Automated early process fault detection and prediction remains a challenging problem in industrial processes. Traditionally it has been done by multivariate statistical analysis of sensor readings and, more recently, with the help of machine learning methods. The quality of machine learning models strongly depends on feature engineering, that in turn heavily relies on expertise of the process engineers and model developers. With the recent advent of deep learning neural network methods and abundance of available sensor data, it became possible to develop advanced approaches to early fault detection and prediction that do not require feature engineering and provide more accurate and timely results.
In this paper we investigate a wide range of recurrent and convolutional architectures on the publicly available simulated Tennessee Eastman Process extended TEP dataset for the fault detection in chemical processes. We have selected the best architecture for the task and proposed a novel temporal CNN1D2D architecture that achieves overall better performance on the dataset than any referenced method. We have also proposed to use Generative Adversarial Network GAN to extend and enrich data used in training.
High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites in tissues, cell cultures, and agar plates with cellular resolution, but it is hampered by the lack of bioinformatics tools for automated metabolite identification. We report pySM, a framework for false discovery rate (FDR)-controlled metabolite annotation at the level of the molecular sum formula, for high-mass-resolution imaging mass spectrometry (https://github.com/alexandrovteam/pySM). We introduce a metabolite-signal match score and a target–decoy FDR estimate for spatial metabolomics.
In 1992, A. Hiltgen provided first constructions of provably (slightly) secure cryptographic primitives, namely feebly one-way functions. These functions are provably harder to invert than to compute, but the complexity (viewed as the circuit complexity over circuits with arbitrary binary gates) is amplified only by a constant factor (in Hiltgen’s works, the factor approaches 2). In traditional cryptography, one-way functions are the basic primitive of private-key schemes, while public-key schemes are constructed using trapdoor functions. We continue Hiltgen’s work by providing examples of feebly secure trapdoor functions where the adversary is guaranteed to spend more time than honest participants (also by a constant factor). We give both a (simpler) linear and a (better) non-linear construction.
A game with a finite (more than three) number of players on a polyhedron of connected player strategies is studied. This game describes the interaction among (a) the base load power plant (the generator), (b) all the large customers of a regional electrical grid that receive electric energy from the generator, as well as from the available renewable sources of energy, both directly and via electricity storing facilities, and (c) the transmission company. An auxiliary three-person game on polyhedra of disjoint player strategies that is associated with the initial game is also considered. It is shown that an equilibrium point in the auxiliary game is an equilibrium point in the above game with connected player strategies. Verifiable necessary and sufficient conditions of an equilibrium in the auxiliary three-person game are proposed, and these conditions allow one to find equilibria in (the auxiliary) solvable game by solving three linear programming problems two of which form a dual pair.
Abstract—A finite algorithm for determining a vehicle’s position by differences in measured pseudoranges to known reference points is considered. Equations are derived for the case of excessive number of reference points and for coplanar reference points. A convenient complexvalued form of the problem solution is obtained for the coplanar case.
We consider the time-dependent 1D Schrödinger equation on the half-axis with variable coefficients becoming constant for large x. We study a two-level symmetric in time (i.e. the Crank-Nicolson) and any order finite element in space numerical method to solve it. The method is coupled to an approximate transparent boundary condition (TBC). We prove uniform in time stability with respect to initial data and a free term in two norms, under suitable conditions on an operator in the approximate TBC. We also consider the corresponding method on an infinite mesh on the half-axis. We derive explicitly the discrete TBC allowing us to restrict the latter method to a finite mesh. The operator in the discrete TBC is a discrete convolution in time; in turn its kernel is a multiple discrete convolution. The stability conditions are justified for it. The accomplished computations confirm that high order finite elements coupled to the discrete TBC are effective even in the case of highly oscillating solutions and discontinuous potentials. The study is carried out by the first author within The National Research University Higher School of Economics' Academic Fund Program in 2012-2013, research grant No. 11-01-0051.
Рассматривается нестационарное одномерное уравнение Шрёдингера на полуоси с переменными коэффициентами, становящимися постоянными при больших х. Изучается двухслойный симметричной во времени (т.е. Кранка-Николсон) и конечных элементов любого порядка по пространству численный метод ее решения. Для метода ставятся приближенные прозрачные граничные условия (ПГУ). Доказывается равномерная во времени устойчивость в двух нормах по начальным данным и свободному члену при подходящих условиях на оператор в приближенном ПГУ. Рассматривается также соответствующий метод на бесконечной сетке на полуоси. Явно выводятся дискретные ПГУ, позволяющие сузить решение последнего метода на конечную сетку. Оператор в дискретном ПГУ является дискретной сверткой во времени; в свою очередь, его ядро является кратной дискретной сверткой. Для него обоснованы упомянутые выше подходящие условия устойчивости. Проведенные расчеты подтверждают, что конечные элементы высокого порядка в сочетании с дискретными ПГУ являются эффективными даже в случае сильно осциллирующих решений и разрывных потенциалов.
Работа выполнена первым автором при финансовой поддержке программы “Научный фонд НИУ ВШЭ” в 2012–2013 гг., проект 11-01-0051.
Lately, the problem of cell formation (CF) has gained a lot of attention in the industrial engineering literature. Since it was formulated (more than 50 years ago), the problem has incorporated additional industrial factors and constraints while its solution methods have been constantly improving in terms of the solution quality and CPU times. However, despite all the efforts made, the available solution methods (including those for a popular model based on the p-median problem, PMP) are prone to two major types of errors. The first error (the modeling one) occurs when the intended objective function of the CF (as a rule, verbally formulated) is substituted by the objective function of the PMP. The second error (the algorithmic one) occurs as a direct result of applying a heuristic for solving the PMP. In this paper we show that for instances that make sense in practice, the modeling error induced by the PMP is negligible. We exclude the algorithmic error completely by solving the adjusted pseudo-Boolean formulation of the PMP exactly, which takes less than one second on a general-purpose PC and software. Our experimental study shows that the PMP-based model produces high-quality cells and in most cases outperforms several contemporary approaches.