Task dynamics in self-organising task groups: expertise, motivational, and performance differences of specialists and generalists

Multi-agent simulation is applied to explore how different types of task variety cause workgroups to change their task allocation accordingly. We studied two groups, generalists and specialists. We hypothesised that the performance of the specialists would decrease when task variety increases. The generalists, on the other hand, would perform better in a high task variety condition. The results show that these hypotheses were only partly supported because both learning and motivational effects changed the task allocation process in a much more complex way. We conclude that although no task variety leads to specialisation and high task variety leads to generalisation, in general, performance is better when task variety is low. Further, in case of no task variety, specialists outperform generalists. In case of moderate variety the opposite is true. With high task variety, since there is no space for any expertise and motivational development, the behaviour of specialists and generalists becomes more similar, and, consequently also their performance.     

Grammar Engineering Support for Precedence Rule Recovery and Compatibility Checking

A wide range of parser generators are used to generate parsers for programming languages. The grammar formalisms that come with parser generators provide different approaches for defining operator precedence. Some generators (e.g. YACC) support precedence declarations, others require the grammar to be unambiguous, thus encoding the precedence rules. Even if the grammar formalism provides precedence rules, a particular grammar might not use it. The result is grammar variants implementing the same language. For the C language, the GNU Compiler uses YACC with precedence rules, the C-Transformers uses SDF without priorities, while the SDF library does use priorities. For PHP, Zend uses YACC with precedence rules, whereas PHP-front uses SDF with priority and associativity declarations.The variance between grammars raises the question if the precedence rules of one grammar are compatible with those of another. This is usually not obvious, since some languages have complex precedence rules. Also, for some parser generators the semantics of precedence rules is defined operationally, which makes it hard to reason about their effect on the defined language. We present a method and tool for comparing the precedence rules of different grammars and parser generators. Although it is undecidable whether two grammars define the same language, this tool provides support for comparing and recovering precedence rules, which is especially useful for reliable migration of a grammar from one grammar formalism to another. We evaluate our method by the application to non-trivial mainstream programming languages, such as PHP and C.     

Behavioral detection of malware: from a survey towards an established taxonomy

Behavioral detection differs from appearance detection in that it identifies the actions performed by the malware rather than syntactic markers. Identifying these malicious actions and interpreting their final purpose is a complex reasoning process. This paper draws up a survey of the different reasoning techniques deployed among the behavioral detectors. These detectors have been classified according to a new taxonomy introduced inside the paper. Strongly inspired from the domain of program testing, this taxonomy divides the behavioral detectors into two main families: simulation-based and formal detectors. Inside these families, ramifications are then derived according to the data collection mechanisms the data interpretation, the adopted model and its generation, and the decision support.     

Ground state of the time-independent Gross-Pitaevskii equation

We present a suite of programs to determine the ground state of the time-independent Gross-Pitaevskii equation, used in the simulation of Bose-Einstein condensates. The calculation is based on the Optimal Damping Algorithm, ensuring a fast convergence to the true ground state. Versions are given for the one-, two-, and three-dimensional equation, using either a spectral method, well suited for harmonic trapping potentials, or a spatial grid.

Program summary

Program title: GPODACatalogue identifier: ADZN_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZN_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 5339No. of bytes in distributed program, including test data, etc.: 19 426Distribution format: tar.gzProgramming language: Fortran 90Computer: ANY (Compilers under which the program has been tested: Absoft Pro Fortran, The Portland Group Fortran 90/95 compiler, Intel Fortran Compiler)RAM: From <1 MB in 1D to ∼¹⁰² MB for a large 3D gridClassification: 2.7, 4.9External routines: LAPACK, BLAS, DFFTPACKNature of problem: The order parameter (or wave function) of a Bose-Einstein condensate (BEC) is obtained, in a mean field approximation, by the Gross-Pitaevskii equation (GPE) [F. Dalfovo, S. Giorgini, L.P. Pitaevskii, S. Stringari, Rev. Mod. Phys. 71 (1999) 463]. The GPE is a nonlinear Schrödinger-like equation, including here a confining potential. The stationary state of a BEC is obtained by finding the ground state of the time-independent GPE, i.e., the order parameter that minimizes the energy. In addition to the standard three-dimensional GPE, tight traps can lead to effective two- or even one-dimensional BECs, so the 2D and 1D GPEs are also considered.Solution method: The ground state of the time-independent of the GPE is calculated using the Optimal Damping Algorithm [E. Cancès, C. Le Bris, Int. J. Quantum Chem. 79 (2000) 82]. Two sets of programs are given, using either a spectral representation of the order parameter [C.M. Dion, E. Cancès, Phys. Rev. E 67 (2003) 046706], suitable for a (quasi) harmonic trapping potential, or by discretizing the order parameter on a spatial grid.Running time: From seconds in 1D to a few hours for large 3D grids     

Survival as a Digital Ghost

You can survive after death in various kinds of artifacts. You can survive in diaries, photographs, sound recordings, and movies. But these artifacts record only superficial features of yourself. We are already close to the construction of programs that partially and approximately replicate entire human lives (by storing their memories and duplicating their personalities). A digital ghost is an artificially intelligent program that knows all about your life. It is an animated auto-biography. It replicates your patterns of belief and desire. You can survive after death in a digital ghost. We discuss a series of digital ghosts over the next 50 years. As time goes by and technology advances, they are progressively more perfect replicas of the lives of their original authors.

Low-cost telepresence for collaborative virtual environments

We present a novel low-cost method for visual communication and telepresence in a CAVEtrade-like environment, relying on 2D stereo-based video avatars. The system combines a selection of proven efficient algorithms and approximations in a unique way, resulting in a convincing stereoscopic real-time representation of a remote user acquired in a spatially immersive display. The system was designed to extend existing projection systems with acquisition capabilities requiring minimal hardware modifications and cost. The system uses infrared-based image segmentation to enable concurrent acquisition and projection in an immersive environment without a static background. The system consists of two color cameras and two additional b/w cameras used for segmentation in the near-IR spectrum. There is no need for special optics as the mask and color image are merged using image-warping based on a depth estimation. The resulting stereo image stream is compressed, streamed across a network, and displayed as a frame-sequential stereo texture on a billboard in the remote virtual environment     

Screening of serum samples from Wegener's granulomatosis patients using antibody microarrays

Wegener's Granulomatosis (WG) is an idiopathic granulomatosis autoimmune vasculitis that primarily affects small vessels and is associated with glomerulonephritis and pulmonary granulomatous vasculitis. Anti‐neutrophil cytoplasmic auto‐antibodies (cANCA) against proteinase‐3 are used to identify WG, but ANCA titers are not present in some patients with the localized disease. The objective of this study was to develop an antibody array to help identify protein expression patterns in serum from patients with WG as compared to normals. The arrays were tested for limits of detection, background, and cross reactivity using standard proteins. The arrays were hybridized with either normal patient serum (n = 30) or with serum samples from a population of WG patients (n = 26) that were age and sex matched. Data analysis and curve fitting of the standard dilution series calculated r² values and determined a sensitivity of <50 pg/mL for the majority of proteins. A total of 24 proteins were assessed. Several statistically significant increases (p<0.05) were seen in the expression of: angiotensin converting enzyme‐I, IFN‐γ, IL‐8, s‐ICAM‐1 and s‐VCAM in WG patients as compared to controls. Utilizing the antibody microarray technology has led to the identification of potential biomarkers of vascular injury in the serum of WG patients.     

Identification of statistical patterns in complex systems via symbolic time series analysis

Identification of statistical patterns from observed time series of spatially distributed sensor data is critical for performance monitoring and decision making in human-engineered complex systems, such as electric power generation, petrochemical, and networked transportation. This paper presents an information-theoretic approach to identification of statistical patterns in such systems, where the main objective is to enhance structural integrity and operation reliability. The core concept of pattern identification is built upon the principles of Symbolic Dynamics, Automata Theory, and Information Theory. To this end, a symbolic time series analysis method has been formulated and experimentally validated on a special-purpose test apparatus that is designed for data acquisition and real-time analysis of fatigue damage in polycrystalline alloys.