Development of bond strength model for FRP plates using back‐propagation algorithm

For the flexural reinforcement of bridge and building structure, synthetic materials whose dynamic properties are superior and those containing the merit of corrosion‐proof are widely used as the substitute for a steel plate. Since FRP plate has improved bond strength owing to the fibers externally adhering to the plate, many researches regarding the bond strength improvement have been substantially performed. To search out such bond strength improvement, previous researchers had ever examined the bond strength of FRP plate through their experiment by setting up many variables. However, since the experiment for a research on the bond strength takes much of expenditure for setting up the equipment and is time‐consuming, also is difficult to be carried out, it is limitedly conducted. The purpose of this study was to develop the most suitable artificial neural network model by application of various neural network models and algorithm to the data of the bond strength experiment conducted by previous researchers. Many variables were used as input layers against bond strength: depth, width, modulus of elasticity, tensile strength of FRP plate and the compressive strength, tensile strength, and width of concrete. The developed artificial neural network model has been applied back‐propagation, and its error was learned to be converged within the range of 0.001. Besides, the process for the over‐fitting problem has been dissolved by Bayesian technique. The verification on the developed model was executed by comparison with the test results of bond strength made by other previous researchers, which was never been utilized to the learning as yet. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 5119–5127, 2006     

Bathymetry and siltation rate for Dokan Reservoir,Iraq

The Dokan Reservoir dam is a concrete cylindrical arch with gravity abutments, located on the Lesser Zab River about 60 km from the city of Sulaimani in north‐eastern Iraq. A bathymetric survey was conducted in November 2014 for a period of 10 days, using an echo sounder of 200‐kHz single beam. The survey results indicated an annual average sediment deposition of 3.8 million m³. Thirty‐two sediment samples were collected from the reservoir bed. The ratio of gravel, sand, silt and clay was 15:14:48:23, respectively. The reservoir bed is covered mainly with silt. The sediments are composed of silty clay (77.6%), silty sandy clay (10%), sandy gravely silty clay (1.2%) and gravely sandy silty clay (1%).     

Effects of personal,psychosocial and occupational factors on low back pain severity in workers

Low back pain (LBP) remains the most common work-related musculoskeletal disorder (WMSD). While most of the LBP research has focused on occupational risk factors, other underlying causal mechanisms may exist since not all workers performing the same task develop an injury. Previous research has identified three primary risk factor categories for LBP (occupational, personal and psychosocial factors); however, few studies have investigated the impact of cross categorical risk factor interactions on LBP. The objective of this study was to investigate the effects of occupational, personal and psychosocial factors, and their interactions, on LBP severity in a population of workers currently suffering from LBP. Sixty LBP patients recruited for the study through local physicians and local announcements, completed questionnaires relating to identified occupational, personal and psychosocial risk factors, and completed an Oswestry Disability Index (ODI). Multiple regression models for predicting LBP severity were developed for each risk factor category and for a combined risk factor model (which included factors from all three risk factor categories) that included two-way interactions. Results showed that the final model consisted of both main effects and interaction terms between risk factor categories and had an adjusted R² value of 0.85, a significant improvement over models developed for the individual categories. These findings illustrate the need to consider all three broad categories of risk factors simultaneously in predicting injury status and in developing effective potential intervention efforts.     

黄河宁夏段河道淤积发展趋势分析

对黄河宁夏段河道淤积因素进行了分析论述,根据实测水文资料和径流模型对现状条件下宁夏河道泥沙淤积发展趋势进行了预测分析：2011—2020年年平均来水量可能为260亿～280亿m^3;2011—2020年宁夏河段的淤积情况可能与1986--1995年淤积情况相近,主槽年淤积速率可能为0．02～0．03m,如若支流来沙量大则年均淤积速率将可能达到0．05m,甚至更大一些．     

基于BP神经网络的集装箱箱号识别

提出一种用BP神经网络实现集装箱箱号识别的方法。提出的图像预处理方法对管柱,底面凹凸,脏污物、光线的强弱、倾斜、缺损或模糊有较强的适应性。在BP网络分类器实现时,考虑集装箱箱号的组成特点,采用并行处理方法。在BP算法中,引入动态因子,动态调整学习步长。实践证明利用这种方法来识别装箱箱号,速度快,识别率高,具有较高的实用价值。     

抗病毒类化合物结构与离解速率的关系

为了解决如何筛选出更加有效的抗病毒类化合物的问题,研究了离解速率(k_(off))与抗病毒类药物结构的关系,理论依据是k_(off)常用于评价药物在人体开放性系统中的活性.首先,应用分子描述符软件计算出每个抗病毒类化合物的分子描述符,并使用多元逐步回归分析法、偏最小二乘法和遗传算法3种方法对描述符进行筛选.然后,分别采用支持向量机和BP神经网络方法建立抗病毒类化合物的k_(off)的预测模型,并用测试集对模型进行了验证.结果表明:筛选出了具有良好预测能力的描述符,建立的2个预测模型经验证均合理,对未来抗病毒类药物的研制具有指导意义.     

基于DM365的视频显示的设计

该文基于德州仪器达芬奇技术下的多媒体处理芯片TMS320DM365,研究了其视频处理后端的硬件架构,设计了视频处理后端与TFT-LCD的硬件连接,实现了DM365视频处理后端对视频文件的解码和显示。经测试,视频显示清晰流畅,可应用于便携式多媒体移动终端。     

4102柴油机缸体起皮问题研究

缸体的覆膜砂芯脱壳引起间隙，浇注时铁液钻入其内形成起皮缺陷。砂芯脱壳的原因与制芯设备、制芯材料、制芯工艺有关。解决措施是：①提高覆膜砂的高温性能；②增加砂芯的结壳厚度；③适当降低射砂压力；④调整模具温度；⑤改进制芯机的射砂、排气、加热和冷却系统。     

可调向靠背式测速探头测向方法的实验验证及标定系数研究

为解决流场中速度、方向的测量问题，自行设计了一种新型的可调向靠背式测速探头，本文介绍了此测速探头的测向方法，通过实验验证了此方法的可行性，并对标定系数曲线进行了测试。     

铸轧辊的改进设计

对铸轧辊辊芯的表层处理、辊芯的结构、铸轧辊的装配进行了改进设计 ,提高了铸轧辊的性能 ,延长了使用寿命