Multi-dimensional Density of States by Multicanonical Monte Carlo

Multi-dimensional density of states provides a useful description of complex frustrated systems. Recent advances in Monte Carlo methods enable efficient calculation of the density of states and related quantities, which renew the interest in them. Here we calculate density of states on the plane (energy, magnetization) for an Ising Model with three-spin interactions on a random sparse network, which is a system of current interest both in physics of glassy systems and in the theory of error-correcting codes. Multicanonical Monte Carlo algorithm is successfully applied, and the shape of densities and its dependence on the degree of frustration is revealed. Efficiency of multicanonical Monte Carlo is also discussed with the shape of a projection of the distribution simulated by the algorithm.Comment: Presented at SPDSA 2004, Hayama, Japa

A computational theory of motor learning

In this paper we present a computational theory of human motor performance and learning. The theory is implemented as a running AI system called MAGGIE. Given a description of a desired movement as input, the system generates simulated motor behavior as output. The theory states that skills are encoded as motor schemas, which specify the positions and velocities of a limb at selected points in time. Moreover, there exist two natural representations for such knowledge: viewer-centered schemas describe visually perceived behavior, and joint-centered schemas are used to generate behavior. When the model acts upon these two representational formats, they exhibit quite different behavioral characteristics. MAGGIE performs the desired movement within a feedback control paradigm, monitoring for errors and correcting them when it detects them. Learning involves improving the joint-centered schema over many practice trials; this reduces the need for monitoring. The model accounts for a number of well-documented motor phenomena, including the speed-accuracy trade-off and the gradual improvement in performance with practice. It also makes several testable predictions. We close with a discussion of the theory's strengths and weaknesses, along with directions for future research

Hubungan Karakteristik Informasi Yang Dihasilkan Oleh Sistem Informasi Akuntansi Manajemen Terhadap Kinerja Manajerial Pada PT. Eurotek Jaya Perkasa Bogor

Tujuan dari penelitian ini adalah untuk mengetahui secara empiris pengaruh karakteristik informasi yang dihasilkan oleh sistem informasi akuntansi manajemen terhadap kinerja manajerial pada PT. Eurotex Jaya Perkasa. Populasi dalam penelitian ini adalah sebanyak 34 pada PT.Eurotex Jaya Perkasa. Berdasarkan metode analisis regresi berganda, diperoleh hasil pengujian secara simultan (Uji-F) dan uji secara parsial dari keempat variabel bebas (uji-t), menunjukkan terdapat hubungan sekaligus pengaruh yang signifikan ke empat variabel, yakni variabel Ruang lingkup (X1), Agregasi (X2), Integrasi (X3), dan Tepat waktu (X4) terhadap kinerja manajerial pada PT.Eurotex Jaya Perkasa. Dengan model statistiknya yakni : Y = 2.205 + 0.127X1 + 0.103X2 + 0.100X3 + 0.142X4. Variabel yang paling besar (paling dominan) adalah variabel tepat waktu, dimana pemakai informasi akuntansi lebih memfokuskan pada ketepatan waktu dari kualitas informasi yang disampaikan oleh pihak penyelenggara sistem informasi