In-situ crystal morphology identification using imaging analysis with application to the L-glutamic acid crystallization

A synthetic image analysis strategy is proposed for in-situ crystal size measurement and shape identification for monitoring crystallization processes, based on using a real-time imaging system. The proposed method consists of image processing, feature analysis, particle sieving, crystal size measurement, and crystal shape identification. Fundamental image features of crystals are selected for efficient classification. In particular, a novel shape feature, referred to as inner distance descriptor, is introduced to quantitatively describe different crystal shapes, which is relatively independent of the crystal size and its geometric direction in an image captured for analysis. Moreover, a pixel equivalent calibration method based on subpixel edge detection and circle fitting is proposed to measure crystal sizes from the captured images. In addition, a kernel function based method is given to deal with nonlinear correlations between multiple features of crystals, facilitating computation efficiency for real-time shape identification. Case study and experimental results from the cooling crystallization of l-glutamic acid demonstrate that the proposed image analysis method can be effectively used for in-situ crystal size measurement and shape identification with good accuracy

Lattice Sieving With G6K

Recent advances in quantum computing threaten the cryptography we use today. This has led to a need for new cryptographic algorithms that are safe against quantum computers. The American standardization organization NIST has now chosen four quantum-safe algorithms in their process of finding new cryptographic standards. Three out of the four algorithms are based on the hardness of finding a shortest vector in a lattice. The biggest threat to such schemes is lattice reduction. One of the best tools used for lattice reduction is the G6K framework. In this thesis, we study sieving algorithms and lattice reduction strategies implemented in G6K. After an introduction to cryptography, we go over the necessary preliminary lattice theory, important concepts, and related problems. Further, we look at lattice reduction where we study different approaches with a main focus on lattice sieving. We then explore the G6K framework, before finally performing some experiments using G6K. The results we get often depend on what type of lattice we are working on. Our experiments show that it is still possible to improve G6K for solving the shortest vector problem for some lattice types.Masteroppgave i informatikkINF399MAMN-INFMAMN-PRO

Improvements on making BKW practical for solving LWE

The learning with errors (LWE) problem is one of the main mathematical foundations of post-quantum cryptography. One of the main groups of algorithms for solving LWE is the Blum–Kalai–Wasserman (BKW) algorithm. This paper presents new improvements of BKW-style algorithms for solving LWE instances. We target minimum concrete complexity, and we introduce a new reduction step where we partially reduce the last position in an iteration and finish the reduction in the next iteration, allowing non-integer step sizes. We also introduce a new procedure in the secret recovery by mapping the problem to binary problems and applying the fast Walsh Hadamard transform. The complexity of the resulting algorithm compares favorably with all other previous approaches, including lattice sieving. We additionally show the steps of implementing the approach for large LWE problem instances. We provide two implementations of the algorithm, one RAM-based approach that is optimized for speed, and one file-based approach which overcomes RAM limitations by using file-based storage.publishedVersio

LUSA: the HPC library for lattice-based cryptanalysis

This paper introduces LUSA - the Lattice Unified Set of Algorithms library - a C++ library that comprises many high performance, parallel implementations of lattice algorithms, with particular focus on lattice-based cryptanalysis. Currently, LUSA offers algorithms for lattice reduction and the SVP. % and the CVP. LUSA was designed to be 1) simple to install and use, 2) have no other dependencies, 3) be designed specifically for lattice-based cryptanalysis, including the majority of the most relevant algorithms in this field and 4) offer efficient, parallel and scalable methods for those algorithms. LUSA explores paralellism mainly at the thread level, being based on OpenMP. However the code is also written to be efficient at the cache and operation level, taking advantage of carefully sorted data structures and data level parallelism. This paper shows that LUSA delivers these promises, by being simple to use while consistently outperforming its counterparts, such as NTL, plll and fplll, and offering scalable, parallel implementations of the most relevant algorithms to date, which are currently not available in other libraries

Fault Detection of Wind Turbine Induction Generators through Current Signals and Various Signal Processing Techniques

Producción CientíficaIn the wind industry (WI), a robust and effective maintenance system is essential. To minimize the maintenance cost, a large number of methodologies and mathematical models for predictive maintenance have been developed. Fault detection and diagnosis are carried out by processing and analyzing various types of signals, with the vibration signal predominating. In addition, most of the published proposals for wind turbine (WT) fault detection and diagnosis have used simulations and test benches. Based on previous work, this research report focuses on fault diagnosis, in this case using the electrical signal from an operating WT electric generator and applying various signal analysis and processing techniques to compare the effectiveness of each. The WT used for this research is 20 years old and works with a squirrel-cage induction generator (SCIG) which, according to the wind farm control systems, was fault-free. As a result, it has been possible to verify the feasibility of using the current signal to detect and diagnose faults through spectral analysis (SA) using a fast Fourier transform (FFT), periodogram, spectrogram, and scalogram

Sugar crystal size characterization using digital image processing.

Thesis (PhD)-University of KwaZulu-Natal, Durban, 2007.The measurement of the crystal size distribution is a key prerequisite in optimising the growth of sugar crystals in crystalisation pans or for quality control of the final product. Traditionally, crystal size measurements are carried out by inspection or using mechanical sieves. Apart from being time consuming, these techniques can only provide limited quantitative information. For this reason, a more quantitative automatic system is required. In our project, software routines for the automated measurement of crystal size using classical image analysis techniques were developed. A digital imaging technique involves automatically analyzing a captured image of a representative sample of ~ 100 crystals for the automated measurement of crystal size has been developed. The main problem of crystals size measurements using image processing is the lack of an efficient algorithm to identify and separate overlapping and touching crystals which otherwise compromise the accuracy of size measurement. This problem of overlapping and touching crystals was addressed in two ways. First, 5 algorithms which identify and separate overlapping and touching crystals, using mathematical morphology as a tool, were evaluated. The accuracy of the algorithms depends on the technique used to mark every crystal in the image. Secondly, another algorithm which used convexity measures of the crystals based on area and perimeter, to identify and reject overlapping and touching crystals, have been developed. Finally, the two crystal sizing algorithms, the one applies ultimate erosion followed by a distance transformation and the second uses convexity measures to identify overlapping crystals, were compared with well established mechanical sieving technique. Using samples obtained from a sugar refinery, the parameters of interest, including mean aperture (MA) and coefficient of variance (CV), were calculated and compared with those obtained from the sieving method. The imaging technique is faster, more reliable than sieving and can be used to measure the full crystal size distributions of both massecuite and dry product