Ontology Engineering The “What’s”, “Why’s”, and “How’s” of Data Exchange

2011 ◽  
Vol 3 (1) ◽  
pp. 40-53 ◽  
Author(s):  
J. M. Easton ◽  
J. R. Davies ◽  
C. Roberts
Keyword(s):  
Data Exchange ◽  
Large Scale ◽  
Distribution Networks ◽  
Process Data ◽  
Semantic Web Technologies ◽  
Intelligent Decision Making ◽  
New Information ◽  
Electricity Grids ◽  
Financial Climate ◽  
Condition Monitoring Systems

In a challenging financial climate, there is a growing impetus for businesses to use existing process data to support more intelligent decision making. For large-scale complex systems such as railways, electricity grids, and gas distribution networks, this often means combining information from numerous different condition monitoring systems; however, given the vast amounts of data produced every day and the frequently incompatible data models used to represent it, is it possible to be sure that the information generated is being used correctly? This paper provides an introduction to the field of Ontology, an emerging technology that allows the exact “meaning” of an item of data to be described in a way that can be interpreted by computers. Through this retention of meaning, it becomes possible for computers to perform simple reasoning operations, inferring new information about a system from the existing facts, and enabling exciting new Semantic Web technologies.

Ontology Engineering The “Whats,” “Whys,” and “Hows” of Data Exchange

2013 ◽  
pp. 72-86
Author(s):  
J. M. Easton ◽  
J. R. Davies ◽  
C. Roberts
Keyword(s):  
Data Exchange ◽  
Large Scale ◽  
Distribution Networks ◽  
Semantic Web Technologies ◽  
Intelligent Decision Making ◽  
New Information ◽  
Intelligent Decision ◽  
Electricity Grids ◽  
Financial Climate ◽  
Condition Monitoring Systems

In a challenging financial climate, there is a growing impetus for businesses to use existing process data to support more intelligent decision making. For large-scale complex systems such as railways, electricity grids, and gas distribution networks, this often means combining information from numerous different condition monitoring systems; however, given the vast amounts of data produced every day and the frequently incompatible data models used to represent it, is it possible to be sure that the information generated is being used correctly? This paper provides an introduction to the field of Ontology, an emerging technology that allows the exact “meaning” of an item of data to be described in a way that can be interpreted by computers. Through this retention of meaning, it becomes possible for computers to perform simple reasoning operations, inferring new information about a system from the existing facts, and enabling exciting new Semantic Web technologies.

A distributed data exchange engine for polystores

2020 ◽  
Vol 62 (3-4) ◽  
pp. 145-156
Author(s):  
Abdulrahman Kaitoua ◽  
Tilmann Rabl ◽  
Volker Markl
Keyword(s):  
High Performance ◽  
Data Exchange ◽  
Data Migration ◽  
Distributed Data ◽  
Performance Gain ◽  
Process Data ◽  
New Information ◽  
Combining Data ◽  
Resource Cost ◽  
And Performance

AbstractThere is an increasing interest in fusing data from heterogeneous sources. Combining data sources increases the utility of existing datasets, generating new information and creating services of higher quality. A central issue in working with heterogeneous sources is data migration: In order to share and process data in different engines, resource intensive and complex movements and transformations between computing engines, services, and stores are necessary.Muses is a distributed, high-performance data migration engine that is able to interconnect distributed data stores by forwarding, transforming, repartitioning, or broadcasting data among distributed engines’ instances in a resource-, cost-, and performance-adaptive manner. As such, it performs seamless information sharing across all participating resources in a standard, modular manner. We show an overall improvement of 30 % for pipelining jobs across multiple engines, even when we count the overhead of Muses in the execution time. This performance gain implies that Muses can be used to optimise large pipelines that leverage multiple engines.

Why Has There Been No People’s Power Rebellion in North Korea?

2018 ◽  
pp. 1-34
Author(s):  
Andrew Jackson
Keyword(s):  
Rural Areas ◽  
North Korea ◽  
Large Scale ◽  
Political Elite ◽  
Information Control ◽  
Al Jazeera ◽  
The North ◽  
New Information ◽  
Effective System ◽  
The Right

One scenario put forward by researchers, political commentators and journalists for the collapse of North Korea has been a People’s Power (or popular) rebellion. This paper analyses why no popular rebellion has occurred in the DPRK under Kim Jong Un. It challenges the assumption that popular rebellion would happen because of widespread anger caused by a greater awareness of superior economic conditions outside the DPRK. Using Jack Goldstone’s theoretical expla-nations for the outbreak of popular rebellion, and comparisons with the 1989 Romanian and 2010–11 Tunisian transitions, this paper argues that marketi-zation has led to a loosening of state ideological control and to an influx of infor-mation about conditions in the outside world. However, unlike the Tunisian transitions—in which a new information context shaped by social media, the Al-Jazeera network and an experience of protest helped create a sense of pan-Arab solidarity amongst Tunisians resisting their government—there has been no similar ideology unifying North Koreans against their regime. There is evidence of discontent in market unrest in the DPRK, although protests between 2011 and the present have mostly been in defense of the right of people to support themselves through private trade. North Koreans believe this right has been guaranteed, or at least tacitly condoned, by the Kim Jong Un government. There has not been any large-scale explosion of popular anger because the state has not attempted to crush market activities outright under Kim Jong Un. There are other reasons why no popular rebellion has occurred in the North. Unlike Tunisia, the DPRK lacks a dissident political elite capable of leading an opposition movement, and unlike Romania, the DPRK authorities have shown some flexibility in their anti-dissent strategies, taking a more tolerant approach to protests against economic issues. Reduced levels of violence during periods of unrest and an effective system of information control may have helped restrict the expansion of unrest beyond rural areas.

scholarly journals Using process data to understand problem-solving strategies and processes for drag-and-drop items in a large-scale mathematics assessment

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Yang Jiang ◽  
Tao Gong ◽  
Luis E. Saldivia ◽  
Gabrielle Cayton-Hodges ◽  
Christopher Agard
Keyword(s):  
Problem Solving ◽  
Time Allocation ◽  
Large Scale ◽  
Solution Process ◽  
Process Data ◽  
Mathematics Assessments ◽  
Assessment Design ◽  
Eighth Grade Students ◽  
Problem Solving Strategies ◽  
Drag And Drop

AbstractIn 2017, the mathematics assessments that are part of the National Assessment of Educational Progress (NAEP) program underwent a transformation shifting the administration from paper-and-pencil formats to digitally-based assessments (DBA). This shift introduced new interactive item types that bring rich process data and tremendous opportunities to study the cognitive and behavioral processes that underlie test-takers’ performances in ways that are not otherwise possible with the response data alone. In this exploratory study, we investigated the problem-solving processes and strategies applied by the nation’s fourth and eighth graders by analyzing the process data collected during their interactions with two technology-enhanced drag-and-drop items (one item for each grade) included in the first digital operational administration of the NAEP’s mathematics assessments. Results from this research revealed how test-takers who achieved different levels of accuracy on the items engaged in various cognitive and metacognitive processes (e.g., in terms of their time allocation, answer change behaviors, and problem-solving strategies), providing insights into the common mathematical misconceptions that fourth- and eighth-grade students held and the steps where they may have struggled during their solution process. Implications of the findings for educational assessment design and limitations of this research are also discussed.

scholarly journals Selecting Optimal Combination of Data Channels for Semantic Segmentation in City Information Modelling (CIM)

2021 ◽  
Vol 13 (7) ◽  
pp. 1367
Author(s):  
Yuanzhi Cai ◽  
Hong Huang ◽  
Kaiyang Wang ◽  
Cheng Zhang ◽  
Lei Fan ◽  
...  
Keyword(s):  
Large Scale ◽  
Semantic Segmentation ◽  
Optimal Combination ◽  
Reconstruction Technique ◽  
Process Data ◽  
Redundant Data ◽  
Multiple Data ◽  
Information Models ◽  
Efficient Data

Over the last decade, a 3D reconstruction technique has been developed to present the latest as-is information for various objects and build the city information models. Meanwhile, deep learning based approaches are employed to add semantic information to the models. Studies have proved that the accuracy of the model could be improved by combining multiple data channels (e.g., XYZ, Intensity, D, and RGB). Nevertheless, the redundant data channels in large-scale datasets may cause high computation cost and time during data processing. Few researchers have addressed the question of which combination of channels is optimal in terms of overall accuracy (OA) and mean intersection over union (mIoU). Therefore, a framework is proposed to explore an efficient data fusion approach for semantic segmentation by selecting an optimal combination of data channels. In the framework, a total of 13 channel combinations are investigated to pre-process data and the encoder-to-decoder structure is utilized for network permutations. A case study is carried out to investigate the efficiency of the proposed approach by adopting a city-level benchmark dataset and applying nine networks. It is found that the combination of IRGB channels provide the best OA performance, while IRGBD channels provide the best mIoU performance.

scholarly journals Can Blockchain Strengthen the Energy Internet?

Network ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 95-115
Author(s):  
Charithri Yapa ◽  
Chamitha de Alwis ◽  
Madhusanka Liyanage
Keyword(s):  
Distributed Generation ◽  
Paradigm Shift ◽  
Distribution Networks ◽  
Future Research ◽  
Disruptive Technology ◽  
Electricity Distribution ◽  
Energy Internet ◽  
Energy Delivery ◽  
Electricity Grids

Emergence of the Energy Internet (EI) demands restructuring of traditional electricity grids to integrate heterogeneous energy sources, distribution network management with grid intelligence and big data management. This paradigm shift is considered to be a breakthrough in the energy industry towards facilitating autonomous and decentralized grid operations while maximizing the utilization of Distributed Generation (DG). Blockchain has been identified as a disruptive technology enabler for the realization of EI to facilitate reliable, self-operated energy delivery. In this paper, we highlight six key directions towards utilizing blockchain capabilities to realize the envisaged EI. We elaborate the challenges in each direction and highlight the role of blockchain in addressing them. Furthermore, we summarize the future research directive in achieving fully autonomous and decentralized electricity distribution networks, which will be known as Energy Internet.

On the Transient Behavior of Large-Scale Distribution Networks During Automatic Feeder Reconfiguration

2012 ◽  
Vol 3 (2) ◽  
pp. 887-896 ◽  
Author(s):  
V. Spitsa ◽  
X. Ran ◽  
R. Salcedo ◽  
J. F. Martinez ◽  
R. E. Uosef ◽  
...  
Keyword(s):  
Large Scale ◽  
Transient Behavior ◽  
Distribution Networks ◽  
Automatic Feeder

Model-Based Analysis of Transient Behavior of Large Scale CFB Boilers

2003 ◽  
Author(s):  
Ari Kettunen ◽  
Timo Hyppa¨nen ◽  
Ari-Pekka Kirkinen ◽  
Esa Maikkola
Keyword(s):  
Flow Rate ◽  
Large Scale ◽  
Air Flow ◽  
Model Parameters ◽  
Air Flow Rate ◽  
Process Data ◽  
Cfb Boiler ◽  
Flow Rates ◽  
Load Change ◽  
Secondary Air

The main objective of this study was to investigate the load change capability and effect of the individual control variables, such as fuel, primary air and secondary air flow rates, on the dynamics of large-scale CFB boilers. The dynamics of the CFB process were examined by dynamic process tests and by simulation studies. A multi-faceted set of transient process tests were performed at a commercial 235 MWe CFB unit. Fuel reactivity and interaction between gas flow rates, solid concentration profiles and heat transfer were studied by step changes of the following controllable variables: fuel feed rate, primary air flow rate, secondary air flow rate and primary to secondary air flow ratio. Load change performance was tested using two different types of tests: open and closed loop load changes. A tailored dynamic simulator for the CFB boiler was built and fine-tuned by determining the model parameters and by validating the models of each process component against measured process data of the transient test program. The know-how about the boiler dynamics obtained from the model analysis and the developed CFB simulator were utilized in designing the control systems of three new 262 MWe CFB units, which are now under construction. Further, the simulator was applied for the control system development and transient analysis of the supercritical OTU CFB boiler.

scholarly journals Comparison of Three Different Parallel Computation Methods for a Two-Dimensional Dam-Break Model

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Shanghong Zhang ◽  
Wenda Li ◽  
Zhu Jing ◽  
Yujun Yi ◽  
Yong Zhao
Keyword(s):  
Parallel Computation ◽  
Data Exchange ◽  
Large Scale ◽  
Good Choice ◽  
Dam Break ◽  
Two Dimensional ◽  
Parallel Method ◽  
Parallel Methods ◽  
Storage Area ◽  
Speedup Factor

Three parallel methods (OpenMP, MPI, and OpenACC) are evaluated for the computation of a two-dimensional dam-break model using the explicit finite volume method. A dam-break event in the Pangtoupao flood storage area in China is selected as a case study to demonstrate the key technologies for implementing parallel computation. The subsequent acceleration of the methods is also evaluated. The simulation results show that the OpenMP and MPI parallel methods achieve a speedup factor of 9.8× and 5.1×, respectively, on a 32-core computer, whereas the OpenACC parallel method achieves a speedup factor of 20.7× on NVIDIA Tesla K20c graphics card. The results show that if the memory required by the dam-break simulation does not exceed the memory capacity of a single computer, the OpenMP parallel method is a good choice. Moreover, if GPU acceleration is used, the acceleration of the OpenACC parallel method is the best. Finally, the MPI parallel method is suitable for a model that requires little data exchange and large-scale calculation. This study compares the efficiency and methodology of accelerating algorithms for a dam-break model and can also be used as a reference for selecting the best acceleration method for a similar hydrodynamic model.

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