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Information systems research has started to use crowdsourcing platforms such as Amazon Mechanical Turks (MTurk) for scientific research, recently. In particular, MTurk provides a scalable, cheap work-force that can also be used as a pool of potential respondents for online survey research. In light of the increasing use of crowdsourcing platforms for survey research, the authors aim to contribute to the understanding of its appropriate usage. Therefore, they assess if samples drawn from MTurk deviate from those drawn via conventional online surveys (COS) in terms of answers in relation to relevant e-commerce variables and test the data in a nomological network for assessing differences in effects.
The authors compare responses from 138 MTurk workers with those of 150 German shoppers recruited via COS. The findings indicate, inter alia, that MTurk workers tend to exhibit more positive word-of mouth, perceived risk, customer orientation and commitment to the focal company. The authors discuss the study- results, point to limitations, and provide avenues for further research.
Unlocking the semantics of multimedia presentations in the web with the multimedia metadata ontology
(2010)
The semantics of rich multimedia presentations in the web such as SMIL, SVG and Flash cannot or only to a very limited extend be understood by search engines today. This hampers the retrieval of such presentations and makes their archival and management a difficult task. Existing metadata models and metadata standards are either conceptually too narrow, focus on a specific media type only, cannot be used and combined together, or are not practically applicable for the semantic description of rich multimedia presentations. In this paper, we propose the Multimedia Metadata Ontology (M3O) for annotating rich, structured multimedia presentations. The M3O provides a generic modeling framework for representing sophisticated multimedia metadata. It allows for integrating the features provided by the existing metadata models and metadata standards. Our approach bases on Semantic Web technologies and can be easily integrated with multimedia formats such as the W3C standards SMIL and SVG. With the M3O, we unlock the semantics of rich multimedia presentations in the web by making the semantics machine-readable and machine-understandable. The M3O is used with our SemanticMM4U framework for the multi-channel generation of semantically-rich multimedia presentations.
The processing of data is often restricted by contractual and legal requirements for protecting privacy and IPRs. Policies provide means to control how and by whom data is processed. Conditions of policies may depend on the previous processing of the data. However, existing policy languages do not provide means to express such conditions. In this work we present a formal model and language allowing for specifying conditions based on the history of data processing. We base the model and language on XACML.
We present a non-linear camera pose estimator, which is able to handle a combined input of point and line feature correspondences. For three or more correspondences, the estimator works on any arbitrary number and choice of the feature type, which provides an estimation of the pose on a preferably small and flexible amount of 2D-3D correspondences. We also give an analysis of different minimization techniques, parametrizations of the pose data, and of error measurements between 2D and 3D data. These will be tested for the usage of point features, lines and the combination case. The result shows the most stable and fast working non-linear parameter set for pose estimation in model-based tracking.
We introduce linear expressions for unrestricted dags (directed acyclic graphs) and finite deterministic and nondeterministic automata operating on them. Those dag automata are a conservative extension of the Tu,u-automata of Courcelle on unranked, unordered trees and forests. Several examples of dag languages acceptable and not acceptable by dag automata and some closure properties are given.
The E-KRHyper system is a model generator and theorem prover for first-order logic with equality. It implements the new E-hyper tableau calculus, which integrates a superposition-based handling of equality into the hyper tableau calculus. E-KRHyper extends our previous KRHyper system, which has been used in a number of applications in the field of knowledge representation. In contrast to most first order theorem provers, it supports features important for such applications, for example queries with predicate extensions as answers, handling of large sets of uniformly structured input facts, arithmetic evaluation and stratified negation as failure. It is our goal to extend the range of application possibilities of KRHyper by adding equality reasoning.
UML models and OWL ontologies constitute modeling approaches with different strength and weaknesses that make them appropriate for use of specifying different aspects of software systems. In particular, OWL ontologies are well suited to specify classes using an expressive logical language with highly flexible, dynamic and polymorphic class membership, while UML diagrams are much more suitable for specifying not only static models including classes and associations, but also dynamic behavior. Though MOF based metamodels and UML profiles for OWL have been proposed in the past, an integrated use of both modeling approaches in a coherent framework has been lacking so far. We present such a framework, TwoUse, for developing integrated models, comprising the benefits of UML models and OWL ontologies
Hybrid systems are the result of merging the two most commonly used models for dynamical systems, namely continuous dynamical systems defined by differential equations and discrete-event systems defined by automata. One can view hybrid systems as constrained systems, where the constraints describe the possible process flows, invariants within states, and transitions on the one hand, and to characterize certain parts of the state space (e.g. the set of initial states, or the set of unsafe states) on the other hand. Therefore, it is advantageous to use constraint logic programming (CLP) as an approach to model hybrid systems. In this paper, we provide CLP implementations, that model hybrid systems comprising several concurrent hybrid automata, whose size is only straight proportional to the size of the given system description. Furthermore, we allow different levels of abstraction by making use of hierarchies as in UML statecharts. In consequence, the CLP model can be used for analyzing and testing the absence or existence of (un)wanted behaviors in hybrid systems. Thus in summary, we get a procedure for the formal verification of hybrid systems by model checking, employing logic programming with constraints.
Hybrid automata are used as standard means for the specification and analysis of dynamical systems. Several researches have approached them to formally specify reactive Multi-agent systems situated in a physical environment, where the agents react continuously to their environment. The specified systems, in turn, are formally checked with the help of existing hybrid automata verification tools. However, when dealing with multi-agent systems, two problems may be raised. The first problem is a state space problem raised due to the composition process, where the agents have to be parallel composed into an agent capturing all possible behaviors of the multi-agent system prior to the verification phase. The second problem concerns the expressiveness of verification tools when modeling and verifying certain behaviors. Therefore, this paper tackles these problems by showing how multi-agent systems, specified as hybrid automata, can be modeled and verified using constraint logic programming(CLP). In particular, a CLP framework is presented to show how the composition of multi-agent behaviors can be captured dynamically during the verification phase. This can relieve the state space complexity that may occur as a result of the composition process. Additionally, the expressiveness of the CLP model flexibly allows not only to model multi-agent systems, but also to check various properties by means of the reachability analysis. Experiments are promising to show the feasibility of our approach.
This paper describes the robot Lisa used by team homer@UniKoblenz of the University of Koblenz Landau, Germany, for the participation at the RoboCup@Home 2017 in Nagoya, Japan. A special focus is put on novel system components and the open source contributions of our team. We have released packages for object recognition, a robot face including speech synthesis, mapping and navigation, speech recognition interface via android and a GUI. The packages are available (and new packages will be released) on
http://wiki.ros.org/agas-ros-pkg.