OpenRaiser/Intern-Atlas huggingface dataset:
Frame Interpretation and Validation in a Open Domain Dialogue System
Venue: arXiv cs.CL 2012
Year: 2012

Our goal in this paper is to establish a means for a dialogue platform to be able to cope with open domains considering the possible interaction between the embodied agent and humans. To this end we present an algorithm capable of processing natural language utterances and validate them against knowledge structures of an intelligent agent's mind. Our algorithm leverages dialogue techniques in order to solve ambiguities and acquire knowledge about unknown entities.
Joint Access Point Selection and Power Allocation for Uplink Wireless Networks
Venue: arXiv cs.IT 2012
Year: 2012

We consider the distributed uplink resource allocation problem in a multi-carrier wireless network with multiple access points (APs). Each mobile user can optimize its own transmission rate by selecting a suitable AP and by controlling its transmit power. Our objective is to devise suitable algorithms by which mobile users can jointly perform these tasks in a distributed manner. Our approach relies on a game theoretic formulation of the joint power control and AP selection problem. In the proposed game, each user is a player with an associated strategy containing a discrete variable (the AP selection decision) and a continuous vector (the power allocation among multiple channels). We provide characterizations of the Nash Equilibrium of the proposed game, and present a set of novel algorithms that allow the users to efficiently optimize their rates. Finally, we study the properties of the proposed algorithms as well as their performance via extensive simulations.
Better Mixing via Deep Representations
Venue: arXiv cs.LG 2012
Year: 2012

It has previously been hypothesized, and supported with some experimental evidence, that deeper representations, when well trained, tend to do a better job at disentangling the underlying factors of variation. We study the following related conjecture: better representations, in the sense of better disentangling, can be exploited to produce faster-mixing Markov chains. Consequently, mixing would be more efficient at higher levels of representation. To better understand why and how this is happening, we propose a secondary conjecture: the higher-level samples fill more uniformly the space they occupy and the high-density manifolds tend to unfold when represented at higher levels. The paper discusses these hypotheses and tests them experimentally through visualization and measurements of mixing and interpolating between samples.
Set-based Multiobjective Fitness Landscapes: A Preliminary Study
Venue: arXiv cs.NE 2012
Year: 2012

Fitness landscape analysis aims to understand the geometry of a given optimization problem in order to design more efficient search algorithms. However, there is a very little knowledge on the landscape of multiobjective problems. In this work, following a recent proposal by Zitzler et al. (2010), we consider multiobjective optimization as a set problem. Then, we give a general definition of set-based multiobjective fitness landscapes. An experimental set-based fitness landscape analysis is conducted on the multiobjective NK-landscapes with objective correlation. The aim is to adapt and to enhance the comprehensive design of set-based multiobjective search approaches, motivated by an a priori analysis of the corresponding set problem properties.
Efficient Core Maintenance in Large Dynamic Graphs
Venue: arXiv cs.DS 2012
Year: 2012

The $k$-core decomposition in a graph is a fundamental problem for social network analysis. The problem of $k$-core decomposition is to calculate the core number for every node in a graph. Previous studies mainly focus on $k$-core decomposition in a static graph. There exists a linear time algorithm for $k$-core decomposition in a static graph. However, in many real-world applications such as online social networks and the Internet, the graph typically evolves over time. Under such applications, a key issue is to maintain the core number of nodes given the graph changes over time. A simple implementation is to perform the linear time algorithm to recompute the core number for every node after the graph is updated. Such simple implementation is expensive when the graph is very large. In this paper, we propose a new efficient algorithm to maintain the core number for every node in a dynamic graph. Our main result is that only certain nodes need to update their core number given the graph is changed by inserting/deleting an edge. We devise an efficient algorithm to identify and recompute the core number of such nodes. The complexity of our algorithm is independent of the graph size. In addition, to further accelerate the algorithm, we develop two pruning strategies by exploiting the lower and upper bounds of the core number. Finally, we conduct extensive experiments over both real-world and synthetic datasets, and the results demonstrate the efficiency of the proposed algorithm.
Exact Algorithms for Maximum Clique: a computational study
Venue: arXiv cs.DS 2012
Year: 2012

We investigate a number of recently reported exact algorithms for the maximum clique problem (MCQ, MCR, MCS, BBMC). The program code used is presented and critiqued showing how small changes in implementation can have a drastic effect on performance. The computational study demonstrates how problem features and hardware platforms influence algorithm behaviour. The minimum width order (smallest-last) is investigated, and MCS is broken into its consituent parts and we discover that one of these parts degrades performance. It is shown that the standard procedure used for rescaling published results is unsafe.
Analyzing the Effect of Objective Correlation on the Efficient Set of MNK-Landscapes
Venue: arXiv cs.NE 2012
Year: 2012

In multiobjective combinatorial optimization, there exists two main classes of metaheuristics, based either on multiple aggregations, or on a dominance relation. As in the single objective case, the structure of the search space can explain the difficulty for multiobjective metaheuristics, and guide the design of such methods. In this work we analyze the properties of multiobjective combinatorial search spaces. In particular, we focus on the features related the efficient set, and we pay a particular attention to the correlation between objectives. Few benchmark takes such objective correlation into account. Here, we define a general method to design multiobjective problems with correlation. As an example, we extend the well-known multiobjective NK-landscapes. By measuring different properties of the search space, we show the importance of considering the objective correlation on the design of metaheuristics.
A Novel Metric Approach Evaluation For The Spatial Enhancement Of Pan-Sharpened Images
Venue: arXiv cs.CV 2012
Year: 2012

Various and different methods can be used to produce high-resolution multispectral images from high-resolution panchromatic image (PAN) and low-resolution multispectral images (MS), mostly on the pixel level. The Quality of image fusion is an essential determinant of the value of processing images fusion for many applications. Spatial and spectral qualities are the two important indexes that used to evaluate the quality of any fused image. However, the jury is still out of fused image's benefits if it compared with its original images. In addition, there is a lack of measures for assessing the objective quality of the spatial resolution for the fusion methods. So, an objective quality of the spatial resolution assessment for fusion images is required. Therefore, this paper describes a new approach proposed to estimate the spatial resolution improve by High Past Division Index (HPDI) upon calculating the spatial-frequency of the edge regions of the image and it deals with a comparison of various analytical techniques for evaluating the Spatial quality, and estimating the colour distortion added by image fusion including: MG, SG, FCC, SD, En, SNR, CC and NRMSE. In addition, this paper devotes to concentrate on the comparison of various image fusion techniques based on pixel and feature fusion technique.
Assume-Guarantee Abstraction Refinement for Probabilistic Systems
Venue: arXiv cs.LO 2012
Year: 2012

We describe an automated technique for assume-guarantee style checking of strong simulation between a system and a specification, both expressed as non-deterministic Labeled Probabilistic Transition Systems (LPTSes). We first characterize counterexamples to strong simulation as "stochastic" trees and show that simpler structures are insufficient. Then, we use these trees in an abstraction refinement algorithm that computes the assumptions for assume-guarantee reasoning as conservative LPTS abstractions of some of the system components. The abstractions are automatically refined based on tree counterexamples obtained from failed simulation checks with the remaining components. We have implemented the algorithms for counterexample generation and assume-guarantee abstraction refinement and report encouraging results.
Analysis of speech under stress using Linear techniques and Non-Linear techniques for emotion recognition system
Venue: arXiv cs.SD 2012
Year: 2012

Analysis of speech for recognition of stress is important for identification of emotional state of person. This can be done using 'Linear Techniques', which has different parameters like pitch, vocal tract spectrum, formant frequencies, Duration, MFCC etc. which are used for extraction of features from speech. TEO-CB-Auto-Env is the method which is non-linear method of features extraction. Analysis is done using TU-Berlin (Technical University of Berlin) German database. Here emotion recognition is done for different emotions like neutral, happy, disgust, sad, boredom and anger. Emotion recognition is used in lie detector, database access systems, and in military for recognition of soldiers' emotion identification during the war.
Ethernet Packet Processor for SoC Application
Venue: arXiv cs.AR 2012
Year: 2012

As the demand for Internet expands significantly in numbers of users, servers, IP addresses, switches and routers, the IP based network architecture must evolve and change. The design of domain specific processors that require high performance, low power and high degree of programmability is the bottleneck in many processor based applications. This paper describes the design of ethernet packet processor for system-on-chip (SoC) which performs all core packet processing functions, including segmentation and reassembly, packetization classification, route and queue management which will speedup switching/routing performance. Our design has been configured for use with multiple projects ttargeted to a commercial configurable logic device the system is designed to support 10/100/1000 links with a speed advantage. VHDL has been used to implement and simulated the required functions in FPGA.
High Reliable secure data collection using Complexity exchanging code key method addressing protocol in Wireless Sensor Network
Venue: arXiv cs.NI 2012
Year: 2012

A Wireless Sensor Network (WSN) is emerging field in Information and communication technology. In WSN data transmission and data collection are unsecure because of sensor node Incompatibility. So providing security to Sensor network is very important. The key based Mechanism is secure data collection and it's mainly used to guarantee data confidentiality. Range pair wise key is largely used due to the necessary of data encryption and decryption between each pair range of communication node. Fixed key mechanism difficult for the attacker to detect the regularity of the randomly generated key chain function in privacy homomorphism (PH).PH means no intermediate node to encrypt and decrypt only direct collect and aggregate data for encryption and decryption. It is special key based scheme. It's totally based on beta distribution and some statistical tool using key code method by using Complexity exchanging code key method addressing protocol. We show how to reduce significant attacks and secure data collection on wireless sensor network.
Guarantees of Augmented Trace Norm Models in Tensor Recovery
Venue: arXiv cs.IT 2012
Year: 2012

This paper studies the recovery guarantees of the models of minimizing $\|\mathcal{X}\|_*+\frac{1}{2α}\|\mathcal{X}\|_F^2$ where $\mathcal{X}$ is a tensor and $\|\mathcal{X}\|_*$ and $\|\mathcal{X}\|_F$ are the trace and Frobenius norm of respectively. We show that they can efficiently recover low-rank tensors. In particular, they enjoy exact guarantees similar to those known for minimizing $\|\mathcal{X}\|_*$ under the conditions on the sensing operator such as its null-space property, restricted isometry property, or spherical section property. To recover a low-rank tensor $\mathcal{X}^0$, minimizing $\|\mathcal{X}\|_*+\frac{1}{2α}\|\mathcal{X}\|_F^2$ returns the same solution as minimizing $\|\mathcal{X}\|_*$ almost whenever $α\geq10\mathop {\max}\limits_{i}\|X^0_{(i)}\|_2$.
Public Key Cryptography Standards: PKCS
Venue: arXiv cs.CR 2012
Year: 2012

Cryptographic standards serve two important goals: making different implementations interoperable and avoiding various known pitfalls in commonly used schemes. This chapter discusses Public-Key Cryptography Standards (PKCS) which have significant impact on the use of public key cryptography in practice. PKCS standards are a set of standards, called PKCS #1 through #15. These standards cover RSA encryption, RSA signature, password-based encryption, cryptographic message syntax, private-key information syntax, selected object classes and attribute types, certification request syntax, cryptographic token interface, personal information exchange syntax, and cryptographic token information syntax. The PKCS standards are published by RSA Laboratories. Though RSA Laboratories solicits public opinions and advice for PKCS standards, RSA Laboratories retain sole decision-making authority on all aspects of PKCS standards. PKCS has been the basis for many other standards such as S/MIME.
Enabling Wireless Power Transfer in Cellular Networks: Architecture, Modeling and Deployment
Venue: arXiv cs.IT 2012
Year: 2012

Microwave power transfer (MPT) delivers energy wirelessly from stations called power beacons (PBs) to mobile devices by microwave radiation. This provides mobiles practically infinite battery lives and eliminates the need of power cords and chargers. To enable MPT for mobile charging, this paper proposes a new network architecture that overlays an uplink cellular network with randomly deployed PBs for powering mobiles, called a hybrid network. The deployment of the hybrid network under an outage constraint on data links is investigated based on a stochastic-geometry model where single-antenna base stations (BSs) and PBs form independent homogeneous Poisson point processes (PPPs) and single-antenna mobiles are uniformly distributed in Voronoi cells generated by BSs. In this model, mobiles and PBs fix their transmission power at p and q, respectively; a PB either radiates isotropically, called isotropic MPT, or directs energy towards target mobiles by beamforming, called directed MPT. The model is applied to derive the tradeoffs between the network parameters including p, q, and the BS/PB densities under the outage constraint. First, consider the deployment of the cellular network. It is proved that the outage constraint is satisfied so long as the product the BS density decreases with increasing p following a power law where the exponent is proportional to the path-loss exponent. Next, consider the deployment of the hybrid network assuming infinite energy storage at mobiles. It is shown that for isotropic MPT, the product between q, the PB density, and the BS density raised to a power proportional to the path-loss exponent has to be above a given threshold so that PBs are sufficiently dense; for directed MPT, a similar result is obtained with the aforementioned product increased by the array gain. Last, similar results are derived for the case of mobiles having small energy storage.
A Framework of Algorithms: Computing the Bias and Prestige of Nodes in Trust Networks
Venue: arXiv cs.SI 2012
Year: 2012

A trust network is a social network in which edges represent the trust relationship between two nodes in the network. In a trust network, a fundamental question is how to assess and compute the bias and prestige of the nodes, where the bias of a node measures the trustworthiness of a node and the prestige of a node measures the importance of the node. The larger bias of a node implies the lower trustworthiness of the node, and the larger prestige of a node implies the higher importance of the node. In this paper, we define a vector-valued contractive function to characterize the bias vector which results in a rich family of bias measurements, and we propose a framework of algorithms for computing the bias and prestige of nodes in trust networks. Based on our framework, we develop four algorithms that can calculate the bias and prestige of nodes effectively and robustly. The time and space complexities of all our algorithms are linear w.r.t. the size of the graph, thus our algorithms are scalable to handle large datasets. We evaluate our algorithms using five real datasets. The experimental results demonstrate the effectiveness, robustness, and scalability of our algorithms.
Improved Interference in Wireless Sensor Networks
Venue: arXiv cs.NI 2012
Year: 2012

Given a set ${\cal V}$ of $n$ sensor node distributed on a 2-dimensional plane and a source node $s \in {\cal V}$, the {\it interference problem} deals with assigning transmission range to each $v \in {\cal V}$ such that the members in ${\cal V}$ maintain connectivity predicate ${\cal P}$, and the maximum/total interference is minimum. We propose algorithm for both {\it minimizing maximum interference} and {\it minimizing total interference} of the networks. For minimizing maximum interference we present optimum solution with running time $O(({\cal P}_n + n^2) \log n)$ for connectivity predicate ${\cal P}$ like strong connectivity, broadcast ($s$ is the source), $k$-edge(vertex) connectivity, spanner, where $O({\cal P}_n)$ is the time complexity for checking the connectivity predicate ${\cal P}$. The running time of the previous best known solution was $O({\cal P}_n \times n^2)$ [Bil$\grave{o}$ and Proietti, 2008]. For the minimizing total interference we propose optimum algorithm for the connectivity predicate broadcast. The running time of the propose algorithm is O(n). For the same problem, the previous best known result was $2(1 + \ln (n-1))$-factor approximation algorithm [Bil$\grave{o}$ and Proietti, 2008]. We also propose a heuristic for minimizing total interference in the case of strongly connected predicate and compare our result with the best result available in the literature. Experimental results demonstrate that our heuristic outperform existing result.
Performance of the Bounded Distance Decoder on the AWGN Channel
Venue: arXiv cs.IT 2012
Year: 2012

In contrast to a maximum-likelihood decoder, it is often desirable to use an incomplete decoder that can detect its decoding errors with high probability. One common choice is the bounded distance decoder. Bounds are derived for the total word error rate, Pw, and the undetected error rate, Pu. Excellent agreement is found with simulation results for a small code, and the bounds are shown to be tractable for a larger code.
Sudoku Associated Two Dimensional Bijections for Image Scrambling
Venue: arXiv cs.CR 2012
Year: 2012

Sudoku puzzles are now popular among people in many countries across the world with simple constraints that no repeated digits in each row, each column, or each block. In this paper, we demonstrate that the Sudoku configuration provides us a new alternative way of matrix element representation by using block-grid pair besides the conventional row-column pair. Moreover, we discover six more matrix element representations by using row-digit pair, digit-row pair, column-digit pair, digit-column pair, block-digit pair, and digit-block pair associated with a Sudoku matrix. These parametric Sudoku associated matrix element representations not only allow us to denote matrix elements in secret ways, but also provide us new parametric two-dimensional bijective mappings. We study these two-dimensional bijections in the problem of image scrambling and propose a simple but effective Sudoku Associated Image Scrambler only using Sudoku associated two dimensional bijections for image scrambling without bandwidth expansion. Our simulation results over a wide collection of image types and contents demonstrate the effectiveness and robustness of the proposed method. Scrambler performance analysis with comparisons to peer algorithms under various investigation methods, including human visual inspections, gray degree of scrambling, autocorrelation coefficient of adjacent pixels, and key space and key sensitivities, suggest that the proposed method outperforms or at least reaches state-of-the-art. Similar scrambling ideas are also applicable to other digital data forms such as audio and video.
Optimal Sampling Points in Reproducing Kernel Hilbert Spaces
Venue: arXiv cs.IT 2012
Year: 2012

The recent developments of basis pursuit and compressed sensing seek to extract information from as few samples as possible. In such applications, since the number of samples is restricted, one should deploy the sampling points wisely. We are motivated to study the optimal distribution of finite sampling points. Formulation under the framework of optimal reconstruction yields a minimization problem. In the discrete case, we estimate the distance between the optimal subspace resulting from a general Karhunen-Loeve transform and the kernel space to obtain another algorithm that is computationally favorable. Numerical experiments are then presented to illustrate the performance of the algorithms for the searching of optimal sampling points.
Accurate and Efficient Private Release of Datacubes and Contingency Tables
Venue: arXiv cs.DB 2012
Year: 2012

A central problem in releasing aggregate information about sensitive data is to do so accurately while providing a privacy guarantee on the output. Recent work focuses on the class of linear queries, which include basic counting queries, data cubes, and contingency tables. The goal is to maximize the utility of their output, while giving a rigorous privacy guarantee. Most results follow a common template: pick a "strategy" set of linear queries to apply to the data, then use the noisy answers to these queries to reconstruct the queries of interest. This entails either picking a strategy set that is hoped to be good for the queries, or performing a costly search over the space of all possible strategies. In this paper, we propose a new approach that balances accuracy and efficiency: we show how to improve the accuracy of a given query set by answering some strategy queries more accurately than others. This leads to an efficient optimal noise allocation for many popular strategies, including wavelets, hierarchies, Fourier coefficients and more. For the important case of marginal queries we show that this strictly improves on previous methods, both analytically and empirically. Our results also extend to ensuring that the returned query answers are consistent with an (unknown) data set at minimal extra cost in terms of time and noise.