50,197 research outputs found
Three Kinds of Disambiguated Author ID Systems for PubMed 2019
No full textAuthor identifier (ID) is essential for many downstream tasks, such as co-author network and scientist mobility analysis. As a widely used bibliometrics database, author ID of PubMed is not officially provided by National Institutes of Health (NIH), that restrict bibliometric research. This study exploited three open bibliographic databases Aminer, Microsoft Academic Graph (MAG) and Semantic Scholar (S2) to associate author ID for PubMed. For this purpose, paper linking and author linking was performed sequencely to mine paper and author links between PubMed and these databases. Performance of author name disambiguation (AND) of there available identifiers was evaluated on two AND datasets. Our findings suggested that, S2 contains full volume of PubMed regarding link completeness. With respect to correctness of author ID, S2 and MAG achieved better performance than Aminer. The best F1 score on both dataset of there available identifiers is below 90\%, indicate that AND for large scale database remain as a difficult task and the need for further improvement. We made the final dataset that contains linked paper and author of PubMed publicly available for facilitating future research
Researcher ID Workshop
No full textPapers presented at the Researcher ID Workshop, Auditorium, Merensky Library, University of Pretoria, 22 July 2015The workshop aimed to share ideas and knowledge on author visibility within the research industry. Presentations, discussions and training sessions focussed on the different IDs such as ORCID, Researcher ID, Scopus Author ID and others. Using these tools to manage and share your professional profile & publications. During the session attention was given to the following areas: The Role of the Information specialist; Real examples of how Information Specialists are involved with author IDs; Sharing of ideas and experiences thus far; Practical training with Melissa Badenhorst on Researcher ID; and Lucia Schoombee from Elsevier.mn201
Effects of workers motivation on construction productivity / Adebowale Oluseyi J. and Fapohunda Julius Ayodeji
No full textThe issue of construction workers motivation becomes a subject of debate among construction project management professionals. Therefore, there are diverse opinions on whether motivation of construction workers positively impacts construction workers performance or rather adversely
affects the general performance of construction labours. This brings about different motivation concepts and principle by researchers towards improvement of construction workforce performance. The paper takes into cognisance the perception of construction practitioners on motivation in relation with construction productivity towards achieving construction project objectives. In order to obtain a viable result of the study, the study adopts quantitative research approach on construction workforce
motivation with project managers, contract managers, site managers, contractors, and site supervisors. Quantitative data obtained was analysed with SPSS statistical tools. The perception of construction practitioners was explored on motivation drives of construction workforce. However, it was
found that motivation is important for construction workers performance, giving bonus to workers is important to improve workers efficiency and there is a need for construction workers recognition by management. The adequate application of recommendation of this study will enhance construction labour productivity, reduce wastes in construction, improve general construction performance and ultimately heightens customer's satisfaction
TAF-ID: An international thermodynamic database for nuclear fuels applications
No full textThe Thermodynamics of Advanced Fuels – International Database (TAF-ID) was developed using the Calphad method to provide a computational tool to perform thermodynamic calculations on nuclear fuel materials under normal and off-normal conditions. Different kinds of fuels are considered: oxide, metallic, carbide and nitride fuels. Many fission products are introduced as well as structural materials (e.g., zirconium, steel, concrete, SiC) and absorbers (e.g., B4C), in order to investigate the thermochemistry of irradiated fuels and to predict their chemical interaction with the surrounding materials. The approach to develop the database and the models implemented in the database are described. Examples of models for key chemical systems are presented. Finally, a few examples of application calculations on severe accidents with UO2 fuels, irradiated fuel chemistry of MOX and metallic fuels and metallic fuel/cladding interaction show how this tool can be used. To validate the database, the calculations are compared to the available experimental data. A good agreement is obtained which gives confidence in the maturity degree and quality of the TAF-ID database. The working version is only accessible to the participants of the TAF-ID project (Canada, France, Japan, the Netherlands, Republic of Korea, United Kingdom, USA). A public version is accessible by all the NEA countries. The current version contains models on the Am–Fe, Am–Np, Am-O-Pu, Am–U, Am–Zr, C–O–U-Pu, Cr–U, Np–U, Np–Zr, O–U–Zr, Re–U, Ru–U, Si–U, Ti–U, U-Pu-Zr, U–W systems. It is progressively extended with our published assessments. Information on how to join the project is available on the website: https://www.oecd-nea.org/science/taf-id/.Accepted Author ManuscriptRST/Reactor Physics and Nuclear Material
A unique author ID is a possible solution to the name ambiguity problem.
No full textWhen more than one person have the same name, names cannot be used to identify authors, which makes it difficult to connect authors with their scholarly work. Open Researcher and Contributor ID (ORCID) is a non-profit organization that aims to solve the name ambiguity problem by providing a personalized 16-digit ID to use as author identification for scholars. The main objective for ORCID is to become the focal point for the validation of scientific work. The outcome of the implementation of ORCID will provide a litmus test for the spread of this new initiative in the scientific communities.</p
OpenAlex Author Name Disambiguation V3 Initial Clusters
No full textAuthor name disambiguation V3 initial clusters for the OpenAlex dataset. See https://openalex.org
There are 633803287 rows, split into 4 CSV (comma-delimited) files (with headers).
The CSV files have two columns: "work_author_id" and "author_id"
"work_author_id": An OpenAlex Work ID and an author sequence number, joined with an underscore ("_")
"author_id": An OpenAlex Author ID, representing a unique author in OpenAle
Dataset of Author Names and Name Frequencies
No full textThis file is a gzipped semicolon separated text file containing block id, frequency of the first name (number of times it appears in the 38M WoC version Q author IDs), frequency of the last name, full name, email, and Author ID. The largest block contains 993 Author IDs. </p
Dataset of Author Names and Name Frequencies
No full textThis file is a gzipped semicolon separated text file containing block id, frequency of the first name (number of times it appears in the 38M World of Code version Q author IDs), frequency of the last name, full name, email, and Author ID. The largest block contains 993 Author IDs.
The email address and Author IDs of individual authors have been replaced by their corresponding SHA1 values for privacy reasons
Investigating Domain Transfer and Viewpoint in the Context of Person Re-Id
No full textDeep learning has significantly improved Re-Id per- formance but it requires a large amount of data, however, obtaining data is expensive from both time and money perspective. Inspired by ImageNet pre- trained models and synthetic data generation techniques, this paper investigates to utilise real-world and syn- thetic Re-Id datasets to augment task performance. Firstly, we propose two methods to apply external Re-Id data, NDTL (Neighbour-Domain Transfer Learning) and NDDS (Neighbour-Domain Data Stitching). Secondly, we quantitatively illustrate that both real-world and syn- thetic data could mitigate Re-Id data shortage problems, using Re-Id dataset to pre-train models is better than us- ing ImageNet, we achieve up to 28.2% mAP improvement on DukeMTMC and 5.2% on Market-1501. Moreover, we find out that viewpoint, one of Re-Id relevant factors, has the an influence on the system performance due to viewpoint-wise non-alignment and unbalance of the orig- inal dataset, it also assists the performance if train set is augmented balanced. Our research strongly illustrates both real-world and synthetic Re-Id dataset can effec- tively augment Re-Id task, viewpoint is an essential fac- tor and based on which, train-test distribution dramati- cally influences Re-Id performance, and balancing train classes are also helpful to improve the performance
Solving Multi-Agent Pathfinding with Matching using A*+ID+OD
No full textThis paper extends the Multi-Agent Pathfinding (MAPF) algorithm, A*+ID+OD, to be able to solve problems with matching. This extension still keeps the optimal and completeness properties of the original algorithm. Matching is added to the algorithm in both an exhaustive and heuristic manner. Exhaustive matching is further improved by adding a new layer of Independence Detection (ID) to reduce the number of matchings. Besides this, the pruning efficiency is increased by sorting the matchings based on the initial heuristic. The exhaustive matching method has been found to perform better than the heuristic matching method. The exhaustive version of A*+ID+OD is finally compared to other extended MAPF algorithms which shows that on small maps, Conflict Based Min-Cost Flow (CBM) performs best as it is the only algorithm that does not use exhaustive matching. A*+ID+OD and Enhanced Partial Expansion A* (EPEA*) also perform well on open maps with multiple teams when compared to other exhaustive matching algorithms due to the addition of matching ID.CSE3000 Research ProjectComputer Science and Engineerin
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