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In order to find the relationship between operation machine status and oil monitoring information, the oil monitoring information characteristics abstraction and fault diagnostic system is established. The purpose of this paper is to find an effective method to monitor and diagnose the machine running status, and consequently, serve the industry.

The operation status information of equipments is obtained through applying the methods of statistical, trend, entropy and clustering characteristics as a whole; and the multi‐characteristic integration method is established based on the existing literature, industry practices and oil characteristic analysis.

Using multi‐characteristic integration method, an oil monitoring and diagnostic system is established based on the above status information. This multi‐characteristic integration method is applied to D‐100/8 air compressor sets in the status monitoring project of a shipbuilding company. The analysis conclusions of the operation status can be obtained promptly and accurately by the method, and can provide guidance for the equipment maintenance.

A novel comprehensive oil monitoring data processing method are presented in this paper, which can scientifically distill latent laws among the monitoring information and detect accurately the measurement index of the fault states and abnormity data.

This study aims to investigate the effect of microalloyed Ca and Ce on microstructure and corrosion behavior of Mg-1.5Zn alloy. Mg-1.5Zn-xCa-xCe alloys were prepared by melting, extrusion and rolling processes.

The effects of adding Ca and Ce elements alone or adding Ca and Ce elements simultaneously on the microstructure and corrosion resistance of Mg-1.5Zn-xCa-xCe (x = 0 or 0.2 Wt.%) alloys were studied by scanning electron microscopy, hydrogen evolution tests and electrochemical experiments.

The addition of Ca and Ce elements alone or the addition of Ca and Ce elements had little impact on the grain size of the rolled and annealed Mg-1.5Zn-xCa-xCe alloy, but had a greater effect on the type and quantity of the second phase.

The order of the corrosion rates for the three alloys was Mg-1.5Zn-0.2Ca < Mg-1.5Zn-0.2Ca-0.2Ce < Mg-1.5Zn-0.2Ce. Mg-1.5Zn-0.2Ca showed the best corrosion resistance, which was related to the second phase and corrosion products.

A significant amount of digital repository research and development activity is taking place worldwide, which calls for the investigation of issues identified as critical to the development, management and sustainability of these repositories. The purpose of this paper is to establish a comprehensive set of critical success factors (CSFs) that would enable successful digital libraries implementation.

The design of this study is exploratory in nature due to lack of previous research about CSFs in digital library projects. The paper builds the research framework to find CSFs for digital libraries initiatives by collecting possible factors from literature on CSFs of information systems; and feedback from ten experts who have had experience in digital library research and development as well as implementation, through e‐mail interviews. Six dimensions in the enterprise architecture framework (namely motivation, resource, people, process, location and time) needed to create the environment in which digital delivery can be effective and sustained, are mapped with the CSF established from the literature.

The results revealed six dimensions of CSFs and 36 potential success factor statements contributed by the study participants. Based on these findings, this paper postulates that successful deployment of a digital library implementation may depend on this set of success factors. The identification of these factors has important implications on digital library development.

There has been no comprehensive study on the success factors of digital libraries in the library and information science context, as such, no investigation of the factors in some real‐life contexts of digital library activities. It may help digital library start‐ups to understand what sources and services they need to develop to make their applications successful in an already very populated network. Both researchers and practitioners in the field of digital libraries may value the novelty and results of this study.

The purpose of this investigation is to identify, evaluate, integrate and summarize relevant and qualified papers through conducting a systematic literature review (SLR) on the application of recommender systems (RSs) to suggest a scholarly publication venue for researcher's paper.

To identify the relevant papers published up to August 11, 2018, an SLR study on four databases (Scopus, Web of Science, IEEE Xplore and ScienceDirect) was conducted. We pursued the guidelines presented by Kitchenham and Charters (2007) for performing SLRs in software engineering. The papers were analyzed based on data sources, RSs classes, techniques/methods/algorithms, datasets, evaluation methodologies and metrics, as well as future directions.

A total of 32 papers were identified. The most data sources exploited in these papers were textual (title/abstract/keywords) and co-authorship data. The RS classes in the selected papers were almost equally used. DBLP was the main dataset utilized. Cosine similarity, social network analysis (SNA) and term frequency–inverse document frequency (TF–IDF) algorithm were frequently used. In terms of evaluation methodologies, 24 papers applied only offline evaluations. Furthermore, precision, accuracy and recall metrics were the popular performance metrics. In the reviewed papers, “use more datasets” and “new algorithms” were frequently mentioned in the future work part as well as conclusions.

Given that a review study has not been conducted in this area, this paper can provide an insight into the current status in this area and may also contribute to future research in this field.