Improving the accuracy of convolutional neural networks by ddentifying and removing outlier images in datasets using t-SNE

In the field of supervised machine learning, the quality of a classifier model is directly correlated with the quality of the data that is used to train the model. The presence of unwanted outliers in the data could significantly reduce the accuracy of a model or, even worse, result in a biased model leading to an inaccurate classification. Identifying the presence of outliers and eliminating them is, therefore, crucial for building good quality training datasets. Pre-processing procedures for dealing with missing and outlier data, commonly known as feature engineering, are standard practice in machine learning problems. They help to make better assumptions about the data and also prepare datasets in a way that best expose the underlying problem to the machine learning algorithms. In this work, we propose a multistage method for detecting and removing outliers in high-dimensional data. Our proposed method is based on utilising a technique called t-distributed stochastic neighbour embedding (t-SNE) to reduce high-dimensional map of features into a lower, two-dimensional, probability density distribution and then use a simple descriptive statistical method called interquartile range (IQR) to identifying any outlier values from the density distribution of the features. t-SNE is a machine learning algorithm and a nonlinear dimensionality reduction technique well-suited for embedding high-dimensional data for visualisation in a low-dimensional space of two or three dimensions. We applied this method on a dataset containing images for training a convolutional neural network model (ConvNet) for an image classification problem. The dataset contains four different classes of images: three classes contain defects in construction (mould, stain, and paint deterioration) and a no-defect class (normal). We used the transfer learning technique to modify a pre-trained VGG-16 model. We used this model as a feature extractor and as a benchmark to evaluate our method. We have shown that, when using this method, we can identify and remove the outlier images in the dataset. After removing the outlier images from the dataset and re-training the VGG-16 model, the results have also shown that the accuracy of the classification has significantly improved and the number of misclassified cases has also dropped. While many feature engineering techniques for handling missing and outlier data are common in predictive machine learning problems involving numerical or categorical data, there is little work on developing techniques for handling outliers in high-dimensional data which can be used to improve the quality of machine learning problems involving images such as ConvNet models for image classification and object detection problems

Automatic Goal Discovery in Subgoal Monte Carlo Tree Search

Monte Carlo Tree Search (MCTS) is a heuristic search algorithm that can play a wide range of games without requiring any domain-specific knowledge. However, MCTS tends to struggle in very complicated games due to an exponentially increasing branching factor. A promising solution for this problem is to focus the search only on a small fraction of states. Subgoal Monte Carlo Tree Search (S-MCTS) achieves this by using a predefined subgoal-predicate that detects promising states called subgoals. However, not only does this make S-MCTS domaindependent, but also it is often difficult to define a good predicate. In this paper, we propose using quality diversity (QD) algorithms to detect subgoals in real-time. Furthermore, we show how integrating QD-algorithms into S-MCTS significantly improves its performance in the Physical Travelling Salesmen Problem without requiring any domain-specific knowledge

Designing a hybrid thin-film/wafer silicon triple photovoltaic junction for solar water splitting

Solar fuels are a promising way to store solar energy seasonally. This paper proposes an earth-abundant heterostructure to split water using a photovoltaic-electrochemical device (PV-EC). The heterostructure is based on a hybrid architecture of a thin-film (TF) silicon tandem on top of a c-Si wafer (W) heterojunction solar cell (a-Si:H (TF)/nc-Si:H (TF)/c-Si(W)) The multijunction approach allows to reach enough photovoltage for water splitting, while maximizing the spectrum utilization. However, this unique approach also poses challenges, including the design of effective tunneling recombination junctions (TRJ) and the light management of the cell. Regarding the TRJs, the solar cell performance is improved by increasing the n-layer doping of the middle cell. The light management can be improved by using hydrogenated indium oxide (IOH) as transparent conductive oxide (TCO). Finally, other light management techniques such as substrate texturing or absorber bandgap engineering were applied to enhance the current density. A correlation was observed between improvements in light management by conventional surface texturing and a reduced nc-Si:H absorber material quality. The final cell developed in this work is a flat structure, using a top absorber layer consisting of a high bandgap a-Si:H. This triple junction cell achieved a PV efficiency of 10.57%, with a fill factor of 0.60, an open-circuit voltage of 2.03 V and a short-circuit current density of 8.65 mA/cm2. When this cell was connected to an IrOx/Pt electrolyser, a stable solar-to-hydrogen (STH) efficiency of 8.3% was achieved and maintained for 10 hours.</p

Quantifying Quantum Correlations in Fermionic Systems using Witness Operators

We present a method to quantify quantum correlations in arbitrary systems of indistinguishable fermions using witness operators. The method associates the problem of finding the optimal entan- glement witness of a state with a class of problems known as semidefinite programs (SDPs), which can be solved efficiently with arbitrary accuracy. Based on these optimal witnesses, we introduce a measure of quantum correlations which has an interpretation analogous to the Generalized Robust- ness of entanglement. We also extend the notion of quantum discord to the case of indistinguishable fermions, and propose a geometric quantifier, which is compared to our entanglement measure. Our numerical results show a remarkable equivalence between the proposed Generalized Robustness and the Schliemann concurrence, which are equal for pure states. For mixed states, the Schliemann con- currence presents itself as an upper bound for the Generalized Robustness. The quantum discord is also found to be an upper bound for the entanglement.Comment: 7 pages, 6 figures, Accepted for publication in Quantum Information Processin

Inflationary Perturbations: the Cosmological Schwinger Effect

This pedagogical review aims at presenting the fundamental aspects of the theory of inflationary cosmological perturbations of quantum-mechanical origin. The analogy with the well-known Schwinger effect is discussed in detail and a systematic comparison of the two physical phenomena is carried out. In particular, it is demonstrated that the two underlying formalisms differ only up to an irrelevant canonical transformation. Hence, the basic physical mechanisms at play are similar in both cases and can be reduced to the quantization of a parametric oscillator leading to particle creation due to the interaction with a classical source: pair production in vacuum is therefore equivalent to the appearance of a growing mode for the cosmological fluctuations. The only difference lies in the nature of the source: an electric field in the case of the Schwinger effect and the gravitational field in the case of inflationary perturbations. Although, in the laboratory, it is notoriously difficult to produce an electric field such that pairs extracted from the vacuum can be detected, the gravitational field in the early universe can be strong enough to lead to observable effects that ultimately reveal themselves as temperature fluctuations in the Cosmic Microwave Background. Finally, the question of how quantum cosmological perturbations can be considered as classical is discussed at the end of the article.Comment: 49 pages, 6 figures, to appear in a LNP volume "Inflationary Cosmology

Vibrational properties of CdGa2S4 at high pressure

[EN] Raman scattering measurements have been performed in cadmium digallium sulphide (CdGa2S4) with defect chalcopyrite structure up to 25 GPa in order to study its pressure-induced phase transitions. These measurements have been complemented and compared with latticedynamics ab initio calculations including the TO-LO splitting at high pressures in order to provide a better assignment of experimental Raman modes. In addition, experimental and theoretical Gruneisen parameters have been reported in order to calculate the molar heat capacity and thermal expansion coefficient of CdGa2S4. Our measurements provide evidence that CdGa2S4 undergoes an irreversible phase transition above 15 GPa to a Raman-inactive phase, likely with a disordered rock salt structure. Moreover, the Raman spectrum observed on downstroke from 25 GPa to 2 GPa has been attributed to a new phase, tentatively identified as a disordered zinc blende structure, that undergoes a reversible phase transition to the Raman-inactive phase above 10 GPa. Published under license by AIP Publishing.The authors thank the financial support of the Spanish Ministerio de Economia y Competitividad (MINECO) under Grant Nos. MAT2016-75586-C4-2/3-P and MAT2015-71070-REDC (MALTA Consolider) and the Generalitat Valenciana under Project No. PROMETEO/2018/123-EFIMAT. E. P.-G., A. M., and P. R.-H. acknowledge computing time provided by Red Espanola de Supercomputacion (RES) and MALTA-Cluster.Gallego-Parra, S.; Gomis, O.; Vilaplana Cerda, RI.; Ortiz, H.; Perez-Gonzalez, E.; Luna Molina, R.; Rodríguez-Hernández, P.... (2019). Vibrational properties of CdGa2S4 at high pressure. 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Patency of endoscopic ultrasound-guided gastroenterostomy in the treatment of malignant gastric outlet obstruction

Background and study aims Endoscopic ultrasoundguided gastroenterostomy (EUS-GE) with a lumen-apposing metal stent (LAMS) is a novel, minimally invasive technique in the palliative treatment of malignant gastric outlet obstruction (GOO). Several studies have demonstrated feasibility and safety of EUS-GE, but evidence on long-term durability is limited. The aim of this study was to evaluate patency of EUS-GE in treatment of malignant GOO. Patients and Methods An international multicenter study was performed in seven centers in four European countries. Patients who underwent EUS-GE with a LAMS between March 2015 and March 2019 for palliative treatment of symptomatic malignant GOO were included retrospectively. Our main outcome was recurrent obstruction due to LAMS dysfunction; other outcomes of interest were technical success, clinical success, adverse events (AEs), and survival. Results A total of 45 patients (mean age 69.9 ± 12.3 years and 48.9% male) were included. Median duration of followup was 59 days (interquartile range [IQR] 41–128). Recurrent obstruction occurred in two patients (6.1 %), after 33 and 283 days of follow-up. Technical success was achieved in 39 patients (86.7 %). Clinical success was achieved in 33 patients (73.3 %). AEs occurred in 12 patients (26.7 %), of which five were fatal. Median overall survival was 57 days (IQR 32–114). Conclusions EUS-GE showed a low rate of recurrent obstruction. The relatively high number of fatal AEs underscores the importance of careful implementation of EUSGE in clinical practice

Evolution of the electronic structure with size in II-VI semiconductor nanocrystals

In order to provide a quantitatively accurate description of the band gap variation with sizes in various II-VI semiconductor nanocrystals, we make use of the recently reported tight-binding parametrization of the corresponding bulk systems. Using the same tight-binding scheme and parameters, we calculate the electronic structure of II-VI nanocrystals in real space with sizes ranging between 5 and 80 {\AA} in diameter. A comparison with available experimental results from the literature shows an excellent agreement over the entire range of sizes.Comment: 17 pages, 4 figures, accepted in Phys. Rev.