Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.     

Oxide-Scale Evolution on a New Ni–Fe-Based Superalloy at High Temperature

Oxidation of Metals - The isothermal oxidation behavior and oxide-scale evolution on a newly developed Ni–Fe-based superalloy were investigated. Three oxidation stages were generally...     

Regulation of sensory nerve conduction velocity of human bodies responding to annual temperature variations in natural environments

The extensive research interests in environmental temperature can be linked to human productivity / performance as well as comfort and health; while the mechanisms of physiological indices responding to temperature variations remain incompletely understood. This study adopted a physiological sensory nerve conduction velocity (SCV) as a temperature‐sensitive biomarker to explore the thermoregulatory mechanisms of human responding to annual temperatures. The measurements of subjects’ SCV (over 600 samples) were conducted in a naturally ventilated environment over all four seasons. The results showed a positive correlation between SCV and annual temperatures and a Boltzmann model was adopted to depict the S‐shaped trend of SCV with operative temperatures from 5°C to 40°C. The SCV increased linearly with operative temperatures from 14.28°C to 20.5°C and responded sensitively for 10.19°C‐24.59°C, while tended to be stable beyond that. The subjects’ thermal sensations were linearly related to SCV, elaborating the relation between human physiological regulations and subjective thermal perception variations. The findings reveal the body SCV regulatory characteristics in different operative temperature intervals, thereby giving a deeper insight into human autonomic thermoregulation and benefiting for built environment designs, meantime minimizing the temperature‐invoked risks to human health and well‐being.     

增效过磷酸钙的增效机制及其对玉米生长的影响

利用猪毛、风化煤和腐植酸钠的水解液为增效剂制备了一种增效过磷酸钙,探讨了增效过磷酸钙的增效机制及其对玉米生长的影响。结果表明,蒸馏水浸提条件下,增效过磷酸钙能减缓水溶磷的释放,具备较高的pH值缓冲性。与普通过磷酸钙相比,增效过磷酸钙处理的玉米生物量平均增加了41.9%,吸磷量和吸钙量分别增加了61.7%和27.8%,根系活力增加了24.3%。该研究结果对过磷酸钙生产的技术改进具有指导意义。     

应届化纤专业人才的工程实践能力培养与实践

随着时代的变化,聚酯化纤企业也在迅速地发生着变化,与此同时对化纤应届生人才需求也提出了新的变化。为了应对这种变化,大连工业大学对化纤人才培养主要体现在积极地针对化纤企业的工程特点去培养学生工程实践能力,以适应是时代的需求。在打造大连工业大学高分子材料与工程专业特色化纤品牌的同时,学生可以得到更好的就业机会与职业发展道路,企业可以得所需化纤人才。