Sensor Method(传感器方法)研究综述
Sensor Method 传感器方法 - Therefore, this paper proposes a new adaptive filtering-based soft sensor method for real-time estimation of total nitrogen concentration. [1] To date, there are many detection methods with a unique detection system available for Salmonella detection utilising immunological-based techniques, molecular-based techniques, mass spectrometry, spectroscopy, optical phenotyping, and biosensor methods. [2] This aptasensor method has the potential to measure the ENaC protein levels in urine samples as well as to be a point-of-care device. [3] Because of its wide detection range, high sensitivity, and excellent stability, the Ag–Cu alloy sensor method may be an excellent alternative to the traditional ascorbic acid measure method. [4] For all multiple staged interfering materials, the reported latest potentiometric sensor methods displayed high selectivity. [5] A trenchantly intended active moiety (E)-2-(((9-ethyl-9H-carabazol-3-yl) imino) methyl)-4, 6-diiodophenol (CS) was synthesized for the expeditious detection of tryptamine (TA) under aqueous medium by means of fluorescent chemosensor methodology. [6] Salivary cortisol and amylase levels of subjects were measured by three different analytical methods as ELISA, chemiluminescence and biosensor methods. [7] Finally, during the process of the simulation and experiment, the failure data measured by the multi-sensor method can be used as a positioning quantity to locate the faulty module. [8] Single-sensor methods such as laser-based or vision-based have proven to be inadequate. [9] This present work reviews valuable studies on the damage detection of existing FRP composite-RC structures conducted by some well-known NDTs, including piezoelectric transducer (PZT) methods, acoustic emission (AE) monitoring, ultrasonic testing, fiber optics sensor methods, microwave detection, acoustic laser detection, infrared thermography (IR), and digital image correlation (DIC). [10] This article presents a comprehensive review of the use of sensor methodologies for portion size estimation. [11] The proposed sensor method is simple, cost-effective, and easy to manufacture. [12] All single-sensor methods overestimated sedentary time. [13] Herein, a novel fluorescence biosensor method for one-step simultaneous detection of multiple miRNAs was proposed by using single-stranded DNA (ssDNA) functionalized double quantum dots (QDs) and black hole quencher (BHQ)-decorated magnetic nanobeads (MNs). [14] This study evaluated the performance of a portable, field-deployable antibody-based PAH biosensor method that can provide measurements of PAH Cfree within a matter of minutes using a small volume of mechanically-extracted sediment porewater. [15] The obtained results confirmed that diffuse ultrasonic sensor methodology with the proposed algorithm is useful and effective in monitoring real RC structures, and it is better than traditional techniques. [16] The use of complementary acquisitions, such as Synthetic Aperture Radar (SAR) data, opens the door to the development of new multi-sensor methodologies aiming at the reconstruction of missing information. [17] This study represents the first attempt to develop an FEN1 assay that involves signal amplification, and the novel biosensor method enriches the tools for FEN1-based diagnostics. [18] In this study, researchers developed computer vision using sensor methods and image processing. [19] Various biosensor methods have been established for identification. [20] The combination of chemogenetic approaches with biosensor methodologies has opened up new lines of investigation, allowing the analysis of intracellular redox pathways that modulate physiological and pathological cell responses. [21] Given the CAD model of the target object, a virtual 3D sensor method is used to generate a virtual 3D view from any viewpoint around the CAD model’s point cloud. [22] Purpose The purpose of this paper is to visualize protein manipulation using dielectrophoresis (DEP) as a substantial perspective on being an effective protein analysis and biosensor method as DEP is able to be used as a means for manipulation, fractionation, pre-concentration and separation. [23] The genosensor methodology implied the immobilization of a A. [24] Thus, the OWLS immunosensor method developed appears to be suitable for the quantitative determination of ZON in aqueous medium. [25] This article reviews biosensor methods of disease detection that have been used effectively in other fields, and these methods could possibly transform the production methods of the agricultural industry. [26] The experimental sensor methodology was based on the detection of H2O2 by analysis of images of novel silver nanostructure-coated papers and processing of color histograms with a RGB (red–green–blue) analyzer software. [27] For example, Raspberry pi board enables the possibility to integrate the agriculture system with online servers as well as an efficient sensor method for monitoring agricultural parameters. [28] We calculated self-noise levels through probabilistic power spectral densities and by applying the Sleeman method, a three-sensor method. [29] Due to the dairy industry’s need for analytical methods for the determination of lactose in milk and dairy products with low- or lactose-free content, the AOAC Stakeholder Group on Strategic Food Analysis Methods approved Standard Performance Requirements for Biosensor Methods (SMPR®) 2018. [30] In this study, we introduce a novel non-disruptive dual-sensor method that provides near real-time information on silage aerobic stability, and demonstrates for the first time that in situ silage temperature (Tsi) and pH are both associated with preservation of lactic acid. [31] Additionally, a distinction between total LiDAR-derived PAI, multispectral-derived GAI, and brown area index (BAI) is made to show how the active and passive optical sensor methods used in this study can complement each other throughout the growing season. [32] We presented a Diagnostic Biosensor Method (DBM) in detail, with validation by comparison with a traditional high-throughput platform (ELISA assay). [33] Other methods, including HPLC, immunoassay method, biosensor method, electrochemical detection, capillary electrophoresis technique, and spectral techniques mainly, have become less and less in recent years. [34] In this paper, a new soft-sensor method combining dynamics and time-lag is proposed. [35] Simulation results on BSM1 showed that the ODRNN based soft sensor method has higher accuracy and robustness than other state-of-the-art methods. [36] The multiple detection experiment demonstrated that this sensor method had high reproducibility with relative standard deviation (RSD) of 11. [37] However, the reconstruction of phase currents using the existing one or two sensor methods developed under CCC control will be more difficult to adopt for the DTC scheme due to the simultaneous conduction of all phases. [38] This paper proposes an adaptive soft sensor method of D-vine copula quantile regression (aDVQR). [39] The findings suggest that the flush sensor methodology is a reliable method for further consideration. [40] This paper proposes a new twelve-step unsymmetrical 160° commutation strategy using a single Hall-effect sensor method for brushless DC (BLDC) motor drives. [41] In case study, we use the debutanizer process and a low temperature transformer case to confirm the quality of the soft sensor method. [42] BoNT/A LC, the surrogate of BoNT/A which embodying the most potent biological poisons, could serve as an ultrasensitive signal reporter with high signal-to-noise ratio to avoid common strong background response, poor stability and low intensity of current biosensor methods. [43] To address this issue, two novel semi-supervised soft sensor methods, namely evolutionary optimization based pseudo labeling method (EOPL) and ensemble EOPL method (EnEOPL), are proposed. [44] When used in combination with the BIOSENSOR method, the sensitivity increased a million fold without losing specificity. [45] Furthermore, advanced analysis methods such as ratiometric sensor and array sensor methods are reviewed. [46] To monitor the illegal use of olaquindox in animals, a monoclonal antibody-based surface plasmon resonance (SPR) biosensor method has been developed to detect 3-methyl-quinoxaline-2-carboxylic acid, the marker residues of olaquindox, in swine tissues. [47] The laboratory electrochemical corrosion test on the wire arc sprayed Al-Zn coating validated the proposed embedded FBG sensor method with a good agreement in comparison. [48] HPLC and biosensor methods provided similar results in the range from zero to 432 μg/g (correlation coefficient, R2 = 0. [49] In addition, we propose a Monte Carlo validation and testing (MCVT) procedure and three MCVT-based performance indices for consistent and fair comparison of different soft sensor methods across different datasets. [50]因此，本文提出了一种新的基于自适应滤波的软传感器方法，用于实时估计总氮浓度。 [1] 迄今为止，有许多检测方法具有独特的检测系统，可利用基于免疫学的技术、基于分子的技术、质谱、光谱学、光学表型和生物传感器方法进行沙门氏菌检测。 [2] 这种适体传感器方法有可能测量尿液样本中的 ENaC 蛋白水平，也可以作为护理点设备。 [3] 因为 Ag-Cu 合金传感器方法检测范围广、灵敏度高、稳定性好，是传统抗坏血酸测量方法的绝佳替代品。 [4] 对于所有多级干扰材料，报道的最新电位传感器方法显示出高选择性。 [5] 为快速检测色胺 (TA) 合成了一个非常有用的活性基团 (E)-2-(((9-乙基-9H-carabazol-3-yl) 亚氨基) 甲基)-4, 6-二碘苯酚 (CS)通过荧光化学传感器方法在水介质下。 [6] 通过ELISA、化学发光和生物传感器法三种不同的分析方法测量受试者的唾液皮质醇和淀粉酶水平。 [7] 最后，在仿真和实验过程中，多传感器方法测得的故障数据可以作为定位量，对故障模块进行定位。 [8] 诸如基于激光或基于视觉的单传感器方法已被证明是不够的。 [9] 本工作回顾了一些著名的无损检测对现有 FRP 复合材料-RC 结构的损伤检测的有价值的研究，包括压电换能器 (PZT) 方法、声发射 (AE) 监测、超声波检测、光纤传感器方法、微波检测、声激光检测、红外热成像 (IR) 和数字图像相关 (DIC)。 [10] 本文全面回顾了使用传感器方法进行部分大小估计。 [11] 所提出的传感器方法简单、具有成本效益且易于制造。 [12] 所有单传感器方法都高估了久坐时间。 [13] 在此，提出了一种使用单链 DNA (ssDNA) 功能化双量子点 (QD) 和黑洞猝灭剂 (BHQ) 装饰的磁性纳米珠 (MNs) 一步同时检测多个 miRNA 的新型荧光生物传感器方法。 [14] 这项研究评估了一种便携式、可现场部署的基于抗体的 PAH 生物传感器方法的性能，该方法可以使用少量机械提取的沉积物孔隙水在几分钟内提供 PAH Cfree 的测量值。 [15] 所得结果证实，采用该算法的扩散超声传感器方法在监测真实RC结构方面是有用且有效的，并且优于传统技术。 [16] 使用合成孔径雷达 (SAR) 数据等补充采集数据为开发旨在重建缺失信息的新多传感器方法打开了大门。 [17] 这项研究代表了开发涉及信号放大的 FEN1 检测的首次尝试，新的生物传感器方法丰富了基于 FEN1 的诊断工具。 [18] 在这项研究中，研究人员使用传感器方法和图像处理开发了计算机视觉。 [19] 已经建立了各种生物传感器方法用于识别。 [20] 化学遗传学方法与生物传感器方法的结合开辟了新的研究方向，允许分析调节生理和病理细胞反应的细胞内氧化还原途径。 [21] 给定目标对象的 CAD 模型，使用虚拟 3D 传感器方法从 CAD 模型点云周围的任何视点生成虚拟 3D 视图。 [22] 目的 本文的目的是将使用介电泳 (DEP) 的蛋白质操作可视化，作为一种有效的蛋白质分析和生物传感器方法的重要视角，因为 DEP 能够用作操作、分馏、预浓缩和分离的手段。 [23] 基因传感器方法暗示了 A. [24] 因此，开发的 OWLS 免疫传感器方法似乎适用于水介质中 ZON 的定量测定。 [25] 本文回顾了已在其他领域有效使用的疾病检测生物传感器方法，这些方法可能会改变农业的生产方式。 [26] 实验传感器方法基于通过分析新型银纳米结构涂层纸的图像和使用 RGB（红-绿-蓝）分析仪软件处理颜色直方图来检测 H2O2。 [27] 例如，Raspberry pi 板可以将农业系统与在线服务器集成在一起，并提供一种用于监测农业参数的有效传感器方法。 [28] 我们通过概率功率谱密度和应用 Sleeman 方法（一种三传感器方法）来计算自噪声水平。 [29] 由于乳制品行业需要分析方法来测定低乳糖或无乳糖含量的牛奶和乳制品中的乳糖，AOAC 战略食品分析方法利益相关者小组批准了 2018 年生物传感器方法标准性能要求 (SMPR®)。 [30] 在这项研究中，我们介绍了一种新的非破坏性双传感器方法，该方法可提供有关青贮饲料需氧稳定性的近实时信息，并首次证明原位青贮饲料温度 (Tsi) 和 pH 值都与乳酸的保存有关。酸。 [31] 此外，对总 LiDAR 衍生的 PAI、多光谱衍生的 GAI 和棕色区域指数 (BAI) 进行了区分，以显示本研究中使用的主动和被动光学传感器方法如何在整个生长季节相互补充。 [32] 我们详细介绍了一种诊断生物传感器方法 (DBM)，并通过与传统的高通量平台 (ELISA 测定) 进行比较进行了验证。 [33] 其他方法，主要包括高效液相色谱法、免疫测定法、生物传感器法、电化学检测法、毛细管电泳技术、光谱技术等，近年来越来越少。 [34] 在本文中，提出了一种结合动态和时滞的新软传感器方法。 [35] 在 BSM1 上的仿真结果表明，基于 ODRNN 的软传感器方法比其他最先进的方法具有更高的准确性和鲁棒性。 [36] 多重检测实验表明，该传感器方法具有较高的重现性，相对标准偏差 (RSD) 为 11。 [37] 然而，由于所有相同时传导，使用在 CCC 控制下开发的现有一或两个传感器方法重建相电流将更难以用于 DTC 方案。 [38] 本文提出了一种D-vine copula分位数回归（aDVQR）的自适应软传感器方法。 [39] 研究结果表明，冲洗传感器方法是一种值得进一步考虑的可靠方法。 [40] 本文提出了一种新的十二步非对称 160° 换向策略，该策略使用单个霍尔效应传感器方法用于无刷直流 (BLDC) 电机驱动。 [41] 在案例研究中，我们使用脱丁烷工艺和低温变压器案例来确认软传感器方法的质量。 [42] BoNT/A LC 是体现最强生物毒物的 BoNT/A 的替代品，可作为具有高信噪比的超灵敏信号报告器，避免当前生物传感器方法常见的强背景响应、稳定性差和低强度. [43] 为了解决这个问题，提出了两种新的半监督软传感器方法，即基于进化优化的伪标记方法（EOPL）和集成EOPL方法（EnEOPL）。 [44] 当与 BIOSENSOR 方法结合使用时，灵敏度增加了一百万倍，而不会失去特异性。 [45] 此外，还回顾了先进的分析方法，例如比率传感器和阵列传感器方法。 [46] nan [47] nan [48] nan [49] nan [50]
Soft Sensor Method
Therefore, this paper proposes a new adaptive filtering-based soft sensor method for real-time estimation of total nitrogen concentration. [1] Simulation results on BSM1 showed that the ODRNN based soft sensor method has higher accuracy and robustness than other state-of-the-art methods. [2] This paper proposes an adaptive soft sensor method of D-vine copula quantile regression (aDVQR). [3] In case study, we use the debutanizer process and a low temperature transformer case to confirm the quality of the soft sensor method. [4] To address this issue, two novel semi-supervised soft sensor methods, namely evolutionary optimization based pseudo labeling method (EOPL) and ensemble EOPL method (EnEOPL), are proposed. [5] In addition, we propose a Monte Carlo validation and testing (MCVT) procedure and three MCVT-based performance indices for consistent and fair comparison of different soft sensor methods across different datasets. [6] And the SOFT SENSOR methodology that can catch the state of a specific weak point by using the detailed analysis model of NVH, thermal, and strength has been constructed. [7]因此，本文提出了一种新的基于自适应滤波的软传感器方法，用于实时估计总氮浓度。 [1] 在 BSM1 上的仿真结果表明，基于 ODRNN 的软传感器方法比其他最先进的方法具有更高的准确性和鲁棒性。 [2] 本文提出了一种D-vine copula分位数回归（aDVQR）的自适应软传感器方法。 [3] 在案例研究中，我们使用脱丁烷工艺和低温变压器案例来确认软传感器方法的质量。 [4] 为了解决这个问题，提出了两种新的半监督软传感器方法，即基于进化优化的伪标记方法（EOPL）和集成EOPL方法（EnEOPL）。 [5] nan [6] nan [7]
sensor method may
Because of its wide detection range, high sensitivity, and excellent stability, the Ag–Cu alloy sensor method may be an excellent alternative to the traditional ascorbic acid measure method. [1] For majority complex cases in biological and chemical industrial processes with especially nonlinear characteristics, traditional VBFR-based inferential sensor method may not function well because of its linearity assumption on the process data. [2]因为 Ag-Cu 合金传感器方法检测范围广、灵敏度高、稳定性好，是传统抗坏血酸测量方法的绝佳替代品。 [1] nan [2]