A model of Distributed Ayurvedic Diagnosis and Therapy System for Hridroga Using Agents

Diagnosis of Hridroga (cardiac disorders) in Ayurveda requires the combination of many different types of data, including personal details, patient symptoms, patient histories, general examination results, Ashtavidha pareeksha results etc. Computer-assisted decision support systems must be able to combine these data types into a seamless system. Intelligent agents, an approach that has been used chiefly in business applications, is used in medical diagnosis in this case. This paper is about a multi-agent system named “Distributed Ayurvedic Diagnosis and Therapy System for Hridroga using Agents” (DADTSHUA). It describes the architecture of the DADTSHUA model .This system is using mobile agents and ontology for passing data through the network. Due to this, transport delay can be minimized. It is a system which will be very helpful for the beginning physicians to eliminate his ambiguity in diagnosis and therapy. The system is implemented using Java Agent DEvelopment framework (JADE), which is a java-complaint mobile agent platform from TILab.

A Generic Software Architecture for a Domain Specific Distributed Embedded System

In this paper, we have evolved a generic software architecture for a domain specific distributed embedded system. The system under consideration belongs to the Command, Control and Communication systems domain. The systems in such domain have very long operational lifetime. The quality attributes of these systems are equally important as the functional requirements. The main guiding principle followed in this paper for evolving the software architecture has been functional independence of the modules. The quality attributes considered most important for the system are maintainability and modifiability. Architectural styles best suited for the functionally independent modules are proposed with focus on these quality attributes. The software architecture for the system is envisioned as a collection of architecture styles of the functionally independent modules identified

Autonomes Performance-Management in dienstorientierten Architekturen

Die Bedeutung des Dienstgüte-Managements (SLM) im Bereich von Unternehmensanwendungen steigt mit der zunehmenden Kritikalität von IT-gestützten Prozessen für den Erfolg einzelner Unternehmen. Traditionell werden zur Implementierung eines wirksamen SLMs Monitoringprozesse in hierarchischen Managementumgebungen etabliert, die einen Administrator bei der notwendigen Rekonfiguration von Systemen unterstützen. Auf aktuelle, hochdynamische Softwarearchitekturen sind diese hierarchischen Ansätze jedoch nur sehr eingeschränkt anwendbar. Ein Beispiel dafür sind dienstorientierte Architekturen (SOA), bei denen die Geschäftsfunktionalität durch das Zusammenspiel einzelner, voneinander unabhängiger Dienste auf Basis deskriptiver Workflow-Beschreibungen modelliert wird. Dadurch ergibt sich eine hohe Laufzeitdynamik der gesamten Architektur. Für das SLM ist insbesondere die dezentrale Struktur einer SOA mit unterschiedlichen administrativen Zuständigkeiten für einzelne Teilsysteme problematisch, da regelnde Eingriffe zum einen durch die Kapselung der Implementierung einzelner Dienste und zum anderen durch das Fehlen einer zentralen Kontrollinstanz nur sehr eingeschränkt möglich sind. Die vorliegende Arbeit definiert die Architektur eines SLM-Systems für SOA-Umgebungen, in dem autonome Management-Komponenten kooperieren, um übergeordnete Dienstgüteziele zu erfüllen: Mithilfe von Selbst-Management-Technologien wird zunächst eine Automatisierung des Dienstgüte-Managements auf Ebene einzelner Dienste erreicht. Die autonomen Management-Komponenten dieser Dienste können dann mithilfe von Selbstorganisationsmechanismen übergreifende Ziele zur Optimierung von Dienstgüteverhalten und Ressourcennutzung verfolgen. Für das SLM auf Ebene von SOA Workflows müssen temporär dienstübergreifende Kooperationen zur Erfüllung von Dienstgüteanforderungen etabliert werden, die sich damit auch über mehrere administrative Domänen erstrecken können. Eine solche zeitlich begrenzte Kooperation autonomer Teilsysteme kann sinnvoll nur dezentral erfolgen, da die jeweiligen Kooperationspartner im Vorfeld nicht bekannt sind und – je nach Lebensdauer einzelner Workflows – zur Laufzeit beteiligte Komponenten ausgetauscht werden können. In der Arbeit wird ein Verfahren zur Koordination autonomer Management-Komponenten mit dem Ziel der Optimierung von Antwortzeiten auf Workflow-Ebene entwickelt: Management-Komponenten können durch Übertragung von Antwortzeitanteilen untereinander ihre individuellen Ziele straffen oder lockern, ohne dass das Gesamtantwortzeitziel dadurch verändert wird. Die Übertragung von Antwortzeitanteilen wird mithilfe eines Auktionsverfahrens realisiert. Technische Grundlage der Kooperation bildet ein Gruppenkommunikationsmechanismus. Weiterhin werden in Bezug auf die Nutzung geteilter, virtualisierter Ressourcen konkurrierende Dienste entsprechend geschäftlicher Ziele priorisiert. Im Rahmen der praktischen Umsetzung wird die Realisierung zentraler Architekturelemente und der entwickelten Verfahren zur Selbstorganisation beispielhaft für das SLM konkreter Komponenten vorgestellt. Zur Untersuchung der Management-Kooperation in größeren Szenarien wird ein hybrider Simulationsansatz verwendet. Im Rahmen der Evaluation werden Untersuchungen zur Skalierbarkeit des Ansatzes durchgeführt. Schwerpunkt ist hierbei die Betrachtung eines Systems aus kooperierenden Management-Komponenten, insbesondere im Hinblick auf den Kommunikationsaufwand. Die Evaluation zeigt, dass ein dienstübergreifendes, autonomes Performance-Management in SOA-Umgebungen möglich ist. Die Ergebnisse legen nahe, dass der entwickelte Ansatz auch in großen Umgebungen erfolgreich angewendet werden kann.

Information Exchange and Fusion in Dynamic and Heterogeneous Distributed Environments

Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

Managing Quality Properties of Web Service Compositions

Web services from different partners can be combined to applications that realize a more complex business goal. Such applications built as Web service compositions define how interactions between Web services take place in order to implement the business logic. Web service compositions not only have to provide the desired functionality but also have to comply with certain Quality of Service (QoS) levels. Maximizing the users' satisfaction, also reflected as Quality of Experience (QoE), is a primary goal to be achieved in a Service-Oriented Architecture (SOA). Unfortunately, in a dynamic environment like SOA unforeseen situations might appear like services not being available or not responding in the desired time frame. In such situations, appropriate actions need to be triggered in order to avoid the violation of QoS and QoE constraints. In this thesis, proper solutions are developed to manage Web services and Web service compositions with regard to QoS and QoE requirements. The Business Process Rules Language (BPRules) was developed to manage Web service compositions when undesired QoS or QoE values are detected. BPRules provides a rich set of management actions that may be triggered for controlling the service composition and for improving its quality behavior. Regarding the quality properties, BPRules allows to distinguish between the QoS values as they are promised by the service providers, QoE values that were assigned by end-users, the monitored QoS as measured by our BPR framework, and the predicted QoS and QoE values. BPRules facilitates the specification of certain user groups characterized by different context properties and allows triggering a personalized, context-aware service selection tailored for the specified user groups. In a service market where a multitude of services with the same functionality and different quality values are available, the right services need to be selected for realizing the service composition. We developed new and efficient heuristic algorithms that are applied to choose high quality services for the composition. BPRules offers the possibility to integrate multiple service selection algorithms. The selection algorithms are applicable also for non-linear objective functions and constraints. The BPR framework includes new approaches for context-aware service selection and quality property predictions. We consider the location information of users and services as context dimension for the prediction of response time and throughput. The BPR framework combines all new features and contributions to a comprehensive management solution. Furthermore, it facilitates flexible monitoring of QoS properties without having to modify the description of the service composition. We show how the different modules of the BPR framework work together in order to execute the management rules. We evaluate how our selection algorithms outperform a genetic algorithm from related research. The evaluation reveals how context data can be used for a personalized prediction of response time and throughput.

Heterogeneous Multi-Robot Cooperation

This report addresses the problem of achieving cooperation within small- to medium- sized teams of heterogeneous mobile robots. I describe a software architecture I have developed, called ALLIANCE, that facilitates robust, fault tolerant, reliable, and adaptive cooperative control. In addition, an extended version of ALLIANCE, called L-ALLIANCE, is described, which incorporates a dynamic parameter update mechanism that allows teams of mobile robots to improve the efficiency of their mission performance through learning. A number of experimental results of implementing these architectures on both physical and simulated mobile robot teams are described. In addition, this report presents the results of studies of a number of issues in mobile robot cooperation, including fault tolerant cooperative control, adaptive action selection, distributed control, robot awareness of team member actions, improving efficiency through learning, inter-robot communication, action recognition, and local versus global control.

Enhanced Reality Visualization in a Surgical Environment

Enhanced reality visualization is the process of enhancing an image by adding to it information which is not present in the original image. A wide variety of information can be added to an image ranging from hidden lines or surfaces to textual or iconic data about a particular part of the image. Enhanced reality visualization is particularly well suited to neurosurgery. By rendering brain structures which are not visible, at the correct location in an image of a patient's head, the surgeon is essentially provided with X-ray vision. He can visualize the spatial relationship between brain structures before he performs a craniotomy and during the surgery he can see what's under the next layer before he cuts through. Given a video image of the patient and a three dimensional model of the patient's brain the problem enhanced reality visualization faces is to render the model from the correct viewpoint and overlay it on the original image. The relationship between the coordinate frames of the patient, the patient's internal anatomy scans and the image plane of the camera observing the patient must be established. This problem is closely related to the camera calibration problem. This report presents a new approach to finding this relationship and develops a system for performing enhanced reality visualization in a surgical environment. Immediately prior to surgery a few circular fiducials are placed near the surgical site. An initial registration of video and internal data is performed using a laser scanner. Following this, our method is fully automatic, runs in nearly real-time, is accurate to within a pixel, allows both patient and camera motion, automatically corrects for changes to the internal camera parameters (focal length, focus, aperture, etc.) and requires only a single image.

Dynamic bandwidth management as part of an integrated network management system based on distributed agents

We present a system for dynamic network resource configuration in environments with bandwidth reservation and path restoration mechanisms. Our focus is on the dynamic bandwidth management results, although the main goal of the system is the integration of the different mechanisms that manage the reserved paths (bandwidth, restoration, and spare capacity planning). The objective is to avoid conflicts between these mechanisms. The system is able to dynamically manage a logical network such as a virtual path network in ATM or a label switch path network in MPLS. This system has been designed to be modular in the sense that in can be activated or deactivated, and it can be applied only in a sub-network. The system design and implementation is based on a multi-agent system (MAS). We also included details of its architecture and implementation

Museum training to develop the social awareness of cultural identity in a time of universalization

The main theme of the ICTOP'94 Lisbon meeting is museum personnel training for the universal museum. At the very beginning it is important to identify what the notion universal museum can cover. It is necessary to underline the ambiguity of the term. On the one hand, the word 'universal' can be taken to refer to the variety of collected museum materials or museum collections, on the other hand it could refer to the efforts of the museum to be active outside the museum walls in order to achieve the integration of the heritage of a certain territory into a museological system. 'Universal' could also refer to the "new dimensions of reality: the fantastic reality of the virtual images, only existing in the human brain" (Scheiner 1994:7), which is very close to M. McLuhan's view of the world as a 'global village'. Thus, what is universal could be taken as being common and available to all the people of the world. 'Universal' can imply also the radical broadening of the concept of object: "mountain, silex, frog, waterfonts, stars, the moon ... everything is an object, with due fluctuations" (Hainard in Scheiner 1994: 7), which will cause the total involvement of the human being into his/her physical and spiritual environment. In the process of universalization, links between cultural and natural heritage and their links with human beings become more solid, helping to create a strong mutual interdependence.

A customizable multi-agent system for distributed data mining

We present a general Multi-Agent System framework for distributed data mining based on a Peer-to-Peer model. Agent protocols are implemented through message-based asynchronous communication. The framework adopts a dynamic load balancing policy that is particularly suitable for irregular search algorithms. A modular design allows a separation of the general-purpose system protocols and software components from the specific data mining algorithm. The experimental evaluation has been carried out on a parallel frequent subgraph mining algorithm, which has shown good scalability performances.

Quantitative analysis of accuracy of an inertial/acoustic 6DOF tracking system in motion

An increasing number of neuroscience experiments are using virtual reality to provide a more immersive and less artificial experimental environment. This is particularly useful to navigation and three-dimensional scene perception experiments. Such experiments require accurate real-time tracking of the observer's head in order to render the virtual scene. Here, we present data on the accuracy of a commonly used six degrees of freedom tracker (Intersense IS900) when it is moved in ways typical of virtual reality applications. We compared the reported location of the tracker with its location computed by an optical tracking method. When the tracker was stationary, the root mean square error in spatial accuracy was 0.64 mm. However, we found that errors increased over ten-fold (up to 17 mm) when the tracker moved at speeds common in virtual reality applications. We demonstrate that the errors we report here are predominantly due to inaccuracies of the IS900 system rather than the optical tracking against which it was compared. (c) 2006 Elsevier B.V. All rights reserved.

A flexible monitoring and notification system for distributed resources

Resource monitoring in distributed systems is required to understand the 'health' of the overall system and to help identify particular problems, such as dysfunctional hardware, a faulty, system or application software. Desirable characteristics for monitoring systems are the ability to connect to any number of different types of monitoring agents and to provide different views of the system, based on a client's particular preferences. This paper outlines and discusses the ongoing activities within the GridRM wide-area resource-monitoring project.

Using a RESTful messaging and registry system to support a range a distributed applications

Tycho was conceived in 2003 in response to a need by the GridRM [1] resource-monitoring project for a ldquolight-weightrdquo, scalable and easy to use wide-area distributed registry and messaging system. Since Tycho's first release in 2006 a number of modifications have been made to the system to make it easier to use and more flexible. Since its inception, Tycho has been utilised across a number of application domains including widearea resource monitoring, distributed queries across archival databases, providing services for the nodes of a Cray supercomputer, and as a system for transferring multi-terabyte scientific datasets across the Internet. This paper provides an overview of the initial Tycho system, describes a number of applications that utilise Tycho, discusses a number of new utilities, and how the Tycho infrastructure has evolved in response to experience of building applications with it.

A camera based digit location and recognition system for garment tracking

Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.