waashk/dblp huggingface dataset:
a uml model consistency verification approach based on meta-modeling formalization. uml language provides a promising way to overcome software system complexity. in particular, uml is a unified language that handles different aspects of software modeling. however, its features are not independent which is the source of numerous inconsistencies. present consistency checking techniques are limited either to certain uml features or to certain kinds of inconsistencies. our study aims at developing a unified checker which is able to handle all inconsistencies on all uml features. this paper develops the translation from uml models to clp (constraint logic programming) clauses taking advantage of meta-modeling techniques. clp is also used to express consistency rules. then clp solver can automatically detect inconsistencies.
modeling and execution of e-learning resources. this poster tries to motivate a specific part of a holistic modeling approach for e-learning with the help of business engineering on a technical level. business engineering defines generic and holistic methodologies and modeling methods for constructing an organizational memory for a complex environment. not only aspects of how to run a business from an organizational point of view have to be modeled but also techniques of how to implement business processes technically. emerging technologies coming from the semantic web and web-services communities leverage great potential to support the execution of business engineering environments especially when thinking of business-to-business contracts integrating business and supply-chain flows among several trading partners. with the help of advisor&copy; - an e-learning modeling platform with a visual modeling interface - a specific part of the engineering lifecycle within an e-learning scenario can be realized: advisor&copy; is able to transform the modeled learning pool into rdf compliant resources. prototypical test-beds to process the modeled learning resources with the help of a web-services execution environment enable queries of any soap enabled requestor - regardless of the platform.
dl-cotf: an xml based digital library for u. s. navy's operational test and evaluation force. this paper describes the development of the xml based digital library (dl-cotf) for the united states navy's operational test and evaluation command (comoptevfor). comoptevor tests new systems (weapons, ships, aircraft, etc.) that industry develops and dependent upon test results, the navy purchases. each development spans several years and has a large number of documents in various formats. these related documents that all belong to a specific program are required to be available electronically to aid workflow, provide controlled dissemination, facilitate document discovery, and ensure achieves are maintained as personnel leave the organization. as a solution we have developed xmlcot, an xml based language, to describe the family of files related to a specific programs as digital objects with a complex structure. the search tools to permit secondary users to find specific the files, retrieve them and simultaneously view the storage structure that provides addition meaning also use the same structure. to support interoperability with other digital libraries, the dl-cotf will present its metadata in compliance with the open archive initiative (oai). a key feature of this digital library environment is its ability to publish, search (discovery), navigate the complex digital objects and dynamically tailor the objects structure within the digital library.
recursive, object-oriented structures for molecular modeling. in this paper, we present a molecular modeling approach based on recursive object-oriented class instances. our approach allows ease of use by the scientist and includes a heuristic for evaluating molecular interaction and rendering at multiple levels of detail. our implementation in c++ employs abstractions to encapsulate the implementation and details of the computations. visualization is accomplished with opengl or the visualization toolkit (vtk), an application-independent scientific visualization library.
making tuple spaces physical with rfid tags. in this paper, we describe the design and implementation of a tuple-based distributed memory realized with the use of rfid technology. the key idea - rooted in a more general scenario of pervasive and mobile computing - is that our everyday environments will be soon pervaded by rfid-tagged objects. by accessing in a wireless way the re-writable memory of such rfid tags according to a tuple-based access model, it is possible to enforce mobile and pervasive coordination and improve our interactions with the physical world. an application example is presented to outline the potential of the approach.
an evaluation of conceptual business process modelling languages. conceptual business process modelling languages (bpmls) express certain aspects of processes (e.g. activities, roles, interactions, data, etc.) and address different application areas. to evaluate bpmls, a general framework is required. although a lot of bpmls are available in research and industry, an established evaluation framework as well as a comprehensive evaluation of bpmls is missing. to bridge this gap, we propose a generic meta-model that captures a wide range of process concepts and evaluate seven bpmls based on this meta-model.
self-maintained distributed tuples for field-based coordination in dynamic networks. field-based coordination is a very promising approach for a wide range of application scenarios in modern dynamic networks. to implement such an approach, one can rely on distributed tuples injected in a network and propagated to form a distributed data structure to be sensed by application agents. however, to gain the full benefits from such a coordination approach, it is important to enable the distributed tuples to preserve their structures despite the dynamics of the network. in this paper, we show how a variety of self-maintained distributed tuple structures for field-based coordination can be easily programmed in the tota middleware. several examples clarify the approach, and performance data is presented to verify its effectiveness.
towards a corporate performance measurement system. corporate performance measurement is focused too strongly on the traditional functional structure of an organisation and business processes are not measured systematically. basically, business processes are designed to transform organisational strategies into operation and create a result of value to customers. as a business process is performed by a group of organisational units, processes and the organisational structure are interdependent. consequently, their performance must not be measured in isolation. this paper illustrates how a data warehouse can be used to facilitate a corporate performance measurement system by the integration of business process performance information into a traditional data warehouse that generally represents only the functional organisation. the corporate performance measurement system provides a single source of information on the performance of the company. as a proof of concept in a business environment, a feasibility study has been implemented in the insurance sector. this performance measurement approach fully supports a modern organisational structure: the customer-oriented process perspective coexisting with the traditional functional structure.
a strategy for selecting multiple components. this paper presents a systematic method for simultaneously defining a software architecture and selecting off-the-shelf components for reuse. the method builds upon existing techniques for component selection and architecture evaluation. we identify architectural decisions that have a large effect on the components used early in the process so that different ways of building the system can be investigated. the result of applying the method is a partial definition of a system's architecture along with a set of components that could be incorporated.
two-level assurance of qos requirements for distributed real-time and embedded systems. assuring quality of service (qos) requirements is critical when assembling a distributed real-time and embedded (dre) system from a repository of existing software and hardware components. this paper presents a two-level approach for assuring satisfaction of qos requirements in the context of a reduced design space for dre systems. techniques from artificial intelligence and statistics are used to fulfill these collective objectives at system assembly time. the result not only lessens the overhead of validation of qos requirements at run-time, but also reduces the development and integration cost of dre systems.
similarity-based clustering of web transactions. we introduce a measure to compute similarity between two sequences containing accesses to web pages, to be exploited in a clustering approach for grouping sessions of accesses to a web site. the notion of sequence similarity is parametric to the sequence topology, and the similarity among web pages within the sequences. in our formalization, two web pages are similar if they can be considered synonymies not only from a content point of view, but also from a usage point of view, i.e., if users exhibit the same behavior on both pages. the refined notion of page similarity, as well as the related notion of sequence siilarity, are envisaged to be effective in the application of a centroid-based clustering technique to the personalization of web experience.
large-scale flow field visualization for aneurysm treatment. an important medical problem of the non-invasive treatment of brain aneurysm has attracted growing interest. aneurysm surgery remains dangerous because surgeons have limited knowledge of blood flow patterns and complex 3d geometry of aneurysms. this information is essential to determine if the aneurysm is suitable for a certain surgical technique. therefore, a virtual aneurysm (va) research was initiated to make it possible for medical specialists to obtain such detailed information.here we discuss two schemes relating to the realization and efficiency of va system. the first is a scheme of data storage and management technique. it is aimed not only to achieve higher access efficiency and storage utilization but also to reduce the stress of memory resources. the second is the scheme of the branching simulation approach attempting to lessen the computational burden at visualization. these schemes illustrated by va system, requiring minimal run-time computing or memory, are suggested so as to best exploit the performance for the simulation and visualization. while there is no intrinsic difference when applied to other scientific and engineering areas, these schemes are more beneficial to typical biomedical visualizations when the data already push the limits of the simulation and visualization environment.
detection and segmentation of tables and math-zones from document images. we propose an algorithm to separate out tables and math-zones from document images. the algorithm relies on the spatial characteristics of tables and math-zones in a document. it has been observed that tables have distinct columns which imply that gaps between the fields are substantially larger than the gaps between the words in text lines and in math-zones the characters and symbols are less dense in comparison to normal text lines. these deceptively simple observations have led us to design a simple but powerful table and math-zone detection system with low computation cost.
knowledge-based query expansion to support scenario-specific retrieval of medical free text. in retrieving medical free text, users are often interested in answers pertinent to certain scenarios that correspond to common tasks performed in medical practice, e.g., treatment or diagnosis of a disease. a major challenge in handling such queries is that scenario terms in the query (e.g., treatment) are often too general to match specialized terms in relevant documents (e.g., chemotherapy). in this paper, we propose a knowledge-based query expansion method that exploits the umls knowledge source to append the original query with additional terms that are specifically relevant to the query's scenario(s). we compared the proposed method with traditional statistical expansion that expands terms which are statistically correlated but not necessarily scenario specific. our study on two standard testbeds shows that the knowledge-based method, by providing scenario-specific expansion, yields notable improvements over the statistical method in terms of average precision-recall. on the ohsumed testbed, for example, the improvement is more than 5% averaging over all scenario-specific queries studied and about 10% for queries that mention certain scenarios, such as treatment of a disease and differential diagnosis of a symptom/disease.
editorial message: special track on applications of spatial simulation of discrete entities. many important phenomena result from localized interactions including: population dynamics and epidemics, cell and tissue modeling, mobile computing and wireless networks. modeling these systems can reduce experimentation costs or enable non-destructive in silica experimentation.simulation models can be classified depending on how they represent reality, in particular time, space and simulated entities (objects). the simplest to described are models based on ordinary differential equations, which are aspatial and they may have either single time step for all objects, making time synchronous, or different time steps for different entities, making time asynchronous. simulation entities are also described by a set of read valued parameters, so they are treated as continuous. it is well known that spatially explicit models can exhibit qualitatively different results than their aspatial counterparts [5]. this makes the models based on partial differential equations very common and popular. in this track however, we focus on a different category of models. to make this difference clear, we start with the following categorization of all models based on how they treat the three orthogonal aspects of simulations: simulation objects (entities) and the world that they inhabit (time and space). the categorization is shown in table 1.the field of numerical computing is well studied, with numerous forums for extensive work and publication of spatial models using continuous time and treating entities as continuous (e.g. diffusion models [3, 1] or finite element method approaches [6, 11]. traditionally, techniques for spatial modeling of discrete systems have tended to be published in application specific forums. in forming this track, we hoped to provide a unique forum for researchers in this area to come together and discuss various applications and approaches to spatial modeling.
moral responsibility and it for human enhancement. what can be said against a moral obligation to use it for enhancement purposes? some have argued - and it is very well conceivable that this is an increasingly common conception - that we may have a moral obligation to use it for enhancing human bodies and human decision-making, for instance by using computers for moral decision-making in cases in which we are dealing with a high level of (moral) complexity such as euthanasia decisions. in this paper i will formulate some objections against the suggestion made by some that it tools can and ought to be used for human enhancement, in the sense of improving moral decision-making.if we were to use it for enhancement purposes, what would be the problems? in this paper i will discuss some problems, such as moral deskilling, epistemic dependence, the allocation of responsibility for it support, and epistemic paternalism. the conclusion is that it is questionable whether we can speak of a moral obligation to use it tools for human enhancement. it is certainly extremely helpful in improving decision-making and improving the quality of life as conceived by some. however, speaking of a moral obligation seems too strong of a claim or at least it should be reconsidered in light of the issues here discussed.
a comparison of two view materialization approaches for disease surveillance system. the effectiveness of a disease surveillance system such as rods depends heavily on the performance of the underlying data management components. given that such system's core functionality is to support decision making and data mining, the response time of complex queries involving aggregation requires special attention. traditionally, materialized views have been advocated to address this issue. the question that this paper examines is which approach implementing materialized views is more suitable in a disease surveillance environment. our comparison focuses on the two most common approaches, namely, the cache tables approach and the data warehousing approach. our evaluation shows that the choice of an approach is not limited by the cost-performance but by the cost-flexibility of usage as well.
the effect of named entities on effectiveness in cross-language information retrieval evaluation. the large number of experiments carried out within evaluation initiatives for information retrieval has led to an invaluable source for further research and meta-analysis. in this study, an analysis of the results of the cross language evaluation forum (clef) campaigns for the years 2000 to 2003 is presented. this study considers the performance of the systems for each individual topic. it is dedicated to the influence of named entities on retrieval performance. named entities in topics lead to significant improvement of the retrieval quality in general and for most systems and tasks. the performance of systems varies for topics without, with one or two and with three or more named entities. this knowledge gained by data mining on the evaluation results can be exploited for the improvement of retrieval systems as well as for the design of topics for future clef campaigns.
efficient target search with relevance feedback for large cbir systems. recent content-based image retrieval (cbir) techniques were designed around query refinement based on relevance feedback. they suffer from slow convergence, high disk i/o, and do not even guarantee to find intended targets. in this paper, we identify the cause of these problems and propose several efficient target search methods to address these drawbacks. our complexity analysis shows that our approach is able to reach any given target image with fewer iterations in the worst and average cases. we evaluated our techniques on large datasets in simulated and realistic environments. the results show that our approach significantly reduces the number of iterations and improves overall retrieval performance. the experiments also confirm that our approach can always retrieve intended targets even with poor selection of initial query points and can be used to improve the effectiveness of existing cbir systems with relevance feedback.
a model for mining outliers from complex data sets. to solve the outlier mining problems where outliers are highly intermixed with normal data, a general variance-based outlier mining model (vomm) is presented, in which the information of data is decomposed into normal and abnormal components according to their variances. with minimal loss of normal information in the vomm, outliers are viewed as the top k samples holding maximal abnormal information in a dataset. and then, the principal curve that is a smooth nonparametric curve passing through the "middle" of the dataset and that provides a good nonlinear summary of the data is introduced as an algorithm of the vomm. experiments carried out on abnormal returns detection in stock market show that the vomm is feasible and performs better than that of gaussian model and garch (generalized auto-regressive conditional heteroscedasticity) model.
netaffx: affymetrix probeset annotations. one challenge in microarray experiments is assessing when the results are biologically significant. this assessment can be aided by detailed annotation of the probeset target sequences, including gene function or category, protein product, and pathway information. netaffx compiles public and in-house annotations for all affymetrix chip sets. public annotations are collected from unigene, locuslink and swiss-prot. in-house annotations are produced by generalized rapid automated protein analysis (grapa), a high-accuracy hmm method for protein annotation. grapa has been used to generate novel annotations under three classification schemes: structural classification of proteins (scop), enzyme commission (ec), and g protein coupled receptors (gpcr). in addition, annotations are generated by searching pfam and blocks databases. these annotation schemes have been applied to diverse genomes including human, mouse, rat, drosophila, and yeast, then mapped onto affymetrix microarray probesets. the combination of protein-level annotations with public source annotations creates a powerful description of genes at both the genomic and protein levels. users can collect information on a target sequence, or cluster microarray probe sets according to a given domain or functional category. netaffx is available on the web at http://www.netaffx.com/.
cost-efficient processing of min/max queries over distributed sensors with uncertainty. the rapid development in micro-sensors and wireless networks has made large-scale sensor networks possible. however, the wide deployment of such systems is still hindered by their limited energy which quickly runs out in case of massive communication. in this paper, we study the cost-efficient processing of aggregate queries that are generally communication-intensive. in particular, we focus on min/max queries that require both identity and value in the answer. we study how to provide an error bound to such answers, and how to design an "optimal" sensor-contact policy that minimizes communication cost in reducing the error to a user-tolerable level.
automatic code generation for a convection scheme. traditional design and implementation of large atmospheric models is a difficult, tedious and error prone task. with the ctadel project we investigate a new method of code generation, where the designer describes the model in an abstract high-level specification language which is translated into highly optimized fortran code. this is applied to a convection scheme as used in a numerical weather prediction model (nwp). we address problems like how to generate efficient code for conditional expressions by using polymorphic templates. finally, we compare the generated code for the convection scheme with the hand-written reference code.
approximating module semantics with constraints. in this paper we present a generic constraint domain for symbolic modular analysis. the idea is that the semantics of a module can be approximated by a set of relations symbolically linking the input, output and local variables. we show how this result is correct w.r.t. a trace semantics, and how it can be used to perform an (incremental) modular analysis. we claim that our construction generalizes existing modular analyses by showing how well-known modular analyses can be instantiated in our framework.