Quantum algorithm for the asymmetric weight decision problem and its generalization to multiple weights

As one of the applications of Grover search, an exact quantum algorithm for the symmetric weight decision problem of a Boolean function has been proposed recently. Although the proposed method shows a quadratic speedup over the classical approach, it only applies to the symmetric case of a Boolean function whose weight is one of the pair {0 < w ₁ < w ₂ < 1, w ₁ + w ₂ = 1}. In this article, we generalize this algorithm in two ways. Firstly, we propose a quantum algorithm for the more general asymmetric case where {0 < w ₁ < w ₂ < 1}. This algorithm is exact and computationally optimal. Secondly, we build on this to exactly solve the multiple weight decision problem for a Boolean function whose weight as one of {0 < w ₁ < w ₂ < · · · < w _m  < 1}. This extended algorithm continues to show a quantum advantage over classical methods. Thirdly, we compare the proposed algorithm with the quantum counting method. For the case with two weights, the proposed algorithm shows slightly lower complexity. For the multiple weight case, the two approaches show different performance depending on the number of weights and the number of solutions. For smaller number of weights and larger number of solutions, the weight decision algorithm can show better performance than the quantum counting method. Finally, we discuss the relationship between the weight decision problem and the quantum state discrimination problem.     

Passivity-based control for a DC/DC high-gain transformerless boost converter

In this work, an adaptive passivity-based controller for a DC-DC high-gain transformerlessdouble-inductor boost converter is fully detailed. The proposed current-mode control scheme results in two feedback loops, a current controller for tracking the inductor current considering damping injection and energy shaping, and a voltage loop composed by a proportional-integral action to guarantee output voltage regulation. Furthermore, a parametric uncertainty estimator using immersion-invariance approach is designed to improve the robustness of the current loop. As a result, a multi-loop adaptive nonlinear energy-based controller, which ensures regional asymptotic stability via Lyapunov analysis is accomplished. In addition, considering practical conditions, real-time numerical simulations, using a 1 kW case-study converter, are carried out in order to assess the effectiveness of the proposed control scheme. Results for output voltage regulation, current tracking, and parametric uncertainty estimation under input voltage and load step changes are shown.     

Comparing Bar Chart Authoring with Microsoft Excel and Tangible Tiles

Providing tools that make visualization authoring accessible to visualization non‐experts is a major research challenge. Currently the most common approach to generating a visualization is to use software that quickly and automatically produces visualizations based on templates. However, it has recently been suggested that constructing a visualization with tangible tiles may be a more accessible method, especially for people without visualization expertise. There is still much to be learned about the differences between these two visualization authoring practices. To better understand how people author visualizations in these two conditions, we ran a qualitative study comparing the use of software to the use of tangible tiles, for the creation of bar charts. Close observation of authoring activities showed how each of the following varied according to the tool used: 1) sequences of action; 2) distribution of time spent on different aspects of the InfoVis pipeline; 3) pipeline task separation; and 4) freedom to manipulate visual variables. From these observations, we discuss the implications of the variations in activity sequences, noting tool design considerations and pointing to future research questions.     

Learning constraints in spreadsheets and tabular data

Spreadsheets, comma separated value files and other tabular data representations are in wide use today. However, writing, maintaining and identifying good formulas for tabular data and spreadsheets can be time-consuming and error-prone. We investigate the automatic learning of constraints (formulas and relations) in raw tabular data in an unsupervised way. We represent common spreadsheet formulas and relations through predicates and expressions whose arguments must satisfy the inherent properties of the constraint. The challenge is to automatically infer the set of constraints present in the data, without labeled examples or user feedback. We propose a two-stage generate and test method where the first stage uses constraint solving techniques to efficiently reduce the number of candidates, based on the predicate signatures. Our approach takes inspiration from inductive logic programming, constraint learning and constraint satisfaction. We show that we are able to accurately discover constraints in spreadsheets from various sources.     

Semantic Inference for Anaphora Resolution: Toward a Framework in Machine Translation

Anaphora is a discourse-level linguistic phenomenon.There is consensus that anaphora resolution shouldrely on prior sentences within the context of thediscourse. We propose to cast anaphora resolution asa semantic inference process in which a combination ofmultiple strategies, each exploiting different aspectsof linguistic knowledge, is employed to provide acoherent resolution of anaphora. A framework whichencompasses several salient linguistic parameters suchas grammatical role, proximity, repetition, sentencerecency and semantic cues is demonstrated. This workalso shows how an anaphora-resolution algorithm can beembedded within a framework which captures all theabove salient parameters, as well as remedies some ofthe inadequacies found in any monolithic resolutionsystem. A language-neutral semantic representationcharacterized by semantic cues is presented in orderto capture the distilled information after resolution.The effectiveness of the language-neutralrepresentation, both for machine translation andanaphora resolution, is demonstrated through a set ofsimulations and evaluations.     

How young children spend their time: Television and other activities.

Time-use diaries were collected over a 3-year period for 2 cohorts of 2- and 4-year-old children. TV viewing declined with age. Time spent in reading and educational activities increased with age on weekdays but declined on weekends. Time-use patterns were sex-stereotyped, and sex differences increased with age. As individuals' time in educational activities, social interaction, and video games increased, their time watching entertainment TV declined, but time spent playing covaried positively with entertainment TV. Educational TV viewing was not related to time spent in non-TV activities. Maternal education and home environment quality predicted frequent viewing of educational TV programs and infrequent viewing of entertainment TV. The results do not support a simple displacement hypothesis; the relations of TV viewing to other activities depend on the program content, the nature of the competing activity, and the environmental context. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Factor replicability and validity of the Temperament and Character Inventory in substance-dependent patients.

The factor structure and validity of the Temperament and Character Inventory (TCI; Cloninger, Svrakic Przybeck, & Wetzel, 1994) were evaluated in 357 inpatient and outpatient alcohol, cocaine, and opioid dependent individuals. A Procrustes rotation of principal components did not fully replicate the TCI's original factor structure in either this clinical sample or in a community sample of 183 individuals who did not abuse substances. These analyses suggested 4 reliable factors that were associated with conceptually related personality dimensions in predictable ways. Higher Novelty Seeking (or low constraint) and Harm Avoidance (or low vigor) were associated with several substance use and psychopathology indicators. Self-Transcendence and a factor we labeled Sociability (Reward Dependence and Cooperativeness) were related to fewer indicators. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The interactive effect of chronic exposure to noise and job complexity on changes in blood pressure and job satisfaction: A longitudinal study of industrial employees.

The hypothesis of this study was that noise exposure level and job complexity interact to affect changes in blood pressure (BP) levels and job satisfaction over 2–4 yrs of follow-up. Results showed that among workers exposed to high noise, those with complex jobs showed increases in BP that were more than double shown by those with simple jobs. Under low noise exposure, there was a small increase in BP for workers with complex jobs but about a 3-fold increase in workers with simple jobs. The prevalence of elevated BP showed a similar trend. Job satisfaction increased among workers with complex jobs but was much less in those exposed to high noise. It was concluded that exposure to occupational noise has a greater negative impact on changes in BP and job satisfaction over time among those performing complex jobs. In contrast, job complexity had a clear beneficial effect for workers exposed to low noise. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

THE EFFECT OF HEAT ON THE STRENGTH OF CALCINED KIESELGUHR-PORTLAND CEMENT MIXTURES1

The effect of heat upon the strength of this material is shown. This decreases rapidly at 100°C and remains fairly constant between 200° and 500°C. It decreases until 800° where a slight increase is shown between this and 1000°C. Above this the strength decreases.     

Coarse-Grained Debris-Flows: Hysteresis and Time-Dependent Rheology

Rheometer tests of coarse-grained debris-flow material show hysteresis of yield stress, the degree of which depends on maximum grain size, solids concentration, and normal stress. Coarse-grained debris-flow material did not exhibit well-defined flow curves based on instantaneous data; shear stresses at a given shear rate varied between ±50–100% of the mean value. Over periods of seconds to minutes this variability is accompanied by more gradual variation of shear stress at constant shear rate. The rheometry of coarse-grained debris-flows resembles that of dense suspensions in its poor precision and reproducibility of viscometric data.