Data structures for order-sensitive predicates in parallel nondeterministic systems

We study the problem of guaranteeing correct execution semantics in parallel implementations of logic programming languages in presence of built-in constructs that are sensitive to order of execution. The declarative semantics of logic programming languages permit execution of various goals in any arbitrary order (including in parallel). However, goals corresponding to extra-logical built-in constructs should respect the sequential order of execution to ensure correct semantics. Ensuring this correctness in presence of such built-in constructs, while efficiently exploiting maximum parallelism, is a difficult problem. In this paper, we propose a formalization of this problem in terms of operations on dynamic trees. This abstraction enables us to: (i) show that existing schemes to handle order-sensitive computations used in current parallel systems are sub-optimal; (ii) develop a novel, optimal scheme to handle order-sensitive goals that requires only a constant time overhead per operation. While we present our results in the context of logic programming, they will apply equally well to most parallel non-deterministic systems. Received: 20 April 1998 / 3 April 2000     

一种新型的多栅极SET/MOS管混合电路

基于多栅极SET的库仑振荡和相移特性,以及SET和MOS管的互补特性,提出了一种新型的多栅极SET/MOS管混合电路.介绍了该电路的结构和工作原理,并利用SPICE进行了仿真分析.仿真结果表明:提出的新电路可以作为取样电路使用,也可以作为一个基本的算术门用于多值逻辑电路系统.     

Fuzzy hypersemigroups

We introduce the notions of fuzzy hypersemigroup, fuzzy hypergroup, fuzzy hyperideal, homomorphism, hyper congruence, fuzzy homomorphism, fuzzy hypercongruence. The purpose of this note is the study of some characterization of fuzzy hypersemigroup, fuzzy hyperideal of a fuzzy hypersemigroup and homomorphism and hypercongruence on a hypersemigroup.     

A stable multimodel scheme control for the regulation of the transient behavior of a tunnel-diode trigger circuit

A multimodel scheme is designed for a triggering tunnel-diode circuit. The scheme improves the transient behavior during the transition time period after switching from a stable system equilibrium point to another one which is known as a triggering process. Each model is obtained by a linearization of the circuit near an equilibrium point. Moreover, each of these models can be described as a combination of two other transfer functions describing the linearized plant behavior near two different equilibrium points. The scheme chooses online the model with the best tracking performance in order to generate the control law. Different reference transfer functions are proposed with the aim of generating the desired transient in the triggering process. Some simulations show the usefulness of this scheme.     

An efficient deconvolution algorithm for estimating oxygen consumption during muscle activities

The reconstruction of an unknown input function from noisy measurements in a biological system is an ill-posed inverse problem. Any computational algorithm for its solution must use some kind of regularization technique to neutralize the disastrous effects of amplified noise components on the computed solution. In this paper, following a hierarchical Bayesian statistical inversion approach, we seek estimates for the input function and regularization parameter (hyperparameter) that maximize the posterior probability density function. We solve the maximization problem simultaneously for all unknowns, hyperparameter included, by a suitably chosen quasi-Newton method. The optimization approach is compared to the sampling-based Bayesian approach. We demonstrate the efficiency and robustness of the deconvolution algorithm by applying it to reconstructing the time courses of mitochondrial oxygen consumption during muscle state transitions (e.g., from resting state to contraction and recovery), from the simulated noisy output of oxygen concentration dynamics on the muscle surface. The model of oxygen transport and metabolism in skeletal muscle assumes an in vitro cylindrical structure of the muscle in which the oxygen from the surrounding oxygenated solution diffuses into the muscle and is then consumed by the muscle mitochondria. The algorithm can be applied to other deconvolution problems by suitably replacing the forward model of the system.     

Modeling sensorimotor learning with linear dynamical systems

Recent studies have employed simple linear dynamical systems to model trial-by-trial dynamics in various sensorimotor learning tasks. Here we explore the theoretical and practical considerations that arise when employing the general class of linear dynamical systems (LDS) as a model for sensorimotor learning. In this framework, the state of the system is a set of parameters that define the current sensorimotor transformation-the function that maps sensory inputs to motor outputs. The class of LDS models provides a first-order approximation for any Markovian (state-dependent) learning rule that specifies the changes in the sensorimotor transformation that result from sensory feedback on each movement. We show that modeling the trial-by-trial dynamics of learning provides a substantially enhanced picture of the process of adaptation compared to measurements of the steady state of adaptation derived from more traditional blocked-exposure experiments. Specifically, these models can be used to quantify sensory and performance biases, the extent to which learned changes in the sensorimotor transformation decay over time, and the portion of motor variability due to either learning or performance variability. We show that previous attempts to fit such models with linear regression have not generally yielded consistent parameter estimates. Instead, we present an expectation-maximization algorithm for fitting LDS models to experimental data and describe the difficulties inherent in estimating the parameters associated with feedback-driven learning. Finally, we demonstrate the application of these methods in a simple sensorimotor learning experiment: adaptation to shifted visual feedback during reaching.     

An Efficient Output-Size Sensitive Parallel Algorithm for Hidden-Surface Removal for Terrains

We describe an efficient parallel algorithm for hidden-surface removal for terrain maps. The algorithm runs in O(log ⁴ n) steps on the CREW PRAM model with a work bound of O((n+k) \polylog ( n)) where n and k are the input and output sizes, respectively. In order to achieve the work bound we use a number of techniques, among which our use of persistent data structures is somewhat novel in the context of parallel algorithms. Received July 29, 1998; revised October 5, 1999.     

Semiconduction properties of some polyene-iodine charge-transfer complexes and their application in solid-state batteries

The conjugated polyenes -carotene, lutein, retinoic acid and -apo-8-carotenal are shown to form charge-transfer (CT) complexes with the electron acceptor iodine. The conductivity increases by several orders of magnitude and the activation energy decreases on CT complex formation. Using these complexes as cathodic material, batteries with the configuration Mg/(polyene-iodine CT complex) /graphite are developed. Different battery parameters are evaluated. The effects of ambient temperature and humidity on battery performance are also studied. Results show that a -apo-8-carotenal-l₂ based battery has the maximum power density and longest self-life and is suitable for use as a micro-electronic gadget energizer.     

工情监视系统在防汛中的应用及维护

以河北省大清河管理处对工情监视系统的管理与维护为例,阐述了工情监控系统在防汛过程中的应用与管理过程,针对工情监控系统应用中网络、设备出现的问题,提出了检测流程和解决办法,为枢纽工程防汛、抢险救灾提供及时快捷的通信服务。     

土地处理系统流态试验及异重流的影响

在土地处理系统的反应器中进行流态试验,考察适用于土地处理系统流态试验的方法,并挑选重现性好的示踪剂.试验结果表明,土地处理系统水流流态为推流式,体积效率达到95%以上,轴向扩散属于中等分散程度,但存在一定的滞留区.采用阶跃法进行流态试验会由于异重流的影响使试验结果不能反映出反应器的真实流态：采用升流式运行,升阶法会增加平均停留时间,具有很好的推流效果和很低的扩散系数,降阶法则相反;降流式运行,降阶法增加了平均停留时间,有更大的体积效率,升阶法则降低了水流推流效果.因而阶跃法不适合土地处理系统的流态试验.脉冲法采用罗丹明B作为示踪剂的试验结果比NaCl具有更好的重现性、更加准确.