Arbitrary Memory Research Articles

Time-strain separability in medium-amplitude oscillatory shear

We derive and study equations for the weakly nonlinear medium-amplitude oscillatory shear (MAOS) response of materials exhibiting time-strain separability. Results apply to constitutive models with arbitrary linear memory function m(s) and for both viscoelastic liquids and viscoelastic solids. The derived equations serve as a reference to identify which models are time-strain separable (TSS) and which may appear separable but are not, in the weakly nonlinear limit. More importantly, we study how the linear viscoelastic (LVE) relaxation spectrum, H(τ), affects the frequency dependence of the TSS MAOS material functions. Continuous relaxation spectra are considered that are associated with analytical functions (log-normal and asymmetric Lorentzian distributions), fractional mechanical models (Maxwell and Zener), and molecular theories (Rouse and Doi-Edwards). TSS MAOS signatures reveal much more than just the perturbation parameter A in the shear damping function small-strain expansion, h(γ)=1+Aγ2+Oγ4. Specifically, the distribution of terminal relaxation times is significantly more apparent in the TSS MAOS functions than their LVE counterparts. We theoretically show that this occurs because TSS MAOS material functions are sensitive to higher-order moments of the relaxation spectrum, which leads to the definition of MAOS liquids. We also show the first examples of MAOS signatures that differ from the liquid-like terminal MAOS behavior predicted by the fourth-order fluid expansion. This occurs when higher moments of the relaxation spectrum are not finite. The famous corotational Maxwell model is a subset of our results here, for which A = −1/6, and any LVE relaxation spectrum could be used.

Uniform stability of semilinear wave equations with arbitrary local memory effects versus frictional dampings

This paper is concerned with the mixed initial–boundary value problem for semilinear wave equations with complementary frictional dampings and memory effects. We successfully establish uniform exponential and polynomial decay rates for the solutions to this initial–boundary value problem under much weak conditions concerning memory effects. More specifically, we obtain the exponential and polynomial decay rates after removing the fundamental condition that the memory-effect region includes a part of the system boundary, while the condition is a necessity in the previous literature; moreover, for the polynomial decay rates we only assume minimal conditions on the memory kernel function g, without the usual assumption of g′ controlled by g.

Recurrent-OctoMap: Learning State-Based Map Refinement for Long-Term Semantic Mapping With 3-D-Lidar Data

This paper presents a novel semantic mapping approach, Recurrent-OctoMap, learned from long-term 3D Lidar data. Most existing semantic mapping approaches focus on improving semantic understanding of single frames, rather than 3D refinement of semantic maps (i.e. fusing semantic observations). The most widely-used approach for 3D semantic map refinement is a Bayesian update, which fuses the consecutive predictive probabilities following a Markov-Chain model. Instead, we propose a learning approach to fuse the semantic features, rather than simply fusing predictions from a classifier. In our approach, we represent and maintain our 3D map as an OctoMap, and model each cell as a recurrent neural network (RNN), to obtain a Recurrent-OctoMap. In this case, the semantic mapping process can be formulated as a sequence-to-sequence encoding-decoding problem. Moreover, in order to extend the duration of observations in our Recurrent-OctoMap, we developed a robust 3D localization and mapping system for successively mapping a dynamic environment using more than two weeks of data, and the system can be trained and deployed with arbitrary memory length. We validate our approach on the ETH long-term 3D Lidar dataset [1]. The experimental results show that our proposed approach outperforms the conventional "Bayesian update" approach.

Shape Neutral Analysis of Graph-based Data-structures

AbstractMalformed data-structures can lead to runtime errors such as arbitrary memory access or corruption. Despite this, reasoning over data-structure properties for low-level heap manipulating programs remains challenging. In this paper we present a constraint-based program analysis that checks data-structure integrity, w.r.t. given target data-structure properties, as the heap is manipulated by the program. Our approach is to automatically generate a solver for properties using the type definitions from the target program. The generated solver is implemented using a Constraint Handling Rules (CHR) extension of built-in heap, integer and equality solvers. A key property of our program analysis is that the target data-structure properties are shape neutral, i.e., the analysis does not check for properties relating to a given data-structure graph shape, such as doubly-linked-lists versus trees. Nevertheless, the analysis can detect errors in a wide range of data-structure manipulating programs, including those that use lists, trees, DAGs, graphs, etc. We present an implementation that uses the Satisfiability Modulo Constraint Handling Rules (SMCHR) system. Experimental results show that our approach works well for real-world C programs.

ПСИХОФІЗІОЛОГІЧНІ ЗМІНИ В ОРГАНІЗМІ СТУДЕНТІВ ПІД ВПЛИВОМ НАВЧАЛЬНОГО НАВАНТАЖЕННЯ

Introduction: Preparation of students for professional activity requires significant psycho-physiological stress. Adaptive changes that occur in the body, characterize the level of functioning of systems and their potential capabilities. Purpose: The aim of the artcle was to investigate the changes in mental functions and vegetative reactions in the formation of long-term adaptation of the students organisms to the study load. Methods: A method for studying the properties of attention for correctional tables Anfimova, the method of arrangement of numbers, red-black tables of Schulte, methods of studying short-term arbitrary visual memory; 5-minute Heart Rate Variability (HRV) records. Results: The study load for students of “Physics and Mathematics” (PHM) and “Chemistry and Biology”(CHB) corresponded to their psychological and mental abilities that were decisive when choosing a specialty, and therefore did not cause significant changes in attention and mnemonic processes. Adaptive reactions manifested in vegetative regulation. Changes in HRV showed an increase in parasympathetic regulation and decreased neurohumoral modulation in women, “Foreign Languages” (FL). Reduced memory for words (p ≤ 0.05), caused tensions of regulatory influences and increased central regulation. Under the influence of the educational load in the students of the “Physical Education” (PHE), the indicators of mental activity improved (p ≤ 0.05). Changes in regulatory influences were manifested in lowering the activity of higher super-segmental levels of cardiac rhythm management and increased activity of the respiratory and vasomotor centers. In women, PHM was observed reduction of cerebro-ergotropic activity (p ≤ 0.05) and maintenance of vegetative balance. Low volume and productivity of attention showed a decrease in efficiency, but it did not have a disruptive effect on the body. In students of CHB the activity of both departments of vegetative regulation decreased. This indicated the development of unsatisfactory adaptation mechanisms under the influence of the study load. Originality: The psycho-physiological parameters of students of different specializations of linked samples have been analyzed. Differences in the formation of adaptive changes in an organism depending on the content of educational activity have been established. Conclusion: The tension of regulatory mechanisms was felt by the students of FL and CHB. Women of PHE, psychophysiological parameters have improved as a result of high motor activity. The smallest psychophysiological discomfort was felt by women of PHM, which was manifested in the stability of the studied indicators.

The Gaussian CEO Problem for Scalar Sources With Arbitrary Memory

In this paper, we consider the achievable sum-rate/distortion tradeoff for the Gaussian central estimation officer (CEO) problem with a scalar source having arbitrary memory. We describe how the arbitrary memory problem can be fully characterized by using known results for the vector CEO problem, and then we formulate the variational problem of minimizing the sum-rate subject to a distortion constraint. To solve the problem, we extend the conventional Lagrange method and show that if the solution exists, it should consist of a zero part and a non-zero part, where the non-zero part is determined by solving a set of Euler equations. By calculating the second variation of the min-sum-rate problem, a sufficient condition is also found that can be used to determine if the necessary solution results in the minimal sum rate. The special case of two terminals is examined in detail, and it is shown that an analytical solution is possible in this case. Analysis and discussion with examples are provided to illustrate the theoretical results. The general solution obtained in this paper is shown to be compatible with the previous results for cases such as the problem of rate evaluation for sources without memory.

Arbitrary and semantic associations insubjective memory impairment and amnestic mild cognitive impairment among Taiwanese individuals: A cross-sectional study.

Researchers have recently proposed a preclinical stage of dementia of Alzheimer's type (DAT), referred to as subjective memory impairment (SMI), with the aim of developing methods for the early detection of DAT and subsequent intervention. It has been proposed that the objective memory functions of individuals with SMI are normal; however, arbitrary and semantic associations are both used to describe the processes of memory. No previous studies have investigated these processes among individuals with SMI. Cross-sectional analysis was used to compare the memory function of individuals with SMI, amnestic mild cognitive impairment (aMCI), or DAT. One hundred and eighty-three participants were recruited from the Memory Clinic of National Taiwan University Hospital and communities in northern Taiwan, including individuals with no memory complaints (HC, n=30) and individuals with SMI (n=61), aMCI-single domain (n=24), aMCI-multiple domain (n=33), or DAT (n=35). The Word Sequence Learning Test (WSLT) was used to assess the formation of arbitrary associations and the Logical Memory subtest of the Wechsler Memory Scale-Third Edition was used to assess the formation of semantic associations. Compared to the HC group, the SMI group performed poorly only on the WSLT, whereas the other groups performed poorly on both of the memory tasks. This study demonstrated that SMI individuals tend to perform poorly in the formation of arbitrary associations. Our findings suggest that tasks requiring arbitrary associations may provide greater sensitivity in the detection cognitive changes associated with preclinical DAT.

Fractional Herglotz variational principles with generalized Caputo derivatives

We obtain Euler–Lagrange equations, transversality conditions and a Noether-like theorem for Herglotz-type variational problems with Lagrangians depending on generalized fractional derivatives. As an application, we consider a damped harmonic oscillator with time-depending mass and elasticity, and arbitrary memory effects.

(Nearly) optimal P values for all Bell inequalities

AbstractA key objective in conducting a Bell test is to quantify the statistical evidence against a local-hidden variable model (LHVM) given that we can collect only a finite number of trials in any experiment. The notion of statistical evidence is thereby formulated in the framework of hypothesis testing, where the null hypothesis is that the experiment can be described by an LHVM. The statistical confidence with which the null hypothesis of an LHVM is rejected is quantified by the so-called P value, where a smaller P value implies higher confidence. Establishing good statistical evidence is especially challenging if the number of trials is small, or the Bell violation very low. Here, we derive the optimal P value for a large class of Bell inequalities. What is more, we obtain very sharp upper bounds on the P value for all Bell inequalities. These values are easily computed from the experimental data, and are valid even if we allow arbitrary memory in the devices. Our analysis is able to deal with imperfect random number generators, and event-ready schemes, even if such a scheme can create different kinds of entangled states. Finally, we review requirements for sound data collection, and a method for combining P values of independent experiments. The methods discussed here are not specific to Bell inequalities. For instance, they can also be applied to the study of certified randomness or to tests of noncontextuality.

Arbitrary Memory Improvement in Older Preschoolers Using Didactic Games

Abstract The success of a child's learning at school largely depends on his or her ability of arbitrary memorization. It is required to establish capabilities of pedagogical contribution to its improvement. The article describes successful use of didactic games for arbitrary memory improvement in older preschoolers using didactic games in the context of implementing a supplementary education program; it provides a short summary of the program and unveils the prospects of isolating children's arbitrary memory as a separate field of concern for the tutor.

Caching Placement in Stochastic Wireless Caching Helper Networks: Channel Selection Diversity via Caching

Content delivery success in wireless caching helper networks depends mainly on cache-based channel selection diversity and network interference. For given channel fading and network geometry, both channel selection diversity and network interference dynamically vary according to what and how the caching helpers cache at their finite storage space. We study probabilistic content placement (or caching placement) to desirably control cache-based channel selection diversity and network interference in a stochastic wireless caching helper network, with sophisticated considerations of wireless fading channels, interactions among multiple users such as interference and loads at caching helpers, and arbitrary memory size. Using stochastic geometry, we derive optimal caching probabilities in closed form to maximize the average success probability of content delivery and propose an efficient algorithm to find the solution in a noise-limited network. In an interference-limited network, based on a lower bound of the average success probability of content delivery, we find near-optimal caching probabilities in closed form to control the channel selection diversity and the network interference. We numerically verify that the proposed content placement is superior to other comparable content placement strategies.

Non-Markovian barotropic-type and Hall-type fluctuation relations in crossed electric and magnetic fields.

In this paper we derive the non-Markovian barotropic-type and Hall-type fluctuation relations for noninteracting charged Brownian particles embedded in a memory heat bath and under the action of crossed electric and magnetic fields. We first obtain a more general non-Markovian fluctuation relation formulated within the context of a generalized Langevin equation with arbitrary friction memory kernel and under the action of a constant magnetic field and an arbitrary time-dependent electric field. It is shown that this fluctuation relation is related to the total amount of an effective work done on the charged particle as it is driven out of equilibrium by the applied time-dependent electric field. Both non-Markovian barotropic- and Hall-type fluctuation relations are then derived when the electric field is assumed to be also a constant vector pointing along just one axis. In the Markovian limit, we show explicitly that they reduce to the same results reported in the literature.

Focus on test, measurement, and analytical equipment

Focus on test, measurement, and analytical equipment

Non-Markovian Brownian motion in a magnetic field and time-dependent force fields

Abstract This work focuses on the derivation of the velocity and phase-space generalized Fokker–Planck equations for a Brownian charged particle embedded in a memory thermal bath and under the action of force fields: a constant magnetic field and arbitrary time-dependent force fields. To achieve the aforementioned goal we use a Gaussian but non-Markovian generalized Langevin equation with an arbitrary friction memory kernel. In a similar way, the generalized diffusion equation in the zero inertia limit is also derived. Additionally we show, in the absence of the time-dependent external forces, that, if the fluctuation–dissipation relation of the second kind is valid, then the generalized Langevin dynamics associated with the charged particle reaches a stationary state in the large-time limit. The consistency of our theoretical results is also verified when they are compared with those derived in the absence of the force fields and in the Markovian case.

Dissipative dynamics at conical intersections: simulations with the hierarchy equations of motion method.

The effect of a dissipative environment on the ultrafast nonadiabatic dynamics at conical intersections is analyzed for a two-state two-mode model chosen to represent the S2(ππ*)-S1(nπ*) conical intersection in pyrazine (the system) which is bilinearly coupled to infinitely many harmonic oscillators in thermal equilibrium (the bath). The system-bath coupling is modeled by the Drude spectral function. The equation of motion for the reduced density matrix of the system is solved numerically exactly with the hierarchy equation of motion method using graphics-processor-unit (GPU) technology. The simulations are valid for arbitrary strength of the system-bath coupling and arbitrary bath memory relaxation time. The present computational studies overcome the limitations of weak system-bath coupling and short memory relaxation time inherent in previous simulations based on multi-level Redfield theory [A. Kühl and W. Domcke, J. Chem. Phys. 2002, 116, 263]. Time evolutions of electronic state populations and time-dependent reduced probability densities of the coupling and tuning modes of the conical intersection have been obtained. It is found that even weak coupling to the bath effectively suppresses the irregular fluctuations of the electronic populations of the isolated two-mode conical intersection. While the population of the upper adiabatic electronic state (S2) is very efficiently quenched by the system-bath coupling, the population of the diabatic ππ* electronic state exhibits long-lived oscillations driven by coherent motion of the tuning mode. Counterintuitively, the coupling to the bath can lead to an enhanced lifetime of the coherence of the tuning mode as a result of effective damping of the highly excited coupling mode, which reduces the strong mode-mode coupling inherent to the conical intersection. The present results extend previous studies of the dissipative dynamics at conical intersections to the nonperturbative regime of system-bath coupling. They pave the way for future first-principles simulations of femtosecond time-resolved four-wave-mixing spectra of chromophores in condensed phases which are nonperturbative in the system dynamics, the system-bath coupling as well as the field-matter coupling.

PaMeCo join: A parallel main memory compact hash join

This paper presents a memory-constrained hash join algorithm (PaMeCo Join) designed to operate with main-memory column-store database systems. Whilst RAM has become more affordable and the popularity of main-memory database systems continues to grow, we recognize that RAM is a finite resource and that database systems rarely have an excess of memory available to them. Therefore, we design PaMeCo to operate within an arbitrary memory limitation by processing the input relations by parts, and by using a compact hash table that represents the contained tuples in a compact format. Coupled with a radix-clustering system that lowers memory latencies, we find that PaMeCo can offer competitive performance levels to other contemporary hash join algorithms in an unconstrained environment, while being up to three times faster than a high-performing hash join when memory constraints are applied.

Non-Markovian work fluctuation theorem in crossed electric and magnetic fields.

The validity of the transient work fluctuation theorem for a charged Brownian harmonic oscillator embedded in a non-Markovian heat bath and under the action of crossed electric and magnetic fields is investigated. The aforementioned theorem is verified to be valid within the context of the generalized Langevin equation with an arbitrary memory kernel and arbitrary dragging in the potential minimum. The fluctuation-dissipation relation of the second kind is assumed to be valid and shows that the non-Markovian stochastic dynamics associated with the particle, in the absence of the external time-dependent electric field, reaches an equilibrium state, as is precisely demanded by such a relation. The Jarzynski equality in this problem is also analyzed.

Energy Harvesting Receivers: Packet Sampling and Decoding Policies

When receivers rely on stochastic energy harvesting, power outages will reduce the reliable communication rate. To model the receiver, we decompose the processing tasks in two parts: (1) sampling or Analog-to-Digital Conversion (ADC), which includes all RF front-end processing, and (2) decoding. This work considers a time-slotted system in which a source transmits coded packets through a time-invariant channel to a receiver with a finite battery and a decoder whose energy consumption can be adapted from slot to slot. Based on the relative energy costs of sampling and decoding and a stochastic model for the energy harvesting, we determine sampling and decoding policies that maximize the packet throughput. When the receiver is battery-constrained, we show that the throughput is maximized by a deferred decoding policy that samples packets at every opportunity but decodes backlogged packets using only excess energy that would otherwise be discarded. This result is shown to hold for Markov-modulated energy harvesting processes with arbitrary memory. In addition, when the average energy harvesting rate is not sufficient to decode all packets, a modified policy that defers decoding only when the backlog is below a threshold is shown to perform well when the threshold is carefully chosen.

Functional contributions and interactions between the human hippocampus and subregions of the striatum during arbitrary associative learning and memory.

The hippocampus and striatum are thought to have different functional roles in learning and memory. It is unknown under what experimental conditions their contributions are dissimilar or converge, and the extent to which they interact over the course of learning. In order to evaluate both the functional contributions of as well as the interactions between the human hippocampus and striatum, the present study used high-resolution functional magnetic resonance imaging (fMRI) and variations of a conditional visuomotor associative learning task that either taxed arbitrary associative learning (Experiment 1) or stimulus-response learning (Experiment 2). In the first experiment, we observed changes in activity in the hippocampus and anterior caudate that reflect differences between the two regions consistent with distinct computational principles. In the second experiment, we observed activity in the putamen that reflected content specific representations during the learning of arbitrary conditional visuomotor associations. In both experiments, the hippocampus and ventral striatum demonstrated dynamic functional coupling during the learning of new arbitrary associations, but not during retrieval of well-learned arbitrary associations using control variants of the tasks that did not preferentially tax one system versus the other. These findings suggest that both the hippocampus and subregions of the dorsal striatum contribute uniquely to the learning of arbitrary associations while the hippocampus and ventral striatum interact over the course of learning.

Competitive analysis of maintaining frequent items of a stream

We study the classic frequent items problem in data streams, but from a competitive analysis point of view. We consider the standard worst-case input model, as well as a weaker distributional adversarial setting. We are primarily interested in the single-slot memory case and for both models we give (asymptotically) tight bounds of Θ(N) and Θ(N3) respectively, achieved by very simple and natural algorithms, where N is the stream's length. We also provide lower bounds, for both models, in the more general case of arbitrary memory sizes of k≥1