Parameter Estimation in Models of Cell Survival Using Scaled Time

2013 ◽  
Author(s):  
Neil T. Wright
Keyword(s):  
Cell Survival ◽  
Treatment Time ◽  
Treatment Temperature ◽  
Separate Experiment ◽  
Small Data ◽  
Data Sets ◽  
Data Points ◽  
Isothermal Analysis ◽  
Time Required ◽  
Few Data

Many individual samples are needed to measure cell survival following heating at multiple temperatures and multiple heating durations. For example, if eight time points are considered for each of seven treatment temperatures with three replicates at each condition, then 168 separate samples are needed. In addition, physical considerations may limit the number of points that can be measured, especially as treatment temperature increases and the heating duration decreases. For a reasonable sample size, there may be a limit to the treatment temperature as the time required to heat the culture to the target temperature becomes comparable to the treatment time. Then, using an isothermal analysis of the data introduces error and the temperature must be considered time varying, requiring estimates of the very parameters being sought. Conversely, for long treatment times, it may be difficult to insure that the temperature remains constant and that the temperature is the only modified experimental condition in the culture medium. These challenges typically lead to relatively small data sets. Furthermore, treating each temperature as a separate experiment leads to challenging statistical analysis of the data, as the few data points lead to difficulty in finding the confidence intervals of the parameters in a given model.

Wheat Prices and Trade in the Early Roman Empire

2012 ◽  
Author(s):  
Peter Temin
Keyword(s):  
Roman Empire ◽  
Roman Republic ◽  
Small Data ◽  
Data Sets ◽  
Data Points ◽  
Small Data Sets ◽  
Few Data ◽  
Late Roman

This chapter discusses how there is little of what economists call data on markets in Roman times, despite lots of information about prices and transactions. Data, as economists consider it, consist of a set of uniform prices that can be compared with each other. According to scholars, extensive markets existed in the late Roman Republic and early Roman Empire. Even though there is a lack of data, there are enough observations for the price of wheat, the most extensively traded commodity, to perform a test. The problem is that there is only a little bit of data by modern standards. Consequently, the chapter explains why statistics are useful in interpreting small data sets and how one deals with various problems that arise when there are only a few data points.

Ensemble of surrogates and cross-validation for rapid and accurate predictions using small data sets

2019 ◽  
Vol 33 (4) ◽  
pp. 484-501 ◽  
Author(s):  
Reza Alizadeh ◽  
Liangyue Jia ◽  
Anand Balu Nellippallil ◽  
Guoxin Wang ◽  
Jia Hao ◽  
...  
Keyword(s):  
Cross Validation ◽  
Weighted Average ◽  
Computational Time ◽  
Small Data ◽  
Data Sets ◽  
Computationally Efficient ◽  
Cross Validation Error ◽  
Rod Rolling ◽  
Ensemble Of Surrogates ◽  
Time Required

AbstractIn engineering design, surrogate models are often used instead of costly computer simulations. Typically, a single surrogate model is selected based on the previous experience. We observe, based on an analysis of the published literature, that fitting an ensemble of surrogates (EoS) based on cross-validation errors is more accurate but requires more computational time. In this paper, we propose a method to build an EoS that is both accurate and less computationally expensive. In the proposed method, the EoS is a weighted average surrogate of response surface models, kriging, and radial basis functions based on overall cross-validation error. We demonstrate that created EoS is accurate than individual surrogates even when fewer data points are used, so computationally efficient with relatively insensitive predictions. We demonstrate the use of an EoS using hot rod rolling as an example. Finally, we include a rule-based template which can be used for other problems with similar requirements, for example, the computational time, required accuracy, and the size of the data.

Characteristics of Dimension Functions Associated With Cutting Measurements

1995 ◽  
Vol 117 (3A) ◽  
pp. 259-264
Author(s):  
M. Rokni ◽  
B. S. Berger ◽  
I. Minis
Keyword(s):  
Reference Points ◽  
Coordinate Space ◽  
Small Data ◽  
Data Sets ◽  
Qualitative Properties ◽  
Acceleration Data ◽  
Orthogonal Turning ◽  
Generic Data ◽  
Data Points ◽  
Small Data Sets

The information dimension, D(0), of attractors associated with orthogonal turning is determined from experimental tool-workpiece relative acceleration data. Let E≡dimension of a delay coordinate space, n≡number of generic data points and m≡ number of reference points on the attractor. It is shown that properties of D(0) as a function of E, denoted by D(0):E, are unchanging, invariant, over large intervals of n and m. The qualitative properties of D(0):E discriminate between various cutting cases. This discrimination can be based on relatively small data sets. The computation of D(0) is shown to be robust in the sense that estimated values of D(0) are invariant or slowly varying over intervals of n and m.

scholarly journals Responses of Whitefly and Poinsettias to Insecticidal Controlled Atmospheres

2000 ◽  
Vol 125 (4) ◽  
pp. 513-517 ◽  
Author(s):  
Susan S. Han ◽  
Jennifer Konieczny
Keyword(s):  
Treatment Time ◽  
Treatment Temperature ◽  
Mortality Data ◽  
Euphorbia Pulcherrima ◽  
Silverleaf Whitefly ◽  
Bemisia Argentifolii ◽  
Complete Elimination ◽  
Greenhouse Whitefly ◽  
Controlled Atmospheres ◽  
Time Required

Eggs, larvae, pupae, and adult stages of greenhouse whitefly (Trialeurodes vaporarium Westwood) and silverleaf whitefly (Bemisia argentifolii Bellows & Perring) were exposed to insecticidal controlled atmospheres at 20 °C or 30 °C. Mortality data were calculated for each stage and results demonstrated that reduced-O2 atmospheres (an O2 level of <2 μL·L-1 balance in N2) resulted in faster and higher mortality than elevated-CO2 atmospheres (25% or 50% CO2). Responses, from the least to most tolerant stage was adult < larvae < eggs = pupae, regardless of the species of whitefly and treatment temperature. At 20 °C, treatment time required to kill >90% of adults, larvae, and eggs and pupae was 2, 4, and 8 hours, respectively. Increasing the treatment temperature from 20 to 30 °C reduced the treatment time to one-half that of 20 °C. Treatment time required to achieve complete elimination of the insects also caused phytotoxicity symptoms on poinsettias (Euphorbia pulcherrima Willd. ex Klotzsch), thus, limiting use of insecticidal controlled atmospheres as the sole means for managing whitefly.

The Effects of Growth Sequence on the Electronic Properties of Al-Ge-Ni Ohmic Contacts on (001) GaAs

1992 ◽  
Vol 281 ◽  
Author(s):  
W. V. Lampert ◽  
T. W. Haas ◽  
E. S. Lambers ◽  
Paul H. Holloway
Keyword(s):  
Heat Treatment ◽  
Phase Formation ◽  
Ohmic Contacts ◽  
Treatment Time ◽  
Contact Layer ◽  
Treatment Temperature ◽  
X Ray Diffraction ◽  
Growth Sequence ◽  
Ohmic Behavior ◽  
Time Required

ABSTRACTThe growth sequence of Al, Ge, and Ni metals was shown to dramatically affect the amount of heat treatment time required to convert the electrical properties from Schottky to ohmic behavior. Differences in the heat treatment times required to convert from rectifying to ohmic contact were dependent on the doping concentration of the contact layer and on the heat treatment temperature. Interdiffusion of component elements and phase formation have been studied to determine the origin of these effects. Auger depth profiles and X-ray diffraction have been used to determine the interdiffusion and phase formation resulting from various types of thermal processing. Elemental profiles and identification of phases of Ni-Ga, Ni-As, and Ni-Ga-Ge will be used to explain the origin of ohmic behavior.

The Kinetic Effects of Layering Sequence of Al-Ge-Ni Ohmic Contact Components on (001) GaAs

1992 ◽  
Vol 260 ◽  
Author(s):  
W. V. Lampert ◽  
T. W. Haas ◽  
Paul H. Holloway
Keyword(s):  
Heat Treatment ◽  
Ohmic Contact ◽  
Heat Treatment Temperature ◽  
Doping Concentration ◽  
Treatment Time ◽  
Contact Layer ◽  
Treatment Temperature ◽  
Semiconductor Interface ◽  
Ohmic Behavior ◽  
Time Required

ABSTRACTElectrical characterization has demonstrated dramatic differences in the amount of heat treatment time required to convert the ohmic contact metallizations from Schottky to ohmic behavior, depending on the layering sequence of the Al, Ge, and Ni metals. Additional time differences were found to be dependent on the doping concentration of the contact layer of the GaAs and on the heat treatment temperature. For samples with Ge at the metal-semiconductor interface, the time required to convert from Schottky to ohmic behavior varies inversely with the doping concentration of the contact layer and directly with heat treatment temperature. Samples with Ni at the metal-semiconductor interface converted from Schottky to ohmic behavior much faster and had a much smaller dependence on the doping concentration and the heat treatment temperature. Models to explain these observations in terms of interdiffusion of the components and phases formed will be proposed.

Time consumption and quality of an automated fusion tool for SPECT and MRI images of the brain

2003 ◽  
Vol 42 (05) ◽  
pp. 215-219
Author(s):  
G. Platsch ◽  
A. Schwarz ◽  
K. Schmiedehausen ◽  
B. Tomandl ◽  
W. Huk ◽  
...  
Keyword(s):  
Data Sets ◽  
3D Mri ◽  
Clinical Routine ◽  
Fusion Procedure ◽  
3D Data ◽  
Mri Scans ◽  
2D Data ◽  
Time Required ◽  
The Brain ◽  
Manual Correction

Summary: Aim: Although the fusion of images from different modalities may improve diagnostic accuracy, it is rarely used in clinical routine work due to logistic problems. Therefore we evaluated performance and time needed for fusing MRI and SPECT images using a semiautomated dedicated software. Patients, material and Method: In 32 patients regional cerebral blood flow was measured using 99mTc ethylcystein dimer (ECD) and the three-headed SPECT camera MultiSPECT 3. MRI scans of the brain were performed using either a 0,2 T Open or a 1,5 T Sonata. Twelve of the MRI data sets were acquired using a 3D-T1w MPRAGE sequence, 20 with a 2D acquisition technique and different echo sequences. Image fusion was performed on a Syngo workstation using an entropy minimizing algorithm by an experienced user of the software. The fusion results were classified. We measured the time needed for the automated fusion procedure and in case of need that for manual realignment after automated, but insufficient fusion. Results: The mean time of the automated fusion procedure was 123 s. It was for the 2D significantly shorter than for the 3D MRI datasets. For four of the 2D data sets and two of the 3D data sets an optimal fit was reached using the automated approach. The remaining 26 data sets required manual correction. The sum of the time required for automated fusion and that needed for manual correction averaged 320 s (50-886 s). Conclusion: The fusion of 3D MRI data sets lasted significantly longer than that of the 2D MRI data. The automated fusion tool delivered in 20% an optimal fit, in 80% manual correction was necessary. Nevertheless, each of the 32 SPECT data sets could be merged in less than 15 min with the corresponding MRI data, which seems acceptable for clinical routine use.

scholarly journals Classification of jujube defects in small data sets based on transfer learning

2021 ◽  
Author(s):  
Jianping Ju ◽  
Hong Zheng ◽  
Xiaohang Xu ◽  
Zhongyuan Guo ◽  
Zhaohui Zheng ◽  
...  
Keyword(s):  
Transfer Learning ◽  
Loss Function ◽  
Training Model ◽  
Parameter Distribution ◽  
Test Accuracy ◽  
Small Data ◽  
Data Sets ◽  
Data Set ◽  
Small Data Sets

AbstractAlthough convolutional neural networks have achieved success in the field of image classification, there are still challenges in the field of agricultural product quality sorting such as machine vision-based jujube defects detection. The performance of jujube defect detection mainly depends on the feature extraction and the classifier used. Due to the diversity of the jujube materials and the variability of the testing environment, the traditional method of manually extracting the features often fails to meet the requirements of practical application. In this paper, a jujube sorting model in small data sets based on convolutional neural network and transfer learning is proposed to meet the actual demand of jujube defects detection. Firstly, the original images collected from the actual jujube sorting production line were pre-processed, and the data were augmented to establish a data set of five categories of jujube defects. The original CNN model is then improved by embedding the SE module and using the triplet loss function and the center loss function to replace the softmax loss function. Finally, the depth pre-training model on the ImageNet image data set was used to conduct training on the jujube defects data set, so that the parameters of the pre-training model could fit the parameter distribution of the jujube defects image, and the parameter distribution was transferred to the jujube defects data set to complete the transfer of the model and realize the detection and classification of the jujube defects. The classification results are visualized by heatmap through the analysis of classification accuracy and confusion matrix compared with the comparison models. The experimental results show that the SE-ResNet50-CL model optimizes the fine-grained classification problem of jujube defect recognition, and the test accuracy reaches 94.15%. The model has good stability and high recognition accuracy in complex environments.

scholarly journals Application of a roller conveyor type plasma disinfection device with fungus-contaminated citrus fruits

AMB Express ◽  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Akikazu Sakudo ◽  
Yoshihito Yagyu
Keyword(s):  
Treatment Time ◽  
Citrus Fruit ◽  
Viable Cell ◽  
Cell Number ◽  
Viable Cell Number ◽  
Citrus Fruits ◽  
Decimal Reduction Time ◽  
Gas Plasma ◽  
Plasma Device ◽  
Time Required

AbstractEfficient methods to achieve the safe decontamination of agricultural products are needed. Here, we investigated the decontamination of citrus fruits to test the antifungal potential of a novel non-thermal gas plasma apparatus, termed a roller conveyer plasma instrument. This instrument generates an atmospheric pressure dielectric barrier discharge (APDBP) plasma on a set of rollers. Penicillium venetum was spotted onto the surface of the fruit or pericarps, as well as an aluminium plate to act as a control, before performing the plasma treatment. The results showed that viable cell number of P. venetum decreased with a decimal reduction time (D value or estimated treatment time required to reduce viable cell number by 90%) of 0.967 min on the aluminium plate, 2.90 min and 1.88 min on the pericarps of ‘Kiyomi’ (Citrus unshiu × C. sinensis) and ‘Kawano-natsudaidai’ (C. natsudaidai) respectively, and 2.42 min on the surface of ‘Unshu-mikan’ (C. unshiu). These findings confirmed a fungicidal effect of the plasma not only on an abiotic surface (aluminium plate) but also on a biotic surface (citrus fruit). Further development of the instrument by combining sorting systems with the plasma device promises an efficient means of disinfecting citrus fruits during food processing.

scholarly journals Faking Signals to Fool Deep Neural Networks in AMC via Few Data Points

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Hongbin Ma ◽  
Shuyuan Yang ◽  
Guangjun He ◽  
Ruowu Wu ◽  
Xiaojun Hao ◽  
...  
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Data Points ◽  
Few Data
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