Standard Examples Research Articles

Learning Probabilities: Towards a Logic of Statistical Learning

We propose a new model for forming beliefs and learning about unknown probabilities (such as the probability of picking a red marble from a bag with an unknown distribution of coloured marbles). The most widespread model for such situations of 'radical uncertainty' is in terms of imprecise probabilities, i.e. representing the agent's knowledge as a set of probability measures. We add to this model a plausibility map, associating to each measure a plausibility number, as a way to go beyond what is known with certainty and represent the agent's beliefs about probability. There are a number of standard examples: Shannon Entropy, Centre of Mass etc. We then consider learning of two types of information: (1) learning by repeated sampling from the unknown distribution (e.g. picking marbles from the bag); and (2) learning higher-order information about the distribution (in the shape of linear inequalities, e.g. we are told there are more red marbles than green marbles). The first changes only the plausibility map (via a 'plausibilistic' version of Bayes' Rule), but leaves the given set of measures unchanged; the second shrinks the set of measures, without changing their plausibility. Beliefs are defined as in Belief Revision Theory, in terms of truth in the most plausible worlds. But our belief change does not comply with standard AGM axioms, since the revision induced by (1) is of a non-AGM type. This is essential, as it allows our agents to learn the true probability: we prove that the beliefs obtained by repeated sampling converge almost surely to the correct belief (in the true probability). We end by sketching the contours of a dynamic doxastic logic for statistical learning.

Improbability of Collisions in n-Body Systems

For a wide class of two-body interactions, including standard examples like gravitational or Coulomb fields, we show that collision orbits in $n$-body systems are of Liouville measure zero for all energies. We use techniques from symplectic geometry to relate the volume of the union of collision orbits to the area of Poincar\'e surfaces surrounding the collision set.

GPU Parallelization Nested Decomposition Method for Solving Large Linear Systems in Reservoir Numerical Simulation

This paper designs a highly parallel Nested Factorization (NF) to solve large linear equations generated in reservoir numerical simulation problems. The NF method is a traditional linear solution preprocessing method for reservoir numerical simulation problems, and has regained attention in recent years due to its potential to extend to parallel architectures such as GPUs (Graphics Processor Units). The parallel algorithm of this paper is based on the MPNF (Massively Parallel Nested Factorization) framework proposed by Appleya (Appleyard, Appleyard, Wakefield, & Desitter, 2011). The MPNF algorithm designed in this paper focuses on its efficient implementation on the GPU parallel architecture. Its features include: using a custom matrix structure to achieve merge access, improving access bottlenecks and improving the efficiency of the SpMV algorithm. It is also applicable to the two-stage preprocessing method CPR. (Constrain Pressure Residual) pressure solution and global preprocessing stage; the MPNF method is extended to the solution of 2.5-dimensional unstructured grid problem. The parallel algorithm in this paper has been integrated into the reservoir numerical simulator. For the SPE10 (million grid, highly heterogeneous) standard example, the GPU-based parallel NF algorithm is in the structured grid model and the equivalent 2.5-dimensional non- On the structured grid model, compared with the serial version of the NF method, the acceleration ratios of 19.8 and 17.0 times were obtained respectively; compared with the mainstream serial solution method, the efficiency was also improved by 2 to 3 times.

Remote sensing data quality model: from data sources to lifecycle phases

ABSTRACT The importance of data quality assessment has significantly increased with the boom of information technology and the growing demand for remote sensing (RS) data. The Remote Sensing Data Quality Working Group of the International Society for Photogrammetry and Remote Sensing aimed to conduct an investigation on the principles of data quality. Literature review revealed that most publications introduce data quality models for application specific processing chains and quality schemes are built case by case with particular domain indicators only. Yet no general concept independent from applications has been developed so far. This paper focuses on the formulation of a RS quality concept adopted from information technology domain describing a triangular RS data quality scheme that relates data sources, quality dimensions and lifecycle phases. Following the introduction it provides examples of international standards and fundamentals of theoretic quality modelling. After a short overview on platforms/sensors, definitions of different quality dimensions are presented with their metrics organised in clusters (like resolution or accuracy). The main achievement of the paper relates lifecycle phases to different quality dimensions of high relevance. The objective is not only to address experts of RS but to raise awareness of uncertainty for the general RS user community.

A Coordinated Dual-Channel Wide Area Damping Control Strategy for a Doubly-Fed Induction Generator Used for Suppressing Inter-Area Oscillation

Using a doubly-fed induction generator (DFIG), with an additional active or reactive damping controller, is a new method of suppressing the inter-area oscillation of a power system. However, using active power modulation (APM) may decrease the damping of the shaft oscillation mode of a DFIG and the system damping target cannot be achieved through reactive power modulation (RPM) in some cases. Either single APM or RPM does not consider system damping and torsional damping simultaneously. In this paper, an active-reactive coordinated dual-channel power modulation (DCPM) damping controller is proposed for DFIGs. First, considering the electromechanical parts and control structure of the wind turbine, an electromechanical transient model and an additional damping controller model of DFIGs are established. Then, the dynamic objective function for coordinating the parameters of the additional damping controller is proposed. The ratio between the active power channel and reactive power channel modulation is derived from the parameters optimized by the particle swarm optimization algorithm. Finally, the effectiveness and practicability of the designed strategy is verified by comparing it with a traditional, simple damping controller design strategy. Standard simulation system examples are used in the comparison. Results show that the DCPM is better at maximizing the damping control capability of the rotor-side controller of a DFIG and simultaneously minimizing adverse effects on torsional damping than the traditional strategy.

Keeping Patient Credit Card and Payment Information on File

Keeping Patient Credit Card and Payment Information on File

Evolutionary Algorithm Optimization of Zeeman Deceleration: Is It Worthwhile for Longer Decelerators?

In Zeeman deceleration, only a small subset of low-field-seeking particles in the incoming beam possess initial velocities and positions that place them within the phase-space acceptance of the device. In order to maximize the number of particles that are successfully decelerated to a selected final velocity, we seek to optimize the phase-space acceptance of the decelerator. Three-dimensional particle trajectory simulations are employed to investigate the potential benefits of using a covariance matrix adaptation evolutionary strategy (CMA-ES) optimization method for decelerators longer than 12 stages and for decelerating species other than H atoms. In all scenarios considered, the evolutionary algorithm-optimized sequences yield vastly more particles within the target velocity range. This is particularly evident in scenarios where standard sequences are known to perform poorly; simulations show that CMA-ES optimization of a standard sequence decelerating H atoms from an initial velocity of 500 ms–1 down to a final velocity of 200 ms–1 in a 24-stage decelerator produces a considerable 5921% (or 60-fold) increase in the number of successfully decelerated particles. Particle losses that occur with standard pulse sequences—for example, arising from the coupling of longitudinal and transverse motion—are overcome in the CMA-ES optimization process as the passage of all particles through the decelerator is explicitly considered and focusing effects are accounted for in the optimization process.

Data-Driven Economic NMPC Using Reinforcement Learning

Reinforcement Learning (RL) is a powerful tool to perform data-driven optimal control without relying on a model of the system. However, RL struggles to provide hard guarantees on the behavior of the resulting control scheme. In contrast, Nonlinear Model Predictive Control (NMPC) and Economic NMPC (ENMPC) are standard tools for the closed-loop optimal control of complex systems with constraints and limitations, and benefit from a rich theory to assess their closed-loop behavior. Unfortunately, the performance of (E)NMPC hinges on the quality of the model underlying the control scheme. In this paper, we show that an (E)NMPC scheme can be tuned to deliver the optimal policy of the real system even when using a wrong model. This result also holds for real systems having stochastic dynamics. This entails that ENMPC can be used as a new type of function approximator within RL. Furthermore, we investigate our results in the context of ENMPC and formally connect them to the concept of dissipativity, which is central for the ENMPC stability. Finally, we detail how these results can be used to deploy classic RL tools for tuning (E)NMPC schemes. We apply these tools on both a classical linear MPC setting and a standard nonlinear example from the ENMPC literature.

Utilization of Symmetric Switching Functions in the Symbolic Reliability Analysis of Multi-State k-out-of-n Systems

Symmetric switching functions (SSFs) play a prominent role in the reliability analysis of a binary k-out-of-n: G system, which is a dichotomous system that is successful if and only if at least k out of its n components are successful. The aim of this paper is to extend the utility of SSFs to the reliability analysis of a multi-state k-out-of-n: G system, which is a multi-state system whose multi-valued success is greater than or equal to a certain value j (lying between 1 (the lowest output level) and M (the highest output level)) whenever at least km components are in state m or above for all m such that 1 ≤ m ≤ j. This paper is devoted to the analysis of non-repairable multi-state k-out-of-n: G systems with independent non-identical components. The paper utilizes algebraic techniques of multiple-valued logic (together with known properties of SSFs) to evaluate each of the multiple levels of the system output as an individual binary or propositional function of the system multi-valued inputs. The formula of each of these levels is then written as a probability–ready expression, thereby allowing its immediate conversion, on a one-to-one basis, into a probability or expected value. The symbolic reliability analysis of a commodity-supply system (which serves as a standard gold example of a multi-state k-out-of-n: G system) is completed successfully herein, yielding results that have been checked symbolically, and also were shown to agree numerically with those obtained earlier.

High‐frequency cycles of brachiopod shell beds on subaqueous delta‐scale clinoforms (early Pliocene, south‐east Spain)

AbstractDuring the early Pliocene, subaqueous delta‐scale clinoforms developed in the Águilas Basin, in a mixed temperate carbonate–siliciclastic system. The facies distribution is consistent with the infralittoral prograding wedge model. Stacking patterns and bounding surfaces indicate that the clinoforms formed during the highstand and falling sea‐level stages of a high rank cycle. Twenty‐two prograding clinothems were recognized over a distance of ≥1 km. Biostratigraphic data indicate a time span shorter than 700 kyr for the whole unit (MPl3 biozone of the Mediterranean Pliocene). Cyclic skeletal concentrations and occasional biostromes of suspension feeders (terebratulid brachiopods, modiolid bivalves and adeoniform bryozoan colonies), slightly evolved glauconite and occasionalGlossifungitesichnofacies formed on the clinoforms during high‐frequency pulses of relative sea‐level rise. During such stages, increased accommodation space in the topsets of the clinoforms caused a strong reduction of terrigenous input into the foresets and bottomsets. This provided favourable conditions for the development of these suspension feeder palaeocommunities. During stillstand stages, however, reduced accommodation space in the topsets eventually resumed progradation in the foresets. There, the abundance ofDitrupatubes indicates frequent siltation events that extirpated the terebratulid populations and other epifaunal suspension feeders in the foreset and bottomset subenvironments. The occurrence of shell beds on the clinoforms suggests that this case study represents lower progradation rates than standard examples where shell beds bound the clinobedded units at their base and top only. Importantly, the distributions of biofacies and ichnoassemblage associations contribute significantly to the understanding of the effects of relative sea‐level fluctuations on the evolution of subaqueous delta‐scale clinoform systems.

Accounting Information in Corporate Governance: Implications for Standard Setting

ABSTRACTAccounting standards are crucially relevant in the context of the use of accounting information in corporate governance. Notwithstanding highly liquid capital markets, large and small shareholders, many activist shareholders, sophisticated analysts, vigilant press reporters, and a vibrant litigious environment, corporate governance challenges continue to make media headlines, and they seem to occur with a great degree of regularity. The essay offers a high-level description of the objectives of accounting standards, a quick run through the evolution of accounting research over the past half-century, and, finally, offers three examples of standards and disclosure requirements that might be worthwhile to reexamine in light of the governance role of accounting information.

Taylor series and twisting-index invariants of coupled spin–oscillators

About six years ago, semitoric systems on 4-dimensional manifolds were classified by Pelayo & Vũ Ngọc by means of five invariants. A standard example of such a system is the coupled spin–oscillator on S2×R2. Calculations of three of the five semitoric invariants of this system (namely the number of focus–focus singularities, the generalised semitoric polygon, and the height invariant) already appeared in the literature, but the so-called twisting index was not yet computed and, of the so-called Taylor series invariant, only the linear terms were known.In the present paper, we complete the list of invariants for the coupled spin–oscillator by calculating higher order terms of the Taylor series invariant and by computing the twisting index. Moreover, we prove that the Taylor series invariant has certain symmetry properties that make the even powers in one of the variables vanish and allow us to show superintegrability of the coupled spin–oscillator on the zero energy level.

Attending to blame

Much has been written lately about cases in which blame of the blameworthy is nonetheless inappropriate because of facts about the blamer. Meddlesome and hypocritical cases are standard examples. Perhaps the matter is none of my business or I am guilty of the same sort of offense, so though the target is surely blameworthy, my blame would be objectionable. In this paper, I defend a novel explanation of what goes wrong with such blame, in a way that draws the cases together. In brief, I argue that blaming is essentially an attentive activity, and that, consequently, meddlesome and hypocritical blamers are attending to the wrong things.

Wind loading on shell structures on example of CICIND and Eurocode standards

Wind loading on shell structures on example of CICIND and Eurocode standards

Hamiltonian circle actions with fixed point set almost minimal

Motivated by recent works on Hamiltonian circle actions satisfying certain minimal conditions, in this paper, we consider Hamiltonian circle actions satisfying an almost minimal condition. More precisely, we consider a compact symplectic manifold $(M, \omega)$ admitting a Hamiltonian circle action with fixed point set consisting of two connected components $X$ and $Y$ satisfying $\dim(X)+\dim(Y)=\dim(M)$. Under certain cohomology conditions, we determine the circle action, the integral cohomology rings of $M$, $X$ and $Y$, and the total Chern classes of $M$, $X$, $Y$, and of the normal bundles of $X$ and $Y$. The results show that these data are unique --- they are exactly the same as those in the standard example $\Gt_2(\R^{2n+2})$, the Grassmannian of oriented $2$-planes in $\R^{2n+2}$, which is of dimension $4n$ with (any) $n\in\N$, equipped with a standard circle action. Moreover, if $M$ is K\"ahler and the action is holomorphic, we can use a few different criteria to claim that $M$ is $S^1$-equivariantly biholomorphic and $S^1$-equivariantly symplectomorphic to $\Gt_2(\R^{2n+2})$.

Reduced-Order Modelling of LTI Systems by Using Routh Approximation and Factor Division Methods

In this paper, a new model reduction technique for the large-scale continuous time systems is proposed. The proposed technique is a mixed method of Routh approximation and factor division techniques. In this technique, the Routh approximation method is applied for determining the denominator coefficients of the reduced model and the numerator coefficients are calculated by the factor division method. The proposed technique has two main advantages as it gives the stable reduced-order model if the original model is stable and ensures the retention of first “r” number of time moments of the actual system in the rth-order reduced system. This method is also applicable for those systems for which Routh approximation method fails. To illustrate the proposed method, a real-time system model is reduced where the reduced model retains the fundamental properties of the actual model. In order to examine the efficiency, accuracy and comparison to other existing standard model reduction methods, the presented technique has been verified on two standard numerical examples taken from the literature.

Estimation of maximum loads of residential electricity users

The subject matter of coefficient factors is not a frequent object of analysis in the scientific literature. However, because of the use of this term in engineering tasks and because of the constantly changing manner of energy use (resulting from the dissemination of new appliances), there is a need for current analysis and possible revision of the approach based on coefficient factors. The aim of the paper is to compare currently recommended values of this coefficient in the task of estimating the peak output of installations on the example of standards applied in Poland. On the basis of smart metering data and statistical methods, coefficient factors for residential consumers supplied from the municipal distribution network were determined. The results were compared with the currently applied values in accordance with the industry standard issued by the Association of Polish Electrical Engineers (standard N SEP-E-002).

Optimization Algorithm for Reduction the Size of Dixon Resultant Matrix: A Case Study on Mechanical Application

In the process of eliminating variables in a symbolic polynomial system, the extraneous factors are referred to the unwanted parameters of resulting polynomial. This paper aims at reducing the number of these factors via optimizing the size of Dixon matrix. An optimal configuration of Dixon matrix would lead to the enhancement of the process of computing the resultant which uses for solving polynomial systems. To do so, an optimization algorithm along with a number of new polynomials is introduced to replace the polynomials in the polynomial system. Moreover, the monomial multipliers are optimally positioned to multiply each of the polynomials. Further, the optimization algorithm has been used in terms of complexity analysis. Implementation of this method on standard examples proves the high efficiency the method.

The multiple dissociation constants of glutathione disulfide: interpreting experimental pH-titration curves with ab initio MD simulations.

The hexapeptide glutathione disulfide (GSSG) has six ionizable groups with six associated dissociation constants. The experimentally measured pH-titration curve, however, does not exhibit the six corresponding equivalence points and bears little resemblance to standard textbook examples of acid-base pH-titration curves. The curve highlights the difficulties in determining multiple pKa values of polyprotic acids - typically proteins and peptides - from experiment. The six pKa values of GSSG can, however, be estimated using Car-Parrinello molecular dynamics (CPMD) simulations in conjunction with metadynamics sampling of the underlying free energy landscape of the dissociation reactions. Ab initio MD simulations were performed on a GSSG molecule solvated by 200 water molecules. Using the estimated pKa values the theoretical titration curve was calculated and found to be in good agreement with experiment. The results clearly highlight how dissociation constants estimated from ab initio MD simulations can facilitate the interpretation of the pH-titration curves of complex chemical and biological systems.

Sundials/ML: Connecting OCaml to the Sundials Numeric Solvers

This paper describes the design and implementation of a comprehensive OCaml interface to the Sundials library of numeric solvers for ordinary differential equations, differential algebraic equations, and non-linear equations. The interface provides a convenient and memory-safe alternative to using Sundials directly from C and facilitates application development by integrating with higher-level language features, like garbage-collected memory management, algebraic data types, and exceptions. Our benchmark results suggest that the interface overhead is acceptable: the standard examples are rarely twice as slow in OCaml than in C, and often less than 50% slower. The challenges in interfacing with Sundials are to efficiently and safely share data structures between OCaml and C, to support multiple implementations of vector operations and linear solvers through a common interface, and to manage calls and error signalling to and from OCaml. We explain how we overcame these difficulties using a combination of standard techniques such as phantom types and polymorphic variants, and carefully crafted data representations.