waashk/dblp huggingface dataset:
discovering parametric clusters in social small-world graphs. we present a strategy for analyzing large, social small-world graphs, such as those formed by human networks. our approach brings together ideas from a number of different research areas, including graph layout, graph clustering and partitioning, machine learning, and user interface design. it helps users explore the networks and develop insights concerning their members and structure that may be difficult or impossible to discover via traditional means, including existing graph visualization and/or statistical methods.
content management on server farm with layer-7 routing. service replication on a server farm is becoming increasingly widespread as the explosive growth of the web is straining the architecture of many internet sites. layer-7 routing, routing packets based on requested content, has been recognized as a powerful approach to distribute workload among these server farms. however, little attention has been given to how to configure content-related knowledge into the layer-7 routing mechanisms. in addition, the used data structures for storing content-related knowledge and lookup operation for making routing decisions are also unclear. this paper presents a management system that can support a configurable and high-performance server farm with layer-7 routing. in this system, we devised a data structure termed url table to hold content-related information for making content-aware routing decisions. we also propose a novel idea termed "url formalization", which provide a scalable solution to speedup the content-aware request routing.
efficient interactive configuration of unbounded modular systems. interactive configuration guides a user searching through a large combinatorial space of solutions to a system of constraints. we investigate a class of very expressive underlying constraint satisfaction problems: modular recursive constraint systems of unbounded size. a precomputation step is used to obtain a configuration algorithm for such systems that supports the user efficiently with bounded response time. this precomputation step determines all solutions for each module, which are computed and stored in compact data structures such as binary decision diagrams (bdds), in order to eliminate run-time search. the precomputation step also detects ill-behaved module collections that have no finite solutions. the runtime interaction algorithm scales well as its response time only depends on the amount of the information passed locally between the modules, and not on the size of the entire configured structure. our algorithm was implemented and tested on an industrial example, and gives good response times. we believe this is the first known sound and complete algorithm for solving unbounded interactive configuration problems, with bounded response time per interaction.
on the composition of java frameworks control-flows. object oriented programming languages provide, in principle, mechanisms to enhance code reuse, as an effort of designing object oriented software, design patterns and frameworks are recognised as good techniques for reuse. frameworks are of particular interest as design and code reuse are achieved. despite of that, most frameworks were designed to be adapted to applications and not to be composed with other frameworks. as a result, problems such as control-flow composition, legacy components composition, frameworks gap, entities overlap and composition of frameworks behaviour arise. the present work is a study on the composition of java frameworks control-flows, where a third framework is created from two existing ones. with this study we have checked the potential problems that may appear as two control-flows are composed via message passing.
a novel data mining algorithm for reconstructing gene regulatory networks from microarray data. in this paper, we propose a novel data mining algorithm for reconstructing gene regulatory networks (grns) from microarray data. by making use of the proposed probabilistic measure, it is able to mine noisy, high dimensional expression data for interesting association patterns of genes without the need for additional feature selection procedures. moreover, it can make explicit hidden patterns discovered for possible biological interpretation and also predict gene expression patterns in the unseen tissue samples. experimental results on real expression data show that it is very effective and the discovered association patterns reveal biologically meaningful regulatory relationships of genes that could help users reconstructing the underlying structures of grns.
a code compression advisory tool for embedded processors. we present a tool which is designed to be used as a code compression advisory system for object code to be run on an embedded processor. all the compression schemes support run-time random decompression. given the machine instruction set architecture, the encoding of instructions, and a set of object programs to be compressed, the tool analyzes the code, gathers statistics about static instruction frequencies and other relevant information, and performs a relative evaluation of a suite of compression strategies. the tool produces as output, the sizes of the compressed code, the line address table (if one is required), and the dictionary (if there is only one) or the sizes of all dictionaries if there are several, for various choices of parameters input by the user. the final result helps one to decide a code compression strategy for the input processor. we have used the tool to evaluate alternate schemes for a suite of benchmarks for the ti tms320c62x instruction set architecture and the intel strongarm processor and report results.
query length impact on misuse detection in information retrieval systems. misuse is the abuse of privileges by an authorized user and is the second most common form of computer crime after viruses. earlier we proposed a misuse detection approach for information retrieval systems that relied on relevance feedback. the central idea focused on the building of a user profile containing both query and feedback terms from prior queries. our algorithm matched new activities to existing profiles and assigned a likelihood of misuse to an activity. only initial evaluation was provided.we now expand and evaluate our system using both short and long queries noting the effect of query length in the accuracy of the detection. the results indicate an overall precision of 83.9% when short queries are used, and 82.2% for long queries. the rate of the undetected misuse for short queries is less than 2% and for long queries less than 6%. although higher precision score configurations result in a lower false alarm rate, unfortunately, they increase the rate of undetected misuse both for short and long queries. given this tradeoff, for any particular application constraint, system behavior can be tuned to minimize either false alarms or undetected misuse.
long time step molecular dynamics using targeted langevin stabilization. we introduce the b-spline mollified impulse (molly) and the targeted molly (tm) for molecular dynamics (md). tm uses targeted langevin coupling to stabilize b-spline molly. results show that with a proper choice of parameters, the radial distribution function can be correctly recovered and the self-diffusion co-efficient can be correctly estimated from md simulations of flexible waters using tm with outer time step of 16 fs, and a six-fold speedup is obtained. the basis of comparison is leapfrog with time step of 1 fs the overhead associated with mollification is low. extention to handle larger molecules is discussed.
transformation of yepc business process models to yawl. model transformations are frequently applied in business process modeling to bridge between languages on a different level of abstraction and formality. in this paper, we define a transformation between yepcs which is an extension to the popular event-driven process chain (epc) and yawl, a formal workflow language that is able to capture all of the 20 workflow patterns reported in [1]. we illustrate the transformation challenges and present a suitable transformation algorithm. the benefit of the transformation is threefold. first, it clarifies the semantics of yepcs via a mapping to yawl. second, the deployment of yepc business process models as workflows is simplified. thirdly, yepc models can be analyzed with yawl verification tools.
nonlinear instability in multiple time stepping molecular dynamics. this paper discusses additional stability limitations of multiple time stepping (mts) integrators for molecular dynamics (md) that attempt to bridge time scales. in particular, it is shown that when constant-energy (nve) simulations of newton's equations of motion are attempted using the verlet-i/r-respa/impulse, there are nonlinear instabilities when the longest step size is one third and possibly one fourth of the period(s) of the fastest motion(s) in the system. this is demonstrated both thorough the analysis of a nonlinear model problem and through a through set of numerical simulations.
optimization of a language for data mining. constraint-based mining has attracted in recent years the interest of the data mining research community because it increases the relevance of the result set, reduces its volume and the amount of workload. however, constrained-based mining will be completely feasible only when efficient optimizers for mining languages will be available.this paper is a first step towards the construction of optimizers for a constraint-based mining language. it provides the guidelines for the comparison of classes of statements by means of the relationships existing between their result sets. furthermore it identifies as useful information to the optimization the presence of unique constraints and functional dependencies in the schema of the database. we show the practical implications of the discussed principles with a set of algorithms designed for a specific mining language. these algorithms use also a new designed index, called mining index that allows to reduce the portion of the database to be read in response to some classes of queries. in these cases the workload of the mining engine is greatly reduced or completely avoided in a significant subset of the cases.
generating correct epcs from configured c-epcs. process reference models play an important role for the alignment and configuration of commercial off-the-shelf enterprise systems to requirements of an organization. recently, configurable event-driven process chains (c-epcs) have been proposed as a language to support the model-driven configuration of such enterprise systems. while some problems of generating correct epcs from a configured c-epc have been discussed, up to now there is no implementation of an algorithm available to automate the configuration task. this paper presents a configuration algorithm that is guided by a minimality criterion. it details and extends a previous algorithm that has only been sketched so far. as a proof-of-concept the algorithm has been implemented.
an empirical evaluation of client-side server selection policies for accessing replicated web services. replicating web services at geographically distributed servers can offer client applications with a number of benefits, including higher service availability and improved response time. however, selecting the "best" server to invoke at the client side is not a trivial task, as this decision needs to account for (and is affected by) a number of factors, such as local connection capacity, external network conditions and servers workload. this paper presents the results of an experiment in which we implemented and empirically evaluated the performance of five server selection policies for accessing replicated web services. the experiment involved two client stations, with different connection capacities, continuously applying the five policies to invoke a real-world web service replicated over four servers in three continents. our results show that, in addition to the individual performance of each server, service response time using the five policies is affected mainly by client differences in terms of connection capacity and workload distribution throughout the day.
a web services composition approach based on software agents and context. we present an agent-based and context-oriented approach for web services composition. a web service is an accessible application that other applications and humans can discover and trigger to satisfy various needs. due to the complexity of web services composition, we consider two concepts to reduce this complexity: software agent and context. a software agent is an autonomous entity that acts on behalf of users, whereas context is any information relevant to characterize a situation. during composition, software agents engage conversations with their peers to agree on the web services that will participate in the composition.
propositional planning in bdi agents. this paper aims to describe the relationship between propositional planning systems and the process of means-end reasoning used by bdi agents. to show such relationship, we define a mapping from bdi mental states to propositional planning problems and from propositional plans back to mental states. in order to test the viability of such mapping, we have implemented it in an extension of a bdi agent model through the use of graphplan as the propositional planning algorithm. the implementation was applied to model a case study of an agent controlled production cell.
intelligent agents for patient monitoring and diagnostics. this paper describes intelligent monitor agents (im-agents), a project that utilizes intelligent multiagents to assist patient health care. clinicians must simultaneously audit and interpret an overwhelming amount of information regarding a patient during the process of monitoring, performing diagnostics and determining therapeutic intervention. multiple im-agents coordinate as a team with each agent performing specialized monitor and diagnostic tasks. fuzzy logic, connection networks, trend analysis and qualitative logic methods are used within the dynamic decision modules of all im-agents. the agents are autonomous, interactive, mobile and capable of performing dynamic intelligent inference during execution. decision functionality is demonstrated in preliminary prototype test cases involving emergency trauma scenarios, particularly focusing on stabilizing hemorrhagic shock.
self-organization and computer security: a case study in adaptive coordination. one frequently hears stories about security breeches. despite all the money that has been fed into research in computer security, it looks like researchers are loosing the battle against attackers. this paper argues that one basic problem in security systems is their staticness, and suggests they should be dynamic in nature. this paper describes two cases where adaptiveness based on self-organization may lead to dynamic solutions to malicious code protection and security policy distribution.
editorial message: special track on coordination models, languages and applications. in last few years, the field of coordination models and languages has earned the respect of other computer science researchers as they recognized that the understanding of how parts can be efficiently organized as a ensemble is of prime importance to the design of distributed complex systems. the proliferation of network computing and mobile computation, and especially the ubiquity of the internet has made coordination one of the key areas in modern computing. this track aims at bringing together researchers working on applied issues in coordination, ranging from new models to applications.
a new approach to scalable linda-systems based on swarms. natural forming multi-agent systems (aka swarms) have the ability to grow to enormous sizes without requiring any of the agents to oversee the entire system. the success of these systems comes from the fact that agents are simple and the interaction with the environment and neighboring agents is local in nature. in this paper we look at abstractions in the field of swarms and study their applicability in the context of coordination systems. in particular, we focus on the problematic issue of scalability of linda systems.
the fading concept in tuple-space systems. tuple-space systems based on the linda model have been in use in distributed systems for nearly two decades. an area that has recently received attention from the distributed systems community is swarm intelligence (si) --- si has been successfully used in fields such as robotics and optimisation. recently its properties have started to attract research in distributed systems. in this paper we merge si concepts into the linda model to provide an adaptive approach to time which is unrelated to external (real) time: the result is the introduction of an adaptive concept of time into the system, without changing the linda model --- we call it fading. some potential applications of this concept are discussed, along with implications for feasible implementation.
an adaptive energy efficient cache invalidation scheme for mobile databases. this paper presents adaptive energy efficient cache invalidation scheme (aeecis) for the wireless mobile environment. the algorithm is adaptive since it changes the data dissemination strategy based on the current conditions. to reduce the bandwidth requirement, the server transmits in one of three modes: slow, fast or super-fast. the mode is selected based on thresholds specified for time and the number of clients requesting updated objects. an efficient implementation of aeecis is presented and simulations have been carried out to evaluate its caching effectiveness. the results demonstrate that it can substantially improve mobile caching by reducing the communication bandwidth for query processing. compared to previous ir-based schemes, aeecis can significantly improve bandwidth consumption and the number of uplink requests.
a mobile agent approach for global database constraint checking. integrity constraints are valuable tools for enforcing consistency of data in a database. global integrity constraints ensure integrity and consistency of data spanning multiple databases. in this paper, we propose a general framework of a mobile agent based approach for checking global constraints. an insert/update/delete initiated on single site, say s1 may cause the violation of a global constraint. the check for such violation involves accessing related data from multiple sites, say s2...sn. constraint checker on site s1 generates sub constraint checks on sites s2...sn and sends multiple remote agents, rmagent2...rmagentn to sites s2...sn respectively for checking the sub constraints. these remote agents carry with them data processing code to be executed at remote sites. constraint checker gathers results from the remote agents and decides if any constraint is violated. the constraint checking mechanism is much faster as the sub constraint checks are executed in parallel.
our guest agents are welcome to your agent platforms. multiagent applications will appear more and more in open, heterogeneous, evolving and distributed environments, such as the internet. in order to run in such environments, agents will need to adapt themselves to new platforms and protocols. we propose a model of agents that are able to run, communicate and move between different multiagent platforms. this model is based on a middleware between such agents and platforms. it has been implemented on a kind of agents called guest which can be used the same way regardless of what kind of servers they run on, notably, through tools such as a graphical management tool or a server launcher. also, we provide a mechanism based on plug-ins that allows modification of basic agent behaviors like manipulation of messages, control of migration, etc. lastly, we propose two kinds of dynamic agent hierarchies based on plug-ins or middleware.
a multi-agent system for efficiently managing query answering in an e-government scenario. this paper aims at studying the exploitation of the intelligent agent technology for supporting citizens in their access to e-government services. it appears particularly suited in the present e-government scenario characterized by a huge amount of heterogeneous data and services, delivered by government agencies, that makes difficult to quickly answer citizen queries. in this paper we show that the exploitation of the intelligent agent technology facilitates the search of information on government data sources in such a way to completely and precisely satisfy citizen queries. our system creates and maintains suitable profiles of involved users, representing their preferences and exigencies; in addition, it adopts suitable algorithms that exploit information stored in citizen profiles for producing recommendations.
supplier network management: evaluating and rating of strategic supply networks. based on changing market conditions and pressure on cost and productivity, companies in different industries have started do concentrate on their core competencies and to decrease vertical range of manufacture which leads to an increasing outsourcing of business processes. with this outsourcing the dependency of companies on their business partners rises significantly forming so called value networks. supplier relationship management (srm) offers methods and tools to manage direct suppliers. in order to perform well in these value networks srm needs to be extended towards supply network management (snm) by methods and tools to identify, evaluate, rate and select strategic suppliers located not only in tier one, but also in the subsequent tiers. the selection of adequate supply networks, satisfying different evaluation criteria, is therefore of main importance and builds the topic of this paper. the paper is based on preparatory work done in the area of strategic supply network development (ssnd), where the identification of strategic supply networks has been elaborated, and focuses on the evaluation and ranking of strategic supply networks providing the base for supply network selection.
can a parser be generated from examples? one of the open problems in the area of domain-specific languages is how to make domain-specific language development easier for domain experts not versed in a programming language design. possible approaches are to build a domain-specific language from parameterized building blocks or by language (grammar) induction. this paper uses an evolutionary approach to grammar induction. grammar-specific genetic operators for crossover and mutation are proposed to achieve this task. suitability of the approach is shown by small experiments where underlying grammars are successfully genetically obtained and parsers are than automatically generated.
k-gram based software birthmarks. software birthmarking relies on unique characteristics that are inherent to a program to identify the program in the event of suspected theft. in this paper we present and empirically evaluate a novel birthmarking technique which uniquely identifies a program through instruction sequences. to evaluate the strength of the birthmarking technique we examine two properties: credibility and resilience to semantics-preserving transformations. we show that the technique provides both high credibility and resilience. additionally, it complements previously proposed static birthmarking techniques.
a bayesian approach for protein classification. in this work, we propose a new approach for protein classification based on bayesian classifiers. our goal is to predict the functional family of novel protein sequences based on their motif composition. for this purpose, datasets extracted from prosite, a curated protein family database, are used as training datasets. in the conducted experiments, the performance of our classifier is compared to other known data mining approaches. the computational results have shown that the proposed method outperforms the other ones and looks very promising for problems with characteristics similar to the problem addressed here.