TinyDDS

2012 ◽  
pp. 819-846 ◽  
Author(s):  
Pruet Boonma ◽  
Junichi Suzuki
Keyword(s):  
Functional Properties ◽  
Empirical Evaluation ◽  
Access Networks ◽  
Processing Efficiency ◽  
Fine Grained ◽  
Standard Data ◽  
Language Interoperability ◽  
Event Filtering ◽  
Key Issues ◽  
Data Distribution Service

Due to stringent constraints in memory footprint, processing efficiency and power consumption, traditional wireless sensor networks (WSNs) face two key issues: (1) a lack of interoperability with access networks and (2) a lack of flexibility to customize non-functional properties such as event filtering, data aggregation and routing. In order to address these issues, this chapter investigates interoperable publish/subscribe middleware for WSNs. The proposed middleware, called TinyDDS, enables the interoperability between WSNs and access networks by providing programming language interoperability and protocol interoperability based on the standard Data Distribution Service (DDS) specification. Moreover, TinyDDS provides a pluggable framework that allows WSN applications to have fine-grained control over application-level and middleware-level non-functional properties. Simulation and empirical evaluation results demonstrate that TinyDDS is lightweight and efficient on the TinyOS and SunSPOT platforms. The results also show that TinyDDS simplifies the development of publish/subscribe WSN applications.

TinyDDS

2010 ◽  
pp. 206-231 ◽  
Author(s):  
Pruet Boonma ◽  
Junichi Suzuki
Keyword(s):  
Functional Properties ◽  
Empirical Evaluation ◽  
Access Networks ◽  
Processing Efficiency ◽  
Fine Grained ◽  
Standard Data ◽  
Language Interoperability ◽  
Event Filtering ◽  
Key Issues ◽  
Data Distribution Service

Due to stringent constraints in memory footprint, processing efficiency and power consumption, traditional wireless sensor networks (WSNs) face two key issues: (1) a lack of interoperability with access networks and (2) a lack of flexibility to customize non-functional properties such as event filtering, data aggregation and routing. In order to address these issues, this chapter investigates interoperable publish/subscribe middleware for WSNs. The proposed middleware, called TinyDDS, enables the interoperability between WSNs and access networks by providing programming language interoperability and protocol interoperability based on the standard Data Distribution Service (DDS) specification. Moreover, TinyDDS provides a pluggable framework that allows WSN applications to have fine-grained control over application-level and middleware-level non-functional properties. Simulation and empirical evaluation results demonstrate that TinyDDS is lightweight and efficient on the TinyOS and SunSPOT platforms. The results also show that TinyDDS simplifies the development of publish/subscribe WSN applications.

scholarly journals An empirical evaluation of cost-based federated SPARQL query processing engines

Semantic Web ◽  
2021 ◽  
pp. 1-26
Author(s):  
Umair Qudus ◽  
Muhammad Saleem ◽  
Axel-Cyrille Ngonga Ngomo ◽  
Young-Koo Lee
Keyword(s):  
Query Processing ◽  
Detailed Analysis ◽  
Performance Metrics ◽  
Empirical Evaluation ◽  
Sparql Query ◽  
Evaluation Metrics ◽  
Future Cost ◽  
Query Plan ◽  
Fine Grained ◽  
Runtime Performance

Finding a good query plan is key to the optimization of query runtime. This holds in particular for cost-based federation engines, which make use of cardinality estimations to achieve this goal. A number of studies compare SPARQL federation engines across different performance metrics, including query runtime, result set completeness and correctness, number of sources selected and number of requests sent. Albeit informative, these metrics are generic and unable to quantify and evaluate the accuracy of the cardinality estimators of cost-based federation engines. To thoroughly evaluate cost-based federation engines, the effect of estimated cardinality errors on the overall query runtime performance must be measured. In this paper, we address this challenge by presenting novel evaluation metrics targeted at a fine-grained benchmarking of cost-based federated SPARQL query engines. We evaluate five cost-based federated SPARQL query engines using existing as well as novel evaluation metrics by using LargeRDFBench queries. Our results provide a detailed analysis of the experimental outcomes that reveal novel insights, useful for the development of future cost-based federated SPARQL query processing engines.

scholarly journals Personality Research and Assessment in the Era of Machine Learning

2020 ◽  
Vol 34 (5) ◽  
pp. 613-631 ◽  
Author(s):  
Clemens Stachl ◽  
Florian Pargent ◽  
Sven Hilbert ◽  
Gabriella M. Harari ◽  
Ramona Schoedel ◽  
...  
Keyword(s):  
Machine Learning ◽  
Personality Assessment ◽  
Latent Variables ◽  
Learning Models ◽  
Personality Psychology ◽  
Fine Grained ◽  
Personality Research ◽  
Key Issues ◽  
Complex Relationships ◽  
Machine Learning Models

The increasing availability of high–dimensional, fine–grained data about human behaviour, gathered from mobile sensing studies and in the form of digital footprints, is poised to drastically alter the way personality psychologists perform research and undertake personality assessment. These new kinds and quantities of data raise important questions about how to analyse the data and interpret the results appropriately. Machine learning models are well suited to these kinds of data, allowing researchers to model highly complex relationships and to evaluate the generalizability and robustness of their results using resampling methods. The correct usage of machine learning models requires specialized methodological training that considers issues specific to this type of modelling. Here, we first provide a brief overview of past studies using machine learning in personality psychology. Second, we illustrate the main challenges that researchers face when building, interpreting, and validating machine learning models. Third, we discuss the evaluation of personality scales, derived using machine learning methods. Fourth, we highlight some key issues that arise from the use of latent variables in the modelling process. We conclude with an outlook on the future role of machine learning models in personality research and assessment.

Complexity in tight gas sand development—an example from Perth Basin, Western Australia

2011 ◽  
Vol 51 (2) ◽  
pp. 743
Author(s):  
Reza Rezaee
Keyword(s):  
Tight Gas ◽  
Gas Reservoirs ◽  
Field Development ◽  
Fine Grained ◽  
Well Completion ◽  
Well Stimulation ◽  
Tight Gas Sands ◽  
Facies Change ◽  
Key Issues ◽  
Reservoir Geometry

One of the key issues for tight gas reservoirs is about reservoir heterogeneities and its connectivity. Knowledge of reservoir geometry, orientation, and connectedness is vital for reservoir modelling, which is the essential tool for successful field development, well completion, and well stimulation strategies. Fluvial sediments are heterogeneous both vertically and laterally due to facies change and diagenetic processes. These make their field development difficult. In terms of sand geometry and connectivity, the first step to making the reservoir model in three directions is to determine the width of sandstone bodies in various directions. Fine-grained facies associated with fluvial deposits can compartmentalise reservoirs and can significantly complicate the development of such units, as well as make well stimulation and fracturing jobs unpredictable. In this paper, the above issues are studied for some fluvial tight gas sands of the Perth Basin. The aim is to discuss the best possible way to successfully plan well and well stimulation strategies.

scholarly journals What is cumulative cultural evolution?

2018 ◽  
Vol 285 (1880) ◽  
pp. 20180712 ◽  
Author(s):  
Alex Mesoudi ◽  
Alex Thornton
Keyword(s):  
Cultural Evolution ◽  
Experimental Studies ◽  
Theoretical Models ◽  
Cognitive Mechanisms ◽  
Human Species ◽  
Fine Grained ◽  
Key Issues ◽  
Evolutionary Success ◽  
Cumulative Cultural Evolution ◽  
Necessary And Sufficient

In recent years, the phenomenon of cumulative cultural evolution (CCE) has become the focus of major research interest in biology, psychology and anthropology. Some researchers argue that CCE is unique to humans and underlies our extraordinary evolutionary success as a species. Others claim to have found CCE in non-human species. Yet others remain sceptical that CCE is even important for explaining human behavioural diversity and complexity. These debates are hampered by multiple and often ambiguous definitions of CCE. Here, we review how researchers define, use and test CCE. We identify a core set of criteria for CCE which are both necessary and sufficient, and may be found in non-human species. We also identify a set of extended criteria that are observed in human CCE but not, to date, in other species. Different socio-cognitive mechanisms may underlie these different criteria. We reinterpret previous theoretical models and observational and experimental studies of both human and non-human species in light of these more fine-grained criteria. Finally, we discuss key issues surrounding information, fitness and cognition. We recommend that researchers are more explicit about what components of CCE they are testing and claiming to demonstrate.

Die Welt aus der Perspektive der Entwicklungssoziologie

2020 ◽  
Keyword(s):  
Social Structure ◽  
East Asia ◽  
Everyday Life ◽  
Case Studies ◽  
South East Asia ◽  
Middle Classes ◽  
Comparative Analyses ◽  
Fine Grained ◽  
Key Issues ◽  
The Impact

In line with the encyclopaedic scope of development sociology, this book offers perspectives on key issues relating to societal processes. These encompass the shaping of everyday life, intergenerational relations in diverse societies, fine-grained comparative analyses of trajectories of violence and the impact of urbanisation in conceptions of freedom. Furthermore, the book discusses issues relating to social structure with particular emphasis on the debate on ‘African middle classes’. Besides presenting case studies from Africa, South East Asia and Europe, it also addresses fundamental issues from sociology. With contributions by Erdmute Alber, Artur Bogner, Antje Daniel, Mamadou Diawara, Gerhard Hauck, Reinhart Kößler, Rüdiger Korff, Roman Loimeier, Henning Melber, Matthias Neef, Matthew Sabbi, Rachel Spronk, Florian Stoll, Alexander Stroh-Steckelberg

scholarly journals Mobile Edge Caching

2021 ◽  
pp. 23-36
Author(s):  
Yan Zhang
Keyword(s):  
Artificial Intelligence ◽  
Access Networks ◽  
Edge Computing ◽  
Topology Design ◽  
Mobile Edge Computing ◽  
Key Issues ◽  
Types Of Information ◽  
Caching Mechanism ◽  
Edge Caching

AbstractEdge caching is a key part of mobile edge computing. It not only can support the necessary task data for edge computing, but also enables powerful Internet of Things applications with massive amounts of data and various types of information in access networks. In this chapter, we present the architecture of the edge caching mechanism and introduce metrics for evaluating caching performance. We then discuss key issues in caching topology design, caching data scheduling, as well as caching server cooperation and present a case study of artificial intelligence–empowered edge caching.

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