Semantic Academic Profiler (SAP): a framework for researcher assessment based on semantic topic modeling

Recent efforts have focused on identifying multidisciplinary teams and detecting co-Authorship Networks based on exploring topic modeling to identify researchers’ expertise. Though promising, none of these efforts perform a real-life evaluation of the quality of the built topics. This paper proposes a Semantic Academic Profiler (SAP) framework that allows summarizing articles written by researchers to automatically build research profiles and perform online evaluations regarding these built profiles. SAP exploits and extends state-of-the-art Topic Modeling strategies based on Cluwords considering n-grams and introduces a new visual interface able to highlight the main topics related to articles, researchers and institutions. To evaluate SAP’s capability of summarizing the profile of such entities as well as its usefulness for supporting online assessments of the topics’ quality, we perform and contrast two types of evaluation, considering an extensive repository of Brazilian curricula vitae: (1) an offline evaluation, in which we exploit a traditional metric (NPMI) to measure the quality of several data representations strategies including (i) TFIDF, (ii) TFIDF with Bi-grams, (iii) Cluwords, and (iv) CluWords with Bi-grams; and (2) an online evaluation through an A/B test where researchers evaluate their own built profiles. We also perform an online assessment of SAP user interface through a usability test following the SUS methodology. Our experiments indicate that the CluWords with Bi-grams is the best solution and the SAP interface is very useful. We also observed essential differences in the online and offline assessments, indicating that using both together is very important for a comprehensive quality evaluation. Such type of study is scarce in the literature and our findings open space for new lines of investigation in the Topic Modeling area.

     

Research subjects and hot topics of foil bearings performance in recent twenty years: analysis and prediction

As one kind of gas bearings, foil bearings that are commonly made of one top foil and at least one bottom foil, have many attractive advantages such as low power loss, wide work temperature range, high rotating speed, low maintenance cost, simple system construct, etc. Nevertheless, foil bearings also have some disadvantages including low carrying load at low speed, wear at start-stop procedure, not easy to predict bearing performance due to the complex bearing structure and so on.

For the sake of better understanding and further utilization of foil bearings, many researchers, institutions and countries have paid great attention to study these special rolling elements in recent decades. The purpose of this paper is to explore the research status of foil bearings performance based on the Web of Science datasets and related tools, meanwhile, the cooperative relationship among individuals or organizations is further studied. Moreover, to figure out influential countries, institutions and authors, the analysis of cited frequency is adopted. In addition, keywords frequency analysis and co-occurrence analysis are applied to explore the future trend of foil bearing. The results identify influential countries, institutions and authors in the research of foil bearings performance and show that whether in quantity or in quality, research of foil bearings performance in developed countries holds a significant lead over that in developing countries. Moreover, the current hot topics are figured out as well as future direction of development is predicted. This study presents intuitive state of research of foil bearings performance and proposes a fresh perspective for relevant researchers to perform foil bearings research in the future.

     

A tutorial survey of topics in wireless networking: Part I

In this two part paper, we provide a survey of recent and emerging topics in wireless networking. We view the area of wireless networking as dealing with problems of resource allocation so that the various connections that utilise the network achieve their desired performance objectives. In the first part of the paper, we first survey the area by providing a taxonomy of wireless networks as they have been deployed. Then, we provide a quick tutorial on the main issues in the wireless ‘physical’ layer, which is concerned with transporting bits over the radio frequency spectrum. Then, we proceed to discuss some resource allocation formulations in CDMA(code division multiple access) cellular networks and OFDMA(orthogonal frequency division multiple access) networks. In the second part of the paper, we first analyse random access wireless networks and pay special attention to 802·11 (Wi-Fi) networks.We then survey some topics in ad hoc multihop wireless networks, where we discuss arbitrary networks, as well as some theory of dense random networks. Finally, we provide an overview of the technical issues in the emerging area of wireless sensor networks.     

Identity and publication in non-university settings: academic co-authorship and collaboration

Increased collaboration between researchers working in university, industry, and governmental settings is changing the landscape of academic science. Traditional models of the interaction between these sectors, such as the triple helix concept, draw clear distinctions between academic and non-academic settings and actors. This study surveyed scientists (n = 469) working outside of university settings who published articles indexed in the Web of Science about their modes of collaboration, perceptions about publishing, workplace characteristics, and information sources. We study the association between these variables, and use text analysis to examine the roles, duties, sites, topics, and workplace missions among non-university based authors. Our analysis shows that 72% of authors working in non-university settings who collaborate and publish with other scientists self-identify as academics. Furthermore, their work life resembles that of those working in university settings in that the majority report doing fundamental research in government research organizations and laboratories. Contrary to our initial hypothesis, this research suggests that peer-reviewed publications are much more dominated by non-university academics than we previously thought and that collaboration as co-authors on academic publications is not likely to be a primary conduit for the transfer of scientific knowledge between academe and industry.

     

Gain in single and paired parametric oscillators

ABSTRACT

The new concept of Quantum Amplification by Superradiant Emission of Radiation for generating high-frequency coherent light has produced several open questions, and one of the most important is how to determine the gain in two coupled oscillators with a parametric amplifier. In this article, we analytically derive the equation for the gain expression and state sufficient conditions to obtain gain. We also draw connections to single oscillator topics, including the Mathieu equation and the Kronig–Penney model.     

Generating process of emerging topics in the life sciences

Scientometrics - Clarifying the mechanism of how emerging topics in science and technology research fields are generated is useful for both researchers and agencies to identify potential emerging...     

Identification of important citations by exploiting research articles’ metadata and cue-terms from content

Citations play a pivotal role in indicating various aspects of scientific literature. Quantitative citation analysis approaches have been used over the decades to measure the impact factor of journals, to rank researchers or institutions, to discover evolving research topics etc. Researchers doubted the pure quantitative citation analysis approaches and argued that all citations are not equally important; citation reasons must be considered while counting. In the recent past, researchers have focused on identifying important citation reasons by classifying them into important and non-important classes rather than individually classifying each reason. Most of contemporary citation classification techniques either rely on full content of articles, or they are dominated by content based features. However, most of the time content is not freely available as various journal publishers do not provide open access to articles. This paper presents a binary citation classification scheme, which is dominated by metadata based parameters. The study demonstrates the significance of metadata and content based parameters in varying scenarios. The experiments are performed on two annotated data sets, which are evaluated by employing SVM, KLR, Random Forest machine learning classifiers. The results are compared with the contemporary study that has performed similar classification employing rich list of content-based features. The results of comparisons revealed that the proposed model has attained improved value of precision (i.e., 0.68) just by relying on freely available metadata. We claim that the proposed approach can serve as the best alternative in the scenarios wherein content in unavailable.

     

Discovering cross-topic collaborations among researchers by exploiting weighted association rules

Identifying the most relevant scientific publications on a given topic is a well-known research problem. The Author-Topic Model (ATM) is a generative model that represents the relationships between research topics and publication authors. It allows us to identify the most influential authors on a particular topic. However, since most research works are co-authored by many researchers the information provided by ATM can be complemented by the study of the most fruitful collaborations among multiple authors. This paper addresses the discovery of research collaborations among multiple authors on single or multiple topics. Specifically, it exploits an exploratory data mining technique, i.e., weighted association rule mining, to analyze publication data and to discover correlations between ATM topics and combinations of authors. The mined rules characterize groups of researchers with fairly high scientific productivity by indicating (1) the research topics covered by their most cited publications and the relevance of their scientific production separately for each topic, (2) the nature of the collaboration (topic-specific or cross-topic), (3) the name of the external authors who have (occasionally) collaborated with the group either on a specific topic or on multiple topics, and (4) the underlying correlations between the addressed topics. The applicability of the proposed approach was validated on real data acquired from the Online Mendelian Inheritance in Man catalog of genetic disorders and from the PubMed digital library. The results confirm the effectiveness of the proposed strategy.

     

RTRS: a recommender system for academic researchers

The ever-evolving nature of research works creates the cacophony of new topics incessantly resulting in an unstable state in every field of research. Researchers are disseminating their works producing a huge volume of articles. In fact, the spectacular growth in scholarly literature is widening the choice sets overwhelmingly for researchers. Consequently, they face difficulties in identifying a suitable topic of current importance from a plethora of research topics. This remains an ill-defined problem for researchers due to the overload of choices. The problem is even more severe for new researchers due to the lack of experience. Hence, there is a definite need for a system that would help researchers make decisions on appropriate topics. Recommender systems are good options for performing this very task. They have been proven to be useful for researchers to keep pace with research dynamics and at the same time to overcome the information overload problem by retrieving useful information from the large information space of scholarly literature. In this article, we present RTRS, a knowledge-based Research Topics Recommender System to assist both novice and experienced researchers in selecting research topics in their chosen field. The core of this system hinges upon bibliometric information of the literature. The system identifies active research topics in a particular area and recommends top N topics to the target users. The results obtained have proven useful to academic researchers, particularly novices, in making an early decision on research topics.     

Introduction to the Special Issue on Causal Discovery

Many empirical sciences, including the social sciences and life sciences, aim to study causal relationships. Researchers in these fields need computational methods for analyzing observed data and identifying causal structures among a set of variables. Such computational methods enable researchers to draw conclusions on the basis of both their assumptions and the observed data. Moreover, these methods are useful for developing hypotheses on causal relations, designing future observational studies, and planning future experimental studies that can potentially provide stronger evidence of estimated causal relations.

The objective of this special issue is to present an up-to-date overview of causal discovery methods, which have witnessed rapid advancements in recent years. The chief editor and guest editors invited the following three survey papers on various hot topics related to causal discovery:

     

Fabrication of a reticular poly(lactide-co-glycolide) cylindrical scaffold for the in vitro development of microvascular networks

Abstract

The microvascular network is a simple but critical system that is responsible for a range of important biological mechanisms in the bodies of all animals. The ability to generate a functional microvessel not only makes it possible to engineer vital tissue of considerable size but also serves as a platform for biomedical studies. However, most of the current methods for generating microvessel networks in vitro use rectangular channels which cannot represent real vessels in vivo and have dead zones at their corners, hence hindering the circulation of culture medium. We propose a scaffold-wrapping method which enables fabrication of a customized microvascular network in vitro in a more biomimetic way. By integrating microelectromechanical techniques with thermal reflow, we designed and fabricated a microscale hemi-cylindrical photoresist template. A replica mold of polydimethylsiloxane, produced by casting, was then used to generate cylindrical scaffolds with biodegradable poly(lactide-co-glycolide) (PLGA). Human umbilical vein endothelial cells were seeded on both sides of the PLGA scaffold and cultured using a traditional approach. The expression of endothelial cell marker CD31 and intercellular junction vascular endothelial cadherin on the cultured cell demonstrated the potential of generating a microvascular network with a degradable cylindrical scaffold. Our method allows cells to be cultured on a scaffold using a conventional culture approach and monitors cell conditions continuously. We hope our cell-covered scaffold can serve as a framework for building large tissues or can be used as the core of a vascular chip for in vitro circulation studies.     

A Dynamic Comparative Analysis of International Innovation Networks in Emerging Market MNCs

This paper compares the international innovation strategies of emerging market MNCs (EMNCs) with those of developed country MNCs (DMNCs). More specifically, we analyze the patent outcomes related to the use of international innovation networks (IINs) of EMNCs in developed markets compared with those of DMNCs in emerging markets. We explore the convergence and volatility patterns in patent generation within these IINs, considering the use of overseas R&D affiliates and the outcomes of interactions between foreign R&D affiliates and home headquarters for generating patents over a 20-year period. Our findings are broadly supportive of the idea that the trends in the volume and volatility of patents generated from the underlying IINs used by EMNCs are converging with those of DMNCs. This is in line with the predictions of a number of current international business theories regarding EMNC international expansion.     

Exploring scientific articles contributed by industries in Taiwan

The scientific knowledge contributed by industries remains ambiguous because prior studies have evaluated only specific industries, large companies, or industries collaborating with universities. We conducted a bibliometric analysis of data in the Web of Science database to explore the research partners of industries and determine which industries generate scientific articles, observing industrial trends in Taiwan from 1982 to 2011. The results showed that articles were published related to 26 industries, and the electronic components industry generated the highest percentage of articles (42.4 %), followed by the computer, electronics, and optical product industry (12.3 %). High-tech industries dominated, generating 84.5 % of the articles and demonstrating an annual increase in publications. In addition, industry researchers tended to cooperate with researchers affiliated with domestic institutions, particularly universities. Those in high-tech industries produced a higher percentage of articles coauthored with universities compared with those in low-tech industries.     

Detecting bursty terms in computer science research

Research topics rise and fall in popularity over time, some more swiftly than others. The fastest rising topics are typically called bursts; for example “deep learning”, “internet of things” and “big data”. Being able to automatically detect and track bursty terms in the literature could give insight into how scientific thought evolves over time. In this paper, we take a trend detection algorithm from stock market analysis and apply it to over 30 years of computer science research abstracts, treating the prevalence of each term in the dataset like the price of a stock. Unlike previous work in this domain, we use the free text of abstracts and titles, resulting in a finer-grained analysis. We report a list of bursty terms, and then use historical data to build a classifier to predict whether they will rise or fall in popularity in the future, obtaining accuracy in the region of 80%. The proposed methodology can be applied to any time-ordered collection of text to yield past and present bursty terms and predict their probable fate.

     

Application of phase-change materials in memory taxonomy

Abstract

Phase-change materials are suitable for data storage because they exhibit reversible transitions between crystalline and amorphous states that have distinguishable electrical and optical properties. Consequently, these materials find applications in diverse memory devices ranging from conventional optical discs to emerging nanophotonic devices. Current research efforts are mostly devoted to phase-change random access memory, whereas the applications of phase-change materials in other types of memory devices are rarely reported. Here we review the physical principles of phase-change materials and devices aiming to help researchers understand the concept of phase-change memory. We classify phase-change memory devices into phase-change optical disc, phase-change scanning probe memory, phase-change random access memory, and phase-change nanophotonic device, according to their locations in memory hierarchy. For each device type we discuss the physical principles in conjunction with merits and weakness for data storage applications. We also outline state-of-the-art technologies and future prospects.     

Comparative case studies on ring gear fault diagnosis of planetary gearboxes using vibrations and acoustic emissions

The analysis of vibrations and acoustic emissions (AE) are two recognized non-destructive techniques used for machine fault diagnosis. In recent years, the two techniques have been comparatively evaluated by different researchers with experimental tests. Several evaluations have shown that the AE analysis has a higher potential than the vibration analysis for fault diagnosis of mechanical components for certain cases. However, the distance between the AE sensor and the fault is an important factor that can considerably decrease the potential to detect damage and that has not been sufficiently investigated. Moreover, the comparisons have not yet addressed conditions of slow speed that for example are usual for wind turbine gearboxes. Therefore, in this paper we present two comparative case studies that address both topics. Both case studies consider planetary gearboxes with faults in their ring gears. The first case study corresponds to a small planetary gearbox in which the AE and vibration sensors were installed together at two different positions. The second case study corresponds to a full-size wind turbine gearbox in which three pairs of AE and vibration sensors were installed on the outside of the ring gear from a low-speed planetary stage. The results of the evaluations demonstrate the important influence of the distance between sensors and fault. Despite this, the good results from the AE analysis indicate that this technique should be considered as an important complement to the traditional vibration analysis. The main contribution of this paper is comparing AE and vibration analysis by using not only experimental data from a small planetary gearbox but also from a full-size wind turbine gearbox. The comparison addresses the topics of proximity of the sensor to the fault and low-speed conditions.

     

Software survey: ScientoPy,a scientometric tool for topics trend analysis in scientific publications

Bibliometric analysis is growing research filed supported in different tools. Some of these tools are based on network representation or thematic analysis. Despite years of tools development, still, there is the need to support merging information from different sources and enhancing longitudinal temporal analysis as part of trending topic evolution. We carried out a new scientometric open-source tool called ScientoPy and demonstrated it in a use case for the Internet of things topic. This tool contributes to merging problems from Scopus and Clarivate Web of Science sources, extracts and represents h-index for the analysis topic, and offers a set of possibilities for temporal analysis for authors, institutions, wildcards, and trending topics using four different visualizations options. This tool enables future bibliometric analysis in different emerging fields.

     

Current performance and future trends in health care sciences and services research

Health care sciences and services research (HCSSR) has come to the fore in recent years and related research literature increased rapidly over the last few decades. The main purpose of this study is to describe the global progress and to determine the current trends on HCSSR by using a scientometrics approach to survey related literature in the Web of Science database from 1900 to 2012. The document types, languages, publication patterns, subject categories, journals, geographic and institutional distributions, top cited articles, and the distribution of keywords were thoroughly examined. The results show that HCSSR has increased rapidly over the past 20 years, most notably in the last decade. In total, there are currently 128,728 research articles in 156 journals listed in 39 WoS subject categories. The top 20 most productive countries, and institutions were analyzed in detail, and 11 frequently cited papers and research foci were identified based on citation analysis. HCSSR spans many disciplines and focuses mainly on public, environmental & occupational health and education educational research. Medical Care, Academic Medicine, Health Affairs and Journal of School Health are the core journals with both high quantity and quality. High-income countries make up the leading nations, especially G7 countries. Meanwhile, “emerging economies” are also increasingly engaging this field. American and Canadian institutions have made greater advances in productions, citations, and cooperation, with stronger and better development prospects overall. The hot topics include internet use and decision making in health care, palliative care and end of life research, health status and quality of life, quality of healthcare and patient’s satisfaction, medical education, and health communication. Also, most researchers tend to study health care sciences based on the topics of quality-of-life assessment, and their interest in quality-of-life measures has increased. Increasing attention has been paid to the developing countries, especially “emerging economies” like China. Although health research has made much progress, many questions still remain unanswered and there are few assessments of how well research systems carry out their essential functions. Hence, there is currently an urgent need for timely establishment of an effective health research system.     

Trends in research foci in life science fields over the last 30 years monitored by emerging topics

We report here a simple method to identify the ‘emerging topics’ in life sciences. First, the keywords selected from MeSH terms on PubMed by filtering the terms based on their increment rate of the appearance, and, then, were sorted into groups dealing with the same topics by ‘co-word’ analysis. These topics were defined as ‘emerging topics’. The survey of the emerging keywords with high increment rates of appearance between 1972 to 2006 showed that emerging topics changed dramatically year by year, and that the major shift of the topics occurred in the late 90s; the topics that cover technical and conceptual aspects in molecular biology to the more systematic ‘-omics’-related and nanoscience-related aspects. We further investigated trends in emerging topics within various sub-fields in the life sciences.     

Stocktaking scientific publication on bi-regional collaboration between Europe 28 and Latin America and the Caribbean

Mapping bi-regional scientific collaboration demands multiple approaches to obtain a picture as complete as possible. Usually, the first approach is the measuring of the number and typology of scientific co-publications in the most visible indexes of journals and publications covered by databases like Web of Science or Scopus, among others. This paper analyzes scientific publications listed by Web of Science (WoS), which comprises authors from the 28 EU countries and Latin American and Caribbean countries (EULAC) between 2005 and 2016. The following questions have been addressed: How are bi-regional scientific relations between EULAC countries reflected by international collaboration? What effects does this scientific collaboration have in smaller or emerging countries? Which area of knowledge has more international collaborations? The study highlights the existence of a growing global network of researchers from several countries that collaborate on their research. EULAC scientific collaboration cannot be understood in isolation from this global network.