Decision making in dynamic stochastic Cournot games

In this paper, the Cournot competition is modeled as a stochastic dynamic game. In the proposed model, a stochastic market price function and stochastic dynamic decision functions of the rivals are considered. Since the optimal decision of a player needs the estimation of the unknown parameters of the market and rivals’ decisions, a combined estimation-optimization algorithm for decision making is proposed. The history of the rivals’ output quantities (supplies) and the market clearing price (MCP) are the only available information to the players. The convergence of the algorithm (for both estimation and decision making processes) is discussed. In addition, the stability conditions of the equilibrium points are analyzed using the converse Lyapunov theorem. Through the case studies, which are performed based on the California Independent System Operator (CA-ISO) historical public data, the theoretical results and the applicability of the proposed method are verified. Moreover, a comparative study among the agents using the proposed method, naïve expectation and adaptive expectation in the market is performed to show the effectiveness and applicability of the proposed method.     

Multi-player detection in soccer broadcast videos using a blob-guided particle swarm optimization method

Soccer is the most popular sport around the world, and automatic processing of soccer images is a precious alternative to the manual solutions regarding the explosive growth of soccer videos. A new multi-player detection algorithm in far view frames as an initial step to a wide range of applications, such as player tracking, is addressed in this paper. In the proposed detector, a two-step blob detection (grass-based blob detection followed by an edge-based blob detection) is combined with an efficient search mechanism based on particle swarm optimization (PSO) by assigning sub-swarms to each detected blob. Then, a sub-swarm is initialized and tripled to search for three models corresponding to two teams and the referee. Therefore, the most player-like regions in detected blobs are simultaneously searched by all sub-swarms flying through the solution space, thus expanding the scope of single player detection to multi-player detection. Experimental results demonstrate the efficiency and robustness of the algorithm.     

Algorithm for Increasing the Speed of Evolutionary Optimization and its Accuracy in Multi-objective Problems

Optimization algorithms are important tools for the solution of combinatorial management problems. Nowadays, many of those problems are addressed by using evolutionary algorithms (EAs) that move toward a near-optimal solution by repetitive simulations. Sometimes, such extensive simulations are not possible or are costly and time-consuming. Thus, in this study a method based on artificial neural networks (ANN) is proposed to reduce the number of simulations required in EAs. Specifically, an ANN simulator is used to reduce the number of simulations by the main simulator. The ANN is trained and updated only for required areas in the decision space. Performance of the proposed method is examined by integrating it with the non-dominated sorting genetic algorithm (NSGAII) in multi-objective problems. In terms of density and optimality of the Pareto front, the hybrid NSGAII-ANN is able to extract the Pareto front with much less simulation time compared to the sole use of the NSGAII algorithm. The proposed NSGAII-ANN methodology was examined using three standard test problems (FON, KUR, and ZDT1) and one real-world problem. The latter addresses the operation of a reservoir with two objectives (meeting demand and flood control). Thus, based on this study, use of the NSGAII-ANN integrative algorithm in problems with time-consuming simulators reduces the required time for optimization up to 50 times. Results of the real-world problem, despite lower computational-time requirements, show a performance similar to that achieved in the aforementioned test problems.     

Diffusion Coefficient of Tin(II) Methanesulfonate in Ionic Liquid and Methane Sulfonic Acid (MSA) Solvent

Voltammetry and chronoamperometry for the electrodeposition of tin from Tin(II) methane sulfonate mixed with ionic liquid and methane sulfonate acid at room temperature was studied. Cyclic voltammetry shows redox waves of Tin(II), which proves that the electrodeposition of tin from Tin(II) methane sulfonate is a diffusion-controlled process. The diffusion coefficient of Tin(II) ions in the solvent mixture showed good agreement from both voltammetry and chronoamperometry results. The diffusion coefficient of Tin(II) in the mixture was much smaller than in aqueous solution, and it depends on the anion of the ionic liquid.     

Normal and Anomalous Codeposition of Ni-Co-Fe-Zn Alloys from EMIC/EG in the Presence of an External Magnetic Field

The codeposition of Ni-Co-Fe-Zn alloys from a mixture of 1-ethyl-3-methylimidazolium chloride (EMIC)/ethylene glycol (EG) was studied using potentiostatic electrodeposition in the potential range of –1.10 and –1.30 V vs saturated calomel electrode (SCE), using a permanent parallel magnetic field (PPMF) of 9 T. The uniform magnetic field was aligned parallel to the cathode surface. It was found that both normal and anomalous codeposition occurred. Films with different elemental percentage and deposit morphology were obtained from a mixture of EMIC/EG solution at the applied potentials (–1.10 and –1.30 V) in the absence and presence of a PPMF. The influence of magnetic field on the nucleation and growth process is studied with respect to the magneto-hydrodynamic effect (MHD) and applied potentials.     

Compiling Vector Pascal to the XeonPhi

Intel's XeonPhi is a highly parallel x86 architecture chip made by Intel. It has a number of novel features which make it a particularly challenging target for the compiler writer. This paper describes the techniques used to port the Glasgow Vector Pascal Compiler to this architecture and assess its performance by comparisons of the XeonPhi with 3 other machines running the same algorithms. Copyright © 2015 John Wiley & Sons, Ltd.     

Effects of cold plasma on the color parameters of Hyssop (Hyssopus officinalis L.) using color imaging instrumentation and spectrophotometer

This research was conducted to evaluate the effects of cold atmospheric plasma treatment on the color of Hyssop (Hyssopus officinalis L.) and also to compare the usage of the spectrophotometer vs the color imaging instrumentation for the evaluation of the treatment on the color parameters. The experiments were investigated at different treatment times of 1, 5, and 10 minutes and the voltage values of 17, 20, and 23 kV. Possible changes of color were evaluated by using CIE L*a*b* values obtained with HunterLab colorimeter and CIE L*a*b* values obtained with a digital still camera (DSC) using digital image processing (MATLAB software). The values of L*, a*, and b* of the samples were obtained using both the methods. The results revealed that the L*, a*, and b* values of the treated Hyssop samples changed with increasing the treatment time and the voltage applied. Evaluating the interaction effects revealed that there was a significant difference in the (−a^*/b^* ) ratio. In addition, the results showed that the effects of all variables on the color parameters were significantly different in the case of the DSC using digital image processing. However, these effects were not significantly different using HunterLab colorimeter except for time variable and interaction effects of a* and (−a^*/b^* ) ratio. The lightest green color and the maximum chlorophyll content loss were observed for 23 kV applied over 10 minutes. Based on the results, the digital image processing can be used as a practical tool to study the variations at the color of dried Hyssop leaves after cold plasma treatment.     

In situ Measurement of the Adhesion Strength and Effective Elastic Stiffness of Single Soft Micropillar

We report the deformation behavior and mechanical properties of a polymeric micropillar, which measures approximately 10 μm by 30 μm in size by measuring the loading/unloading response using an in situ force measurement system. When the single poly(dimethylsiloxane) (PDMS) micropillar was subjected to compression, we observed a periodic wrinkle and global (Euler) buckling at the sidewall. During unloading, we found the pull-off force (adhesion force) to increase for higher values of preloading and also for lower loading/unloading rates. From the slope of the load–displacement curves measured in situ, we calculated the effective elastic stiffness of the PDMS micropillar to be about 2.03 MPa. In addition to the current work, we report that this method can be used more broadly for in situ measurement of the intrinsic mechanical and adhesion properties of polymers and other relatively soft materials.     

Strain‐rate‐dependent mechanical properties of polypropylene separator for lithium‐ion batteries

The mechanical integrity of battery separators is critical for battery safety and durability. A comprehensive study of strain‐rate‐dependent tensile and puncture properties of a polypropylene lithium‐ion battery separator is presented here with a new model. Due to anisotropy of the polymeric membrane, tensile testing was conducted for different directions. Results showed that tensile strength and elastic modulus were increased 1000% and 500%, respectively, for different directions. It was also demonstrated that tensile strength changed 10 to 25% with strain rate (1.67 × 10^?4 to 1.67 × 10^?1 s^?1) for different directions. An equation was obtained for the first time for flow stress versus strain rate at varied tensile directions with respect to machine direction. Moreover, puncture testing was performed and it was shown that puncture strength was increased 140% with increasing strain rate from 0.25 to 250 mm min^?1. Two failure modes were also observed in puncture samples. Finally, Eyring's model was used to calculate activation enthalpy of the porous polypropylene separator. © 2020 Society of Chemical Industry