OpenRaiser/Intern-Atlas huggingface dataset:
Storage and Search in Dynamic Peer-to-Peer Networks
Venue: arXiv cs.DC 2013
Year: 2013

We study robust and efficient distributed algorithms for searching, storing, and maintaining data in dynamic Peer-to-Peer (P2P) networks. P2P networks are highly dynamic networks that experience heavy node churn (i.e., nodes join and leave the network continuously over time). Our goal is to guarantee, despite high node churn rate, that a large number of nodes in the network can store, retrieve, and maintain a large number of data items. Our main contributions are fast randomized distributed algorithms that guarantee the above with high probability (whp) even under high adversarial churn: 1. A randomized distributed search algorithm that (whp) guarantees that searches from as many as $n - o(n)$ nodes ($n$ is the stable network size) succeed in ${O}(\log n)$-rounds despite ${O}(n/\log^{1+δ} n)$ churn, for any small constant $δ> 0$, per round. We assume that the churn is controlled by an oblivious adversary (that has complete knowledge and control of what nodes join and leave and at what time, but is oblivious to the random choices made by the algorithm). 2. A storage and maintenance algorithm that guarantees (whp) data items can be efficiently stored (with only $Θ(\log{n})$ copies of each data item) and maintained in a dynamic P2P network with churn rate up to ${O}(n/\log^{1+δ} n)$ per round. Our search algorithm together with our storage and maintenance algorithm guarantees that as many as $n - o(n)$ nodes can efficiently store, maintain, and search even under ${O}(n/\log^{1+δ} n)$ churn per round. Our algorithms require only polylogarithmic in $n$ bits to be processed and sent (per round) by each node. To the best of our knowledge, our algorithms are the first-known, fully-distributed storage and search algorithms that provably work under highly dynamic settings (i.e., high churn rates per step).
Techniques for Feature Extraction In Speech Recognition System : A Comparative Study
Venue: arXiv cs.SD 2013
Year: 2013

The time domain waveform of a speech signal carries all of the auditory information. From the phonological point of view, it little can be said on the basis of the waveform itself. However, past research in mathematics, acoustics, and speech technology have provided many methods for converting data that can be considered as information if interpreted correctly. In order to find some statistically relevant information from incoming data, it is important to have mechanisms for reducing the information of each segment in the audio signal into a relatively small number of parameters, or features. These features should describe each segment in such a characteristic way that other similar segments can be grouped together by comparing their features. There are enormous interesting and exceptional ways to describe the speech signal in terms of parameters. Though, they all have their strengths and weaknesses, we have presented some of the most used methods with their importance.
Optimizing CUDA Code By Kernel Fusion---Application on BLAS
Venue: arXiv cs.DC 2013
Year: 2013

Modern GPUs are able to perform significantly more arithmetic operations than transfers of a single word to or from global memory. Hence, many GPU kernels are limited by memory bandwidth and cannot exploit the arithmetic power of GPUs. However, the memory locality can be often improved by kernel fusion when a sequence of kernels is executed and some kernels in this sequence share data. In this paper, we show how kernels performing map, reduce or their nested combinations can be fused automatically by our source-to-source compiler. To demonstrate the usability of the compiler, we have implemented several BLAS-1 and BLAS-2 routines and show how the performance of their sequences can be improved by fusions. Compared to similar sequences using CUBLAS, our compiler is able to generate code that is up to 2.61x faster for the examples tested.
Calculation of the Performance of Communication Systems from Measured Oscillator Phase Noise
Venue: arXiv cs.IT 2013
Year: 2013

Oscillator phase noise (PN) is one of the major problems that affect the performance of communication systems. In this paper, a direct connection between oscillator measurements, in terms of measured single-side band PN spectrum, and the optimal communication system performance, in terms of the resulting error vector magnitude (EVM) due to PN, is mathematically derived and analyzed. First, a statistical model of the PN, considering the effect of white and colored noise sources, is derived. Then, we utilize this model to derive the modified Bayesian Cramer-Rao bound on PN estimation, and use it to find an EVM bound for the system performance. Based on our analysis, it is found that the influence from different noise regions strongly depends on the communication bandwidth, i.e., the symbol rate. For high symbol rate communication systems, cumulative PN that appears near carrier is of relatively low importance compared to the white PN far from carrier. Our results also show that 1/f^3 noise is more predictable compared to 1/f^2 noise and in a fair comparison it affects the performance less.
A Note on (Parallel) Depth- and Breadth-First Search by Arc Elimination
Venue: arXiv cs.DS 2013
Year: 2013

This note recapitulates an algorithmic observation for ordered Depth-First Search (DFS) in directed graphs that immediately leads to a parallel algorithm with linear speed-up for a range of processors for non-sparse graphs. The note extends the approach to ordered Breadth-First Search (BFS). With $p$ processors, both DFS and BFS algorithms run in $O(m/p+n)$ time steps on a shared-memory parallel machine allowing concurrent reading of locations, e.g., a CREW PRAM, and have linear speed-up for $p\leq m/n$. Both algorithms need $n$ synchronization steps.
Speech Enhancement Modeling Towards Robust Speech Recognition System
Venue: arXiv cs.SD 2013
Year: 2013

Form about four decades human beings have been dreaming of an intelligent machine which can master the natural speech. In its simplest form, this machine should consist of two subsystems, namely automatic speech recognition (ASR) and speech understanding (SU). The goal of ASR is to transcribe natural speech while SU is to understand the meaning of the transcription. Recognizing and understanding a spoken sentence is obviously a knowledge-intensive process, which must take into account all variable information about the speech communication process, from acoustics to semantics and pragmatics. While developing an Automatic Speech Recognition System, it is observed that some adverse conditions degrade the performance of the Speech Recognition System. In this contribution, speech enhancement system is introduced for enhancing speech signals corrupted by additive noise and improving the performance of Automatic Speech Recognizers in noisy conditions. Automatic speech recognition experiments show that replacing noisy speech signals by the corresponding enhanced speech signals leads to an improvement in the recognition accuracies. The amount of improvement varies with the type of the corrupting noise.
Achievable Rate Derivations and Further Simulation Results for "Physical-Layer Multicasting by Stochastic Transmit Beamforming and Alamouti Space-Time Coding"
Venue: arXiv cs.IT 2013
Year: 2013

This is a companion technical report of the main manuscript "Physical-Layer Multicasting by Stochastic Transmit Beamforming and Alamouti Space-Time Coding". The report serves to give detailed derivations of the achievable rate functions encountered in the main manuscript, which are too long to be included in the latter. In addition, more simulation results are presented to verify the viability of the multicast schemes developed in the main manuscript.
Speech based Password Protected Cyber Applications
Venue: arXiv cs.CY 2013
Year: 2013

Whenever we think of cyber applications, we visualize the model that gives the idea that we are sitting in front of computer at home or workplace connected to internet and performing all the work that generally we have to go and do on a specific place for example e-shopping, e-banking, e-education etc. In case of e-shopping, we view all the products on the computer screen with all details by a single mouse click, select the product and do all further money transaction through net. When we think of security, is it 100% secure? No, not at all because though it is password protected, the password is a text base secrete code that can be open. Therefore this paper is concentrated on preparation of speech based password protected applications.
Speech User Interface for Information Retrieval
Venue: arXiv cs.IR 2013
Year: 2013

Along with the rapid development of information technology, the amount of information generated at a given time far exceeds human's ability to organize, search, and manipulate without the help of automatic systems. Now a days so many tools and techniques are available for storage and retrieval of information. User uses interface to interact with these techniques, mostly text user interface (TUI) or graphical user interface (GUI). Here, I am trying to introduce a new interface i.e. speech for information retrieval. The goal of this project is to develop a speech interface that can search and read the required information from the database effectively, efficiently and more friendly. This tool will be highly useful to blind people, they will able to demand the information to the computer by giving voice command/s (keyword) through microphone and listen the required information using speaker or headphones.
On the variety of planar spirals and their applications in computer aided design
Venue: arXiv cs.GR 2013
Year: 2013

In this paper we discuss the variety of planar spiral segments and their applications in objects in both the real and artificial world. The discussed curves with monotonic curvature function are well-known in geometric modelling and computer aided geometric design as fair curves, and they are very significant in aesthetic shape modelling. Fair curve segments are used for two-point G1 and G2 Hermite interpolation, as well as for generating aesthetic splines.
Most borrowed is most cited? Library loan statistics as a proxy for monograph selection in citation indexes
Venue: arXiv cs.DL 2013
Year: 2013

This study aims to analyse whether library loans statistics can be used as a measure of monograph use and as a selection criteria for inclusion in citation indexes. For this, we conducted an exploratory study based on loan data (1000 most borrowed monographs) from two non-Anglo-Saxon European university libraries (Granada and Vienna) with strong social sciences and humanities components. Loans to scientists only were also analysed at the University of Vienna. Furthermore, citation counts for the 100 most borrowed scientific monographs (SM) and textbooks or manuals (MTB) were retrieved from Web of Science and Google Scholar. The results show considerable similarities in both libraries: the percentage of loans for books in national languages represents almost 96 per cent of the total share and SM accounts only for 10 to 13 per cent. When considering loans to scientists only, the percentage of English books increases to 30 per cent, the percentage of SM loans also increases (approx 80 per cent). Furthermore, we found no significant correlations between loans and citations. Since loan statistics are currently insufficient for measuring the use of monographs, their suggested use as an applicable selection criterion for book citation indexes is not yet feasible. Data improvement and aggregation at different levels is a challenge for modern libraries in order to enable the exploitation of this invaluable information source for scientometric purposes.
A Method for Visuo-Spatial Classification of Freehand Shapes Freely Sketched
Venue: arXiv cs.CV 2013
Year: 2013

We present the principle and the main steps of a new method for the visuo-spatial analysis of geometrical sketches recorded online. Visuo-spatial analysis is a necessary step for multi-level analysis. Multi-level analysis simultaneously allows classification, comparison or clustering of the constituent parts of a pattern according to their visuo-spatial properties, their procedural strategies, their structural or temporal parameters, or any combination of two or more of those parameters. The first results provided by this method concern the comparison of sketches to some perfect patterns of simple geometrical figures and the measure of dissimilarity between real sketches. The mean rates of good decision higher than 95% obtained are promising in both cases.
Shannon capacity of nonlinear regenerative channels
Venue: arXiv cs.IT 2013
Year: 2013

We compute Shannon capacity of nonlinear channels with regenerative elements. Conditions are found under which capacity of such nonlinear channels is higher than the Shannon capacity of the classical linear additive white Gaussian noise channel. We develop a general scheme for designing the proposed channels and apply it to the particular nonlinear sine-mapping. The upper bound for regeneration efficiency is found and the asymptotic behavior of the capacity in the saturation regime is derived.
A short note on estimating intelligence from user profiles in the context of universal psychometrics: prospects and caveats
Venue: arXiv cs.AI 2013
Year: 2013

There has been an increasing interest in inferring some personality traits from users and players in social networks and games, respectively. This goes beyond classical sentiment analysis, and also much further than customer profiling. The purpose here is to have a characterisation of users in terms of personality traits, such as openness, conscientiousness, extraversion, agreeableness, and neuroticism. While this is an incipient area of research, we ask the question of whether cognitive abilities, and intelligence in particular, are also measurable from user profiles. However, we pose the question as broadly as possible in terms of subjects, in the context of universal psychometrics, including humans, machines and hybrids. Namely, in this paper we analyse the following question: is it possible to measure the intelligence of humans and (non-human) bots in a social network or a game just from their user profiles, i.e., by observation, without the use of interactive tests, such as IQ tests, the Turing test or other more principled machine intelligence tests?
Low Complexity Indoor Localization in Wireless Sensor Networks by UWB and Inertial Data Fusion
Venue: arXiv cs.NI 2013
Year: 2013

Precise indoor localization of moving targets is a challenging activity which cannot be easily accomplished without combining different sources of information. In this sense, the combination of different data sources with an appropriate filter might improve both positioning and tracking performance. This work proposes an algorithm for hybrid positioning in Wireless Sensor Networks based on data fusion of UWB and inertial information. A constant-gain Steady State Kalman Filter is used to bound the complexity of the system, simplifying its implementation on a typical low-power WSN node. The performance of the presented data fusion algorithm has been evaluated in a realistic scenario using both simulations and realistic datasets. The obtained results prove the validity of this approach, which efficiently fuses different positioning data sources, reducing the localization error.
Optimization of stochastic database cracking
Venue: arXiv cs.DB 2013
Year: 2013

Variant Stochastic cracking is a significantly more resilient approach to adaptive indexing. It showed [1]that Stochastic cracking uses each query as a hint on how to reorganize data, but not blindly so; it gains resilience and avoids performance bottlenecks by deliberately applying certain arbitrary choices in its decision making. Therefore bring, adaptive indexing forward to a mature formulation that confers the workload-robustness that previous approaches lacked. Original cracking relies on the randomness of the workloads to converge well. [2][3] However, where the workload is non-random, cracking needs to introduce randomness on its own. Stochastic Cracking clearly improves over original cracking by being robust in workload changes while maintaining all original cracking features when it comes to adaptation. But looking at both types of cracking, it conveyed an incomplete picture as at some point of time it is must to know whether the workload is random or sequential. In this paper our focus is on optimization of variant stochastic cracking, that could be achieved in two ways either by reducing the initialization cost to make stochastic cracking even more transparent to the user, especially for queries that initiate a workload change and hence incur a higher cost or by combining the strengths of the various stochastic cracking algorithms via a dynamic component that decides which algorithm to choose for a query on the fly. The efforts have been put in to make an algorithm that reduces the initialization cost by using the main notion of both cracking, while considering the requirements of adaptive indexing [2].
A Simple Technique for the Converse of Finite Blocklength Multiple Access Channels
Venue: arXiv cs.IT 2013
Year: 2013

A converse for the Discrete Memoryless Multiple Access Channel is given. The result in [13] is refined, and the third order term is obtained. Moreover, our proof is much simpler than [13]. With little modification, the region can be further improved.
The Redundancy of Slepian-Wolf Coding Revisited
Venue: arXiv cs.IT 2013
Year: 2013

[Draft] In this paper, the redundancy of Slepian Wolf coding is revisited. Applying the random binning and converse technique in \cite{yang}, the same results in \cite{he} are obtained with much simpler proofs. Moreover, our results reflect more details about the high-order terms of the coding rate. The redundancy is investigated for both fixed-rate and variable-rate cases. The normal approximation (or dispersion) can also be obtained with minor modification.
Strong Products of Hypergraphs: Unique Prime Factorization Theorems and Algorithms
Venue: arXiv cs.DM 2013
Year: 2013

It is well-known that all finite connected graphs have a unique prime factor decomposition (PFD) with respect to the strong graph product which can be computed in polynomial time. Essential for the PFD computation is the construction of the so-called Cartesian skeleton of the graphs under investigation. In this contribution, we show that every connected thin hypergraph H has a unique prime factorization with respect to the normal and strong (hypergraph) product. Both products coincide with the usual strong graph product whenever H is a graph. We introduce the notion of the Cartesian skeleton of hypergraphs as a natural generalization of the Cartesian skeleton of graphs and prove that it is uniquely defined for thin hypergraphs. Moreover, we show that the Cartesian skeleton of hypergraphs can be determined in O(|E|^2) time and that the PFD can be computed in O(|V|^2|E|) time, for hypergraphs H = (V,E) with bounded degree and bounded rank.
Speech: A Challenge to Digital Signal Processing Technology for Human-to-Computer Interaction
Venue: arXiv cs.HC 2013
Year: 2013

This software project based paper is for a vision of the near future in which computer interaction is characterized by natural face-to-face conversations with lifelike characters that speak, emote, and gesture. The first step is speech. The dream of a true virtual reality, a complete human-computer interaction system will not come true unless we try to give some perception to machine and make it perceive the outside world as humans communicate with each other. This software project is under development for listening and replying machine (Computer) through speech. The Speech interface is developed to convert speech input into some parametric form (Speech-to-Text) for further processing and the results, text output to speech synthesis (Text-to-Speech)
Scalable Routing Easy as PIE: a Practical Isometric Embedding Protocol (Technical Report)
Venue: arXiv cs.NI 2013
Year: 2013

We present PIE, a scalable routing scheme that achieves 100% packet delivery and low path stretch. It is easy to implement in a distributed fashion and works well when costs are associated to links. Scalability is achieved by using virtual coordinates in a space of concise dimensionality, which enables greedy routing based only on local knowledge. PIE is a general routing scheme, meaning that it works on any graph. We focus however on the Internet, where routing scalability is an urgent concern. We show analytically and by using simulation that the scheme scales extremely well on Internet-like graphs. In addition, its geometric nature allows it to react efficiently to topological changes or failures by finding new paths in the network at no cost, yielding better delivery ratios than standard algorithms. The proposed routing scheme needs an amount of memory polylogarithmic in the size of the network and requires only local communication between the nodes. Although each node constructs its coordinates and routes packets locally, the path stretch remains extremely low, even lower than for centralized or less scalable state-of-the-art algorithms: PIE always finds short paths and often enough finds the shortest paths.
Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logic
Venue: arXiv cs.AI 2013
Year: 2013

In many probabilistic first-order representation systems, inference is performed by "grounding"---i.e., mapping it to a propositional representation, and then performing propositional inference. With a large database of facts, groundings can be very large, making inference and learning computationally expensive. Here we present a first-order probabilistic language which is well-suited to approximate "local" grounding: every query $Q$ can be approximately grounded with a small graph. The language is an extension of stochastic logic programs where inference is performed by a variant of personalized PageRank. Experimentally, we show that the approach performs well without weight learning on an entity resolution task; that supervised weight-learning improves accuracy; and that grounding time is independent of DB size. We also show that order-of-magnitude speedups are possible by parallelizing learning.
Quality Measures of Parameter Tuning for Aggregated Multi-Objective Temporal Planning
Venue: arXiv cs.AI 2013
Year: 2013

Parameter tuning is recognized today as a crucial ingredient when tackling an optimization problem. Several meta-optimization methods have been proposed to find the best parameter set for a given optimization algorithm and (set of) problem instances. When the objective of the optimization is some scalar quality of the solution given by the target algorithm, this quality is also used as the basis for the quality of parameter sets. But in the case of multi-objective optimization by aggregation, the set of solutions is given by several single-objective runs with different weights on the objectives, and it turns out that the hypervolume of the final population of each single-objective run might be a better indicator of the global performance of the aggregation method than the best fitness in its population. This paper discusses this issue on a case study in multi-objective temporal planning using the evolutionary planner DaE-YAHSP and the meta-optimizer ParamILS. The results clearly show how ParamILS makes a difference between both approaches, and demonstrate that indeed, in this context, using the hypervolume indicator as ParamILS target is the best choice. Other issues pertaining to parameter tuning in the proposed context are also discussed.