42894925
Modeling of Context-Aware Self-Adaptive Applications in Ubiquitous and Service-Oriented Environments
Mobile computing in ubiquitous environments has to cope with both predictable and unpredictable changes in the execution context, which introduces the need for context-aware adaptive applications. Such environments are also characterized by dynamically discoverable services that can be utilized by applications to improve their functionality and quality of service (QoS). Thus, application adaptation decisions not only depend on context properties, but also on service availability and QoS-properties. In this chapter we present a novel comprehensive modeling approach that facilitates the model-driven development of such applications. Our focus is on modeling concepts which align the description of services and their QoS-properties with the context modeling approach. We provide a harmonized view on context and service properties, bridging the syntactical and semantic differences through an ontology. We also consider related aspects like semantic service discovery and service level agreements.
13591397
A Context Query Language for Pervasive Computing Environments
This paper identifies requirements for querying and accessing context information in mobile and pervasive computing environments. Furthermore it studies existing query languages showing that they satisfy only a subset of these requirements or cover some of them only to a limited extent. A new context query language is presented to overcome these shortcomings, improving the state of the art in several respects: heterogeneous representations of context information, definition of complex filtering mechanisms, elaborate aggregation functions and ontology integration, all in one language.
14005418
A Comprehensive Context Modeling Framework for Pervasive Computing Systems
Context management in pervasive computing environments must reflect the specific characteristics of these environments, e.g. distribution, mobility, resource-constrained devices, or heterogeneity of context sources. Although a number of context models have been presented in the literature, none of them supports all of these requirements to a sufficient extent at the same time. In this paper, we present a comprehensive and integrated approach for context modeling in pervasive computing environments. It combines the advantages of existing approaches and addresses the need for supporting effective software development. The proposed context model follows an ontology-based approach and has three layers of abstraction, i.e. conceptual layer, exchange layer, and functional layer. This layered approach facilitates a model-driven development of context-aware applications. Throughout the paper we compare our solution with the related work in order to clearly demonstrate why we needed to develop a new context management framework and where we have adopted existing ideas.
13925823
Context inference of users' social relationships and distributed policy management
Inference of high-level context is becoming crucial in development of context-aware applications. An example is social context inference - i.e., deriving social relations based upon the user's daily communication with other people. The efficiency of this mechanism mainly depends on the method(s) used to draw inferences based on existing evidence and sample information, such as a training data. Our approach uses rule-based data mining, Bayesian network inference, and user feedback to compute the probabilities of another user being in the specific social relationship with a user whose daily communication is logged by a mobile phone. In addition, a privacy mechanism is required to ensure the user's personal integrity and privacy when sharing this user's sensitive context data. Therefore, the derived social relations are used to define a user's policies for context access control, which grant the restricted context information scope depending on the user's current context. Finally, we propose a distributed architecture capable of managing this context information based upon these context access policies.
14972044
Service-Oriented Adaptation in Ubiquitous Computing Environments
Ubiquitous computing environments may offer dynamically discoverable services that can be utilized by adaptive applications to improve their functionality and quality of service. We have developed a general software development framework for context-aware adaptive applications. In this paper we present our novel modeling concepts that extend an existing component-based modeling approach by service-oriented adaptation concepts. With our new extensions a dynamically discovered service may replace an application component if it increases the overall utility of the application. We discuss open questions and point to potential solution approaches.
209498655
Preface
The title of this book ‘One-Dimensional Finite Elements: An Introduction to the FE Method’ stands for content and focus. Nowadays, much literature regarding the topic of the finite element method exists. The different works reflect the multifaceted perceptions and application possibilities. The basic idea of this introduction into the finite element method relies on the concept of explaining the complex method with the help of one-dimensional elements. It is the goal to introduce the manifold aspects of the finite element method and to enable the reader to get a methodical understanding of important subject areas. The reader learns to understand the assumptions and derivations at different physical problems in structural mechanics. Furthermore, he/she learns to critically evaluate possibilities and limitations of the finite element method. Additional comprehensive mathematical descriptions, which solely result from advanced illustrations for twoor three-dimensional problems, are omitted. Hence, the mathematical description largely remains simple and clear. The focus on one-dimensional elements, however, is not just a pure limitation on a simpler and clearer formal illustration of the necessary equations. Within structural engineering, there are various structures— for example bridges or high transmission towers—which are usually modeled via one-dimensional elements. Therefore, this work also contains a ‘set of tools’, which can also be applied in practice. The concentration on one-dimensional elements is new for a textbook and allows the treatment of various basic and demanding physical questions of structural mechanics within one single textbook. This new concept, therefore, allows a methodical understanding of important subject areas (for example plasticity or composite materials), which occur to a prospective engineer during professional work, which however are seldom treated in this way at universities. Consequently, simple access is possible, also in supplementary areas of application of the finite element method. This book originates from a collection of lecture notes which were developed as written material for lectures and training documents for specialized courses on the finite element method. Especially, the calculated examples and the supplementary
10411388
Large-scale linear programming techniques for the design of protein folding potentials
Abstract.We present large-scale optimization techniques to model the energy function that underlies the folding process of proteins. Linear Programming is used to identify parameters in the energy function model, the objective being that the model predict the structure of known proteins correctly. Such trained functions can then be used either for ab-initio prediction or for recognition of unknown structures. In order to obtain good energy models we need to be able to solve dense Linear Programming Problems with tens (possibly hundreds) of millions of constraints in a few hundred parameters, which we achieve by tailoring and parallelizing the interior-point code PCx.
6423442
Rule-based anomaly pattern detection for detecting disease outbreaks
This paper presents an algorithm for performing early detection of disease outbreaks by searching a database of emergency department cases for anomalous patterns. Traditional techniques for anomaly detection are unsatisfactory for this problem because they identify individual data points that are rare due to particular combinations of features. When applied to our scenario, these traditional algorithms discover isolated outliers of particularly strange events, such as someone accidentally shooting their ear, that are not indicative of a new outbreak. Instead, we would like to detect anomalous patterns. These patterns are groups with specific characteristics whose recent pattern of illness is anomalous relative to historical patterns. We propose using a rule-based anomaly detection algorithm that characterizes each anomalous pattern with a rule. The significance of each rule is carefully evaluated using Fisher's Exact Test and a randomization test. Our algorithm is compared against a standard detection algorithm by measuring the number of false positives and the timeliness of detection. Simulated data, produced by a simulator that creates the effects of an epidemic on a city, is used for evaluation. The results indicate that our algorithm has significantly better detection times for common significance thresholds while having a slightly higher false positive rate.
61094772
Video to the rescue
Automatic person identity verification based on biometrics is a challenging problem, and has received much attention during recent years due to its many applications in on-line transaction processing, law enforcement, and security applications. However, most identity verification systems are primarily based on voice biometrics, and hence are more vulnerable to acoustic noise and channel distortions, in addition to train/test mismatch conditions. In this paper, we show how we can use video information to improve the performance of identity verification systems. The approach based on multimodal fusion of voice and face information from speaking face video allows robust identity verification performance. In addition, depending on the type of features and fusion technique used, it is also possible to perform liveness checks, allowing the system to detect fraudulent attacks on the system.
7724289
Outpatient clinic scheduling - a simulation approach
The process by which outpatients are scheduled for a doctor's visit is a crucial determinant of the overall efficiency of the patient flow. The problem at hand consists of determining prioritization (triage) rules so that adequate patient care is guaranteed, resources (provider schedules) are utilized efficiently and a service guarantee can be ensured. We present a simulation framework for the evaluation and optimization of scheduling rules. We outline the basic ingredients of our model, illustrate the kinds of analyses it has enabled us to perform and summarize our experience with a preliminary implementation for the Division of Pediatric Ophthalmology at Cincinnati Children's Hospital Medical Center. Challenges for adaptations to other settings are also outlined.
40752599
Liveness Assurance in Voice Authentication
The process of verifying whether the face image presented to an authentication system is real (i.e., alive), or whether it is reproduced or synthetic, and thus fraudulent. When a face authentication system is to recognize the face of a person by means of an electronic camera and associated image recognition software, it is important to be sure that the person seeking the authentication actually presents his or her face to the camera at the time and place of the authentication request. The face is presented live as on live television as distinct from a movie or cartoon programme. In contrast, an impostor could try to present a photograph, or a video recording, of a legitimate client to the camera in order to be falsely authenticated by the system as that client. That kind of threat to authentication systems is known generally as replay attack. In turn, liveness assurance uses a range of measures to reduce the vulnerability of face authentication systems to the threats of replay attack.