F-MPJ: scalable Java message-passing communications on parallel systems

This paper presents F-MPJ (Fast MPJ), a scalable and efficient Message-Passing in Java (MPJ) communication middleware for parallel computing. The increasing interest in Java as the programming language of the multi-core era demands scalable performance on hybrid architectures (with both shared and distributed memory spaces). However, current Java communication middleware lacks efficient communication support. F-MPJ boosts this situation by: (1) providing efficient non-blocking communication, which allows communication overlapping and thus scalable performance; (2) taking advantage of shared memory systems and high-performance networks through the use of our high-performance Java sockets implementation (named JFS, Java Fast Sockets); (3) avoiding the use of communication buffers; and (4) optimizing MPJ collective primitives. Thus, F-MPJ significantly improves the scalability of current MPJ implementations. A performance evaluation on an InfiniBand multi-core cluster has shown that F-MPJ communication primitives outperform representative MPJ libraries up to 60 times. Furthermore, the use of F-MPJ in communication-intensive MPJ codes has increased their performance up to seven times.     

Multiobjective hierarchical control architecture for greenhouse crop growth

The problem of determining the trajectories to control greenhouse crop growth has traditionally been solved by using constrained optimization or applying artificial intelligence techniques. The economic profit has been used as the main criterion in most research on optimization to obtain adequate climatic control setpoints for the crop growth. This paper addresses the problem of greenhouse crop growth through a hierarchical control architecture governed by a high-level multiobjective optimization approach, where the solution to this problem is to find reference trajectories for diurnal and nocturnal temperatures (climate-related setpoints) and electrical conductivity (fertirrigation-related setpoints). The objectives are to maximize profit, fruit quality, and water-use efficiency, these being currently fostered by international rules. Illustrative results selected from those obtained in an industrial greenhouse during the last eight years are shown and described.     

A Haar wavelet quasilinearization approach for numerical simulation of Burgers’ equation

In this paper, an efficient numerical scheme based on uniform Haar wavelets and the quasilinearization process is proposed for the numerical simulation of time dependent nonlinear Burgers’ equation. The equation has great importance in many physical problems such as fluid dynamics, turbulence, sound waves in a viscous medium etc. The Haar wavelet basis permits to enlarge the class of functions used so far in the collocation framework. More accurate solutions are obtained by wavelet decomposition in the form of a multi-resolution analysis of the function which represents a solution of boundary value problems. The accuracy of the proposed method is demonstrated by three test problems. The numerical results are compared with existing numerical solutions found in the literature. The use of the uniform Haar wavelet is found to be accurate, simple, fast, flexible, convenient and has small computation costs.     

Support and precursor effects on the preparation of new heterogenized Pt/Sn catalysts for the selective hydroformylation of 1-pentene

New heterogenized Pt/Sn catalysts selective for the hydroformylation of 1-pentene have been synthesized. The complex cis-[PtCl₂(PPh₃)₂] and the SnCl₂.2H₂O or SnC₂O₄ precursors have been anchored on silica-, magnesia- and alumina-carriers. X-ray photoelectron spectroscopy was used to determine the surface composition and the nature of the anchored species. The hydroformylation activity was found to depend on the type of support and tin precursor used. Only the silica supported catalysts were active in the hydroformylation reaction. Samples prepared from SnCl₂-2H₂O were 200-fold more active than those prepared from SnC₂O₄. Selectivity ton-hexanal of the silica-supported catalyst prepared from SnCl₂-2H₂O was as high as 94.4% at 39.2% conversion of 1-pentene.     

Orthographic Structure Versus Morphological Structure: Principles of Lexical Organization in a Given Language.

Most models of visual word recognition in alphabetic orthographies assume that words are lexically organized according to orthographic similarity. Support for this is provided by form-priming experiments that demonstrate robust facilitation when primes and targets share similar sequences of letters. The authors examined form-orthographic priming effects in Hebrew, Arabic, and English. Hebrew and Arabic have an alphabetic writing system but a Semitic morphological structure. Hebrew morphemic units are composed of noncontiguous phonemic (and letter) sequences in a given word. Results demonstrate that form-priming effects in Hebrew or Arabic are unreliable, whereas morphological priming effects with minimal letter overlap are robust. Hebrew bilingual subjects, by contrast, showed robust form-priming effects with English material, suggesting that Semitic words are lexically organized by morphological rather than orthographic principles. The authors conclude that morphology can constrain lexical organization even in alphabetic orthographies and that visual processing of words is first determined by morphological characteristics. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

考虑环保因素的最小费用电源规划研究

介绍电力部门降低污染物排放的必要性、可行性以及需要采取的一些措施，并介绍由泰国亚洲理工大学（AIT）开发的考虑环保因素的综合资源规划软件(IRPA)及其规划思路、所需数据和特点。对我国某省2003年～2017年的电力发展进行了规划研究。     

Augmenting a conceptual model with geospatiotemporal annotations

While many real-world applications need to organize data based on space (e.g., geology, geomarketing, environmental modeling) and/or time (e.g., accounting, inventory management, personnel management), existing conventional conceptual models do not provide a straightforward mechanism to explicitly capture the associated spatial and temporal semantics. As a result, it is left to database designers to discover, design, and implement - on an ad hoc basis - the temporal and spatial concepts that they need. We propose an annotation-based approach that allows a database designer to focus first on nontemporal and nongeospatial aspects (i.e., "what") of the application and, subsequently, augment the conceptual schema with geospatiotemporal annotations (i.e., "when" and "where"). Via annotations, we enable a supplementary level of abstraction that succinctly encapsulates the geospatiotemporal data semantics and naturally extends the semantics of a conventional conceptual model. An overarching assumption in conceptual modeling has always been that expressiveness and formality need to be balanced with simplicity. We posit that our formally defined annotation-based approach is net only expressive, but also straightforward to understand and implement.     

High Performance Air Pollution Simulation Using OpenMP

The aim of this work is to provide a high performance air quality simulation using the sulphur transport Eulerian model 2 (STEM-II) program. First of all we optimize the sequential program with the aim of increasing data locality. Then, the optimized program is parallelized using OpenMP shared-memory directives. Experimental results on a 32-processor SGI Origin 2000 show that the parallel program achieves important reductions in the execution times.     

Groundwater Flow and Contaminant Transport Simulation with Imprecise Parameters

A methodology has been developed in this study wherein a genetic algorithm (GA) is used to find a global optimal solution to a groundwater flow and contaminant problem by incorporating an artificial neural network (ANN) to evaluate the objective function within the genetic algorithm. The study shows that an ANN-GA technique can be used to find the uncertainties in output parameters due to imprecision in input parameters. The ANN-GA methodology is applied to five case studies involving radial flow in a well, one-dimensional solute transport in steady uniform flow, a two-dimensional heterogeneous steady flow, a two-dimensional solute transport, and a two-dimensional unsteady groundwater flow to demonstrate the efficiency and effectiveness of the developed algorithm. The results show that, with this approach, one can successfully measure the uncertainty in groundwater flow and contaminant transport simulations and achieve a considerable reduction in computational effort when compared to the vertex method that has been widely used in the past.     

Investigation of temperature-dependent polarization, dielectric, and magnetization behavior of multiferroic layered nanostructure

The PbZr_0.53Ti_0.47O₃(PZT)/CoFe₂O₄(CFO) layered nanostructures show lowering of dielectric constant and polarization, and an enhanced magnetization with a decrease in temperature from 400 K to 100 K. The temperature dependence of the real part of the dielectric constant illustrates a step-like behavior, whereas the imaginary part gives a relaxation peak near the step maxima temperature. A slow decrease in the polarization was observed from 300 K to 200 K, with an eventual collapse of polarization at ~ 100 K, and a complete polarization recovery with heating, these phenomena is reproducible over cycles of experiment. Remanent magnetization of the layered nanostructure was found to be three times higher at 100 K than that at room temperature. There is a slow enhancement in remanent (internal) magnetization with lowering of temperature, resulting in slow polarization switch and finally the collapse. The temperature-dependent dielectric, polarization and magnetization were different from the parent layer, indicating a kind of dynamic magneto-electric coupling in the layered nanostructures.