OpenRaiser/Intern-Atlas huggingface dataset:
Indoor 3D Video Monitoring Using Multiple Kinect Depth-Cameras
Venue: arXiv cs.CV 2014
Year: 2014

This article describes the design and development of a system for remote indoor 3D monitoring using an undetermined number of Microsoft(R) Kinect sensors. In the proposed client-server system, the Kinect cameras can be connected to different computers, addressing this way the hardware limitation of one sensor per USB controller. The reason behind this limitation is the high bandwidth needed by the sensor, which becomes also an issue for the distributed system TCP/IP communications. Since traffic volume is too high, 3D data has to be compressed before it can be sent over the network. The solution consists in selfcoding the Kinect data into RGB images and then using a standard multimedia codec to compress color maps. Information from different sources is collected into a central client computer, where point clouds are transformed to reconstruct the scene in 3D. An algorithm is proposed to merge the skeletons detected locally by each Kinect conveniently, so that monitoring of people is robust to self and inter-user occlusions. Final skeletons are labeled and trajectories of every joint can be saved for event reconstruction or further analysis.
Application of Selective Algorithm for Effective Resource Provisioning in Cloud Computing Environment
Venue: arXiv cs.DC 2014
Year: 2014

Modern day continued demand for resource hungry services and applications in IT sector has led to development of Cloud computing. Cloud computing environment involves high cost infrastructure on one hand and need high scale computational resources on the other hand. These resources need to be provisioned (allocation and scheduling) to the end users in most efficient manner so that the tremendous capabilities of cloud are utilized effectively and efficiently. In this paper we discuss a selective algorithm for allocation of cloud resources to end-users on-demand basis. This algorithm is based on min-min and max-min algorithms. These are two conventional task scheduling algorithm. The selective algorithm uses certain heuristics to select between the two algorithms so that overall makespan of tasks on the machines is minimized. The tasks are scheduled on machines in either space shared or time shared manner. We evaluate our provisioning heuristics using a cloud simulator, called CloudSim. We also compared our approach to the statistics obtained when provisioning of resources was done in First-Cum-First- Serve(FCFS) manner. The experimental results show that overall makespan of tasks on given set of VMs minimizes significantly in different scenarios.
The Four Principles of Geographic Routing
Venue: arXiv cs.DC 2014
Year: 2014

Geographic routing consists in using the position information of nodes to assist in the routing process, and has been a widely studied subject in sensor networks. One of the outstanding challenges facing geographic routing has been its applicability. Authors either make some broad assumptions on an idealized version of wireless networks which are often unverifiable, or they use costly methods to planarize the communication graph. The overarching questions that drive us are the following. When, and how should we use geographic routing? Is there a criterion to tell whether a communication network is fit for geographic routing? When exactly does geographic routing make sense? In this paper we formulate the four principles that define geographic routing and explore their topological consequences. Given a localized communication network, we then define and compute its geographic eccentricity, which measures its fitness for geographic routing. Finally we propose a distributed algorithm that either enables geographic routing on the network or proves that its geographic eccentricity is too high.
Efficient Legendre moment computation for grey level images
Venue: arXiv cs.CV 2014
Year: 2014

Legendre orthogonal moments have been widely used in the field of image analysis. Because their computation by a direct method is very time expensive, recent efforts have been devoted to the reduction of computational complexity. Nevertheless, the existing algorithms are mainly focused on binary images. We propose here a new fast method for computing the Legendre moments, which is not only suitable for binary images but also for grey levels. We first set up the recurrence formula of one-dimensional (1D) Legendre moments by using the recursive property of Legendre polynomials. As a result, the 1D Legendre moments of order p, Lp = Lp(0), can be expressed as a linear combination of Lp-1(1) and Lp-2(0). Based on this relationship, the 1D Legendre moments Lp(0) is thus obtained from the array of L1(a) and L0(a) where a is an integer number less than p. To further decrease the computation complexity, an algorithm, in which no multiplication is required, is used to compute these quantities. The method is then extended to the calculation of the two-dimensional Legendre moments Lpq. We show that the proposed method is more efficient than the direct method.
Set-Membership Adaptive Constant Modulus Algorithm with a Generalized Sidelobe Canceler and Dynamic Bounds for Beamforming
Venue: arXiv cs.IT 2014
Year: 2014

In this work, we propose an adaptive set-membership constant modulus (SM-CM) algorithm with a generalized sidelobe canceler (GSC) structure for blind beamforming. We develop a stochastic gradient (SG) type algorithm based on the concept of SM filtering for adaptive implementation. The filter weights are updated only if the constraint cannot be satisfied. In addition, we also propose an extension of two schemes of time-varying bounds for beamforming with a GSC structure and incorporate parameter and interference dependence to characterize the environment which improves the tracking performance of the proposed algorithm in dynamic scenarios. A convergence analysis of the proposed adaptive SM filtering techniques is carried out. Simulation results show that the proposed adaptive SM-CM-GSC algorithm with dynamic bounds achieves superior performance to previously reported methods at a reduced update rate.
Parallel WiSARD object tracker: a ram-based tracking system
Venue: arXiv cs.CV 2014
Year: 2014

This paper proposes the Parallel WiSARD Object Tracker (PWOT), a new object tracker based on the WiSARD weightless neural network that is robust against quantization errors. Object tracking in video is an important and challenging task in many applications. Difficulties can arise due to weather conditions, target trajectory and appearance, occlusions, lighting conditions and noise. Tracking is a high-level application and requires the object location frame by frame in real time. This paper proposes a fast hybrid image segmentation (threshold and edge detection) in YcbCr color model and a parallel RAM based discriminator that improves efficiency when quantization errors occur. The original WiSARD training algorithm was changed to allow the tracking.
Executable Refinement Types
Venue: arXiv cs.PL 2014
Year: 2014

This dissertation introduces executable refinement types, which refine structural types by semi-decidable predicates, and establishes their metatheory and accompanying implementation techniques. These results are useful for undecidable type systems in general. Particular contributions include: (1) Type soundness and a logical relation for extensional equivalence for executable refinement types (though type checking is undecidable); (2) hybrid type checking for executable refinement types, which blends static and dynamic checks in a novel way, in some sense performing better statically than any decidable approximation; (3) a type reconstruction algorithm - reconstruction is decidable even though type checking is not, when suitably redefined to apply to undecidable type systems; (4) a novel use of existential types with dependent types to ensure that the language of logical formulae is closed under type checking (5) a prototype implementation, Sage, of executable refinement types such that all dynamic errors are communicated back to the compiler and are thenceforth static errors.
Concept Trees: Building Dynamic Concepts from Semi-Structured Data using Nature-Inspired Methods
Venue: arXiv cs.IR 2014
Year: 2014

This paper describes a method for creating structure from heterogeneous sources, as part of an information database, or more specifically, a 'concept base'. Structures called 'concept trees' can grow from the semi-structured sources when consistent sequences of concepts are presented. They might be considered to be dynamic databases, possibly a variation on the distributed Agent-Based or Cellular Automata models, or even related to Markov models. Semantic comparison of text is required, but the trees can be built more, from automatic knowledge and statistical feedback. This reduced model might also be attractive for security or privacy reasons, as not all of the potential data gets saved. The construction process maintains the key requirement of generality, allowing it to be used as part of a generic framework. The nature of the method also means that some level of optimisation or normalisation of the information will occur. This gives comparisons with databases or knowledge-bases, but a database system would firstly model its environment or datasets and then populate the database with instance values. The concept base deals with a more uncertain environment and therefore cannot fully model it beforehand. The model itself therefore evolves over time. Similar to databases, it also needs a good indexing system, where the construction process provides memory and indexing structures. These allow for more complex concepts to be automatically created, stored and retrieved, possibly as part of a more cognitive model. There are also some arguments, or more abstract ideas, for merging physical-world laws into these automatic processes.
Automata Theory Meets Barrier Certificates: Temporal Logic Verification of Nonlinear Systems
Venue: arXiv cs.FL 2014
Year: 2014

We consider temporal logic verification of (possibly nonlinear) dynamical systems evolving over continuous state spaces. Our approach combines automata-based verification and the use of so-called barrier certificates. Automata-based verification allows the decomposition the verification task into a finite collection of simpler constraints over the continuous state space. The satisfaction of these constraints in turn can be (potentially conservatively) proved by appropriately constructed barrier certificates. As a result, our approach, together with optimization-based search for barrier certificates, allows computational verification of dynamical systems against temporal logic properties while avoiding explicit abstractions of the dynamics as commonly done in literature.
Language Heedless of Logic - Philosophy Mindful of What? Failures of Distributive and Absorption Laws
Venue: arXiv cs.CL 2014
Year: 2014

Much of philosophical logic and all of philosophy of language make empirical claims about the vernacular natural language. They presume semantics under which `and' and `or' are related by the dually paired distributive and absorption laws. However, at least one of each pair of laws fails in the vernacular. `Implicature'-based auxiliary theories associated with the programme of H.P. Grice do not prove remedial. Conceivable alternatives that might replace the familiar logics as descriptive instruments are briefly noted: (i) substructural logics and (ii) meaning composition in linear algebras over the reals, occasionally constrained by norms of classical logic. Alternative (ii) locates the problem in violations of one of the idempotent laws. Reasons for a lack of curiosity about elementary and easily testable implications of the received theory are considered. The concept of `reflective equilibrium' is critically examined for its role in reconciling normative desiderata and descriptive commitments.
Learning the Latent State Space of Time-Varying Graphs
Venue: arXiv cs.SI 2014
Year: 2014

From social networks to Internet applications, a wide variety of electronic communication tools are producing streams of graph data; where the nodes represent users and the edges represent the contacts between them over time. This has led to an increased interest in mechanisms to model the dynamic structure of time-varying graphs. In this work, we develop a framework for learning the latent state space of a time-varying email graph. We show how the framework can be used to find subsequences that correspond to global real-time events in the Email graph (e.g. vacations, breaks, ...etc.). These events impact the underlying graph process to make its characteristics non-stationary. Within the framework, we compare two different representations of the temporal relationships; discrete vs. probabilistic. We use the two representations as inputs to a mixture model to learn the latent state transitions that correspond to important changes in the Email graph structure over time.
Martta: A C++ Language Workbench
Venue: arXiv cs.PL 2014
Year: 2014

Language-orientated programming promises to elevate programmer productivity through increased abstrac- tion capabilities. Structural programming environments provide apparatus to reduce the difficulties with syntax. The language workbench, a conceptual combination of these two approaches, is a comparatively novel approach to software development and has so far been attempted only in dynamic-dispatch, run-time-compiled languages (e.g. Java). However, it must be remembered that several fields of engineering exist, each having their own priorities. In the video games industry, where large, complex and diverse projects are routinely developed, efficiency is paramount and as such C++, as a development platform, is widely used. I explore the possibility of a language workbench capable of a gradual transition in both skills and code from the traditional C++ development environment. This article is the design for a language workbench. It uses novel techniques including a context-sensitive event- driven input system and a hybrid single/multiple-inherited class model and through a prototype implementation demon- strates that is both concise and practical for C++. I refute the hitherto implicit hypothesis that the language workbench paradigm is not applicable to the C++ language, showing that C++ can be used for creating an effective development framework usable in otherwise pure-C++ programming environments.
A Bootstrap Theory: the SEMAT Kernel Itself as Runnable Software
Venue: arXiv cs.SE 2014
Year: 2014

The SEMAT kernel is a thoroughly thought generic framework for Software Engineering system development in practice. But one should be able to test its characteristics by means of a no less generic theory matching the SEMAT kernel. This paper claims that such a matching theory is attainable and describes its main principles. The conceptual starting point is the robustness of the Kernel alphas to variations in the nature of the software system, viz. to software automation, distribution and self-evolution. From these and from observed Kernel properties follows the proposed bootstrap principle: a software system theory should itself be a runnable software. Thus, the kernel alphas can be viewed as a top-level ontology, indeed the Essence of Software Engineering. Among the interesting consequences of this bootstrap theory, the observable system characteristics can now be formally tested. For instance, one can check the system completeness, viz. that software system modules fulfill each one of the system requirements.
V2V communication survey wireless technology
Venue: arXiv cs.NI 2014
Year: 2014

This paper presents the specific application of wireless communication,automotive Wireless Communication also called as Vehicle to Vehicle Communication.It explains the technology used for automotive Wireless Communication along with the various automotive applications relying on wireless communication. Automotive Wireless Communication gives drivers a sixth sense to know whats going on around them to help avoid accidents and improve traffic flow.The paper also describes VANETS (vehicular adhoc networks) and real world test network implementation.Finally,the paper is summarized.
Quantum codes from affine variety codes and their subfield-subcodes
Venue: arXiv cs.IT 2014
Year: 2014

We use affine variety codes and their subfield-subcodes for obtaining quantum stabilizer codes via the CSS code construction. With this procedure, we get codes with good parameters and a code whose parameters exceed the CSS quantum Gilbert-Varshamov bound given by Feng and Ma.
Towards 3-Dimensional Rewriting Theory
Venue: arXiv cs.LO 2014
Year: 2014

String rewriting systems have proved very useful to study monoids. In good cases, they give finite presentations of monoids, allowing computations on those and their manipulation by a computer. Even better, when the presentation is confluent and terminating, they provide one with a notion of canonical representative of the elements of the presented monoid. Polygraphs are a higher-dimensional generalization of this notion of presentation, from the setting of monoids to the much more general setting of n-categories. One of the main purposes of this article is to give a progressive introduction to the notion of higher-dimensional rewriting system provided by polygraphs, and describe its links with classical rewriting theory, string and term rewriting systems in particular. After introducing the general setting, we will be interested in proving local confluence for polygraphs presenting 2-categories and introduce a framework in which a finite 3-dimensional rewriting system admits a finite number of critical pairs.
Approximate Dynamic Programming based on Projection onto the (min,+) subsemimodule
Venue: arXiv cs.SY 2014
Year: 2014

We develop a new Approximate Dynamic Programming (ADP) method for infinite horizon discounted reward Markov Decision Processes (MDP) based on projection onto a subsemimodule. We approximate the value function in terms of a $(\min,+)$ linear combination of a set of basis functions whose $(\min,+)$ linear span constitutes a subsemimodule. The projection operator is closely related to the Fenchel transform. Our approximate solution obeys the $(\min,+)$ Projected Bellman Equation (MPPBE) which is different from the conventional Projected Bellman Equation (PBE). We show that the approximation error is bounded in its $L_\infty$-norm. We develop a Min-Plus Approximate Dynamic Programming (MPADP) algorithm to compute the solution to the MPPBE. We also present the proof of convergence of the MPADP algorithm and apply it to two problems, a grid-world problem in the discrete domain and mountain car in the continuous domain.
Spatial Performance Analysis and Design Principles for Wireless Peer Discovery
Venue: arXiv cs.IT 2014
Year: 2014

In wireless peer-to-peer networks that serve various proximity-based applications, peer discovery is the key to identifying other peers with which a peer can communicate and an understanding of its performance is fundamental to the design of an efficient discovery operation. This paper analyzes the performance of wireless peer discovery through comprehensively considering the wireless channel, spatial distribution of peers, and discovery operation parameters. The average numbers of successfully discovered peers are expressed in closed forms for two widely used channel models, i.e., the interference limited Nakagami-m fading model and the Rayleigh fading model with nonzero noise, when peers are spatially distributed according to a homogeneous Poisson point process. These insightful expressions lead to the design principles for the key operation parameters including the transmission probability, required amount of wireless resources, level of modulation and coding scheme (MCS), and transmit power. Furthermore, the impact of shadowing on the spatial performance and suggested design principles is evaluated using mathematical analysis and simulations.
Concept Based vs. Pseudo Relevance Feedback Performance Evaluation for Information Retrieval System
Venue: arXiv cs.IR 2014
Year: 2014

This article evaluates the performance of two techniques for query reformulation in a system for information retrieval, namely, the concept based and the pseudo relevance feedback reformulation. The experiments performed on a corpus of Arabic text have allowed us to compare the contribution of these two reformulation techniques in improving the performance of an information retrieval system for Arabic texts.
Efficient Network Generation Under General Preferential Attachment
Venue: arXiv cs.SI 2014
Year: 2014

Preferential attachment (PA) models of network structure are widely used due to their explanatory power and conceptual simplicity. PA models are able to account for the scale-free degree distributions observed in many real-world large networks through the remarkably simple mechanism of sequentially introducing nodes that attach preferentially to high-degree nodes. The ability to efficiently generate instances from PA models is a key asset in understanding both the models themselves and the real networks that they represent. Surprisingly, little attention has been paid to the problem of efficient instance generation. In this paper, we show that the complexity of generating network instances from a PA model depends on the preference function of the model, provide efficient data structures that work under any preference function, and present empirical results from an implementation based on these data structures. We demonstrate that, by indexing growing networks with a simple augmented heap, we can implement a network generator which scales many orders of magnitude beyond existing capabilities ($10^6$ -- $10^8$ nodes). We show the utility of an efficient and general PA network generator by investigating the consequences of varying the preference functions of an existing model. We also provide "quicknet", a freely-available open-source implementation of the methods described in this work.
Model Predictive HVAC Control with Online Occupancy Model
Venue: arXiv cs.SY 2014
Year: 2014

This paper presents an occupancy-predicting control algorithm for heating, ventilation, and air conditioning (HVAC) systems in buildings. It incorporates the building's thermal properties, local weather predictions, and a self-tuning stochastic occupancy model to reduce energy consumption while maintaining occupant comfort. Contrasting with existing approaches, the occupancy model requires no manual training and adapts to changes in occupancy patterns during operation. A prediction-weighted cost function provides conditioning of thermal zones before occupancy begins and reduces system output before occupancy ends. Simulation results with real-world occupancy data demonstrate the algorithm's effectiveness.
Enhancing Dictionary Based Preprocessing For Better Text Compression
Venue: arXiv cs.IT 2014
Year: 2014

With the rapid growing of data and number of applications, there is a crucial need of dictionary based reversible transformation techniques to increase the efficiency of the compression algorithms and hence contribute towards the enhancement in compression ratio. Performance analysis of compression methods in combination with the various transformation techniques is obtained for different text files of varying sizes. The popular block sorting lossless Burrows Wheeler Compression Algorithm (BWCA) is implemented along with one proposed method. For efficient compression a dictionary based transformation algorithm is also developed. It is observed that much increase in terms of compression ratio is attained when a source file is preprocessed with dictionary and then applied to BWCA and the proposed method.