Relevant bibliographies by topics / Sesimic source parameter retrieval

Contents

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

Academic literature on the topic 'Sesimic source parameter retrieval'

Author: Grafiati
Published: 10 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Sesimic source parameter retrieval"

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Meiser, Thorsten. "Analyzing Stochastic Dependence of Cognitive Processes in Multidimensional Source Recognition." Experimental Psychology 61, no. 5 (2014): 402–15. http://dx.doi.org/10.1027/1618-3169/a000261.

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Stochastic dependence among cognitive processes can be modeled in different ways, and the family of multinomial processing tree models provides a flexible framework for analyzing stochastic dependence among discrete cognitive states. This article presents a multinomial model of multidimensional source recognition that specifies stochastic dependence by a parameter for the joint retrieval of multiple source attributes together with parameters for stochastically independent retrieval. The new model is equivalent to a previous multinomial model of multidimensional source memory for a subset of th
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Jin, Sheng, Xiaojian Ding, Su Wang, Yao Dong, and Jianghui Ji. "Nii: a Bayesian orbit retrieval code applied to differential astrometry." Monthly Notices of the Royal Astronomical Society 509, no. 3 (2021): 4608–19. http://dx.doi.org/10.1093/mnras/stab3317.

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ABSTRACT Here, we present an open source python-based Bayesian orbit retrieval code (Nii) that implements an automatic parallel tempering Markov chain Monte Carlo (APT-MCMC) strategy. Nii provides a module to simulate the observations of a space-based astrometry mission in the search for exoplanets, a signal extraction process for differential astrometric measurements using multiple reference stars, and an orbital parameter retrieval framework using APT-MCMC. We further verify the orbit retrieval ability of the code through two examples corresponding to a single-planet system and a dual-planet
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Allen, Douglas R., Karl W. Hoppel, Gerald E. Nedoluha, Stephen D. Eckermann, and Cory A. Barton. "Ensemble-Based Gravity Wave Parameter Retrieval for Numerical Weather Prediction." Journal of the Atmospheric Sciences 79, no. 3 (2022): 621–48. http://dx.doi.org/10.1175/jas-d-21-0191.1.

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Abstract Gravity wave (GW) momentum and energy deposition are large components of the momentum and heat budgets of the stratosphere and mesosphere, affecting predictability across scales. Since weather and climate models cannot resolve the entire GW spectrum, GW parameterizations are required. Tuning these parameterizations is time-consuming and must be repeated whenever model configurations are changed. We introduce a self-tuning approach, called GW parameter retrieval (GWPR), applied when the model is coupled to a data assimilation (DA) system. A key component of GWPR is a linearized model o
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Zhang, Luo, Haoran Gu, Zhengqiang Li, et al. "A Sequence-to-Sequence Transformer Model for Satellite Retrieval of Aerosol Optical and Microphysical Parameters from Space." Remote Sensing 16, no. 24 (2024): 4659. https://doi.org/10.3390/rs16244659.

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Aerosol optical and microphysical properties determine their radiative capabilities, climatic impacts, and health effects. Satellite remote sensing is a crucial tool for obtaining aerosol parameters on a global scale. However, traditional physical and statistical retrieval methods face bottlenecks in data mining capacity as the volume of satellite observation information increases rapidly. Artificial intelligence methods are increasingly applied to aerosol parameter retrieval, yet most current approaches focus on end-to-end single-parameter retrieval without considering the inherent relationsh
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Zhang, Yun, Xu Chen, Wanting Meng, et al. "Wind Direction Retrieval Using Support Vector Machine from CYGNSS Sea Surface Data." Remote Sensing 13, no. 21 (2021): 4451. http://dx.doi.org/10.3390/rs13214451.

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In view of the difficulty of wind direction retrieval in the case of the large space and time span of the global sea surface, a method of sea surface wind direction retrieval using a support vector machine (SVM) is proposed. This paper uses the space-borne global navigation satellite systems reflected signal (GNSS-R) as the remote sensing signal source. Using the Cyclone Global Navigation Satellite System (CYGNSS) satellite data, this paper selects a variety of feature parameters according to the correlation between the features of the sea surface reflection signal and the wind direction, incl
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Zhao, Zhonghe, Yuyang Li, Kun Liu, et al. "Layered Soil Moisture Retrieval and Agricultural Application Based on Multi-Source Remote Sensing and Vegetation Suppression Technology: A Case Study of Youyi Farm, China." Remote Sensing 17, no. 13 (2025): 2130. https://doi.org/10.3390/rs17132130.

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Soil moisture dynamics are a key parameter in regulating agricultural productivity and ecosystem functioning. The accurate monitoring and quantitative retrieval of soil moisture play a crucial role in optimizing agricultural water resource management. In recent years, the development of multi-source remote sensing technologies—such as high spatiotemporal resolution optical, radar, and thermal infrared sensors—has opened new avenues for efficient soil moisture retrieval. However, the accuracy of soil moisture retrieval decreases significantly when the soil is covered by vegetation. This study p
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Soni, Vikas, and Kinsuk Acharyya. "Signature of Vertical Mixing in Hydrogen-dominated Exoplanet Atmospheres." Astrophysical Journal 977, no. 1 (2024): 52. https://doi.org/10.3847/1538-4357/ad891f.

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Abstract Vertical mixing is a crucial disequilibrium process in exoplanet atmospheres, significantly impacting chemical abundance and observed spectra. While current state-of-the-art observations have detected its signatures, the effect of vertical mixing on atmospheric spectra varies widely based on planetary parameters. In this study, we explore the influence of disequilibrium chemistry across a parameter space that includes eddy diffusion, surface gravity, internal and equilibrium temperature, and metallicity. We also assess the effectiveness of retrieval models in constraining the eddy dif
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Bressler, I., B. R. Pauw, and A. F. Thünemann. "McSAS: software for the retrieval of model parameter distributions from scattering patterns." Journal of Applied Crystallography 48, no. 3 (2015): 962–69. http://dx.doi.org/10.1107/s1600576715007347.

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A user-friendly open-source Monte Carlo regression package (McSAS) is presented, which structures the analysis of small-angle scattering (SAS) using uncorrelated shape-similar particles (or scattering contributions). The underdetermined problem is solvable, provided that sufficient external information is available. Based on this, the user picks a scatterer contribution model (or `shape') from a comprehensive library and defines variation intervals of its model parameters. A multitude of scattering contribution models are included, including prolate and oblate nanoparticles, core–shell objects
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Khaliq, Ayesha, Sikander Bakht Abbasi, Arslan Ilyas, Saim Masood Shaikh, and Syed Ashar Ali. "Optimizing Academic Queries With Retrieval-Augmented Large Language Models." Migration Letters 21, S10 (2024): 1274–83. https://doi.org/10.59670/ml.v21is10.11858.

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This research investigates the application of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) methods to enhance the management of academic queries, providing advantages for both students and educators. The study aims to improve the precision and pertinence of generated answers by combining LLMs with multi-source RAG systems. The model employs PDF datasets of various sizes and incorporates vector database support to streamline storage and retrieval, thereby boosting the model's capacity to handle extensive datasets. To process and produce comprehensive responses, the rese
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BADUROWICZ, Marcin, Stanisław SKULIMOWSKI, and Maciej LASKOWSKI. "FEASIBILITY OF USING LOW-PARAMETER LOCAL LLMS IN ANSWERING QUESTIONS FROM ENTERPRISE KNOWLEDGE BASE." Applied Computer Science 20, no. 4 (2024): 175–91. https://doi.org/10.35784/acs-2024-46.

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This paper evaluates the feasibility of deploying locally-run Large Language Models (LLMs) for retrieval-augmented question answering (RAG-QA) over internal knowledge bases in small and medium enterprises (SMEs), with a focus on Polish-language datasets. The study benchmarks eight popular open-source and source-available LLMs, including Google’s Gemma-9B and Speakleash’s Bielik-11B, assessing their performance across closed, open, and detailed question types, with metrics for language quality, factual accuracy, response stability, and processing efficiency. The results highlight that desktop-c
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Dissertations / Theses on the topic "Sesimic source parameter retrieval"

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Premier, Valentina. "Development of Novel Approaches to Snow Parameter Retrieval in Alpine Areas by Using Multi-temporal and Multi-sensor Remote Sensing Images." Doctoral thesis, Università degli studi di Trento, 2022. https://hdl.handle.net/11572/356729.

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Snow represents an important resource in mountainous regions. Monitoring its extent and amount is relevant for several applications, such as hydrology, ecology, avalanche monitoring, or hydropower production. However, a correct understanding of the high spatial and temporal variability of snow accumulation, redistribution and ablation processes requires its monitoring in a spatialized and detailed way. Recently, the launch of the Sentinel missions has opened the doors to new approaches that mainly exploit high resolution (HR) data having a spatial detail of few dozens of m. In this thesis, we
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Artchounin, Daniel. "Tuning of machine learning algorithms for automatic bug assignment." Thesis, Linköpings universitet, Programvara och system, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139230.

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In software development projects, bug triage consists mainly of assigning bug reports to software developers or teams (depending on the project). The partial or total automation of this task would have a positive economic impact on many software projects. This thesis introduces a systematic four-step method to find some of the best configurations of several machine learning algorithms intending to solve the automatic bug assignment problem. These four steps are respectively used to select a combination of pre-processing techniques, a bug report representation, a potential feature selection tec
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Stramondo, S. "Seismic Source Quantitative Parameters Retrieval from InSAR Data and Neural Networks." Thesis, 2007. http://hdl.handle.net/2122/3043.

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The basic idea of this thesis is to exploit the capabilities of neural networks in a very new framework: the quantitative modelling of the seismic source and the interferogram inversion for retrieving its geometric parameters. The problem can be sum up as follows. When a moderateto- strong earthquake occurs we can apply SAR Interferometry (InSAR) technique to compute a differential interferogram. The latter is used to detect and measure the surface displacement field. The earthquake has been generated by an active, seismogenic, fault having its own specific geometry. Therefore each diffe
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Book chapters on the topic "Sesimic source parameter retrieval"

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Khalid, Nafisah, Noraain Mohamed Saraf, Juazer Rizal Abdul Hamid, and Zulkiflee Abd. Latif. "Tree Biophysical Parameter Retrieval from Multi-source Remote Sensing Data Fusion." In Concepts and Applications of Remote Sensing in Forestry. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4200-6_22.

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Shi, Yunxiao, Xing Zi, Zijing Shi, Haimin Zhang, Qiang Wu, and Min Xu. "Enhancing Retrieval and Managing Retrieval: A Four-Module Synergy for Improved Quality and Efficiency in RAG Systems." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. http://dx.doi.org/10.3233/faia240748.

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Retrieval-augmented generation (RAG) techniques leverage the in-context learning capabilities of large language models (LLMs) to produce more accurate and relevant responses. Originating from the simple ‘retrieve-then-read’ approach, the RAG framework has evolved into a highly flexible and modular paradigm. A critical component, the Query Rewriter module, enhances knowledge retrieval by generating a search-friendly query. This method aligns input questions more closely with the knowledge base. Our research identifies opportunities to enhance the Query Rewriter module to Query Rewriter+ by gene
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Conference papers on the topic "Sesimic source parameter retrieval"

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Zhong, Xin, Yoke San Wong, Wen Feng Lu, Kelvin W. C. Foong, and Alan Ho-lun Cheng. "A Dental Matching Approach Using Partial Surface Features for Human Identification." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70890.

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A novel 3D dental identification framework is presented. The objective is to develop a methodology to enable computer-automated matching of complex dental surfaces with possible missing regions for human identification. Thus far, there is no reported attempt at 3D dental identification given partially available dental casts or impressions. This approach overcomes a number of key hurdles in traditional 2D methods. Given the 3D digital form of a dental cast surface, the developed method will facilitate the search for the closest match in the database of digitized dental casts. A salient curvatur
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Abdelaziem, O. E., A. Nasser Khafagy, and T. A. Yehia. "Innovative Approach of Generative AI for Automating Technical Bid Evaluations in Oil Companies." In Mediterranean Offshore Conference. SPE, 2024. http://dx.doi.org/10.2118/223359-ms.

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Summary The process of outlining a scope of work and evaluating technical bids in the oil and gas industry is commonly burdensome, labor-intensive, and susceptible to human bias. This paper introduces an AI-assistant chatbot based on the power of open-source large language models (LLMs), natural language processing (NLP), and data analytics, to aid in automating the entire workflow of technical tendering processes, facilitating an improved decision support system (DSS), and mitigating potential subjectivity. The workflow starts with loading documents in the format of scanned PDF files. Firstly
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Journal articles
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