Thematische Bibliographien / DIT prediction

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Auswahl der wissenschaftlichen Literatur zum Thema „DIT prediction“

Autor: Grafiati

Veröffentlicht am 7. Juni 2025

Zuletzt aktualisiert am 2. August 2025

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Zeitschriftenartikel zum Thema "DIT prediction"

Prykhodko, Sergiy, Natalia Prykhodko, and Tetyana Smykodub. "A Statistical Evaluation of The Depth of Inheritance Tree Metric for Open-Source Applications Developed in Java." Foundations of Computing and Decision Sciences 46, no. 2 (2021): 159–72. http://dx.doi.org/10.2478/fcds-2021-0011.

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Abstract The Depth of Inheritance Tree (DIT) metric, along with other ones, is used for estimating some quality indicators of software systems, including open-source applications (apps). In cases involving multiple inheritances, at a class level, the DIT metric is the maximum length from the node to the root of the tree. At an application (app) level, this metric defines the corresponding average length per class. It is known, at a class level, a DIT value between 2 and 5 is good. At an app level, similar recommended values for the DIT metric are not known. To find the recommended values for t

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Lin, Jinzhu, Yujie He, Chengxiang Ru, Wulin Long, Menglong Li, and Zhining Wen. "Advancing Adverse Drug Reaction Prediction with Deep Chemical Language Model for Drug Safety Evaluation." International Journal of Molecular Sciences 25, no. 8 (2024): 4516. http://dx.doi.org/10.3390/ijms25084516.

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The accurate prediction of adverse drug reactions (ADRs) is essential for comprehensive drug safety evaluation. Pre-trained deep chemical language models have emerged as powerful tools capable of automatically learning molecular structural features from large-scale datasets, showing promising capabilities for the downstream prediction of molecular properties. However, the performance of pre-trained chemical language models in predicting ADRs, especially idiosyncratic ADRs induced by marketed drugs, remains largely unexplored. In this study, we propose MoLFormer-XL, a pre-trained model for enco

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Chen, Weijun, and Yanze Wang. "DHMoE: Diffusion Generated Hierarchical Multi-Granular Expertise for Stock Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 11 (2025): 11490–99. https://doi.org/10.1609/aaai.v39i11.33250.

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Stock prediction stands as a pivotal research objective within the Fintech. Existing deep learning research revolves around the development and scaling of one individual neural network predictor. However, in the dynamic and noisy landscape of the stock market, reliance solely on a single predictor poses risks of limited adaptability to diverse market conditions and challenges in effectively integrating multi-source information. Besides, top-down teaching and bottom-up hierarchical decision-making paradigms are critical for robust and accurate stock prediction within successful quantitative fir

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Lv, Lingling, Pucheng Pei, Peng Ren, He Wang, and Geng Wang. "Exploring Performance Degradation of Proton Exchange Membrane Fuel Cells Based on Diffusion Transformer Model." Energies 18, no. 5 (2025): 1191. https://doi.org/10.3390/en18051191.

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Proton exchange membrane fuel cells (PEMFCs) stand at the forefront of energy conversion technology, efficiently converting the chemical energy of hydrogen and oxygen directly into electricity. Research on predicting the remaining useful life of PEMFCs has long been a focus, as it plays a crucial role in preventing failures and mitigating safety risks. This paper introduces a robust diffusion transformer (DiT) model, which is a novel approach leveraging generative artificial intelligence (GAI) technology to innovate the existing methods for predicting the performance degradation of PEMFCs. Thi

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Prykhodko, A. S., and E. V. Malakhov. "DETERMINING OBJECT-ORIENTED DESIGN COMPLEXITY DUE TO THE IDENTIFICATION OF CLASSES OF OPEN-SOURCE WEB APPLICATIONS CREATED USING PHP FRAMEWORKS." Radio Electronics, Computer Science, Control, no. 2 (June 27, 2024): 160. http://dx.doi.org/10.15588/1607-3274-2024-2-16.

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Context. The problem of determining the object-oriented design (OOD) complexity of the open-source software, including Web apps created using the PHP frameworks, is important because nowadays open-source software is growing in popularity and using the PHP frameworks making app development faster. The object of the study is the process of determining the OOD complexity of the open-source Web apps created using the PHP frameworks. The subject of the study is the mathematical models to determine the OOD complexity due to the identification of classes of the open-source Web apps created using the

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Kar, Subhajit, Madhabi Ganguly, and Saptarshi Das. "USING DIT-FFT ALGORITHM FOR IDENTIFICATION OF PROTEIN CODING REGION IN EUKARYOTIC GENE." Biomedical Engineering: Applications, Basis and Communications 31, no. 01 (2019): 1950002. http://dx.doi.org/10.4015/s1016237219500029.

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The new research platform on biomedical engineering by Digital Signal Processing (DSP) is playing a vital role in the prediction of protein coding regions (Exons) from genomic sequences with great accuracy. We can determine the protein coding area in DNA sequences with the help of period-3 property. It has been seen that in order to find out the period-3 property, the DFT algorithm is mostly used but in this paper, we have tested FFT algorithm instead of DFT algorithm. DSP is basically concerned with processing numerical sequences. When digital signal processing used in DNA sequences analysis,

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Yousefi, Mehran, Mehdi Panahali, Kamran Azarkhish, et al. "Diagnostic value of DWI-MRI for the detection of acute plaques in the relapse phase of multiple sclerosis." Romanian Journal of Neurology 20, no. 1 (2021): 35–40. http://dx.doi.org/10.37897/rjn.2021.1.5.

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Background. The 2010 revision of the McDonald criteria, widely used for the diagnosis of multiple sclerosis (MS), has established that dissemination in time (DIT) can be demonstrated by the simultaneous presence of asymptomatic gadolinium-enhancing and non-enhancing plaques on a single magnetic resonance imaging (MRI). When the use of gadolinium contrast agents is contraindicated, diffusion-weighted imaging (DWI) is utilized to confirm diffusion alterations in active inflammatory plaques. This study intended to examine whether DWI can be a viable alternative to contrast-enhanced T1-weighted im

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Aziz, Syed Rashid, Tamim Ahmed Khan, and Aamer Nadeem. "Exclusive use and evaluation of inheritance metrics viability in software fault prediction—an experimental study." PeerJ Computer Science 7 (June 4, 2021): e563. http://dx.doi.org/10.7717/peerj-cs.563.

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Software Fault Prediction (SFP) assists in the identification of faulty classes, and software metrics provide us with a mechanism for this purpose. Besides others, metrics addressing inheritance in Object-Oriented (OO) are important as these measure depth, hierarchy, width, and overriding complexity of the software. In this paper, we evaluated the exclusive use, and viability of inheritance metrics in SFP through experiments. We perform a survey of inheritance metrics whose data sets are publicly available, and collected about 40 data sets having inheritance metrics. We cleaned, and filtered t

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Taylor, C. S., J. I. Murray, and A. W. Illius. "Relative growth of incisor arcade breadth and eating rate in cattle and sheep." Animal Science 45, no. 3 (1987): 453–58. http://dx.doi.org/10.1017/s0003356100002932.

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ABSTRACTMaximum eating rate, rmax in kj metabolizable energy per min, at a given body weight W kg, can be predicted in normally growing cattle when adult body weight, A kg, is known, by the formula of Taylor and Murray (1987) as rmax = 31μ0·86 A0·73 where u = W/A is degree of maturity in body weight. When the pattern of normal growth is disturbed by fluctuating levels of food intake, a better prediction can be obtained in terms of incisor arcade breadth. This paper gives the allometric relationship between degree of maturity in body weight, u, and degree of maturity in incisor arcade breadth u

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Lebedevas, Sergejus, Saugirdas Pukalskas, and Vygintas Daukšys. "MATHEMATICAL MODELLING OF INDICATIVE PROCESS PARAMETERS OF DUAL-FUEL ENGINES WITH CONVENTIONAL FUEL INJECTION SYSTEM." Transport 35, no. 1 (2020): 57–67. http://dx.doi.org/10.3846/transport.2020.12212.

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Modern engine research uses multi-dimensional Mathematical Models (MMs) that are applicable to multi-fuel engines. However, their use involves the availability of detailed technical data on the design and characteristics of the engine, which is not always possible. The use of a one-dimensional MM is more expedient for the prediction of engine parameters, but their application for this purpose has not yet been sufficiently investigated. This publication presents the results of numerical studies evaluating the application of a one-dimensional MM with bi-phase Vibe combustion laws for dual-fuel (

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Dissertationen zum Thema "DIT prediction"

Hogan, Patrick Alan. "Prediction and Reduction of Die Soldering." Digital WPI, 2008. https://digitalcommons.wpi.edu/etd-theses/523.

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Die Soldering occurs in aluminum permanent mold casting when the cast metal bonds with the die surface and remains stuck upon ejection of the part. Eventually, this layer builds up and production must be stopped for cleaning. It was estimated in a Contech squeeze casting plant in Pierceton, IN, that 1.5% of variable overhead can be directly attributed to die soldering. Previous work at WPI has focused on developing the mechanism of how soldering occurs. This work focuses on how that knowledge can be applied in an industrial setting. The work has focused on 4 major areas: (1) Using MAGMA

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Bielby, Matthew Iain. "Ultra low power cooperative branch prediction." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/14187.

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Branch Prediction is a key task in the operation of a high performance processor. An inaccurate branch predictor results in increased program run-time and a rise in energy consumption. The drive towards processors with limited die-space and tighter energy requirements will continue to intensify over the coming years, as will the shift towards increasingly multicore processors. Both trends make it increasingly important and increasingly difficult to find effective and efficient branch predictor designs. This thesis presents savings in energy and die-space through the use of more efficient coope

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Wynn, Jamie Michael. "First-principles structure prediction of extreme nanowires." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/282997.

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Low-dimensional systems are an important and intensely studied area of condensed matter physics. When a material is forced to adopt a low-dimensional structure, its behaviour is often dramatically different to that of the bulk phase. It is vital to predict the structures of low-dimensional systems in order to reliably predict their properties. To this end, the ab initio random structure searching (AIRSS) method, which has previously been used to identify the structures of bulk materials, has been extended to deal with the case of nanowires encapsulated inside carbon nanotubes. Such systems are

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Shi, Qi. "PREDICTION OF THERMAL DISTORTION AND THERMAL FATIGUE IN SHOT SLEEVES." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1034967167.

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Goyenola, Cecilia. "Nanostructured carbon-based thin films : prediction and design." Doctoral thesis, Linköpings universitet, Tunnfilmsfysik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121021.

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Carbon-based thin films are a vast group of materials of great technological importance. Thanks to the different bonding options for carbon, a large variety of structures (from amorphous to nanostructured) can be achieved in the process of film synthesis. The structural diversity increases even more if carbon is combined with relatively small quantities of atoms of other elements. This results in a set of materials with many different interesting properties for a wide range of technological applications. This doctoral thesis is about nanostructured carbon-based thin films. In particular, the f

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Grobaski, Thomas. "Preliminary Research for the Development of a Hot Forging Die Life Prediction Model." Ohio University / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1102695461.

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Sivertsen, Halses Sebastian. "Die life prediction using High Pressure Die Casting simulations." Thesis, Tekniska Högskolan, Jönköping University, JTH, Material och tillverkning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-50031.

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Global trends in automotive industry for weight reduction drives an interest for casting of structural aluminum parts. High pressure die casting (HPDC) is chosen for this purpose since it enables manufacturing of large series parts where complexity and repeatability is demanded. Aluminum alloys have hence been developed through the years to obtain suitable mechanical properties for high strength parts. These alloys have been investigated to predict the types of potential failure mechanisms during HPDC in order to determine die life through simulations. Die life prediction was performed through

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Lindner, Dominik. "Towards the fracture prediction of turbomachinery disks : a contribution of the digital image correlation." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLN023/document.

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Cette thèse s'intéresse à l'amélioration de la prévision de l'éclatement des pièces tournantes des turbomachines. L'axe de recherche principal a été celui de l'identification du comportement du matériau jusqu'à rupture pour des sollicitations multi-axiales représentatives et l'identification des conditions de rupture locale elles mêmes. Pour cela une approche basée sur la corrélation d'image numérique intégrée a été suivie. L'autre axe abordé dans cette thèse a été celui de la prévision objective et robuste de la rupture par la mécanique de l'endommagement dans le cadre de simulations explicit

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Keating, Marvin Scott. "Prediction of diet quality parameters of Rocky Mountain Elk via near infrared reflectance spectroscopy (NIRS) fecal profiling." Texas A&M University, 2003. http://hdl.handle.net/1969.1/3949.

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The objective of this experiment was to determine the validity of predicting the diet quality of Rocky Mountain Elk (Cervus elaphus nelsoni) by exposing a dried fecal sample to light energy (a spectrophotometer). The resulting spectra measured were then compared to the known wet chemistry of the diet to arrive at an equation for forecasting the crude protein (CP) and digestible organic matter (DOM) ingested by the elk. Forages were gathered from western ranges and blended to simulate plant species ingested representing various elk diet qualities at different seasons of the year. Feeding trials

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Buda, Corneliu. "De novo prediction of the ground state structure of transition metal complexes." Thesis, University of North Texas, 2004. https://digital.library.unt.edu/ark:/67531/metadc4669/.

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One of the main goals of computational methods is to identify reasonable geometries for target materials. Organometallic complexes have been investigated in this dissertation research, entailing a significant challenge based on transition metal diversity and the associated complexity of the ligands. A large variety of theoretical methods have been employed to determine ground state geometries of organometallic species. An impressive number of transition metals entailing diverse isomers (e.g., geometric, spin, structural and coordination), different coordination numbers, oxidation states and va

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Bücher zum Thema "DIT prediction"

Plessis, Lourens Marthinus Du. Tien perspektiewe: Gesprekke oor die toekoms. Tafelberg, 1988.

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Luhmann, Hans-Jochen. Die Blindheit der Gesellschaft: Filter der Risikowahrnehmung. Gerling Akademie Verlag, 2001.

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Gehmacher, Ernst. Reich und Grün: Die Zukunft unserer Gesellschaft. Molden, 1998.

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Dahle, Klaus-Peter. Psychologische Kriminalprognose: Wege zu einer integrativen Methodik für die Beurteilung der Rückfallwahrscheinlichkeit bei Strafgefangenen. Centaurus, 2005.

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Iris, Hossmann, Klingholz Reiner, and Berlin-Institut für Bevölkerung und Entwicklung, eds. Die demografische Zukunft von Europa: Wie sich die Regionen verändern. Deutscher Taschenbuch Verlag, 2008.

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Spode, Hasso. Die Zukunftsfähigkeit Deutschlands: Versuch einer Synthese : politisch, historisch, philosophisch. Wissenschaftszentrum Berlin für Sozialforschung (WZB), 2006.

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Zellmann, Peter. Die Zukunftsgesellschaft: --und wie wir in Österreich mit ihr umgehen müssen. Österreichische Verlagsgesellschaft, 2005.

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Hentschel, Karl-Martin. Von wegen alternativlos!: Die gerechte Gesellschaft als Ziel. Europa Verlag, 2013.

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Ambros, Hans. Die nächsten 40 Jahre: Das herausgeforderte Abendland und die Apokalypsen. J & V, 1993.

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Geisteswissenschaften, Stiftung für, ed. Die Schweiz, Aufbruch aus der Verspätung: Unsere Zukunft : 78 Autoren im Gespräch. Weltwoche-ABC-Verlag, 1991.

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Buchteile zum Thema "DIT prediction"

Hossen, Abdulnasir, and Ulrich Heute. "General Sub-Band DCT: Fast Approximate Adaptive Algorithm." In Signal Analysis and Prediction. Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-1768-8_3.

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Seebacher, Uwe. "Die Predictive Intelligence Fallstudien." In Predictive Intelligence für Manager. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-62776-1_9.

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Seebacher, Uwe. "Predictive Intelligence und die ökonomischen Grundprinzipien." In Predictive Intelligence für Manager. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-62776-1_1.

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Gu, Liang, and Xiaoming Li. "DFT Performance Prediction in FFTW." In Languages and Compilers for Parallel Computing. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13374-9_10.

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Frape, D. L. "Cancer and Diet." In The Future of Predictive Safety Evaluation. Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3201-2_12.

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Russell, Cheryl. "What the Baby Boom Will Die of." In 100 Predictions for the Baby Boom. Springer US, 1987. http://dx.doi.org/10.1007/978-1-4899-3468-0_8.

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Frape, D. L. "Immune Function and Diet." In The Future of Predictive Safety Evaluation. Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3201-2_11.

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von der Hude, Marlis. "Logistische Regression – Ein Prognoseverfahren für die Klassifikationsfragestellung." In Predictive Analytics und Data Mining. Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-30153-8_10.

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Holzer, Lorenz, Philip Marmet, Mathias Fingerle, Andreas Wiegmann, Matthias Neumann, and Volker Schmidt. "Towards a Quantitative Understanding of Microstructure-Property Relationships." In Tortuosity and Microstructure Effects in Porous Media. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-30477-4_5.

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Abstract100 years ago, the concept of tortuosity was introduced by Kozeny in order to express the limiting influence of the microstructure on porous media flow. It was also recognized that transport is hindered by other microstructure features such as pore volume fraction, narrow bottlenecks, and viscous drag at the pore surface. The ground-breaking work of Kozeny and Carman makes it possible to predict the macroscopic flow properties (i.e., permeability) based on the knowledge of the relevant microstructure characteristics. However, Kozeny and Carman did not have access to tomography and 3D i

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Frape, D. L. "Influence of Diet on Longevity." In The Future of Predictive Safety Evaluation. Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3201-2_13.

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Konferenzberichte zum Thema "DIT prediction"

Onuoha, C., S. McDonnell, and E. Pozniak. "Predicted and Actual Dig Outcome of Dry Gas Internal Corrosion Direct Assessment of Unpiggable Pipelines." In CORROSION 2018. NACE International, 2018. https://doi.org/10.5006/c2018-11300.

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Abstract Dry Gas Internal Corrosion Direct Assessment (DG-ICDA) specified in NACE SP0206-2006 was developed in an attempt to proactively prevent and predict locations susceptible to internal corrosion in natural gas pipelines normally transporting dry gas. The DG-ICDA inspection program is used for pipelines that are difficult or impossible to pig or inspect with inline inspection (ILI), as well as piggable pipelines, where it can be used as a supplement to ILI. This inspection program is suitable for natural gas pipelines that normally carry dry gas, but may suffer from infrequent short-term

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S, Aravamuthan, and Suhas S Kangde. "Prediction of Buckling and Maximum Displacement of Hood Oilcanning Using Machine Learning." In WCX SAE World Congress Experience. SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0155.

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<div class="section abstract"><div class="htmlview paragraph">Modern day automotive market demands shorter time to market. Traditional product development involves design, virtual simulation, testing and launch. Considerable amount of time being spent on virtual validation phase of product development cycle can be saved by implementing machine learning based predictive models for key performance predictions instead of traditional CAE. Durability oil canning loadcase for vehicle hood which impacts outer styling and involves time consuming CAE workflow takes around 11 days to complet

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Fan, Lei, Su Zhou, Chaokai Wen, and Jianhua Gao. "Prediction of the Remaining Useful Life of the Proton Exchange Membrane Fuel Cell with an Integrated Health Index." In SAE 2023 Vehicle Powertrain Diversification Technology Forum. SAE International, 2023. http://dx.doi.org/10.4271/2023-01-7013.

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<div class="section abstract"><div class="htmlview paragraph">To improve the prediction accuracy of the remaining useful life (RUL) of the proton exchange membrane fuel cell (PEMFC), an integrated health index (IHI) including electrical and non-electrical parameters of PEMFC is established, and the RUL prediction is conducted based on the above index. Firstly, several operating conditions including the PEMFC degradation information are selected according to the information theory method. Moreover, the IHI is established by the sequential quadratic programming method. Secondly, RUL

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Liu, Yuan, Xiaonan Chen, Zhou Lin, Yi-shou Wang, Qifeng Zhou, and Xinlin Qing. "Aeroengine Gas Path Parameter Trend Prediction Based on LSTM." In SAE 2023 Intelligent Urban Air Mobility Symposium. SAE International, 2023. http://dx.doi.org/10.4271/2023-01-7087.

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<div class="section abstract"><div class="htmlview paragraph">Accurately predicting the trend of aero-engine gas path parameters is crucial for ensuring safe flight and enabling condition-based maintenance. However, the demanding and uncertain service environment introduces challenges in dealing with the noisy and non-stationary data collected by engine gas path sensors. Traditional time series models struggle to accurately predicts parameter trends, resulting in insufficient fitting and prediction accuracy. In this paper, we address these challenges by leveraging the characteristi

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LAKSHMANAN, Vinith Kumar, Shobhit Gupta, Stefano D'Alessandro, et al. "Predicting Lead Vehicle Velocity for Eco-Driving in the Absence of V2V Information." In WCX SAE World Congress Experience. SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0220.

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<div class="section abstract"><div class="htmlview paragraph">Accurately predicting the future behavior of the surrounding traffic, especially the velocity of the lead vehicle is important for optimizing the energy consumption and improve the safety of Connected and Automated Vehicles (CAVs). Several studies report methods to predict short-to-mid-length lead vehicle velocity using stochastic models or other data-driven techniques, which require availability of extensive data and/or Vehicle-to-Vehicle (V2V) communication. In the absence of connectivity, or in data-restricted cases,

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Chen, Linxian, Xiuyu Shen, Jingxu Chen, and Xize Liu. "Network Feature-Enriched Machine Learning Model for Predictive Analytics of Flight Departure Delays in Smart Aviation." In 2024 International Conference on Smart Transportation Interdisciplinary Studies. SAE International, 2025. https://doi.org/10.4271/2025-01-7133.

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<div class="section abstract"><div class="htmlview paragraph">Due to the crucial impact on flight scheduling, airline planning, and airport operations, flight departure delay prediction has emerged as a severe and prominent issue within the realm of smart aviation systems. Accurately predicting flight departure delay durations constitutes a crucial aspect of smart aviation management. Such predictive capability empowers aviation authorities and airport regulators to implement optimized air traffic control strategies, mitigating delays and elevating airport operational efficiency, w

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Mahdev, Akash Ravishankar, Vinayak Lal, Pramod Muralimohan, Hemanjaneya Reddy, and Rachit Mathur. "Hybrid Approaches to Software Reliability: Evaluating and Enhancing Prediction Models." In Automotive Technical Papers. SAE International, 2025. https://doi.org/10.4271/2025-01-5024.

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<div class="section abstract"><div class="htmlview paragraph">Software reliability prediction involves predicting future failure rates or expected number of failures that can happen in the operational timeline of the software. The time-domain approach of software reliability modeling has received great emphasis and there exists numerous software reliability models that aim to capture the underlying failure process by using the relationship between time and software failures. These models work well for one-step prediction of time between failures or failure count per unit time. But

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Zhu, Shaopeng, Yuanning Tang, Bing Li, Xiaoliang Wang, and Huipeng Chen. "Angle-Weighted Time-to-Collision Algorithm for Enhanced Obstacle Avoidance in Autonomous Driving." In SAE 2024 Vehicle Powertrain Diversification Technology Forum. SAE International, 2025. https://doi.org/10.4271/2025-01-7022.

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<div class="section abstract"><div class="htmlview paragraph">To tackle the challenge of accurately predicting collision times for autonomous vehicles navigating complex dynamic obstacles, this paper proposes an innovative Angle-Weighted Time-to-Collision (AW-TTC) algorithm. Traditional TTC algorithms are known for their computational simplicity and strong real-time performance, making them widely applicable across various driving scenarios. However, they often struggle with predictive accuracy when encountering obstacles moving at angles, which can delay vehicle response and compr

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Yuan, Chuo, Zhiming Bao, Weizhuo Li, Zezheng Liu, Xu Zhao, and Kui Jiao. "Advanced SOH and SOC Prediction Models for Lithium-Ion Batteries: Integrating Machine Learning with Battery Management Systems." In SAE 2024 Vehicle Powertrain Diversification Technology Forum. SAE International, 2025. https://doi.org/10.4271/2025-01-7015.

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<div class="section abstract"><div class="htmlview paragraph">This paper focuses on the development and validation of predictive models for battery management systems, specifically targeting State of Health (SOH) and State of Charge (SOC) estimation, as well as the design of a comprehensive Battery Management System (BMS). The study begins by establishing and evaluating SOH prediction models, employing both linear regression and Long Short-Term Memory (LSTM) algorithms. Comparative analysis is conducted to assess the prediction accuracy between Recurrent Neural Networks (RNN) and L

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S, Aravamuthan, Ayush Sharma, Karthikeyan K, and Suhas S Kangde. "Predictive Model Development Using Machine Learning for Engine Cranktrain System." In WCX SAE World Congress Experience. SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0150.

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<div class="section abstract"><div class="htmlview paragraph">Highly competitive automotive market demands shorter product development cycle while maintaining higher standards of performance in terms of durability and Noise Vibration &amp; Harness (NVH). Engine cranktrain system is one of the major vibration sources in engine and first torsional mode frequency is a key parameter which influences vibration characteristics. Current CAE (Computer Aided Engineering) workflow for evaluating cranktrain system performance is time-consuming and takes around 55 Hrs. It involves cranksha

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Berichte der Organisationen zum Thema "DIT prediction"

R. Allen Miller. Prediction of Part Distortion in Die Casting. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/838429.

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Dr, R. Allen Miller. Die Casting Part Distortion: Prediction and Attenuation. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/793689.

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Oliver, Amanda, Catherine Murphy, Edmund Howe, and John Vest. Comparing methods for estimating water surface elevation between gages in the Lower Mississippi River. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/46915.

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Predicting a water surface elevation (WSElev) at a particular location has a wide range of applications like determining if a levee will overtop or how much a dike notch will increase water flow into a secondary channel. Five existing methods for predicting the water’s surface, (1) daily slope, (2) average slope, (3) River Analysis System (RAS) 1D, (4) RAS 2D, and (5) Adaptive Hydraulics modeling system (AdH), were used to predict the Mississippi River’s daily water surface from 10 October 2014 to 31 May 2016 at Friar’s Point, Greenville, and Natchez gages. The error, calculated as the model-p

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Miller, R. A., H. Ahuett-Garza, A. K. Choudhury, and S. Dedhia. Die casting die deflections: Prediction and attenuation. Final report, July 1, 1995--September 30, 1997. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/307966.

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Miller, R. Allen, Horacio Ahuett-Garza, Aswin K. Choudhury, and Sanjay Dedhia. Die casting die deflections: Prediction and attenuation. Final report, July 1, 1995--September 30, 1997. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/607496.

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Fluhr, Robert, and Volker Brendel. Harnessing the genetic diversity engendered by alternative gene splicing. United States Department of Agriculture, 2005. http://dx.doi.org/10.32747/2005.7696517.bard.

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Our original objectives were to assess the unexplored dimension of alternative splicing as a source of genetic variation. In particular, we sought to initially establish an alternative splicing database for Arabidopsis, the only plant for which a near-complete genome has been assembled. Our goal was to then use the database, in part, to advance plant gene prediction programs that are currently a limiting factor in annotating genomic sequence data and thus will facilitate the exploitation of the ever increasing quantity of raw genomic data accumulating for plants. Additionally, the database was

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Cherian, Jerald, Jodi Segal, Ritu Sharma, Allen Zhang, Eric Bass, and Michael Rosen. Patient Safety Practices Focused on Sepsis Prediction and Recognition. Agency for Healthcare Research and Quality (AHRQ), 2024. http://dx.doi.org/10.23970/ahrqepc_mhs4sepsis.

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Objectives. Patient safety practices (PSPs) focused on sepsis prediction and recognition, encompass interventions designed to identify patients with sepsis early and improve timely adherence to guidelines. Our objectives were to review the evidence published after the previous Making Healthcare Safer (MHS) report to determine the effectiveness of sepsis prediction and recognition PSPs on patient safety related outcomes. Methods. We searched PubMed and the Cochrane library for systematic reviews and primary studies published from January 2018 through August 2023, supplemented by gray literature

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Kellner, Trey A., Kenneth J. Prusa, and John F. Patience. Prediction of Loin, Belly and Jowl IV Based on Diet Composition Verses Daily Fatty Acid Intake. Iowa State University, 2015. http://dx.doi.org/10.31274/ans_air-180814-1326.

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Paparazzoa, Ersilia, Vincenzo Lagani, Silvana Geracitano, et al. An ELOVL2 based epigenetic clock for forensic age prediction: a systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.12.0006.

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Review question / Objective: To develop an easy, robust and improved blood-based age prediction model using ELOVL2 promoter methylation data. Eligibility criteria: All studies with the aim of understanding the relationship between the ELOVL2 methylation levels and age written in English language, carried out in humans and providing a publicly available dataset will be included in the systematic review. Articles that did not include original research (e.g., review, opinion article or conference abstract) and for which methylation analysis will be carried out using a technology different from th

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Naderer, Thomas, Alexander Hammer, Wolfgang Roland, Maximilian Zacher, and Gerald Berger-Weber. Optimizing modeling the multilayer coextrusion flow of non-newtonian fluids through rectangular ducts: appropriate shear rate definition for a local power law formulation. Universidad de los Andes, 2024. https://doi.org/10.51573/andes.pps39.gs.ms.4.

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The accuracy of viscosity predictions is a crucial aspect of polymer melt flow modeling and essential for the design of coextrusion die systems. In the field of non-Newtonian fluid modeling for coextrusion flows through rectangular ducts, significant progress has been made in understanding multilayer flow dynamics. Our fundamental research, employing numerical techniques such as the shooting method, finite element method, and finite difference method for flow evaluation, has established a critical base for the field. Our current research advances fluid dynamics by refining our existing numeric

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