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1.
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。 相似文献
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《International Journal of Hydrogen Energy》2022,47(49):21231-21240
To explore the feasibility and related mechanism of MFC biosensor for wastewater detection under the action of combined heavy metals. Cyclic voltammetry (CV) and scanning electrochemical impedance spectroscopy (EIS) were used to explore the related bioelectrochemical process. The response of the reactor to single/combined heavy metals, low/high heavy metal concentrations, and the differences in ohmic resistance (Rs) and charge transfer resistance (Rct) were investigated using Ni as the core heavy metal and the combined action of Cd, Cu and Zn. The results indicated that there was a linear relationship between the concentration and output voltage of the MFC biosensor under the action of combined heavy metals (R2 = 0.8803–0.973). However, the internal resistance (Rint) of the MFC biosensor under the action of single heavy metal was far less than that of the combined heavy metal group, and the power density (19.849 W m?3) was 4 times that of the combined heavy metal group (3.109–4.589 W m?3). The Rs of the biosensors in the combined heavy metal group were 0.868Ω and 0.860, which were higher than 0.768Ω of the single heavy metal sensor. With the increase of the concentration of heavy metals in the influent, the increase of Rct was more obvious in the combined group, while the Rs in the single group significantly increased (P < 0.05). The results imply that it is possible for MFC biosensors to be used in the detection of actual water polluted by various heavy metals, but the biosensor performance is mainly limited by Rct, which needs to be further improved. 相似文献
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甫沙4井位于塔里木盆地塔西南坳陷昆仑山前冲断带的柯东构造带上,北部和东部分别发育有柯克亚和柯东1井油气田。为研究甫沙4井原油来源与充注过程,对原油样品和连续抽提后的含油砂样各组分(游离态、束缚态、包裹体)进行GC、GC?MS和 GC?IRMS分析,与柯克亚凝析油气田油样进行油—油对比。结果表明:甫沙4井晚期充注原油组分具有C29?32重排藿烷、重排甾烷和Ts相对含量高,C27?29甾烷ααα 20R分布呈反“L”型,以及正构烷烃单体碳同位素值较低等特征,与柯克亚凝析油气田来源于二叠系普司格组(P2?3p)烃源岩的主体原油(I类)地球化学特征一致。而早期充注的原油组分具有重排藿烷、重排甾烷和Ts相对含量较低,C27?29甾烷ααα 20R分布呈“V”型,以及正构烷烃单体碳同位素值较高等特征,与柯克亚凝析油气田来源于中—下侏罗统湖相泥岩的II类原油地球化学特征一致。甫沙4井经历3个阶段成藏过程:①在上新世,二叠系烃源岩于生油晚期阶段生成的I类原油运移至柯克亚构造带或柯东构造带深部形成油藏;②在更新世早期,侏罗系烃源岩于生油早—中期生成的II类原油运移至甫沙4井白垩系储层;③在第四纪,强烈的构造作用使深部I类原油沿断裂调整进入甫沙4井白垩系储层。最终造成甫沙4井白垩系储层II类原油先充注,I类原油后充注的特殊现象。 相似文献
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《Journal of the European Ceramic Society》2022,42(3):1014-1022
In this work we have investigated the effect of the solvent during the processing of SrFe12O19 platelet-based permanent magnets by cold sintering process (CSP) plus a post-thermal treatment. Several organic solvents: glacial acetic acid, oleic acid and oleylamine have been analyzed, optimizing the CSP temperatures at 190?270 °C, under pressures of 375?670 MPa and 6?50 wt% of solvent. Modifications in the morphological and structural properties are identified depending on the solvent, which impacts on the magnetic response. Independently of the solvent, the mechanical integrity of ferrite magnets obtained by CSP is improved by a post-annealing at 1100 °C for 2 h, resulting in relative densities around 92 % with an average grain size of 1 μm and a fraction of SrFe12O19 phase >91 %. HC ≥ 2.1 kOe and MS of 73 emu/g are obtained in the final sintered ceramic magnets, exhibiting the highest HC value of 2.8 kOe for the magnet sintered using glacial acetic acid. 相似文献
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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。 相似文献
8.
《Digital Communications & Networks》2022,8(5):614-624
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. 相似文献
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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. 相似文献
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