We propose a novel fragment assembly method for low-resolution modeling of RNA and show how it may be used along with small-angle X-ray solution scattering (SAXS) data to model low-resolution structures of particles having as many as 12 independent secondary structure elements. We assessed this model-building procedure by using both artificial data on a previously proposed benchmark and publicl...

In the field of post-disaster assessment, for timely and accurate rescue localization after a disaster, people need to know location damaged buildings. deep learning, some scholars have proposed methods make automatic highly building damage assessments by remote sensing images, which are proved be more efficient than assessment domain experts. However, due lack large amount labeled data, these ...

Due to the climate change debate, a lot of research and maps of external climate parameters are available. However, maps of indoor climate performance parameters are still lacking. This paper presents a methodology for obtaining maps of performances of similar buildings that are virtually spread over whole Europe. The produced maps are useful for analyzing regional climate influence on building...

This paper describes a methodology for building a benchmark to evaluate automatic music transcription tools, i.e., softwares that can extract music information from digital audio signals. There are numerous applications to these tools, like data acquisition for music virtual libraries and computer-aided music learning for instance. The main purpose of this benchmark is to present a method to ra...

This paper reports a collective reflection led in our team about conceptual graph benchmarks. We tackle four issues for which agreement should be obtained before benchmarks can be built: what are the fragments of CGs considered? How is information exchanged? What are the problems to be solved? What kinds of tool properties are evaluated by the benchmarks? We define a basic building block built ...

Six months of HECToR dCSE funding was given to implement mixed-mode OpenMP parallelism in CP2K, building on the results of an earlier successful dCSE project. Improved scalability of up to 8 times as many cores was demonstrated for a small benchmark, and a larger, inhomogeneous benchmark was shown to scale up to 9000+ cores. An increase in peak performance of up to 60% was also realised on HECT...