The Frequent Items Problem in Online Streaming under Various Performance Measures

In this paper, we strengthen the competitive analysis results obtained for a fundamental online streaming problem, the Frequent Items Problem. Additionally, we contribute with a more detailed analysis of this problem, using alternative performance measures, supplementing the insight gained from competitive analysis. The results also contribute to the general study of performance measures for online algorithms. It has long been known that competitive analysis suffers from drawbacks in certain situations, and many alternative measures have been proposed. However, more systematic comparative studies of performance measures have been initiated recently, and we continue this work, using competitive analysis, relative interval analysis, and relative worst order analysis on the Frequent Items Problem.Comment: IMADA-preprint-c

First-principles Calculation of the Formation Energy in MgO-CaO Solid Solutions

The electronic structure and total energy were calculated for ordered and disordered MgO-CaO solid solutions within the multiple scattering theory in real space and the local density approximation. Based on the dependence of the total energy on the unit cell volume the equilibrium lattice parameter and formation energy were determined for different solution compositions. The formation energy of the solid solutions is found to be positive that is in agreement with the experimental phase diagram, which shows a miscibility gap.Comment: 11 pages, 3 figure

Strength and endurance training reduces the loss of eccentric hamstring torque observed after soccer specific fatigue

Objectives: To investigate the effect of two hamstring training protocols on eccentric peak torque before and after soccer specific fatigue. Participants: Twenty-two university male soccer players. Design: Isokinetic strength tests were performed at 60°/s pre and post fatigue, before and after 2 different training interventions. A 45-minute soccer specific fatigue modified BEAST protocol (M-BEAST) was used to induce fatigue. Players were randomly assigned to a 4 week hamstrings conditioning intervention with either a maximum strength (STR) or a muscle endurance (END) emphasis. Main outcome measures: The following parameters were evaluated:– Eccentric peak torque (EccPT), angle of peak torque (APT), and angle specific torques at knee joint angles of 10°, 20°, 30°, 40°, 50°, 60°, 70°, 80° and 90°. Results: There was a significant effect of the M-BEAST on the Eccentric torque angle profile before training as well as significant improvements in post-fatigue torque angle profile following the effects of both strength and muscle endurance interventions. Conclusions: Forty-five minutes of simulated soccer activity leads to reduced eccentric hamstring torque at longer muscle lengths. Short-term conditioning programs (4-weeks) with either a maximum strength or a muscular endurance emphasis can equally reduce fatigue induced loss of strength over this time period

Non-Markovian control of qubit thermodynamics by frequent quantum measurements

We explore the effects of frequent, impulsive quantum nondemolition measurements of the energy of two-level systems (TLS), alias qubits, in contact with a thermal bath. The resulting entropy and temperature of both the system and the bath are found to be completely determined by the measurement rate, and unrelated to what is expected by standard thermodynamical rules that hold for Markovian baths. These anomalies allow for very fast control of heating, cooling and state-purification (entropy reduction) of qubits, much sooner than their thermal equilibration time.Comment: 8 pages, 9 figure

Equilibrium and nonequilibrium fluctuations at the interface between two fluid phases

We have performed small-angle light-scattering measurements of the static structure factor of a critical binary mixture undergoing diffusive partial remixing. An uncommon scattering geometry integrates the structure factor over the sample thickness, allowing different regions of the concentration profile to be probed simultaneously. Our experiment shows the existence of interface capillary waves throughout the macroscopic evolution to an equilibrium interface, and allows to derive the time evolution of surface tension. Interfacial properties are shown to attain their equilibrium values quickly compared to the system's macroscopic equilibration time.Comment: 10 pages, 5 figures, submitted to PR

Mechanical versus thermodynamical melting in pressure-induced amorphization: the role of defects

We study numerically an atomistic model which is shown to exhibit a one--step crystal--to--amorphous transition upon decompression. The amorphous phase cannot be distinguished from the one obtained by quenching from the melt. For a perfectly crystalline starting sample, the transition occurs at a pressure at which a shear phonon mode destabilizes, and triggers a cascade process leading to the amorphous state. When defects are present, the nucleation barrier is greatly reduced and the transformation occurs very close to the extrapolation of the melting line to low temperatures. In this last case, the transition is not anticipated by the softening of any phonon mode. Our observations reconcile different claims in the literature about the underlying mechanism of pressure amorphization.Comment: 7 pages, 7 figure

Machine Learning in Automated Text Categorization

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey

Epistemic and social scripts in computer-supported collaborative learning

Collaborative learning in computer-supported learning environments typically means that learners work on tasks together, discussing their individual perspectives via text-based media or videoconferencing, and consequently acquire knowledge. Collaborative learning, however, is often sub-optimal with respect to how learners work on the concepts that are supposed to be learned and how learners interact with each other. One possibility to improve collaborative learning environments is to conceptualize epistemic scripts, which specify how learners work on a given task, and social scripts, which structure how learners interact with each other. In this contribution, two studies will be reported that investigated the effects of epistemic and social scripts in a text-based computer-supported learning environment and in a videoconferencing learning environment in order to foster the individual acquisition of knowledge. In each study the factors ‘epistemic script’ and ‘social script’ have been independently varied in a 2×2-factorial design. 182 university students of Educational Science participated in these two studies. Results of both studies show that social scripts can be substantially beneficial with respect to the individual acquisition of knowledge, whereas epistemic scripts apparently do not to lead to the expected effects

Dynamics of barrier penetration in thermal medium: exact result for inverted harmonic oscillator

Time evolution of quantum tunneling is studied when the tunneling system is immersed in thermal medium. We analyze in detail the behavior of the system after integrating out the environment. Exact result for the inverted harmonic oscillator of the tunneling potential is derived and the barrier penetration factor is explicitly worked out as a function of time. Quantum mechanical formula without environment is modifed both by the potential renormalization effect and by a dynamical factor which may appreciably differ from the previously obtained one in the time range of 1/(curvature at the top of potential barrier).Comment: 30 pages, LATEX file with 11 PS figure

Classification of protein interaction sentences via gaussian processes

The increase in the availability of protein interaction studies in textual format coupled with the demand for easier access to the key results has lead to a need for text mining solutions. In the text processing pipeline, classification is a key step for extraction of small sections of relevant text. Consequently, for the task of locating protein-protein interaction sentences, we examine the use of a classifier which has rarely been applied to text, the Gaussian processes (GPs). GPs are a non-parametric probabilistic analogue to the more popular support vector machines (SVMs). We find that GPs outperform the SVM and na\"ive Bayes classifiers on binary sentence data, whilst showing equivalent performance on abstract and multiclass sentence corpora. In addition, the lack of the margin parameter, which requires costly tuning, along with the principled multiclass extensions enabled by the probabilistic framework make GPs an appealing alternative worth of further adoption