The South Manchuria Railway, being the earliest constructed railway in Northeast China, has preserved a vast array of modern architectural heritage along its route, which holds significant research value. This study takes the urban agglomerations along the Shenyang–Yingkou section of the South Manchuria Railway as the research object, convening scholars from various fields to construct a hierarchy analysis model for heritage value and using fuzzy control tools to mitigate the impact of subjective cognition on the experimental results, thereby determining the weight values of the influencing factors of modern architectural heritage along the South Manchuria Railway. We invited professional scholars and stakeholders to score the modern architectural heritage, and after combining the weight values derived from the hierarchy analysis model and calculating the weighted average, the heritage value scores were determined for each piece of modern architectural heritage. This study utilizes heritage value scores to measure the degree of danger and the extent of protection required for these architectural heritages, identifies the current shortcomings and insufficiencies in the protection and renewal of these heritages, and compares the effectiveness of heritage conservation efforts in various cities and towns.

With the progress of China’s economy, there is an increasing focus on accessibility systems. Enhancements to accessibility infrastructure are being implemented in all types of structures, with a particular focus on educational institutions such as college campuses. This research was carried out to examine the campus accessibility system of Northeastern University’s Nanhu and Hunnan Campuses in Shenyang City, China, using failure mode and effects analysis (FMEA) as a methodology and using incorporating fuzzy control, which overcomes the limitations of traditional FMEA. Fuzzy-FMEA integrates the fuzzy linguistic assessment to assist the analysis process, in contrast to standard analysis which mainly relies on subjective judgment. Through calculations, it is known that ramps, barrier-free toilets, and barrier-free entrances are the items with the highest failure modes. The construction of the campus accessible environment needs to prioritize solving the problems of these facilities. The research results also found that there is a lack of research specifications for accessible environments in China’s cold regions, and universal specifications are not fully suitable. The accessibility of the new campus was improved and management was improved, reflecting the school’s increased awareness of accessible environment construction in recent years. However, there are still many common problems in the old and new campuses, proving that they are not aware of the importance and urgency of improving these problems. In addition, the construction of barrier-free facilities in the administrative office buildings where management and faculty are located on both campuses is generally in good condition. The accessible design of dormitories and canteens commonly used by students is often ignored. Moreover, the rough detailing in many buildings prevents these facilities from being used properly. These are the challenges faced by the Northeastern University in building an accessible environment.

Huizhou architectural heritage images are important visual materials for regional heritage documentation, digital archiving, and conservation support. However, Huizhou architecture shares many visual cues with Jiangnan white-walled and grey-tiled buildings and other visually similar Classical Chinese architectural forms. In practical image archiving, the critical risk is therefore not only whether a model can achieve high four-class accuracy, but also whether visually similar Classical Chinese buildings are incorrectly archived as Huizhou architecture. To address this problem, this study constructs the HuizhouStyle-4C image recognition task and proposes a reliability-oriented evaluation workflow for Huizhou architectural heritage image archiving. The workflow combines group-aware leakage control, hard-boundary diagnosis, and an out-of-fold (OOF)-safe fixed decision rule. A structure-aware baseline classifier, SAB-ResNet, is further used to incorporate architectural boundary and facade-structure cues into the recognition process. The evaluation includes group-aware five-fold cross-validation, an independent holdout subset from the curated dataset, and a hard-boundary test focused on the distinction between Huizhou architecture and visually similar Classical Chinese samples. Under this within-dataset held-out evaluation setting, the OOF-safe balanced point achieved an Independent Holdout Macro-F1 of 0.9501 and a Hard Binary F1 of 0.8182. The results indicate that Huizhou architectural heritage image archiving benefits from not only conventional four-class recognition, but also explicit diagnosis of near-neighbour misclassification risks and fixed decision rules selected without test-set labels. Additional stronger backbone comparisons further show that competitive held-out four-class performance does not eliminate the need for hard-boundary diagnosis.