Physically-based hydrological-geotechnical modeling at large scales is difficult, especially due to the time-consuming nature of flow routing and 3D soil stability models. Although parallelization techniques are commonly used for each model individually, there is currently no concurrent parallelization strategy for both. This study proposed an open-source, Parallelized, and modular modeling software for regional Hydrologic processes and Landslides simulation and prediction (PHyL v1.0). It offers parallel computation in both hydrological and 3D slope stability modules, cross-scale modeling ability via a soil moisture downscaling method, and advanced input/output (I/O) and post-processing visualization. Additionally, PHyL v1.0 is flexible and extensible, making it compatible with all mainstream operating systems. We applied PHyL v1.0 in the Yuehe River Basin, where the computational efficiencies, parallel performance, parameter sensitivity analysis, and predictive capabilities were evaluated. The PHyL v1.0 is therefore appropriately used as an advanced software for high-resolution and complex simulations of regional floods and landslides.

Industrial Internet of Things (IoT) has suffered from insufficient identity authentication and dynamic network topology, thereby resulting in vulnerabilities to data confidentiality. Recently, the attribute-based encryption (ABE) schemes have been regarded as a solution to ensure data transmission security and the fine-grained sharing of encrypted IoT data. However, most of existing ABE schemes that bring tremendous computational cost are not suitable for resource-constrained IoT devices. Therefore, lightweight and efficient data sharing and searching schemes suitable for IoT applications are of great importance. To this end, In this article, we propose a light searchable ABE scheme (namely LSABE). Our scheme can significantly reduce the computing cost of IoT devices with the provision of multiple-keyword searching for data users. Meanwhile, we extend the LSABE scheme to multiauthority scenarios so as to effectively generate and manage the public/secret keys in the distributed IoT environment. Finally, the experimental results demonstrate that our schemes can significantly maintain computational efficiency and save the computational cost at IoT devices, compared to other existing schemes.