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Unlike many other quantitative characteristics used to determine higher education rankings, opinion-based peer assessment scores and the factors that may influence them are not well understood. Using peer scores of US colleges of engineering as reported annually in US News and World Report (USNews) rankings, the purpose of this paper is to provide some insights into peer assessments by statistically identifying factors that influence them.

With highly detailed data, a random parameters linear regression is estimated to statistically identify the factors determining a college of engineering’s average USNews peer assessment score.

The findings show that a wide variety of college- and university-specific attributes influence average peer impressions of a university’s college of engineering including the size of the faculty, the quality of admitted students and the quality of the faculty measured by their citation data and other factors.

The paper demonstrates that average peer assessment scores can be readily and accurately predicted with observable data on the college of engineering and the university as a whole. In addition, the individual parameter estimates from the statistical modeling in this paper provide insights as to how specific college and university attributes can help guide policies to improve an individual college’s average peer assessment scores and its overall ranking.

This paper aims to introduce a conceptual model for the shaping of the innovation district under the anchor approach by extracting the specifications of the fourth-generation university.

This study selected 550 resources and reduced them to 190 to achieve the most appropriate resources. This study used a meta-synthesis analysis approach using a text-mining method due to the multidisciplinary and voluminous nature of contents.

The results first reveal the shaping process and the components of innovation districts, which are: innovational urban infrastructures, knowledge economy and competitiveness and academic development. Second, this study also shows the specifications of a fourth-generation university to shape innovation districts.

This study also informs the policymakers and researchers internationally about the implementation requirements of a fourth-generation university and the shaping mechanisms of an innovation district.

This paper is pioneer about two concepts, first, it shows the shaping process of an innovation district, providing a large-scale insight about the components and second, this illustrates for the first time the specifications of a fourth-generation University practically as an anchor institute to shape innovation district.

In this paper, the seismic behavior of the gusset plate moment connection (GPMC) exposed to the post-earthquake fire (PEF) is investigated.

For this purpose, for the sake of verification, first, a numerical model is built using ABAQUS software and then exposed to earthquakes and high temperatures. Afterward, the effects of a series of parameters, such as gusset plate thickness, gap width, steel grade, vertical load value and presence of the stiffeners, are evaluated on the behavior of the connection in the PEF conditions.

Based on the results obtained from the parametric study, all parameters effectively played a role against the seismic loads, although, when exposed to fire, it was found that the vertical load value and presence of the stiffener revealed a great contribution and the other parameters could not significantly affect the connection performance. Finally, to develop the modeling and further study the performance of the connection, the 4 and 8-story frames are subjected to 11 accelerograms and 3 different fire scenarios. The findings demonstrate that high temperatures impose rotations on the structure, such that the story drifts were changed compared to the post-earthquake drift values.

The obtained results can be used by engineers to design the GPMC for the combined action of earthquake and fire.