Re-identifying beef cattle using improved AlignedReID++

Accurate and continuous identification of individual cattle is crucial to precision farming in recent years.It is also the prerequisite to monitor the individual feed intake and feeding time of beef cattle at medium to long distances over different cameras.However,beef cattle can tend to frequently move and change their feeding position during feeding.Furthermore,the great variations in their head direction and complex environments(light,occlusion,and background)can also lead to some difficulties in the recognition,particularly for the bio-similarities among individual cattle.Among them,AlignedReID++model is characterized by both global and local information for image matching.In particular,the dynamically matching local information(DMLI)algorithm has been introduced into the local branch to automatically align the horizontal local information.In this research,the AlignedReID++model was utilized and improved to achieve the better performance in cattle re-identification(ReID).Initially,triplet attention(TA)modules were integrated into the BottleNecks of ResNet50 Backbone.The feature extraction was then enhanced through cross-dimensional interactions with the minimal computational overhead.Since the TA modules in AlignedReID++baseline model increased the model size and floating point operations(FLOPs)by 0.005 M and 0.05 G,the rank-1 accuracy and mean average precision(mAP)were improved by 1.0 percentage points and 2.94 percentage points,respectively.Specifically,the rank-1 accuracies were outperformed by 0.86 percentage points and 0.12 percentage points,respectively,compared with the convolution block attention module(CBAM)and efficient channel attention(ECA)modules,although 0.94 percentage points were lower than that of squeeze-and-excitation(SE)modules.The mAP metric values were exceeded by 0.22,0.86 and 0.12 percentage points,respectively,compared with the SE,CBAM,and ECA modules.Additionally,the Cross-Entropy Loss function was replaced with the CosFace Loss function in the global branch of baseline model.CosFace Loss and Hard Triplet Loss were jointly employed to train the baseline model for the better identification on the similar individuals.AlignedReID++with CosFace Loss was outperformed the baseline model by 0.24 and 0.92 percentage points in the rank-1 accuracy and mAP,respectively,whereas,AlignedReID++with ArcFace Loss was exceeded by 0.36 and 0.56 percentage points,respectively.The improved model with the TA modules and CosFace Loss was achieved in a rank-1 accuracy of 94.42%,rank-5 accuracy of 98.78%,rank-10 accuracy of 99.34%,mAP of 63.90%,FLOPs of 5.45 G,frames per second(FPS)of 5.64,and model size of 23.78 M.The rank-1 accuracies were exceeded by 1.84,4.72,0.76 and 5.36 percentage points,respectively,compared with the baseline model,part-based convolutional baseline(PCB),multiple granularity network(MGN),and relation-aware global attention(RGA),while the mAP metrics were surpassed 6.42,5.86,4.30 and 7.38 percentage points,respectively.Meanwhile,the rank-1 accuracy was 0.98 percentage points lower than TransReID,but the mAP metric was exceeded by 3.90 percentage points.Moreover,the FLOPs of improved model were only 0.05 G larger than that of baseline model,while smaller than those of PCB,MGN,RGA,and TransReID by 0.68,6.51,25.4,and 16.55 G,respectively.The model size of improved model was 23.78 M,which was smaller than those of the baseline model,PCB,MGN,RGA,and TransReID by 0.03,2.33,45.06,14.53 and 62.85 M,respectively.The inference speed of improved model on a CPU was lower than those of PCB,MGN,and baseline model,but higher than TransReID and RGA.The t-SNE feature embedding visualization demonstrated that the global and local features were achieve in the better intra-class compactness and inter-class variability.Therefore,the improved model can be expected to effectively re-identify the beef cattle in natural environments of breeding farm,in order to monitor the individual feed intake and feeding time.

Application of Fisher method to discriminating earthquakes and explosions using criterion m_b/M_S

We try to give a quantitative and global discrimination function by studying mb/MS data using Fisher method that is a kind of pattern recognition methods. The reliability of the function is also analyzed. The results show that this criterion works well and has a global feature, which can be used as first-level filtering criterions in event identification. The quantitative and linear discrimination function makes it possible to identify events automatically and achieve the goal to react the events quickly and effectively.

Using Different Standardized Methods for Species Identification:A Case Study Using Beaks from Three Ommastrephid Species

The cephalopod beak is a vital hard structure with a stable configuration and has been widely used for the identification of cephalopod species. This study was conducted to determine the best standardization method for identifying different species by measuring 12 morphological variables of the beaks of Illex argentinus, Ommastrephes bartramii, and Dosidicus gigas that were collected by Chinese jigging vessels. To remove the effects of size, these morphometric variables were standardized using three methods. The average ratios of the upper beak morphological variables and upper crest length of O. bartramii and D. gigas were found to be greater than those of I. argentinus. However, for lower beaks, only the average of LRL(lower rostrum length)/LCL(lower crest length), LRW(lower rostrum width)/LCL, and LLWL(lower lateral wall length)/LCL of O. bartramii and D. gigas were greater than those of I. argentinus. The ratios of beak morphological variables and crest length were found to be all significantly different among the three species(P < 0.001). Among the three standardization methods, the correct classification rate of stepwise discriminant analysis(SDA) was the highest using the ratios of beak morphological variables and crest length. Compared with hood length, the correct classification rate was slightly higher when using beak variables standardized by crest length using an allometric model. The correct classification rate of the lower beak was also found to be greater than that of the upper beak. This study indicates that the ratios of beak morphological variables to crest length could be used for interspecies and intraspecies identification. Meanwhile, the lower beak variables were found to be more effective than upper beak variables in classifying beaks found in the stomachs of predators.

A circular zone counting method of identifying a Duffing oscillator state transition and determining the critical value in weak signal detection

Identifying state transition and determining the critical value of the Duffing oscillator are crucial to indicating external signal existence and have a great influence on detection accuracy in weak signal detection. A circular zone counting （CZC） method is proposed in this paper, by combining the Duffing oscillator＇s phase trajectory feature and numerical calculation for quickly and accurately identifying state transition and determining the critical value, to realize a high- efficiency weak signal detection. Detailed model analysis and method construction of the CZC method are introduced. Numerical experiments into the reliability of the proposed CZC method compared with the maximum Lyapunov exponent （MLE） method are carried out. The CZC method is demonstrated to have better detecting ability than the MLE method, and furthermore it is simpler and clearer in calculation to extend to engineering application.

THE QUASI-BOUNDARY VALUE METHOD FOR IDENTIFYING THE INITIAL VALUE OF THE SPACE-TIME FRACTIONAL DIFFUSION EQUATION

In this article,we consider to solve the inverse initial value problem for an inhomogeneous space-time fractional diffusion equation.This problem is ill-posed and the quasi-boundary value method is proposed to deal with this inverse problem and obtain the series expression of the regularized solution for the inverse initial value problem.We prove the error estimates between the regularization solution and the exact solution by using an a priori regularization parameter and an a posteriori regularization parameter choice rule.Some numerical results in one-dimensional case and two-dimensional case show that our method is efficient and stable.

A New Discriminating Experiment on the Invariance Hypothesis of Light Speed

This thesis puts forward a conjecture that, owing to some unknown special character of light, it is impossible to determine whether the speed of light is variable by the interference method. To verify the hypothesis of the invariance of light speed, a new method must be found to take accurate measurement of the infinitesimal change in the travelling time of light. The thesis suggests the adoption of high frequency laser pulse technology to carry out the measurement. On the basis of this idea a new discriminating experiment is proposed to test the hypothesis of the invariance of light speed. The thesis also makes some forecast of the future prospects of this experiment and of the future development of the theory of special relativity.

信息化赋能革命文化资源传播的价值分析

革命文化资源是宝贵的物质财富和精神财富,信息化赋能革命文化资源传播有着极其重要的价值意蕴。信息化虚仿矩阵的温度、数据场域的深度、平台聚合的效度及符号编码的力度拓展了革命文化资源传播的实践时空;信息化符号具象解码、复归记忆之场和两维体验场域增强了革命文化资源传播的政治认同;信息化赋能融情于艺、寄介于景和寓教于游的三重进路拓展了革命文化资源传播的方法。

水稻耐苏打盐碱性鉴定方法的研究进展

盐碱胁迫是影响水稻正常生长发育和产量形成的主要非生物因素之一。我国是世界第三大盐碱土国家,研究水稻耐盐碱性对于保障国家粮食安全具有重要战略意义。本文综述了国内外对水稻耐盐碱性鉴定和分级评价方法,系统介绍了苏打盐碱地分布及类型、苏打盐碱胁迫对水稻产量和品质的影响、水稻耐盐碱性鉴定方法等方面的研究进展,并进一步对水稻耐盐碱鉴定研究和标准规范进行了展望,以期为水稻耐盐碱性研究和耐盐碱水稻选育提供理论依据。

铀矿井降氡优势通风方式研究

本文以矿井通风网络入风段和用风段氡析出规律为出发点,由铀矿通风降氡基本方程导出不同通风方式下铀矿降氡需风量的计算公式,并由入风段有效供风能力导出优势通风方式评价指标,给出铀矿通风降氡方式的判别方法。

基于综合赋权与云熵优化的园区综合能源系统评价

综合能源系统(integrated energy system,IES)作为能源转型中的重要环节已得到越来越多国家的广泛关注。构建一套匹配中国国情的综合能源系统评价体系和评价方法不仅能够为综合能源系统规划后评价打下基础,以此对规划方案进行优劣排序;还能够提高综合能源系统项目的管理水平,在制定统一、完整的综合能源系统综合评价标准时提供参考。为此,首先结合园区IES基本特征以及运行特性,构建包含经济性、可靠性、环保性以及智能友好性4个方面的综合评价指标体系;然后为解决IES在运行中的不确定性问题,对基于传统云物元模型的综合评价体系提出云熵优化,即考虑不同评价者对模糊性的可接受程度;为解决单一赋权方法可能导致的评价结果过于主观或过于客观的问题,选择基于最小鉴别信息原理将决策实验室法与熵权法相结合的综合赋权法,并采用变权法进一步完善综合评价指标;最后通过算例分析,验证所提综合评价体系的科学正确性。

不同干燥方式对柳蒿芽山野菜挥发性风味的影响研究

为研究不同干燥方式对柳蒿芽山野菜中的挥发性风味化合物影响的差异性,采用气相色谱-离子迁移谱联用(GC-IMS)技术对3种不同干燥处理的柳蒿芽样品进行挥发性化合物检测分析。从样品中共检出103种挥发性有机化合物(volatile organic compounds,VOCs);经归一化处理,结合指纹图谱分析,真空冷冻干燥样品中93种VOCs得到了有效的保留,显著高于电热鼓风干燥和自然干燥组,根据气味描述数据库检索可知冷冻干燥对柳蒿芽中的甜香、焦香气味有较好的保留。正交偏最小二乘法判别分析(OPLS-DA)结果筛选出了12种对区分不同干燥方式的柳蒿芽挥发性风味物质贡献较大的变量,分别为十二醛、2-甲基异冰片、1-辛醇、薄荷脑、(E,E)-2,4-庚二烯醛、乙酸冰片酯、香茅醛、DL-2-羟基-4-甲基戊酸乙酯、1-石竹烯、三亚乙基二胺。

超声弹性成像硬度评分法及面积比法鉴别诊断乳腺病变性质的临床研究

目的 探索超声弹性成像硬度评分法及面积比法鉴别诊断乳腺病变性质的临床价值。方法 选择2023年4月至9月来我院就诊的120例乳腺病变患者为试验对象,均进行超声弹性成像面积比法、硬度评分法评估,对比、分析2项评估法在分辨乳腺病变良、恶性中准确性,且用受试者工作特征(ROC)曲线分析单用和联合预测价值。结果 面积比法对恶性病变准确率为86.1%,对良性病变准确率89.3%;硬度评分法对恶性病变准确率为83.3%,对良性病变准确率86.9%。用ROC曲线分析,面积比、硬度评分法、联合早期预测乳腺病变良恶性的曲线下面积(AUC)分别为0.877、0.851、0.974。结论 在诊断乳腺病变时,将超声弹性成像硬度评分法及面积比法联合运用,更利于分辨肿块良恶性。

鹿茸标准鉴别技术进展研究

鹿茸是一种具有重要药用价值的中药材,具有多种功效和广泛的临床应用。然而,由于市场上出现了大量的假冒伪劣产品,对鹿茸的鉴别技术的研究变得十分重要。本文综述了近年来鹿茸的鉴别技术进展,包括传统的鉴别方法以及现代分子生物学和化学分析技术等。同时,还对当前鹿茸鉴别技术的挑战和未来发展方向进行了讨论。

外语教学研究中问卷调查法的应用——如何进行问卷信度、效度和区分度检验

问卷调查法是中小学英语教师在教学研究中收集信息的常用手段,其质量关乎结论的可靠性,因此不仅在编制问卷时需遵循科学严谨的原则,还需借助统计学手段检验其质量。本研究依托“中学生英语阅读品格调查问卷”的试测数据,归纳了问卷结果的量化录入方法,介绍了编码手册的构成,解释了四种问卷数据类型的特点,详述了利用SPSS 23.0进行信度、效度和区分度分析的要求与操作方法。

基于眼动和脑电特征的高速铁路行车调度员疲劳状态判别研究

针对当前高速铁路行车调度员疲劳状态判别方法尚未结合多源信息的优势,提出了一种基于多源信息的高速铁路行车调度员疲劳状态判别方法,在利用支持向量机对眼动和脑电特征进行软分类作为决策层输入的基础上,结合上一时间点疲劳状态判别结果,利用改进的D-S证据理论进行决策层融合得到最终的判别结果。通过采集20名行车调度员的模拟实验数据对模型进行检测,结果表明:改进后的研究方法在疲劳状态判别方面准确率达到93.75%。可以看出,信息融合判别的准确率高于单纯依靠眼动和脑电特征的方法,增加上一时间点的疲劳判别结果有助于提高模型的鲁棒性和可靠性,并且改进的模型对高速铁路行车调度员疲劳状态判别具有有效性。

一种基于图论理论的大尺度连续变形机构构型综合分析方法

针对航空航天领域大尺度连续变形机构构型问题,提出了一种基于图论理论的大尺度连续变形机构构型综合分析方法。首先,分析了大尺度连续变形机构的组成与基本功能,获得了满足机构拓扑结构、约束条件的要求,对变形机构运动链进行了分析,得到了符合条件的运动链,并对其进行了数学描述;其次,选择并分析了运动链的拓扑对称性,利用特征数组的方法得到了判别矩阵,对运动链进行了同构判别,从而得到了可行的多种运动链形式;再次,建立了各运动链的拓扑图,通过筛选得到了最终的拓扑图,去掉该拓扑图的各个构件,得到了拓扑变换子图和相对应的邻接矩阵,对拓扑图进行了同构判别,再通过改变机架与移动副的位置得到了满足要求的12种构型,画出了其相应的机构拓扑图和机构简图;最后,考虑了大尺度连续变形机构的整体稳定性,避免了尺寸过大等因素,对大尺度变形机构进行了构型优选,得到了符合要求的多种新构型。研究结果表明:该方法能够将大尺度连续变形机构抽象为图形式,获得了22种构型,可根据机构变形要求的不同,改变优选依据,从而得到符合不同要求的构型。

基于时空结合的道路交通事故的黑点判别方法

为精准识别道路交通事故黑点,辅助交通事故的防控,提出了一种基于时空结合的交通事故黑点判别方法。以时空重叠率,来衡量道路危险程度;用双曲正切函数拟合时空重叠率的累积频率;将拟合函数最小曲率半径对应的点,规定为临界值;以大于临界值的时空复合点,来判别为事故黑点;对成南(成都—南充)高速第二辖区交警大队收集的交通事故数据,进行实例研究。利用本时空结合的判别方法,从64例有效案例中,共判别出13个事故黑点。结果表明:事故频率法、累积频率曲线法、核密度分析法、时空重叠率法的碰撞预测准确率指标(CPAI)值分别为2.29、2.03、2.03、2.29,这意味着:时空重叠率法具有良好的判别准确性。时空重叠率法同时结合空间和时间维度,增加了黑点判别的可靠性。

基于LDA-MURE模型的背景音乐自适应推荐方法

用户的情绪状态不同,需要的背景音乐也不同,因此提出基于LDA-MURE模型的背景音乐自适应推荐方法。提取背景音乐的音频特征和社会化标签,通过Fisher线性判别分析方法融合上述数据的特征,结合投影变换方法获得不同类别背景音乐的类内离散度和类间离散度。通过现代心理学分析人类情绪的节律周期变化,在此基础上判断用户当前的情绪状态。最后在LDA模型的基础上构建LDA-MURE模型,为用户推荐不同类别的背景音乐。实验结果表明,所提方法的MEA指标值较低、P@N指标值较高、用户满意度较高。

DCVAE与DPC融合的网络入侵检测模型研究

入侵检测是主动防御网络中攻击行为的技术,以往入侵检测模型因正常网络流量与未知攻击内在特征区分度不足,导致对未知攻击识别率不够高,本文设计基于判别条件变分自编码器与密度峰值聚类算法的入侵检测模型(DCVAE-DPC).利用判别条件变分自编码器能够生成指定类别样本的能力,学习正常网络流量特征的隐空间表示并计算其重建误差,增加其与未知攻击间的特征区分度,并使用密度峰值聚类算法求出正常网络流量重建误差的分布,提高未知攻击识别率.实验结果表明,在NSL-KDD数据集中与当前流行的入侵检测模型相比,模型的分类准确率可以达到97.08%,具有更高的未知攻击检测能力,面对当前复杂网络环境,有更强的入侵检测性能.

沉积矿床中重要(变价)金属元素与古海洋环境关系综述--以新元古代-早古生代扬子板块周缘为例

对氧化—还原敏感元素和生命必需元素地球化学性质和相关沉积矿产形成机制及其时空分布特征的分析、总结和归纳,有助于对古海洋环境演化与相关沉积矿产形成关系的深入认识,这对沉积矿床学理论的发展具有重要意义。新元古代南华纪—早古生代早志留世,扬子板块周缘黑色岩系中依次沉积了举世瞩目的南华纪锰矿、震旦纪—早寒武世沉积磷块岩、早寒武世重晶石矿、镍—钼—钴多金属矿、钒矿和早志留世铀矿的完整沉积矿床系列,不同时代地层、同一时代不同沉积环境地层赋存不同类型的沉积矿产,有必要对其成矿机理进行系统研究、总结和归纳。笔者等在对氧化—还原敏感金属元素、生命必需元素和海底热液元素等元素地球化学性质综述的基础上,兼论了它们在结合黄铁矿矿物学对氧化—还原环境、生物生产力和盆地限制性分析方面具体作用;进一步结合新元古代—早古生代扬子板块古环境演化特征,对扬子板块周缘特定时代中特定沉积矿产的分布、成因机理进行分析、总结和归纳;最终得出扬子板块周缘相关沉积矿产,是在全球氧化事件、冰期—间冰期、Rodina大陆裂解大背景下,海洋中成矿金属元素得到长期积累,在特定时代区域性海水—海底热液—生物作用(根据不同矿种各有侧重)影响下,在相关重要元素地球化学性质的控制下、局部区域特殊氧化—还原环境的控制下形成的特定矿产的初步认识。最后,结合相关沉积矿床研究中存在的问题,提出下一步解决方案与展望。