Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

http://www.geoplanning.it/test/wp-content/uploads/2012/02/Practical-estimates-of-rock-mass-strength.pdf

Practical estimates of rock mass strength

本文对国际科学计量学杂志《Ｓｃｉｅｎｔｏｍｅｔｒｉｃｓ》１９７９－１９９１年的研究论文内容、栏目、作者及国别和编委及国别作了计量分析，揭示出科学计量学研究的重点、活动的中心及发展趋势，说明了学科带头人在发展科学计量学这门新兴学科中的作用。

国际刊物《Scientometrics》文献计量研究

In the last years, Artificial Intelligence (AI) has achieved a notable momentum that may deliver the best of expectations over many application sectors across the field. For this to occur, the entire community stands in front of the barrier of explainability, an inherent problem of AI techniques brought by sub-symbolism (e.g. ensembles or Deep Neural Networks) that were not present in the last hype of AI. Paradigms underlying this problem fall within the so-called eXplainable AI (XAI) field, which is acknowledged as a crucial feature for the practical deployment of AI models. This overview examines the existing literature in the field of XAI, including a prospect toward what is yet to be reached. We summarize previous efforts to define explainability in Machine Learning, establishing a novel definition that covers prior conceptual propositions with a major focus on the audience for which explainability is sought. We then propose and discuss about a taxonomy of recent contributions related to the explainability of different Machine Learning models, including those aimed at Deep Learning methods for which a second taxonomy is built. This literature analysis serves as the background for a series of challenges faced by XAI, such as the crossroads between data fusion and explainability. Our prospects lead toward the concept of Responsible Artificial Intelligence, namely, a methodology for the large-scale implementation of AI methods in real organizations with fairness, model explainability and accountability at its core. Our ultimate goal is to provide newcomers to XAI with a reference material in order to stimulate future research advances, but also to encourage experts and professionals from other disciplines to embrace the benefits of AI in their activity sectors, without any prior bias for its lack of interpretability.

Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI.

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Landslide inventory maps: New tools for an old problem

Excavation and implementation of tunnel support system of T341 tunnel of Ankara-Sivas High Speed Train Project were completed recently. Throughout the tunnel excavation, serious stability problems occurred both in the entrance portal section and tunnel. The purposes of this study are to explain the failure mechanism and to propose a suitable support system for the section between Km: 341 + 040 - 341 + 114. Tunnel works were interrupted after the collapse, which occurred in a section of approximately 74 m between Km: 341 + 040 - 341 + 114. As a result of the collapse in the tunnel, local settlements emerged on the surface and it was observed that the effects of the collapse on the surface, as well. To surpass the collapsed section, extra reinforcements were performed by grouting taking place both at the surface and inside the tunnel. Afterwards, tunnel excavation was completed in relatively short stages by applying double umbrella system and rigid support system. Consequently, the causes of the failure, excavation and support system design and results of the numerical analyses are discussed.

Assessment of collapse mechanism of a High Speed Railway Tunnel (T341 Tunnel, Turkey)

Abstract. On 6 February 2023, two major earthquakes occurred in the East Anatolian Fault Zone (EAFZ) of Türkiye. The EAFZ forms the east border of the Anatolian Plate. The magnitude 7.7 and 7.5 Kahramanmaraş – Türkiye Earthquakes that struck southern Türkiye and resulted in common destruction in 11 provinces in the region. Total 6 main fault segments of the EAFZ ruptured during the earthquake sequence on 6 February 2023, and approximately 400 km surface rupture occurred. The life losses are reported as over 50000, and approximately 300,000 buildings were collapsed or severely damaged. In addition to damages on the buildings and the infrastructures, liquefactions, landslides, rockfalls, and rock avalanches were also observed during the earthquake sequence. The purpose of this study is to present a general overview on the 6 February 2023 Earthquake sequence.


/pdf/6-february-2023-kahramanmaras-turkiye-earthquakes-a-general-2fy97bop.pdf

6 february 2023 kahramanmaraş – türki̇ye earthquakes: a general overview

Abstract. Generating precise and up-to-date landslide susceptibility maps (LSMs) in landslide-prone areas is important to identify hazard potential in the future. The data quality and the method selection affect the accuracy of the LSMs. In this context, the accuracy and precision of the digital elevation models (DEMs) used as input are among the most important performance elements. Therefore, the influence of DEM accuracy and spatial resolution in producing LSMs was investigated here. A high accuracy DEM with 5 m grid spacing produced from aerial photographs and the EU-DEM v1.1 freely accessible from Copernicus Land Monitoring Service with 25 m spatial resolution were used for producing two different LSMs using the Random Forest (RF) method in this study. The RF method has proven success for this purpose. A total of eight conditioning factors, which include topographical and geological features, was used as model input. The landslide inventory was derived with the help of aerial stereo images with 20 cm and 30 cm ground sampling distances. The performances of the LSMs were assessed with receiver operating characteristics (ROC) area under curve (AUC) values. In addition, the results were compared with visual inspection. The results show that although the AUC values obtained from the aerial DEM (0.95) and EU-DEM v1.1 (0.93) were comparable; based on the visual assessments, the LSM obtained from the higher resolution DEM was found more successful in detecting the landslides and thus exhibited better prediction performance.


/pdf/on-the-effect-of-dem-quality-for-landslide-susceptibility-n5z69osg.pdf

Candan Gokceoglu

Papers

Assessment of collapse mechanism of a High Speed Railway Tunnel (T341 Tunnel, Turkey)

6 february 2023 kahramanmaraş – türki̇ye earthquakes: a general overview

On the effect of dem quality for landslide susceptibility mapping