An Introduction to Requirements Traceability

This report surveys the requirements traceability literature and gives some recommendations for further research and for an approach to consultancy concerning traceability in the 2RARE project. The problem of maintaining traceability in a development project is viewed as the problem of maintaining an information system that maintains the relevant links between items developed during the process. These items may vary from requirements to design and implementation documents. To develop and implement such an information system, we must identify the needs for tracking information, made a model of this information, design usage procedures for the system, and implement the system. Accordingly, the literature on traceability is organized under the headings needs, models and usage. Furthermore, tracking tools are briefly reviewed

Deterministic and probabilistic verification of multi-model meteorological forecasts on the subseasonal timescale

In questo studio, un multi-model ensemble è stato implementato e verificato, seguendo una delle priorità di ricerca del Subseasonal to Seasonal Prediction Project (S2S). Una regressione lineare è stata applicata ad un insieme di previsioni di ensemble su date passate, prodotte dai centri di previsione mensile del CNR-ISAC e ECMWF-IFS. Ognuna di queste contiene un membro di controllo e quattro elementi perturbati. Le variabili scelte per l'analisi sono l'altezza geopotenziale a 500 hPa, la temperatura a 850 hPa e la temperatura a 2 metri, la griglia spaziale ha risoluzione 1 ◦ × 1 ◦ lat-lon e sono stati utilizzati gli inverni dal 1990 al 2010. Le rianalisi di ERA-Interim sono utilizzate sia per realizzare la regressione, sia nella validazione dei risultati, mediante stimatori nonprobabilistici come lo scarto quadratico medio (RMSE) e la correlazione delle anomalie. Successivamente, tecniche di Model Output Statistics (MOS) e Direct Model Output (DMO) sono applicate al multi-model ensemble per ottenere previsioni probabilistiche per la media settimanale delle anomalie di temperatura a 2 metri. I metodi MOS utilizzati sono la regressione logistica e la regressione Gaussiana non-omogenea, mentre quelli DMO sono il democratic voting e il Tukey plotting position. Queste tecniche sono applicate anche ai singoli modelli in modo da effettuare confronti basati su stimatori probabilistici, come il ranked probability skill score, il discrete ranked probability skill score e il reliability diagram. Entrambe le tipologie di stimatori mostrano come il multi-model abbia migliori performance rispetto ai singoli modelli. Inoltre, i valori più alti di stimatori probabilistici sono ottenuti usando una regressione logistica sulla sola media di ensemble. Applicando la regressione a dataset di dimensione ridotta, abbiamo realizzato una curva di apprendimento che mostra come un aumento del numero di date nella fase di addestramento non produrrebbe ulteriori miglioramenti

The XDEM Multi-physics and Multi-scale Simulation Technology: Review on DEM-CFD Coupling, Methodology and Engineering Applications

The XDEM multi-physics and multi-scale simulation platform roots in the Ex- tended Discrete Element Method (XDEM) and is being developed at the In- stitute of Computational Engineering at the University of Luxembourg. The platform is an advanced multi- physics simulation technology that combines flexibility and versatility to establish the next generation of multi-physics and multi-scale simulation tools. For this purpose the simulation framework relies on coupling various predictive tools based on both an Eulerian and Lagrangian approach. Eulerian approaches represent the wide field of continuum models while the Lagrange approach is perfectly suited to characterise discrete phases. Thus, continuum models include classical simulation tools such as Computa- tional Fluid Dynamics (CFD) or Finite Element Analysis (FEA) while an ex- tended configuration of the classical Discrete Element Method (DEM) addresses the discrete e.g. particulate phase. Apart from predicting the trajectories of individual particles, XDEM extends the application to estimating the thermo- dynamic state of each particle by advanced and optimised algorithms. The thermodynamic state may include temperature and species distributions due to chemical reaction and external heat sources. Hence, coupling these extended features with either CFD or FEA opens up a wide range of applications as diverse as pharmaceutical industry e.g. drug production, agriculture food and processing industry, mining, construction and agricultural machinery, metals manufacturing, energy production and systems biology

Pushing AI to Wireless Network Edge: An Overview on Integrated Sensing, Communication, and Computation towards 6G

Pushing artificial intelligence (AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things (AIoT) in the sixth-generation (6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like intelligence from the huge amount of data scattered at wireless network edge. In general, realizing edge intelligence corresponds to the process of sensing, communication, and computation, which are coupled ingredients for data generation, exchanging, and processing, respectively. However, conventional wireless networks design the sensing, communication, and computation separately in a task-agnostic manner, which encounters difficulties in accommodating the stringent demands of ultra-low latency, ultra-high reliability, and high capacity in emerging AI applications such as auto-driving. This thus prompts a new design paradigm of seamless integrated sensing, communication, and computation (ISCC) in a task-oriented manner, which comprehensively accounts for the use of the data in the downstream AI applications. In view of its growing interest, this article provides a timely overview of ISCC for edge intelligence by introducing its basic concept, design challenges, and enabling techniques, surveying the state-of-the-art development, and shedding light on the road ahead

Development Of The Strategy To Select Optimum Reflective Cracking Mitigation Methods For The Hot-mix Asphalt Overlays In Florida

Hot Mix Asphalt (HMA) overlay is a major rehabilitation treatment for the existing deteriorated pavements (both flexible and rigid pavements). Reflective cracking (RC) is the most common distress type appearing in the HMA overlays which structurally and functionally degrades the whole pavement structure, especially under high traffic volume. Although many studies have been conducted to identify the best performing RC mitigation technique, the level of success varies from premature failure to good performance in the field. In Florida, Asphalt Rubber Membrane Interlayers (ARMIs) have been used as a RC mitigation technique but its field performance has not been successful. In this study, the best performing means to mitigate RC in the overlays considering Florida’s special conditions have been investigated. The research methodology includes (1) extensive literature reviews regarding the RC mechanism and introduced mitigation options, (2) nationwide survey for understanding the current practice of RC management in the U.S., and (3) the development of decision trees for the selection of the best performing RC mitigation method. Extensive literature reviews have been conducted to identify current available RC mitigation techniques and the advantages and disadvantages of each technique were compared. Lesson learned from the collected case studies were used as input for the selection of the best performing RC mitigation techniques for Florida’s roads. The key input parameters in selecting optimum mitigation techniques are: 1) overlay characterization, 2) existing pavement condition, 3) base and subgrade structural condition, 4) environmental condition and 5) traffic level. In addition, to understand the current iv practices how reflective cracking is managed in each state, a nationwide survey was conducted by distributing the survey questionnaire (with the emphasis on flexible pavement) to all other highway agencies. Based on the responses, the most successful method of treatment is to increase the thickness of HMA overlay. Crack arresting layer is considered to be in the second place among its users. Lack of cost analysis and low rate of successful practices raise the necessity of conducting more research on this subject. Considering Florida’s special conditions (climate, materials, distress type, and geological conditions) and the RC mechanism, two RC mitigation techniques have been proposed: 1) overlay reinforcement (i.e. geosynthetic reinforcement) for the existing flexible pavements and 2) Stress Absorbing Membrane Interlayer (SAMI) for the existing rigid pavements. As the final products of this study, decision trees to select an optimum RC mitigation technique for both flexible and rigid pavements were developed. The decision trees can provide a detailed guideline to pavement engineer how to consider the affecting parameters in the selection of RC mitigation technique

Perspectives of 2D and 3D mapping of atmospheric pollutants over urban areas by means of airborne DOAS spectrometers

tants, offering numerous advantages over conventional networks of in situ analysers. We propose some innovative solutions in the field of DOAS (Differential Optical Absorption Spectroscopy) remote systems, utilizing diffuse solar light as the radiation source. We examine the numerous potentialities of minor gas slant column calculations, applying the «off-axis» methodology for collecting the diffuse solar radiation. One of these particular approaches, using measurements along horizontal paths, has already been tested with the spectrometer installed on board the Geophysica aircraft during stratospheric flights up to altitudes of 20 km. The theoretical basis of these new measurement techniques using DOAS remote sensing systems are delineated to assess whether low altitude flights can provide 2D and 3D pollution tomography over metropolitan areas. The 2D or 3D trace gas total column mapping could be used to investigate: i) transport and dispersion phenomena of air pollution, ii) photochemical process rates, iii) gas plume tomography, iv) minor gas vertical profiles into the Planetary Boundary Layer and v) minor gas flux divergence over a large area