waashk/dblp huggingface dataset:
towards self-configuration and management of e-service provisioning in dynamic value constellations. networked value constellations are collections of enterprises that jointly satify complex consumer needs. increasingly, such needs are satisfied by e-services, i.e. commercial services that can be ordered and provisioned via the internet. current research in dynamic web-service composition has yielded run-time platforms to dynamically compose complex web services, but there is still a considerable gap between web services and commercial e-services. to compose e-services, an estimation of commercial profitability must be made, which is absent from web service composition. in this paper, we extend our earlier approach to e-service composition with a dynamic part, that ensures that a commercial e-service can be dynamically composed from other commercial e-services, and can be mapped on a web service composition process composition of lower-level web services. we propose a skeleton-oriented approach, that first composes a network of enterprises, jointly satisfying need, based on commercial considerations. second, given a set of such candidate value constellations, the business processes providing the services can be dynamically configured. we illustrate this skeleton-driven composition of networked value constellations by using a case study of clearing and repartitioning of intellectual property rights (ipr).
extending an ontology-based search with a formalism for spatial reasoning. with the objective of extending an existing ontology-based search with a formalism for spatial reasoning two approaches to a representation of the region connection calculus (rcc) in owl dl are explored. the exploration results in a representation which is minimal yet still allows inferring the relations between all connecting regions in any of the different rcc species using a sound and complete calculus. the theoretical results are demonstrated in a sample application. the scale of the representation in the sample application is discussed. while the successful approach can be applied to small applications, we conclude that further research is required before applying it to large applications.
an algorithm for the tracing problem using interval analysis. we give an algorithm for the tracing problem in dynamic geometry that uses interval arithmetic. in this work, we focus on an algebraic model. here the objects are real or complex numbers with the operations +, --, .,/, and &radic;. originally, geometric objects like points, lines, or circles have been considered. our algorithm proceeds stepwise and detects (potential) critical points in advance. for each step, the algorithm computes a steplength that is small enough to handle the ambiguity of the root function. this is achieved by using interval arithmetic. after the detection of a critical point, the singularity is avoided by a detour through the complex plane c.
aggregation languages for moving object and places of interest. we address aggregate queries over gis data and moving object data, where non-spatial information is stored in a data warehouse. we propose a formal data model and query language to express complex aggregate queries. next, we study the compression of trajectory data, produced by moving objects, using the notions of stops and moves. we show that stops and moves are expressible in our query language and we consider a fragment of this language, consisting of regular expressions to talk about temporally ordered sequences of stops and moves. this fragment can be used not only for querying, but also for expressing data mining and pattern matching tasks over trajectory data.
system level power profile analysis and optimization for smart cards and mobile devices. the steadily increasing performance of rf-powered devices implies also a rise in power consumption. to counteract this trend, it is mandatory to accomplish power optimizations at every stage in the hw/sw co-design process. since the momentarily available energy depends on the power profile of anterior tasks, the behavior of the rf-interface has to be considered in the optimization process to achieve a maximum of efficiency by maintaining the system stability. this paper introduces an accurate discrete-time model of the energy source of rf-powered devices. based on this model, a power profile analysis tool has been developed, which identifies automatically critical regions for the energy source in the current profile of the system. the use of this framework is illustrated in a software optimization process, which intends to eliminate the detected critical areas.
supporting ethnographic studies of ubiquitous computing in the medical grand round experience. ethnography is a research method to understand how people carry out their tasks in real-world experiences. medical grand rounds are quotidian, formal meeting experiences where physicians discuss clinical problems of patients. this paper presents an ethnographic study of medical grand rounds that has driven the design and development of a ubiquitous computing prototype to address the lack of a proper documentation of medical grand rounds. we have learnt that ethnography is a powerful means of understanding tacit knowledge about physicians' needs, behaviors and rituals
a umls interoperable solution to support collaborative diagnosis decision making over the internet. hospitals can supply clinical decision support systems with electronic healthcare record provided by different users and stored in different computer systems. this way, during a diagnosis decision a user can be supported by a remote knowledge database constructed by other users, like, for instance, a reference specialist discussion board. usually, medical applications scenarios like this use different terminology systems leading to terminological interoperability problems. still, clinical applications frequently make use of different clinical ontology systems that do not provide semantic types necessary to create a structure to carry shared knowledge database. the lack of this semantic types brings ontology interoperability problems which difficult the support of collaborative clinical decision-making. this paper presents a umls interoperable solution to promote clinical applications development intended to contribute with collaborative diagnosis decision, in a distributed computer environment based on service-oriented architecture. this paper still presents a case study to demonstrate ddsont usability through the development of a system prototype integrated to a collaborative and multimedia communication distance-learning environment.
strategies for qos improvement on the time-interval scheduling. in this paper we analyze the interference among the non-preemptive segments in the time-interval problem. also, we explore the subject of fixed priority assignment for those segments through a suboptimal algorithm. consequently, the offline feasibility test becomes less pessimistic resulting in higher qos values comparing to previous studies.
context-aware information retrieval on a ubiquitous medical learning environment. this paper proposes an information retrieval process that employs a relevance feedback approach based on implicit evidences provided by contextual information and explicit evidences provided by the user behavior during interaction. this process takes advantage of semantic information processing enabled by the use of ontologies to build semantic indexes, to represent context and domain knowledge and to aid interactions mediated by mobile devices.
semantic mapping and k-means applied to hybrid som-based document organization system construction. in this paper, we present and evaluate a hybrid document organization system based on self-organizing maps. the proposed system uses semantic mapping to dimensionality reduction and k-means to volume reduction of document vectors of a medium text collection. the vectors obtained after dimensionality and volume reduction steps are used to train the document maps with the som algorithm, thus the training time is reduced without compromising the quality of the generated map. we compare experimentally the hybrid system with the correspondent som system in organization of documents of reuters-21758 v1.0 collection. the performances of the systems were measured in terms of classification error in text categorization and training time. the experimental results show that the proposed system generates pretty good document maps with smallest training time.
a hierarchical model-based approach to co-clustering high-dimensional data. we propose a hierarchical, model-based co-clustering framework for handling high-dimensional datasets. the technique views the dataset as a joint probability distribution over row and column variables. our approach starts by clustering tuples in a dataset, where each cluster is characterized by a different probability distribution. subsequently, the conditional distribution of attributes over tuples is exploited to discover natural co-clusters in the data. an intensive empirical evaluation highlights the effectiveness of our approach.
automatic software fault localization using generic program invariants. despite extensive testing in the development phase, residual defects can be a great threat to dependability in the operational phase. this paper studies the utility of low-cost, generic invariants ("screeners") in their capacity of error detectors within a spectrum-based fault localization (sfl) approach aimed to diagnose program defects in the operational phase. the screeners considered are simple bit-mask and range invariants that screen every load/store and function argument/return program point. their generic nature allows them to be automatically instrumented without any programmer-effort, while training is straightforward given the test cases available in the development phase. experiments based on the siemens program set demonstrate diagnostic performance that is similar to the traditional, development-time application of sfl based on the program pass/fail information known before-hand. this diagnostic performance is currently attained at an average 14% screener execution time overhead, but this overhead can be reduced at limited performance penalty.
modeling adversary scheduling with qcsp. we consider cumulative scheduling problems in the presence of an adversary. in such setting the scheduler tries to manage the available resources in so as to meet the scheduling deadline, while the adversary is allowed to change some parameters---like the resource consumption of some tasks---up to a certain limit. we ask whether a robust schedule exists, i.e., one that is guaranteed to work whatever (malicious) actions the opponent may take. we propose to model this family of decision problems using a variant of quantified constraint satisfaction problems called qcsp+, and to solve them by using the solver qecode.
face recognition using dct coefficients selection. this paper presents a face recognition method based on discrete cosine transform (dct) coefficient's selection. without a normalization phase, the proposed method uses, in its feature selection stage, a technique based only on the dct coefficients amplitudes. three coefficient selection criterions were analyzed: the first one is the average of the coefficients' amplitudes; the second one is based on counting the occurrence of each coefficient, which are stored in a set of lists containing the most significant coefficients; finally, the third criterion is based on the average position of the coefficients in a list of coefficients ordered by amplitude. experimental tests on the orl face database [1] achieved 99.00% of recognition accuracy using only 50 dct coefficients, with low computational cost. additionally, the method achieved 100.00% of recognition accuracy when the correct face is within a range of eight returned faces.
coordination schemes in distributed simulation of relativistic particle transport. in distributed simulation, overheads of coordinating operations across computing nodes could counteract the benefit of having extra machines. meanwhile, some scientific applications such as relativistic particle transport exhibit strong data dependency among events. this paper proposed several coordination schemes to reduce communication frequency and volume, overlap computation and communication operations, and arrange event simulation speculatively. performance gains are expected.
on the meaning of modes in uniprocessor real-time systems. one way to manage the complexity of the design and the implementation of large and adaptive real-time systems is to partition the design into modes of operation. this approach allows designers to break down the complexity of these systems into a number of layers of control (modes), which are then multiplexed in time (by means of mode changes) during system operation. however, due to a lack of a uniform view of modes within the literature, the task of successfully designing complex real-time systems with modes of operation becomes more difficult, if not compromised [1]. in this paper we consider the following recurring issues of modes in real-time systems, both from the application and design concerns: 1) what is a mode of operation, i.e. which features are exclusive to a particular mode of operation that allow its identification and distinction from other modes? 2) what can be understood by the concept of mode changes in realtime systems? the examination of these issues is lacking in the literature and will facilitate the analysis, design and construction of the next generation of complex real-time systems.
consistent privacy preferences (cpp): model, semantics, and properties. the platform for privacy preferences (p3p) is a w3c specification that can be used to build useful protocols and services for protecting user privacy on the semantic web. an outstanding issue is the need for a simple and efficient representation and management of consistent sets of rules for user privacy preferences. thus we describe a model for privacy preference representation and management that has a number of desirable properties which are lacking in privacy preference models proposed thus far. we detail semantics and properties of matching preference rules with requests. we specify the properties of a consistent set of privacy preferences, and propose maintenance operations. finally, we describe an implementation of our proposal that uses owl (web ontology language) and the jena reasoning engine to illustrate the practicality of managing consistent user preferences in privacy rule-sets. an important advantage of our approach is that the user is encouraged to clarify privacy preferences as he/she modifies them as part of a back-end management task, as opposed to mainly at website interaction times.
exploiting program cyclic behavior to reduce memory latency in embedded processors. in this work we modify the conventional row buffer allocation mechanism used in ddr2 sdram banks to improve average memory latency and overall processor performance. our method assigns row buffers to different banks dynamically and by taking into account program cyclic behavior and bank row buffer demand. as we show in this work, memory requests go through several phases. in each phase, programs tend to access a single bank most of the time. we exploit this repetitive behavior and improve the concurrency level for memory read and write operations. we do so by assigning idle row buffers to more demanding banks during specific program phases. this improves average memory latency and processor performance by 12.7% and 7.6% respectively.
improving network management with mobile agents in peer-to-peer networks. regarding the size and the complexity growth of today's networks, several network management models have been studied and proposed. furthermore, new requirements emerge with the interaction among entities that compose the management system, such as interoperability, collaboration among managers geographically separated, resources sharing, load balancing and inter-domain manager. it occurs that many of these models don't worry about the network logical configuration. in this paper, we present an improvement in the network management by combining p2p-based management system and mobile agents. the idea is to provide a mobile agent system extension for its integration with an architecture of network management based on peer-to-peer (p2p) networks. the mobile agent system makes it possible to have a more robust and self-organized network, together with the distributed system benefits.
path-based verification for composition of semantic web services. this paper proposes a novel approach to the verification for composition of web services annotated by ontology-based input, output, precondition and effect. in this approach, implicit inconsistency and explicit inconsistency may be detected on a path. firstly, a normal form for the description of precondition and effect is defined, then an algorithm for automatically determining the accumulated effects of ordered services is given out. thirdly, an algorithm for verifying a single path extracted from the composition is illustrated. on the basis of the approach, some experiments for verifying a single path are demonstrated. eventually an e-business example is presented to demonstrate the approach.
borderline detection by bayes vector quantizers. borderline detection is the problem of finding samples falling near the decision boundary. it has many applications, related to the fact that for these samples small variations of feature values, due for instance to the presence of noise, can completely change their classification. in this paper, we propose an approach to borderline detection based on the geometric characteristics of labeled vector quantizers. the approach is based on the estimation of the true decision boundary by means of the bayes vector quantizer (bvq) algorithm. bvq is a stochastic gradient algorithm for the minimization of the misclassification risk, hence it guarantees the accurate approximation of the optimal decision boundary. the features of the approach are discussed in comparison with support vector machines (svm), that is the best boundary hunting technique known in the literature.
reachability analysis of generalized polygonal hybrid systems. a polygonal hybrid system (spdis) is a planar hybrid system, whose dynamics is defined by constant differential inclusions, for which the reachability problem is decidable. the decidability result is based, among other things, on the fact that a trajectory cannot enter and leave a given region through the same edge. spdis without such an assumption are called generalized spdis (gspdis). in this paper we show that in general it is not possible to reduce gspdi reachability to spdi reachability. furthermore, we provide a terminating algorithm implementing a semi-test for gspdi reachability, based on that for spdis.
automated classification of change messages in open source projects. source control systems permit developers to attach a free form message to every committed change. the content of these change messages can support software maintenance activities. we present an automated approach to classify a change message as either a bug fix, a feature introduction, or a general maintenance change. researchers can study the evolution of project using our classification. for example, researchers can monitor the rate of bug fixes in a project without having access to bug reporting databases like bugzilla. a case study using change messages from several open source projects, shows that our approach produces results similar to a manual classifications performed by professional developers. these findings are similar to ones reported by mockus and votta for commercial projects.
using process algebra to control the execution of business processes. integrating information systems with tools that manage workflows and business processes is not always a simple task. this difficulty becomes more accentuated when the execution control assumes countless business processes. this work presents an alternative to control the execution of business processes. this alternative consists in a library of functions, called navigationplantool, which can be easily integrated into the information systems and uses navigation plan definition language (npdl) as the language to define business processes. npdl is a language for business processes specification that uses process algebra as formal foundation. the navigationplantool implements npdl language as a sql extension and offers two other important services: processes instantiation and process instances execution monitor. the navigationplantool combines the process algebra features with a relational database model to provide a scalable and reliable control in the execution of business processes.
an anomaly intrusion detection method using the csi-knn algorithm. machine learning-based anomaly detection approaches have attracted increasing attention in the network intrusion detection community because of their intrinsic capabilities in discovering novel attacks. however, most of today's anomaly-based idss generate high false positive rates and miss many attacks because of a deficiency in their ability to discriminate attacks from legitimate behaviors. in this paper, we propose an anomaly intrusion detection method using the combined strangeness and isolation measure k-nearest neighbors (csi-knn) algorithm. the intrusion detection algorithm analyzes different characteristics of network data by employing two measures: strangeness and isolation. based on these measures, a correlation unit raises intrusion alerts with associated confidence estimates. multiple csi-knn classifiers work in parallel to deal with different types of network services so that the csi-knn-based nids can work more efficiently than processing all network services together.
analyzing the impact of churn and malicious behavior on the quality of peer-to-peer web search. in an attempt to increase the spectrum of searchable information while attenuating scalability issues, peer-to-peer (p2p) networks have been viewed as an alternative way to design new web search engines. however, the effectiveness of p2p web searching may be severely limited by characteristics commonly observed in real p2p systems such as peer churn and malicious behavioral patterns. this paper analyzes the impact of each such issue on the effectiveness of p2p web searching. in order to estimate boundaries, we focus our analysis on p2p network models with very high and low levels of peer collaboration. our findings reveal that such patterns could strongly affect the effectiveness of p2p web searching. in networks with a high level of peer collaboration, a significant fraction of queries suffer an impact on the quality of search of at least 24% and 26% even in slightly insecure and unstable scenarios. we also confirm that the impact of each such issue in real-world, less collaborative networks can be even more intense (73% and 75%). thus, together with the high autonomy of peers and the absence of file-sharing benefits in replicating documents into the network, we argue that effectiveness of p2p web search engines would strongly depend on new, application-specific reputation and incentive mechanisms.
embedding sparql into xquery/xslt. the tree-based languages xquery and xslt for xml are widely supported. many tools do not yet support the new rdf graph query language sparql. we propose to embed sparql subqueries into xquery/xslt, such that xquery and xslt benefit from the graph query language constructs of sparql, and sparql benefits from features of xquery/xslt, which sparql does not support. the embedding enables xquery/xslt tools to handle at the same time xml queries and sparql subqueries, and xml and rdf data.