The impact of distributed practice schedules within a classwide computation intervention: A randomized control trial.

This research presents a methodology to evaluate data path topologies that implement a conditional statement for an average-case performance that is better than the worst-case performance. A conditional statement executes one of many alternatives depending on how Boolean conditions evaluate to true or false. Alternatives with simple computations take less time to execute. The self-timed designs can exploit the faster executing alternatives and provide an average-case behavior, where the average depends on the frequency of simple and complex computations, and the difference in the completion times of simple and complex computations. The frequency of simple and complex computations depends on a given workload. The difference in the completion times of a simple and complex computations depend on the choice of a data path topology. Conventional wisdom suggests that a fully-speculative data path, independent of the design style, yields the best performance. A fully-speculative data path executes all the choices or alternatives in a conditional statement in parallel and then chooses the correct result. Using a division algorithm as an example of an instruction that embodies a conditional statement, the proposed methodology shows that a fully-speculative design is suitable for a synchronous design but a less-speculative design is suitable for a self-timed design. Consequently, the results from the SPICE simulation of the extracted netlists show that on average, the self-timed divider is approximately 10% faster, consumes 42% less energy per division and 20% less area than the synchronous divider. In addition to the evaluation methodology, this research also presents the derivation of four new radix-2 division algorithms that offer a simpler quotient selection logic compared to the existing radix-2 division algorithms. A circuit optimization technique called Glissando is presented in this research. Glissando exploits a simple idea that the non-critical bits can arrive late at the input of the registers to reduce the delay of the data paths. The effect of the variations in manufacturing on the functionality of the divider designs is also analyzed in this research.

The data cube and iceberg cube computation problem has been studied by many researchers. There are three major approaches developed in this direction: (1) top-down computation, represented by MultiWay array aggregation (Zhao et. al., 1997) which utilizes shared computation and performs well on dense data sets; (2) bottom-up computation, represented by BUC (Beyer and Ramakrishnan, 1999), which takes advantage of Apriori Pruning and performs well on sparse data sets; and (3) integrated top-down and bottom-up computation, represented by Star-Cubing (Xin, et. al., 2003), which takes advantages of both and has high performance in most cases. However; the performance of Star-Cubing degrades in very sparse data sets due to the additional cost introduced by the tree structure. None of the three approaches achieves uniformly high performance on all kinds of data sets. In this paper; we present a new approach that compute Iceberg Cubes by factorizing the lattice space according to the frequency of values. This approach, different from all the previous dimension-based approaches where the importance of data distribution is not recognized, partitions the cube lattice into one dense subspace and several sparse subspaces. With this approach, a new method called MM-Cubing has been developed. MM-Cubing is highly adaptive to dense, sparse or skewed data sets. Our performance study shows that MM-Cubing is efficient and achieves high performance over all kinds of data distributions.

Behavior modification and medication have been proven to be the most effective interventions for children with ADHD. For these treatments to be effective, utilization of mental health care services as well as compliance with treatment recommendations is necessary. There has been shown lower care utilization among minorities for the treatment of behavioral disorders. In addition, lack of adherence among these populations to ADHD treatment is not explained by SES, parenting stress, or family coping. An alternative explanation may be parental knowledge of ADHD and opinions of commonly used treatments. The present investigation examined the effect of a brief knowledge intervention aimed at increasing knowledge of ADHD on treatment acceptability of commonly utilized treatments for ADHD in a low SES, minority population seeking initial services at a multidisciplinary behavior clinic for ADHD. Participants included 48 female guardians. They completed a demographic questionnaire, the Conners' Parent Rating Scale-Revised: Long Form (CPRS-R:L), six Treatment Evaluation Inventory - Short Forms (TEI-SF), and an Attention-Deficit/Hyperactivity Disorder Knowledge Survey (AKOS-R). Upon their next visit to the clinic, participants were randomly assigned to one of two groups. One group received an educational video intervention while the other group watched a control video. Following the videos, all participants again completed six TEI-SF's and the AKOS-R. Results revealed that parent ratings of their child's behavior did not correlate with treatment acceptability ratings. Baseline knowledge was low and increased significantly for the experimental group when compared to the control group demonstrating good treatment integrity, F (1, 45) = 29.37, p = .01. A significant negative correlation was identified between changes in knowledge as assessed by the AKOS-R and the changes in the TEI-SF diet intervention (r = -.43, p = .01, r2 = .19). Change in knowledge accounted for 18% of the change in treatment acceptability of the diet intervention (R2 = .18). Changes in knowledge scores did not otherwise relate to changes in treatment acceptability ratings. Overall, it appears that adding a parental educational component to the treatment of children with ADHD will not lead to increased acceptability of empirically supported treatments with this population.

In this paper, a multi-body system dynamics problem is considered as a complex system modeling and computation problem. A parallel programming model and its execution environment are designed to reduce model complexity and to improve computational speed. In this architecture, the problem is divided into two levels: 1. Find a parallel mathematical algorithm to describe the behavior of this multi-body system. 2. Build a unified programming language that could leverage many different pieces of computational resources, such as symbolic computing, and numerical libraries. To tackle the first level, Space-Time Finite Element Method (FEM) is applied. The Space-Time FEM formats of Newton-Euler formula is given, as well as its constraint formula. This algorithm has avoided the loop operation during the time field solving. To tackle the second level, a network-based functional programming language - Object Computing Network (OCN) is designed. OCN is inspired by Object-Process Methodology (OPM). In OCN, every computation behavior is treated as a function, which is constructed by a three element set: {Var, Rule. Condition}. Three basic patterns - Branching, Synchronizing, Merging are given in OCN to prove the flexibility of OCN. An communication interface is designed in OCN to connect different programming languages together. Two multi-body system dynamics computing models - Semi-discretization method and Space-Time discretization method - are constructed with OCN, and a significant contrast in task parallelization is shown by different OCN models.

To achieve low latency, existing radix-4 scalable architectures for word-based Montgomery modular multiplication usually suffer from high design and hardware complexities. This brief presents a simple compression scheme and circuit to remove the data dependence in the accumulation process and accomplish one-cycle latency without quotient pipeline. The complex computation and encoding of quotient digits are thus avoided, leading to up to 10.6% and 17.7% reductions in area and power than previous work while maintaining very high performance. Consequently, the proposed radix-4 scalable architecture appears to be very suited for low-complexity and low-power cryptographic applications.

Designers need a way to overcome information related risks, including information leakage and misuse from their own collaborators during a collaborative product realization process. Existing cryptographic techniques aimed at overcoming these information related risks are computationally expensive and slow even for moderate problem sizes, and legal approaches (e.g., the use of non-disclosure agreements) are not effective. The computational practicality problem is particularly pronounced for simulation computations like finite element analysis (FEA), that involve both a geometric partitioning (meshing) and computations of cubic time complexity. In this paper, we propose a technological approach that enables designers to perform simulations, such as FEA computations, without the need for revealing their information to anyone, including their design collaborators. We demonstrate our approach using secure finite element analysis (sFEA) which enables designers to perform FEA without having to reveal structural/material information to their counterparts even though the computed answer depends on all the collaborators’ confidential information. We build sFEA using computationally efficient protocols implementing a secure co-design framework. One of our findings is that the most natural implementations of sFEA, using existing protocols, suffer from limited scalability. To overcome these limitations, we propose strategies that help improve the scalability of sFEA. We document and discuss the experiments we conducted to determine the computational overhead imposed by sFEA. The results indicate that the computational burden imposed by sFEA makes it challenging for large-scale FEA — our scheme significantly increases the problem sizes that can be handled when compared to implementations using previous algorithms and protocols, but large enough problem sizes will swamp our scheme as well (in some sense this is unavoidable because of the cubic nature of the FEA time complexity). This work is another step towards opening up new avenues for improving the way information is exchanged in collaborative simulation computations such as FEA.

A center-of-concentrated-based prediction interval for wind power forecasting

The commercialization of transistors capable of both switching and amplification in 1960 resulted in the development of second-generation computers, which resulted in the miniaturization and lightening while accelerating the reduction and development of production costs. However, the self-resistance and the resistance used in conjunction with semiconductors, which are the basic principles of computers, generate a lot of heat, which results in semiconductor obsolescence, and limits the computation speed (clock rate). In implementing logic operation, this paper proposes the concept of Structure-based Computer which can implement NOT gate made of semiconductor transistor only by Structure-based twist of cable without resistance. In Structure-based computer, the theory of 'inverse signal pair' of digital signals was introduced so that it could operate in a different way than semiconductor-based transistors. In this paper, we propose a new hardware called Structure-based computer that can solve various problems in semiconductor computers only with the wiring structure of the conductor itself, not with the silicon-based semiconductor. Furthermore, we propose a deep-priority exploration-based simulation method that can easily implement and test complex Structure-based computer circuits. Furthermore, this paper suggests a mechanism to implement optical computers currently under development and research based on structures rather than devices.

This paper presents an efficient method for estimating capacity-fade uncertainty in lithium-ion batteries (LIBs) in order to integrate them into the battery-management system (BMS) of electric vehicles, which requires simple and inexpensive computation for successful application. The study uses the pseudo-two-dimensional (P2D) electrochemical model, which simulates the battery state by solving a system of coupled nonlinear partial differential equations (PDEs). The model parameters that are responsible for electrode degradation are identified and estimated, based on battery data obtained from the charge cycles. The Bayesian approach, with parameters estimated by probability distributions, is employed to account for uncertainties arising in the model and battery data. The Markov Chain Monte Carlo (MCMC) technique is used to draw samples from the distributions. The complex computations that solve a PDE system for each sample are avoided by employing a polynomial-based metamodel. As a result, the computational cost is reduced from 5.5 h to a few seconds, enabling the integration of the method into the vehicle BMS. Using this approach, the conservative bound of capacity fade can be determined for the vehicle in service, which represents the safety margin reflecting the uncertainty.

The early theoretical models of practical machine scheduling and sequencing problems and their mathematical analysis were motivated mostly by problems arising in manufacturing and service industries. Later models have also been influenced by new developments in flexible manufacturing, computer systems and communication systems. Analogous problems arise, however, almost everywhere, and the number of various problem types is practically unlimited. Nevertheless, the resulting mathematical and computational problems often have the form of the following optimization problem: Given a finite number of jobs to be processed on a finite number of machines, find a feasible schedule that minimizes the value of a given objective function.

We present a novel 4096 complex-point, fully systolic VLSI FFT architecture based on the combination of three consecutive radix-4 stages resulting in a 64-point FFT engine. The outcome of cascading these 64-point FFT engines is an improved architecture that efficiently processes large input data sets in real time. Using 64-point FFT engines reduces the buffering and the latency to one third of a fully unfolded radix-4 architecture, while the radix-4 schema simplifies the calculations within each engine. The proposed 4096 complex point architecture has been implemented on a FPGA achieving a post-route clock frequency of 200 MHz resulting in a sustained throughput of 4096 point/20.48 μs. It has also been implemented on a high performance 0.13 μm, 1P8M CMOS process achieving a worst-case (0.9 V, 125 C) post-route clock frequency of 604.5 MHz and a sustained throughput of 4096 point/3.89 μs while consuming 4.4 W. The architecture is extended to accomplish FFT computations of 16K, 64K and 256K complex points with 352, 256 and 188 MHz operating frequencies respectively.

Enhancing cognitive and emotional well-being in older adults through aerobic, strength, or balance training: insights from a randomized controlled trial.

In this paper, a new technique which employs random wobble on the method of exact Doppler spread (MEDS) for the design of high performance Rayleigh fading channel simulators was proposed. The new method could be used on any deterministic parameter computation method in theory, such as the method of equal areas (MEA), the method of equal distance (MED) and the LP norm method (LPNM), etc, and if the random wobble amplitude is set to be an infinitesimal real value, the autocorrelation (ACF) of inphase (quadrature) components will converge to the ones of reference model exactly. Due to the ACF arithmetic errors of the inphase and quadrature components compensate each other over a determined domain; The ACF of complex waveform matches the desired ones perfectly even if the number of sinusoids is a single-digit integer. Simulation results show that the proposed method is useful for the design of simulation models for diversity-combined fading channels, frequency-selective channels, and multiple-input multiple-output (MIMO) channels; moreover, it has many kinds of realization and can be directly used to simulating multiple uncorrelated Rayleigh fading waveforms with low model complexity and low computation costs.

An adolescent with severe mental retardation and fragile X syndrome who displayed destructive behavior maintained by positive reinforcement in the form of adult compliance with mands was assessed and treated in an outpatient setting. A levels system treatment was assessed, consisting of a continuum of attention and reinforcement ranging from access to the functional reinforcer in level 3 contingent upon appropriate behavior to a 10 min room time‐out for level 1 contingent upon aggressive and dangerous behavior. While the efficacy of this treatment has been demonstrated in an inpatient setting (Hagopian et al., 2002), this application extended the findings to outpatient and community settings. The levels system treatment resulted in a 98.1% reduction in destructive behavior from baseline levels. Treatment was successfully transferred to the home and school and reductions were maintained at 6 and 9 months. Treatment acceptability ratings were high across both home and school staff. Copyright © 2003 John Wiley & Sons, Ltd.

Web-based intervention for adolescent nonsmokers to help parents stop smoking: A pilot feasibility study