Relevant bibliographies by topics / Log-linear parameters

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Log-linear parameters'

Author: Grafiati
Published: 9 March 2023
Last updated: 19 July 2025

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Journal articles on the topic "Log-linear parameters"

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ALBA, RICHARD D. "Interpreting the Parameters of Log-Linear Models." Sociological Methods & Research 16, no. 1 (1987): 45–77. http://dx.doi.org/10.1177/0049124187016001003.

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Evans, Robin J., and Thomas S. Richardson. "Marginal log-linear parameters for graphical Markov models." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 75, no. 4 (2013): 743–68. http://dx.doi.org/10.1111/rssb.12020.

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Nagulu, Banoth, Y. Satyanarayana, Rao P. Srinivasa, and Krishna Gopal. "ESTIMATION OF THE GROWTH CURVE PARAMETERS IN Macrobrachium rosenbergii." Continental J. Fisheries and Aquatic Science 5, no. 1 (2011): 38–48. https://doi.org/10.5281/zenodo.3526086.

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Growth is one of the most important characteristics of cultured species. The objective of this study was to determine the fitness of linear, log linear, polynomial, exponential and Logistic functions to the growth curves of <em>Macrobrachium rosenbergii</em> obtained by using weekly records of live weight, total length, head length, claw length, and last segment length from 20 to 192 days of age. The models were evaluated according to the coefficient of determination (R<sup>2</sup>), and error sum off square (ESS) and helps in formulating breeders in selective breeding programs. Twenty full-si
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Haber, Michael. "Log-Linear Models for Linked Loci: Variances of Estimated Parameters." Biometrical Journal 30, no. 5 (2007): 589–93. http://dx.doi.org/10.1002/bimj.4710300513.

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Danaher, Peter J. "A Log-Linear Model for Predicting Magazine Audiences." Journal of Marketing Research 25, no. 4 (1988): 356–62. http://dx.doi.org/10.1177/002224378802500403.

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A log-linear model for predicting magazine exposure distributions is developed and its parameters are estimated by the maximum likelihood technique. The log-linear model is compared empirically with the best-found model for equal-insertion schedules, one of Leckenby and Kishi's Dirichlet multinomial models. For unequal-insertion schedules the log-linear model is compared with the popular Metheringham beta-binomial model. The results show that the log-linear model has significantly smaller prediction errors than either of the other models.
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Mukhopadhyay, Late Anis Chandra, and Rabindra Nath Das. "Inference on log-linear regression model parameters with composite autocorrelated errors." Model Assisted Statistics and Applications 10, no. 3 (2015): 231–42. http://dx.doi.org/10.3233/mas-150327.

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Gasmi, Soufiane. "Estimating parameters of a log-linear intensity for a repairable system." Applied Mathematical Modelling 37, no. 6 (2013): 4325–36. http://dx.doi.org/10.1016/j.apm.2012.09.050.

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Janjic, Tomislav, Gordana Vuckovic, and Milenko Celap. "Theoretical consideration and application of the SP and SP' scales in RP chromatographic systems in which Everett’s equation is valid." Journal of the Serbian Chemical Society 67, no. 3 (2002): 179–86. http://dx.doi.org/10.2298/jsc0203179j.

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It is shown that in the case of ODS and less polar modifiers the log k values are a linear function of the SP?parameters. This findings differ from earlier investigated systems, in which a linear dependence between log k and SP parameters (SP = log SP?) was found. Both linear relationships have been analyzed and the corresponding possible separation mechanisms have been considered. In addition, the advantages of normalization of both scales are shown and how then they can be applied in the investigation of substances congenerity.
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Habib, Elsayed Ali. "Estimation of Log-Linear-Binomial Distribution with Applications." Journal of Probability and Statistics 2010 (2010): 1–13. http://dx.doi.org/10.1155/2010/423654.

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Log-linear-binomial distribution was introduced for describing the behavior of the sum of dependent Bernoulli random variables. The distribution is a generalization of binomial distribution that allows construction of a broad class of distributions. In this paper, we consider the problem of estimating the two parameters of log-linearbinomial distribution by moment and maximum likelihood methods. The distribution is used to fit genetic data and to obtain the sampling distribution of the sign test under dependence among trials.
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Bucca, Mauricio. "Heatmaps for Patterns of Association in log-Linear Models." Socius: Sociological Research for a Dynamic World 6 (January 2020): 237802311989921. http://dx.doi.org/10.1177/2378023119899219.

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Log-linear models offer a detailed characterization of the association between categorical variables, but the breadth of their outputs is difficult to grasp because of the large number of parameters these models entail. Revisiting seminal findings and data from sociological work on social mobility, the author illustrates the use of heatmaps as a visualization technique to convey the complex patterns of association captured by log-linear models. In particular, turning log odds ratios derived from a model’s predicted counts into heatmaps makes it possible to summarize large amounts of informatio
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Dissertations / Theses on the topic "Log-linear parameters"

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NICOLUSSI, FEDERICA. "Marginal parametrizations for conditional independence models and graphical models for categorical data." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/43679.

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The graphical models (GM) for categorical data are models useful to representing conditional independencies through graphs. The parametric marginal models for categorical data have useful properties for the asymptotic theory. This work is focused on nding which GMs can be represented by marginal parametrizations. Following theorem 1 of Bergsma, Rudas and Németh [9], we have proposed a method to identify when a GM is parametrizable according to a marginal model. We have applied this method to the four types of GMs for chain graphs, summarized by Drton [22]. In particular, with regard to
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Sung, Chin-Hsiung, and 宋志雄. "Evaluation of Parameter Estimations in Log-Linear Model under Zero-Inflated Count Data." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/46545339679568069406.

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碩士<br>國立臺北大學<br>統計學系<br>103<br>More and more customers use credit cards or electronic purse to pay their bills instead of real money. Quite frequently, people have more than one credit card on average. Nevertheless, only a few credit cards are used. To analyze the consumer behavior in using credit cards, there exists many zeros. Such a data with many zeros are called zero-inflated count data. To deal with the excess zeros, Lambert (1992) proposed a zero-inflated Poisson distribution. The most popular model for consumer consumption behavior was proposed by Ehrenberg (1959) which is called the p
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Yu, Kuan Yi, and 余冠毅. "Some discussions on the performance of parameter estimations of the log-linear model and its extended models under the zero-inflated count data." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/72534318388068624846.

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碩士<br>國立臺北大學<br>統計學系<br>103<br>The most common parametric assumption for analyzing count data is Poisson distribution. However, it constructs under the assumption that the data have features that the mean equals variance. Nowadays, owing to there rapid development in technology storage, data are abundant and come from many different sources. In turn, the data no longer have the feature that the mean equals variance. Adding a new dispersion parameter in Poisson distribution, Consul and Jain (1970) proposed the generalized Poisson distribution. Mullahy (1986) suggested combining the Bernoulli an
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Books on the topic "Log-linear parameters"

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Back, Kerry E. Representative Investors. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190241148.003.0007.

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There is a representative investor at any Pareto optimal competitive equilibrium. If investors have linear risk tolerance with the same cautiousness parameter, then there is a representative investor with the same utility function. When there is a representative investor, there is a factor model with the representative investor’s marginal utility of consumption as the factor. If the representative investor has constant relative risk aversion, then the risk‐free return and log equity premium can be calculated in terms of moments of aggregate consumption. The equity premium and risk‐free rate pu
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Book chapters on the topic "Log-linear parameters"

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Ayad, Amel, Fabrice Mutelet, and Amina Negadi. "Temperature-Dependent Linear Solvation Energy Relationship for the Determination of Gas-Liquid Partition Coefficients of Organic Compounds in Ionic Liquids." In Recent Advances in Gas Chromatography. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.102733.

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In this work, a new group contribution method was used for calculating gas-to-ionic liquid partition coefficients (log KL) of molecular solutes in ILs with a temperature-dependent linear solvation energy relationship. About 36 group parameters are used to correlate 14,762 log KL data points of organic compounds in ionic liquids. The experimental log KL data have been collected from the published literature for different solutes in ionic liquids at different temperatures within the range of 293.15–396.35 K. The calculated log KL data showed a satisfactory agreement with experimental data with an average absolute relative deviation (AARD) of 6.39%.
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Balakrishnan, N., and P. S. Chan. "3 Log-gamma order statistics and linear estimation of parameters." In Handbook of Statistics. Elsevier, 1998. http://dx.doi.org/10.1016/s0169-7161(98)17005-0.

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Conrad Koch, Michael, Kazunori Fujisawa, and Akira Murakami. "Numerical Gradient Computation for Simultaneous Detection of Geometry and Spatial Random Fields in a Statistical Framework." In Inverse Problems - Recent Advances and Applications [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.108363.

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The target of this chapter is the evaluation of gradients in inverse problems where spatial field parameters and geometry parameters are treated separately. Such an approach can be beneficial especially when the geometry needs to be detected accurately using L2-norm-based regularization. Emphasis is laid upon the computation of the gradients directly from the governing equations. Working in a statistical framework, the Karhunen-Loève (K-L) expansion is used for discretization of the spatial random field and inversion is done using the gradient-based Hamiltonian Monte Carlo (HMC) algorithm. The HMC gradients involve sensitivities w.r.t the random spatial field and geometry parameters. Building on a method developed by the authors, a procedure is developed which considers the gradients of the associated integral eigenvalue problem (IEVP) as well as the interaction between the gradients w.r.t random spatial field parameters and the gradients w.r.t the geometry parameters. The same mesh and linear shape functions are used in the finite element method employed to solve the forward problem, the artificial elastic deformation problem and the IEVP. Analysis of the rate of convergence using seven different meshes of increasing density indicates a linear rate of convergence of the gradients of the log posterior.
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Wen, Teo Kai, and Azeb Demisi Habte. "Pressure Transient Behavior of Horizontal Gas Injection Well in Low Permeable Reservoirs." In Unconventional Methods for Geoscience, Shale Gas and Petroleum in the 21st Century. IOS Press, 2023. http://dx.doi.org/10.3233/aerd230015.

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This work addresses the pressure transient behavior of horizontal gas injection well in low permeable reservoirs. Low permeable reservoirs such as shale oil reservoirs have been receiving great attentions lately which normally require hydraulic fracturing and horizontal well development to maximize the oil production. However, the primary recovery factor of shale oil reservoirs is still low and has been estimated to be below 10–15% due to tight nature of the shale formations. Enhanced oil recovery method such as miscible carbon dioxide (CO2) injection is said to be one of the most efficient and effective methods used to increase the oil recovery factor of a low permeable shale oil reservoir. The objective of this paper is to study the pressure transient behavior of the horizontal gas injection well in low permeable shale oil reservoirs using numerical simulator, CMG-GEM. Flow regimes and its significant reservoir parameters are investigated from the log-log plot of pressure-derivatives. It is found that a unit-slope line is developed on pressure-derivative log-log plot at early time due to the gas compressibility effect, followed by early radial flow and early linear flow regimes. The effect of various parameters such as gas injection rate, duration of gas injection, well location and well perforation length are studied and analyzed on the changes of pressure transient characteristics. It is identified that gas injection rate affects the pressure-derivative response significantly at middle time due to gas mobility and viscosity; whereas well location and well perforation length affect the late time pressure-derivative response which relate to dominant boundary effect; however, duration of gas injection is not able to show or prove any impacts on the pressure-derivative behavior due to numerical instability issue. Reservoir characteristics such as average permeability and skin can be identified from the flow regimes equations similar to the horizontal production well.
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"Parameter Interpretation and Significance Tests." In Log-Linear Modeling. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118391778.ch7.

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Thajeel Jawad, Al-Bittar Tamara, Ahmed Ashraf, and Soubra Abdul-Hamid. "Probabilistic Analysis at Ultimate Limit State of Strip Footings Resting on a Spatially Varying Soil Using Subset Simulation Approach." In Geotechnical Safety and Risk V. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-580-7-326.

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The failure probability of geotechnical structures with spatially varying soil properties is generally computed using Monte Carlo simulation (MCS) methodology. This approach is well known to be very time-consuming when dealing with small failure probabilities. One alternative to MCS is the subset simulation approach. This approach was mainly used in the literature in cases where the uncertain parameters are modelled by random variables. In this paper, it is employed in the case where the uncertain parameters are modelled by random fields because the spatial variability of the soil properties has proven to greatly affect the behavior of geotechnical structures and to induce a significant change in the variability of their responses. This is illustrated through the probabilistic analysis at the ultimate limit state (ULS) of a strip footing resting on a one- and two-layer purely cohesive soil with a spatially varying cohesion. The soil cohesion parameter was modeled as anisotropic non-Gaussian (log-normal) random field using a square exponential autocorrelation function. The Expansion Optimal Linear Estimation (EOLE) method was used to dicretize this random field. The deterministic model was based on numerical simulations using the finite difference software FLAC3D.
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Thajeel Jawad, Al-Bittar Tamara, Ahmed Ashraf, and Soubra Abdul-Hamid. "Probabilistic Analysis at Ultimate Limit State of Strip Footings Resting on a Spatially Varying Soil Using Subset Simulation Approach." In Geotechnical Safety and Risk V. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-580-7-328.

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The failure probability of geotechnical structures with spatially varying soil properties is generally computed using Monte Carlo simulation (MCS) methodology. This approach is well known to be very time-consuming when dealing with small failure probabilities. One alternative to MCS is the subset simulation approach. This approach was mainly used in the literature in cases where the uncertain parameters are modelled by random variables. In this paper, it is employed in the case where the uncertain parameters are modelled by random fields, because the spatial variability of the soil properties has proven to greatly affect the behavior of geotechnical structures and to induce a significant change in the variability of their responses. This is illustrated through the probabilistic analysis at the ultimate limit state (ULS) of a strip footing resting on a one- and two-layer purely cohesive soil with a spatially varying cohesion. The soil cohesion parameter was modeled as an anisotropic non-Gaussian (log-normal) random field using a square exponential autocorrelation function. The Expansion Optimal Linear Estimation (EOLE) method was used to discretize this random field. The deterministic model was based on numerical simulations using the finite difference software FLAC3D.
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Kamaraj A., Selva Nidhyananthan S, and Kalyana Sundaram C. "Voice Biometric for Learner Authentication." In Biometric Authentication in Online Learning Environments. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7724-9.ch007.

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The objective of this chapter is to verify the identity of the claimed learner by extracting the prosodic features of the speech signal. TIMIT Acoustic-Phonetic Continuous Speech Corpus is used for learner verification using prosodic and articulation features such as energy, pitch, and formants. The prosodic feature includes pitch (F0), and articulation feature includes formants (F1-F7). From this database, for this project in the training phase, 200 learners were used and in the testing phase 160 learners were used. The pitch and formants were extracted using linear predictive analysis. The first seven formants were used for verification purpose. The feature set consists of eight features. The features are fed into the Guassian mixture model. In the Gaussian mixture model, parameters are estimated from the training and testing data using the iterative expectation-maximization. Log likelihood score is computed using these parameters, and then these scores are normalized to make decisions. The decision is made based on the threshold.
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Bhardwaj, Akashdeep. "Comparison of IoT Communication Protocols Using Anomaly Detection with Security Assessments of Smart Devices." In Smart Home and Industrial IoT Devices: Critical Perspectives on Cyberthreats, Frameworks and Protocols. BENTHAM SCIENCE PUBLISHERS, 2024. http://dx.doi.org/10.2174/9789815256710124010009.

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The authors implemented an attack scenario simulating attacks to compromise node and sensor data. This research proposes a framework with algorithms that generate automated malicious commands, which conform to device protocol standards and bypass compromise detection. The authors performed attack detection testing with three different home setup simulations and referred to accuracy of detection, ease of precision, and attack recall, with F1-score as the parameters. The results obtained for anomaly detection of IoT logs and messages used K-nearest neighbor, multi-layer perceptron, logistic regression, random forest, and linear support vector classifier models. The attack results presented false-positive responses with and without the proposed framework and false-negative responses for different models. This research calculated precision, accuracy, F1-score, and recall as attack detection performance models. Finally, the authors evaluated the performance of the proposed IoT communication protocol attack framework by evaluating a range of anomalies and compared them with the maliciously generated log messages. IoT Home #1 in which the model involved IP Camera and NAS device traffic displayed 97.7% Accuracy, 96.54% Precision, 97.29% Recall, and 96.88% F-1 Score. This demonstrated the model classified the Home #1 dataset consistently.
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Ordóñez, Diego, Carlos Dafonte, Bernardino Arcay, and Minia Manteiga. "Connectionist Systems and Signal Processing Techniques Applied to the Parameterization of Stellar Spectra." In Soft Computing Methods for Practical Environment Solutions. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-893-7.ch012.

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A stellar spectrum is the finger-print identification of a particular star, the result of the radiation transport through its atmosphere. The physical conditions in the stellar atmosphere, its effective temperature, surface gravity, and the presence and abundance of chemical elements explain the observed features in the stellar spectra, such as the shape of the overall continuum and the presence and strength of particular lines and bands. The derivation of the atmospheric stellar parameters from a representative sample of stellar spectra collected by ground-based and spatial telescopes is essential when a realistic view of the Galaxy and its components is to be obtained. In the last decade, extensive astronomical surveys recording information of large portions of the sky have become a reality since the development of robotic or semi-automated telescopes. The Gaia satellite is one of the key missions of the European Space Agency (ESA) and its launch is planned for 2011. Gaia will carry out the so-called Galaxy Census by extracting precise information on the nature of its main constituents, including the spectra of objects (Wilkinson, 2005). Traditional methods for the extraction of the fundamental atmospheric stellar parameters (effective temperature (Teff), gravity (log G), metallicity ([Fe/H]), and abundance of alpha elements [a/Fe], elements integer multiples of the mass of the helium nucleus) are time-consuming and unapproachable for a massive survey involving 1 billion objects (about 1% of the Galaxy constituents) such as Gaia. This work presents the results of the authors’ study and shows the feasibility of an automated extraction of the previously mentioned stellar atmospheric parameters from near infrared spectra in the wavelength region of the Gaia Radial Velocity Spectrograph (RVS). The authors’ approach is based on a technique that has already been applied to problems of the non-linear parameterization of signals: artificial neural networks. It breaks ground in the consideration of transformed domains (Fourier and Wavelet Transforms) during the preprocessing stage of the spectral signals in order to select the frequency resolution that is best suited for each atmospheric parameter. The authors have also progressed in estimating the noise (SNR) that blurs the signal on the basis of its power spectrum and the application of noise-dependant algorithms of parameterization. This study has provided additional information that allows them to progress in the development of hybrid systems devoted to the automated classification of stellar spectra.
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Conference papers on the topic "Log-linear parameters"

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Pye, E. L., J. F. Stephenson, and M. L. Pye. "Pol Plot." In CORROSION 1990. NACE International, 1990. https://doi.org/10.5006/c1990-90327.

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Abstract Software for corrosion monitoring and data analysis is discussed. These are a series of modularized IBM-compatible computer programs. They provide a wide range of polarization data-acquisition as well as extensive data analysis programs. A system, composed of a computer, interface, and potentiostat/galvanostat, is used. The system provides for operator selection from a menu of numerous acquisition and analysis programs. The acquisition programs include Ecorr, cyclic voltammetry and polarization, anodic and cathodic polarization, linear polarization, log polarization, degree of sensiti
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Pourbaix, M., and A. Pourbaix. "Recent Progress in Atmospheric Corrosion Testing." In CORROSION 1987. NACE International, 1987. https://doi.org/10.5006/c1987-87408.

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Abstract An accelerated electrochemical test with cyclic immersions and emersions, and electrode potential measurements during the periods of immersion, helps to assess the corrosion behavior of metallic material under different climatic conditions, and to understand the mechanism of atmospheric corrosion or passivation. Results of both natural exposure tests and laboratory tests may often be expressed by the linear bilogarithmic law log p = A + B log t, where A measures the initial corrosion intensity and B measures the passivating action of the atmosphere. Correlations between electrode pote
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Schell, H. C., and D. G. Manning. "Evaluating the Performance of Cathodic Protection Systems on Reinforced Concrete Bridge Substructures." In CORROSION 1985. NACE International, 1985. https://doi.org/10.5006/c1985-85263.

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Abstract This paper describes the instrumentation and monitoring techniques used in the evaluation of eight experimental substructure cathodic protection systems, constructed on piers on the Burlington Bay Skyway Bridge during 1982/83. The use of E-log I tests to aid in determining protective current levels, and the variation of test parameters, are described. Corrosion currents predicted by E-log I tests are compared with those predicted by linear polarization methods. The instrumentation which was embedded in the concrete included artificial corrosion macrocells, current pick-up probes and r
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Leinonen, H. "Stress Corrosion Cracking and Life Prediction Evaluation of Austenitic Stainless Steels in CaCl2 Solution." In CORROSION 1995. NACE International, 1995. https://doi.org/10.5006/c1995-95170.

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Abstract Stress corrosion cracking susceptibility of austenitic stainless steels in CaCl2 solutions was studied by using a constant load method. Initiation and propagation of stress corrosion cracks were examined by using fractography. The number and distribution of cracks were classified. A physical model for cracking was introduced as well as some creep deformation measurements were performed and analyzed. The steady state strain rate obtained from corrosion elongation curve (elongation vs. time curve) showed a linear function of time to failure in a log-log plot. This implies that steady st
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"Optimization of Log-linear Machine Translation Model Parameters Using SVMs." In 8th International Workshop on Pattern Recognition in Information Systems. SciTePress - Science and and Technology Publications, 2008. http://dx.doi.org/10.5220/0001739000480056.

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Pratikno, Helmi, W. John Lee, and Cesario K. Torres. "Application of Multiple Diagnostic Plots to Identify End of Linear Flow in Unconventional Reservoirs." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205906-ms.

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Abstract This paper presents a method to identify switch time from end of linear flow (telf) to transition or boundary-dominated flow (BDF) by utilizing multiple diagnostic plots including a Modified Fetkovich type curve (Eleiott et al. 2019). In this study, we analyzed publicly available production data to analyze transient linear flow behavior and boundary-dominated flow from multiple unconventional reservoirs. This method applies a log-log plot of rate versus time combined with a log-log plot of rate versus material balance time (MBT). In addition to log-log plots, a specialized plot of rat
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Wei, Zhigang, Richard C. Rice, Masataka Yatomi, and Kamran M. Nikbin. "The Equivalency-Based Linear Regression Method for Statistical Analysis of Creep/Fatigue Data." In ASME 2010 Pressure Vessels and Piping Division/K-PVP Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/pvp2010-25691.

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Materials scientists and mechanical engineers working on structural integrity are making increasing use of statistical analysis in interpreting creep/fatigue data as they contain an inherent scatter which cannot be substantially reduced even under controlled testing conditions. In practice, in most cases the uniaxial failure or cracking data can be reasonably approximated by a straight line on log-log coordinates, indicating that there is a linear log relationship with the appropriate correlating parameter. Linear regression is the most used method in statistical data analysis and is being rec
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Crews, John H., and Ralph C. Smith. "Density Function Optimization for the Homogenized Energy Model of Shape Memory Alloys." In ASME 2011 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASMEDC, 2011. http://dx.doi.org/10.1115/smasis2011-5036.

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In this paper, we present two methods for optimizing the density functions in the homogenized energy model (HEM) of shape memory alloys (SMA). The density functions incorporate the polycrystalline behavior of SMA by accounting for material inhomogeneities and localized interaction effects. One method represents the underlying densities for the relative stress and interaction stress as log-normal and normal probability density functions, respectively. The optimal parameters in the underlying densities are found using a genetic algorithm. A second method represents the densities as a linear para
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Wasle, Helena, Anne Goralzik, Birte Thomas-friedrich, David Schackmann, and Esther Bosch. "When Something Is in the Way: Parameters of Perception and Reaction Speed in Train Drivers." In 5th International Conference on Human Systems Engineering and Design: Future Trends and Applications (IHSED 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004139.

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A challenge for automation in open track railway systems is the lack of safety standards for obstacle detection and benchmarks for the performance of automated systems. In this work, the foundation for such a benchmark was established with the help of two studies aimed at understanding the reaction time mechanisms of this task. A simulator experiment with professional train drivers and an online study with a larger sample of non-train-drivers were conducted to analyze the reaction time to obstacles along the tracks. The size and contrast of the obstacles, as well as driving speed and use of tr
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Han, Zhilei, Yunjiang Cui, Sainan Xu, and Chao Ma. "Experimental Research on Mechanical Properties for Hydraulic Fracture Design of Weak Sands: A Case Study in Bohai." In Offshore Technology Conference. OTC, 2022. http://dx.doi.org/10.4043/32072-ms.

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Abstract In recent years, in order to improve the oil production of unconsolidated sand reservoirs, hydraulic fracture through the screen liner has been carried out in the Bohai oilfield. Traditional hydraulic fracture design methods usually assume the rock is elastic, while the weak sands are often nonlinear elastic rocks. This study investigates how to optimize the mechanical parameters used in the hydraulic fracture design to best approximate the rock elastic properties under in-situ formation conditions, and show how to derive them from well logs. We performed uniaxial strain and triaxial
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