40 research outputs found

    Bedload sediment transport regimes of urban gravel-bed rivers under different management scenarios

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    Watershed urbanization profoundly alters the hydrologic characteristics of urban rivers compared to their rural counterparts. This change in hydrologic conditions in combination with alterations to the sediment supply regime in urban watersheds leads to adjustments to channel form and the widespread degradation of urban rivers. Urban river management increasingly attempts to balance the societal needs of flood and erosion control, while simultaneously improving the ecological health or waterways. Two common types of river management include stormwater management (SWM), which focuses on the attenuation of urban floods, and in-stream restoration, which attempts to reconstruct stable and ecologically favourable channels. However, current urban river management designs lack consideration of the key process responsible for channel stability and habitat availability: bedload sediment transport. Two reasons for this shortcoming are the lack of bedload sediment data in urban watersheds and the consequent gap in understanding of the bedload transport dynamics of urban rivers. Consequently, the degradation of urban rivers persists. This project investigates bedload transport dynamics in urban rivers with different management scenarios to focus on four themes: (1) how urbanization affects bedload transport dynamics and its relationship to channel morphology, (2) how to best predict bedload transport dynamics in urban rivers, (3) how current urban river management strategies change the transport dynamics of rivers, and (4) how to improve bedload sediment monitoring technology. This project focuses on the grain-scale bedload transport dynamics of coarse material because it links to the morphodynamics and ecological processes of channels, it provides insights on the exact controls and spatial variability of bedload transport, and the responses to individual flood events can be directly measured. The overarching goal of this study is to contribute to improved urban river management strategies that focus on adaptive management and interdisciplinary approaches. Bedload sediment transport was monitored using RFID tracer stones in three streams with different hydrologic settings: rural, urban with no SWM, and urban with SWM. High-resolution water level data confirmed the hydrologic differences expected from the three watershed conditions, as well as channel enlargement characteristic of urban rivers. Results demonstrate that the morphologic differences between the study streams can be linked to changes in the grain-scale bedload transport dynamics of the streams. Bedload transport is accelerated in the urban stream due to an increase in the frequency of bedload mobilization, particularly of coarse sediment sizes. In contrast, SWM hasdecreased the bedload transport to an immobile and armoured state indicative of a competence-limit transport regime. Results are used to make recommendations for improved urban river management. Results from the bedload tracking were used to build predictive models of tracer displacements. A new variable that captures both the mobility and travel length of bed particles is introduced. Several flow metrics developed in the literature in rural and laboratory settings are calculated, and their ability to predict tracer displacements in the three streams is tested. Scaling tracer travel lengths by mean channel width collapses the data into a single, strong relationship with cumulative energy expenditure, providing a single model that can be used across systems with different watershed conditions. To assess the impact of an in-stream riffle-pool channel reconstruction on bedload sediment dynamics, bedload transport and morphologic change was monitored in adjacent unrestored and restored reaches of an urban channel. Results reveal that the restored reach is stable and self- maintaining, mirroring bedform maintenance processes in natural riffle-pool streams. However, the construction is more successful at slowing down the transport of coarse sediment more than fine sediment, leading to a coarse sediment discontinuity that may be contributing to accelerated channel adjustment beyond the limits of the constructed riffle-pool sequences. This project highlights the importance of considering the entire channel corridor when designing and monitoring restoration projects. A large limitation of bedload sediment tracking technology is the inability to determine the vertical position of tracers, which hinders the ability to study vertical mixing and translate tracer data into bedload transport rates. A new Radio Frequency Identification (RFID) bedload tracer stone is presented, along with results of laboratory performance tests. This new bedload tracer improves upon existing bedload sediment monitoring technology by providing the ability to measure the burial depth of tracers without disturbing the bed. An important contribution of this study is the extensive dataset of bedload transport collected in urban rivers. This study attempts to move away from descriptive differences in the characteristics of urban rivers compared to rural streams, and towards a process-level understanding of the anthropogenic effects on river systems. Grain-scale bedload transport theory, developed in rural and laboratory settings, is applied to urban settings to gain insights into the effects of urbanization and common river management strategies on the geomorphic processes of urban rivers. Recommendations for improved urban river management are developed from the results of this thesis

    Inferring Complex Activities for Context-aware Systems within Smart Environments

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    The rising ageing population worldwide and the prevalence of age-related conditions such as physical fragility, mental impairments and chronic diseases have significantly impacted the quality of life and caused a shortage of health and care services. Over-stretched healthcare providers are leading to a paradigm shift in public healthcare provisioning. Thus, Ambient Assisted Living (AAL) using Smart Homes (SH) technologies has been rigorously investigated to help address the aforementioned problems. Human Activity Recognition (HAR) is a critical component in AAL systems which enables applications such as just-in-time assistance, behaviour analysis, anomalies detection and emergency notifications. This thesis is aimed at investigating challenges faced in accurately recognising Activities of Daily Living (ADLs) performed by single or multiple inhabitants within smart environments. Specifically, this thesis explores five complementary research challenges in HAR. The first study contributes to knowledge by developing a semantic-enabled data segmentation approach with user-preferences. The second study takes the segmented set of sensor data to investigate and recognise human ADLs at multi-granular action level; coarse- and fine-grained action level. At the coarse-grained actions level, semantic relationships between the sensor, object and ADLs are deduced, whereas, at fine-grained action level, object usage at the satisfactory threshold with the evidence fused from multimodal sensor data is leveraged to verify the intended actions. Moreover, due to imprecise/vague interpretations of multimodal sensors and data fusion challenges, fuzzy set theory and fuzzy web ontology language (fuzzy-OWL) are leveraged. The third study focuses on incorporating uncertainties caused in HAR due to factors such as technological failure, object malfunction, and human errors. Hence, existing studies uncertainty theories and approaches are analysed and based on the findings, probabilistic ontology (PR-OWL) based HAR approach is proposed. The fourth study extends the first three studies to distinguish activities conducted by more than one inhabitant in a shared smart environment with the use of discriminative sensor-based techniques and time-series pattern analysis. The final study investigates in a suitable system architecture with a real-time smart environment tailored to AAL system and proposes microservices architecture with sensor-based off-the-shelf and bespoke sensing methods. The initial semantic-enabled data segmentation study was evaluated with 100% and 97.8% accuracy to segment sensor events under single and mixed activities scenarios. However, the average classification time taken to segment each sensor events have suffered from 3971ms and 62183ms for single and mixed activities scenarios, respectively. The second study to detect fine-grained-level user actions was evaluated with 30 and 153 fuzzy rules to detect two fine-grained movements with a pre-collected dataset from the real-time smart environment. The result of the second study indicate good average accuracy of 83.33% and 100% but with the high average duration of 24648ms and 105318ms, and posing further challenges for the scalability of fusion rule creations. The third study was evaluated by incorporating PR-OWL ontology with ADL ontologies and Semantic-Sensor-Network (SSN) ontology to define four types of uncertainties presented in the kitchen-based activity. The fourth study illustrated a case study to extended single-user AR to multi-user AR by combining RFID tags and fingerprint sensors discriminative sensors to identify and associate user actions with the aid of time-series analysis. The last study responds to the computations and performance requirements for the four studies by analysing and proposing microservices-based system architecture for AAL system. A future research investigation towards adopting fog/edge computing paradigms from cloud computing is discussed for higher availability, reduced network traffic/energy, cost, and creating a decentralised system. As a result of the five studies, this thesis develops a knowledge-driven framework to estimate and recognise multi-user activities at fine-grained level user actions. This framework integrates three complementary ontologies to conceptualise factual, fuzzy and uncertainties in the environment/ADLs, time-series analysis and discriminative sensing environment. Moreover, a distributed software architecture, multimodal sensor-based hardware prototypes, and other supportive utility tools such as simulator and synthetic ADL data generator for the experimentation were developed to support the evaluation of the proposed approaches. The distributed system is platform-independent and currently supported by an Android mobile application and web-browser based client interfaces for retrieving information such as live sensor events and HAR results

    Semantic discovery and reuse of business process patterns

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    Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

    Pertanika Journal of Science & Technology

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    Pertanika Journal of Science & Technology

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    Proceedings of the 5th International Workshop on Reconfigurable Communication-centric Systems on Chip 2010 - ReCoSoC\u2710 - May 17-19, 2010 Karlsruhe, Germany. (KIT Scientific Reports ; 7551)

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    ReCoSoC is intended to be a periodic annual meeting to expose and discuss gathered expertise as well as state of the art research around SoC related topics through plenary invited papers and posters. The workshop aims to provide a prospective view of tomorrow\u27s challenges in the multibillion transistor era, taking into account the emerging techniques and architectures exploring the synergy between flexible on-chip communication and system reconfigurability

    Mobile Ad Hoc Networks

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    Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms
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