All posts by VPInstitute

Future of sustainable military operations under emerging energy and security considerations

Research Examples, Strategic planning

Highlights
• The nature of warfare is changing thus the requirement for energy.
• Energy is a key component of sustainable operations.
• Energy trends are analyzed in three stages including generation, transfer and storage through technology mining.
• Scenarios are developed based on the future characteristics of warfare and emerging energy needs of military operations.
• Stages of military energy transformation are described and strategies for military energy are formulated.

Abstract

Due to limited energy sources and growing concerns about environment, secure, safe and sustainable energy has become one of the Grand Challenges at the global level. Likewise in many other aspects of life, energy is crucial for military forces. In parallel to the changing nature of warfare, the need for energy in military operations has increased dramatically. While energy consumption in the World War II was 1 gal per soldier per day, it was 4 gal per soldier per day during the Desert Storm operation in 1991. Not only the quantity, but also the type of energy required for military operations has changed dramatically. Shifts have been observed from individual man power to machines powered by fuel and electricity. Energy demand and type have changed further through the introduction of more sophisticated devices with new capabilities such as to enable night vision, designate targets with lasers, provide advanced sensing and communication capabilities and reduce human involvement in operations through drones and robotic technologies. Investigating the trends in changing nature of warfare and energy through review, technology mining and scientometrics, the present study develops future scenarios, and a strategic roadmap to identify priority technology areas and strategies for the future military energy R&D.

Author(s): Ozcan Saritas, Serhat Burmaoglu
Organization(s): Higher School of Economics (HSE)
Source: TF&SC
http://www.sciencedirect.com/science/article/pii/S0040162515002577
Year: 2015

Technology Early Warning Model: A New Approach Based on Patent Data

CTI, Future-oriented technology analysis, Research Examples, Research Type, Strategic planning

With the development of technology, more and more technical issues have been exposed, such as technical disputes, technical barriers and technical crisis. Thus, it is necessary to warn enterprises about technical deviation and predict future technology crises. Patent data can contain much information about technologies and would be useful in this setting. This paper proposes a technology early warning model based on patent data. This model helps enterprises analyse the technical crisis level and trends from four different perspectives (technical stability, technical monopoly, technical security and technical prospects).

http://ceur-ws.org/Vol-1437/ipamin2015_paper4.pdf

Author(s): Ganlu Sun, Ying Guo, Fan Yang
Organization(s): Beijing Institute of Technology
Source: Proceedings of the Second International Workshop on Patent Mining and
its Applications (IPAMIN)
Year: 2015

Technological Prospection on Nanotechnologies Applied to the Petroleum Industry

Patents, Research Examples, Research profiling, Research Type

This paper presents a technological prospection on nanotechnologies applied to the petroleum industry through the creation of a worldwide overview regarding scientific paper publications and patents concerning that business, with the purpose of identifying the main trends on research and development (R&D), the annual evolution, as well as the key agents and countries involved. In this research, it was possible to verify the presence of services oil companies, like Baker, Schlumberger and Halliburton. In scientific paper publications, it was possible to observe university departments, related to petroleum studies, from different countries, as Thailand, China, USA, Iran.

Author(s): M.A. Parreiras, Viviane; M. de S. Antunes, Adelaide
Source: Recent Patents on Nanotechnology http://www.ingentaconnect.com/content/ben/nanotec/2015/00000009/00000002/art00006
Year: 2015

Scientometric cognitive and evaluation on smart city related construction and building journals data

Citation analysis, Research evaluation, Research Examples, Research Type

In this paper, scientometrics cognitive and knowledge visualization technology were used to evaluate global scientific production and development trends in construction and building technology research of smart cities. All the data was collected from the Science Citation Index-Expanded (SCIE) database and Journal Citation Reports (JCR). The published papers from the subject of construction and building technology and their journals, authors, countries and keywords spanning over several aspects of research topics, proved that architecture/building research grew rapidly over the past 30 years, and the trend still continues in recent smart cities era. The purposed of this study were to identify the journals in the field of construction and building technology in smart city, make a comparative report on related researches, as well as propose a quality evaluation of those journals. Based on JCR and SCI paper data, the journals related to construction and building technology in smart city were assessed using ten metrics: languages, active degree, references, citation trends, main countries, leading institutes, cooperation trends, productive authors, author keywords and keywords plus. The results indicate that all the factors have great significance and are related to the impact of a journal. It also provides guidance to both evaluators and the study groups which assess journals during the process of judging or selecting research outlets, and future perspective on how to improve the impact of a paper or a journal.

Author(s): Liang-xing Su, Peng-hui Lyu , Zheng Yang, Shuai Ding, Kai-le Zhou
Organization(s): Wuhan University; Hefei University of Technology
Source: Scientometrics http://link.springer.com/article/10.1007/s11192-015-1697-0
Year: 2015

Meta Data: Big Data Research Evolving across Disciplines, Players, and Topics

Research profiling, Research Type

We present a meta-analysis of BigData research activity since 2009. Our purpose here is to present “tech mining” (bibliometric and text analyses of research publication abstract record sets) to provide a research landscape of who is doing what, where, and when. Our larger purpose is to help Forecast Innovation Pathways for big data & analytics over the coming decade. We download 7006 research publication abstracts from Web of Science resulting from a search algorithm devised to recall a high percentage of core BigData research and a moderate percentage of peripherally related research (fair recall). We find interesting engagement of different disciplines in Big Data over time. On a national level, the USA and China dominate these fundamental research publications to a striking degree. Mapping topics presents interesting evidence on what topics are emerging in this dynamic field.

Author(s): Porter, A.L. ; Ying Huang ; Schuehle, J. ; Youtie, J.
Organization(s): Georgia Institute of Technology
Source: 4th IEEE International Congress on Big Data (BigData Congress)
http://www.researchgate.net/publication/280529689_MetaData_BigData_Research_Evolving_Across_Disciplines_Players_and_Topics
Year: 2015

Nanotechnology Research in Post-Soviet Russia: Science System Path-Dependencies and their Influences

Research Examples, Research profiling, Research Type,

This paper contributes to the analysis of Russian research dynamics and output in nanotechnology. The paper presents an analysis of Russian nanotechnology research outputs during the period of 1990-2012. By examining general outputs, publication paths and collaboration patterns, the paper identifies a series of quantified factors that help to explain Russia’s limited success in leveraging its ambitious national nanotechnology initiative. Attention is given to path-dependent institutionalised practices, such as established publication pathways that are dominated by the Academy of Sciences, the high centralisation of the entire research system, and issues of internal collaborations of actors within the domestic research system.

Author(s): Maria Karaulova, Oliver Shackleton, Abdullah Gök, and Philip Shapira
Organization(s): Manchester Institute of Innovation Research, University of Manchester
Source: Proceeding of 15th International Conference on Scientometrics and Infometrics
http://www.issi2015.org/files/downloads/all-papers/0755.pdf
Year: 2015

Graphene Research and Enterprise: Mapping Innovation and Business Growth in a Strategic Emerging Technology

CTI, novel source, Research Examples, Research Type, Science mapping, ST&I indicators

This paper presents the results of research to develop new data sources and methods that can be combined with existing information for real-time intelligence to understand and map enterprise development and commercialisation in a rapidly emerging and growing new technology. As a demonstration case, the study examines enterprise development and commercialisation strategies in graphene, focusing on a set of 65 graphenebased small and medium-sized enterprises located in 16 different countries. We draw on available secondary sources and bibliometric methods to profile developments in graphene. We then use computerised data mining methods and analytical techniques, including cluster and regression modelling, to identify patterns from publicly available online information on enterprise web sites. We identify groups of graphene small and medium-sized enterprises differentiated by how they became involved with graphene, the materials they target, whether they make equipment, and their orientation towards science and intellectual property. In general, access to finance and the firms’ location are significant factors that are associated with graphene product introductions. We also find that patents and scientific publications are not statistically significant predictors of product development in our sample of graphene SMEs. We show that the UK has a cohort of graphene-oriented SMEs that is signalling plans to develop intermediate graphene products that should have higher value in the marketplace. Our findings suggest that UK policy needs to ensure attention to the introduction and scale-up of downstream intermediate and final graphene products and associated financial, intermediary, and market identification support.

Author(s): Philip Shapira, Abdullah Gök, and Fatemeh Salehi Yazdi
Organization(s): Manchester Institute of Innovation Research, University of Manchester
Source: Nesta Working Paper Series
http://www.nesta.org.uk/publications/graphene-research-and-enterprise-mapping-innovation-and-business-growth-strategic-emerging-technology
Year: 2015

A Technology Foresight Model: Used for Foreseeing Impelling Technology in Life Science

Future-oriented technology analysis, Research Examples, Research Type

This paper constructs an Impelling Technology Foresight Model (ITFM) for foreseeing impelling technology in the field of life science, which is a comprehensive model consisting of four class indicators: international scientific environment, evolving of papers and patents, collaboration features of patent assignees’ collaboration networks, and impacts. A case study was carried out in the field of life science. Recombinant DNA (RbDNA) and Monoclonal Antibody (mAb) were selected as impelling technologies to carry out the case study. ELISA Diagnosis (ELISA) and Fermentation Technology (FT) were defined as non-impelling technologies to be control group. Results revealed that impelling technologies have higher evolving rates from the stage of growth to maturity. Significant policies or programs usually boost the rapid progress of impelling technologies. Impelling
technologies have much higher impact than non-impelling ones. Collaboration behaviour is much more broad and general for impelling technologies. To our knowledge, this is the first study carried out to date to foreseeing impelling technologies at this way.

Author(s): Yunwei Chen, Yong Deng, Fang Chen, Chenjun Ding, Ying Zheng and Shu Fang
Organization: Chengdu Library of the Chinese Academy of Sciences
Source: Proceeding of 15th International Conference on Scientometrics and Infometrics
http://www.issi2015.org/files/downloads/all-papers/0920.pdf
Year: 2015

Do Nobel Laureates Create Prize-Winning Networks? An Analysis of Collaborative Research in Physiology or Medicine

Network analysis, Research Examples, S&T lit

Nobel Laureates in Physiology or Medicine who received the Prize between 1969 and 2011 are compared to a matched group of scientists to examine productivity, impact, coauthorship and international collaboration patterns embedded within research networks. After matching for research domain, h-index, and year of first of publication, we compare bibliometric statistics and network measures. We find that the Laureates produce fewer papers but with higher average citations. The Laureates also produce more sole-authored papers both before and after winning the Prize. The Laureates have a lower number of coauthors across their entire careers than the matched group, but are equally collaborative on average. Further, we find no differences in international collaboration patterns. The Laureates coauthor network reveals significant differences from the non-Laureate network. Laureates are more likely to build bridges across a network when measuring by average degree, density, modularity, and communities. Both the Laureate and non-Laureate networks have “small world” properties, but the Laureates appear to exploit “structural holes” by reaching across the network in a brokerage style that may add social capital to the network. The dynamic may be making the network itself highly attractive and selective. These findings suggest new insights into the role “star scientists” in social networks and the production of scientific discoveries.

Author(s): Caroline S. Wagner , Edwin Horlings, Travis A. Whetsell, Pauline Mattsson, and Katarina Nordqvist
Organization(s): Battelle Center for Science and Technology Policy, Ohio State University; Rathenau Institute
Source: PLoS One http://www.plosone.org/article/Authors/info:doi/10.1371/journal.pone.0134164
Year: 2015

ClusterSuite – term-clumping macro toolset

VP Macros

NOTE: The macro below will work for VantagePoint version 9 or earlier because of changes mandated by Chromium. For those with VantagePoint or VP Student Edition version 12 or later, use the “Refine NLP” function included with the software, it provides similar functionality. 

ClusterSuite is a macro which runs a series of thesauri, macros, and other term-cleaning and clustering programs to perform dimension reduction on a list, making it more approachable and manageable. It intends to minimize noise and maximize prominent topics, which enables the user to more quickly extract meaning from large amounts of text. More specifically, term clumping macros indicate (i) how closely related two or more terms are, (ii) a good name for a group that includes common terms, and (iii) the nature of the relationship between terms (e.g. parent-child, siblings, etc).

At present, ClusterSuite organizes its parts into three phases. Phase I executes five thesauri. Phase II iteratively runs a fuzzy list cleaning macro following a removal of extremely common or uncommon items. Phase III is designed to run a basic clustering macro after again removing extremely uncommon items. After the completion of these three steps, the user has the option to run an additional program to perform more advanced clustering.

1. Copy the ClusterSuite’ folder
to C:\Program Files (x86)\VantagePoint

2. Copy ‘general-85cutoff-95fuzzywordmatch-1 exact.fuz’  to C:\Program Files (x86)\VantagePoint\Fuzzy

3. Copy ‘ClusterSuite.vpm’ to C:\Program Files (x86)\VantagePoint\Macros

4. Open a VantagePoint file and run ClusterSuite.vpm (from C:\Program Files (x86)\VantagePoint\Macros)

ClusterSuite Tutorial PowerPoint

To watch an instructional video, goto VP Resources>VP How-To>Advanced Analytics
ClusterSuite Tutorial Video

Rough Guide to Dataflow in ClusterSuite

1)ClusterSuite.vpm calls the Tutorial.html (poorly named, I know) window
2)ClusterSuite runs a while loop that waits for Tutorial.html to send a window.status back to VantagePoint
3)Tutorial.html has multiple checkboxes each with their own ID.
4)When a button, such as “About ClusterSuite” or “Start” is presses, Tutorial.html updates the window.status. If “About ClusterSuite” is selected, the while loop continues to run while ClusterSuite launches another window. If “Start” is pressed, the while loop is stopped and ClusterSuite is told to record every checkbox ID with that is marked as checked. Additionally, the numbers from the Remove Extremes boxes are stored in an array.
5)The id of every checked box is stored in a giant array.
6)A for loop reads through each item in this array and executes the items in order. This prevents unchecked items from being executed.
7)Each component is executed in its own function, and the checklist is updated along the way.
8)At the end of this, the user is given the option of running TermCluster. If the user selects yes, a Term-Document matrix is created in ClusterSuite. This is then converted to Excel with a combination of a .vpm and .xlsm Matrix_to_columns macro.
9)Next, a  combination of runTermCluster.bat and .xlsm launch termCluster.jar.
10)TermCluster imports Excel, uses MySQL to store and manipulate it, and exports back to Excel

In order to use TermCluster, you first must install and configure MySQL, a free database from http://www.mysql.com/. Click here for a tutorial:
MySQL-Setup

Additional resources:
TermCluster data flow
Acronym_Eliminator_Instructions