OpenRaiser/Intern-Atlas huggingface dataset:
Product Review Summarization based on Facet Identification and Sentence Clustering
Venue: arXiv cs.CL 2011
Year: 2011

Product review nowadays has become an important source of information, not only for customers to find opinions about products easily and share their reviews with peers, but also for product manufacturers to get feedback on their products. As the number of product reviews grows, it becomes difficult for users to search and utilize these resources in an efficient way. In this work, we build a product review summarization system that can automatically process a large collection of reviews and aggregate them to generate a concise summary. More importantly, the drawback of existing product summarization systems is that they cannot provide the underlying reasons to justify users' opinions. In our method, we solve this problem by applying clustering, prior to selecting representative candidates for summarization.
A Probabilistic Approach for Authenticating Text or Graphical Passwords Using Back Propagation
Venue: arXiv cs.CR 2011
Year: 2011

Password authentication is a common approach to the system security and it is also a very important procedure to gain access to user resources. In the conventional password authentication methods a server has to authenticate the legitimate user. In our proposed method users can freely choose their passwords from a defined character set or they can use a graphical image as password and that input will be normalized. Neural networks have been used recently for password authentication in order to overcome pitfall of traditional password authentication methods. In this paper we proposed a method for password authentication using alphanumeric password and graphical password. We used Back Propagation algorithm for both alphanumeric (Text) and graphical password by which the level of security can be enhanced. This paper along with test results show that converting user password in to Probabilistic values enhances the security of the system
A Novel Approach For Intranet Mailing For Providing User Authentication
Venue: arXiv cs.CR 2011
Year: 2011

With the explosion of the public Internet and e-commerce, private computers, and computer networks, if not adequately secured, are increasingly vulnerable to damaging attacks. Hackers, viruses, vindictive employees and even human error all represent clear and present dangers to networks. Various antidotes that are in fact inextricable with security issues are - Cryptography, Authentication, Integrity and Non Repudiation, Key Distribution and certification, Access control by implementing Firewalls etc.The main idea of this paper is to overcome the PGP's(Pretty Good Privacy) main limitation of incomplete non-repudiation Service, which increases the degree of security and efficiency of an email message communication through NRR(Non-Repudiation of Receipt) and including PGPs original feature of NRO(Non-Repudiation of Origin), and there it assures new security service of Mutual Non-Repudiation (MNR) .
A Cryptosystem Based on Hilbert Matrix using Cipher Block Chaining Mode
Venue: arXiv cs.CR 2011
Year: 2011

Cryptography is the science of using mathematics to encrypt and decrypt data. Cryptography enables you to store sensitive information or transmit it across insecure networks so that it cannot be read by anyone except the intended recipient. While cryptography is the science of securing data, cryptanalysis is the science of analyzing and breaking secure communication. Classical cryptanalysis involves an interesting combination of analytical reasoning, application of mathematical tools and pattern finding. The objectives of the proposed work are to propose a new cryptographic method based on the special matrix called the Hilbert matrix for authentication and confidentiality and to propose a model for confidentiality and authentication using a combination of symmetric and public cryptosystems. Further, it is extended to shared key cryptosystems with the concept of digital enveloping using a session key. In the present work an algorithm for shared key encryption is developed using Hilbert matrix cryptosystem. In this the block chaining modes of operation have been used to tackle the issues of confusion and diffusion.
Foliage Plant Retrieval using Polar Fourier Transform, Color Moments and Vein Features
Venue: arXiv cs.CV 2011
Year: 2011

This paper proposed a method that combines Polar Fourier Transform, color moments, and vein features to retrieve leaf images based on a leaf image. The method is very useful to help people in recognizing foliage plants. Foliage plants are plants that have various colors and unique patterns in the leaf. Therefore, the colors and its patterns are information that should be counted on in the processing of plant identification. To compare the performance of retrieving system to other result, the experiments used Flavia dataset, which is very popular in recognizing plants. The result shows that the method gave better performance than PNN, SVM, and Fourier Transform. The method was also tested using foliage plants with various colors. The accuracy was 90.80% for 50 kinds of plants.
Adaptive Data Stream Management System Using Learning Automata
Venue: arXiv cs.DB 2011
Year: 2011

In many modern applications, data are received as infinite, rapid, unpredictable and time- variant data elements that are known as data streams. Systems which are able to process data streams with such properties are called Data Stream Management Systems (DSMS). Due to the unpredictable and time- variant properties of data streams as well as system, adaptivity of the DSMS is a major requirement for each DSMS. Accordingly, determining parameters which are effective on the most important performance metric of a DSMS (i.e., response time) and analysing them will affect on designing an adaptive DSMS. In this paper, effective parameters on response time of DSMS are studied and analysed and a solution is proposed for DSMSs' adaptivity. The proposed adaptive DSMS architecture includes a learning unit that frequently evaluates system to adjust the optimal value for each of tuneable effective. Learning Automata is used as the learning mechanism of the learning unit to adjust the value of tuneable effective parameters. So, when system faces some changes, the learning unit increases performance by tuning each of tuneable effective parameters to its optimum value. Evaluation results illustrate that after a while, parameters reach their optimum value and then DSMS's adaptivity will be improved considerably.
Voting with Limited Information and Many Alternatives
Venue: arXiv cs.DM 2011
Year: 2011

The traditional axiomatic approach to voting is motivated by the problem of reconciling differences in subjective preferences. In contrast, a dominant line of work in the theory of voting over the past 15 years has considered a different kind of scenario, also fundamental to voting, in which there is a genuinely "best" outcome that voters would agree on if they only had enough information. This type of scenario has its roots in the classical Condorcet Jury Theorem; it includes cases such as jurors in a criminal trial who all want to reach the correct verdict but disagree in their inferences from the available evidence, or a corporate board of directors who all want to improve the company's revenue, but who have different information that favors different options. This style of voting leads to a natural set of questions: each voter has a {\em private signal} that provides probabilistic information about which option is best, and a central question is whether a simple plurality voting system, which tabulates votes for different options, can cause the group decision to arrive at the correct option. We show that plurality voting is powerful enough to achieve this: there is a way for voters to map their signals into votes for options in such a way that --- with sufficiently many voters --- the correct option receives the greatest number of votes with high probability. We show further, however, that any process for achieving this is inherently expensive in the number of voters it requires: succeeding in identifying the correct option with probability at least $1 - η$ requires $Ω(n^3 ε^{-2} \log η^{-1})$ voters, where $n$ is the number of options and $ε$ is a distributional measure of the minimum difference between the options.
On the Efficiency of Influence-and-Exploit Strategies for Revenue Maximization under Positive Externalities
Venue: arXiv cs.DS 2011
Year: 2011

We study the problem of revenue maximization in the marketing model for social networks introduced by (Hartline, Mirrokni, Sundararajan, WWW '08). We restrict our attention to the Uniform Additive Model and mostly focus on Influence-and-Exploit (IE) marketing strategies. We obtain a comprehensive collection of results on the efficiency and the approximability of IE strategies, which also imply a significant improvement on the best known approximation ratios for revenue maximization. Specifically, we show that in the Uniform Additive Model, both computing the optimal marketing strategy and computing the best IE strategy are $\NP$-hard for undirected social networks. We observe that allowing IE strategies to offer prices smaller than the myopic price in the exploit step leads to a measurable improvement on their performance. Thus, we show that the best IE strategy approximates the maximum revenue within a factor of 0.911 for undirected and of roughly 0.553 for directed networks. Moreover, we present a natural generalization of IE strategies, with more than two pricing classes, and show that they approximate the maximum revenue within a factor of roughly 0.7 for undirected and of roughly 0.35 for directed networks. Utilizing a connection between good IE strategies and large cuts in the underlying social network, we obtain polynomial-time algorithms that approximate the revenue of the best IE strategy within a factor of roughly 0.9. Hence, we significantly improve on the best known approximation ratio for revenue maximization to 0.8229 for undirected and to 0.5011 for directed networks (from 2/3 and 1/3, respectively, by Hartline et al.).
Stratified Outsourcing Theory
Venue: arXiv cs.SE 2011
Year: 2011

The terminology of sourcing, outsourcing and insourcing is developed in detail on the basis of the preliminary definitions of outsourcing and insourcing and related activities and competences as given in our three previous papers on business mereology, on the concept of a sourcement, and on outsourcing competence respectively. Besides providing more a detailed semantic analysis we will introduce, explain, and illustrate a number of additional concepts including: principal unit of a sourcement, theme of a sourcement, current sourcement, (un)stable sourcement, and sourcement transformation. A three level terminology is designed: (i) factual level: operational facts that hold for sourcements including histories thereof, (ii) business level: roles and objectives of various parts of the factual level description, thus explaining each partner's business process and business objectives, (iii) contract level: specification of intended facts and intended business models as found at the business level. Orthogonal to these three conceptual levels, are four temporal aspects: history, now (actuality), transformation, and transition. A detailed description of the well-known range of sourcement transformations is given.
Cluster-Based Load Balancing Algorithms for Grids
Venue: arXiv cs.DC 2011
Year: 2011

E-science applications may require huge amounts of data and high processing power where grid infrastructures are very suitable for meeting these requirements. The load distribution in a grid may vary leading to the bottlenecks and overloaded sites. We describe a hierarchical dynamic load balancing protocol for Grids. The Grid consists of clusters and each cluster is represented by a coordinator. Each coordinator first attempts to balance the load in its cluster and if this fails, communicates with the other coordinators to perform transfer or reception of load. This process is repeated periodically. We analyze the correctness, performance and scalability of the proposed protocol and show from the simulation results that our algorithm balances the load by decreasing the number of high loaded nodes in a grid environment.
Open Source Software: How Can Design Metrics Facilitate Architecture Recovery?
Venue: arXiv cs.SE 2011
Year: 2011

Modern software development methodologies include reuse of open source code. Reuse can be facilitated by architectural knowledge of the software, not necessarily provided in the documentation of open source software. The effort required to comprehend the system's source code and discover its architecture can be considered a major drawback in reuse. In a recent study we examined the correlations between design metrics and classes' architecture layer. In this paper, we apply our methodology in more open source projects to verify the applicability of our method. Keywords: system understanding; program comprehension; object-oriented; reuse; architecture layer; design metrics;
Acceleration of Uncertainty Updating in the Description of Transport Processes in Heterogeneous Materials
Venue: arXiv cs.CE 2011
Year: 2011

The prediction of thermo-mechanical behaviour of heterogeneous materials such as heat and moisture transport is strongly influenced by the uncertainty in parameters. Such materials occur e.g. in historic buildings, and the durability assessment of these therefore needs a reliable and probabilistic simulation of transport processes, which is related to the suitable identification of material parameters. In order to include expert knowledge as well as experimental results, one can employ an updating procedure such as Bayesian inference. The classical probabilistic setting of the identification process in Bayes's form requires the solution of a stochastic forward problem via computationally expensive sampling techniques, which makes the method almost impractical. In this paper novel stochastic computational techniques such as the stochastic Galerkin method are applied in order to accelerate the updating procedure. The idea is to replace the computationally expensive forward simulation via the conventional finite element (FE) method by the evaluation of a polynomial chaos expansion (PCE). Such an approximation of the FE model for the forward simulation perfectly suits the Bayesian updating. The presented uncertainty updating techniques are applied to the numerical model of coupled heat and moisture transport in heterogeneous materials with spatially varying coefficients defined by random fields.
Computational homogenization of non-stationary transport processes in masonry structures
Venue: arXiv cs.CE 2011
Year: 2011

A fully coupled transient heat and moisture transport in a masonry structure is examined in this paper. Supported by several successful applications in civil engineering the nonlinear diffusion model proposed by Künzel is adopted in the present study. A strong material heterogeneity together with a significant dependence of the model parameters on initial conditions as well as the gradients of heat and moisture fields vindicates the use of a hierarchical modeling strategy to solve the problem of this kind. Attention is limited to the classical first order homogenization in a spatial domain developed here in the framework of a two step (meso-macro) multi-scale computational scheme (FE^2 problem). Several illustrative examples are presented to investigate the influence of transient flow at the level of constituents (meso-scale) on the macroscopic response including the effect of macro-scale boundary conditions. A two-dimensional section of Charles Bridge subjected to actual climatic conditions is analyzed next to confirm the suitability of algorithmic format of FE^2 scheme for the parallel computing.
Memristors can implement fuzzy logic
Venue: arXiv cs.ET 2011
Year: 2011

In our work we propose implementing fuzzy logic using memristors. Min and max operations are done by antipodally configured memristor circuits that may be assembled into computational circuits. We discuss computational power of such circuits with respect to m-efficiency and experimentally observed behavior of memristive devices. Circuits implemented with real devices are likely to manifest learning behavior. The circuits presented in the work may be applicable for instance in fuzzy classifiers.
Closed-Loop Learning of Visual Control Policies
Venue: arXiv cs.CV 2011
Year: 2011

In this paper we present a general, flexible framework for learning mappings from images to actions by interacting with the environment. The basic idea is to introduce a feature-based image classifier in front of a reinforcement learning algorithm. The classifier partitions the visual space according to the presence or absence of few highly informative local descriptors that are incrementally selected in a sequence of attempts to remove perceptual aliasing. We also address the problem of fighting overfitting in such a greedy algorithm. Finally, we show how high-level visual features can be generated when the power of local descriptors is insufficient for completely disambiguating the aliased states. This is done by building a hierarchy of composite features that consist of recursive spatial combinations of visual features. We demonstrate the efficacy of our algorithms by solving three visual navigation tasks and a visual version of the classical Car on the Hill control problem.
Learning Symbolic Models of Stochastic Domains
Venue: arXiv cs.LG 2011
Year: 2011

In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a probabilistic, relational planning rule representation that compactly models noisy, nondeterministic action effects, and show how such rules can be effectively learned. Through experiments in simple planning domains and a 3D simulated blocks world with realistic physics, we demonstrate that this learning algorithm allows agents to effectively model world dynamics.
The Generalized A* Architecture
Venue: arXiv cs.AI 2011
Year: 2011

We consider the problem of computing a lightest derivation of a global structure using a set of weighted rules. A large variety of inference problems in AI can be formulated in this framework. We generalize A* search and heuristics derived from abstractions to a broad class of lightest derivation problems. We also describe a new algorithm that searches for lightest derivations using a hierarchy of abstractions. Our generalization of A* gives a new algorithm for searching AND/OR graphs in a bottom-up fashion. We discuss how the algorithms described here provide a general architecture for addressing the pipeline problem --- the problem of passing information back and forth between various stages of processing in a perceptual system. We consider examples in computer vision and natural language processing. We apply the hierarchical search algorithm to the problem of estimating the boundaries of convex objects in grayscale images and compare it to other search methods. A second set of experiments demonstrate the use of a new compositional model for finding salient curves in images.
Constructions of Rank Modulation Codes
Venue: arXiv cs.IT 2011
Year: 2011

Rank modulation is a way of encoding information to correct errors in flash memory devices as well as impulse noise in transmission lines. Modeling rank modulation involves construction of packings of the space of permutations equipped with the Kendall tau distance. We present several general constructions of codes in permutations that cover a broad range of code parameters. In particular, we show a number of ways in which conventional error-correcting codes can be modified to correct errors in the Kendall space. Codes that we construct afford simple encoding and decoding algorithms of essentially the same complexity as required to correct errors in the Hamming metric. For instance, from binary BCH codes we obtain codes correcting $t$ Kendall errors in $n$ memory cells that support the order of $n!/(\log_2n!)^t$ messages, for any constant $t= 1,2,...$ We also construct families of codes that correct a number of errors that grows with $n$ at varying rates, from $Θ(n)$ to $Θ(n^{2})$. One of our constructions gives rise to a family of rank modulation codes for which the trade-off between the number of messages and the number of correctable Kendall errors approaches the optimal scaling rate. Finally, we list a number of possibilities for constructing codes of finite length, and give examples of rank modulation codes with specific parameters.
Survey of Latest Wireless Cellular Technologies for Enhancement of Spectral Density at Reduced Cost
Venue: arXiv cs.CY 2011
Year: 2011

The future of mobile wireless communication networks will include existing 3rd generation, 4th generation (implemented in Japan, USA, South Korea etc.), 5th generation (based on cognitive radio which implies the whole wireless world interconnection & WISDOM - Wireless innovative System for Dynamic Operating Megacommunications concept), 6th generation (with very high data rates Quality of Service (QoS) and service applications) and 7th generation (with space roaming). This paper is focused on the specifications of future generations and latest technologies to be used in future wireless mobile communication networks. However keeping in view the general poor masses of India, some of the future generation technologies will be embedded with 2G and 2.5G so that general masses may get the advantage of internet, multimedia services and the operators may get proper revenues with little extra expenditure in the existing mobile communication networks.
Hierarchical Cellular Structures in High-Capacity Cellular Communication Systems
Venue: arXiv cs.CY 2011
Year: 2011

In the prevailing cellular environment, it is important to provide the resources for the fluctuating traffic demand exactly in the place and at the time where and when they are needed. In this paper, we explored the ability of hierarchical cellular structures with inter layer reuse to increase the capacity of mobile communication network by applying total frequency hopping (T-FH) and adaptive frequency allocation (AFA) as a strategy to reuse the macro and micro cell resources without frequency planning in indoor pico cells [11]. The practical aspects for designing macro- micro cellular overlays in the existing big urban areas are also explained [4]. Femto cells are inducted in macro / micro / pico cells hierarchical structure to achieve the required QoS cost effectively.
Information Transfer in Social Media
Venue: arXiv cs.SI 2011
Year: 2011

Recent research has explored the increasingly important role of social media by examining the dynamics of individual and group behavior, characterizing patterns of information diffusion, and identifying influential individuals. In this paper we suggest a measure of causal relationships between nodes based on the information-theoretic notion of transfer entropy, or information transfer. This theoretically grounded measure is based on dynamic information, captures fine-grain notions of influence, and admits a natural, predictive interpretation. Causal networks inferred by transfer entropy can differ significantly from static friendship networks because most friendship links are not useful for predicting future dynamics. We demonstrate through analysis of synthetic and real-world data that transfer entropy reveals meaningful hidden network structures. In addition to altering our notion of who is influential, transfer entropy allows us to differentiate between weak influence over large groups and strong influence over small groups.
Imperfect Match: PDDL 2.1 and Real Applications
Venue: arXiv cs.AI 2011
Year: 2011

PDDL was originally conceived and constructed as a lingua franca for the International Planning Competition. PDDL2.1 embodies a set of extensions intended to support the expression of something closer to real planning problems. This objective has only been partially achieved, due in large part to a deliberate focus on not moving too far from classical planning models and solution methods.