Coal seam thickness prediction is crucial in coal mine design and coal mining. In order to improve the prediction accuracy, an improved Kriging interpolation method on the basis of efficient data and Radial Basis Function (RBF-Kriging) is firstly proposed to interpolate the cutting data that is obtained in pre-mining, especially at the edge of the geological surface of coal seam by taking into account the spatial structure and the efficient spatial range, ensuring the integrity of the edge data during the movement of structural elements. Subsequently, a structural element transition probability based Gaussian process progression (STTP-GPR) method is proposed to predict the coal seam thickness from the interpolated coal seam data. The experimental results demonstrated that the proposed STTP-GPR method has superior performance in coal seam thickness prediction. The average absolute error of thickness prediction for thin coal seams is 0.025 m, which significantly improves the prediction accuracy in comparison to the existing back propagation (BP) neural networks, support vector machine, and Gaussian process regression methods.

Writing and editing mathematical expressions with complicated structures in computer system is difficult and time-consuming. To address this, we proposed MathAssist, a mathematical expression autocomplete technique that recommends full formulas in real-time based on the user’s input strokes. Our technique identifies user’s input purpose by matching the structure of the current user input to the structure of formulas in a database. To facilitate such process, we propose a novel tree-based formalization to represent formula. In comparison to a mathematical expression recognition algorithm (SRD) and a commercial MicroSoft Ink Equation (InkEqu), our approach outperformed both of them on task completion time (reduced by 37.14% and 37.58%) and accuracy (32.78% and 10.55% higher). We also discuss our findings in using autocomplete to assist formula editing.

Virtual reality is an important technology of computer area. This paper built a 3D mechanized mining system via applying technologies of virtual reality, 3DS MAX and Quest 3D. Full scene roaming, interaction control and devices simulations are designed and realized in the VR system. Moreover, behavior modeling and interactive control of coal cutter, hydraulic support and scraper conveyer are achieved. This paper Used hierarchical bounding volumes and hierarchical bounding balls algorithm to solve the collision detection in virtual control. The system proposed a developing model of 3D coal mining face. It can promote the safety of coal mine production.

Hospitalized adolescents often encounter difficulties in emotional communication due to the mismatch between their developmental needs and adult-centered clinical environments. While prior work has explored psychological and technological interventions, less is known about adolescents’ own experiences and acceptable forms of support. We present a qualitative study using questionnaires and semi-structured interviews to examine adolescents’ emotional communication in hospital settings. Our analysis reveals ambivalent social connection, indirect and mediated emotional communication, and adolescents’ expectations for emotional expression tools. Based on these findings, we discuss implications for designing low-intrusion emotional support tools that align with adolescents’ emotional needs in hospital settings.