Spacetime Singularities in String and its Low Dimensional Effective Theory

Spacetime singularities are studied in both the $D+d$-dimensional string theory and its $D$-dimensional effective theory, obtained by the Kaluza-Klein compactification. It is found that spacetime singularities in the low dimensional effective theory may or may not remain after lifted to the $D+d$-dimensional string theory, depending on particular solutions. It is also found that there exist cases in which spacetime singularities appearing in high/low dimensional spacetimes do not necessarily happen on the same surfaces.Comment: revtex4, 15 pages, 10 figures. Typos are corrected. Version to appear in Inter. J. Mod. Phys.

A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols

Soil spectral libraries (SSLs) are important big-data archives (spectra associated with soil properties) that are analyzed via machine-learning algorithms to estimate soil attributes. Since different spectral measurement protocols are applied when constructing SSLs, it is necessary to examine harmonization techniques to merge the data. In recent years, several techniques for harmonization have been proposed, among which the internal soil standard (ISS) protocol is the most largely applied and has demonstrated its capacity to rectify systematic effects during spectral measurements. Here, we postulate that a spectral transfer function (TF) can be extracted between existing (old) SSLs if a subset of samples from two (or more) different SSLs are remeasured using the ISS protocol. A machine-learning TF strategy was developed, assembling random forest (RF) spectral-based models to predict the ISS spectral condition using soil samples from two existing SSLs. These SSLs had already been measured using different protocols without any ISS treatment the Brazilian (BSSL, generated in 2019) and the European (LUCAS, generated in 2009-2012) SSLs. To verify the TF's ability to improve the spectral assessment of soil attributes after harmonizing the different SSLs' protocols, RF spectral-based models for estimating organic carbon (OC) in soil were developed. The results showed high spectral similarities between the ISS and the ISS-TF spectral observations, indicating that post-ISS rectification is possible. Furthermore, after merging the SSLs with the TFs, the spectral-based assessment of OC was considerably improved, from R2 = 0.61, RMSE (g/kg) = 12.46 to R2 = 0.69, RMSE (g/kg) = 11.13. Given our results, this paper enhances the importance of soil spectroscopy by contributing to analyses in remote sensing, soil surveys, and digital soil mapping

Colliding branes and formation of spacetime singularities in string theory

Colliding branes without $Z_{2}$ symmetry and the formation of spacetime singularities in string theory are studied. After developing the general formulas to describe such events, we study a particular class of exact solutions first in the 5-dimensional effective theory, and then lift it to the 10-dimensional spacetime. In general, the 5-dimensional spacetime is singular, due to the mutual focus of the two colliding 3-branes. Non-singular cases also exist, but with the price that both of the colliding branes violate all the three energy conditions, weak, dominant, and strong. After lifted to 10 dimensions, we find that the spacetime remains singular, whenever it is singular in the 5-dimensional effective theory. In the cases where no singularities are formed after the collision, we find that the two 8-branes necessarily violate all the energy conditions.Comment: revtex4, 13 figures. Some typos were corrected, and new refereeces added. Final version to appear in JHE

Autoencoders for Anomaly Detection in an Industrial Multivariate Time Series Dataset †

In smart manufacturing, the automation of anomaly detection is essential for increasing productivity. Timeseries data from production processes are often complex sequences and their assessment involves many variables. Thus, anomaly detection with deep learning approaches is considered as an efficient and effective methodology. In this work, anomaly detection with deep autoencoders is examined. Three autoencoders are employed to analyze an industrial dataset and their performance is assessed. Autoencoders based on long short-term memory and convolutional neural networks appear to be the most promising. © 2022 by the authors

Soil organic carbon prediction and mapping using Sentinel-2 multi-temporal imagery data over Greek croplands

International audienc

Wafer Map Defect Pattern Recognition using Imbalanced Datasets

The accurate and automatic inspection of wafer maps is vital for semiconductor engineers to identify defect causes and to optimize the wafer fabrication process. This research work seeks to address the pattern recognition task for the identification of defects in wafer maps, by developing a deep Convolutional Neural Network (CNN) classifier. The proposed CNN-based model utilizes various pre- and post-processing tools and is applied on the public but highly imbalanced industrial dataset WM-811K. To handle imbalance, a methodology of treating each class individually is proposed by applying different processing techniques for down-sampling, splitting and data augmentation based on the number of samples. The proposed model achieves 95.3% accuracy and 93.78% macro F1-score and outperformes other models in the related literature concerning the identification of the majority of classes. © 2022 IEEE

Project Icarus: progress report on technical developments and design considerations

Icarus is a theoretical design study of an interstellar spacecraft that is the successor to the 1970s Project Daedalus. This paper summarises some of the technical progress that has occurred since its launch in September 2009 and discusses each of the twenty research modules that define the project, encompassing all the major spacecraft systems. A number of options are currently available for the design configuration and mission profile and these are discussed prior to entering Phase IV of the design study which begins the process of down selecting design options. This paper represents a progress report on Project Icarus and is a submission of the Project Icarus Study Group