Telecommunications: Making Sense of New Technology and New Legislation. Papers Presented at the 1984 Clinic on Library Applications of Data Processing, April 14-16, 1984. James L. Divilbiss

1988 ◽  
Vol 58 (1) ◽  
pp. 114-114
Keyword(s):  
Data Processing ◽  
New Technology ◽  
Making Sense

scholarly journals DEVELOPMENT OF A HETEROGENIC DISTRIBUTED ENVIRONMENT FOR SPATIAL DATA PROCESSING USING CLOUD TECHNOLOGIES

2016 ◽  
Vol XLI-B4 ◽  
pp. 385-390
Author(s):  
A. S. Garov ◽  
I. P. Karachevtseva ◽  
E. V. Matveev ◽  
A. E. Zubarev ◽  
I. V. Florinsky
Keyword(s):  
Data Processing ◽  
Spatial Data ◽  
3D Visualization ◽  
New Technology ◽  
Main Idea ◽  
Remote Sensing Data ◽  
Data Access ◽  
Working Environment ◽  
Software Environment ◽  
Spatial Data Processing

We are developing a unified distributed communication environment for processing of spatial data which integrates web-, desktop- and mobile platforms and combines volunteer computing model and public cloud possibilities. The main idea is to create a flexible working environment for research groups, which may be scaled according to required data volume and computing power, while keeping infrastructure costs at minimum. It is based upon the "single window" principle, which combines data access via geoportal functionality, processing possibilities and communication between researchers. Using an innovative software environment the recently developed planetary information system (<a href="http://cartsrv.mexlab.ru/geoportal"target="_blank">http://cartsrv.mexlab.ru/geoportal</a>) will be updated. The new system will provide spatial data processing, analysis and 3D-visualization and will be tested based on freely available Earth remote sensing data as well as Solar system planetary images from various missions. Based on this approach it will be possible to organize the research and representation of results on a new technology level, which provides more possibilities for immediate and direct reuse of research materials, including data, algorithms, methodology, and components. The new software environment is targeted at remote scientific teams, and will provide access to existing spatial distributed information for which we suggest implementation of a user interface as an advanced front-end, e.g., for virtual globe system.

TITAN to Google Earth: Workflow for Data Processing for Mobile Terrestrial LIDAR

2017 ◽  
Author(s):  
Michael Martin
Keyword(s):  
Data Processing ◽  
Spatial Information ◽  
New Technology ◽  
Google Earth ◽  
Lidar Data ◽  
Terrestrial Lidar ◽  
Urban Modelling ◽  
Feature Based ◽  
Point Data ◽  
Object Models

Terrestrial LIDAR scanners are pushing the boundaries of accurate urban modelling. Automation and the usability of tools used in feature abstraction and, to a lesser degree, presentation have become the chief concerns with this new technology. To broaden the use and impact of LIDAR in the geomatics, LiDAR datasets must be converted to feature-based representations without loss of precision. One approach, taken here, is to simultaneously examine the overall path that data takes through an organization and the operatordriven tasks carried out on the data as it is transformed from a raw point cloud to final product. We present a review of the current practices in LiDAR data processing and a foundation for future efforts to optimize. We examine alternative LIDAR processing workflows with two key questions in mind: computational efficiency - whether the process can be done using the tools at all - and tool complexity - what operator skill level is needed at each step. Using these workflows the usability of the specific software tools and the required knowledge to effectively carry out the procedures using the tools are examined. Preliminary results have yielded workflows that successfully translate LIDAR to 3D object models, highly decimated point representations of street data represented in Google Earth, and large volume point data flythroughs in ESRI ArcScene. We are documenting the pragmatic limits on each of these workflows and tools for endusers. Terrestrial LIDAR brings with it new innovations for spatial visualizations, but also questions of viability. The technology has proved valuable for specialized applications for experts, but can it be useful as a tool for proliferating 3d spatial information by and to non-experts. This study illustrates the issues associated with preparing 3d LIDAR data for presentation in mainstream visualization environments.

scholarly journals Making sense of a new technology in clinical practice: a qualitative study of patient and physician perspectives

2015 ◽  
Vol 15 (1) ◽  
Author(s):  
Regitze A. S. Pals ◽  
Ulla M. Hansen ◽  
Clea B. Johansen ◽  
Christian S. Hansen ◽  
Marit E. Jørgensen ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Qualitative Study ◽  
New Technology ◽  
Making Sense ◽  
Physician Perspectives

Making sense of neural machine translation

2017 ◽  
Vol 6 (2) ◽  
pp. 291-309 ◽  
Author(s):  
Mikel L. Forcada
Keyword(s):  
Machine Translation ◽  
New Technology ◽  
Statistical Machine Translation ◽  
Software Requirements ◽  
Word Embeddings ◽  
Neural Machine Translation ◽  
Training Time ◽  
Making Sense ◽  
Translation Systems ◽  
New Machine

Abstract The last few years have witnessed a surge in the interest of a new machine translation paradigm: neural machine translation (NMT). Neural machine translation is starting to displace its corpus-based predecessor, statistical machine translation (SMT). In this paper, I introduce NMT, and explain in detail, without the mathematical complexity, how neural machine translation systems work, how they are trained, and their main differences with SMT systems. The paper will try to decipher NMT jargon such as “distributed representations”, “deep learning”, “word embeddings”, “vectors”, “layers”, “weights”, “encoder”, “decoder”, and “attention”, and build upon these concepts, so that individual translators and professionals working for the translation industry as well as students and academics in translation studies can make sense of this new technology and know what to expect from it. Aspects such as how NMT output differs from SMT, and the hardware and software requirements of NMT, both at training time and at run time, on the translation industry, will be discussed.

scholarly journals Pengaruh Kemanfaatan, Kemudahan Penggunaan dan Promosi terhadap Keputusan Penggunaan E-Wallet OVO di Depok

2020 ◽  
Vol 7 (1) ◽  
pp. 54-68
Author(s):  
Wiwik Widiyanti
Keyword(s):  
Data Processing ◽  
Research Method ◽  
Sampling Method ◽  
New Technology ◽  
Linear Analysis ◽  
Ease Of Use ◽  
Online Transactions ◽  
The People ◽  
Convenience Sampling ◽  
Quantitative Descriptive

Abstract  - More online transactions are increasing, causing some new technology in the financial sector, one of which is e-wallet. There are 38 recorded e-wallets in Indonesia that have been licensed by Bank Indonesia, one of which is OVO. As the second most popular e-wallet in Indonesia OVO continues to innovate to increase the use of OVO. This study discusses the great benefits, benefits of using and promoting the decision to use OVO e-wallet by the people in Depok. This research method is quantitative descriptive, with 100 respondents using convenience sampling method. Data processing uses multiple linear analysis. This study produced significant and significant conclusions both partially and simultaneously between the variables of expediency, ease of use and promotion of the decision to use the OVO e-wallet. Keywords : expediency, ease of use, promotion, decision on use, e-wallet

scholarly journals DEVELOPMENT OF A HETEROGENIC DISTRIBUTED ENVIRONMENT FOR SPATIAL DATA PROCESSING USING CLOUD TECHNOLOGIES

2016 ◽  
Vol XLI-B4 ◽  
pp. 385-390 ◽  
Author(s):  
A. S. Garov ◽  
I. P. Karachevtseva ◽  
E. V. Matveev ◽  
A. E. Zubarev ◽  
I. V. Florinsky
Keyword(s):  
Data Processing ◽  
Spatial Data ◽  
3D Visualization ◽  
New Technology ◽  
Main Idea ◽  
Remote Sensing Data ◽  
Data Access ◽  
Working Environment ◽  
Software Environment ◽  
Spatial Data Processing

We are developing a unified distributed communication environment for processing of spatial data which integrates web-, desktop- and mobile platforms and combines volunteer computing model and public cloud possibilities. The main idea is to create a flexible working environment for research groups, which may be scaled according to required data volume and computing power, while keeping infrastructure costs at minimum. It is based upon the "single window" principle, which combines data access via geoportal functionality, processing possibilities and communication between researchers. Using an innovative software environment the recently developed planetary information system (&lt;a href="http://cartsrv.mexlab.ru/geoportal"target="_blank"&gt;http://cartsrv.mexlab.ru/geoportal&lt;/a&gt;) will be updated. The new system will provide spatial data processing, analysis and 3D-visualization and will be tested based on freely available Earth remote sensing data as well as Solar system planetary images from various missions. Based on this approach it will be possible to organize the research and representation of results on a new technology level, which provides more possibilities for immediate and direct reuse of research materials, including data, algorithms, methodology, and components. The new software environment is targeted at remote scientific teams, and will provide access to existing spatial distributed information for which we suggest implementation of a user interface as an advanced front-end, e.g., for virtual globe system.

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