基于数据质量评价的目标估计

针对目标估计过程需要大量人工参与、自动化程度低的问题，提出了基于数据质量评价的目标估计方法。利用目标数据质量评价方法，对不同传感器得到的目标数据质量进行科学、有效的测度和评价，并根据质量得分动态调整各数据源在目标估计过程中所占的权重，从而减少人工干预，提高目标估计效能。仿真试验结果证明了该方法的有效性。     

高面板坝全寿命周期变形控制方法及应用

高面板坝的变形对面板的安全运行有着特别重要的影响，国内外已建的高面板坝工程中，因坝体变形大导致防渗面板挤压破损，坝体渗漏量大的实例较多，不得不降低水库水位进行修复处理，造成较大的经济损失乃至给大坝的长期运行留下安全隐患。通过发生挤压破损的实例分析，发现变形控制缺乏系统性是发生面板挤压破损的主要因素，为预防面板破损，系统提出了“控制坝体总变形，转化有害变形，适应纵向变形”的坝体变形控制方法，并在使用软硬岩混合料筑坝的董箐面板堆石坝中得到的应用，取得了良好效果，该工程运行至今达十余年，未见面板有挤压破损迹象，该方法对建设200 m以上乃至300 m级超高面板坝具有重要借鉴意义。     

高效液相色谱法测定化妆品中依克多因的含量

建立高效液相色谱法测定化妆品中依克多因的分析方法,采用Agilent Poroshell 120 EC-C₁₈色谱柱（100 mm×3.0 mm,2.7μm）分离,以甲醇和p H为3.0的40 mmol/L磷酸二氢钠-10 mmol/L 1-庚烷磺酸钠缓冲溶液梯度洗脱,流速0.8 m L/min,柱温30℃,检测波长210 nm。采用外标法定量测定化妆品中的依克多因含量。结果表明,依克多因在5～800 mg/L的质量浓度范围内呈现良好线性关系,相关系数为0.999 8,方法的检出限和定量限分别为0.3和1.0 mg/L。该方法具有分离效率高、分析时间短、节省溶剂等优点,解决了依克多因在C₁₈色谱柱上保留弱的问题。     

机器翻译译文质量估计综述

机器翻译译文质量估计(Quality Estimation,QE)是指在不需要人工参考译文的条件下,估计机器翻译系统产生的译文的质量,对机器翻译研究和应用具有很重要的价值。机器翻译译文质量估计经过最近几年的发展,取得了丰富的研究成果。该文首先介绍了机器翻译译文质量估计的背景与意义;然后详细介绍了句子级QE、单词级QE、文档级QE的具体任务目标、评价指标等内容,进一步概括了QE方法发展的三个阶段: 基于特征工程和机器学习的QE方法阶段,基于深度学习的QE方法阶段,融入预训练模型的QE方法阶段,并介绍了每一阶段中的代表性研究工作;最后分析了目前的研究现状及不足,并对未来QE方法的研究及发展方向进行了展望。     

A blockchain-based audit approach for encrypted data in federated learning

The development of data-driven artificial intelligence technology has given birth to a variety of big data applications. Data has become an essential factor to improve these applications. Federated learning, a privacy-preserving machine learning method, is proposed to leverage data from different data owners. It is typically used in conjunction with cryptographic methods, in which data owners train the global model by sharing encrypted model updates. However, data encryption makes it difficult to identify the quality of these model updates. Malicious data owners may launch attacks such as data poisoning and free-riding. To defend against such attacks, it is necessary to find an approach to audit encrypted model updates. In this paper, we propose a blockchain-based audit approach for encrypted gradients. It uses a behavior chain to record the encrypted gradients from data owners, and an audit chain to evaluate the gradients’ quality. Specifically, we propose a privacy-preserving homomorphic noise mechanism in which the noise of each gradient sums to zero after aggregation, ensuring the availability of aggregated gradient. In addition, we design a joint audit algorithm that can locate malicious data owners without decrypting individual gradients. Through security analysis and experimental evaluation, we demonstrate that our approach can defend against malicious gradient attacks in federated learning.     

Prediction of fish quality level with machine learning

In this study, sea bream, sea bass, anchovy and trout were captured and recorded using a digital camera during refrigerated storage for 7 days. In addition, their total viable counts (TVC) were determined on a daily basis. Based on the TVC, each fish was classified as ‘fresh’ when it was <5 log cfu per g, and as ‘not fresh’ when it was >7 log cfu per g. They were uploaded on a web-based machine learning software called Teachable Machine (TM), which was trained about the pupils and heads of the fish. In addition, images of each species from different angles were uploaded to the software in order to ensure the recognition of fish species by TM. The data of the study indicated that the TM was able to distinguish fish species with high accuracy rates and achieved over 86% success in estimating the freshness of the fish species tested.     

Predictive process mapping for laser powder bed fusion: A review of existing analytical solutions

One of the main challenges in the laser powder bed fusion (LPBF) process is making dense and defect-free components. These porosity defects are dependent upon the melt pool geometry and the processing conditions. Power-velocity (PV) processing maps can aid in visualizing the effects of LPBF processing variables and mapping different defect regimes such as lack-of-fusion, under-melting, balling, and keyholing. This work presents an assessment of existing analytical equations and models that provide an estimate of the melt pool geometry as a function of material properties. The melt pool equations are then combined with defect criteria to provide a quick approximation of the PV processing maps for a variety of materials. Finally, the predictions of these processing maps are compared with experimental data from the literature. The predictive processing maps can be computed quickly and can be coupled with dimensionless numbers and high-throughput (HT) experiments for validation. The present work provides a boundary framework for designing the optimal processing parameters for new metals and alloys based on existing analytical solutions.     

Fresh beef tumbling at different post-mortem times to improve tenderness and proteolytic features of M. longissimus lumborum

The aim of this study was to determine the effects of tumbling at different post-mortem times on the proteolytic features and quality attributes of beef loins (M. longissimus lumborum). Loins (n = 12) were cut into 4 sections and assigned to tumbling at 1, 6 or 11 days post-mortem or non-tumbled control. Upon tumbling, additional ageing was applied to a common post-mortem time of 16 days. In general, tumbling had no considerable impacts on water-holding ability of samples. Tumbling resulted in an immediate decrease in shear force values (WBSF) of beef samples. Tumbling at 1 day post-mortem with no ageing had similar WBSF compared to the non-tumbled controls at 16 days (P > 0.05). With ageing, tumbling increased amounts of protein degradation, myofibrillar fragmentation and calpain-1 autolysis of samples. These results suggest that early post-mortem tumbling coupled with ageing can synergistically impact the tenderness development of beef loins and shorten the necessary ageing period.     

超高分子量聚乙烯纤维增强中空蜂窝模压复合材料性能研究

为研制车船等壳体所用的轻质、高强复合板材,选用超高分子量聚乙烯(UHMWPE)短纤维纱,制备成单层经纬为120根/(10 cm)的平纹组织,采用多组经纱持续更替交织层的方法制成2L(1+0)型、4L(2+1)型、6L(3+2)型3种多层角联锁结构织物,采用扦插芯棒、模压成型方法制成菱形蜂窝状的热固性环氧树脂基中空板,并与2块真空吸液法制成的面板组成“三合一”复合板,同时测定了复合板材的结构特征及其平拉、平压和弯曲性能。结果表明:3种类型复合板的密度均远小于水的密度,其中6L(3+2)型最小,为0.48 g/cm³;复合板层数越多,环氧树脂越难渗透尤其是在中空板菱形交叉点处,复合板平拉、平压、抗弯曲强度则呈现递增,制成的6L(3+2)型复合板试样平压强度可达到1.03 MPa。