bluuebunny/crossref_metadata_2025_split huggingface dataset:
Posibilidades e imposibilidades del dialogismo socio-cultural en la literatura hispanoamericana
Authors: Perus Françoise 
Published: March 2024

Este ensayo busca delimitar los diferentes ámbitos de pertinencia de las categorías bajtinianas de dialogismo, monologismo y polifonía, así como de los enunciados, imagen y voz. La autora plantea los alcances y limitaciones de estas nociones para el estudio de las prácticas narrativas hispanoamericanas, y ejemplifica la problemática con el estudio del cuento “Luvina” de Juan Rulfo.
El texto sagrado no existe
Authors: Costantini Michel 
Published: March 2024

La hipótesis sostenida en este estudio es que en semiótica no existe lo sagrado en sí, que no hay sacralidad del texto (en el sentido semiótico del término) sino aquella que se puede demostrar a partir de las marcas, las cuales no son universales sino culturales (por lo menos en lo que a cierto nivel de análisis se refiere). Para sustentar esta hipótesis, se considerarán sucesivamente dos ejemplos de un posible trabajo sobre las marcas: uno, tomado de los cuadros de El Greco, tiende a identificar el funcionamiento paradigmático de ciertos elementos, en particular de ciertos desnudos; el otro, a partir del ciclo de la Vida de San Francisco pintado por Giotto en Asís, muestra cómo se construye sintagmáticamente, a lo largo de veintiocho frescos, una cierta concepción de lo sagrado.
Roles creadores de los contextos en el recorrido interpretativo de los pasajes
Authors: Chollier Christine 
Published: March 2024

Este artículo recuerda dos de las hipótesis planteadas en semántica de los textos. La primera concierne al papel creador de los contextos en torno a la interpretación. La práctica interpretativa incita a devolver los problemas a su contexto: vecindario (sintagma, periodo); otros pasajes del texto elegidos por asimilación o disimilación; otros pasajes de otros textos escogidos como interpretantes externos. Esta contextualización interpretativa permite validar rasgos inherentes o actualizar por propagación rasgos aferentes. Transforma la interpretación en actividad (doing) más que en resultado (done).La segunda hipótesis sugiere que una obra comprende secuencias desiguales desde un punto de vista tanto cualitativo como cuantitativo. Estos lugares del texto son pasajes, siendo que una parte de la obra pasa por ellos, y que los fondos y las formas son susceptibles de sufrir allí modificaciones.El propósito del artículo es cruzar estas dos hipótesis para ponerlas a prueba en uno o varios textos: seguir una tipología de los papeles creadores de los contextos con el fin de subrayar la función de pasaje y de justificar la plausibilidad de una interpretación.Los textos serán extraídos, entre otros, de la novela distópica, The Handmaid’s Tale, de la canadiense Margaret Atwood.
La construcción de sentido: el caso de los enunciados metafóricos y el discurso académico
Authors: Hall Beatriz 
Published: March 2024

En las últimas décadas, el discurso académico se ha convertido en objeto de estudio de numerosas investigaciones que, a partir de diferentes marcos teóricos, proponen distintos objetivos.Por otra parte, si bien la llamada metáfora ha sido motivo de reflexión teórica desde la antigüedad, en los últimos años la cantidad y variedad de estudios que se han desarrollado y siguen desarrollándose en torno a este objeto de estudio ha aumentado considerablemente. En tal contexto de múltiples propuestas teóricas y metodológicas, este trabajo tiene por objetivo demostrar que, tanto el estudio de la metáfora como el del discurso académico, involucra decisivamente conceptos que no siempre aparecen explicitados. Nos referimos, entre otros, a los conceptos de lengua, sujeto, sentido, sentido literal y sentido metafórico. Por nuestra parte, desde un punto de vista semántico discursivo noreferencialista de la lengua (Schulz, 2000; 2002; 2004), recogemos los aportes provenientes del Análisis del Discurso (línea francesa-brasileña). Así, partimos de la definición de discurso como efecto de sentido entre locutores y lo estudiamos en su relación constitutiva con las condiciones de producción. Entendemos que las condiciones de producción y circulación de los textos se materializan en mecanismos discursivos, según las representaciones imaginarias de los sujetos. De acuerdo con esta línea investigativa, finalmente, proponemos caracterizar las llamadas metáforas como construcciones semánticas insertas en una dinámica discuriva y, en este sentido, las redefinimos como enunciados metafóricos.
Theoretical Background and Prognostic Modeling for Benchmarking SHM Sensors for Composite Structures
Authors: Smelyanski Vadim , Hafiychuk Vasyl , G. Luchinsky Dmitry , Banks Curtis , Conn Chris , Miller Jim , Watson Mike 
Published: March 2024

This paper reports on analytical as well as computer simulation of waves propagating in sandwich-type composite structures. Sandwich-type composites are being studied for use in NASA’s new heavy lift launch vehicle, and flaw detection is crucial for safety and for failure prognostics. Theoretical analysis, as well as numerical modeling, is needed for benchmarking of available technologies for structural health monitoring (SHM) sensors and sensor systems. This benchmarking activity is important for answering the basic question of what minimum flaw size can be detected by the existing SHM based monitoring methods. Sandwich panels with foam, WebCore and honeycomb structures were considered for use in this study. Eigenmode frequency analysis and Frequency Response Analysis of the panels were made to understand fundamental properties of the panel physics and limitations that may affect the application of current SHM sensors and methods. An analytical study of the transient wave propagation is considered based on Mindlin plate theory. The mathematical model, accompanied by numerical simulations, shows that small size defects can be recognized but the frequency of waves should be sufficiently high. It is concluded that a combination of analytical results coupled with the high-fidelity simulations should make it possible to analyze experimental data and to predict the applicability of SHM methods for this type of structure.
A Cost-Benefit Approach to Evaluating Engine Health Monitoring Systems
Authors: Gordon Grant , Hickenbottom Chris , Mylaraswamy Dinkar 
Published: March 2024

Condition-based maintenance (CBM) enables fleet-level decisions that increase readiness, increase time between overhaul (TBO) and reduce inspections. Since engines account for a significant portion in overall maintenance cost drivers, detection of incipient faults is an important element of the overall CBM equation. The last few years have seen significant progress in design, development and deployment of engine health monitoring. In order for such potential health monitoring solutions to be operationally viable, they must integrate with existing engine designs and maintenance processes. That is, technical factors must be balanced against economic and operational benefits.
A Cost-Benefit Analysis (CBA) is used to provide a comparison of alternative solutions that decision-makers can use to identify the most cost-effective approach to CBM. In this paper we describe our approach to developing the underlying value capture expressions for monetizing cost and benefits. We illustrate the approach to evaluate two options for mechanical components health monitoring techniques for a gas turbine engine. We conclude the paper with how CBA summary results can be presented to a decision maker.
Bringing the Aircraft System Health Management Tool to Life Using the Informatica Tool Suite
Authors: Peters Glenn , Mosher Mark , Carlson Chris 
Published: March 2024

Earlier this year, UTC Aerospace Systems introduced the Aircraft System Health Management (ASHM) Tool, a web application that takes in Aircraft Condition Monitoring Function (ACMF) reports for selected subsystems and components of an aircraft platform, parses and processes the reported parameters against thresholds and computes estimated or expected values for some key parameters, and serves the report data and the processed results as part of a fleet view available to airline and maintenance users.
The ASHM application uses Informatica PowerCenter to parse and store incoming report data and Informatica RulePoint to apply alert rules and analytic processing to the report data as it is persisted to the ASHM database. This paper describes how UTC Aerospace Systems has leveraged a commercial off-the-shelf tool suite rather than continue to build custom components for the ASHM architecture, with the goals of achieving a short development cycle, robust transaction processing, and scalability to other aircraft systems and other aircraft platforms.
Instead of building tools from scratch that would need to be reworked as the application scales, a set of scalable tools that suit the task at hand and in the future were selected. The full suite of tools, beyond what has been implemented so far, appears to provide capability to address data integrity, reliability and performance as the application grows.
Rotor Track and Balance Improvements
Authors: Bechhoefer Eric , Fang Austin , Garcia Ephrahim 
Published: March 2024

Vibration derived from the main rotor dynamics and imbalance causes premature wear to the aircraft components, and can cause pilot fatigue. While improvements have been made in rotor track and balance (RTB) techniques; there is room to enhance the quality of the recommended RTB adjustments.
One aspect that limits the development of RTB algorithms is the difficulty in quantifying the performance of new algorithms. This is because there are limited data sets to work on, and no agreed upon metrics on which to measure RTB performance.This paper develops a methodology to simulate the vibration due to injecting a fault into the rotor system, and demonstrates metrics to evaluate the performance of a RTB algorithm. A new Bayes RTB method is evaluated against a standard least squares technique. In addition, a technique is presented to automate the selection of active adjustments.
Efficient Generation of Minimal Dynamic Bayesian Networks for Hybrid Systems Fault Diagnosis using Hybrid Possible Conflicts
Authors: Pulido Belarmino , Moya Noemi , J. Alonso-Gonza ́lez Carlos , Bregon Anibal 
Published: March 2024

Hybrid systems diagnosis requires different sets of equations for each operation mode in order to estimate the continuous system behaviour. In this work we rely upon Hybrid Possible Conflicts (HPCs), which are an extension of Possible Conflicts (PCs) for hybrid systems, that introduce the information about potential system modes as control specifications that activate/deactivate different sets of equations. We also introduce the concept of Hybrid Minimal Evaluation Models (H-MEMs) to represent the set of globally consistent causal assignments in an HPC for any potential mode.
H-MEMs can be explored for a specific operation mode, and its computational model automatically generated. In this work, the selected computational models are minimal Dynamic Bayesian Networks (DBNs). Since DBNs can be directly generated from PCs, and can be used for fault detection and isolation, we propose to efficiently generate Mini- mal DBNs models on-line using the H-MEM structure. By introducing fault parameters in the DBN model, we can also perform fault identification, providing an unifying framework for fault diagnosis, under single fault assumption. We test the approach in a simulation four-tank system.
A Time-domain Modeling and Simulation Framework for Comparative Analysis of Prognostics, Reliability and Robustness in System Design
Authors: A. Lambert Nicholas , B. Ferrio Kyle , L. Goodman Douglas 
Published: March 2024

Redundancy is an effective, high-level solution to the requirement for reliable safety-critical systems, but it comes at the cost of Size, Weight and Power (SWaP) and reduced capability. A modeling and simulation framework was developed to address the need for robust design alternatives to redundancy. Robustness, in our application, is treated as the insensitivity of the performance with reference to specification. The necessity to characterize both reliability and robustness in the same framework has resulted in a time-domain simulation approach to modeling behaviors associated with unreliability and a lack of robustness. The incorporation of these features offers a novel insight into potential applications of prognostic technology. Further development of this approach has the potential to allow designers to choose how risks associated with failures are mitigated, by redundancy, robustness, or prognosis.
By modeling the life of parts, the factors that impact them and the resulting behaviors, the observability and predictability (even controllability in the case of optimized, fault-tolerant, closed-loop control) of faults and failures is identified. Designers can determine which parts of a system would benefit from prognostic health management (PHM) technologies, adaptive / tolerant features to yield robust design, or redundancy based approaches. The complex causality in the models requires a Monte Carlo approach analogous to the simulation of fleets of systems; this, combined with the ability to simulate systems made from new and old parts, can inform strategies for condition-based maintenance (CBM). We present the mathematical modeling concept and the simulation framework which permits comparative assessment of reliability, robustness and prognostics. The multi-hierarchical, systems integration aspects inherent to the concept make this technique highly applicable to real- world dynamic systems. The framework also supports statistical, standards based and physics-of-failure descriptions of stress, aging, fault and failure behaviors in a unified way. There are challenges to be overcome in realizing the benefits of this approach to model-based system design. Issues of model validation, data availability and computational burden are recognized and discussed. As we show, these challenges can be overcome to produce new design tools providing better products and transparent project quality.
Operation Condition Monitoring using Temporal Weighted Dempster-Shafer Theory
Authors: Wang Xiaoyun , Zhao Tingdi 
Published: March 2024

System operation is a real time, dynamic decision process, a continuous observation should be implemented to support timely decision. Real time condition monitoring and diagnosis is featured with ongoing event sequence. The more recent observation, the much detailed, accurate information, and the more obsolete observations with much weak correlation to current faults and errors vise versa.
Dempster-Shafer evidence theory is best suitable for the problem of redundant sensors, insufficient data reasoning. However, D-S base applications largely focused on causational relationship between symptoms and effects, and the fusion process of evidences was performed regardless whatever order observed. As an improvement to the frame of discernment of the D-S theory, we purposed a time weighted evidence combination method. Observed events were extracted from multiple time points to form a temporal evidence sequence. Basic probability assignment was altered by temporal weights in accordance with the time proximity between the observed events and current time. The temporal weights value set was in accordance with its occurring time point. Evidences with same timestamps should be allocated with the same temporal weights. An example was discussed to illustrate the temporal weight, D-S rule based assessment framework. In the framework, latest observed evidences stream were combined into the framework to improving fault recognition.
Characterization of Fault Size in Bearings
Authors: Mendelovich Matan , Sanders Yitschak , Kogan Gideon , Battat Mor , Klein Renata , Bortman Jacob 
Published: March 2024

Bearings are important components in rotating machines. An initial small damage in the bearing may cause a fast degradation, which may lead to the machine breakdown. The health condition of bearings can be monitored using proven vibro-acoustic methods effective for detecting bearing faults. However, the existing bearing health indicators do not provide a reliable estimation of the fault characteristics, such as fault size and fault location. As a result, the ability to assess the severity of the bearing damage and to make maintenance decisions is limited.The presented study is a part of an ongoing research on bearing prognostics, aimed to improve the understanding of the effects of fault size on the bearing dynamics. The research methodology combines dynamic modeling of the faulty bearing with experimental validation and confirmation of model simulations.
In the presented study, small faults (starting from 0.3 mm), simulating incipient damage are generated at increasing sizes by an electrical discharge machine. The recorded vibration data is then analyzed and compared to the vibration signatures predicted by the model. The experimental and the simulation results add new insights on the manifestation of the size of the fault and possible indicators of the damage severity.
Device Health Estimation by Combining Contextual Control Information with Sensor Data and Device Health Prognostics Utilizing Restricted Boltzmann Machine
Authors: Liao Linxia , Honda Tomonori , Pavel Radu 
Published: March 2024

The goal of this work is to bridge the gap between business decision-making and real-time factory data. Beyond real- time data collection, we aim to provide analysis capability to obtain insights from the data and converting the learnings into actionable recommendations.
For device health estimation, we focus on analyzing device health conditions and propose a data fusion method that com- bines sensor data with limited diagnostic signals with the de- vice’s operating context. We propose a segmentation algo- rithm that provides a temporal representation of the device’s operation context, which is combined with sensor data to fa- cilitate device health estimation. Sensor data is decomposed into features by time-domain and frequency-domain analy- sis. Principal component analysis is used to project the high- dimensional feature space into a low-dimensional space fol- lowed by a linear discriminant analysis to search the optimal separation among different device health conditions. Our in- dustrial experimental results show that by combining device operating context with sensor data, our proposed segmenta- tion and linear transformation approach can accurately iden- tify various device imbalance conditions even for limited sen- sor data which could not be used to diagnose imbalance on its own.
For device health prediction, we propose a restricted Boltz- mann machine based method to automatically generate fea- tures that can be used for remaining useful life prediction, which is performed by a random forest regression algorithm. The proposed method was validated through run-to-failure dataset of a machine tool spindle test-bed.
A New Generic Approach to Convert FMEA in Causal Trees for the Purpose of Hydro-Generator Rotor Failure Mechanisms Identification
Authors: Blancke Olivier , Amyot Normand , Hudon Claude , Lévesque Mélanie , Tahan Antoine 
Published: March 2024

At Hydro-Québec (HQ), an integrated diagnostic system (MIDA) is currently used to assess hydro-generators health index. This system gives the global health index but does not propose any understanding of active failure mechanisms. At this point, this work needs to be done by experts after analysis of the diagnostic data in MIDA.
To relieve the expert from part of this work, a prognostic tool, that uses a Failure Mechanisms and Symptoms Analysis (FMSA), is under development. The approach is based on the understanding of the evolution of degradation processes for each failure mechanism. Failure mechanisms are structured as causal trees and defined as a sequence of physical states starting from a root cause and ending with a failure mode. A physical state corresponds to characteristic degradation condition of a component of the generator. Each physical state being defined by a unique combination of symptoms as measured with diagnostic tools. After consigning all possible mechanisms occurring in both the rotor and the stator, the symptoms logged into a database can be read to automatically identify all active physical state and active failure mechanisms. This approach has been under development in HQ for the stator for a number of years and is now extended to the rotors of hydro-generators.The purpose of this paper is to present the structured method used to build the failure mechanisms from bits and pieces of information (sub-mechanisms) found in the literature and from discussions with experts. This new methodology is based on a two steps process. First, sub-mechanisms were extracted from FMEA in the literature. Then, an algorithm was used to generate a set of causal trees from these sub- mechanisms. The generated results then had to be validated by experts to make sure that automatically generated mechanisms were logical and plausible. The resulting extended failure mechanisms trees built can then be used for the purpose of Root Cause Analysis (RCA), model-based diagnostics and prognosis. This method was developed to be as generic as possible so it could be applied to any complex system.
Advances in Ultrasonic Imaging for Internal Flaws in Structures
Authors: Vu Nguyen Thompson , Sternini Simone , Lanza di Scalea Francesco 
Published: March 2024

In the field of non-destructive testing of structures, 3D imag- ing of internal flaws is a critical task. Defect imaging allows the engineer to make informed follow-up decisions based on the morphology of the flaw.
This paper will present advances in ultrasonic tomography for the 3D visualization of internal flaws in solids. In particular, improvements to the conventional tomographic imaging algorithms have been made by utilizing a mode-selective im- age reconstruction scheme that exploits the specific displacement field, respectively, of the longitudinal wave modes and the shear wave modes, both propagating simultaneously in the test volume. The specific mode structure is exploited by an adaptive weight assignment to the ultrasonic tomographic array. Such adaptive weighting forces the imaging array to look at a specific scan direction and better focus the imaging onto the actual flaw (ultrasound reflector).
This study shows that the adaptive weighing based on mode structure improves image contrast and resolution compared to a conventional ultrasonic imaging technique based on delay- and-sum. Results will be shown from simulations and imaging experiments of simulated flaws in an aluminum block.