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With new government regulations and emerging knowledge of the risk to the environment posed by the failure of stormwater pipelines, stormwater infrastructure asset management is becoming increasingly important in the U.S. An essential aspect of asset management practice is the accurate performance assessment of one's assets. This paper presents a weighted factor framework to determine the performance of stormwater pipes. This paper prepares a list of 50 parameters affecting the performance of stormwater pipelines; the list is based on a review of the literature, existing asset management plans, and feedback from utilities. This list is broken down into essential and preferential parameters. Indeed, not all utilities necessarily possess sufficient resources to collect such a large set of parameters. This study also develops a three-level hierarchical structure of the degradation of stormwater pipeline infrastructure. The structure consists of five failure modules and the essential parameters only. On the basis of the survey results gathered from 10 utilities across the EPA regions, the study combines the essential parameters into a performance index. The index is a scale of 1 to 5, similar to the National Association of Sewer Service Companies' Pipeline Assessment and Certification Program grading system. Grade 1 implies excellent condition and Grade 5 implies collapse is imminent. / Master of Science

The increasing penetration of distributed generation, responsive loads and emerging smart metering technologies will continue the transformation of distribution systems from passive to active network conditions. In such active networks, State Estimation (SE) tools will be essential in order to enable extensive monitoring and enhanced control technologies. In future distribution management systems, the novel electrical power distribution system SE requires development in a scalable manner in order to accommodate small to massive size networks, be operable with limited real time measurements and a restricted time frame. Furthermore, a significant phase of new sensor deployment is inevitable to enable distribution system SE, since present-day distribution networks lack the required level of measurement and instrumentation. In the above context, the research presented in this thesis investigates five SE optimization solution methods with various case studies related to expected scenarios of future distribution networks to determine their suitability. Hachtel's Augmented Matrix method is proposed and developed as potential SE optimizer for distribution systems due to its potential performance characteristics with regard to accuracy and convergence. Differential Evolution Algorithm (DEA) and Overlapping Zone Approach (OZA) are investigated to achieve scalability of SE tools; followed by which the network division based OZA is proposed and developed. An OZA requiring additional measurements is also proposed to provide a feasible solution for voltage estimation at a reduced computation cost. Realising the requirement of additional measurements deployment to enable distribution system SE, the development of a novel meter placement algorithm that provides economical and feasible solutions is demonstrated. The algorithm is strongly focused on reducing the voltage estimation errors and is capable of reducing the error below desired threshold with limited measurements. The scalable SE solution and meter placement algorithm are applied on a multi-processor system in order to examine effective reduction of computation time. Significant improvement in computation time is observed in both cases by dividing the problem into smaller segments. However, it is important to note that enhanced network division reduces computation time further at the cost of accuracy of estimation. Different networks including both idealised (16, 77, 356 and 711 node UKGDS) and real (40 and 43 node EG) distribution network data are used as appropriate to the requirement of the applications throughout this thesis.

Master of Science / Department of Computing and Information Sciences / Doina Caragea / Over the last decade, the Internet has become an involving medium and user-generated content is continuously growing. Recommender systems that exploit user feedback are widely used in e-commerce and quite necessary for business enhancement. To make use of such user feedback, we propose a new content/collaborative hybrid approach, which is built on top of the recently released hetrec2011-movielens-2k dataset and is an extension of a previously proposed approach, called Weighted Tag Recommender (WTR). The WTR approach makes use of tag information available in hetrec2011-movielens-2k, but it does not use explicit ratings. As opposed to WTR, our modified approach can make use of ratings to capture collaborative filtering and either user-tags, available in the hetrec2011-movielens-2k, or movie keywords retrieved from IMDB, to capture movie content information. We call the two versions of our approach Weighted Tag Rating Recommender (WTRR) and Weighted Keyword Rating Recommender (WKRR), respectively. Movie keywords (which are not user specific) allow us to use all ratings available in hetrec2011-movielens-2k, as WKKR associates the content information from movies with the users, based on their ratings. On the other hand, tags provide more specific information for a user, but limit the usage of the data to the user-movie pairs that have tags (significantly smaller number compared with all pairs that have ratings). Both our keyword and tag representations of users can help alleviate the noise and semantic ambiguity problems inherent in information contributed by users of social networks. Experiments using the WTRR approach on a subset of the dataset (which contains both ratings and tags) show that it slightly outperforms the WKRR approach. However, WKRR can be applied to the whole hetrec2011-movielens-2k dataset and results show that the information from keywords can help build a movie recommender system competitive with other neighborhood based approaches and even with more sophisticated state-of-the-art approaches.

The tension-compression vibration of an elastic cusped plate is studied under all the reasonable boundary conditions at the cusped edge, while at the noncusped edge displacements and at the upper and lower faces of the plate stresses are given.

Intelligent Tutoring Systems (ITS) have a significant educational impact on student's learning. However, researchers report time intensive interaction is needed between ITS developers and domain-experts to gather and represent domain knowledge. The challenge is augmented when the target domain is ill-defined. The primary problem resides in often using traditional approaches for gathering domain and tutoring experts' knowledge at design time and conventional methods for knowledge representation built for well-defined domains. Similar to evolving knowledge acquisition approaches used in other fields, we replace this restricted view of ITS knowledge learning merely at design time with an incremental approach that continues training the ITS during run time. We investigate a gradual knowledge learning approach through continuous instructor-student demonstrations. We present a Mixed-response Intelligent Tutoring System based on Learning from Demonstration that gathers and represents knowledge at run time. Furthermore, we implement two knowledge representation methods (Weighted Markov Models and Weighted Context Free Grammars) and corresponding algorithms for building domain and tutoring knowledge-bases at run time. We use students' solutions to cybersecurity exercises as the primary data source for our initial framework testing. Five experiments were conducted using various granularity levels for data representation, multiple datasets differing in content and size, and multiple experts to evaluate framework performance. Using our WCFG-based knowledge representation method in conjunction with a finer data representation granularity level, the implemented framework reached 97% effectiveness in providing correct feedback. The ITS demonstrated consistency when applied to multiple datasets and experts. Furthermore, on average, only 1.4 hours were needed by instructors to build the knowledge-base and required tutorial actions per exercise. Finally, the ITS framework showed suitable and consistent performance when applied to a second domain. These results imply that ITS domain models for ill-defined domains can be gradually constructed, yet generate successful results with minimal effort from instructors and framework developers. We demonstrate that, in addition to providing an effective tutoring performance, an ITS framework can offer: scalability in data magnitude, efficiency in reducing human effort required for building a confident knowledge-base, metacognition in inferring its current knowledge, robustness in handling different pedagogical and tutoring criteria, and portability for multiple domain use.

In 1994, Alur and Dill introduced timed automata as a simple mathematical model for modelling the behaviour of real-time systems. In this thesis, we extend timed automata with weights. More detailed, we equip both the states and transitions of a timed automaton with weights taken from an appropriate mathematical structure. The weight of a transition determines the weight for taking this transition, and the weight of a state determines the weight for letting time elapse in this state. Since the weight for staying in a state depends on time, this model, called weighted timed automata, has many interesting applications, for instance, in operations research and scheduling. We give characterizations for the behaviours of weighted timed automata in terms of rational expressions and logical formulas. These formalisms are useful for the specification of real-time systems with continuous resource consumption. We further investigate the relation between the behaviours of weighted timed automata and timed automata. Finally, we present important decidability results for weighted timed automata.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第22351号 / 医博第4592号 / 新制||医||1042(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 妹尾 浩, 教授 溝脇 尚志, 教授 戸井 雅和 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Endliche Wortautomaten ermöglichen es, reguläre Wortsprachen sowohl zu erkennen als auch zu erzeugen. Julius Richard Büchi gelang es, diese erkennbaren Wortsprachen mithilfe der monadischen Logik zweiter Stufe, kurz MSO, zu charakterisieren [7, 19]. Dieses Ergebnis wurde dann auf erkennbare Baumsprachen, das heißt Mengen von geordneten Bäumen, die durch einenAufwärtsbaumautomaten erkannt werden, erweitert [11, 28]. Anstelle der <-Relation auf den Positionen eines Wortes tritt dabei die Kindrelation edgei(x; y) für die Positionen eines Baumes. Die erkennbaren Wort- und Baumsprachen haben breite Anwendung in der Informatik gefunden. Zu den bekanntesten gehören beispielsweise reguläre Ausdrücke und Syntaxbäume vieler Programmiersprachen. Im Zusammenspiel mit XML ist die Schemasprache RelaxNG zur Dokumentvalidierung [9, 29], im Gegensatz zu XML-Schema, durch die reiche Theorie erkennbarer Baumsprachen fundiert.

Context: Obesity is a growing global health concern. The increased body mass and altered mass distribution associated with obesity may be related to increases in plantar shear that putatively leads to physical functional deficits. Therefore, measurement of plantar shear may provide unique insights on the effects of body mass and body distribution on physical function or performance. Purpose: 1) To investigate the effects of body mass and distribution on plantar shear; 2) To examine how altered plantar shear influences postural control and gait kinetics. Hypothesis: 1) a weighted vest forward distributed (FV) would shift the center of pressure (CoP) location forward during standing compared with a weighted vest evenly distributed (EV); 2) FV would increase plantar shear spreading forces more than EV during standing; 3) FV would increase postural sway during standing while EV would not; and 4) FV would increase peak braking force, plantar impulses, and plantar shear spreading forces during walking more than EV. Methods: Twenty healthy young males participated in four different tests: 1) static test (for measuring plantar shear and CoP location without acceleration; 2) two-leg standing postural control test; 3) one-leg standing postural test; and 4) walking test. All tests were executed in three different weight conditions: 1) unweighted (NV); 2) evenly distributed vest (EV) with 20% added body mass; and 3) front-loaded vest (FV), also with 20% added body mass. Plantar shear stresses were measured using a pressure/shear device, and several shear and postural control metrics were extracted. Repeated measures ANOVAs with Holms post hoc test were used to compare each metric among the three conditions (α = 0.05). Results: FV and EV increased both anterior-posterior and medial-lateral plantar shear forces in single-foot trials compared to NV. FV shifted CoP forward. FV and EV showed decreased CoP range and velocity and increased time-to-boundary (TTB) during postural control compared to NV. While EV increased medial-lateral plantar shear spreading force, FV increased anterior-posterior plantar shear spreading force during walking. Conclusion: Added body mass increases plantar shear spreading forces. Body mass distribution had greater effects during dynamic tasks. In addition, healthy young individuals seem to quickly adapt to external stimuli to control postural stability. However, the interactive effects between body mass and distribution may disrupt physical function and/or performance in other populations—such as elderly, obese, and diabetes. Plantar shear may play a critical role in clinical diagnosis. However, as it is the first step study, follow-up studies are necessary to further support the clinical role of plantar shear.