Closing Information Gaps with Need-driven Knowledge Sharing

Informationslücken schließen durch bedarfsgetriebenen Wissensaustausch Systeme zum asynchronen Wissensaustausch – wie Intranets, Wikis oder Dateiserver – leiden häufig unter mangelnden Nutzerbeiträgen. Ein Hauptgrund dafür ist, dass Informationsanbieter von Informationsuchenden entkoppelt, und deshalb nur wenig über deren Informationsbedarf gewahr sind. Zentrale Fragen des Wissensmanagements sind daher, welches Wissen besonders wertvoll ist und mit welchen Mitteln Wissensträger dazu motiviert werden können, es zu teilen. Diese Arbeit entwirft dazu den Ansatz des bedarfsgetriebenen Wissensaustauschs (NKS), der aus drei Elementen besteht. Zunächst werden dabei Indikatoren für den Informationsbedarf erhoben – insbesondere Suchanfragen – über deren Aggregation eine fortlaufende Prognose des organisationalen Informationsbedarfs (OIN) abgeleitet wird. Durch den Abgleich mit vorhandenen Informationen in persönlichen und geteilten Informationsräumen werden daraus organisationale Informationslücken (OIG) ermittelt, die auf fehlende Informationen hindeuten. Diese Lücken werden mit Hilfe so genannter Mediationsdienste und Mediationsräume transparent gemacht. Diese helfen Aufmerksamkeit für organisationale Informationsbedürfnisse zu schaffen und den Wissensaustausch zu steuern. Die konkrete Umsetzung von NKS wird durch drei unterschiedliche Anwendungen illustriert, die allesamt auf bewährten Wissensmanagementsystemen aufbauen. Bei der Inversen Suche handelt es sich um ein Werkzeug das Wissensträgern vorschlägt Dokumente aus ihrem persönlichen Informationsraum zu teilen, um damit organisationale Informationslücken zu schließen. Woogle erweitert herkömmliche Wiki-Systeme um Steuerungsinstrumente zur Erkennung und Priorisierung fehlender Informationen, so dass die Weiterentwicklung der Wiki-Inhalte nachfrageorientiert gestaltet werden kann. Auf ähnliche Weise steuert Semantic Need, eine Erweiterung für Semantic MediaWiki, die Erfassung von strukturierten, semantischen Daten basierend auf Informationsbedarf der in Form strukturierter Anfragen vorliegt. Die Umsetzung und Evaluation der drei Werkzeuge zeigt, dass bedarfsgetriebener Wissensaustausch technisch realisierbar ist und eine wichtige Ergänzung für das Wissensmanagement sein kann. Darüber hinaus bietet das Konzept der Mediationsdienste und Mediationsräume einen Rahmen für die Analyse und Gestaltung von Werkzeugen gemäß der NKS-Prinzipien. Schließlich liefert der hier vorstellte Ansatz auch Impulse für die Weiterentwicklung von Internetdiensten und -Infrastrukturen wie der Wikipedia oder dem Semantic Web

Automatic Annotation, Classification and Retrieval of Traumatic Brain Injury CT Images

Ph.DDOCTOR OF PHILOSOPH

Sixth Goddard Conference on Mass Storage Systems and Technologies Held in Cooperation with the Fifteenth IEEE Symposium on Mass Storage Systems

This document contains copies of those technical papers received in time for publication prior to the Sixth Goddard Conference on Mass Storage Systems and Technologies which is being held in cooperation with the Fifteenth IEEE Symposium on Mass Storage Systems at the University of Maryland-University College Inn and Conference Center March 23-26, 1998. As one of an ongoing series, this Conference continues to provide a forum for discussion of issues relevant to the management of large volumes of data. The Conference encourages all interested organizations to discuss long term mass storage requirements and experiences in fielding solutions. Emphasis is on current and future practical solutions addressing issues in data management, storage systems and media, data acquisition, long term retention of data, and data distribution. This year's discussion topics include architecture, tape optimization, new technology, performance, standards, site reports, vendor solutions. Tutorials will be available on shared file systems, file system backups, data mining, and the dynamics of obsolescence

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

Rule Extraction from Support Vector Machines: A Geometric Approach

Despite the success of connectionist systems in prediction and classi¯cation problems, critics argue that the lack of symbol processing and explanation capability makes them less competitive than symbolic systems. Rule extraction from neural networks makes the interpretation of the behaviour of connectionist networks possible by relating sub-symbolic and symbolic process- ing. However, most rule extraction methods focus only on speci¯c neural network architectures and present limited generalization performance. Support Vector Machine is an unsupervised learning method that has been recently applied successfully in many areas, and o®ers excellent generalization ability in comparison with other neural network, statistical, or symbolic machine learning models. In this thesis, an algorithm called Geometric and Oracle-Based Support Vector Machines Rule Extraction (GOSE) has been proposed to overcome the limitations of other rule-extraction methods by extracting comprehensible models from Support Vector Machines (SVM). This algorithm views the extraction as a geometric task. Given a trained SVM network, GOSE queries the synthetic instances and draws conjunction rules by approximating the optimization problem. The extracted rule set also represents the approximation of the SVM classi¯cation boundary. Unlike previous works in SVM rule-extraction, GOSE is broadly applicable to different networks and problems because it need not rely on training examples and network architectures. Theoretical proof guarantees that GOSE is capable of approximating the behavior of SVM networks. Empirical experiments are conducted on di®erent SVM networks from binary classification networks to multi-class networks in various classi¯cation domains. The result of experiments demonstrates that GOSE can extract comprehensible rules with high levels of accuracy and ¯delity for their corresponding networks. GOSE also exhibits superior consistency. After analyzing and applying several optimizing measures, the complexity of GOSE was improved. In brief, GOSE provides a novel way to explain how an SVM network functions

Programming Persistent Memory

Beginning and experienced programmers will use this comprehensive guide to persistent memory programming. You will understand how persistent memory brings together several new software/hardware requirements, and offers great promise for better performance and faster application startup times—a huge leap forward in byte-addressable capacity compared with current DRAM offerings. This revolutionary new technology gives applications significant performance and capacity improvements over existing technologies. It requires a new way of thinking and developing, which makes this highly disruptive to the IT/computing industry. The full spectrum of industry sectors that will benefit from this technology include, but are not limited to, in-memory and traditional databases, AI, analytics, HPC, virtualization, and big data. Programming Persistent Memory describes the technology and why it is exciting the industry. It covers the operating system and hardware requirements as well as how to create development environments using emulated or real persistent memory hardware. The book explains fundamental concepts; provides an introduction to persistent memory programming APIs for C, C++, JavaScript, and other languages; discusses RMDA with persistent memory; reviews security features; and presents many examples. Source code and examples that you can run on your own systems are included. What You’ll Learn Understand what persistent memory is, what it does, and the value it brings to the industry Become familiar with the operating system and hardware requirements to use persistent memory Know the fundamentals of persistent memory programming: why it is different from current programming methods, and what developers need to keep in mind when programming for persistence Look at persistent memory application development by example using the Persistent Memory Development Kit (PMDK) Design and optimize data structures for persistent memory Study how real-world applications are modified to leverage persistent memory Utilize the tools available for persistent memory programming, application performance profiling, and debugging Who This Book Is For C, C++, Java, and Python developers, but will also be useful to software, cloud, and hardware architects across a broad spectrum of sectors, including cloud service providers, independent software vendors, high performance compute, artificial intelligence, data analytics, big data, etc

The Value of Balanced Growth for Transportation

The Ohio Balanced Growth Program is a voluntary, locally-driven, incentive-driven program which aims to encourage compact, nodal development patterns. The Ohio Department of Transportation provided support for this research to evaluate potential links between Balanced Growth-type policy, land use and development patterns, and transportation benefits. A literature review was completed to understand the existing body of knowledge regarding the connection between policy, land use, and transportation. This included a scan of Balanced Growth-type programs across the US. Twenty-six US Metropolitan Statistical Areas (MSAs) were selected and reviewed for general geographic and policy characteristics. Land use and transportation outcome data were examined via scatterplot and linear regression across all of the MSAs. The results were evaluated broadly in light of policy frameworks in effect in each MSA, by categorizing land use policy into “tiers” based on voluntary vs. mandatory provisions, and applicability to private and public investment. Finally, a policy review was completed to understand the potential benefits of policy change at the state, regional, and local agency levels. Significant relationships were found between land use patterns, measured in terms of a sprawl composite index, and transportation outcomes for freeway lane miles, hours of delay, vehicle miles traveled, emissions, and safety. MSAs with “Tier 3” policies (mandatory, rigorous policy affecting both public and private investment) clustered together on both axes (transportation outcomes and sprawl); and MSAs within states clustered together along the sprawl score axis. Otherwise, there was no apparent pattern in the location of policy tiers along either the transportation or land use axes. Possible alternative explanations that could be evaluated in the future include overall transportation investment levels; inter-state and inter-regional travel demand; size and shape of the MSA; and market, economic and social factors. Conclusions included policy recommendations for ODOT in supporting compact, nodal development at the local, regional and state levels. Future study recommendations include pursuing future data collection, monitoring and evaluation over time

The Value of Balanced Growth for Transportation

The Ohio Balanced Growth Program is a voluntary, locally-driven, incentive-driven program which aims to encourage compact, nodal development patterns. The Ohio Department of Transportation provided support for this research to evaluate potential links between Balanced Growth-type policy, land use and development patterns, and transportation benefits. A literature review was completed to understand the existing body of knowledge regarding the connection between policy, land use, and transportation. This included a scan of Balanced Growth-type programs across the US. Twenty-six US Metropolitan Statistical Areas (MSAs) were selected and reviewed for general geographic and policy characteristics. Land use and transportation outcome data were examined via scatterplot and linear regression across all of the MSAs. The results were evaluated broadly in light of policy frameworks in effect in each MSA, by categorizing land use policy into “tiers” based on voluntary vs. mandatory provisions, and applicability to private and public investment. Finally, a policy review was completed to understand the potential benefits of policy change at the state, regional, and local agency levels. Significant relationships were found between land use patterns, measured in terms of a sprawl composite index, and transportation outcomes for freeway lane miles, hours of delay, vehicle miles traveled, emissions, and safety. MSAs with “Tier 3” policies (mandatory, rigorous policy affecting both public and private investment) clustered together on both axes (transportation outcomes and sprawl); and MSAs within states clustered together along the sprawl score axis. Otherwise, there was no apparent pattern in the location of policy tiers along either the transportation or land use axes. Possible alternative explanations that could be evaluated in the future include overall transportation investment levels; inter-state and inter-regional travel demand; size and shape of the MSA; and market, economic and social factors. Conclusions included policy recommendations for ODOT in supporting compact, nodal development at the local, regional and state levels. Future study recommendations include pursuing future data collection, monitoring and evaluation over time