each player a turn to play the game. The program will update after each player makes their move and check for the conditions of game as it goes on. Overall program works without any bugs and is able to use
Elimination of a Second-Law-attack, and all cable-resistance-based attacks, in the Kirchhoff-law-Johnson-noise (KLJN) secure key exchange system
Venue: arXiv cs.ET 2014
Year: 2014

We introduce the so far most efficient attack against the Kirchhoff-law-Johnson-noise (KLJN) secure key exchange system. This attack utilizes the lack of exact thermal equilibrium in practical applications and is based on cable resistance losses and the fact that the Second Law of Thermodynamics cannot provide full security when such losses are present. The new attack does not challenge the unconditional security of the KLJN scheme, but it puts more stringent demands on the security/privacy enhancing protocol than for any earlier attack. In this paper we present a simple defense protocol to fully eliminate this new attack by increasing the noise-temperature at the side of the smaller resistance value over the noise-temperature at the at the side with the greater resistance. It is shown that this simple protocol totally removes Eve's information not only for the new attack but also for the old Bergou-Scheuer-Yariv attack. The presently most efficient attacks against the KLJN scheme are thereby completely nullified.
R-CNNs for Pose Estimation and Action Detection
Venue: arXiv cs.CV 2014
Year: 2014

We present convolutional neural networks for the tasks of keypoint (pose) prediction and action classification of people in unconstrained images. Our approach involves training an R-CNN detector with loss functions depending on the task being tackled. We evaluate our method on the challenging PASCAL VOC dataset and compare it to previous leading approaches. Our method gives state-of-the-art results for keypoint and action prediction. Additionally, we introduce a new dataset for action detection, the task of simultaneously localizing people and classifying their actions, and present results using our approach.
Bounds on Eigenvalues of a Spatial Correlation Matrix
Venue: arXiv cs.IT 2014
Year: 2014

It is critical to understand the properties of spatial correlation matrices in massive multiple-input multiple-output (MIMO) systems. We derive new bounds on the extreme eigenvalues of a spatial correlation matrix that is characterized by the exponential model in this paper. The new upper bound on the maximum eigenvalue is tighter than the previous known bound. Moreover, numerical studies show that our new lower bound on the maximum eigenvalue is close to the true maximum eigenvalue in most cases. We also derive an upper bound on the minimum eigenvalue that is also tight. These bounds can be exploited to analyze many wireless communication scenarios including uniform planar arrays, which are expected to be widely used for massive MIMO systems.
Effective Capacity of Cognitive Radio Links: Accessing Primary Feedback Erroneously
Venue: arXiv cs.IT 2014
Year: 2014

We study the performance of a cognitive system modeled by one secondary and one primary link and operating under statistical quality of service (QoS) delay constraints. We analyze the effective capacity (EC) to quantify the secondary user (SU) performance under delay constraints. The SU intends to maximize the benefit of the feedback messages on the primary link to reduce SU interference for primary user (PU) and makes opportunistic use of the channel to transmit his packets. We assume that SU has erroneous access to feedback information of PU. We propose a three power level scheme and study the tradeoff between degradation in EC of SU and reliability of PU defined as the success rate of the transmitted packets. Our analysis shows that increase in error in feedback access causes more interference to PU and packet success rate decreases correspondingly.
A QoS-Aware Scheduling Algorithm for High-Speed Railway Communication System
Venue: arXiv cs.NI 2014
Year: 2014

With the rapid development of high-speed railway (HSR), how to provide the passengers with multimedia services has attracted increasing attention. A key issue is to develop an effective scheduling algorithm for multiple services with different quality of service (QoS) requirements. In this paper, we investigate the downlink service scheduling problem in HSR network taking account of end-to-end deadline constraints and successfully packet delivery ratio requirements. Firstly, by exploiting the deterministic high-speed train trajectory, we present a time-distance mapping in order to obtain the highly dynamic link capacity effectively. Next, a novel service model is developed for deadline constrained services with delivery ratio requirements, which enables us to turn the delivery ratio requirement into a single queue stability problem. Based on the Lyapunov drift, the optimal scheduling problem is formulated and the corresponding scheduling service algorithm is proposed by stochastic network optimization approach. Simulation results show that the proposed algorithm outperforms the conventional schemes in terms of QoS requirements.
Playing with Duality: An Overview of Recent Primal-Dual Approaches for Solving Large-Scale Optimization Problems
Venue: arXiv cs.NA 2014
Year: 2014

Optimization methods are at the core of many problems in signal/image processing, computer vision, and machine learning. For a long time, it has been recognized that looking at the dual of an optimization problem may drastically simplify its solution. Deriving efficient strategies which jointly brings into play the primal and the dual problems is however a more recent idea which has generated many important new contributions in the last years. These novel developments are grounded on recent advances in convex analysis, discrete optimization, parallel processing, and non-smooth optimization with emphasis on sparsity issues. In this paper, we aim at presenting the principles of primal-dual approaches, while giving an overview of numerical methods which have been proposed in different contexts. We show the benefits which can be drawn from primal-dual algorithms both for solving large-scale convex optimization problems and discrete ones, and we provide various application examples to illustrate their usefulness.
The Multidimensional Assessment of Scholarly Research Impact
Venue: arXiv cs.DL 2014
Year: 2014

This article introduces the Multidimensional Research Assessment Matrix of scientific output. Its base notion holds that the choice of metrics to be applied in a research assessment process depends upon the unit of assessment, the research dimension to be assessed, and the purposes and policy context of the assessment. An indicator may by highly useful within one assessment process, but less so in another. For instance, publication counts are useful tools to help discriminating between those staff members who are research active, and those who are not, but are of little value if active scientists are to be compared one another according to their research performance. This paper gives a systematic account of the potential usefulness and limitations of a set of 10 important metrics including altmetrics, applied at the level of individual articles, individual researchers, research groups and institutions. It presents a typology of research impact dimensions, and indicates which metrics are the most appropriate to measure each dimension. It introduces the concept of a meta-analysis of the units under assessment in which metrics are not used as tools to evaluate individual units, but to reach policy inferences regarding the objectives and general setup of an assessment process.
Kinetic Reverse $k$-Nearest Neighbor Problem
Venue: arXiv cs.CG 2014
Year: 2014

This paper provides the first solution to the kinetic reverse $k$-nearest neighbor (\rknn) problem in $\mathbb{R}^d$, which is defined as follows: Given a set $P$ of $n$ moving points in arbitrary but fixed dimension $d$, an integer $k$, and a query point $q\notin P$ at any time $t$, report all the points $p\in P$ for which $q$ is one of the $k$-nearest neighbors of $p$.
SurveyMan: Programming and Automatically Debugging Surveys
Venue: arXiv cs.PL 2014
Year: 2014

Surveys can be viewed as programs, complete with logic, control flow, and bugs. Word choice or the order in which questions are asked can unintentionally bias responses. Vague, confusing, or intrusive questions can cause respondents to abandon a survey. Surveys can also have runtime errors: inattentive respondents can taint results. This effect is especially problematic when deploying surveys in uncontrolled settings, such as on the web or via crowdsourcing platforms. Because the results of surveys drive business decisions and inform scientific conclusions, it is crucial to make sure they are correct. We present SurveyMan, a system for designing, deploying, and automatically debugging surveys. Survey authors write their surveys in a lightweight domain-specific language aimed at end users. SurveyMan statically analyzes the survey to provide feedback to survey authors before deployment. It then compiles the survey into JavaScript and deploys it either to the web or a crowdsourcing platform. SurveyMan's dynamic analyses automatically find survey bugs, and control for the quality of responses. We evaluate SurveyMan's algorithms analytically and empirically, demonstrating its effectiveness with case studies of social science surveys conducted via Amazon's Mechanical Turk.
An Epitome of Multi Secret Sharing Schemes for General Access Structure
Venue: arXiv cs.CR 2014
Year: 2014

Secret sharing schemes are widely used now a days in various applications, which need more security, trust and reliability. In secret sharing scheme, the secret is divided among the participants and only authorized set of participants can recover the secret by combining their shares. The authorized set of participants are called access structure of the scheme. In Multi-Secret Sharing Scheme (MSSS), k different secrets are distributed among the participants, each one according to an access structure. Multi-secret sharing schemes have been studied extensively by the cryptographic community. Number of schemes are proposed for the threshold multi-secret sharing and multi-secret sharing according to generalized access structure with various features. In this survey we explore the important constructions of multi-secret sharing for the generalized access structure with their merits and demerits. The features like whether shares can be reused, participants can be enrolled or dis-enrolled efficiently, whether shares have to modified in the renewal phase etc., are considered for the evaluation.
Natural Color Image Enhancement based on Modified Multiscale Retinex Algorithm and Performance Evaluation usingWavelet Energy
Venue: arXiv cs.CV 2014
Year: 2014

This paper presents a new color image enhancement technique based on modified MultiScale Retinex(MSR) algorithm and visual quality of the enhanced images are evaluated using a new metric, namely, wavelet energy. The color image enhancement is achieved by down sampling the value component of HSV color space converted image into three scales (normal, medium and fine) following the contrast stretching operation. These down sampled value components are enhanced using the MSR algorithm. The value component is reconstructed by averaging each pixels of the lower scale image with that of the upper scale image subsequent to up sampling the lower scale image. This process replaces dark pixel by the average pixels of both the lower scale and upper scale, while retaining the bright pixels. The quality of the reconstructed images in the proposed method is found to be good and far better then the other researchers method. The performance of the proposed scheme is evaluated using new wavelet domain based assessment criterion, referred as wavelet energy. This scheme computes the energy of both original and enhanced image in wavelet domain. The number of edge details as well as wavelet energy is less in a poor quality image compared with naturally enhanced image. Experimental results presented confirms that the proposed wavelet energy based color image quality assessment technique efficiently characterizes both the local and global details of enhanced image.
Lost in Abstraction: Monotonicity in Multi-Threaded Programs (Extended Technical Report)
Venue: arXiv cs.PL 2014
Year: 2014

Monotonicity in concurrent systems stipulates that, in any global state, extant system actions remain executable when new processes are added to the state. This concept is not only natural and common in multi-threaded software, but also useful: if every thread's memory is finite, monotonicity often guarantees the decidability of safety property verification even when the number of running threads is unknown. In this paper, we show that the act of obtaining finite-data thread abstractions for model checking can be at odds with monotonicity: Predicate-abstracting certain widely used monotone software results in non-monotone multi-threaded Boolean programs - the monotonicity is lost in the abstraction. As a result, well-established sound and complete safety checking algorithms become inapplicable; in fact, safety checking turns out to be undecidable for the obtained class of unbounded-thread Boolean programs. We demonstrate how the abstract programs can be modified into monotone ones, without affecting safety properties of the non-monotone abstraction. This significantly improves earlier approaches of enforcing monotonicity via overapproximations.
Publicly Verifiable Outsourced Computation with a Key Distribution Centre
Venue: arXiv cs.CR 2014
Year: 2014

The combination of software-as-a-service and the increasing use of mobile devices gives rise to a considerable difference in computational power between servers and clients. Thus, there is a desire for clients to outsource the evaluation of complex functions to a server and to be able to verify that the resulting value is correct. Previous work in this area of Publicly Verifiable Outsourced Computation (PVC) requires a costly pre-processing stage. However, in many practical situations multiple clients will be interested in the same set of core functions and will make use of the same servers. Thus, the pre-processing phase may be performed many more times than is necessary. In this paper we introduce a Key Distribution Center (KDC) that handles the generation and distribution of the keys that are required to support PVC, thereby eliminating this redundancy. We define a number of new security models and functionalities that arise with the introduction of the KDC, and present a construction of such a scheme built upon Key-Policy Attribute-based Encryption.