waashk/dblp huggingface dataset:
self-organizing broker topologies for publish/subscribe systems. distributed publish/subscribe systems are usually deployed on top of an overlay network that enables complex routing strategies implemented in the application layer. up to now, only little effort has been spent on the design of the broker overlay network assuming that it is either static or manually administered. as publish/subscribe systems are increasingly targeted at dynamic environments where client behavior and network characteristics vary over time, static overlay networks lead to suboptimal performance. in this paper, we present a self-organizing broker overlay infrastructure that adapts dynamically to achieve a better efficiency on both, the application and the network layer. this is obtained by taking network metrics as well as notification traffic into account.
a progressive learning method for symbols recognition. this paper deals with a progressive learning method for symbols recognition which improves its own recognition rate when new symbols are recognized in graphics documents. we propose a discriminant analysis method which provides allocation rules from learning samples with known classes. however a discriminant analysis method is efficient only if learning samples and data are defined in the same conditions but it is rare in real life. in order to overcome this problem, a conditional vector is added to each observation to take into account the parasitic effects between the data and the learning samples. we propose also an adaptation to consider the user feedback.
semi-automatic model integration using matching transformations and weaving models. model transformations are at the heart of model driven engineering (mde) and can be used in many different application scenarios. for instance, model transformations are used to integrate very large models. as a consequence, they are becoming more and more complex. however, these transformations are still developed manually. several code patterns are implemented repetitively, increasing the probability of programming errors and reducing code reusability. there is not yet a complete solution that automates the development of model transformations. in this paper we propose a novel approach that uses matching transformations and weaving models to semi-automate the development of transformations. matching transformations are a special kind of transformations that implement heuristics and algorithms to create weaving models. weaving models are models that capture different kinds of relationships between models. our solution enables to rapidly implement and to customize these heuristics. we combine different heuristics, and we propose a new metamodel-based heuristic that exploits metamodel data to automatically produce weaving models. the weaving models are derived into model integration transformations.
automating model transformation by example using inductive logic programming. model transformation by example [18] is a novel approach in model-driven software engineering to derive model transformation rules from an initial prototypical set of interrelated source and target models, which describe critical cases of the model transformation problem in a purely declarative way. in the current paper, we automate this approach using inductive logic programming [14] which aims at the inductive construction of first-order clausal theories from examples and background knowledge.
system support for mobile augmented reality services. developing and deploying augmented reality (ar) services in pervasive computing environments is quite difficult because almost of all current systems require heavy and bulky head-mounted displays (hmds) and are based on inflexible centralized architectures for detecting service locations and superimposing ar images. we propose a light-weight mobile ar service framework that combines personal mobile devices most of people own nowadays, visual tags as inexpensive ar techniques, and mobile code that enables easy-to-deploy environments. our framework enables developers to easily deploy mobile ar services in pervasive computing environments and users to interact them in a both of practical and intuitive way.
quorum-based consistency management among replicas in ad hoc networks with data update. in this paper, we propose a consistency management method that constructs quorums with a small number of mobile hosts in ad hoc networks. in this method, when a mobile host discovers paths to other mobile hosts that construct quorums, it restricts the propagation area of query packets. as a result, this method can reduce the communication overhead while keeping the strict consistency among replicas.
capturing data usefulness and privacy protection in k-anonymisation. k-anonymisation is an approach to protecting privacy contained within a data set. a good k-anonymisation algorithm should anonymise a data set in such a way that private information contained within it is hidden, yet anonymised data is still useful in intended applications. maximising both data usefulness and privacy protection in k-anonymisation is however difficult. in this paper, we suggest a metric that attempts to quantify these two properties and introduce a clustering based algorithm that can achieve a balance between them in k-anonymisation.
bounded-distance multi-coverage backbones in wireless sensor networks. topology control can improve the performance of wireless sensor network (wsn) by allowing only a subset of nodes to be active at any time with guaranteed network coverage. we present the first centralized and distributed solutions for computing bounded-distance multi-coverage backbones in wsns. the solutions are based on the (k, r)-cds problem from graph theory for computing backbones in which any regular node is covered by at least k backbone members within distance r, offering a variable degree of redundancy and reliability. applications that require reliable data gathering with bounded-delays are the intended targets for such structures. given that the centralized solution is unsuitable for wsns, because of the incurred control overhead, it is used as a lower bound for evaluating the performance of the distributed solution. the distributed solution is source-based in the sense that usually the base-station (or sink) is the focus of attention in a wsn. the two approaches are evaluated through extensive simulations, and it is shown that even though the distributed solution builds larger backbones, it does not incur on much control overhead.
an aspect-generated approach for the integration of applications into grid. updating legacy applications to let them properly run in a grid environment generally requires a noticeable development effort. the approach proposed in this work is intended to reduce this effort through the automated generation of aspects that, once incorporated into legacy applications, ensure integration with the globus grid environment. the generated aspects encapsulate concerns handling the interaction with globus services, thus keeping the relevant code separated from application classes.
a component-based framework for the internet content adaptation domain. small mobile devices for accessing the internet through wireless access networks have become increasingly common in recent years. in this new context, a major challenge is the adaptation of content to these devices, satisfying their capabilities and user preferences and optimizing the use of wireless access networks. this paper therefore presents a framework based on component reuse for the development of applications for internet content adaptations.
videolib: a video digital library with support to spatial and temporal dimensions. nowadays, a large amount of digital video can be found on the web, and this number is increasing rapidly. metadata should be associated to video in order to enable an efficient identification, indexing and semantic representation of it, so that effective video information retrieval tools can be built. both dublin core and mpeg-7 standards provide a metadata set which enables the description of multimedia content. this paper presents a video digital library, known as videolib, which utilizes dublin core and mpeg-7 audiovisual descriptions to provide video content retrieval. mainly, videolib enhances video retrieval by introducing spatial and temporal operators.
a new adaptive accrual failure detector for dependable distributed systems. the detection of failures in distributed environments is a crucial part for developing dependable, robust, and self-healing systems. the contribution of this paper is a new failure detection algorithm that can be described as an adaptive accrual algorithm coupled with features to increase flexiblity and decrease computation costs. furthermore our evaluation results show a very good detection quality in the case of message losses.
mass edge detection in mammography based on plane fitting and dynamic programming. in this paper an automatic and effective method was proposed for mass segmentation in mammography. based on the facts that mass edges are continuous and closed curves consisted of points which have larger gradient transformation, a plane fitting method and a dynamic programming technique were applied. the regions of interest (rois) used in this study were extracted from ddsm. the preliminary experimental results show that the segmentation algorithm performs well for various types of masses.
la-tinyos: a locality-aware operating system for wireless sensor networks. a number of wsn (wireless sensor networks) applications have been deployed to monitor the environment periodically and identify anomalous events. anomalous events occur rarely. however, when an anomaly event occurs, it often carries temporal and spatial locality. observations of such events are improved by reducing the period of monitoring to increase the frequency. a task is said to be locality-aware if it supports temporal and spatial locality to automatically adjust its monitoring period. this work implements locality-aware tinyos or la-tinyos as the first locality-aware wsn operating system. with locality-aware features embedded in a kernel component, la-tinyos provides a reliable and efficient framework for developing locality-aware applications. the novel la-tinyos has significantly (more than 80%) reduce the lines of user code to perform such a task, than does tinyos. finally, we use la-tinyos to develop a locality-aware monitoring application using two dozen micaz sensors. this system is currently deployed in the reading room of public library at our university to record noise violation events.
multidimensional querying in wireless ad hoc networks. as mobile ad hoc networks (manets) become more present, new ways of data exchange become feasible. this paper presents the case of multidimensional querying in wireless ad hoc networks. new challenges both in comparison with querying of relational data in manets and respective multidimensional querying in infrastructure based wireless networks are outlined. the main objective is the optimal execution of a multidimensional query, in terms of generated traffic, access time and energy consumption overhead. in order to address these topics, we introduce a simple and collaborative query propagation and data dissemination protocol, exclusively tailored for multidimensional data. extensive performance evaluation validates the efficiency and robustness of the proposed protocol.
using hypothesis margin to boost centroid text classifier. centroid classifier is a simple and yet efficient method for text categorization. however it often suffers from the inductive bias or model misfit incurred by its assumption. in order to address this issue, training-set errors as well as training-set margins are regarded as training criterions. based on these two criterions, an overall (or global) objective function over all training examples is constructed, and optimized to produce a refined centroid classification model. the empirical assessment conducted on four benchmark collections evidence that proposed method performs comparably to state-of-the-art svm classifier in classifying performance, as well as beats it in running time.
large scale news video database browsing and retrieval via information visualization. in this paper, we have developed a novel framework to enable more effective visual analysis and retrieval of large-scale news videos via interactive visualization, so that the audiences can find news stories of interest at first glance. keyframes and keywords are automatically extracted from news video clips and visually represented according to their interestingness measurement and relations. a computational approach is also developed to quantify the interestingness measurement of video clips. our experimental results have shown that our techniques for intelligent news video analysis have the capacity to enable more effective visualization and retrieval of large-scale news videos. our visualization-based news video analysis and retrieval system is very useful for security applications and for general audiences to quickly find the news stories of interest from large-scale news videos among many channels.
solving conditional and composite constraint satisfaction problems. constraint satisfaction problems (csps) have been widely used to solve combinatorial problems. in order to deal with dynamic csps where the information regarding any possible change is known a priori and can thus be enumerated beforehand, conditional constraints and composite variables have been studied in the past decade. indeed, these two concepts allow the addition of variables and their related constraints in a dynamic manner during the resolution process. more precisely, a conditional constraint restricts the participation of a variable in a feasible scenario while a composite variable allows us to express a disjunction of variables where only one will be added to the problem to solve. in this paper we introduce a unique csp framework including conditional constraints and composite variables. we call this model, a conditional and composite csp (or cccsp). in order to solve a cccsp, we propose two methods respectively based on stochastic local search (sls) and backtrack search with constraint propagation. the experimental comparison of these two methods, on randomly generated consistent cccsps, demonstrates the efficiency of the exact method based on constraint propagation in the case of middle and under constrained problems while the sls based method is the technique of choice for highly constrained problems and also in case we want to trade search time for the quality of the solution returned (number of solved constraints).
semi-mechanization method for a unsolved optimization problem in combinatorial geometry. this paper presents a new semi-mechanization method for proving the validity of an inequality conjecture about convex n-gon when n = 8 and gaining headway in proving it when n = 9. this conjecture is generally converted into a global optimization problem which is related to heilbronn triangular problem. for solving it, the bottleneck is the complexity increasing very quickly with n. in the proposed algorithm, to reduce the dimension of freedom we first analyze the properties of the optimal configurations and try to obtain the strict polynomial inequality and equality conditions as many as possible. after the precondition, the mechanization method can be implemented to solve this nonlinear optimization problem, so we call the overall approach as semi-mechanization method. we hope our algorithm will be useful for proving the conjecture with larger value of n.
equivalent disk allocations. declustering techniques reduce query response times through parallel i/o by distributing data among multiple devices. except for a few cases it is not possible to find declustering schemes that are optimal for all spatial range queries. as a result of this, most of the research on declustering have focused on finding schemes with low worst case additive error. number-theoretic declustering techniques provide low additive error and high threshold. in this paper, we investigate equivalent disk allocations and focus on number-theoretic declustering. most of the disk allocations are equivalent and provide the same additive error and threshold. investigation of equivalent allocations offer many advantages. by keeping one of the equivalent disk allocations, we can reduce the complexity of search for good disk allocations under various criteria such as additive error and threshold. probabilistic approaches to finding good declustering schemes is feasible using equivalent allocations.
mining multiple private databases using a knn classifier. modern electronic communication has collapsed geographical boundaries for global information sharing but often at the expense of data security and privacy boundaries. distributed privacy preserving data mining tools are increasingly becoming critical for mining multiple databases with a minimum information disclosure. we present a framework including a general model as well as multi-round algorithms for mining horizontally partitioned databases using a privacy preserving k nearest neighbor (knn) classifier. a salient feature of our approach is that it offers a trade-off between accuracy, efficiency and privacy through multi-round protocols.
performance monitor unit design for an axi-based multi-core soc platform. as the physical gate-count in system-on-chip (soc) system increases and system design complexity grows steadily, it becomes more and more difficult to achieve good resource utilization by assigning each task to certain hardware ip and tracing the execution patterns of each task efficiently. therefore, the performance monitoring feature is getting more and more important to provide the ease of system monitoring and performance debugging. in this paper, we present a performance monitoring unit (pmu) for the amba advanced extensible interface (axi) bus. the pmu has capability to measure major performance metrics, such as bus latency for the specific master requests and amount of memory traffic for specific durations. it can also measure the contention of the bus masters and slaves in the soc. we present the distributor and the synchronization method to use multiple performance counting units as well. the performance monitoring unit has been verified in the platform fpga board with 9 by 4 axi interconnect configuration. these monitoring features can give the insight to system design architect by helping to find and analyze the performance bottleneck of target system.
towards an homogeneous handling of under-constrained and well-constrained systems of geometric constraints. most of the geometric constraints solvers consider systems of constraints well-constrained modulo the rigid motions group, and either halt on error when they encounter under-constrained sub-systems, or attempt to add parameterized constraints so as to get rid of the under-constriction. we studied transformations groups making well-constrained some problems that are usually considered as under-constrained. this leads to new algorithms which allow an homogeneous handling of systems of geometric constraints and thus a better adaptation to the needs of the user.
a methodology for the separation of foreground/background in arabic historical manuscripts using hybrid methods. this paper presents a new color document image segmentation system suitable for historical arabic manuscripts. our system is composed of a hybrid method which couple together background light intensity normalization algorithm and k-means clustering with maximum likelihood (ml) estimation, for foreground/background separation. firstly, the background normalization algorithm performs separation between foreground and background. this foreground is used in later steps. secondly, our algorithm proceeds on luminance and distort the contrast. these distortions are corrected with a gamma correction and contrast adjustment. finally, the new enhanced foreground image is segmented to foreground/background on the basis of ml estimation. the initial parameters for the ml method are estimated by k-means clustering algorithm. the segmented image is used to produce a final restored document image. the techniques are tested on a set of arabic historical manuscripts documents from the national tunisian library. the performance of the algorithm is demonstrated on by real color manuscripts distorted with show-through effects, uneven background color and localized spot.
extending the arc model with generative coordination. the arc (actor, role, coordinator) model extends the actor model with roles and coordinators to achieve a behavior-based coordination model that preserves the semantics of the actor model. an arc role coordinates a dynamic set of actors whose intensional representation and membership criteria are defined by a static description of abstract behavior. an arc coordinator enacts role-based coordination policies expressed in terms of arc roles. in this paper, we focus on the satisfaction of functional coordination requirements via the generation and manipulation of actor messages by role and coordinator actors in the arc model.
federated directories of semantic web services. this paper presents a federated directory system called ws-dir, which allows registration and discovery of semantic web services. the system is designed and implemented as a federation: directory services form its atomic units, and the federation emerges from the registration of directory services in other directory services. directories are virtual clusters of service entries stored in one or more directory services. to create the topology, policies are defined on all possible operations to be called on directories.
performance problem localization in self-healing, service-oriented systems using bayesian networks. in distributed, service-oriented environments, performance problem localization is required to provide self-healing capabilities and deliver the desired quality of service (qos). this paper presents an automated approach to identifying system elements causing performance problems. applying probabilistic inference to collected response time and elapsed time data, the approach 1) infers elapsed time for services where data is missing, 2) estimates the response time degradation caused by different services using the duration, abnormality and response time correlation of their elapsed times, and 3) identifies the services that are the most important causes of slow response time and yield the most benefit if recovered. the approach has been used to localize a performance problem on the test bed of a real-world service-oriented grid. evaluation using simulations shows that the approach consistently achieves better accuracy than traditional techniques in various service-oriented settings.
dynamic populations in genetic algorithms. biological populations are dynamic in both space and time, that is, the population size of a species fluctuates across their habitats over time. there are rarely any static or fixed size populations in nature. in evolutionary computation (ec), population size is one of the most important parameters and it received attention from ec pioneers from the very beginning. despite many attempts to optimize the population sizing, the prevailing scheme in ec is still possibly the simplest --- the fixed size population. this is in strong contrast with population entities in nature. in this paper, we explore the effects of dynamic (fluctuating) populations on the performance of genetic algorithms (ga). in particular, we test five dynamic population-sizing patterns: random fluctuating population, increasing population, decreasing population, bell-shaped population, and inverse bell-shaped population and compare them against the fixed size population. our experiment shows very promising results that the dynamic populations perform more efficiently than the traditional fixed size populations, in terms of the number of fitness function evaluations and memory space requirements. we also analyze why the dynamic populations should perform superior to the fixed size populations from the biological perspective.