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。     

Double pyrovanadates CaMgV2O7: Formation mechanism,phase structure,and thermodynamic properties

A double pyrovanadate CaMgV₂O₇ sample was synthesized via a facile solid-state route under an air atmosphere. The nonequilibrium formation pathways of the CaMgV₂O₇ were investigated via powder X-ray diffraction. A multistep reactions path (metavanadates–pyrovanadates–double pyrovanadate CaMgV₂O₇) was proposed to describe the formation of the CaMgV₂O₇ considering the thermodynamic and kinetic factors. The cell unit parameters of the CaMgV₂O₇ sample indicated the crystallization according to a monoclinic system with space group P12/c1(14), and the lattice parameters of a = 6.756 Å, b = 14.495 Å, c = 11.253 Å, β = 99.12, and V = 108.806 Å³. X-ray photoelectron spectroscopy also confirmed the +5 oxidation state vanadium in CaMgV₂O₇. The endothermic effects at 1033 and 1143 K were related to the incongruent melting and liquidus temperatures of CaMgV₂O₇, respectively. The comprehensive thermodynamic properties of CaMgV₂O₇ were established in both low- and high-temperature regions, utilizing a physical property measurement system and multi-high-temperature calorimetry (96 lines). The heat capacity (200 J mol K⁻¹) and entropy (198 J mol K⁻¹) at 298.15 K were computed based on the low-temperature heat capacity values, and the enthalpy of formation at 298.15 K was also estimated. The fitted high-temperature capacity can be used to obtain the changes in the enthalpy, entropy, and Gibbs free energy. This study is part of building a reliable thermodynamic database of the CaO–MgO–V₂O₅ system.     

一种可传输轨道角动量的螺旋光子晶体光纤北大核心

设计了一种基于阿基米德螺线的新型螺旋光子晶体光纤,该光纤以二氧化硅为基底材料,包层由24个螺旋臂组成,每个螺旋臂包含11个小空气孔,纤芯设有大空气孔,包层与纤芯中间的环形区域用于传输轨道角动量模式。该结构在1300~1800 nm波段上可支持22种轨道角动量模式稳定传输,在1550 nm波长下,有效折射率差最高可达2.89×10^(-3),色散系数最低可达66.4 ps/(nm·km),非线性系数最低可达2.17 W^(-1)·km^(-1),且1500~1600 nm波段上的色散值变化均小于15.15 ps/(nm·km)。此螺旋光子晶体光纤不仅结构简单,且具有低非线性、色散平坦的性能,为螺旋光子晶体光纤的设计提供了思路。     

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.     

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.     

日本の寒地，北海道における2030年代の水稲生育への温暖化の影響予測とその対応(日语原文)

北海道では1980年代から2010年代まで，水稲圃場栽培期間である5–9月の気温は年代とともに上昇した。そこで，直近の2010年代（2010—2019年平均）と比べて， 2つの2030年代の予測気象から，既報の関係式より水稲生育を予測した。その結果，2030年代では2010年代に比べ，限界移植日（移植早限）が水稲栽培17地域の平均で8～9日早い。また，早限出穂期が1～5日早く，晩限出穂期が1～5日遅く，安全出穂期間が2～10日長い。出穂期は1～3日早い。出穂期から晩限出穂まで2～9日長いため，遅延型冷害の発生がやや少ない。生育期別気象は，出穂前24日以降30日間では生育が早いため平均気温が同じかやや低い。出穂前10日以降40日間および出穂期以降40日間では平均気温がやや高く，日射量はやや少ない。そのため，玄米収量は96～98％とやや低く，潜在収量性を示す気候登熟量示数は同じである。障害不稔発生に関係する穂ばらみ期冷害危険期の平均気温はわずかに低いかほぼ同じであるため，冷害発生の危険性は残る。一方，不稔発生をもたらす低温域の出現頻度には，地域間で差異がある。精米蛋白質含有率は同じであるが，アミロース含有率はやや低く，やや良食味である。米粒外観品質では被害粒歩合と着色粒歩合は一定の傾向がなく，未熟粒歩合はやや高い。精米白度は同じであるが，玄米白度はやや高い。以上の予測に対する技術的対応方向を示した。     

No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.