waashk/dblp huggingface dataset:
a predictive framework for retrieving the best answer. in a question answering (qa) system, each user interaction with the system is different and since there are a variety of arguably correct answers to complex questions, identifying factors for improving the quality of the retrieved answer is difficult. this research aims to develop a framework that identifies predictive variables for the best quality answer in a qa system. it was found that accuracy, completeness and relevance were predictors of best answer. we believe that these findings can serve to guide future developments in the answer extraction modules in the qa systems.
offline count-limited certificates. in this paper, we present the idea of offline count-limited certificates (or clics for short), and show how these can be implemented using minimal trusted hardware functionality already widely available today. offline count-limited certificates are digital certificates that: (1) specify usage conditions that depend on irreversible counters, and (2) are used in a protocol that guarantees that any attempt to use them in violation of these usage conditions will be detected even if the user of the certificate and the verifying party have no contact at all with the outside world at the time of the transaction. such certificates enable many interesting applications not possible with traditional (unlimited use) certificates, including count-limited delegation and access, offline commerce and trading using cashlike migratable certificates, and others. we show how all these applications can be made possible by using only a simple trusted timestamping device (ttd), which can in turn be implemented using existing trusted hardware devices such as smartcards, and the trusted platform module (tpm) chips embedded in pcs available today. significantly, our solutions do not require trust in any other components in the host machines aside from the ttd itself; they remain tamper-evident as long as the ttd is not compromised, even if the entire host system, including the bios, cpu, os and memory, is compromised. this not only provides better security by minimizing the required trusted computing base, but also makes implementation possible on present-day machines without requiring a particular kind of os. we demonstrate all these ideas by implementing a prototype application that runs under both linux and windows, and presenting experimental performance results.
&eacute;nfasis: a model for local variable crosscutting. crosscutting on local variable is suitable for all problem domains where local variables provide a natural implementation of sequential algorithms. however, local variable crosscutting has been neglected, resorting to refactoring on fields as a better implementation option, conveying severe short-comings and inefficiencies. this paper introduces &eacute;nfasis, a join point model for local variable crosscutting along with its experimental framework written in java. &eacute;nfasis formal model is based on a notion of join point that supports an operational interpretation suitable for pointcut composition and a straightforward implementation. the implementation demonstrates the importance of fine grained resolution in join point selection with advising mechanisms, automatic passing context, thisjoinpoint variable and pattern matching of local variables.
a small extension to java for class refinement. this paper presents an extended java language in which users can refine a class definition to a certain degree. they can statically or dynamically redefine methods and append a new method, field, and interfaces to the class like dynamic languages. a unique feature of this language, named gluonj, is that users can use a standard java ide (integrated development environment) to exploit coding support by the ide. this is significant for the industrial acceptability of a new language. a gluonj program is written in standard java with additional java annotations. gluonj was carefully designed so that the ide can recognize a gluonj program and reflect it on the coding support such as the code assist of eclipse. moreover, a gluonj program never throws a runtime exception reporting that an undefined method is called. guaranteeing this property is not straightforward because gluonj allows users to refine a class definition at runtime.
on the conformity of models: a transducer-based approach for model transformation. model transformation is one of the main operations in model engineering. it consists of transforming a source model to a target one. any transformation needs to satisfy some basic requirements, namely the conformity of a model to its meta-model. such model is thus said to be valid. in the litterature, several approaches and languages have been proposed. while they exhibit important features, they unfortunately suffer from a main drawback. indeed, it is difficult to check whether the target model is valid or not. the paper advances the state of the art by proposing a new approach for model transformation that palliates the above limitation. the basic idea behind this approach is to define model transformation as a binary relation, captured by a transducer, between two domains. the use of transducer makes it possible to both translate models and to validate them. note that the proposed approach establishes a bridge from model space to grammar space.
a space-identifying ubiquitous infrastructure and its application for tour-guiding service. in this paper, a novel tour-guiding system is introduced, based on our space-identifying ubiquitous infrastructure, where positioning devices are deployed ubiquitously to identify the place of users. in this infrastructure, we can flexibly construct information service related to the places of interest in the city by modeling the space of the real world as a set of relations among the discrete places, and attaching space-identifying devices to them. our developed tour-guiding system introduces many art works in a large commercial complex in japan. based on the benefit of the infrastructure, this system can provide detailed navigation service as well as art introduction service in both indoor and outdoor environments, and can guide the users to reach their interested art works. currently, this system is already used in practice for a commercial service. in this paper, the design of this system is described and its navigation capability is verified through a user test in the real environment to discuss the effectiveness of our approach.
when a mismatch can be good: large vocabulary speech recognition trained with idealized tandem features. this paper explores tandem feature extraction used in a large-vocabulary speech recognition system. in this framework a multi-layer perceptron estimates phone probabilities which are treated as acoustic observations in a traditional hmm-gmm system. to determine a lower error bound, we simulated an idealized classifier based on alignment of reference transcriptions. this cheating experiment demonstrated a best-case scenario for tandem feature extraction, highlighting the potential for dramatic system improvement. more importantly, we discovered a way to exploit the result without cheating: using the simulated classifier during training and a mlp classifier at test, the performance improved despite the mismatched tandem features.
a clustering-based approach for discovering interesting places in trajectories. because of the large amount of trajectory data produced by mobile devices, there is an increasing need for mechanisms to extract knowledge from this data. most existing works have focused on the geometric properties of trajectories, but recently emerged the concept of semantic trajectories, in which the background geographic information is integrated to trajectory sample points. in this new concept, trajectories are observed as a set of stops and moves, where stops are the most important parts of the trajectory. stops and moves have been computed by testing the intersections of trajectories with a set of geographic objects given by the user. in this paper we present an alternative solution with the capability of finding interesting places that are not expected by the user. the proposed solution is a spatio-temporal clustering method, based on speed, to work with single trajectories. we compare the two different approaches with experiments on real data and show that the computation of stops using the concept of speed can be interesting for several applications.
web service access management for integration with agent systems. the agent paradigm includes the notion that agents interact with services. this paper identifies the need for controlled access to such services, from the perspective of agent systems (and not as is generally the case by web service providers). mediating between web service requests from (virtual) organizations of agents, the web service gateway proposed regulates (i.e., monitors and controls) web service access according to the slas and organizational policies that are in effect. in addition to a model for web service access regulation, an implementation of a middleware component for web services access regulation based on soap and described in wsdl is presented.
a ga-based feature selection and parameters optimization for support vector regression applied to software effort estimation. the precision of the estimation of the effort of software projects is very important for the competitiveness of software companies. machine learning methods have recently been applied for this task, included methods based on support vector regression (svr). this paper proposes and investigates the use of a genetic algorithm approach for simultaneously (1) select an optimal feature subset and (2) optimize svr parameters, aiming to improve the precision of the software effort estimates. we report on experiments carried out using two datasets of software projects. in both datasets, the simulations have shown that the proposed ga-based approach was able to improve substantially the performance of svr and outperform some recent results reported in the literature.
special track on requirements engineering: editorial message. requirements eengineering is a branch of computer science that encompasses tasks that go into determining the requirements of a new or altered system, taking into account the possibly conflicting requirements of the various stakeholders, such as end users. the existing methods for requirements specification are far from being completely satisfactory, and requirements analysis is critical to the success of a project. requirements must be measurable, testable, related to identified business needs or opportunities, and defined to a level of detail sufficient for system design. independently of the nature of the software, the elicitation, analysis, negotiation, specification, validation and management of requirements are fundamental for the development of quality in complex software.
special track on embedded systems: applications, solutions, and techniques: editorial message. high performance embedded computing has recently become more and more present in devices used in everyday life. a wide variety of applications, from consumer electronics to biomedical systems, require building up powerful yet cheap embedded devices. embedded software has tumed out to be more and more complex, posing new challenging issues: the adoption of further flexible programming paradigms/architectures is becoming almost mandatory. nonetheless, embedded systems development nowadays must rely on a tight coupling of hardware and software components. in this scenario, efficient solutions can be proposed at different levels of abstraction, making use of an assortment of tools and methodologies: researchers and practitioners have a chance to propose new ideas and to compare experimentations. the focus of this conference track is on the application of both novel and well-known techniques to the embedded systems development. particular attention is paid to solutions that require expertise in different fields (e.g. computer architecture, os, compilers, security, software engineering, simulation). the track benefits also from direct experiences in the employment of embedded devices in unconventional application areas, so to show up new challenges in the system design/development process. in this setting, researchers, and practitioners from academia and industry get a chance to keep in touch with problems, open issues and future directions in the field of development of dedicated applications for embedded systems.
discrete wavelet transform-based multivariate exploration of tissue via imaging mass spectrometry. mass spectral imaging (msi) or imaging mass spectrometry is a developing technology that combines spatial information with traditional mass spectrometry. it enables researchers to study the spatial distribution of biomolecules such as proteins, peptides, and metabolites throughout organic tissue sections. msi has particular merit in exploratory settings where there is no prior hypothesis of relevant target molecules. it is rapidly becoming a potent exploratory instrument for tissue biomarker studies. msi is a high-throughput technique that mines massive amounts of measurements from a single tissue section. as various parameters such as the covered tissue surface area, the spatial resolution, and the extent of the mass range grow, msi data sets rapidly become very large, making analysis from a computational and memory standpoint increasingly difficult. in this paper we introduce the discrete wavelet transform (dwt) as a means of reducing the dimensionality of the data, while retaining a maximum amount of biochemical information. the dwt delivers a more compact description of each mass spectrum, expressed as wavelet coefficients. the efficacy of performing analyses directly in the dwt-reduced space is illustrated using unsupervised trend detection via principal component analysis (pca) on the msi measurement of a sagittal section of mouse brain.
an objective way to evaluate and compare binarization algorithms. the choice of the best binarization algorithm is very critical for any document image processing system, since it is one of the first tasks and any mistake it performs will be carried through the whole system. here, a new technique for the validation of document binarization algorithms is proposed. our method is simple in its implementation and it can be applied to any binarization algorithm since it doesn't require anything more than the binarization stage. it is based on the use of synthetic images from pdf document. then the binarization algorithm is applied and the result is compared with the original pdf.
a requirements specification case study with projectit-studio/requirements. the early stages of the software development process are crucial to overcome the generalized unsuccess among it projects. therefore, we embraced the goal of creating a case tool for requirements specification. our approach is based on a controlled natural language, seeking to achieve a higher level of rigor and quality of requirements specifications. moreover, this tool belongs to a broader workbench, which covers the software development life-cycle, providing guidance according to se best practices. this paper presents an illustrative specification case study, emphasizing the tool's support and its advantages.
an efficient feature ranking measure for text categorization. a major obstacle that decreases the performance of text classifiers is the extremely high dimensionality of text data. to reduce the dimension, a number of approaches based on rough-set theory have been proposed. however, these works often suffer from two problems: the first is that they cannot directly deal with continuous text features; the second is that they often incur considerable running time. to deal with the first issue, we make some extensions to discernibility matrix so that it can work with continuous features. to cut down running time, we employ centroids rather than examples to construct discernibility matrix, which reduce the time complexity from o(t2w) to o(k2w) where t denotes the size of training examples, k denotes the number of training classes and w denotes the size of vocabulary. the experimental results indicate that proposed method not only yields much higher accuracy than information gain when the number of selected features is smaller than 6000, but also incurs much smaller cpu time than information gain.
an integrated view on business- and it-architecture. the paper outlines the domains of enterprise architecture and fundamental design techniques. the consolidation of architecture description to three basic views is proposed. the component view describes the elements of architecture and their relationships. the communication view shows how the elements interact with one another. the distribution view describes how the elements are distributed in terms of location or organizational assignment. key element of architecture design is to account for interdependencies among the building blocks of architecture. blueprints are introduced as a means in planning the deployment of architecture on a large scale. they give a comprehensive view on the building blocks and how the interact. blueprints show the effects of architecture design between business-, application-, and infrastructure architecture, thus providing an integrated view on architecture. the techniques introduced for architecture design are illustrated by using a selection of real life examples from an architecture design project.
special track on programming for separation of concerns: editorial message. complex systems are intrinsically expensive to develop because several concerns must be addressed simultaneously. once the development phase is over, these systems are often hard to reuse and evolve because their concerns are intertwined and making apparently small changes forces programmers to modify many parts. moreover, legacy systems are difficult to evolve due the following problems: the lack of a well defined architecture, use of several programming languages and paradigms, etc.
special track on database theory, technology, and applications: editorial message. the world nowadays revolves around dealing with data presented in various formats. so it is inevitable that researchers focus their work on advancing the state of managing information. from here, the importance of database technology ranks amongst the hottest areas of research. this year the track has received many papers covering different areas of databases.
enterprise systems modeling: the erp5 development process. the design and implementation of an erp system involves capturing the information necessary for implementing the system's structure and behavior that support enterprise management. this process should start on the enterprise modeling level and finish at the coding level, going down through different abstraction layers. for the case of free/open source erp, the lack of proper modeling methods and tools jeopardizes the advantages of source code availability. moreover, the distributed, decentralized decision-making, and source-code driven development culture of open source communities, generally doesn't rely on methods for modeling the higher abstraction levels necessary for an erp solution. the aim of this paper is to present a model driven development process for the open source erp erp5. the proposed process covers the different abstraction levels involved, taking into account well established standards and common practices, as well as new approaches, by supplying enterprise, requirements, analysis, design, and implementation workflows.
symbiosis in logic-based pointcuts over a history of join points. within aspect-oriented programming, the quality of aspect code depends on the readability and expressiveness of pointcut languages. readability is increased by using specialized, declarative pointcut languages. for such languages, their expressiveness is increased if they offer an integration with the base code language. as has previously been shown, offering access to the past history of the base program also increases pointcut expressiveness. a logical desire then is creating pointcut languages that combine both features, but taken to the extreme this is not implementable. we discuss the unimplementable ideal model of declarative history-based logic pointcut languages, and the possible approximations that can be made that are still implementable and what limits they impose on the ideal expressiveness.
restoration of vibro-acoustography images. vibro-acoustography (va) is an imaging modality that produces an image of the mechanical response of an object to a localized dynamic radiation force of an ultrasound field. this technique has been studied and used in clinical applications as to image calcification in breast tissue and arteries. this paper presents the application of restoration algorithms to va images.
hierarchical memory system design for a heterogeneous multi-core processor. multi-core architecture has become hot issue recently both for performance and power consideration. memory system is the bottleneck under this circumstance. a multi-core architecture using simple cores based on transport triggered architecture is proposed. this architecture has a uniform programming view. the memory system design exploration and optimization is done and a hierarchical memory system is designed. a balanced memory bandwidth is provided to the multi-core architecture.
designing semantic web services using conceptual model. there are emerging technologies such as sawsdl or wsmo that extend the current web services technologies to so called semantic web services by combining the structural and semantic descriptions of web services. in this paper, we identify problems that can arise when using these technologies for the design and management of semantic web services and we show that using a conceptual model instead of these technologies can help to solve these problems. we also show how to automatically derive the description of semantic web services represented with existing technologies, concretely with sawsdl, from the conceptual level because this representation brings other advantages.
tcm-knn scheme for network anomaly detection using feature-based optimizations. with the rapid increase of network threats and cyber attacks, network security problem is becoming more and more serious. network anomaly detection is a key technique to secure information systems and resist cyber attacks. in this paper, we first propose an efficient network anomaly detection technique based on tcm-knn scheme. secondly, we emphasize the feature-based optimizations for our tcm-knn. we employ feature selection and feature weight mechanisms to optimize tcm-knn as a promising lightweight and on-line anomaly detection technique both in reducing its computational cost and in boosting its detection performance. a series of experiments on well-known intrusion detection dataset kdd cup 1999 demonstrate the effectiveness of our methods presented in this paper.
securing aspect composition. although research in aop is increasing in maturity there remain many unresolved issues. while current aop languages offer ever-increasing levels of flexibility, they still fail to offer a sufficient discipline of application to ensure that advanced aop facilities are used safely and appropriately. researchers have recognised the need to control aspect composition and have started to explore mechanisms to achieve this [2, 3, 4, 5]. in this paper we aim to provide a novel approach to control aspect composition (using aspectj as reference) and we employ the concept of roles from role based access control models [1] to characterise aspects in terms of both their internal behaviour and their external composition. then, using policies, we express invariants and constraints on the associated advice and pointcuts.