OpenRaiser/Intern-Atlas huggingface dataset:
A Human-Centric Approach to Group-Based Context-Awareness
Venue: arXiv cs.AI 2011
Year: 2011

The emerging need for qualitative approaches in context-aware information processing calls for proper modeling of context information and efficient handling of its inherent uncertainty resulted from human interpretation and usage. Many of the current approaches to context-awareness either lack a solid theoretical basis for modeling or ignore important requirements such as modularity, high-order uncertainty management and group-based context-awareness. Therefore, their real-world application and extendability remains limited. In this paper, we present f-Context as a service-based context-awareness framework, based on language-action perspective (LAP) theory for modeling. Then we identify some of the complex, informational parts of context which contain high-order uncertainties due to differences between members of the group in defining them. An agent-based perceptual computer architecture is proposed for implementing f-Context that uses computing with words (CWW) for handling uncertainty. The feasibility of f-Context is analyzed using a realistic scenario involving a group of mobile users. We believe that the proposed approach can open the door to future research on context-awareness by offering a theoretical foundation based on human communication, and a service-based layered architecture which exploits CWW for context-aware, group-based and platform-independent access to information systems.
Analysis of Web Logs and Web User in Web Mining
Venue: arXiv cs.DB 2011
Year: 2011

Log files contain information about User Name, IP Address, Time Stamp, Access Request, number of Bytes Transferred, Result Status, URL that Referred and User Agent. The log files are maintained by the web servers. By analysing these log files gives a neat idea about the user. This paper gives a detailed discussion about these log files, their formats, their creation, access procedures, their uses, various algorithms used and the additional parameters that can be used in the log files which in turn gives way to an effective mining. It also provides the idea of creating an extended log file and learning the user behaviour.
A correspondence-less approach to matching of deformable shapes
Venue: arXiv cs.CV 2011
Year: 2011

Finding a match between partially available deformable shapes is a challenging problem with numerous applications. The problem is usually approached by computing local descriptors on a pair of shapes and then establishing a point-wise correspondence between the two. In this paper, we introduce an alternative correspondence-less approach to matching fragments to an entire shape undergoing a non-rigid deformation. We use diffusion geometric descriptors and optimize over the integration domains on which the integral descriptors of the two parts match. The problem is regularized using the Mumford-Shah functional. We show an efficient discretization based on the Ambrosio-Tortorelli approximation generalized to triangular meshes. Experiments demonstrating the success of the proposed method are presented.
Minimizing Hidden-Node Network Interference by Optimizing SISO and MIMO Spectral Efficiency
Venue: arXiv cs.IT 2011
Year: 2011

In this paper, the optimal spectral efficiency (data rate divided by the message bandwidth) that minimizes the probability of causing disruptive interference for ad hoc wireless networks or cognitive radios is investigated. Two basic problem constraints are considered: a given message size, or fixed data rate. Implicitly, the trade being optimized is between longer transmit duration and wider bandwidth versus higher transmit power. Both single-input single-output (SISO) and multiple-input multiple-output (MIMO) links are considered. Here, a link optimizes its spectral efficiency to be a "good neighbor." The probability of interference is characterized by the probability that the signal power received by a hidden node in a wireless network exceeds some threshold. The optimized spectral efficiency is a function of the transmitter-to-hidden-node channel exponent, exclusively. It is shown that for typical channel exponents a spectral efficiency of slightly greater than 1~b/s/Hz per antenna is optimal. It is also shown that the optimal spectral efficiency is valid in the environment with multiple hidden nodes. Also explicit evaluations of the probability of collisions is presented as a function of spectral efficiency.
Polarized Montagovian Semantics for the Lambek-Grishin calculus
Venue: arXiv cs.CL 2011
Year: 2011

Grishin proposed enriching the Lambek calculus with multiplicative disjunction (par) and coresiduals. Applications to linguistics were discussed by Moortgat, who spoke of the Lambek-Grishin calculus (LG). In this paper, we adapt Girard's polarity-sensitive double negation embedding for classical logic to extract a compositional Montagovian semantics from a display calculus for focused proof search in LG. We seize the opportunity to illustrate our approach alongside an analysis of extraction, providing linguistic motivation for linear distributivity of tensor over par, thus answering a question of Kurtonina&Moortgat. We conclude by comparing our proposal to the continuation semantics of Bernardi&Moortgat, corresponding to call-by- name and call-by-value evaluation strategies.
Co-Designing Multi-Packet Reception, Network Coding, and MAC Using a Simple Predictive Model
Venue: arXiv cs.NI 2011
Year: 2011

We design a cross-layer approach to optimize the joint use of multi-packet reception and network coding, in order to relieve congestion. We construct a model for the behavior of the 802.11 MAC and apply it to several key canonical topology components and their extensions to any number of nodes. The results obtained from this model match the available experimental results, which are for routing and opportunistic network coding, with fidelity. Using this model, we show that fairness allocation by the MAC can seriously impact performance; hence, we devise a new MAC that not only substantially improves throughput relative to the current 802.11 MAC, but also provides fairness to flows of information rather than to nodes. We show that the proper combination of network coding, multi-packet reception, and our new MAC protocol achieves super-additive throughput gains of up to 6.3 times that of routing alone with the use of the standard 802.11 MAC. Finally, we extend the model to analyze the asymptotic behavior of our new MAC as the number of nodes increases.
The Degrees of Freedom Region and Interference Alignment for the MIMO Interference Channel with Delayed CSI
Venue: arXiv cs.IT 2011
Year: 2011

The degrees of freedom (DoF) region of the 2-user multiple-antenna or MIMO (multiple-input, multiple-output) interference channel (IC) is studied under fast fading and the assumption of {\em delayed} channel state information (CSI) wherein all terminals know all (or certain) channel matrices perfectly, but with a delay, and each receiver in addition knows its own incoming channels instantaneously. The general MIMO IC is considered with an arbitrary number of antennas at each of the four terminals. Dividing it into several classes depending on the relation between the numbers of antennas at the four terminals, the fundamental DoF regions are characterized under the delayed CSI assumption for {\em all} possible values of number of antennas at the four terminals. In particular, an outer bound on the DoF region of the general MIMO IC is derived. This bound is then shown to be tight for all MIMO ICs by developing interference alignment based achievability schemes for each class. A comparison of these DoF regions under the delayed CSI assumption is made with those of the idealistic `perfect CSI' assumption where perfect and instantaneous CSI is available at all terminals on the one hand and with the DoF regions of the conservative `no CSI' assumption on the other, where CSI is available at the receivers but not at all at the transmitters.
The Documents and Assets Created During the Video Game Production Process
Venue: arXiv cs.DL 2011
Year: 2011

The purpose of this paper is to take that first step in helping archivists understand the video game industry by examining the documents and assets created by game companies. This paper is intended as a survey of the records generated during video game production, and an overview of why and how those records are created. It is not intended to be a statement on archiving best practices, but rather a tool for archivists to use when assessing and processing video game collections. It is an overview of how a video game is made and the paper trail left behind that an archivist might encounter.
The Gaussian Interference Relay Channel: Improved Achievable Rates and Sum Rate Upperbounds Using a Potent Relay
Venue: arXiv cs.IT 2011
Year: 2011

We consider the Gaussian interference channel with an intermediate relay as a main building block for cooperative interference networks. On the achievability side, we consider compress-and-forward based strategies. Specifically, a generalized compress-and-forward strategy, where the destinations jointly decode the compression indices and the source messages, is shown to improve upon the compress-and-forward strategy which sequentially decodes the compression indices and source messages, and the recently proposed generalized hash-and-forward strategy. We also construct a nested lattice code based compute-and-forward relaying scheme, which outperforms other relaying schemes when the direct link is weak. In this case, it is shown that, with a relay, the interference link can be useful for decoding the source messages. Noting the need for upperbounding the capacity for this channel, we propose a new technique with which the sum rate can be bounded. In particular, the sum capacity is upperbounded by considering the channel when the relay node has abundant power and is named potent for that reason. For the Gaussian interference relay channel with potent relay, we study the strong and the weak interference regimes and establish the sum capacity, which, in turn, serve as upperbounds for the sum capacity of the GIFRC with finite relay power. Numerical results demonstrate that upperbounds are tighter than the cut-set bound, and coincide with known achievable sum rates for many scenarios of interest. Additionally, the degrees of freedom of the GIFRC are shown to be 2 when the relay has large power, achievable using compress-and-forward.
Business Intelligence for Small and Middle-Sized Entreprises
Venue: arXiv cs.DB 2011
Year: 2011

Data warehouses are the core of decision support sys- tems, which nowadays are used by all kind of enter- prises in the entire world. Although many studies have been conducted on the need of decision support systems (DSSs) for small businesses, most of them adopt ex- isting solutions and approaches, which are appropriate for large-scaled enterprises, but are inadequate for small and middle-sized enterprises. Small enterprises require cheap, lightweight architec- tures and tools (hardware and software) providing on- line data analysis. In order to ensure these features, we review web-based business intelligence approaches. For real-time analysis, the traditional OLAP architecture is cumbersome and storage-costly; therefore, we also re- view in-memory processing. Consequently, this paper discusses the existing approa- ches and tools working in main memory and/or with web interfaces (including freeware tools), relevant for small and middle-sized enterprises in decision making.
Optimal Band Allocation for Cognitive Cellular Networks
Venue: arXiv cs.IT 2011
Year: 2011

FCC new regulation for cognitive use of the TV white space spectrum provides a new means for improving traditional cellular network performance. But it also introduces a number of technical challenges. This letter studies one of the challenges, that is, given the significant differences in the propagation property and the transmit power limitations between the cellular band and the TV white space, how to jointly utilize both bands such that the benefit from the TV white space for improving cellular network performance is maximized. Both analytical and simulation results are provided.
Threshold Saturation on Channels with Memory via Spatial Coupling
Venue: arXiv cs.IT 2011
Year: 2011

We consider spatially coupled code ensembles. A particular instance are convolutional LDPC ensembles. It was recently shown that, for transmission over the memoryless binary erasure channel, this coupling increases the belief propagation threshold of the ensemble to the maximum a-posteriori threshold of the underlying component ensemble. This paved the way for a new class of capacity achieving low-density parity check codes. It was also shown empirically that the same threshold saturation occurs when we consider transmission over general binary input memoryless channels. In this work, we report on empirical evidence which suggests that the same phenomenon also occurs when transmission takes place over a class of channels with memory. This is confirmed both by simulations as well as by computing EXIT curves.
Asymptotic fingerprinting capacity for non-binary alphabets
Venue: arXiv cs.CR 2011
Year: 2011

We compute the channel capacity of non-binary fingerprinting under the Marking Assumption, in the limit of large coalition size c. The solution for the binary case was found by Huang and Moulin. They showed that asymptotically, the capacity is $1/(c^2 2\ln 2)$, the interleaving attack is optimal and the arcsine distribution is the optimal bias distribution. In this paper we prove that the asymptotic capacity for general alphabet size q is $(q-1)/(c^2 2\ln q)$. Our proof technique does not reveal the optimal attack or bias distribution. The fact that the capacity is an increasing function of q shows that there is a real gain in going to non-binary alphabets.
Asymptotically false-positive-maximizing attack on non-binary Tardos codes
Venue: arXiv cs.CR 2011
Year: 2011

We use a method recently introduced by Simone and Skoric to study accusation probabilities for non-binary Tardos fingerprinting codes. We generalize the pre-computation steps in this approach to include a broad class of collusion attack strategies. We analytically derive properties of a special attack that asymptotically maximizes false accusation probabilities. We present numerical results on sufficient code lengths for this attack, and explain the abrupt transitions that occur in these results.
Evaluation of Three Vision Based Object Perception Methods for a Mobile Robot
Venue: arXiv cs.RO 2011
Year: 2011

This paper addresses object perception applied to mobile robotics. Being able to perceive semantically meaningful objects in unstructured environments is a key capability in order to make robots suitable to perform high-level tasks in home environments. However, finding a solution for this task is daunting: it requires the ability to handle the variability in image formation in a moving camera with tight time constraints. The paper brings to attention some of the issues with applying three state of the art object recognition and detection methods in a mobile robotics scenario, and proposes methods to deal with windowing/segmentation. Thus, this work aims at evaluating the state-of-the-art in object perception in an attempt to develop a lightweight solution for mobile robotics use/research in typical indoor settings.
Glioblastoma Multiforme Segmentation in MRI Data with a Balloon Inflation Approach
Venue: arXiv cs.GR 2011
Year: 2011

Gliomas are the most common primary brain tumors, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the preoperative tumor volume is essential. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming process that can be overcome with the help of computer-assisted segmentation methods. In this paper, a semi-automatic approach for World Health Organization (WHO) grade IV glioma segmentation is introduced that uses balloon inflation forces, and relies on the detection of high-intensity tumor boundaries that are coupled by using contrast agent gadolinium. The presented method is evaluated on 27 magnetic resonance imaging (MRI) data sets and the ground truth data of the tumor boundaries - for evaluation of the results - are manually extracted by neurosurgeons.
Architecture of A Scalable Dynamic Parallel WebCrawler with High Speed Downloadable Capability for a Web Search Engine
Venue: arXiv cs.IR 2011
Year: 2011

Today World Wide Web (WWW) has become a huge ocean of information and it is growing in size everyday. Downloading even a fraction of this mammoth data is like sailing through a huge ocean and it is a challenging task indeed. In order to download a large portion of data from WWW, it has become absolutely essential to make the crawling process parallel. In this paper we offer the architecture of a dynamic parallel Web crawler, christened as "WEB-SAILOR," which presents a scalable approach based on Client-Server model to speed up the download process on behalf of a Web Search Engine in a distributed Domain-set specific environment. WEB-SAILOR removes the possibility of overlapping of downloaded documents by multiple crawlers without even incurring the cost of communication overhead among several parallel "client" crawling processes.
A Dynamic Web Page Prediction Model Based on Access Patterns to Offer Better User Latency
Venue: arXiv cs.NI 2011
Year: 2011

The growth of the World Wide Web has emphasized the need for improvement in user latency. One of the techniques that are used for improving user latency is Caching and another is Web Prefetching. Approaches that bank solely on caching offer limited performance improvement because it is difficult for caching to handle the large number of increasingly diverse files. Studies have been conducted on prefetching models based on decision trees, Markov chains, and path analysis. However, the increased uses of dynamic pages, frequent changes in site structure and user access patterns have limited the efficacy of these static techniques. In this paper, we have proposed a methodology to cluster related pages into different categories based on the access patterns. Additionally we use page ranking to build up our prediction model at the initial stages when users haven't already started sending requests. This way we have tried to overcome the problems of maintaining huge databases which is needed in case of log based techniques.
Intelligent Semantic Web Search Engines: A Brief Survey
Venue: arXiv cs.AI 2011
Year: 2011

The World Wide Web (WWW) allows the people to share the information (data) from the large database repositories globally. The amount of information grows billions of databases. We need to search the information will specialize tools known generically search engine. There are many of search engines available today, retrieving meaningful information is difficult. However to overcome this problem in search engines to retrieve meaningful information intelligently, semantic web technologies are playing a major role. In this paper we present survey on the search engine generations and the role of search engines in intelligent web and semantic search technologies.
Incentive Compatible Influence Maximization in Social Networks and Application to Viral Marketing
Venue: arXiv cs.GT 2011
Year: 2011

Information diffusion and influence maximization are important and extensively studied problems in social networks. Various models and algorithms have been proposed in the literature in the context of the influence maximization problem. A crucial assumption in all these studies is that the influence probabilities are known to the social planner. This assumption is unrealistic since the influence probabilities are usually private information of the individual agents and strategic agents may not reveal them truthfully. Moreover, the influence probabilities could vary significantly with the type of the information flowing in the network and the time at which the information is propagating in the network. In this paper, we use a mechanism design approach to elicit influence probabilities truthfully from the agents. We first work with a simple model, the influencer model, where we assume that each user knows the level of influence she has on her neighbors but this is private information. In the second model, the influencer-influencee model, which is more realistic, we determine influence probabilities by combining the probability values reported by the influencers and influencees. In the context of the first model, we present how VCG (Vickrey-Clarke-Groves) mechanisms could be used for truthfully eliciting the influence probabilities. Our main contribution is to design a scoring rule based mechanism in the context of the influencer-influencee model. In particular, we show the incentive compatibility of the mechanisms when the scoring rules are proper and propose a reverse weighted scoring rule based mechanism as an appropriate mechanism to use. We also discuss briefly the implementation of such a mechanism in viral marketing applications.
An Evaluation of Link Neighborhood Lexical Signatures to Rediscover Missing Web Pages
Venue: arXiv cs.IR 2011
Year: 2011

For discovering the new URI of a missing web page, lexical signatures, which consist of a small number of words chosen to represent the "aboutness" of a page, have been previously proposed. However, prior methods relied on computing the lexical signature before the page was lost, or using cached or archived versions of the page to calculate a lexical signature. We demonstrate a system of constructing a lexical signature for a page from its link neighborhood, that is the "backlinks", or pages that link to the missing page. After testing various methods, we show that one can construct a lexical signature for a missing web page using only ten backlink pages. Further, we show that only the first level of backlinks are useful in this effort. The text that the backlinks use to point to the missing page is used as input for the creation of a four-word lexical signature. That lexical signature is shown to successfully find the target URI in over half of the test cases.
The BinProlog Experience: Architecture and Implementation Choices for Continuation Passing Prolog and First-Class Logic Engines
Venue: arXiv cs.PL 2011
Year: 2011

We describe the BinProlog system's compilation technology, runtime system and its extensions supporting first-class Logic Engines while providing a short history of its development, details of some of its newer re-implementations as well as an overview of the most important architectural choices involved in their design. With focus on its differences with conventional WAM implementations, we explain key details of BinProlog's compilation technique, which replaces the WAM with a simplified continuation passing runtime system (the "BinWAM"), based on a mapping of full Prolog to binary logic programs. This is followed by a description of a term compression technique using a "tag-on-data" representation. Later derivatives, the Java-based Jinni Prolog compiler and the recently developed Lean Prolog system refine the BinProlog architecture with first-class Logic Engines, made generic through the use of an Interactor interface. An overview of their applications with focus on the ability to express at source level a wide variety of Prolog built-ins and extensions, covers these newer developments.