Quadratic approximate dynamic programming for input‐affine systems

We consider the use of quadratic approximate value functions for stochastic control problems with input‐affine dynamics and convex stage cost and constraints. Evaluating the approximate dynamic programming policy in such cases requires the solution of an explicit convex optimization problem, such as a quadratic program, which can be carried out efficiently. We describe a simple and general method for approximate value iteration that also relies on our ability to solve convex optimization problems, in this case, typically a semidefinite program. Although we have no theoretical guarantee on the performance attained using our method, we observe that very good performance can be obtained in practice.Copyright © 2012 John Wiley & Sons, Ltd.     

Graph attention-based collaborative filtering for user-specific recommender system using knowledge graph and deep neural networks

Knowledge and Information Systems - Collaborative filtering suffers from the issues of data sparsity and cold start. Due to which recommendation models that only rely on the user–item...     

A Demonstration of High-Throughput Electrophoresis

Automating electrophoresis significantly reduces the time required for loading a large number of samples, increases the speed of electrophoresis analysis, and maximizes the resolution power (clear separation of fragments) of this technique. In addition, automation increases the precision of electrophoresis analysis. Here we demonstrate an automated, high-throughput method of loading 96 samples simultaneously onto an electrophoresis gel, using the Apogent Discoveries Tango™ system and the Invitrogen™ E-Gel® 96 system.     

Tokamak edge plasma rotation in the presence of the biased electrode

Electrode biasing system was designed, constructed, and installed on the IR-T1 tokamak, and then biasing experiments were carried out. Also, using a Mach probes the effects of radial electric field (produced by biased electrode) on the poloidal and toroidal components of the edge plasma velocity were investigated. The results showed an increase in both toroidal and poloidal components of the edge plasma velocity during biasing regime. Results compared and discussed. During positive biasing, increased E_r tends to slow the poloidal rotation in the electron diamagnetic drift direction, i.e., to speed up rotation in the ion diamagnetic drift direction. An increased toroidal rotation velocity has the opposite effect on the poloidal rotation.     

Plasma Internal Inductance in the Presence of External Resonant Fields in IR-T1 Tokamak

In this paper we presented experimental investigation of effects of local limiter biasing (V_biasing = +200 v, V_biasing = +320 v) on the plasma parameters as plasma current, loop voltage, poloidal beta, plasma pressure, plasma energy, plasma resistance, plasma temperature, plasma displacement, Shafranov parameter and plasma internal inductance in IR-T1 tokamak. For these purposes, array of magnetic probes and also a diamagnetic loop have been used. The results show that applied biased voltage V_biasing = +200 v causes to decrease of about 40 % in plasma internal inductance. The plasma resistance and the plasma displacement have been decreased by V_biasing = +200 v. The main result of the application of V_biasing = +200 v is flatting the plasma parameters profiles. In other words, the addition of biasing voltage V_biasing = +200 v to plasma could be effective for improving the quality of tokamak plasma discharge by creating the steady state plasma. The plasma current, plasma pressure, plasma energy, plasma temperature and shift parameter have increased after the application of limiter biasing with V_biasing = +320 v but they decrease rapidly.     

Edge-Localized Modes (ELM) Modification with Transport Barrier Control in Tokamak by Analytical Strategies

High confinement mode (H-mode) in tokamaks is characterized by the formation of a transport barrier at the edge of the plasma. The H-mode increases the plasma energy confinement time by around a factor of two compared to the Low confinement mode (L-mode). This result made a great step towards achieving the higher temperatures and pressures needed to create ignition conditions. The Grad–Shafranov Equation describes the magnetic flux distribution of plasma in an axisymmetric system like a tokamak. In this paper, we have calculated the magnetic flux surfaces in IR-T1 tokamak by two methods. An analytical solution of magnetic surfaces approximated by equilibrium calculation of GS equation based on first three (and then four) terms of expansion in flux function. Results of two methods are in good agreement with each other.     

STFT Analysis of the Particle Transport on the IR-T1 Tokamak Plasma Sheath

The time-resolved frequency component analysis has been performed using short time Fourier transform. Fourier-based techniques and auto-correlation have been employed to analyze the frequency of the MHD fluctuations. The time evolution of potential fluctuation, and electric field and turbulent transport have been measured by using two arrays of the Langmuir probes in both the radial and poloidal directions. The experiments have been done in different regimes as Limiter biasing and RHF and both of them. The analyses have been done by the fast Fourier transport (FFT) method and spectral features of them are obtained with the help of the standard auto-correlation technique. The results show that radial turbulent transport decreases about 60 % after positive biasing application while it increases about 40 % after negative biasing. The effect of positive biasing on poloidal turbulent transport displays an increase of about 55 % while the negative bias voltage decreases the poloidal turbulent transport about 30 %. Consequently, confinement is improved and plasma density rises significantly due to the applied positive biasing in IR-T1. But the results are reversed when negative biasing is applied. Also, in this work, the results of applied RHF (L = 3) are compared with biasing results and analysed.     

Plasma Confinement Modification in IR-T1 Tokamak by Velocity Shear Stabilization

E × B velocity shear effects on the plasma confinement were investigated in the IR-T1 tokamak. The investigations have been done at the presence of external applied electric and Resonant Helical magnetic Fields (RHF). In this work, experimental data have been measured by using two arrays of the Langmuir probes in both the radial and poloidal directions. A velocity shear stabilization mechanism has also been proposed to be responsible for an improvement in plasma confinement. The results show that E_r × B drift velocity (V_E×B) reduces about 90 % due to applied biasing and RHF at edge plasma. We have also observed that positive biasing and RHF lead to a significant decrease (>80 %) for radial turbulent transport (Γ_E×B) at edge plasma. In this paper, the electrostatic Reynolds stress (Rs) and the shearing rate γ_E×B have been calculated. We have also compared the Rs and γ_E×B at presence of the biasing and RHF and without biasing and RHF. A good correlation between confinement modifications and E_r × B velocity shear has been found suggesting that confinement enhancement originates at the edge plasma as a consequence of the formation of a particle transport barrier just inside the limiter.     

A model for measuring e-learning systems success in universities

In the era of internet, universities and higher education institutions are increasingly tend to provide e-learning. For suitable planning and more enjoying the benefits of this educational approach, a model for measuring success of e-learning systems is essential. So in this paper, we try to survey and present a model for measuring success of e-learning systems in universities. For this purpose, at first, according to literature review, a conceptual model was designed. Then, based on opinions of 33 experts, and assessing their suggestions, research indicators were finalized. After that, to examine the relationships between components and finalize the proposed model, a case study was done in 5 universities: Amir Kabir University, Tehran University, Shahid Beheshti University, Iran University of Science & Technology and Khaje Nasir Toosi University of Technology. Finally, by analyzing questionnaires completed by 369 instructors, students and alumni, which were e-learning systems user, the final model (MELSS Model¹).