A genetic algorithm for a bicriteria supplier selection problem

In this paper, we discuss the problem of selecting suppliers for an organisation, where a number of suppliers have made price offers for supply of items, but have limited capacity. Selecting the cheapest combination of suppliers is a straightforward matter, but purchasers often have a dual goal of lowering the number of suppliers they deal with. This second goal makes this issue a bicriteria problem – minimisation of cost and minimisation of the number of suppliers. We present a mixed integer programming (MIP) model for this scenario. Quality and delivery performance are modelled as constraints. Smaller instances of this model may be solved using an MIP solver, but large instances will require a heuristic. We present a multi-population genetic algorithm for generating Pareto-optimal solutions of the problem. The performance of this algorithm is compared against MIP solutions and Monte Carlo solutions.     

Assisting requirements analysts to find latent concerns with <Emphasis Type="Italic">REAssistant</Emphasis>

Textual requirements are very common in software projects. However, this format of requirements often keeps relevant concerns (e.g., performance, synchronization, data access, etc.) from the analyst’s view because their semantics are implicit in the text. Thus, analysts must carefully review requirements documents in order to identify key concerns and their effects. Concern mining tools based on NLP techniques can help in this activity. Nonetheless, existing tools cannot always detect all the crosscutting effects of a given concern on different requirements sections, as this detection requires a semantic analysis of the text. In this work, we describe an automated tool called REAssistant that supports the extraction of semantic information from textual use cases in order to reveal latent crosscutting concerns. To enable the analysis of use cases, we apply a tandem of advanced NLP techniques (e.g, dependency parsing, semantic role labeling, and domain actions) built on the UIMA framework, which generates different annotations for the use cases. Then, REAssistant allows analysts to query these annotations via concern-specific rules in order to identify all the effects of a given concern. The REAssistant tool has been evaluated with several case-studies, showing good results when compared to a manual identification of concerns and a third-party tool. In particular, the tool achieved a remarkable recall regarding the detection of crosscutting concern effects.     

Toward large-scale Hybrid Monte Carlo simulations of the Hubbard model on graphics processing units

One of the most efficient non-perturbative methods for the calculation of thermal properties of quantum systems is the Hybrid Monte Carlo algorithm, as evidenced by its use in large-scale lattice quantum chromodynamics calculations. The performance of this algorithm is determined by the speed at which the fermion operator is applied to a given vector, as it is the central operation in the preconditioned conjugate gradient iteration. We study a simple implementation of these operations for the fermion matrix of the Hubbard model in d+1 spacetime dimensions, and report a performance comparison between a 2.66 GHz Intel Xeon E5430 CPU and an NVIDIA Tesla C1060 GPU using double-precision arithmetic. We find speedup factors ranging between 30 and 350 for d=1, and in excess of 40 for d=3. We argue that such speedups are of considerable impact for large-scale simulational studies of quantum many-body systems.     

Using results of eye movement signal analysis in the neural network recognition of otoneurological patients

We extracted a collection of eye movement signals employed for almost two decades in clinical otoneurological tests at a balance laboratory. During those years we designed and programmed signal analysis methods to analyse their features in detail and to compute medically important attributes. In the present study, using such attributes and their results computed we classified test cases into groups of healthy subjects and patients with multilayer perceptron neural networks. Classification succeeded in total accuracies from 60% to 90% depending on the type of eye movements, which were saccades, nystagmus, sinusoidal movements and vestibulo-ocular reflex stimulated in two different ways; these are the chief eye movement tests applied in otoneurology.     

Bridging the physical and virtual worlds by local connectivity-based physical selection

The prevalent visions of ambient intelligence emphasise natural interaction between user and functions and services embedded in the environment or available through mobile devices. In these scenarios the physical and virtual worlds seamlessly gear into each other, making crossing the border between these worlds natural or even invisible to the user. The bottleneck in reaching these scenarios appear in the natural mapping between the physical objects and their virtual counterparts. The emergence of local connectivity in mobile devices opens possibilities for implementing novel user interface paradigms to enhance this mapping. We present physical selection paradigm for implementing an intuitive human technology interaction for mobile devices. In order to demonstrate the feasibility of the paradigm we implemented two experimental set-ups using commercially available smart phones with IrDA connectivity. The experiments involved selecting a website by physically pointing at its symbol and making a phone call by pointing at an icon representing the person to be called. In tentative user experiments the physical selection method was more time-efficient and it was perceived more positively by the users than a conventional method.

Cryptography Regulations for E-commerce and Digital Rights Management.

Strong encryption is an urgent need for e-commerce development, as it allows the privacy and secure transactions of the financial data. International regulations must allow the spreading of e-commerce and the associated encryption products, in order to establish a secure e-commerce environment that customers can trust and allowing an international deployment of e-commerce solutions without restrictions.     

Nuclear orientation of recoil-implanted52Mn in Au down to 3 mK

Measurements of the -ray anisotropy of recoil-implanted⁵²Mn ions in pure Au down to 3 mK indicate marked deviations from free-ion behavior in low applied fields. The effective hyperfine field that explains the anisotropy is found to decrease below 10 mK. Although this behavior could be a signature of a bound Kondon state with a lower effective hyperfine coupling constant, it is better explained as arising from a combination of Kondo and relaxation effects. The data indicate that the Mn local moment relaxation timeT ₁ is comparable to or larger than the Larmor precession time of the Mn nuclei at 3 mK. Other possible reasons for an attenuated -ray anisotropy, such as nuclear quadrupole and second-order crystal field effects, are also considered.This work was supported by the Bundesministerium für Forschung und Technologie.     

Exploring US Business Cycles with Bivariate Loops Using Penalized Spline Regression

The phrase business cycle is usually used for short term fluctuations in macroeconomic time series. In this paper we focus on the estimation of business cycles in a bivariate manner by fitting two series simultaneously. The underlying model is thereby nonparametric in that no functional form is prespecified but smoothness of the functions are assumed. The functions are then estimated using penalized spline estimation. The bivariate approach will allow to compare business cycles, check and compare phase lengths and visualize this in forms of loops in a bivariate way. Moreover, the focus is on separation of long and short phase fluctuation, where only the latter is the classical business cycle while the first is better known as Friedman or Goodwin cycle, respectively. Again, we use nonparametric models and fit the functional shape with penalized splines. For the separation of long and short phase components we employ an Akaike criterion.