Example of Visualization in Engineering format
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Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format Example of Visualization in Engineering format
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open access Open Access e-ISSN: 22137459
recommended Recommended

Visualization in Engineering — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Engineering (miscellaneous) #3 of 77 up up by 13 ranks
Modeling and Simulation #10 of 290 up up by 70 ranks
Computer Science Applications #64 of 693 up up by 164 ranks
Computer Graphics and Computer-Aided Design #9 of 88 up up by 18 ranks
Computer Vision and Pattern Recognition #14 of 85 up up by 17 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 30 Published Papers | 259 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 03/06/2020
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FAQ

Journal Performance & Insights

  • CiteRatio
  • SJR
  • SNIP

CiteRatio is a measure of average citations received per peer-reviewed paper published in the journal.

8.6

3% from 2019

CiteRatio for Visualization in Engineering from 2016 - 2020
Year Value
2020 8.6
2019 8.9
2018 4.9
2017 2.8
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has decreased by 3% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR) measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

0.53

28% from 2019

SJR for Visualization in Engineering from 2018 - 2020
Year Value
2020 0.53
2019 0.739
2018 0.537
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 28% in last years.
  • This journal’s SJR is in the top 10 percentile category.

Source Normalized Impact per Paper (SNIP) measures actual citations received relative to citations expected for the journal's category.

2.363

19% from 2019

SNIP for Visualization in Engineering from 2017 - 2020
Year Value
2020 2.363
2019 1.982
2018 1.423
2017 1.059
graph view Graph view
table view Table view

insights Insights

  • SNIP of this journal has increased by 19% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Related Journals

open access Open Access ISSN: 18616410 e-ISSN: 18616429
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CiteRatio: 5.3 | SJR: 0.701 | SNIP: 1.408
open access Open Access ISSN: 1676393
recommended Recommended

Elsevier

CiteRatio: 4.8 | SJR: 0.459 | SNIP: 1.587
open access Open Access ISSN: 13875868

Taylor and Francis

CiteRatio: 5.2 | SJR: 0.519 | SNIP: 1.627
open access Open Access e-ISSN: 22137467

Springer

CiteRatio: 2.6 | SJR: 1.01 | SNIP: 0.941

Visualization in Engineering

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Springer

Visualization in Engineering

Approved by publishing and review experts on SciSpace, this template is built as per for Visualization in Engineering formatting guidelines as mentioned in Springer author instructions. The current version was created on 02 Jun 2020 and has been used by 577 authors to write and format their manuscripts to this journal.

Engineering design

i
Last updated on
02 Jun 2020
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ISSN
2213-7459
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
i
Bibliography Name
SPBASIC
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Citation Type
Author Year
(Blonder et al, 1982)
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Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1186/S40327-015-0029-Z
Visual monitoring of civil infrastructure systems via camera-equipped Unmanned Aerial Vehicles (UAVs): a review of related works
Youngjib Ham1, Kevin Han2, Jacob J. Lin2, Mani Golparvar-Fard2

Abstract:

Over the past few years, the application of camera-equipped Unmanned Aerial Vehicles (UAVs) for visually monitoring construction and operation of buildings, bridges, and other types of civil infrastructure systems has exponentially grown. These platforms can frequently survey construction sites, monitor work-in-progress, crea... Over the past few years, the application of camera-equipped Unmanned Aerial Vehicles (UAVs) for visually monitoring construction and operation of buildings, bridges, and other types of civil infrastructure systems has exponentially grown. These platforms can frequently survey construction sites, monitor work-in-progress, create documents for safety, and inspect existing structures, particularly for hard-to-reach areas. The purpose of this paper is to provide a concise review of the most recent methods that streamline collection, analysis, visualization, and communication of the visual data captured from these platforms, with and without using Building Information Models (BIM) as a priori information. Specifically, the most relevant works from Civil Engineering, Computer Vision, and Robotics communities are presented and compared in terms of their potential to lead to automatic construction monitoring and civil infrastructure condition assessment. read more read less
View PDF
275 Citations
open accessOpen access Journal Article DOI: 10.1186/S40327-015-0031-5
Low-cost virtual reality environment for engineering and construction
Thomas Hilfert1, Markus König1

Abstract:

Presenting significant building or engineering 3D-models is a crucial part of the planning, construction and maintenance phases in terms of collaboration and understanding. Especially in complex or large-scale models, immersion is one of the major key factors for being able to intuitively perceive all aspects of the scene. A ... Presenting significant building or engineering 3D-models is a crucial part of the planning, construction and maintenance phases in terms of collaboration and understanding. Especially in complex or large-scale models, immersion is one of the major key factors for being able to intuitively perceive all aspects of the scene. A fully immersive system needs to give the user a large field-of-view with reduced latency for lifelike impression. Technologies such as VRwalls and shutter glasses can deliver high refresh rates, yet fail to give a large field-of-view. Head-mounted-devices for virtual reality fill this gap. Head tracking mechanisms translate movements of the user’s head into virtual camera movements and enable a natural way of examining models. Unlike a stereoscopic representation with projectors, point-of-view tracking can be achieved separately for each individual user. Hardware costs for such systems were very high in the past, but have dropped due to virtual reality systems now gaining traction in the mainstream gaming community. In this paper we present a way to build a low-cost, highly immersive virtual reality environment for engineering and construction applications. Furthermore, we present a method to simplify and partly automate the process of reusing digital building models, which are already used in construction, to create virtual scenes, instead of having to do parallel content creation for visualization. Using the Oculus Rift head-mounted display and the Leap Motion hand-tracking device, we show the possibilities of naturally interacting within a virtual space in different use cases. The software, based on the popular game engine Unreal Engine 4, will be used as a basis for further research and development. Building Information Modeling data can be imported to UE4 with our presented plugin. Using an automated database for mapping materials to the geometry simplifies the process of importing Building Information Modeling entities. The refresh rate of the system stays within acceptable margins needed for virtual reality applications using head-mounted devices. Head-mounted devices present a great potential for the Architecture, Engineering and Construction industry, as a person can experience realistic first-person situations without having to care about injuries. Automated processes for the simplification of content creation, leveraging existing models, and the usage of visual programming languages enable even nonprogrammers to create scenarios to their needs. read more read less

Topics:

Virtual reality (58%)58% related to the paper, Building information modeling (53%)53% related to the paper, Immersion (virtual reality) (53%)53% related to the paper, Use case (52%)52% related to the paper, Content creation (52%)52% related to the paper
View PDF
132 Citations
open accessOpen access Journal Article DOI: 10.1186/S40327-018-0064-7
Machine learning for estimation of building energy consumption and performance: a review
Saleh Seyedzadeh1, Farzad Pour Rahimian2, Ivan Glesk1, Marc Roper1

Abstract:

Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy efficiency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption... Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy efficiency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most effective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy efficiency at a very early design stage. On the other hand,efficient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, artificial intelligence (AI) in general and machine learning (ML) techniques in specific terms have been proposed for forecasting of building energy consumption and performance. This paper provides a substantial review on the four main ML approaches including artificial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance. read more read less

Topics:

Energy consumption (69%)69% related to the paper, Efficient energy use (65%)65% related to the paper, Population (52%)52% related to the paper
View PDF
117 Citations
open accessOpen access Journal Article DOI: 10.1186/2213-7459-1-3
High-precision vision-based mobile augmented reality system for context-aware architectural, engineering, construction and facility management (AEC/FM) applications
Hyojoon Bae1, Mani Golparvar-Fard2, Jules White3

Abstract:

Many context-aware techniques have been proposed to deliver cyber-information, such as project specifications or drawings, to on-site users by intelligently interpreting their environment. However, these techniques primarily rely on RF-based location tracking technologies (e.g., GPS or WLAN), which typically do not provide su... Many context-aware techniques have been proposed to deliver cyber-information, such as project specifications or drawings, to on-site users by intelligently interpreting their environment. However, these techniques primarily rely on RF-based location tracking technologies (e.g., GPS or WLAN), which typically do not provide sufficient precision in congested construction sites or require additional hardware and custom mobile devices. This paper presents a new vision-based mobile augmented reality system that allows field personnel to query and access 3D cyber-information on-site by using photographs taken from standard mobile devices. The system does not require any location tracking modules, external hardware attachments, and/or optical fiducial markers for localizing a user’s position. Rather, the user’s location and orientation are purely derived by comparing images from the user’s mobile device to a 3D point cloud model generated from a set of pre-collected site photographs. The experimental results show that 1) the underlying 3D reconstruction module of the system generates complete 3D point cloud models of target scene, and is up to 35 times faster than other state-of-the-art Structure-from-Motion (SfM) algorithms, 2) the localization time takes at most few seconds in actual construction site. The localization speed and empirical accuracy of the system provides the ability to use the system on real-world construction sites. Using an actual construction case study, the perceived benefits and limitations of the proposed method for on-site context-aware applications are discussed in detail. read more read less

Topics:

Augmented reality (59%)59% related to the paper, Mobile device (55%)55% related to the paper, Point cloud (51%)51% related to the paper, Global Positioning System (50%)50% related to the paper
View PDF
115 Citations
open accessOpen access Journal Article DOI: 10.1186/2213-7459-1-9
Review and analysis of augmented reality literature for construction industry
Sara Rankohi1, Lloyd M. Waugh1

Abstract:

Research has identified various beneficial capabilities for augmented reality technologies in the AEC industry such as virtual site visits, comparing as-built and as-planned status of projects, pre-empting schedule disputes, enhancing collaboration opportunities, and planning/training for similar projects. This paper provides... Research has identified various beneficial capabilities for augmented reality technologies in the AEC industry such as virtual site visits, comparing as-built and as-planned status of projects, pre-empting schedule disputes, enhancing collaboration opportunities, and planning/training for similar projects. This paper provides an expanded foundation for future research by presenting a statistical review of augmented reality technology in the AEC industry. The review is based on articles found within eight well-known journals in architecture, engineering, construction, and facility management (AEC/FM) until the end of the year 2012. The review further narrows the literature within these journals by considering only those 133 articles found through a key word search for “augmented reality.” The selected journal articles are classified within the following dimensions: improvement focus, industry sector, target audience, project phase, stage of technology maturity, application area, comparison role, and technology. The number of articles within these dimensions are used to identify maturing and emerging trends in the literature as well as to synthesize the current state-of-the-art of augmented reality research in the AEC industry. In summary, the AR literature has increasingly focused on the demonstration of visualization and simulation applications for comparison of as-planned versus as-built statuses of the project during the construction phase to monitor project progress and address issues faced by field workers. In addition, the future trend is toward using web-based mobile augmented systems for field construction monitoring. read more read less

Topics:

Augmented reality (58%)58% related to the paper, Construction management (56%)56% related to the paper, Word search (53%)53% related to the paper, Target audience (50%)50% related to the paper
View PDF
97 Citations
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Visualization in Engineering format uses SPBASIC citation style.

Automatically format and order your citations and bibliography in a click.

SciSpace allows imports from all reference managers like Mendeley, Zotero, Endnote, Google Scholar etc.

Frequently asked questions

Absolutely not! With our tool, you can freely write without having to focus on LaTeX. You can write your entire paper as per the Visualization in Engineering guidelines and autoformat it.

Yes. The template is fully compliant as per the guidelines of this journal. Our experts at SciSpace ensure that. Also, if there's any update in the journal format guidelines, we take care of it and include that in our algorithm.

Sure. We support all the top citation styles like APA style, MLA style, Vancouver style, Harvard style, Chicago style, etc. For example, in case of this journal, when you write your paper and hit autoformat, it will automatically update your article as per the Visualization in Engineering citation style.

You can avail our Free Trial for 7 days. I'm sure you'll find our features very helpful. Plus, it's quite inexpensive.

Yup. You can choose the right template, copy-paste the contents from the word doc and click on auto-format. You'll have a publish-ready paper that you can download at the end.

A matter of seconds. Besides that, our intuitive editor saves a load of your time in writing and formating your manuscript.

One little Google search can get you the Word template for any journal. However, why do you need a Word template when you can write your entire manuscript on SciSpace, autoformat it as per Visualization in Engineering's guidelines and download the same in Word, PDF and LaTeX formats? Try us out!.

Absolutely! You can do it using our intuitive editor. It's very easy. If you need help, you can always contact our support team.

SciSpace is an online tool for now. We'll soon release a desktop version. You can also request (or upvote) any feature that you think might be helpful for you and the research community in the feature request section once you sign-up with us.

Sure. You can request any template and we'll have it up and running within a matter of 3 working days. You can find the request box in the Journal Gallery on the right sidebar under the heading, "Couldn't find the format you were looking for?".

After you have written and autoformatted your paper, you can download it in multiple formats, viz., PDF, Docx and LaTeX.

To be honest, the answer is NO. The impact factor is one of the many elements that determine the quality of a journal. Few of those factors the review board, rejection rates, frequency of inclusion in indexes, Eigenfactor, etc. You must assess all the factors and then take the final call.

SHERPA/RoMEO Database

We have extracted this data from Sherpa Romeo to help our researchers understand the access level of this journal. The following table indicates the level of access a journal has as per Sherpa Romeo Archiving Policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

The 5 most common citation types in order of usage are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
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After uploading your paper on SciSpace, you would see a button to request a journal submission service for Visualization in Engineering.

Each submission service is completed within 4 - 5 working days.

Yes. SciSpace provides this functionality.

After signing up, you would need to import your existing references from Word or .bib file.

SciSpace would allow download of your references in Visualization in Engineering Endnote style, according to springer guidelines.

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