Academic literature on the topic 'Square root transformations'
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Journal articles on the topic "Square root transformations"
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Ergin, M., and Ö. Koşkan. "Assessing transformation methods for group comparisons under violated assumptions: type I error rate and test power." Arquivo Brasileiro de Medicina Veterinária e Zootecnia 75, no. 5 (2023): 883–92. http://dx.doi.org/10.1590/1678-4162-13026.
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ABSTRACT In this study, some transformation methods that are applied when the assumptions of analysis of variance are not met are evaluated in terms of type I error rate and the test power, under circumstances with different distributions, number of groups, number of observations, variance ratios, and different standard deviation differences. The data set used in the study consisted of random numbers generated from N (0,1), and χ2(3) distributions using the random function of the Numpy library in the Python programming language. The logarithmic, square root and root transformations were evaluated on ANOVA based on simulation combinations. It was observed that the transformation techniques of taking the square root after adding 0.5 and 0.375 to the data were relatively more reliable compared to other transformations in terms of type I error rate. However, in every case, type I error rate determined at the beginning of the experiment increased both before and after the transformation was applied. In particular, interestingly, the third and fourth degree root transformations gave better results of test power in the right skewed distribution. In addition, we compared the transformation techniques in question to determine the normality of the data and the homogeneity of variances by a real data.
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Ahrens, William H., Darrell J. Cox, and Girish Budhwar. "Use of the Arcsine and Square Root Transformations for Subjectively Determined Percentage Data." Weed Science 38, no. 4-5 (1990): 452–58. http://dx.doi.org/10.1017/s0043174500056824.
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The arcsine and square root transformations were tested on 82 weed control data sets and 62 winter wheat winter survival data sets to determine effects on normality of the error terms, homogeneity of variance, and additivity of the model. Transformations appeared to correct deficiencies in these three parameters in the majority of data sets, but had adverse effects in certain other data sets. Performing the recommended transformation in conjunction with omitting treatments having identical replicate observations provided a high percentage of correction of non-normality, heterogeneity of variance, and nonadditivity. The arcsine transformation, not generally recommended for data sets having values from 0 to 20% or 80 to 100%, was as effective in correcting non-normality, heterogeneity of variance, and nonadditivity in these data sets as was the recommended square root transformation. A majority of data sets showed differences between transformed and nontransformed data in mean separations determined using LSD (0.05), although most of these differences were minor and had little effect on interpretation of results.
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Nerger, Lars, Tijana Janjić, Jens Schröter, and Wolfgang Hiller. "A Unification of Ensemble Square Root Kalman Filters." Monthly Weather Review 140, no. 7 (2012): 2335–45. http://dx.doi.org/10.1175/mwr-d-11-00102.1.
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Abstract In recent years, several ensemble-based Kalman filter algorithms have been developed that have been classified as ensemble square root Kalman filters. Parallel to this development, the singular “evolutive” interpolated Kalman (SEIK) filter has been introduced and applied in several studies. Some publications note that the SEIK filter is an ensemble Kalman filter or even an ensemble square root Kalman filter. This study examines the relation of the SEIK filter to ensemble square root filters in detail. It shows that the SEIK filter is indeed an ensemble square root Kalman filter. Furthermore, a variant of the SEIK filter, the error subspace transform Kalman filter (ESTKF), is presented that results in identical ensemble transformations to those of the ensemble transform Kalman filter (ETKF), while having a slightly lower computational cost. Numerical experiments are conducted to compare the performance of three filters (SEIK, ETKF, and ESTKF) using deterministic and random ensemble transformations. The results show better performance for the ETKF and ESTKF methods over the SEIK filter as long as this filter is not applied with a symmetric square root. The findings unify the separate developments that have been performed for the SEIK filter and the other ensemble square root Kalman filters.
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Thinh, Hoang Xuan, Nguyen Truong Giang, and Vu Van Khiem. "A Comparative Analysis of Data Transformation Methods for Constructing a Surface Roughness Model in Turning Processes." International Journal of Mechanical Engineering and Robotics Research 13, no. 4 (2024): 428–34. http://dx.doi.org/10.18178/ijmerr.13.4.428-434.
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Data conversion methods are used to transform datasets into new datasets, which may exhibit a distribution pattern different from the original dataset. Enhancing model accuracy is one of the applications of data transformation. This study compared the effectiveness of three data transformation methods: square root, logarithmic, and inverse transformation. This comparison was conducted in the context of constructing a surface roughness model for a turning process. Surface roughness plays a crucial role in determining corrosion resistance, chemical corrosion resistance, fatigue strength, and joint accuracy. These parameters significantly impact the product's operational ability and durability. An experimental turning process was performed, comprising a total of eighteen experiments designed using the Box-Behnken method. Surface roughness was selected as the response for each experiment. The three aforementioned data transformation methods were applied to the surface roughness dataset. Four surface roughness regression models were constructed, including a model without data transformation, a model with square root transformation, a model with logarithmic transformation, and a model with inverse transformation. The effectiveness of the three data transformation methods was compared using four metrics: Coefficient of Determination (R2), Adjusted Coefficient of Determination (R2(adj)), Mean Absolute Error (%MAE), and Mean Squared Error (%MSE). The study revealed that the logarithmic transformation was the most effective, followed by the square root transformation. The accuracy of the surface roughness regression model improved when utilizing these two transformations. The inverse transformation exhibited the least effectiveness among the three data transformation methods.
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Hildebrandt, Anna K., Matthias Dietzen, Thomas Lengauer, Hans-Peter Lenhof, Ernst Althaus, and Andreas Hildebrandt. "Efficient computation of root mean square deviations under rigid transformations." Journal of Computational Chemistry 35, no. 10 (2013): 765–71. http://dx.doi.org/10.1002/jcc.23513.
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Thinh, Hoang Xuan, and Tran Van Dua. "Optimal Surface Grinding Regression Model Determination with the SRP Method." Engineering, Technology & Applied Science Research 14, no. 3 (2024): 14713–18. http://dx.doi.org/10.48084/etasr.7573.
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The construction of the regression models used to control machining processes is the objective of many experimental studies. Therefore, the effectiveness of the machining process control largely depends on the regression model’s accuracy. This study was conducted to determine the optimal regression model of surface grinding. Accordingly, eight different surface grinding regression models were constructed, including one model without data transformation and seven models that utilized various data transformations. The seven data transformations employed entailed square root transformation, logarithmic transformation, inverse transformation, exponential transformation, asinh transformation, Box-Cox transformation, and Johnson transformation. The process of determining the optimal model was carried out considering five parameters: R2, R2(adj), R2(pred) (predicted R2), MAE (Mean Absolute Error), and MSE (Mean Squared Error). SRP (Simple Ranking Process) was the optimization method followed to identify the best regression model. The Box-Cox transformation was recognized as the most accurate surface grinding regression model.
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Tsyganov, A. V., and Yu V. Tsyganova. "Decentralized square-root information Kalman filtering based on J-orthogonal transformations." Journal of Physics: Conference Series 1745, no. 1 (2021): 012112. http://dx.doi.org/10.1088/1742-6596/1745/1/012112.
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Kaptsov, Oleg V. "Iterations and Groups of Formal Transformations." Journal of Siberian Federal University. Mathematics & Physics 14, no. 5 (2021): 584–88. http://dx.doi.org/10.17516/1997-1397-2021-14-5-584-588.
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In this paper, we consider the problem of formal iteration. We construct an area preserving mapping which does not have any square root. This leads to a counterexample to Moser’s existence theorem for an interpolation problem. We give examples of formal transformation groups such that the iteration problem has a solution for every element of the groups
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BINNENHEI, CARSTEN. "IMPLEMENTATION OF ENDOMORPHISMS OF THE CAR ALGEBRA." Reviews in Mathematical Physics 07, no. 06 (1995): 833–69. http://dx.doi.org/10.1142/s0129055x95000323.
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The implementation of non-surjective Bogoliubov transformations in Fock states over CAR algebras is investigated. Such a transformation is implementable by a Hilbert space of isometries if and only if the well-known Shale-Stinespring condition is met. In this case, the dimension of the implementing Hilbert space equals the square root of the Watatani index of the associated inclusion of CAR algebras, and both are determined by the Fredholm index of the corresponding one-particle operator. Explicit expressions for the implementing operators are obtained, and the connected components of the semigroup of implementable transformations are described.
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Yuan, Munan, Xiru Li, and Haibao Tan. "An Elastic Fine-Tuning Dual Recurrent Framework for Non-Rigid Point Cloud Registration." Sensors 25, no. 11 (2025): 3525. https://doi.org/10.3390/s25113525.
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Non-rigid transformation is based on rigid transformation by adding distortions to form a more complex but more consistent common scene. Many advanced non-rigid alignment models are implemented using supervised learning; however, the large number of labels required for the training process makes their application difficult. Here, an elastic fine-tuning dual recurrent computation for unsupervised non-rigid registration is proposed. At first, we transform a non-rigid transformation into a series of combinations of rigid transformations using an outer recurrent computational network. Then, the inner loop layer computes elastic-controlled rigid incremental transformations by controlling the threshold to obtain a finely coherent rigid transformation. Finally, we design and implement loss functions that constrain deformations and keep transformations as rigid as possible. Extensive experiments validate that the proposed method achieves state-of-the-art performance with 0.01219 earth mover’s distances (EMDs) and 0.0153 root mean square error (RMSE) in non-rigid and rigid scenes, respectively.
Dissertations / Theses on the topic "Square root transformations"
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Tejkal, Martin. "Vybrané transformace náhodných veličin užívané v klasické lineární regresi." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-318798.
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Klasická lineární regrese a z ní odvozené testy hypotéz jsou založeny na předpokladu normálního rozdělení a shodnosti rozptylu závislých proměnných. V případě že jsou předpoklady normality porušeny, obvykle se užívá transformací závisle proměnných. První část této práce se zabývá transformacemi stabilizujícími rozptyl. Značná pozornost je udělena náhodným veličinám s Poissonovým a negativně binomickým rozdělením, pro které jsou studovány zobecněné transformace stabilizující rozptyl obsahující parametry v argumentu navíc. Pro tyto parametry jsou stanoveny jejich optimální hodnoty. Cílem druhé části práce je provést srovnání transformací uvedených v první části a dalších často užívaných transformací. Srovnání je provedeno v rámci analýzy rozptylu testováním hypotézy shodnosti středních hodnot p nezávislých náhodných výběrů s pomocí F testu. V této části jsou nejprve studovány vlastnosti F testu za předpokladu shodných a neshodných rozptylů napříč výběry. Následně je provedeno srovnání silofunkcí F testu aplikovaného pro p výběrů z Poissonova rozdělení transformovanými odmocninovou, logaritmickou a Yeo Johnsnovou transformací a z negativně binomického rozdělení transformovaného argumentem hyperbolického sinu, logaritmickou a Yeo-Johnsnovou transformací.
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Lin, Chien-Chih, and 林建志. "Improved Square Root Transformation for Attribute Control Charts." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/79083646337915341895.
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碩士<br>淡江大學<br>統計學系<br>90<br>The 3-sigma control limits have historically been used in attribute control charts. It is inadequate to apply p-chart and np-chart on monitoring the binomial data and that always result in negative 3-sigma lower control limits for these charts when p is small. These shortcomings will also occur in c-chart when we monitoring the Poisson data with c is small. To improve these shortcomings of these attribute control charts, the article suggests to use a square root transformation technique to produce the control limits for p-chart、np-chart and c-chart. These charts are named ISRT attribute control charts .
In this article we provide the control limits of ISRT attribute control charts, such that these charts can produce tail probabilities that are close to the nominal tail probabilities ( 0.00135 , 0.00135 ), and we provide some tables that can be used in practical operation. In addition, comparing with the classical 3-sigma p-chart, the modified p-chart proposed by Winterbottom (1993) and Chen (1998), the regression-based p-chart proposed by Ryan and Schwertman (1997) and Q-chart, the minimum sample size needed to produce a positive lower control limit for the ISRT p-chart is much smaller than others. Finally, we conduct sensitivity analysis to compare the performance of these approaches. The numerical results suggest that the ISRT attribute control charts are adequate for charting Poisson and binomial data, especially for c and p are small.
Books on the topic "Square root transformations"
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Gentile, Emilio. God's Democracy. Praeger, 2008. http://dx.doi.org/10.5040/9798400658228.
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InGod's Democracy, Emilio Gentile argues that the presidency of George W. Bush sought to alter the way religion functions in American political life. Prior to the events of 9/11, the national government operated under a civil religious regime that placed a sacred umbrella over the entire country and its leading political figures. American civil religion was not only an inclusive faith, but one that provided ample room for citizens with different politics and different world views. But in the wake of 9/11, President Bush used religion to differentiate Americans on partisan lines. Relying heavily on his evangelical Christian base, he attempted to substitute for the inclusivism of the traditional American civil religion an exclusivist political religion in which Democrats were portrayed as hostile to religious values and incapable of dealing with the country's foreign enemies. This book provides the historical context for this attempted transformation, and shows in a detailed way how the Bush administration pursued it. Gentile concludes by posing the question of whether this radical shift in the way Americans understand themselves religiously will prove permanent. Unlike other works that strive to show how religion has generally come to be treated in American politics, this new book looks more squarely at the Bush Administration and its attempt to shut out Democrats from the political process by invoking religious language and ideals. He goes on to consider the political exclusivism and whether or not it will persist beyond Bush's tenure.
Book chapters on the topic "Square root transformations"
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Rukhin, Andrew L. "Estimating Quadratic Polynomials with Applications to Square Root Normalizing Transformations." In Mathematical Statistics and Probability Theory. Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3965-3_19.
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Selliah, J., and A. Sharma. "Square Root Transformation of Data in an Effluent Limit Setting Program." In Stochastic and Statistical Methods in Hydrology and Environmental Engineering. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-017-3081-5_10.
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Pham, Anh Thu, Adèle Lesage, Pierrick Sergent, and Adrien Aubert. "Physical Modelling of Container Ship Propulsion and Comparison with Operational Data." In Lecture Notes in Mobility. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-89444-2_83.
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Abstract International Maritime Organization (IMO) has adopted a strategy to reduce at least 50% of GHG emissions from the global shipping sector by 2050, compared to 2008. Preparing for these requirements, a 4-year R&D project, TNTM (Digital Transformation of Maritime Transport) was initiated. As part of this project, the current work presents the physical models that compares their outputs with actual on-board measurements on a LNG powered containership. The main propulsive systems were modelled using SEECAT (Ship Energy Efficiency Calculation and Analysis Tool), an in-house tool developed by Bureau Veritas Marine & Offshore. A custom hull performance model was developed assuming the vessel’s static equilibrium under the different forces and moments. The later have been estimated through CFD and includes calm water resistance depending on drift & rudder angles as well as added resistance by wave and wind. A simulation has been performed for a complete rotation, which lasts about 3 months between Asia and Europe. The comparison of the numerical results and the data recorded at sea were carried out. A good agreement has been obtained, the root-mean-square error during the steady state of the engine power and the fuel consumption is 7.6% and 9.1% respectively.
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Hector, Andy. "Generalized Linear Models." In The New Statistics with R. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198798170.003.0015.
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This chapter revisits a regression analysis to explore the normal least squares assumption of approximately equal variance. It also considers some of the data transformations that can be used to achieve this. A linear regression of transformed data is compared with a generalized linear-model equivalent that avoids transformation by using a link function and non-normal distributions. Generalized linear models based on maximum likelihood use a link function to model the mean (in this case a square-root link) and a variance function to model the variability (in this case the gamma distribution, where the variance increases as the square of the mean). The Box–Cox family of transformations is explained in detail.
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Anderson, Raymond A. "Practical Application." In Credit Intelligence & Modelling. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192844194.003.0013.
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This chapter provides further practical detail where prior theoretical background was insufficient but focused on binary categorization. (1) Data transformation—i) rescaling—mathematical transformations applied directly to predictors {min-max, log/exponent, power/root, theoretical distribution &c}; ii) discretization—subject counts allow {dummy variables, weights of evidence, piecewise}. (2) Characteristic assessments—more specifics around use for discretized predictors and binary targets {weight of evidence, information value, population stability index, chi-square}. (3) Model assessments—like (2), but for assessing model outputs {Lorenz curve, Gini coefficients, cumulative accuracy profile, divergence statistic}. (4) Odds and sods—measures that do not fit nicely elsewhere, like both subject-level and naïve accuracy based on log-likelihoods, and Calinski–Harabasz statistic to identify clusters based on model outputs {e.g. scores}. Methods for calculating Gini coefficients’ variance are also included.
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Vargas-Zapata, Mateo, Marisol Medina-Sierra, Luis Fernando Galeano-Vasco, and Mario Fernando Cerón-Muñoz. "Development of Machine Learning Models for Predicting Soil Texture Variables through Hyperspectral Imaging." In Technologies and Innovations in Agriculture [Working Title]. IntechOpen, 2025. https://doi.org/10.5772/intechopen.1009853.
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Soil texture is a crucial property that can provide insight into its productive capacity. However, determining soil texture can be a complex and time-consuming process. To address this challenge, we aimed to develop machine learning (ML) models that could predict the composition of sand, clay, and silt in soil based on hyperspectral imaging (HSI) data. We collected and analyzed 500 soil samples and processed the HSI data by masking samples with reflectance and transforming the texture variables with Box-Cox. We also employed various techniques, such as moving average, Savitzky–Golay filtering (SG), first and second derivatives (FD and SD), gap-segment (GS) with FD and SD, standard normal variate (SNV), SNV with detrending (DT), SNV-SG, multiplicative scatter correction (MSC), and GS-DT for the covariates. We applied cubist models (CUB), principal component regression (PCR), partial least squares regression (PLSR), and artificial neural networks (ANN). A total of 1240 models were obtained. For clay, the models with the best performance in the TRAIN and TEST sets were a CUB-tuned model, where R2-TEST = 0.93 and the test root-mean-square error (RMSE-TEST) = 3.63%. For silt and sand, CUB models without refinement were selected, with R2-TEST values of 0.63 and 0.61 and RMSE-TEST of 5.55 and 8.65%, respectively. In conclusion, clay prediction with HSI is feasible if purified spectra are used, with outlier detection techniques, evaluation in the overlap zone, and transformations such as GS-FD. The models for silt and sand prediction are not recommended due to their low performance.
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López-Correa, Juan Manuel, Caroline König, and Alfredo Vellido. "Long Short-Term Memory to Predict 3D Amino Acids Positions in GPCR Molecular Dynamics." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2022. http://dx.doi.org/10.3233/faia220339.
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G-Protein Coupled Receptors (GPCRs) are a big family of eukaryotic cell transmembrane proteins, responsible for numerous biological processes. From a practical viewpoint around 34% of the drugs approved by the US Food and Drug Administration target these receptors. They can be analyzed from their simulated molecular dynamics, including the prediction of their behavior in the presence of drugs. In this paper, the capability of Long Short-Term Memory Networks (LSTMs) are evaluated to learn and predict the molecular dynamic trajectories of a receptor. Several models were trained with the 3D position of the amino acids of the receptor considering different transformations on the position of the amino acid, such as their centers of mass, the geometric centers and the position of the α–carbon for each amino acid. The error of the prediction of the position was evaluated by the mean average error (MAE) and root-mean-square deviation (RMSD). The LSTM models show a robust performance, with results comparable to the state-of-the-art in non-dynamic 3D predictions. The best MAE and RMSD values were found for the mass center of the amino acids with 0.078 Å and 0.156 Å respectively. This work shows the potential of LSTM to predict the molecular dynamics of GPRCs.
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Feng, Haoxian, and Thomas Tran. "Context-Aware Approach for Restaurant Recommender Systems." In Advances in Computer and Electrical Engineering. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7598-6.ch024.
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This chapter addresses the issue of how to effectively use users' historical data in restaurant recommender systems, as opposed to systems, such as FindMe, that only rely on online operations. Towards that end, the authors propose a bias-based SVD method as the underlying recommendation algorithm and test it against the traditional item-based collaborative filtering method on the Entrée restaurant dataset. The results are promising as the obtained root-mean-square-error (RMSE) values reach 0.58 for the SVD and 0.62 for the item-based system. Researchers can extend the transformation from user behaviors to ratings in more application domains other than the restaurant one.
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Feng, Haoxian, and Thomas Tran. "Context-Aware Approach for Restaurant Recommender Systems." In Encyclopedia of Information Science and Technology, Fourth Edition. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2255-3.ch153.
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This paper addresses the issue of how to effectively use users' historical data in restaurant recommender systems, as opposed to systems, such as FindMe, that only rely on online operations. Towards that end, the authors propose a bias-based SVD method as the underlying recommendation algorithm and test it against the traditional item-based collaborative filtering method on the Entrée restaurant dataset. The results are promising as the obtained Root-Mean-Square-Error (RMSE) values reach 0.58 for the SVD and 0.62 for the item-based system. Researchers can extend the transformation from user behaviors to ratings in more application domains other than the restaurant one.
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Ashcroft, E. A., A. A. Faustini, R. Jaggannathan, and W. W. Wadge. "Transformation and Verification." In Multidimensional Programming. Oxford University Press, 1995. http://dx.doi.org/10.1093/oso/9780195075977.003.0007.
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The ability to verify and reason about programs was one of the main goals behind the design and development of Lucid. In fact, from its very inception Lucid was intended to be not just a programming language, but also a formal system in which program specifications and correctness proofs could be expressed as well. Our goal was a formal programming system in which programs for “realistically” complicated problems could be proved correct with only a realistic amount of effort. The nonprocedural nature of Lucid and its mathematical semantics led naturally to a reasoning technique where properties proved of variables and functions (assertions) are true throughout the where clauses in which the variables and functions are defined, and are not just thought of as being true at particular points where they are “attached” (as would be the case in the usual verification technique for procedural programs). In that respect, Lucid verification is like verification of functional programs. The assertions proved for Lucid, however, have the basic simplicity of the assertions proved in the procedural case, and the proofs are very similar. We will illustrate the differences by using a very simple program for computing integer square roots. We will express it in an imperative language, in a functional language, and in Lucid and show how verification would be performed for each language using the different techniques. In all three techniques, we will use the following terminology from the procedural approach, namely that the precondition is a restriction on the inputs of a program and the postcondition is a desired property of the outputs of the program, assuming that the inputs satisfied the precondition.
Conference papers on the topic "Square root transformations"
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Carreira, Beatriz Liara, Analice Costacurta Brandi, Laison Junio da Silva Furlan, Matheus Tozo de Araujo, and Leandro Franco de Souza. "Log-Conformation and Square Root-Conformation Transformations in High Weissenberg Number Flows." In 25th International Congress of Mechanical Engineering. ABCM, 2019. http://dx.doi.org/10.26678/abcm.cobem2019.cob2019-1949.
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M. Khudhur, Azhin, Dler H. Kadir, Sakar A. Jalal, and Rebaz O. Yahya. "Evaluating Power Usage Patterns: A Case Study on Time Series Modeling Forecasting in Erbil City, 2015–2024." In The 5th International Scientific Conference on Administrative and Financial Sciences (CIC-ISCAFS'2025). Cihan University-Erbil, 2025. https://doi.org/10.24086/icafs2025/paper.1598.
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Abstract—Precise electricity consumption predictions are essential for efficient energy management, resource allocation, and power system stability, especially in expanding urban areas like Erbil. Time series models are crucial in this field because they can capture trends, seasonal variations, and structural shifts in energy use patterns. This study aims to forecast electricity consumption in Erbil for 2025 by leveraging the Autoregressive Integrated Moving Average (ARIMA) model, a widely recognized approach in time series analysis. 3,652 historical daily electricity use data observations from 2015 to 2024 were examined. Among the preprocessing procedures were first differencing to attain stationarity and logarithmic transformation to handle outliers. Evaluation criteria including the Akaike Information Criterion (AIC), Root Mean Square Error (RMSE), and Mean Squared Error (MSE) were given top priority during the model selection process. With an MSE of 0.0487347, the seasonal ARIMA(1,1,1)x(0,1,1)12 model was found to be the most successful. Yule-Walker equations, Maximum Likelihood, and Least Squares were among the optimization approaches used in parameter estimation; t-tests were used to confirm statistical significance. Monthly averages for 2025 ranged from 955 MW in January to 916 MW in December, indicating notable seasonal changes. The importance of time series models in tackling the difficulties of resource planning and energy demand forecasting is highlighted by this study, which offers a solid foundation for controlling Erbil's seasonal and structural consumption patterns. Keywords—Electricity Consumption Forecasting, Time Series Analysis, ARIMA Model, Seasonal Patterns, Statistical Modeling, Akaike Information Criterion (AIC), Mean Squared Error (MSE)
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Makaryan, Vahagn, Michael Sutton, Gurgen Chlingaryan, Davresh Hasanyan, and Xiaomin Deng. "Some Boundary Value Problems of Elastic Media Containing Rigid Inclusions Under Compressive Mechanical Loads." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-11843.
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In this work we discuss some 2D boundary-value problems related to an elastic medium containing a thin rigid inclusion with general geometrical shape located in the interface between two separate elastic half-planes and subjected to compressive loading. Assuming perfect bonding between the inclusion and elastic medium, Fourier and Henkel integral transformation techniques are used to obtain the exact solution for the problem. Explicit forms are presented for arbitrary forms of thin inclusions, demonstrating that the tangent shear stress at the end-points of the inclusion has a square-root singularity. It is also shown that the normal stress has a logarithmic singularity when the end-points of the inclusion are approached from the inside of the inclusion and a square-root singularity when the end-points of the inclusion are approached from the outside of the inclusion. For special, extreme cases the solutions for anti-cracks are also presented.
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Aghili, F. "A gauge-invariant formulation for constrained robotic systems using square-root factorization and unitary transformation." In 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2008. http://dx.doi.org/10.1109/iros.2008.4650682.
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Baxevanis, Theocharis, Yves Chemisky, and Dimitris Lagoudas. "On the Path-Dependency of the J-Integral in a Pseudoelastic Shape Memory Alloy." In ASME 2011 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASMEDC, 2011. http://dx.doi.org/10.1115/smasis2011-5004.
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Detailed finite-element calculations are carried out to examine the path-dependence of the J-integral in a pseudoelastic Shape Memory Alloy (SMA) for mode I loading under the approximation of linear kinematics. The evolution equation for the transformation strain is consistent with the classical rate-independent J2 flow theory. The small-scale nonlinearity assumption is employed using a boundary layer approach, wherein the actual boundary conditions have been replaced by the requirement of an asymptotic approach to the linear elastic inverse-square-root stress/strain distribution at large distances from the crack tip. The J-integral is found to be path-dependent inside the transformation zone, close to the crack tip.
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Khodaygan, S., M. R. Movahhedy, A. Mirabolghasemi, M. Zendehbad, and H. Moradi. "Statistical Error Analysis for Dimensional Control in Automotive Body Assembly Process." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-25411.
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In mechanical assemblies, the performance, quality, cost and assemblability of the product are significantly affected by the geometric errors of the parts. This paper develops the statistical error analysis approach for dimensional control in automotive body multi-station assembly process. In this method, the homogeneous transformation matrices are used to describe the location and orientation of part and assembly features and the small homogeneous transformation matrices are used to model the errors. In this approach, the effective errors in automotive body assembly process are classified in three categories: manufacturing errors (dimensional and geometric tolerances), locating errors (fixture errors) and process errors (joining errors). In a mechanical assembly, small variations due the errors propagate according to a complex mechanism that in this approach it formulated in error analysis procedure. The propagation chain of geometric errors is described based on CAD models. The estimation of the error accumulation and the percent contributions of individual errors are based on the statistical model (root-sum-square method). The application of the proposed method is illustrated through presenting an example problem.
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Li, Yajing, Dunji Yu, and Xu Chen. "Effects of Strain Amplitude and Loading Path on Cyclic Behavior and Martensitic Transformation of 304 Stainless Steel." In ASME 2018 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/pvp2018-84888.
Full textAbstract:
Effects of strain amplitude and loading path on cyclic deformation behavior and martensitic transformation of 304 stainless steel were experimentally investigated at room temperature. Series of symmetrical strain-control low cycle fatigue tests with strain amplitude ranging from 0.4% to 1.0% and various loading paths (uniaxial, torsional, proportional, rhombus, square and circular) with the same equivalent strain amplitude of 0.5% were carried out. Three-stage cyclic deformation behavior containing initial hardening, cyclic softening or saturation, and secondary hardening as well as near-linear relationship between α’-martensite content and number of cycles was observed during the whole life regime as for each test. Besides, a nearly linear relation between peak stress and α’-martensite content was found during secondary hardening stage. Furthermore, higher strain amplitude or non-proportionality of loading path resulted in higher cyclic stress response and α’-martensite content growth rate, defined by the slope of curves of α’-martensite content versus number of cycles.
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Narvaez-Aroche, Octavio, Andrew Packard, and Murat Arcak. "Motion Planning of the Sit to Stand Movement for Powered Lower Limb Orthoses." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5289.
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We propose a generalizable strategy for planning the sit to stand movement of a powered lower limb orthosis and its user. Modeling the system as a three rigid link planar robot, we rely on its kinematic equations to obtain a set of transformations that allows us to compute reference trajectories for the angular positions of the links, starting from a desired kinematic behavior for the center of mass of the robot and the angular position of link 2 relative to link 1; as we consider them more suitable to define for achieving a safe sit to stand transition. We then proceed to design a tracking controller via feedback linearization and solve a constrained least-squares program to address the control allocation problem from including the loads applied by the arms of the user as inputs. We simulate two relevant STS movements to illustrate the system tracking the reference trajectories generated with our strategy, in the presence of parameter uncertainty.
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LIU, Yang. "Superplastic microstructure characteristics and unified constitutive model of TA32 titanium alloy." In Metal Forming 2024. Materials Research Forum LLC, 2024. http://dx.doi.org/10.21741/9781644903254-9.
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Abstract. The superplastic deformation behavior and microstructure characteristics of TA32 titanium alloy were studied at different deformation temperatures (920-960°C) and initial strain rates (1×10-3-3×10-3 s-1). A unified constitutive model was developed and coupled with internal state variables. Results show that TA32 alloy featured steady flow stress and uniform plastic deformability under the dynamic equilibrium between softening and hardening effects. Increasing temperature and strain induced α→β phase transformation and α grain growth. Dislocation accumulation and grain boundary migration formed the dynamic recovery (DRV) and dynamic recrystallization (DRX) mechanisms. Using dislocation density, the proposed unified constitutive model built a quantitative relationship between superplastic flow stress and internal state variables such as grain size, with the correlation coefficient R, average absolute relative error (AARE), and root mean square error (RMSE) between the predicted and experimental stress values being 0.98, 6.91%, and 1.94, respectively. The unified constitutive model could predict well the flow stress and grain size evolution of TA32 titanium alloy during superplastic deformation.
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Lu, Ping, Y. Kevin Chou, and Raymond G. Thompson. "AE Signal Evolutions in Machining by Diamond Coated Tools." In ASME 2009 International Manufacturing Science and Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/msec2009-84372.
Full textAbstract:
Diamond coated cutting tools have a potential to replace costly polycrystalline diamond tools. However, coating delaminations remain the primary wear mode that often results in catastrophic tool failures, causing to poor part quality and possible damage to machine tools. Moreover, delamination events are difficult to be precisely predicted. Thus, tool delamination identification is necessary for process monitoring. Following a previous work, this study examines the acoustic emission (AE) signal evolutions during machining by diamond coated tools, in particular, the frequency response along cutting time as well as during a specific cutting pass. The intent was to correlate the characteristics of the AE spectral components with coating delaminations. The results are summarized as follows. Though AE root-mean-square values have been used to monitor tool failure, it may not show clear transition registered to coating delamination in some cases. The fast Fourier transformation (FFT) spectra of AE data along cutting time generally show decreased intensity for low frequency peaks, but increased intensity for high frequency peaks. In addition, the AE FFT spectra of sub-divided time zones during one cutting pass may clearly indicate the coating failure transition.
Reports on the topic "Square root transformations"
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Cohen, Roni, Kevin Crosby, Menahem Edelstein, et al. Grafting as a strategy for disease and stress management in muskmelon production. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7613874.bard.
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The overall objective of this research was to elucidate the horticultural, pathological, physiological and molecular factors impacting melon varieties (scion) grafted onto M. cannonballus resistant melon and squash rootstocks. Specific objectives were- to compare the performance of resistant melon germplasm (grafted and non-grafted) when exposed to M. cannoballus in the Lower Rio Grande valley and the Wintergarden, Texas, and in the Arava valley, Israel; to address inter-species relationships between a Monosporascus resistant melon rootstock and susceptible melon scions in terms of fruit-set, fruit quality and yield; to study the factors which determine the compatibility between the rootstock and the scion in melon; to compare the responses of graft unions of differing compatibilities under disease stress, high temperatures, deficit irrigation, and salinity stress; and to investigate the effect of rootstock on stress related gene expression in the scion. Some revisions were- to include watermelon in the Texas investigations since it is much more economically important to the state, and also to evaluate additional vine decline pathogens Didymella bryoniae and Macrophomina phaseolina. Current strategies for managing vine decline rely heavily on soil fumigation with methyl bromide, but restrictions on its use have increased the need for alternative management strategies. Grafting of commercial melon varieties onto resistant rootstocks with vigorous root systems is an alternative to methyl bromide for Monosporascus root rot/vine decline (MRR/VD) management in melon production. Extensive selection and breeding has already produced potential melon rootstock lines with vigorous root systems and disease resistance. Melons can also be grafted onto Cucurbita spp., providing nonspecific but efficient protection from a wide range of soil-borne diseases and against some abiotic stresses, but compatibility between the scion and the rootstock can be problematic. During the first year experiments to evaluate resistance to the vine decline pathogens Monosporascus cannonballus, Didymella bryoniae, and Macrophomina phaseolina in melon and squash rootstocks proved the efficacy of these grafted plants in improving yield and quality. Sugars and fruit size were better in grafted versus non-grafted plants in both Texas and Israel. Two melons (1207 and 124104) and one pumpkin, Tetsukabuto, were identified as the best candidate rootstocks in Texas field trials, while in Israel, the pumpkin rootstock RS59 performed best. Additionally, three hybrid melon rootstocks demonstrated excellent resistance to both M. cannonballus and D. bryoniae in inoculated tests, suggesting that further screening for fruit quality and yield should be conducted. Experiments with ABA in Uvalde demonstrated a significant increase in drought stress tolerance and concurrent reduction in transplant shock due to reduced transpiration for ‘Caravelle’ plants. In Israel, auxin was implicated in reducing root development and contributing to increased hydrogen peroxide, which may explain incompatibility reactions with some squash rootstocks. However, trellised plants responded favorably to auxin (NAA) application at the time of fruit development. Gene expression analyses in Israel identified several cDNAs which may code for phloem related proteins, cyclins or other factors which impact the graft compatibility. Manipulation of these genes by transformation or traditional breeding may lead to improved rootstock cultivars. Commercial applications of the new melon rootstocks as well as the ABA and TIBA growth regulators have potential to improve the success of grafted melons in both Israel and Texas. The disease resistance, fruit quality and yield data generated by the field trials will help producers in both locations to decide what rootstock/scion combinations will be best.