OpenRaiser/Intern-Atlas huggingface dataset:
A Note on Program Specialization. What Can Syntactical Properties of Residual Programs Reveal?
Venue: arXiv cs.PL 2012
Year: 2012

The paper presents two examples of non-traditional using of program specialization by Turchin's supercompilation method. In both cases we are interested in syntactical properties of residual programs produced by supercompilation. In the first example we apply supercompilation to a program encoding a word equation and as a result we obtain a program representing a graph describing the solution set of the word equation. The idea of the second example belongs to Alexandr V. Korlyukov. He considered an interpreter simulating the dynamic of the well known missionaries-cannibals puzzle. Supercompilation of the interpreter allows us to solve the puzzle. The interpreter may also be seen as an encoding of a non-deterministic protocol.
Controlling and securing a Digital Home using Multiple Sensor Based Perception system Integrated with Mobile and Voice technology
Venue: arXiv cs.OH 2012
Year: 2012

Fully controlled digital home had always been considered as a luxury of rich people because of excessive cost to install the system. It is now within the reach of mass people with lots of inexpensive cool features. In this paper we have designed and developed a very low cost, efficient and reliable Digital home system. Fully Controlled Digital Home is no more a Luxury. Our proposed system made it affordable. We built a low-cost feature-rich Digital Home System (DHS). Digital Home System is combination of automated services i.e. Electronic Device Controller, IR Security System, Web Desktop, Remote Video Surveillance System and Virtual Mobile by which we can control our home by avoiding old manual processes e.g. our physical presence at home is optional. The System provides some of the modern luxury & security features to us. Now we can control Light, fan, AC or any electronic devices by voice command, Blue-tooth, GPRS or Website. To control the system remotely, GPRS connectivity is added. We can also monitor our home from remote area by using Remote Video Surveillance System. This enables live video into mobile device of the digital home. Moreover, we can also access our PC and do the necessary tasks from any internet enabled computer in the world by using Web Desktop which is specially built for this purpose. Furthermore, access of unauthorized person in the home will be notified by SMS & store the image of the person and also generate a voice alarm. So that ensures the security of our valuable things. Also we can identify and monitor the location of our valuable assets e.g. precious metals remotely. Finally, Virtual mobile application is a Universal mobile Driver by which we can exactly perform some same task e.g. Remote call, Phone book access, SMS read-write of our mobile device from our new invented computer's virtual mobile.
Flow-Level Stability of Wireless Networks: Separation of Congestion Control and Packet Scheduling
Venue: arXiv cs.NI 2012
Year: 2012

It is by now well-known that wireless networks with file arrivals and departures are stable if one uses alpha-fair congestion control and back-pressure based scheduling and routing. In this paper, we examine whether ?alpha-fair congestion control is necessary for flow-level stability. We show that stability can be ensured even with very simple congestion control mechanisms, such as a fixed window size scheme which limits the maximum number of packets that are allowed into the ingress queue of a flow. A key ingredient of our result is the use of the difference between the logarithms of queue lengths as the link weights. This result is reminiscent of results in the context of CSMA algorithms, but for entirely different reasons.
Feature selection with test cost constraint
Venue: arXiv cs.AI 2012
Year: 2012

Feature selection is an important preprocessing step in machine learning and data mining. In real-world applications, costs, including money, time and other resources, are required to acquire the features. In some cases, there is a test cost constraint due to limited resources. We shall deliberately select an informative and cheap feature subset for classification. This paper proposes the feature selection with test cost constraint problem for this issue. The new problem has a simple form while described as a constraint satisfaction problem (CSP). Backtracking is a general algorithm for CSP, and it is efficient in solving the new problem on medium-sized data. As the backtracking algorithm is not scalable to large datasets, a heuristic algorithm is also developed. Experimental results show that the heuristic algorithm can find the optimal solution in most cases. We also redefine some existing feature selection problems in rough sets, especially in decision-theoretic rough sets, from the viewpoint of CSP. These new definitions provide insight to some new research directions.
Managing Complex Structured Data In a Fast Evolving Environment
Venue: arXiv cs.DB 2012
Year: 2012

Criminal data comes in a variety of formats, mandated by state, federal, and international standards. Specifying the data in a unified fashion is necessary for any system that intends to integrate with state, federal, and international law enforcement agencies. However, the contents, format, and structure of the data is highly inconsistent across jurisdictions, and each datum requires different ways of being printed, transmitted, and displayed. The goal was to design a system that is unified in its approach to specify data, and is amenable to future "unknown unknowns". We have developed a domain-specific language in Common Lisp which allows the specification of complex data with evolving formats and structure, and is inter-operable with the Common Lisp language. The resultant system has enabled the easy handling of complex evolving information in the general criminal data environment and has made it possible to manage and extend the system in a high-paced market. The language has allowed the principal product of Secure Outcomes Inc. to enjoy success with over 50 users throughout the United States.
Sampling Error Analysis and Properties of Non-bandlimited Signals That Are Reconstructed by Generalized Sinc Functions
Venue: arXiv cs.IT 2012
Year: 2012

Recently efforts have been made to use generalized sinc functions to perfectly reconstruct various kinds of non-bandlimited signals. As a consequence, perfect reconstruction sampling formulas have been established using such generalized sinc functions. This article studies the error of the reconstructed non-bandlimited signal when an adaptive truncation scheme is employed. Further, when there are noises present in the samples, estimation on the expectation and variance of the error pertinent to the reconstructed signal is also given. Finally discussed are the reproducing properties and the Sobolev smoothness of functions in the space of non-bandlimited signals that admits such a sampling formula.
Automatic Unbounded Verification of Alloy Specifications with Prover9
Venue: arXiv cs.FL 2012
Year: 2012

Alloy is an increasingly popular lightweight specification language based on relational logic. Alloy models can be automatically verified within a bounded scope using off-the-shelf SAT solvers. Since false assertions can usually be disproved using small counter-examples, this approach suffices for most applications. Unfortunately, it can sometimes lead to a false sense of security, and in critical applications a more traditional unbounded proof may be required. The automatic theorem prover Prover9 has been shown to be particularly effective for proving theorems of relation algebras [7], a quantifier-free (or point-free) axiomatization of a fragment of relational logic. In this paper we propose a translation from Alloy specifications to fork algebras (an extension of relation algebras with the same expressive power as relational logic) which enables their unbounded verification in Prover9. This translation covers not only logic assertions, but also the structural aspects (namely type declarations), and was successfully implemented and applied to several examples.
Appcessory Economics: Enabling loosely coupled hardware / software innovation
Venue: arXiv cs.CY 2012
Year: 2012

An appcessory (app + accessory) is a smart phone accessory that is combined with a specially written app to perform a useful function. An example is a toy helicopter controlled by a smart phone app: the full value proposition involves both new hardware outside the phone and new software running inside the phone. Like the smart phone itself and like a PC, the appcessory hardware is a platform: it has the property that it becomes even more valuable if innovative new software is written for it. It is technically possible that innovation in the appcessory space becomes loosely coupled, with different parties specializing to innovate on either the hardware (accessory) side or the software (app) side. However, we are not seeing this loose coupling yet in the current market. We argue that the reason for this is economical: a market framework in which loosely coupled software parties are adequately rewarded is not yet in place. We describe a technical solution for creating the needed market framework, consisting of an automated micropayment system by which money can flow from appcessory hardware makers to app software innovators. This solution also has a broader applicability to the problem of innovation in the Internet of Things.
On Designs of Full Diversity Space-Time Block Codes for Two-User MIMO Interference Channels
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, a design criterion for space-time block codes (STBC) is proposed for two-user MIMO interference channels when a group zero-forcing (ZF) algorithm is applied at each receiver to eliminate the inter-user interference. Based on the design criterion, a design of STBC for two-user interference channels is proposed that can achieve full diversity for each user with the group ZF receiver. The code rate approaches one when the time delay in the encoding (or code block size) gets large. Performance results demonstrate that the full diversity can be guaranteed by our proposed STBC with the group ZF receiver.
Minimum Weight Dynamo and Fast Opinion Spreading
Venue: arXiv cs.SI 2012
Year: 2012

We consider the following multi--level opinion spreading model on networks. Initially, each node gets a weight from the set [0..k-1], where such a weight stands for the individuals conviction of a new idea or product. Then, by proceeding to rounds, each node updates its weight according to the weights of its neighbors. We are interested in the initial assignments of weights leading each node to get the value k-1 --e.g. unanimous maximum level acceptance-- within a given number of rounds. We determine lower bounds on the sum of the initial weights of the nodes under the irreversible simple majority rules, where a node increases its weight if and only if the majority of its neighbors have a weight that is higher than its own one. Moreover, we provide constructive tight upper bounds for some class of regular topologies: rings, tori, and cliques.
DAARIA: Driver Assistance by Augmented Reality for Intelligent Automobile
Venue: arXiv cs.HC 2012
Year: 2012

Taking into account the drivers' state is a major challenge for designing new advanced driver assistance systems. In this paper we present a driver assistance system strongly coupled to the user. DAARIA 1 stands for Driver Assistance by Augmented Reality for Intelligent Automobile. It is an augmented reality interface powered by several sensors. The detection has two goals: one is the position of obstacles and the quantification of the danger represented by them. The other is the driver's behavior. A suitable visualization metaphor allows the driver to perceive at any time the location of the relevant hazards while keeping his eyes on the road. First results show that our method could be applied to a vehicle but also to aerospace, fluvial or maritime navigation.
From Functions to Object-Orientation by Abstraction
Venue: arXiv cs.SE 2012
Year: 2012

In previous work we developed a framework of computational models for function and object execution. The models on an higher level of abstraction in this framework allow for concurrent execution of functions and objects. We show that the computational model for object execution complies with the fundamentals of object-orientation.
Examples of Artificial Perceptions in Optical Character Recognition and Iris Recognition
Venue: arXiv cs.AI 2012
Year: 2012

This paper assumes the hypothesis that human learning is perception based, and consequently, the learning process and perceptions should not be represented and investigated independently or modeled in different simulation spaces. In order to keep the analogy between the artificial and human learning, the former is assumed here as being based on the artificial perception. Hence, instead of choosing to apply or develop a Computational Theory of (human) Perceptions, we choose to mirror the human perceptions in a numeric (computational) space as artificial perceptions and to analyze the interdependence between artificial learning and artificial perception in the same numeric space, using one of the simplest tools of Artificial Intelligence and Soft Computing, namely the perceptrons. As practical applications, we choose to work around two examples: Optical Character Recognition and Iris Recognition. In both cases a simple Turing test shows that artificial perceptions of the difference between two characters and between two irides are fuzzy, whereas the corresponding human perceptions are, in fact, crisp.
Reclassification formula that provides to surpass K-means method
Venue: arXiv cs.CV 2012
Year: 2012

The paper presents a formula for the reclassification of multidimensional data points (columns of real numbers, "objects", "vectors", etc.). This formula describes the change in the total squared error caused by reclassification of data points from one cluster into another and prompts the way to calculate the sequence of optimal partitions, which are characterized by a minimum value of the total squared error E (weighted sum of within-class variance, within-cluster sum of squares WCSS etc.), i.e. the sum of squared distances from each data point to its cluster center. At that source data points are treated with repetitions allowed, and resulting clusters from different partitions, in general case, overlap each other. The final partitions are characterized by "equilibrium" stability with respect to the reclassification of the data points, where the term "stability" means that any prescribed reclassification of data points does not increase the total squared error E. It is important that conventional K-means method, in general case, provides generation of instable partitions with overstated values of the total squared error E. The proposed method, based on the formula of reclassification, is more efficient than K-means method owing to converting of any partition into stable one, as well as involving into the process of reclassification of certain sets of data points, in contrast to the classification of individual data points according to K-means method.
Interactive Joint Transfer of Energy and Information
Venue: arXiv cs.IT 2012
Year: 2012

In some communication networks, such as passive RFID systems, the energy used to transfer information between a sender and a recipient can be reused for successive communication tasks. In fact, from known results in physics, any system that exchanges information via the transfer of given physical resources, such as radio waves, particles and qubits, can conceivably reuse, at least part, of the received resources. This paper aims at illustrating some of the new challenges that arise in the design of communication networks in which the signals exchanged by the nodes carry both information and energy. To this end, a baseline two-way communication system is considered in which two nodes communicate in an interactive fashion. In the system, a node can either send an "on" symbol (or "1"), which costs one unit of energy, or an "off" signal (or "0"), which does not require any energy expenditure. Upon reception of a "1" signal, the recipient node "harvests", with some probability, the energy contained in the signal and stores it for future communication tasks. Inner and outer bounds on the achievable rates are derived. Numerical results demonstrate the effectiveness of the proposed strategies and illustrate some key design insights.
Learning Robust Low-Rank Representations
Venue: arXiv cs.LG 2012
Year: 2012

In this paper we present a comprehensive framework for learning robust low-rank representations by combining and extending recent ideas for learning fast sparse coding regressors with structured non-convex optimization techniques. This approach connects robust principal component analysis (RPCA) with dictionary learning techniques and allows its approximation via trainable encoders. We propose an efficient feed-forward architecture derived from an optimization algorithm designed to exactly solve robust low dimensional projections. This architecture, in combination with different training objective functions, allows the regressors to be used as online approximants of the exact offline RPCA problem or as RPCA-based neural networks. Simple modifications of these encoders can handle challenging extensions, such as the inclusion of geometric data transformations. We present several examples with real data from image, audio, and video processing. When used to approximate RPCA, our basic implementation shows several orders of magnitude speedup compared to the exact solvers with almost no performance degradation. We show the strength of the inclusion of learning to the RPCA approach on a music source separation application, where the encoders outperform the exact RPCA algorithms, which are already reported to produce state-of-the-art results on a benchmark database. Our preliminary implementation on an iPad shows faster-than-real-time performance with minimal latency.
Robust Estimation in Rayleigh Fading Channels Under Bounded Channel Uncertainties
Venue: arXiv cs.IT 2012
Year: 2012

We investigate channel equalization for Rayleigh fading channels under bounded channel uncertainties. We analyze three robust methods to estimate an unknown signal transmitted through a Rayleigh fading channel, where we avoid directly tuning the equalizer parameters to the available inaccurate channel information. These methods are based on minimizing certain mean-square error criteria that incorporate the channel uncertainties into the problem formulations. We present closed-form solutions to the channel equalization problems for each method and for both zero mean and nonzero mean signals. We illustrate the performances of the equalization methods through simulations.
Partial Gaussian Graphical Model Estimation
Venue: arXiv cs.LG 2012
Year: 2012

This paper studies the partial estimation of Gaussian graphical models from high-dimensional empirical observations. We derive a convex formulation for this problem using $\ell_1$-regularized maximum-likelihood estimation, which can be solved via a block coordinate descent algorithm. Statistical estimation performance can be established for our method. The proposed approach has competitive empirical performance compared to existing methods, as demonstrated by various experiments on synthetic and real datasets.
Fast Packed String Matching for Short Patterns
Venue: arXiv cs.IR 2012
Year: 2012

Searching for all occurrences of a pattern in a text is a fundamental problem in computer science with applications in many other fields, like natural language processing, information retrieval and computational biology. In the last two decades a general trend has appeared trying to exploit the power of the word RAM model to speed-up the performances of classical string matching algorithms. In this model an algorithm operates on words of length w, grouping blocks of characters, and arithmetic and logic operations on the words take one unit of time. In this paper we use specialized word-size packed string matching instructions, based on the Intel streaming SIMD extensions (SSE) technology, to design very fast string matching algorithms in the case of short patterns. From our experimental results it turns out that, despite their quadratic worst case time complexity, the new presented algorithms become the clear winners on the average for short patterns, when compared against the most effective algorithms known in literature.
Enhanced Load Balancing Approach to Avoid Deadlocks in Cloud
Venue: arXiv cs.DC 2012
Year: 2012

The state-of-art of the technology focuses on data processing to deal with massive amount of data. Cloud computing is an emerging technology, which enables one to accomplish the aforementioned objective, leading towards improved business performance. It comprises of users requesting for the services of diverse applications from various distributed virtual servers. The cloud should provide resources on demand to its clients with high availability, scalability and with reduced cost. Load balancing is one of the essential factors to enhance the working performance of the cloud service provider. Since, cloud has inherited characteristic of distributed computing and virtualization there is a possibility of occurrence of deadlock. Hence, in this paper, a load balancing algorithm has been proposed to avoid deadlocks among the Virtual Machines (VMs) while processing the requests received from the users by VM migration. Further, this paper also provides the anticipated results with the implementation of the proposed algorithm. The deadlock avoidance enhances the number of jobs to be serviced by cloud service provider and thereby improving working performance and the business of the cloud service provider.
Comparative Analysis of dynamic graph techniques and data strucutre
Venue: arXiv cs.DS 2012
Year: 2012

Dynamically changing graphs are used in many applications of graph algorithms. The scope of these graphs are in graphics, communication networks and in VLSI designs where graphs are subjected to change, such as addition and deletion of edges and vertices. There is a rich body of the algorithms and data structures used for dynamic graphs. The paper overview the techniques and data structures used in various dynamic algorithms. The effort is tried to find out the comparison in these techniques namely the hierarchical decomposition of graphs and highlighting the ingenuity used in designing these algorithms.
Quantum Monte Carlo for large chemical systems: Implementing efficient strategies for petascale platforms and beyond
Venue: arXiv cs.PF 2012
Year: 2012

Various strategies to implement efficiently QMC simulations for large chemical systems are presented. These include: i.) the introduction of an efficient algorithm to calculate the computationally expensive Slater matrices. This novel scheme is based on the use of the highly localized character of atomic Gaussian basis functions (not the molecular orbitals as usually done), ii.) the possibility of keeping the memory footprint minimal, iii.) the important enhancement of single-core performance when efficient optimization tools are employed, and iv.) the definition of a universal, dynamic, fault-tolerant, and load-balanced computational framework adapted to all kinds of computational platforms (massively parallel machines, clusters, or distributed grids). These strategies have been implemented in the QMC=Chem code developed at Toulouse and illustrated with numerical applications on small peptides of increasing sizes (158, 434, 1056 and 1731 electrons). Using 10k-80k computing cores of the Curie machine (GENCI-TGCC-CEA, France) QMC=Chem has been shown to be capable of running at the petascale level, thus demonstrating that for this machine a large part of the peak performance can be achieved. Implementation of large-scale QMC simulations for future exascale platforms with a comparable level of efficiency is expected to be feasible.