OpenRaiser/Intern-Atlas huggingface dataset:
Data Mining: A prediction Technique for the workers in the PR Department of Orissa (Block and Panchayat)
Venue: arXiv cs.DB 2012
Year: 2012

This paper presents the method of mining the data and which contains the information about the large information about the PR (Panchayat Raj Department)of Orissa.We have focused some of the techniques,approaches and different methodologies of the demand forecasting. Every organizations are operated in different places of the country. Each place of operation may generate a huge amount of data. In an organization, worker prediction is the difficult task of the manager. It is the complex process not only because its nature of feature prediction but also various approaches methodologies always makes user confused. This paper aims to deal with the problem selection process. In this paper we have used some of the approaches from literature are been introduced and analyzed to find its suitable organization and situation. Based on this we have designed with automatic selection function to help users make a prejudgment. This information about each approach will be showed to users with examples to help understanding. This system also provides calculation function to help users work out a predication result. Generally the new developed system has a more comprehensive functions compared with existing ones. It aims to improve the accuracy of demand forecasting by implementing the forecasting algorithm. While it is still a decision support system with no ability of make the final judgment.This type of huge amount of data are are available in the form of different ways which has drastically changed in the areas of science and engineering.To analyze, manage and make a decision of such type of huge amount of data we need techniques called the data mining which will transforming in many fields. We have implemented the algorithms in JAVA technology. This paper provides the prediction algorithm Linear Regression, result which will helpful in the further research.
Hierarchic Power Allocation for Spectrum Sharing in OFDM-Based Cognitive Radio Networks
Venue: arXiv cs.GT 2012
Year: 2012

In this paper, a Stackelberg game is built to model the hierarchic power allocation of primary user (PU) network and secondary user (SU) network in OFDM-based cognitive radio (CR) networks. We formulate the PU and the SUs as the leader and the followers, respectively. We consider two constraints: the total power constraint and the interference-to-signal ratio (ISR) constraint, in which the ratio between the accumulated interference and the received signal power at each PU should not exceed certain threshold. Firstly, we focus on the single-PU and multi-SU scenario. Based on the analysis of the Stackelberg Equilibrium (SE) for the proposed Stackelberg game, an analytical hierarchic power allocation method is proposed when the PU can acquire the additional information to anticipate SUs' reaction. The analytical algorithm has two steps: 1) The PU optimizes its power allocation with considering the reaction of SUs to its action. In the power optimization of the PU, there is a sub-game for power allocation of SUs given fixed transmit power of the PU. The existence and uniqueness for the Nash Equilibrium (NE) of the sub-game are investigated. We also propose an iterative algorithm to obtain the NE, and derive the closed-form solutions of NE for the perfectly symmetric channel. 2) The SUs allocate the power according to the NE of the sub-game given PU's optimal power allocation. Furthermore, we design two distributed iterative algorithms for the general channel even when private information of the SUs is unavailable at the PU. The first iterative algorithm has a guaranteed convergence performance, and the second iterative algorithm employs asynchronous power update to improve time efficiency. Finally, we extend to the multi-PU and multi-SU scenario, and a distributed iterative algorithm is presented.
Multi-User Detection in Multibeam Mobile Satellite Systems: A Fair Performance Evaluation
Venue: arXiv cs.IT 2012
Year: 2012

Multi-User Detection (MUD) techniques are currently being examined as promising technologies for the next generation of broadband, interactive, multibeam, satellite communication (SatCom) systems. Results in the existing literature have shown that when full frequency and polarization reuse is employed and user signals are jointly processed at the gateway, more than threefold gains in terms of spectral efficiency over conventional systems can be obtained. However, the information theoretic results for the capacity of the multibeam satellite channel, are given under ideal assumptions, disregarding the implementation constraints of such an approach. Considering a real system implementation, the adoption of full resource reuse is bound to increase the payload complexity and power consumption. Since the novel techniques require extra payload resources, fairness issues in the comparison among the two approaches arise. The present contribution evaluates in a fair manner, the performance of the return link (RL) of a SatCom system serving mobile users that are jointly decoded at the receiver. More specifically, the achievable spectral efficiency of the assumed system is compared to a conventional system under the constraint of equal physical layer resource utilization. Furthermore, realistic link budgets for the RL of mobile SatComs are presented, thus allowing the comparison of the systems in terms of achievable throughput. Since the proposed systems operate under the same payload requirements as the conventional systems, the comparison can be regarded as fair. Finally, existing analytical formulas are also employed to provide closed form descriptions of the performance of clustered multibeam MUD, thus introducing insights on how the performance scales with respect to the system parameters.
Application-tailored Linear Algebra Algorithms: A search-based Approach
Venue: arXiv cs.MS 2012
Year: 2012

In this paper, we tackle the problem of automatically generating algorithms for linear algebra operations by taking advantage of problem-specific knowledge. In most situations, users possess much more information about the problem at hand than what current libraries and computing environments accept; evidence shows that if properly exploited, such information leads to uncommon/unexpected speedups. We introduce a knowledge-aware linear algebra compiler that allows users to input matrix equations together with properties about the operands and the problem itself; for instance, they can specify that the equation is part of a sequence, and how successive instances are related to one another. The compiler exploits all this information to guide the generation of algorithms, to limit the size of the search space, and to avoid redundant computations. We applied the compiler to equations arising as part of sensitivity and genome studies; the algorithms produced exhibit, respectively, 100- and 1000-fold speedups.
Power Allocation Strategies for Fixed-Gain Half-Duplex Amplify-and-Forward Relaying in Nakagami-m Fading
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we study power allocation strategies for a fixed-gain amplify-and-forward relay network employing multiple relays. We consider two optimization problems for the relay network: 1) optimal power allocation to maximize the end-to-end signal-to-noise ratio (SNR) and 2) minimizing the total consumed power while maintaining the end-to-end SNR over a threshold value. We investigate these two problems for two relaying protocols of all-participate relaying and selective relaying and multiple cases of available channel state information (CSI) at the relays. We show that the SNR maximization problem is concave and the power minimization problem is convex for all protocols and CSI cases considered. We obtain closed-form expressions for the two problems in the case for full CSI and CSI of all the relay-destination links at the relays and solve the problems through convex programming when full CSI or CSI of the relay-destination links are not available at the relays. Numerical results show the benefit of having full CSI at the relays for both optimization problems. However, they also show that CSI overhead can be reduced by having only partial CSI at the relays with only a small degradation in performance.
Design of Calibration Experiments for Identification of Manipulator Elastostatic Parameters
Venue: arXiv cs.RO 2012
Year: 2012

The paper is devoted to the elastostatic calibration of industrial robots, which is used for precise machining of large-dimensional parts made of composite materials. In this technological process, the interaction between the robot and the workpiece causes essential elastic deflections of the manipulator components that should be compensated by the robot controller using relevant elastostatic model of this mechanism. To estimate parameters of this model, an advanced calibration technique is applied that is based on the non-linear experiment design theory, which is adopted for this particular application. In contrast to previous works, it is proposed a concept of the user-defined test-pose, which is used to evaluate the calibration experiments quality. In the frame of this concept, the related optimization problem is defined and numerical routines are developed, which allow generating optimal set of manipulator configurations and corresponding forces/torques for a given number of the calibration experiments. Some specific kinematic constraints are also taken into account, which insure feasibility of calibration experiments for the obtained configurations and allow avoiding collision between the robotic manipulator and the measurement equipment. The efficiency of the developed technique is illustrated by an application example that deals with elastostatic calibration of the serial manipulator used for robot-based machining.
A semantic association page rank algorithm for web search engines
Venue: arXiv cs.IR 2012
Year: 2012

The majority of Semantic Web search engines retrieve information by focusing on the use of concepts and relations restricted to the query provided by the user. By trying to guess the implicit meaning between these concepts and relations, probabilities are calculated to give the pages a score for ranking. In this study, I propose a relation-based page rank algorithm to be used as a Semantic Web search engine. Relevance is measured as the probability of finding the connections made by the user at the time of the query, as well as the information contained in the base knowledge of the Semantic Web environment. By the use of "virtual links" between the concepts in a page, which are obtained from the knowledge base, we can connect concepts and components of a page and increase the probability score for a better ranking. By creating these connections, this study also looks to eliminate the possibility of getting results equal to zero, and to provide a tie-breaker solution when two or more pages obtain the same score.
Tracking and Quantifying Censorship on a Chinese Microblogging Site
Venue: arXiv cs.IR 2012
Year: 2012

We present measurements and analysis of censorship on Weibo, a popular microblogging site in China. Since we were limited in the rate at which we could download posts, we identified users likely to participate in sensitive topics and recursively followed their social contacts. We also leveraged new natural language processing techniques to pick out trending topics despite the use of neologisms, named entities, and informal language usage in Chinese social media. We found that Weibo dynamically adapts to the changing interests of its users through multiple layers of filtering. The filtering includes both retroactively searching posts by keyword or repost links to delete them, and rejecting posts as they are posted. The trend of sensitive topics is short-lived, suggesting that the censorship is effective in stopping the "viral" spread of sensitive issues. We also give evidence that sensitive topics in Weibo only scarcely propagate beyond a core of sensitive posters.
Lessons Learned From Microkernel Verification -- Specification is the New Bottleneck
Venue: arXiv cs.SE 2012
Year: 2012

Software verification tools have become a lot more powerful in recent years. Even verification of large, complex systems is feasible, as demonstrated in the L4.verified and Verisoft XT projects. Still, functional verification of large software systems is rare - for reasons beyond the large scale of verification effort needed due to the size alone. In this paper we report on lessons learned for verification of large software systems based on the experience gained in microkernel verification in the Verisoft XT project. We discuss a number of issues that impede widespread introduction of formal verification in the software life-cycle process.
CTGEN - a Unit Test Generator for C
Venue: arXiv cs.SE 2012
Year: 2012

We present a new unit test generator for C code, CTGEN. It generates test data for C1 structural coverage and functional coverage based on pre-/post-condition specifications or internal assertions. The generator supports automated stub generation, and data to be returned by the stub to the unit under test (UUT) may be specified by means of constraints. The typical application field for CTGEN is embedded systems testing; therefore the tool can cope with the typical aliasing problems present in low-level C, including pointer arithmetics, structures and unions. CTGEN creates complete test procedures which are ready to be compiled and run against the UUT. In this paper we describe the main features of CTGEN, their technical realisation, and we elaborate on its performance in comparison to a list of competing test generation tools. Since 2011, CTGEN is used in industrial scale test campaigns for embedded systems code in the automotive domain.
Measuring Time in Sporting Competitions with the Domain-Specific Language EasyTime
Venue: arXiv cs.PL 2012
Year: 2012

Measuring time in mass sporting competitions is unthinkable manually today because of their long duration and unreliability. Besides, automatic timing devices based on the RFID technology have become cheaper. However, these devices cannot operate stand-alone. To work efficiently, they need a computer timing system for monitoring results. Such system should be capable of processing the incoming events, encoding and assigning results to a individual competitor, sorting results according to the achieved time and printing them. In this paper, a domain-specific language named EasyTime will be defined. It enables controlling an agent by writing events to a database. Using the agent, the number of measuring devices can be reduced. Also, EasyTime is of a universal type that can be applied to many different sporting competitions
Intégration des intergiciels de grilles de PC dans le nuage SlapOS : le cas de BOINC
Venue: arXiv cs.DC 2012
Year: 2012

In this article we describe the problems and solutions related to the integration of desktop grid middleware in a cloud, in this case the open source SlapOS cloud. We focus on the issues about recipes that describe the integration and the problem of the confinement of execution. They constitute two aspects of service-oriented architecture and Cloud Computing. These two issues solved with SlapOS are not in relation to what is traditionally done in the clouds because we do not rely on virtual machines and, there is no data center (as defined in cloud). Moreover, we show that from the initial deployment model we take into account not only Web applications, B2B applications... but also applications from the field of grids; here desktop grid middleware which is a case study.
Complexity Measures for Map-Reduce, and Comparison to Parallel Computing
Venue: arXiv cs.DC 2012
Year: 2012

The programming paradigm Map-Reduce and its main open-source implementation, Hadoop, have had an enormous impact on large scale data processing. Our goal in this expository writeup is two-fold: first, we want to present some complexity measures that allow us to talk about Map-Reduce algorithms formally, and second, we want to point out why this model is actually different from other models of parallel programming, most notably the PRAM (Parallel Random Access Memory) model. We are looking for complexity measures that are detailed enough to make fine-grained distinction between different algorithms, but which also abstract away many of the implementation details.
A contraction theory-based analysis of the stability of the Extended Kalman Filter
Venue: arXiv cs.SY 2012
Year: 2012

The contraction properties of the Extended Kalman Filter, viewed as a deterministic observer for nonlinear systems, are analyzed. This yields new conditions under which exponential convergence of the state error can be guaranteed. As contraction analysis studies the evolution of an infinitesimal discrepancy between neighboring trajectories, and thus stems from a differential framework, the sufficient convergence conditions are different from the ones that previously appeared in the literature, which were derived in a Lyapunov framework. This article sheds another light on the theoretical properties of this popular observer.
Asymptotic Properties of Likelihood Based Linear Modulation Classification Systems
Venue: arXiv cs.IT 2012
Year: 2012

The problem of linear modulation classification using likelihood based methods is considered. Asymptotic properties of most commonly used classifiers in the literature are derived. These classifiers are based on hybrid likelihood ratio test (HLRT) and average likelihood ratio test (ALRT), respectively. Both a single-sensor setting and a multi-sensor setting that uses a distributed decision fusion approach are analyzed. For a modulation classification system using a single sensor, it is shown that HLRT achieves asymptotically vanishing probability of error (Pe) whereas the same result cannot be proven for ALRT. In a multi-sensor setting using soft decision fusion, conditions are derived under which Pe vanishes asymptotically. Furthermore, the asymptotic analysis of the fusion rule that assumes independent sensor decisions is carried out.
An Equivalence between Network Coding and Index Coding
Venue: arXiv cs.IT 2012
Year: 2012

We show that the network coding and index coding problems are equivalent. This equivalence holds in the general setting which includes linear and non-linear codes. Specifically, we present an efficient reduction that maps a network coding instance to an index coding one while preserving feasibility. Previous connections were restricted to the linear case.
Examining users preferences towards vertical graphical toolbars in simple search and point tasks
Venue: arXiv cs.HC 2012
Year: 2012

The main purpose of this study was to investigate the nature of preferences and their relation to the objective measures in simple direct manipulation tasks involving both the cognitive process as well as the visually guided pointing activities. The conducted experiment was concerned with the graphical structures resembling toolbars widely used in graphical interfaces. The influence of the graphical panel location, panel configuration as well as the target size on the user task efficiency and subjects' preferences were examined. The participants were requested to express their attitudes towards the tested panels before and after the efficiency examination. This subjective evaluation was carried out within the framework of Analytic Hierarchy Process (AHP; Saaty, 1977; 1980). The subjective results that were obtained showed significant differences in the subjects' preferences towards examined panels before and after completing the tasks. It seems that the users are able to comparatively quickly change their minds after gaining some experience with the investigated stimuli. Additionally, the applied cluster analysis revealed that the subjects were not homogenous in their opinions, and they formed groups having similar preference structures.
The effects of graphical interface design characteristics on human-computer interaction task efficiency
Venue: arXiv cs.HC 2012
Year: 2012

The main objective of this paper was to investigate the effects of a computer screen interface design and its related geometrical characteristics of 36 graphical objects on a user's task efficiency. A total of 490 subjects took part in laboratory experiments that focused on the direct manipulation of a visual dialogue between a user and a computer. The subjects were asked to select an object from among a group of items randomly placed on the computer screen that were visible exclusively during the visual search process. A model expressing the mean object acquisition time as a function of graphical object size and the configuration was developed and statistically validated. The model showed an influence of geometrical design characteristics of the graphical objects (icons) and their groupings (icon structures) on the observed task efficiency. The reported results can be used at those stages of a software lifecycle that concentrate on prototyping, designing, and implementing graphical solutions for the efficient graphical user-computer interface.
Cooperative Sparsity Pattern Recovery in Distributed Networks Via Distributed-OMP
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we consider the problem of collaboratively estimating the sparsity pattern of a sparse signal with multiple measurement data in distributed networks. We assume that each node makes Compressive Sensing (CS) based measurements via random projections regarding the same sparse signal. We propose a distributed greedy algorithm based on Orthogonal Matching Pursuit (OMP), in which the sparse support is estimated iteratively while fusing indices estimated at distributed nodes. In the proposed distributed framework, each node has to perform less number of iterations of OMP compared to the sparsity index of the sparse signal. Thus, with each node having a very small number of compressive measurements, a significant performance gain in support recovery is achieved via the proposed collaborative scheme compared to the case where each node estimates the sparsity pattern independently and then fusion is performed to get a global estimate. We further extend the algorithm to estimate the sparsity pattern in a binary hypothesis testing framework, where the algorithm first detects the presence of a sparse signal collaborating among nodes with a fewer number of iterations of OMP and then increases the number of iterations to estimate the sparsity pattern only if the signal is detected.
Classification Recouvrante Basée sur les Méthodes à Noyau
Venue: arXiv cs.LG 2012
Year: 2012

Overlapping clustering problem is an important learning issue in which clusters are not mutually exclusive and each object may belongs simultaneously to several clusters. This paper presents a kernel based method that produces overlapping clusters on a high feature space using mercer kernel techniques to improve separability of input patterns. The proposed method, called OKM-K(Overlapping $k$-means based kernel method), extends OKM (Overlapping $k$-means) method to produce overlapping schemes. Experiments are performed on overlapping dataset and empirical results obtained with OKM-K outperform results obtained with OKM.
A New Automatic Method to Adjust Parameters for Object Recognition
Venue: arXiv cs.CV 2012
Year: 2012

To recognize an object in an image, the user must apply a combination of operators, where each operator has a set of parameters. These parameters must be well adjusted in order to reach good results. Usually, this adjustment is made manually by the user. In this paper we propose a new method to automate the process of parameter adjustment for an object recognition task. Our method is based on reinforcement learning, we use two types of agents: User Agent that gives the necessary information and Parameter Agent that adjusts the parameters of each operator. Due to the nature of reinforcement learning the results do not depend only on the system characteristics but also on the user favorite choices.