On Dynamic Compromise

What prevents majorities from extracting surplus from minorities in a dynamic legislative process? In this paper we study an infinitely repeated game where legislators determine the division of a surplus each period. A division proposal is made at the beginning of the period by a randomly selected legislator and is then voted on. Proposals that are accepted by a simple majority are implemented, otherwise the status quo allocation prevails. We show existence of a symmetric Markov perfect equilibrium in which more than a minimum winning majority receive a positive allocation for an intermediate range of discount factors. However, the equilibrium outcome is sensitive to initial conditions: compromise is achieved when initial allocations are well distributed, otherwise the equilibrium spirals towards a complete absence of compromise. We find that, contrary to intuition, compromise becomes easier to sustain as the number of legislators increases. Classification-JEL Codes: C73, D74

The Effect of wake Turbulence Intensity on Transition in a Compressor Cascade

Direct numerical simulations of separating flow along a section at midspan of a low-pressure V103 compressor cascade with periodically incoming wakes were performed. By varying the strength of the wake, its influence on both boundary layer separation and bypass transition were examined. Due to the presence of small-scale three-dimensional fluctuations in the wakes, the flow along the pressure surface undergoes bypass transition. Only in the weak-wake case, the boundary layer reaches a nearly-separated state between impinging wakes. In all simulations, the flow along the suction surface was found to separate. In the simulation with the strong wakes, separation is intermittently suppressed as the periodically passing wakes managed to trigger turbulent spots upstream of the location of separation. As these turbulent spots convect downstream, they locally suppress separation. © 2014 Springer Science+Business Media Dordrecht

High performance subgraph mining in molecular compounds

Structured data represented in the form of graphs arises in several fields of the science and the growing amount of available data makes distributed graph mining techniques particularly relevant. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. The problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiver-initiated, load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening dataset, where the approach attains close-to linear speedup in a network of workstations

Constraint-based sequence mining using constraint programming

The goal of constraint-based sequence mining is to find sequences of symbols that are included in a large number of input sequences and that satisfy some constraints specified by the user. Many constraints have been proposed in the literature, but a general framework is still missing. We investigate the use of constraint programming as general framework for this task. We first identify four categories of constraints that are applicable to sequence mining. We then propose two constraint programming formulations. The first formulation introduces a new global constraint called exists-embedding. This formulation is the most efficient but does not support one type of constraint. To support such constraints, we develop a second formulation that is more general but incurs more overhead. Both formulations can use the projected database technique used in specialised algorithms. Experiments demonstrate the flexibility towards constraint-based settings and compare the approach to existing methods.Comment: In Integration of AI and OR Techniques in Constraint Programming (CPAIOR), 201

Pembentukan Karakter Siswa Melalui Penerapan Pendekatan Scientific

Penelitian ini bertujuan untuk menganalisis apakah penerapan pendekatan Scientific dapat membentuk karakter siswa. Karena rendahnya karakter bangsa serta menurunnya kualitas moral dalam kehidupan manusia terutama di kalangan siswa disebabkan kurangnya pendidikan karakter yang ditanamkan semenjak masih sekolah. Penelitian ini menggunakan penelitian deskriptif kuantitatif. Penelitian ini dilaksanakan di SMK Negeri 1 Langsa di kelas X-Akuntasi-1. Dalam penelitian ini data diperoleh dari lembar angket yang diisi oleh 23 responden, 30 butir daftar pernyataan tertutup yang dibuat berdasarkan aspek nilai-nilai karakter yang telah ditentukan. Data dianalisis dengan langah-langkah: pengeditian (editing), skoring, tabulasi dengan cara menghitung mean dan standar deviasi, kategorisasi dengan tiga kategori yaitu: (baik,cukup,kurang), dan analisis persentase. Berdasarkan hasil persentase lembar angket karakter siswa kelas X-Akuntansi-1 temasuk kategori “baik” dengan persentase 60,86%, artinya melalui lembar angket, telah terlihat siswa memiliki karakter yang baik dan mampu sesuai dengan aspek karakter yang diamati. Dengan demikian, berdasarkan hasil persentase lembar observasi dan angket karakter siswa di kelas X-Akuntansi-1 diperoleh lebih dari 60%. Jadi dapat disimpulkan bahwa dengan menerapkan pendekatan scientific pada materi statistika dapat membentuk karakter siswa

Prefix-Projection Global Constraint for Sequential Pattern Mining

Sequential pattern mining under constraints is a challenging data mining task. Many efficient ad hoc methods have been developed for mining sequential patterns, but they are all suffering from a lack of genericity. Recent works have investigated Constraint Programming (CP) methods, but they are not still effective because of their encoding. In this paper, we propose a global constraint based on the projected databases principle which remedies to this drawback. Experiments show that our approach clearly outperforms CP approaches and competes well with ad hoc methods on large datasets

Transition induced by linear and nonlinear perturbation growth in flow past a compressor blade

Flow past a NACA 65 blade at chord-based Reynolds number 138;500 is studied using stability analysis, generalised (spatially weighted) transient growth analysis and direct numerical simulations (DNS). The mechanisms of transition on various sections of the blade observed in previous work (Zaki et al. 2010) are examined, with a focus on the pressure side around the leading edge. In this region, the linearly most energetic perturbation has spanwise wavenumber 40π (five boundary layer thicknesses) and is tilted against the mean shear to take advantage of the Orr mechanism. In a DNS, the nonlinear development of this optimal perturbation induces ˄ structures, which are further stretched to hairpin vortices before breaking down to turbulence. At higher spanwise wavenumber, e.g. 120π, a free-stream optimal perturbation is obtained upstream of the leading edge, in the form of streamwise vortices. During its nonlinear evolution, this optimal perturbation tilts the mean shear and generates spanwise periodic high and low-speed streaks. Then through a nonlinear lift-up mechanism, the low-speed streaks are lifted above the high speed ones. This layout of streaks generates a mean shear with two in inflectional points, and activates secondary instabilities, namely inner and outer instabilities previously reported in the literature

Entropy and fluctuation relations in isotropic turbulence

Based on a generalized local Kolmogorov-Hill equation expressing the evolution of kinetic energy integrated over spheres of size $\ell$ in the inertial range of fluid turbulence, we examine a possible definition of entropy and entropy generation for turbulence. Its measurement from direct numerical simulations in isotropic turbulence leads to confirmation of the validity of the fluctuation relation (FR) from non-equilibrium thermodynamics in the inertial range of turbulent flows. Specifically, the ratio of probability densities of forward and inverse cascade at scale $\ell$ is shown to follow exponential behavior with the entropy generation rate if the latter is defined by including an appropriately defined notion of ``temperature of turbulence'' proportional to the kinetic energy at scale $\ell$