An improved generative adversarial network for translating clothes from the human body to tiled image

Neural Computing and Applications - Nowadays, purchasing the products similar to the styles of stars’ products has become a new trend in e-commerce platforms. Clothing transaction constitutes...     

μC／OS—Ⅲ在Cortex—M3处理器上的移植

为了将μC／OS-Ⅲ移植到Cortex—M3处理器上,选用RealView MDK作为软件开发平台,针对Cortex—M3处理器特性编写了移植所需的C语言和汇编语言源代码,并验证了移植的正确性。移植后的μC／OS-Ⅲ能够稳定运行于Cortex～M3处理器上。该移植对大部分Cortex—M3处理器具有通用性,对其他架构处理器的μC／OS-Ⅲ移植具有参考作用。     

MapReduce Workload Modeling with Statistical Approach

Large-scale data-intensive cloud computing with the MapReduce framework is becoming pervasive for the core business of many academic, government, and industrial organizations. Hadoop, a state-of-the-art open source project, is by far the most successful realization of MapReduce framework. While MapReduce is easy- to-use, efficient and reliable for data-intensive computations, the excessive configuration parameters in Hadoop impose unexpected challenges on running various workloads with a Hadoop cluster effectively. Consequently, developers who have less experience with the Hadoop configuration system may devote a significant effort to write an application with poor performance, either because they have no idea how these configurations would influence the performance, or because they are not even aware that these configurations exist. There is a pressing need for comprehensive analysis and performance modeling to ease MapReduce application development and guide performance optimization under different Hadoop configurations. In this paper, we propose a statistical analysis approach to identify the relationships among workload characteristics, Hadoop configurations and workload performance. We apply principal component analysis and cluster analysis to 45 different metrics, which derive relationships between workload characteristics and corresponding performance under different Hadoop configurations. Regression models are also constructed that attempt to predict the performance of various workloads under different Hadoop configurations. Several non-intuitive relationships between workload characteristics and performance are revealed through our analysis and the experimental results demonstrate that our regression models accurately predict the performance of MapReduce workloads under different Hadoop configurations.     

多媒体教学中的问题与对策

随着计算机技术及多媒体技术的发展,多媒体在教学中的应用越来越广泛,多媒体有着传统教学媒体不具备的独特优势,但在实际教学中也有不足之处,在教学中必须根据实际情况灵活运用多媒体才能取得理想的教学效果。     

压力机八杆内滑块机构的优化设计

提出用拉深区速度波动量、拉深速度、拉深深度、拉深角为评价压力机八杆内滑块机构性能优劣的指标。根据机构优化设计理论，用步长搜索法对其进行了优化设计，优化出多组以上指标均好于原机构的方案，并且最大压力角比原机构减小很多，其运动学性能超过原机构水平。     

不同基质配比对银毛野牡丹扦插的影响

银毛野牡丹是优良的园林观赏性植物,但是繁殖有性结实率低。通过为期30天的扦插试验,对比不同基质（原土、草炭土、蛭石、珍珠岩）配比对银毛野牡丹插穗生长的影响,分析插穗生根时间、生根数目、最长根长、生根率、生长状态以及基质变化,找出适合其生长发育的优良基质,为银毛野牡丹的繁殖提供技术支撑。研究表明：试验组T8（原土：细沙：草炭土：蛭石：珍珠岩=1：1：2：1：1）的插穗生根率、最长根长、插穗长势为最佳,试验组T2（草炭土）效果次之,在条件有限的情况下可以作为备用方案以供生产所需。     

TA15合金的热变形行为及加工图

研究了TA15合金的热模拟压缩实验。结果表明：变形温度的升高和应变速率的减小使峰值应力和稳态应力显著降低，变形温度会影响进入稳态流动所需变形量。以热模拟压缩实验为基础，建立的加工图表明：TA15合金高温变形时存在2个非稳定区域，一个是变形温度1300K以上和应变速率10．0s^-1以上的区域，另一个是变形温度1200K以下和应变速率0．006s^-1～1．995s^-1之间的区域。同时，建立的TA15合金高温变形时的流动应力模型表征了变形温度、应变速率和变形程度对流动应力的影响，模型的计算精度较高。     

基于改进的CDKF锂电池SOC估计方法

准确估算荷电状态(SOC)可以为电池之间的均衡管理提供依据,延长锂电池组整体的使用寿命.针对中心差分卡尔曼滤波算法(CDKF)存在较大线性误差的问题,提出一种改进的CDKF算法.在原算法中引入迭代滤波思想,多次利用测量信息更新状态量估算值,使得观测信息不断迭代更新,基于LM优化方法不断修正协方差矩阵,有效减小了线性误差.首先基于二阶阻容(RC)电路单元模型,选择最小二乘参数辨识方法,辨识出模型阻容参数;然后进行HPPC实验,验证电池等效模型的准确性;最后分别在恒流放电和动态工况下应用改进后的CDKF算法对电池SOC和电压进行估计,并将估计结果与CDKF算法进行比较.两种工况下验证结果表明改进后的CDKF算法精度更高,SOC估计精度可提升1.16％,最大估计误差小于1.7％,算法收敛时间也比原算法短,改进后的CDKF算法在估计精度和鲁棒性方面均有所提升,更具有应用优势.     

定频房间空调器APF的不确定度评定方法研究

新版房间空调器的能效标准GB 21455-2019《房间空气调节器能效限定值及能效等级》中将定频热泵型房间空调器能效等级评价指标调整为全年能源消耗效率APF值,为了提高检测质量,评定APF的不确定度显得尤为重要.通过空气焓值法对空调器性能进行测试,对APF的计算、测量以及不确定度的评估等进行了分析,得到APF的相对扩展不确定度为1.96％,其中额定制冷量引入的不确定度分量最大,占比达75.11％.以额定制冷工况为例,对额定制冷量影响较大的测量参数为室内侧进风湿球温度和室内侧出风湿球温度,不确定度分量占比分别达51.99％和36.42％.     

Synthesis and characterization of caprolactone based polyurethane with degradable and antifouling performance

In this work,a degradable polyurethane composed of caprolactone(CL)and L-Lactide(LLA)as soft seg-ments,and 4,4'-methylenebis(cyclohexyl isocyanate)(H12MDI)and polytetramethylene ether glycol(PTMEG)as hard segments,was prepared.Hydrolytic degradation experiment revealed that the degrad-able polyurethane(PU)could be degraded in artificial seawater.It also showed that caprolactone-co-polyurethane(CL-PU)copolymer with higher crystallinity degraded much slower in artificial seawater.However,the introduction of LLA resulted in an increase in the hydrophilicity and reduction in the crys-tallinity of degradable PU,as demonstrated by the contact angle analysis.The result of the scanning elec-tron microscope showed that the surface of degradable PU renewed under static condition.Moreover,degradable PU was able to be used as a carrier,and it controlled the release rate of 4,5-dichloro-2-octyl-isothiazolone(DCOIT).The anti-diatom(Navicula incerta)test demonstrated that the(caprolactone-co-L-lactide)-co-polyurethane 4(CL/LAx-PU4)with DCOIT contents prevented the adhe-sion of diatom Navicula incerta(88.37％reduction)due to their self-polishing and the release of antifou-lants.Therefore,the degradable PU consisted of CL,LLA,and DCOIT could be a durable resin with good antifouling activity for the application in the marine anti-biofouling field.