Electronic records management at the coal face: Testing a behaviour search model for EDRMS

<p>The main objective of this proposed research is to test the reliability and validity of the information search model presented by Joseph, Debowski & Goldschmidt (2013a) which relates to searching in EDRMS. In order to do this, the search behaviour of employees using the EDRMS eDOCS Hummingbird in a New Zealand local authority will be compared with the model. Another research objective is to gain information about current search behaviour in relationship to the design of the new EDRMS system Objective which will soon be installed in the test organisation. As the literature review shows, introducing an EDRMS to a workplace is difficult, requiring a major change to the way that employees have managed their information, (Maguire, 2005). The last objective is to gain insights from the search behaviour in regards to training for the new system.</p>

Electronic records management at the coal face: Testing a behaviour search model for EDRMS

<p>The main objective of this proposed research is to test the reliability and validity of the information search model presented by Joseph, Debowski & Goldschmidt (2013a) which relates to searching in EDRMS. In order to do this, the search behaviour of employees using the EDRMS eDOCS Hummingbird in a New Zealand local authority will be compared with the model. Another research objective is to gain information about current search behaviour in relationship to the design of the new EDRMS system Objective which will soon be installed in the test organisation. As the literature review shows, introducing an EDRMS to a workplace is difficult, requiring a major change to the way that employees have managed their information, (Maguire, 2005). The last objective is to gain insights from the search behaviour in regards to training for the new system.</p>

A Weakly Supervised Academic Search Model Based on Knowledge-Enhanced Feature Representation

Internet of Things search has great potential applications with the rapid development of Internet of Things technology. Combining Internet of Things technology and academic search to build academic search framework based on Internet of Things is an effective solution to realize massive academic resource search. Recently, the academic big data has been characterized by a large number of types and spanning many fields. The traditional web search technology is no longer suitable for the search environment of academic big data. Thus, this paper designs academic search framework based on Internet of Things Technology. In order to alleviate the pressure of the cloud server processing massive academic big data, the edge server is introduced to clean and remove the redundancy of the data to form a clean data for further analysis and processing by the cloud server. Edge computing network effectively makes up for the deficiency of cloud computing in the conditions of distributed and high concurrent access, reduces long-distance data transmission, and improves the quality of network user experience. For Academic Search, this paper proposes a novel weakly supervised academic search model based on knowledge-enhanced feature representation. The proposed model can relieve high cost of acquisition of manually labeled data by obtaining a lot of pseudolabeled data and consider word-level interactive matching and sentence-level semantic matching for more accurate matching in the process of academic search. The experimental result on academic datasets demonstrate that the performance of the proposed model is much better than that of the existing methods.

MrParse: Finding homologues in the PDB and the EBI AlphaFold database for Molecular Replacement and more

Crystallographers have an array of search model options for structure solution by Molecular Replacement (MR). Well-established options of homologous experimental structures and regular secondary structure elements or motifs are increasingly supplemented by computational modelling. Such modelling may be carried out locally or use pre-calculated predictions retrieved from databases such as the EBI AlphaFold database. MrParse is a new pipeline to help streamline the decision process in MR by consolidating bioinformatic predictions in one place. When reflection data are provided, MrParse can rank any homologues found using eLLG which indicates the likelihood that a given search model will work in MR. In-built displays of predicted secondary structure, coiled-coil and transmembrane regions further inform the choice of MR protocol. MrParse can also identify and rank homologues in the EBI AlphaFold database, a function that will also interest other structural biologists and bioinformaticians.

Discrete mission planning algorithm for air-sea integrated search model

The selection of optimal search effort for air-sea integrated search has become the most concerned issue for maritime search and rescue (MSAR) departments. Helicopters play an important role in maritime search because of their strong maneuverability and hovering ability. In this work, the requirements of maritime search were analyzed, from which a global optimization model with quantitative constraints for vessels and aircraft was developed by setting the least search time as single-objective optimization problem; then the improved Dinkelbach algorithm was used to solve the continuous programming problem, and the discrete mission planning algorithm was used to improve the calculation accuracy of search time and area. A case study shows that the errors in calculating search time and area decrease from 12–18 min to 36 s and from 76.5 to 0.45 n mile2, respectively. The results obtained from the discrete mission planning algorithm can provide better guidance for MASR departments in selecting optimal search scheme.

Workplace Heterogeneity and the Returns to Versatility

In the canonical random on-the-job search model with continuous firm heterogeneity, I show that a mean-preserving spread of the firm-productivity distribution raises the returns to mobility, i.e., the inter-firm mobility of workers as measured by the number of outside contacts per employment spell. Both sorting and rent-share mechanisms play a role. In a further contribution, I distinguish frictional and structural impediments to mobility in order to establish a link between mobility and skills via the concept of versatility. Versatility enhances a person’s mobility since a mismatch between job requirements and the person’s skill set is less likely to occur. I provide some statistics in support of the discussed mechanisms. The findings are particularly intriguing in light of the concurrent rise in the productivity dispersion across firms and in the skill premium in many countries.

What Can We Learn from Idiosyncratic Wage Changes?

I document six facts about wage changes. First, most pay revisions occur at yearly frequency, but a small proportion occur at idiosyncratic times. Second, idiosyncratic pay changes are larger and more dispersed than year-end pay changes and resemble more pay changes occurring at job-to-job transitions. Third, idiosyncratic pay changes are more common for workers with less experience and, fourth, in firms higher on the job-ladder. Fifth, industries in which the incidence of idiosyncratic raises have risen have experienced greater declines in labor share. Sixth, industries in which more firms report willingness to negotiate wages have greater concentrations of idiosyncratic revisions. An on-the-job search model with heterogeneous wage contracts can rationalize these facts.