scholarly journals A KNOWLEDGE-BASED METHOD FOR GENERATING SUMMARIES OF SPATIAL MOVEMENT IN GEOGRAPHIC AREAS

2010 ◽  
Vol 19 (04) ◽  
pp. 393-415 ◽  
Author(s):  
MARTIN MOLINA ◽  
AMANDA STENT
Keyword(s):  
Mobile Phones ◽  
Data Streams ◽  
Large Data ◽  
Gps Data ◽  
Knowledge Representations ◽  
Knowledge Based ◽  
Spatial Movement ◽  
Present Evaluation ◽  
Main Components

In this article we describe a method for automatically generating text summaries of data corresponding to traces of spatial movement in geographical areas. The method can help humans to understand large data streams, such as the amounts of GPS data recorded by a variety of sensors in mobile phones, cars, etc. We describe the knowledge representations we designed for our method and the main components of our method for generating the summaries: a discourse planner, an abstraction module and a text generator. We also present evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions.

A proposal to leverage high-quality veterinary diagnostic laboratory large data streams for animal health, public health, and One Health

2021 ◽  
pp. 104063872110030
Author(s):  
Craig N. Carter ◽  
Jacqueline L. Smith
Keyword(s):  
Public Health ◽  
Data Streams ◽  
One Health ◽  
Animal Health ◽  
Disease Outbreaks ◽  
Large Data ◽  
Health Impact ◽  
The United States ◽  
Zoonotic Diseases ◽  
Diagnostic Laboratory

Test data generated by ~60 accredited member laboratories of the American Association of Veterinary Laboratory Diagnosticians (AAVLD) is of exceptional quality. These data are captured by 1 of 13 laboratory information management systems (LIMSs) developed specifically for veterinary diagnostic laboratories (VDLs). Beginning ~2000, the National Animal Health Laboratory Network (NAHLN) developed an electronic messaging system for LIMS to automatically send standardized data streams for 14 select agents to a national repository. This messaging enables the U.S. Department of Agriculture to track and respond to high-consequence animal disease outbreaks such as highly pathogenic avian influenza. Because of the lack of standardized data collection in the LIMSs used at VDLs, there is, to date, no means of summarizing VDL large data streams for multi-state and national animal health studies or for providing near-real-time tracking for hundreds of other important animal diseases in the United States that are detected routinely by VDLs. Further, VDLs are the only state and federal resources that can provide early detection and identification of endemic and emerging zoonotic diseases. Zoonotic diseases are estimated to be responsible for 2.5 billion cases of human illness and 2.7 million deaths worldwide every year. The economic and health impact of the SARS-CoV-2 pandemic is self-evident. We review here the history and progress of data management in VDLs and discuss ways of seizing unexplored opportunities to advance data leveraging to better serve animal health, public health, and One Health.

scholarly journals Survey on Feature Transformation Techniques for Data Streams

2020 ◽  
Author(s):  
Maroua Bahri ◽  
Albert Bifet ◽  
Silviu Maniu ◽  
Heitor Murilo Gomes
Keyword(s):  
Machine Learning ◽  
Data Streams ◽  
Large Data ◽  
High Dimensional ◽  
Feature Transformation ◽  
Transformation Techniques ◽  
Computational Costs ◽  
The Past ◽  
Fundamental Challenge ◽  
Mining Algorithms

Mining high-dimensional data streams poses a fundamental challenge to machine learning as the presence of high numbers of attributes can remarkably degrade any mining task's performance. In the past several years, dimension reduction (DR) approaches have been successfully applied for different purposes (e.g., visualization). Due to their high-computational costs and numerous passes over large data, these approaches pose a hindrance when processing infinite data streams that are potentially high-dimensional. The latter increases the resource-usage of algorithms that could suffer from the curse of dimensionality. To cope with these issues, some techniques for incremental DR have been proposed. In this paper, we provide a survey on reduction approaches designed to handle data streams and highlight the key benefits of using these approaches for stream mining algorithms.

A Grey-DEMATEL approach for implicating e-waste management practice

2018 ◽  
Vol 8 (1) ◽  
pp. 84-99 ◽  
Author(s):  
Atul Kumar Sahu ◽  
Harendra Kumar Narang ◽  
Mridul Singh Rajput
Keyword(s):  
Mobile Phones ◽  
Decision Model ◽  
Management Practice ◽  
Working Environment ◽  
Waste Generation ◽  
Content Type ◽  
Case Research ◽  
Knowledge Based ◽  
The Government ◽  
Smart Mobile

Purpose The use of smart electronic gadgets is proportionately increased during last decades as these gadgets are crafting coziness and relief to the society by making their work easier, effective, etc. These gadgets are the need of today’s working environment for effective planning and work execution. Today, people pertaining to almost every corner of the world are addicted to smart mobile phones, and nowadays, these mobile handsets have become very essential and it is not possible to survive without using them. On the other hand, these smart mobile handsets become inefficient and obsolete over time due to which there is a need to replace the old phones by the new ones, thus creating e-waste. The purpose of this paper is to recognize the significant enablers which are responsible for replacing the existing working mobile phones with the new ones by the end consumers. Design/methodology/approach The Grey-DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach is proposed by the authors to compute the decision results. The present work is supported by the structural modeling equations for supporting sustainability throughout and recognizes the most significant enablers responsible for creating e-waste by replacing the working mobile phones with the new ones. Findings The implication for reducing e-waste using a qualitative approach is presented by easy computation steps for collaborating green issues in the present work. The authors explained numerous enablers, which are responsible for handsets replacement by the consumers. The work can aid the companies as well as the government legislations to identify the significant enablers, drivers, factors, attributes, etc., in moving toward green environmental issue; the generation of e-waste by the obsolete existing working handsets due to non-identification of deficient enablers can be insignificant to the society. Research limitations/implications The implication of developed Grey-DEMATEL techniques is presented by its integration with the application field of e-waste generation by mobile handsets. The authors attempt to devise a conceptual framework linked with knowledge-based theory. The work is illustrated by the case research to understand its applicability and validity in the present scenario. Originality/value The authors attempt to propose a decision model, which will aid in identifying the most significant factorial condition responsible for replacing the existing mobile phones with the new ones by the end consumers. The proposed appraisement module can be used as an investigative tool to build and fabricate a planned environmental progress map for overall business considering environmental domain by the companies.

Research on Semantic Retrieval System for the Document Knowledge Based on Domain Ontology

2011 ◽  
Vol 204-210 ◽  
pp. 2171-2175
Author(s):  
Zi Yu Liu ◽  
Dong Li Zhang ◽  
Xue Hui Li
Keyword(s):  
High Speed ◽  
Retrieval System ◽  
Domain Ontology ◽  
Experimental Results ◽  
Semantic Retrieval ◽  
High Speed Railway ◽  
Knowledge Based ◽  
Main Components ◽  
Railway Domain ◽  
Concept Similarity

Domain ontology can effectively organize the knowledge of that domain and make it easier to share and reuse. We can build domain ontology on thesaurus and thematic words and index document knowledge using domain ontology. Under which this paper designs a semantic retrieval system for the document knowledge based on domain ontology, and the system consists of four main components: ontology query, semantic precomputation for document and the concept similarity, semantic extended search and reasoning search. Finally, this paper makes an experiment on high-speed railway domain. The experimental results show that the developed semantic retrieval system can reach the satisfied recall and precision.

scholarly journals Practical Constraint K-Segment Principal Curve Algorithms for Generating Railway GPS Digital Map

2013 ◽  
Vol 2013 ◽  
pp. 1-11
Author(s):  
Dewang Chen ◽  
Long Chen
Keyword(s):  
Data Storage ◽  
Expert Knowledge ◽  
Low Cost ◽  
Large Data ◽  
Gps Data ◽  
Small Data ◽  
Data Sets ◽  
Digital Map ◽  
Digital Maps ◽  
Practical Algorithms

In order to obtain a decent trade-off between the low-cost, low-accuracy Global Positioning System (GPS) receivers and the requirements of high-precision digital maps for modern railways, using the concept of constraint K-segment principal curves (CKPCS) and the expert knowledge on railways, we propose three practical CKPCS generation algorithms with reduced computational complexity, and thereafter more suitable for engineering applications. The three algorithms are named ALLopt, MPMopt, and DCopt, in which ALLopt exploits global optimization and MPMopt and DCopt apply local optimization with different initial solutions. We compare the three practical algorithms according to their performance on average projection error, stability, and the fitness for simple and complex simulated trajectories with noise data. It is found that ALLopt only works well for simple curves and small data sets. The other two algorithms can work better for complex curves and large data sets. Moreover, MPMopt runs faster than DCopt, but DCopt can work better for some curves with cross points. The three algorithms are also applied in generating GPS digital maps for two railway GPS data sets measured in Qinghai-Tibet Railway (QTR). Similar results like the ones in synthetic data are obtained. Because the trajectory of a railway is relatively simple and straight, we conclude that MPMopt works best according to the comprehensive considerations on the speed of computation and the quality of generated CKPCS. MPMopt can be used to obtain some key points to represent a large amount of GPS data. Hence, it can greatly reduce the data storage requirements and increase the positioning speed for real-time digital map applications.

scholarly journals SPMgr: Dynamic workflow manager for sampling and filtering data streams over Apache Storm

2019 ◽  
Vol 15 (7) ◽  
pp. 155014771986220
Author(s):  
Youngkuk Kim ◽  
Siwoon Son ◽  
Yang-Sae Moon
Keyword(s):  
Data Streams ◽  
Distributed Processing ◽  
Workflow Management ◽  
Large Data ◽  
Integrated System ◽  
Input Processing ◽  
Dynamic Workflow ◽  
Processing Platform ◽  
Apache Storm ◽  
Workflow Manager

In this article, we address dynamic workflow management for sampling and filtering data streams in Apache Storm. As many sensors generate data streams continuously, we often use sampling to choose some representative data or filtering to remove unnecessary data. Apache Storm is a real-time distributed processing platform suitable for handling large data streams. Storm, however, must stop the entire work when it changes the input data structure or processing algorithm as it needs to modify, redistribute, and restart the programs. In addition, for effective data processing, we often use Storm with Kafka and databases, but it is difficult to use these platforms in an integrated manner. In this article, we derive the problems when applying sampling and filtering algorithms to Storm and propose a dynamic workflow management model that solves these problems. First, we present the concept of a plan consisting of input, processing, and output modules of a data stream. Second, we propose Storm Plan Manager, which can operate Storm, Kafka, and database as a single integrated system. Storm Plan Manager is an integrated workflow manager that dynamically controls sampling and filtering of data streams through plans. Third, as a key feature, Storm Plan Manager provides a Web client interface to visually create, execute, and monitor plans. In this article, we show the usefulness of the proposed Storm Plan Manager by presenting its design, implementation, and experimental results in order.

Development of Clusters in Poland

2019 ◽  
Vol 5 (5) ◽  
pp. 15-25
Author(s):  
Lilla Knop
Keyword(s):  
Development Project ◽  
Organizational Relationships ◽  
Knowledge Based ◽  
Management Standards ◽  
Knowledge Based Economy ◽  
Study Results ◽  
Main Components ◽  
Project Data

The current study results attribute great importance to the role of clusters in innovation and competitive development creation. While seeking not so much the operational solutions, but the main components that form the cluster management process, it was noticed that a cluster – despite being already well- defined— does not come into being together with the declaration, willingness, initiative or the signing of the document. The creation and development of clusters is a long term process that can last for years and is exposed to a number of strategic obstacles. The experience both on a national and global level relating to the dynamics of the development of clusters show how difficult this task is, especially in a knowledge-based economy. The development of specialization and knowledge in clusters is no longer linear in nature, based on knowledge generated by the function of research and development of an individual company. It is defined as the result of a process of interaction through inter-organizational relationships, providing access to various types of resources. The article assumes that clusters in Poland after the quantum boom, are moving to the next phase of development based on improvement of activities. The aim of the article is to present the dynamics of cluster development in Poland. The research was done in 2015-2017, but the research period covered the years 2003-2016. Besides basic information on: number of clusters, year of creation, number of cluster members etc., the article analyzes cluster specializations against the background of smart specializations being developed in regions in Poland. Furthermore, the article presents the preliminary results of research on meeting management standards by Polish clusters. The research was based on PARP (The Polish Agency for Enterprise Development) project data and own studies.

scholarly journals Time-evolving O-D matrix estimation using high-speed GPS data streams

2016 ◽  
Vol 44 ◽  
pp. 275-288 ◽  
Author(s):  
Luís Moreira-Matias ◽  
João Gama ◽  
Michel Ferreira ◽  
João Mendes-Moreira ◽  
Luis Damas
Keyword(s):  
Data Streams ◽  
High Speed ◽  
Gps Data ◽  
Matrix Estimation
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