scholarly journals A network approach to expertise retrieval based on path similarity and credit allocation

Author(s):  
Xiancheng Li ◽  
Luca Verginer ◽  
Massimo Riccaboni ◽  
P. Panzarasa

AbstractWith the increasing availability of online scholarly databases, publication records can be easily extracted and analysed. Researchers can promptly keep abreast of others’ scientific production and, in principle, can select new collaborators and build new research teams. A critical factor one should consider when contemplating new potential collaborations is the possibility of unambiguously defining the expertise of other researchers. While some organisations have established database systems to enable their members to manually produce a profile, maintaining such systems is time-consuming and costly. Therefore, there has been a growing interest in retrieving expertise through automated approaches. Indeed, the identification of researchers’ expertise is of great value in many applications, such as identifying qualified experts to supervise new researchers, assigning manuscripts to reviewers, and forming a qualified team. Here, we propose a network-based approach to the construction of authors’ expertise profiles. Using the MEDLINE corpus as an example, we show that our method can be applied to a number of widely used data sets and outperforms other methods traditionally used for expertise identification.

Author(s):  
Ryan Mullins ◽  
Deirdre Kelliher ◽  
Ben Nargi ◽  
Mike Keeney ◽  
Nathan Schurr

Recently, cyber reasoning systems demonstrated near-human performance characteristics when they autonomously identified, proved, and mitigated vulnerabilities in software during a competitive event. New research seeks to augment human vulnerability research teams with cyber reasoning system teammates in collaborative work environments. However, the literature lacks a concrete understanding of vulnerability research workflows and practices, limiting designers’, engineers’, and researchers’ ability to successfully integrate these artificially intelligent entities into teams. This paper contributes a general workflow model of the vulnerability research process, and identifies specific collaboration challenges and opportunities anchored in this model. Contributions were derived from a qualitative field study of work habits, behaviors, and practices of human vulnerability research teams. These contributions will inform future work in the vulnerability research domain by establishing an empirically-driven workflow model that can be adapted to specific organizational and functional constraints placed on individual and teams.


2017 ◽  
Vol 12 (7) ◽  
pp. 851-855 ◽  
Author(s):  
Louis Passfield ◽  
James G. Hopker

This paper explores the notion that the availability and analysis of large data sets have the capacity to improve practice and change the nature of science in the sport and exercise setting. The increasing use of data and information technology in sport is giving rise to this change. Web sites hold large data repositories, and the development of wearable technology, mobile phone applications, and related instruments for monitoring physical activity, training, and competition provide large data sets of extensive and detailed measurements. Innovative approaches conceived to more fully exploit these large data sets could provide a basis for more objective evaluation of coaching strategies and new approaches to how science is conducted. An emerging discipline, sports analytics, could help overcome some of the challenges involved in obtaining knowledge and wisdom from these large data sets. Examples of where large data sets have been analyzed, to evaluate the career development of elite cyclists and to characterize and optimize the training load of well-trained runners, are discussed. Careful verification of large data sets is time consuming and imperative before useful conclusions can be drawn. Consequently, it is recommended that prospective studies be preferred over retrospective analyses of data. It is concluded that rigorous analysis of large data sets could enhance our knowledge in the sport and exercise sciences, inform competitive strategies, and allow innovative new research and findings.


2017 ◽  
Vol 34 (3) ◽  
pp. 299-319
Author(s):  
Daniela Tomio ◽  
Daniela Andersen ◽  
Luciane Schulz

A permacultura é um movimento internacional de pessoas, organizadas em comunidades ecológicas, que se engajam em buscar outras formas de produção e consumo mais sustentáveis. No contexto educacional este modelo de (com)viver é fundamento de projetos de escolas que buscam ressignificar seus tempos, espaços e relações sociais a partir práticas sustentáveis. Neste cenário, por meio de uma pesquisa de estado da arte, objetivamos caracterizar compreensões e métodos das pesquisas sobre práticas educativas em permacultura na escola, divulgadas na produção científica brasileira. O conhecimento sistematizado permite apontar lacunas e oportunizar reflexões para novas investigações, contribuindo para repensar o cotidiano escolar, ampliar referências e mobilizar para construção de uma rede de conhecimentos integrados entre a pesquisa acadêmica, a escola e as comunidades na direção de uma cultura permanente de relações sustentáveis. The Permaculture is an international movement of peoples, organized in ecological communities, which are engaged in seeking other forms of more sustainable production and consumption. In the educational context this model of (co)living is the foundation of projects of schools that seek to re-signify their times, spaces and social relations from sustainable practices. In this scenario, through state-of-the-art research, we aim to characterize understandings and methods of research on educational practices in permaculture at school, disseminated in Brazilian scientific production. Systematized knowledge allows us to point out gaps and to provide reflections for new research, contributing to rethinking school daily life, expanding references and mobilizing to build a network of integrated knowledge between academic research, school and communities towards a permanent culture of relationships sustainable development. La permacultura es un movimiento internacional de personas, organizadas en comunidades ecológicas, que se dedican a buscar otras formas de producción y consumo más sostenibles. En el contexto educativo este modelo de (con) vivir es fundamento de proyectos de escuelas que buscan resignificar sus tiempos, espacios y relaciones sociales a partir de prácticas sustentables. En este escenario, por medio de una investigación de estado del arte, pretendemos caracterizar comprensiones y métodos de las investigaciones sobre prácticas educativas en permacultura en la escuela, divulgadas en la producción científica brasileña. El conocimiento sistematizado permite apuntar lagunas y oportunizar reflexiones para nuevas investigaciones, contribuyendo a repensar el cotidiano escolar, a ampliar referencias y movilizar para la construcción de una red de conocimientos integrados entre la investigación académica, la escuela y las comunidades hacia una cultura permanente de relaciones sostenibles.


2021 ◽  
Vol 8 (3) ◽  
pp. 594
Author(s):  
Karinne M. Carvalho ◽  
Mariana S. N. De Carvalho ◽  
Rafaela L. Grando ◽  
Livia A. De Menezes

Children with complex chronic conditions (CCC) belong to a distinct pediatric group, characterized by the (potential) manifestation of a wide range of pathologies requires long-term multidisciplinary health care, alongside recurrent hospitalizations and, in many cases, dependent on the use of technology for life maintenance. The need to seek, organize and disseminate bibliographic information on CCC led us to chart the scientific production on this theme, and a complete search of the academic publications was conducted in two scientific databases, the Web of Science and Scopus. The results indicate a significant growth in CCC research over the years, matching both, the increased number of cases and the consequent rise in life expectancy of these children. The scientific production on CCC is concentrated in the United States of America, reflecting and discussing the access to the health system of that country. We observed that the main thematic areas of the publications were related to hospitalization, health needs, coordination of care and oral health. Children have inequitable levels of access to treatment for CCC, according to family income, place of residence, educational level, race/ethnicity, evidencing the urgent need for formulation and implementation of public policies that address this portion of the population. Thus, it is expected that the present study will serve as a bridge guide for the development of potential new research projects, actions to promote and stimulate studies on this relevant theme and so far, neglected.


Author(s):  
Ashish Ranjan Mishra ◽  
Neelendra Badal

This chapter explains an algorithm that can perform vertical partitioning of database tables dynamically on distributed database systems. After vertical partitioning, a new algorithm is developed to allocate that fragments to the proper sites. To accomplish this, three major tasks are performed in this chapter. The first task is to develop a partitioning algorithm, which can partition the relation in such a way that it would perform better than most of the existing algorithms. The second task is to allocate the fragments to the appropriate sites where allocating the fragments will incur low communication cost with respect to other sites. The third task is to monitor the change in frequency of queries at different sites as well as same site. If the change in frequency of queries at different sites as well as the same site exceeds the threshold, the re-partitioning and re-allocation are performed.


2019 ◽  
Vol 31 (6) ◽  
pp. 1215-1233 ◽  
Author(s):  
Yunhua Chen ◽  
Yingchao Mai ◽  
Jinsheng Xiao ◽  
Ling Zhang

Although deep neural networks (DNNs) have led to many remarkable results in cognitive tasks, they are still far from catching up with human-level cognition in antinoise capability. New research indicates how brittle and susceptible current models are to small variations in data distribution. In this letter, we study the stochasticity-resistance character of biological neurons by simulating the input-output response process of a leaky integrate-and-fire (LIF) neuron model and proposed a novel activation function, rand softplus (RSP), to model the response process. In RSP, a scale factor [Formula: see text] is employed to mimic the stochasticity-adaptability of biological neurons, thereby enabling the antinoise capability of a DNN to be improved by the novel activation function. We validated the performance of RSP with a 19-layer residual network (ResNet) and a 19-layer visual geometry group (VGG) on facial expression recognition data sets and compared it with other popular activation functions, such as rectified linear units (ReLU), softplus, leaky ReLU (LReLU), exponential linear unit (ELU), and noisy softplus (NSP). The experimental results show that RSP is applied to VGG-19 or ResNet-19, and the average recognition accuracy under five different noise levels exceeds the other functions on both of the two facial expression data sets; in other words, RSP outperforms the other activation functions in noise resistance. Compared with the application in ResNet-19, the application of RSP in VGG-19 can improve a network's antinoise performance to a greater extent. In addition, RSP is easier to train compared to NSP because it has only one parameter to be calculated automatically according to the input data. Therefore, this work provides the deep learning community with a novel activation function that can better deal with overfitting problems.


Neurology ◽  
2020 ◽  
Vol 94 (12) ◽  
pp. 526-537 ◽  
Author(s):  
Codrin Lungu ◽  
Laurie Ozelius ◽  
David Standaert ◽  
Mark Hallett ◽  
Beth-Anne Sieber ◽  
...  

ObjectiveDystonia is a complex movement disorder. Research progress has been difficult, particularly in developing widely effective therapies. This is a review of the current state of knowledge, research gaps, and proposed research priorities.MethodsThe NIH convened leaders in the field for a 2-day workshop. The participants addressed the natural history of the disease, the underlying etiology, the pathophysiology, relevant research technologies, research resources, and therapeutic approaches and attempted to prioritize dystonia research recommendations.ResultsThe heterogeneity of dystonia poses challenges to research and therapy development. Much can be learned from specific genetic subtypes, and the disorder can be conceptualized along clinical, etiology, and pathophysiology axes. Advances in research technology and pooled resources can accelerate progress. Although etiologically based therapies would be optimal, a focus on circuit abnormalities can provide a convergent common target for symptomatic therapies across dystonia subtypes. The discussions have been integrated into a comprehensive review of all aspects of dystonia.ConclusionOverall research priorities include the generation and integration of high-quality phenotypic and genotypic data, reproducing key features in cellular and animal models, both of basic cellular mechanisms and phenotypes, leveraging new research technologies, and targeting circuit-level dysfunction with therapeutic interventions. Collaboration is necessary both for collection of large data sets and integration of different research methods.


2019 ◽  
Vol 9 (22) ◽  
pp. 4818
Author(s):  
Usman Akhtar ◽  
Anita Sant’Anna ◽  
Sungyoung Lee

Vast amounts of data, especially in biomedical research, are being published as Linked Data. Being able to analyze these data sets is essential for creating new knowledge and better decision support solutions. Many of the current analytics solutions require continuous access to these data sets. However, accessing Linked Data at query time is prohibitive due to high latency in searching the content and the limited capacity of current tools to connect to these databases. To reduce this overhead cost, modern database systems maintain a cache of previously searched content. The challenge with Linked Data is that databases are constantly evolving and cached content quickly becomes outdated. To overcome this challenge, we propose a Change-Aware Maintenance Policy (CAMP) for updating cached content. We propose a Change Metric that quantifies the evolution of a Linked Dataset and determines when to update cached content. We evaluate our approach on two datasets and show that CAMP can reduce maintenance costs, improve maintenance quality and increase cache hit rates compared to standard approaches.


2017 ◽  
pp. 36-47
Author(s):  
Andrea De Montis ◽  
Amedeo Ganciu ◽  
Fabio Recanatesi ◽  
Antonio Ledda ◽  
Vittorio Serra ◽  
...  

According to a worldwide well-known attitude, also in Italy, the assessment of scientific production in the last decades has been progressively based on the analysis of the impact through bibliometric variables. Various data sets, such as Scopus by Elsevier and Web of Science by Thomson Reuters, are designed and maintained to index a steadily increasing range of essays: mostly journal articles, book chapters, and conference proceedings. The indexing relays on the capacity to evaluate and update specific impact measures by keeping track of the citations representing the relations between the essays. The related opportunity to interpret bibliographic systems as research and development (R&D) networks attracted the interest of scientists operating, beyond the field of bibliometric analysis, in the realm of social networking. Network analysis belongs to mechanical statistics and is able to make sense of interconnected systems including very large sets of nodes and links. In this paper, we present a network approach to the review of the scientific production in the time period January, 2003-June, 2016 of Italian agricultural engineers, namely scientists belonging to the Italian ministerial scientific disciplinary sector AGR/10 - rural buildings and agro-forestry territory. Starting from 238 articles indexed in the Web of Knowledge database and published by 87 AGR/10 scholars, we apply four network analysis approaches to the study of the citations among articles, the most influential journals and topics, the co-authorship, the most favourite keywords with their evolution in time, and the communities’ pattern. We discover that Italian agricultural engineers are interlaced in a sparse network with a still limited tendency toward citing each other and are inclined to team up in established research groups based on a single university. As for the dualism between rural buildings and territory, we document on a relevant expansion of the issues related to landscape analysis and planning and a continuous renewal of studies concerning the relation between rural buildings and biomass and energy management. We advance that Italian agricultural engineers are not confronted anymore with two monolithic macro themes, i.e. building design and landscape analysis and planning. Instead, the complexity and interplay between these two domains has dramatically increased in a somehow diverging universe of even more specialised and trans-scale topics.


2016 ◽  
Vol 2 (3) ◽  
pp. 131-139 ◽  
Author(s):  
Marta Macedoni Luksic ◽  
Tanja Urbancic ◽  
Ingrid Petric ◽  
Bojan Cestnik

Purpose – The increase of prevalence of autism spectrum disorders (ASD) has been accompanied by much new research. The amount and the speed of growth of scientific information available online have strongly influenced the way of work in the research community which calls for new methods and tools to support it. The purpose of this paper is to present ontology-based text mining in the field of autism trend analysis that may help to understand the broader picture of the disorder since its discovery. Design/methodology/approach – The data sets consisted of abstracts of more than 18,000 articles on ASD published from 1943 to the end of 2012 found in MEDLINE and of the documents’ titles for all those articles where the abstracts were not available. Findings – In this way, the authors demonstrated a steeper exponential curve of ASD publications compared with all publications in MEDLINE. In addition, the main research topics over time were identified using the “open discovery” approach. Finally, the relationship between a priori setting up research topics including communication, genetics, environmental risk factors, vaccination and adulthood were revealed. Originality/value – Using ontology-based text mining the authors were able to identify the main research topics in the field of autism during the time, as well as to show the dynamics of some research topics as a priori setting up. The computerised methodology that was used allowed the authors to analyse a much larger quantity of information, saving time and manual work.


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