Preparation of high-activity coal char-based catalysts from high metals containing coal gangue and lignite for catalytic decomposition of biomass tar

The potential of using high metals containing coal gangue and lignite to prepare high-activity coal char-based catalysts is investigated for effective biomass tar decomposition. Loose structure and rough surface are formed for these char-based catalysts with heterogeneous distribution of a large number of inorganic particles. In the biomass tar decomposition, the performance of the coal char-based catalysts is significantly influenced by the content of the metals in the raw materials and coal gangue char (GC) with the ash content as high as 50.80% exhibits the highest activity in this work. A high biomass tar conversion efficiency of 93.5% is achieved at 800 °C along with a significant increase in the fuel gas product. During the five-time consecutive tests, the catalytic performance of GC increases a little at the second or third times reuse and remains relatively stable, showing the remarkable stability of the catalyst in biomass tar decomposition applications.     

Application of web embedded system and machine learning in english corpus vocabulary recognition

Built-in applications built on a stand-alone device, TCP / IP network and interconnected are a need for high integration with other systems. The system provided through Web services interconnects service-oriented distributed architecture. The TCP / IP network is widely employed to integrate business applications. This integration is still not provided through the embedded application. The applications connected to the Internet are an especially difficult problem in embedded systems to interpret the sensor data. Real-time sensor function generates a training/classification result for IoT application selected, customized, or data structure design. It has an integrated hardware/software system to achieve the continuous training and real-time data analysis and re-training of Machine Learning (ML) algorithm. World of English native speakers on top of all, this is the database of words that have been separated from the local and non-collection English. It also reported a variety of methods that are used in the English vocabulary recognition system. Please check the study of learners of mediation based on the part of the corpus. Students, in writing, too much-advanced technology and general vocabulary. These students, publicly their discourse in and contributed to the professional corpus of "existence" I mentioned that there is a professional writer, is better. To stimulate the different means of integration, it evaluated several network technology today, discussing the balance between the use of shared with this integration in the adaptability and built-in the field of Web network technology of today.     

基于卓越工程师教育的频率特性分析课堂教学研究

频率特性分析在工程应用中具有重要的作用,在电路分析、模拟电子技术、信号与系统、自动控制理论等相关课程中都涉及到相关章节内容,在不同课程中如何根据工程应用和学生学习阶段把握具体的讲解内容和讲解方式非常重要。本文从频率特性的求解方法和具体物理意义角度开展在不同课程中讲解的方法,从时域和频域角度分别讨论其物理意义和具体的分析方法。通过渐进深化的教学过程和教学方法不断提高学生的知识掌握和应用技能,提高学生的工程意识、工程素质和工程创新能力,强化学生对于频率特性课程知识的综合应用能力。     

Simulation is essential for embedded control systems with task jitter

Sampling or task jitter affects the performance of digital control systems but realistic simulation of this effect has not been possible to date. Our previous work has developed a novel method to simulate sampling jitter in MATLAB/Simulink simulation software where the jitter is generated randomly. What has been missing is a way to capture sampling jitter from a target platform and then feed this timing information into the simulation. This paper presents a low-cost and novel solution to these problems. The method uses an Arduino board to capture task jitter from two different hardware platforms with multiple stressing conditions. Then the recorded performance data is used to drive realistic simulations of a control system. Measurement shows that the task jitter data does not follow any specific random distribution such as Gaussian or Uniform. Furthermore, very occasional timing patterns, which may not be picked up while testing a real system, can result in extreme controller responses. This novel method allows comparisons of different platforms and reduces the effort required to choose the most appropriate platform for full implementation.

     

毫米波三维异质异构集成技术的进展与应用

三维异质异构集成技术是实现电子信息系统向着微型化、高效能、高整合、低功耗及低成本方向发展的最重要方法,也是决定信息化平台中微电子和微纳系统领域未来发展的一项核心高技术。文章详细介绍了毫米波频段三维异质异构集成技术的优势、近年来的发展趋势以及面临的挑战。利用硅基MEMS 光敏复合薄膜多层布线工艺可实现异质芯片的低损耗互连,同时三维集成高性能封装滤波器、高辐射效率封装天线等无源元件,还能很好地处理布线间的电磁兼容和芯片间的屏蔽问题。最后介绍了一款新型毫米波三维异质异构集成雷达及其在远距离生命体征探测方面的应用。     

小型核桃脱壳分选一体机的设计

核桃不仅营养价值极高,而且核桃壳的药用价值也非常高,国内小企业和家庭在核桃硬壳脱壳加工环节,一般采用人工破壳取仁的方式,这种方式劳动强度大,人工成本高且不卫生;针对这个问题设计了一款小型的硬壳脱壳,壳仁分离分选的机器来提高生产效率,减少成本,提高收入。     

Down-link OFDRMA communications

Wireless Networks - Orthogonal frequency-division multiplexing with random multiple access (OFDRMA) is discussed for down-link communications, whereby a single base-station transmits information...     

Stability enhancement of polypyrrole thin film ammonia sensor by camphor sulfonic acid dopant

Journal of Materials Science: Materials in Electronics - The main weakness of polymer gas sensors is its stability. Here, we report stability enhancement of a 100 nm polypyrrole (PPy) thin...     

基于阶段注意力机制的电力线提取算法

电力系统维护是电力系统稳定运行的重要保障，应用智能算法的无人机电力巡检则为电力系统维护提供便捷。电力线提取是自主电力巡检以及保障飞行器低空飞行安全的关键技术，结合深度学习理论进行电力线提取是电力巡检的重要突破点。本文将深度学习方法用于电力线提取任务，结合电力线图像特点嵌入改进的图像输入策略和注意力模块，提出一种基于阶段注意力机制的电力线提取模型（SA-Unet）。本文提出的SA-Unet模型编码阶段采用阶段输入融合策略（Stage input fusion strategy， SIFS），充分利用图像的多尺度信息减少空间位置信息丢失。解码阶段通过嵌入阶段注意力模块（Stage attention module，SAM）聚焦电力线特征，从大量信息中快速筛选出高价值信息。实验结果表明，该方法在复杂背景的多场景中具有良好的性能。     

A blind dual color images watermarking based on quaternion singular value decomposition

Multimedia Tools and Applications - With the rapid development of the Internet, the color digital image copyright protection is facing severe challenges. Simultaneously, the color digital images...