waashk/dblp huggingface dataset:
on the persistence of deleted windows registry data structures. deleted entries in the windows registry remain in the hives that contain them but their space is marked as free for future use. in this paper we analyse the fragmentation of these deallocated blocks and how long they persist by surveying a number of hives over a long period of time. we formalise retrieval of data and define 'consistency' with respect to deleted keys. we illustrate how uninstallation programs may inadvertently corrupt the keys they are deleting in the uninstallation process by analysing the keys during the uninstallation of a popular media software suite.
resource sharing in behavioral based scheduling. in this paper, two main contributions are presented. first, the behavioral importance dual priority server (bids) reservation mechanism is extended to contemplate more than two importance levels. in fact, an integer-value function is used to postpone the reactivation of the server based on the last result obtained. second, a resource contention algorithm for bids is presented. although it may seem simple, the resource reservation paradigm may have certain anomalies while sharing resources. the proposal is an extension of the stack resource policy which is formally proved.
a mobility management scheme using sctp-sip for real-time services across heterogeneous networks. the session initiation protocol (sip) has been enhanced to support seamless mobility in heterogeneous networks. however, it still suffers from significant handoff delays and packet losses unacceptable for real-time multimedia services. in this paper, we propose a mobility management scheme for real-time services across heterogeneous networks that combines sip and stream control transmission protocol (sctp). our scheme ensures transport-layer continuance through the multi-homing functionality of sctp while maintaining location and network transparency through sip without the use of re-invite message signaling. an evaluation of our approach demonstrates that it provides seamless mobility while satisfying the quality of service (qos) requirements for real-time multimedia services without any changes in the underlying network infrastructure.
enhancing xml data warehouse query performance by fragmentation. xml data warehouses form an interesting basis for decision-support applications that exploit heterogeneous data from multiple sources. however, xml-native database systems currently suffer from limited performances in terms of manageable data volume and response time for complex analytical queries. fragmenting and distributing xml data warehouses (e.g., on data grids) allow to address both these issues. in this paper, we work on xml warehouse fragmentation. in relational data warehouses, several studies recommend the use of derived horizontal fragmentation. hence, we propose to adapt it to the xml context. we particularly focus on the initial horizontal fragmentation of dimensions' xml documents and exploit two alternative algorithms. we experimentally validate our proposal and compare these alternatives with respect to a unified xml warehouse model we advocate for.
diverse peer selection in collaborative web search. effective peer selection for intelligent query routing is a challenge in collaborative peer-based web search systems, especially unstructured networks that do not have any centralized control of peer document collections. in particular, routing a query to multiple peers that provide the same results is a waste of resources. to deal with overlapping document collections we propose a diverse peer selection approach for adaptive query routing. this approach takes into account not only which neighbors are the best resource providers for a given query, but also which combinations of neighbors can provide the least redundant results. we validate the feasibility of our proposed algorithm by presenting several simulation experiments conducted with different configurations of peer network environments. two novel evaluation measures, distributed precision and distributed recall, are also introduced to provide an effective comparison of different peer network systems. these two performance measures extend the well known ir measures of precision and recall by integrating network costs, namely bandwidth and latency. our algorithm finds results of equivalent quality using less time and generating less traffic in the presence of varying amounts of document duplication.
a practical solution for scripting language compilers. although scripting languages are becoming increasingly popular, even mature scripting language implementations remain interpreted. several compilers and reimplementations have been attempted, generally focusing on performance. based on our survey of these reimplementations, we determine that there are three important features of scripting languages that are difficult to compile or reimplement. since scripting languages are defined primarily through the semantics of their original implementations, they often change semantics between releases. they provide large standard libraries, which are difficult to re-use, and costly to reimplement. they provide c apis, used both for foreign-function-interfaces and to write third-party extensions. these apis typically have tight integration with the original implementation. finally, they support run-time code generation. these features make the important goal of correctness difficult to achieve. we present a technique to support these features in an ahead-of-time compiler for php. our technique uses the original php implementation through the provided c api, both in our compiler, and an our generated code. we support all of these important scripting language features, particularly focusing on the correctness of compiled programs. additionally, our approach allows us to automatically support limited future language changes. we present a discussion and performance evaluation of this technique, which has not previously been published.
preservation of ordering in a network of brokers. some distributed applications, such as online collaborative whiteboards, chat systems, multiplayer games and others, have a need for causal and total ordering. those applications exploit computer networks in order to connect publishers and subscribers of events, generally using a publish/subscribe middleware for that purpose. however, most state of the art pub-sub middlewares focus on best-effort services, without providing event ordering guarantees. this paper presents an overview of our proposed solution, which uses the distributed shared memory model to provide causal and total ordering of events in subject-based pub-sub middlewares. we also present a proof of concept for our architecture, an online collaborative whiteboard.
legal-tree: a lexicographic multi-objective genetic algorithm for decision tree induction. decision trees are widely disseminated as an effective solution for classification tasks. decision tree induction algorithms have some limitations though, due to the typical strategy they implement: recursive top-down partitioning through a greedy split evaluation. this strategy is limiting in the sense that there is quality loss while the partitioning process occurs, creating statistically insignificant rules. in order to prevent the greedy strategy and to avoid converging to local optima, we present a novel genetic algorithm for decision tree induction based on a lexicographic multi-objective approach, and we compare it with the most well-known algorithm for decision tree induction, j48, over distinct public datasets. the results show the feasibility of using this technique as a means to avoid the previously described problems, reporting not only a comparable accuracy but also, importantly, a significantly simpler classification model in the employed datasets.
multi-agent system adaptation in a peer-to-peer scenario. from a system's perspective ---as opposed to an individual agent perspective---, mas adaptation is now becoming an important topic, since it can help to obtain expected outcomes under changing circumstances. in this paper, we propose a mas architecture (2-lama) to adapt social conventions in dynamic systems. the proposed architecture consist of two layers: the conventional mas system (we call domain-level) and an additional layer or meta-level in charge of adaptation. a peer-to-peer scenario helps us to illustrate our approach. the resulting model changes participant organisation depending on environment and agent changes. finally, we present some preliminary results of the empirical evaluation of our approach.
prestige-based peer sampling service: interdisciplinary approach to secure gossip. the peer sampling service (pss) has been proposed as a method to initiate and maintain the set of connections between nodes in unstructured peer to peer (p2p) networks. the pss usually relies on gossip-style communication where participants exchange their links in a randomized way. however, the pss network organization can be easily modified by malicious nodes running a "hub attack", in which they achieve a leading structural position. from this prestigious status, the malicious nodes can severely affect the overlay and achieve several application dependent advantages. we present a novel method to overcome this attack and provide results from simulation experiments that validate our claim. this method is inspired by a simple technique used to detect social leaders in firm's organizations that is based on the social (structural) "prestige" of actors.
bulk based preconditioning for quantum dot computations. this article describes how to accelerate the convergence of preconditioned conjugate gradient (pcg) type eigensolvers for the computation of several states around the band gap of colloidal quantum dots. our new approach uses the hamiltonian from the bulk materials constituent for the quantum dot to design an efficient preconditioner for the folded spectrum pcg method. the technique described shows promising results when applied to cdse quantum dot model problems. we show a decrease in the number of iteration steps by at least a factor of 4 compared to the previously used diagonal preconditioner.
rpp: reference pattern based prefetching controller. we propose a prefetching technique that recognizes and exploits reference patterns. reference pattern based prefetching (rpp) detects sequential and non-sequential reference patterns and takes different prefetch action according to this information. beyond sequential detection, rpp recognizes repetitive occurences of consecutive sequences, and then exploits these repetitions. in this paper, we show that rpp results in favorable performance gains.
a robust and tractable contact model for dynamic robotic simulation. existing contact modeling in rigid body simulation is inadequate for robotics: no algorithms guarantee both convergence and nonpenetration at multiple contact points in the presence of coulomb friction. we present a convex optimization based algorithm that models simultaneous contact at multiple points, ensures nonpenetration, and yields coulomb friction effects. an example of simulated robotic grasping shows that the proposed algorithm is robust where most other methods fail.
a recommender system for requirements elicitation in large-scale software projects. in large and complex software projects, the knowledge needed to elicit requirements and specify the functional and behavioral properties can be dispersed across many thousands of stakeholders. unfortunately traditional requirements engineering techniques, which were primarily designed to support face-to-face meetings, do not scale well to handle the needs of larger projects. we therefore propose a semi-automated requirements elicitation framework which uses data-mining techniques and recommender system technologies to facilitate stakeholder collaboration in a large-scale, distributed project. our proposed recommender model is a hybrid one designed to manage the placement of stakeholders into highly focused discussion forums, where they can work collaboratively to generate requirements. in our approach, statements of need are first gathered from the project stakeholders; unsupervised clustering techniques are then used to identify cohesive and finely-grained themes and a users' profile is constructed according to the interests of the stakeholders in each of these themes. this profile feeds information to a collaborative recommender, which predicts stakeholders' interests in additional forums. the validity and effectiveness of the proposed recommendation framework is evaluated through a series of experiments using feature requests from three software systems.
: a scalable multicore code for rna secondary structure prediction. the prediction of the correct secondary structures of large rnas is one of the unsolved challenges of computational molecular biology. among the major obstacles is the fact that accurate calculations scale as o(n4), so the computational requirements become prohibitive as the length increases. existing folding programs implement heuristics and approximations to overcome these limitations. we present a new parallel multicore and scalable program called gtfold, which is one to two orders of magnitude faster than the de facto standard programs and achieves comparable accuracy of prediction. development of gtfold opens up a new path for the algorithmic improvements and application of an improved thermodynamic model to increase the prediction accuracy. in this paper we analyze the algorithm's concurrency and describe the parallelism for a shared memory environment such as a symmetric multiprocessor or multicore chip. in a remarkable demonstration, gtfold now optimally folds 11 picornaviral rna sequences ranging from 7100 to 8200 nucleotides in 8 minutes, compared with the two months it took in a previous study. we are seeing a paradigm shift to multicore chips and parallelism must be explicitly addressed to continue gaining performance with each new generation of systems. we also show that the exact algorithms like internal loop speedup can be implemented with our method in an affordable amount of time. gtfold is freely available as open source from our website.
secure web-based retrieval of documents with usage controls. usage controls enable the provider of some information to limit how recipients may use it. usage controls may be desirable in enterprise environments, e.g., for regulatory compliance or to protect intellectual property in collaborative endeavors. we contribute web protocol, server, and browser modifications for hardening existing software-based usage controls (e.g., pdf's) with trusted platform modules (tpms). tpms are low-cost secure coprocessors present in an increasing number of computers. we use the tpm to prevent untrusted software from opening usage-controlled files. we implemented the proposed solution on linux by adding a linux security module to the kernel and modifying apache and firefox. no modifications are necessary in applications used for authoring and displaying usage-controlled files (e.g., openoffice and xpdf). experiments show that the proposed scheme has modest impact on client response time and server cpu utilization.
banzai: a java framework for the implementation of high-performance servers. this paper presents banzai a java framework that uses the tatoo parser generator to simplify the implementation of high-performance servers based on plain-text protocols. this approach conciliates the use of formally defined grammars for protocol parsing and the efficiency of the implementation. we argue that the use of the formal grammars simplifies the implementation of the protocol and we show that an http server built using the banzai framework is as efficient as several existing ad-hoc high-performance http servers. the banzai framework relies on the ability of tatoo to produce push non-blocking parsers with a fixed memory footprint during parsing and on a generic and efficient server architecture.
a detecting and tracing algorithm for unauthorized internet-news plagiarism using spatio-temporal document evolution model. prevailing plagiarism among digital documents is one of the serious problems associated with the development of the internet. it is not difficult to find news articles which have been copied without authorization. internationally, newspapers may deal with the same event, and want to publish the article as soon as possible. so, a few internet-based news media plagiarize news articles of other companies, rather than writing their own articles, by sending a reporter or relying on syndication. this kind of news article plagiarism boosts the number of internet news articles, which are all mostly identical, due to text copying and pasting. and, these kinds of plagiarized articles prevent internet searching tools from collecting original articles. for example, it is known that more than 10--20% of articles collected by portal sites are nearly identical or quite similar. in order to deal with this problem we need a strict and stable tool for detecting internet news plagiarism. also, if possible, it is highly desirable to perform a trace back to reconstruct the history of plagiarism. in this paper, we suggest a new detection algorithm for unauthorized news article plagiarism using a spatio-temporal evolution model. using this model, we can reveal the sequence of plagiarism among news articles.
information-theoretic identification of content pages for analyzing user information needs and actions on the multimedia web. increasing use of media in web pages is fueling the metamorphosis of the www into a multimedia web. the development of information organization, analysis, and search technologies that enable people to efficiently find the specific information they require becomes especially important in this context. determining the information goal of a user is a critical step in this direction. however, the information goal is typically subjective and latent. its determination is further complicated in multimedia websites since the semantics of media-based information is context-based and emergent. furthermore, interaction modalities with media are, unlike static link-based browsing, complex to analyze. in this paper we address the problem of automatically determining the content pages given the browsing behavior of a user. the content pages contain the information the user came to the site to find. thus, their identification is a critical step in reasoning about user information goals. we propose an information theoretic approach that takes into account the organization of the web site, the multimedia information content, as well as the influence of a specific browsing pattern to identify one or more pages that putatively contain the information goal(s). this method can be used irrespective of whether the user has a single information goal or is looking to satisfy multiple information needs. experimental investigations on media rich sites illustrate the efficacy of the technique and its potential in modeling user information needs and actions in a multimedia web.
modeling and analyzing review information on the web focusing on credibility. in this paper we modeled review information to assess its credibility. we think the information to support users in credibility evaluation of reviews is necessary. this paper presents method for detecting reviewers' activity areas and biases. we also discuss the problem of glorified terms in online reviews. as these terms cause cognitive bias, supporting information that enables accurate understanding is needed.
a light-weight summarizer based on language model with relative entropy. a new method for sentence extraction on the basis of language model with relative entropy is presented in this paper. the proposed technique first builds a sentence language model and document cluster language model respectively for the sentence and the documents. the sentences are then ranked according to the relative entropies of the estimated document language model with respect to the estimated sentence language model. the overall results on duc and mse corpus demonstrate that the proposed approach outperforms some of the best reported results for generic multi-document summarization.
user-media interaction with interactive tv. watching tv is a practice many people enjoy and feel comfortable with. we propose the capture of the user interaction while interacting with a remote control to watch tv: such detailed information is most valuable to many applications and services. we discuss our proposed approach in the context of the brazilian interactive digital tv platform.
policy management architecture based on provisioning model and authorization certificates. the unified management of user rights and access control policies in a corporation with many units is not easy to implement. moreover, most of the distributed access control systems are complex and heterogeneous, making it hard to maintain a unified control over all fine grained policies employed by each unit. this paper proposes a unified administration of policies for corporation environments by applying a management scheme based on authorization certificates. these certificates allow the derivation of new fine grained policies in the domain of each unit, assuring that no corporation policies will be violated. these new policies update automatically the corporation repository, preserving the unified management of user rights, and then update the corresponding policy repository of each unit. our proposal provides a real loosely coupled policy management scheme using a serverless public key infrastructure and the web services technology. the prototype shows the proposal viability.
efficient mobile reasoning for pervasive discovery. semantic service discovery architectures that operate in mobile environments must cope with the significant challenges of finding relevant services rapidly, while facing constrained computational resources. this paper presents our m-tableaux algorithm for enabling cost-efficient and optimised semantic reasoning to support semantic service matching, on the device itself. we present a performance evaluation of the m-tableaux optimisation strategies which clearly demonstrate its operational feasibility on a mobile device. we also present comparative evaluations with other semantic reasoners and establish the improved performance of our engine.
body-and-cad geometric constraint systems. motivated by constraint-based cad software, we develop the foundation for the rigidity theory of a very general model: the body-and-cad structure, composed of rigid bodies in 3d constrained by pairwise coincidence, angle and distance constraints. we identify 21 relevant geometric constraints and develop the corresponding infinitesimal rigidity theory for these structures. the classical body-and-bar rigidity model can be viewed as a body-and-cad structure that uses only one constraint from this new class. as a consequence, we identify a new, necessary but not sufficient, counting condition for minimal rigidity of body-and-cad structures: nested sparsity. this is a slight generalization of the well-known sparsity condition of maxwell.
an approximate approach to constraint solving in soft sensing. soft sensing is usually presented as a constraint solving problem. in a manufacturing context, traditional methods of soft sensing have to face challenges in robustness and efficiency. in this paper, we proposed a granular-based approach to constraint solving for soft sensing. in our method, we first construct a granular-based soft sensing model, then estimate bounds of each granule, and finally solve this granulated problem with a smaller size. according to our analysis, this method is robust and efficient.