Software Distributed Shared Memory: a VIA‐based implementation and comparison of sequential consistency with home‐based lazy release consistency

A Distributed Shared Memory (DSM) system provides a distributed application with a shared virtual address space. This article proposes a design for implementing the DSM communication layer on top of the Virtual Interface Architecture (VIA), an industry standard for user‐level networking protocols on high‐speed clusters. User‐level communication protocols operate in user mode, thus removing the operating system kernel's overhead from the critical communication pass, and significantly diminishing communication overhead as a result. We analyze VIA's facilities and limitations in order to ascertain which implementation trade‐offs can be best applied to our development of an efficient communication substrate optimized for DSM requirements. We then implement a multithreaded version of the Home‐based Lazy Release Consistency (HLRC) protocol on top of this substrate. In addition, we compare the performance of this HLRC protocol with that of the Sequential Consistency (SC) protocol in which a Multi View (MV) memory mapping technique was used. This technique enables a fine‐grained access to shared memory, while still relying on the virtual memory hardware to track memory accesses. We perform an ‘apple‐to‐apple’ comparison on the same testbed environment and benchmark suite, and investigate the effectiveness and scalability of both protocols. Copyright © 2005 John Wiley & Sons, Ltd.     

Identification of Hammerstein nonlinear ARMAX systems

Two identification algorithms, an iterative least-squares and a recursive least-squares, are developed for Hammerstein nonlinear systems with memoryless nonlinear blocks and linear dynamical blocks described by ARMAX/CARMA models. The basic idea is to replace unmeasurable noise terms in the information vectors by their estimates, and to compute the noise estimates based on the obtained parameter estimates. Convergence properties of the recursive algorithm in the stochastic framework show that the parameter estimation error consistently converges to zero under the generalized persistent excitation condition. The simulation results validate the algorithms proposed.     

Handling sectional views in volume-based approach to automatically construct 3D solid from 2D views

This paper presents an algorithm for solid model reconstruction from 2D sectional views based on volume-ba`sed approach. None of the existing work in automatic reconstruction from 2D orthographic views have addressed sectional views in detail. It is believed that the volume-based approach is better suited to handle different types of sectional views. The volume-based approach constructs the 3D solid by a boolean combination of elementary solids. The elementary solids are formed by sweep operation on loops identified in the input views. The only adjustment to be made for the presence of sectional views is in the identification of loops that would form the elemental solids. In the algorithm, the conventions of engineering drawing for sectional views, are used to identify the loops correctly. The algorithm is simple and intuitive in nature. Results have been obtained for full sections, offset sections and half sections. Future work will address other types of sectional views such as removed and revolved sections and broken-out sections.     

Maintaining associativity between form feature models

The promise of features technology was that the task domains would have access to task specific product data through feature based models. This is an important requirement in a distributed and concurrent design environment, where data of part geometry has to be shared between different task domains.Associativity between feature models implies the automatic updating of different feature models of a part after changes are made in one of its feature models. The proposed algorithm takes multiple feature models of a part as input and modifies other feature models to reflect the changes made to a feature in a feature model. The proposed algorithm updates feature volumes in other feature models and then classifies the updated volumes to obtain the updated feature model. The spatial arrangement of feature faces and adjacency relationship between features are used to isolate features in a view that are affected by the modification. Feature volumes are updated based on the classification of the feature volume of the modified feature with respect to feature volumes of the model being updated. The algorithm is capable of handling all types of feature modifications namely, feature deletion, feature creation, and changes to feature location and parameters. In contrast to current art in automatic updating of feature models, the proposed algorithm does not use an intermediate representation, does not re-interpret the feature model from a low level representation and handles interacting features. The present work considers modifications to form features only. Modification of constraints and application attributes are under investigation. Results of implementation on typical cases are presented.     

电磁式惯性型作动器与结构耦合系统建模与试验研究

针对结构振动与电磁驱动AMD控制系统（以下简称EMD系统）的相互作用问题,提出了是否考虑、以及考虑何种程度相互作用的三种理论计算模型并进行了试验研究.首先试验比较了EMD系统在正弦扫频控制电压输入下各阶理论模型预测结果与试验结果的差异,验证了各模型对系统的描述精度;其次以El Centro地震波输入为例,试验比较了3种计算模型在3种控制算法共9种试验工况下,EMD控制系统对结构地震响应控制效果的影响.本文所有试验结果均表明只有考虑相互作用、并且充分考虑高阶相互作用才能最佳地描述EMD控制系统在结构中真实的工作状态,才能充分发挥EMD系统对结构振动的控制作用,从而为实现高性能的结构振动主动控制试验与应用奠定基础.     

Exploring the Bidding Situation for Economically Most Advantageous Tender Projects Using a Bidding Game

Most open tendering procedures in the real world are highly complex, uncertain, and costly. With an increasing emphasis on the quality and value of procurement, economically most advantageous tender (EMAT) has been widely adopted as an alternative contract-awarding criteria, which has changed competitive strategies in the construction industry. A conceptual model of competitive bidding in EMAT is first established to reflect the credibility of the bidding situation. A bidding game for EMAT projects is performed by 24 participants to partially test the conceptual model. The result reveals that the game has the potential to reveal important factors in the bidding situation, simulate competitive bidding behaviors, and explore competitive advantages in the EMAT bidding process. The learning effect from the game should be useful for contractors who are preparing to deliver optimal tenders in EMAT projects.     

Long-Term Dynamic Modeling Approach to Quantifying Attached Algal Growth and Associated Impacts on Dissolved Oxygen in the Lower Truckee River, Nevada

Nutrient loads enter the lower Truckee River of western Nevada, affecting the growth of attached algae (periphyton) which causes depressed nighttime dissolved oxygen (DO) levels. The lower Truckee River is home to the endangered cui-ui and threatened Lahontan cut-throat trout, with DO standards being established to in part protect these species. Hydrodynamics, nutrient concentrations, periphyton biomass, and DO data spanning August 2000–December 2001 were used to calibrate and verify a modified version of the Water Quality Analysis Simulation Program Version 5 (WASP5). Under typical loading conditions the periphyton community is nitrogen limited, however nitrogen loading from an upstream wastewater treatment facility increased greatly during the analysis period due to approved site construction activities (discharge permit excursion) causing the periphyton community to temporarily become phosphorus limited. The developed modeling approach, with limited calibration, was able to accurately track dynamic system responses. Removing the impact of the noted discharge permit excursion resulted in a minimum computed DO value of 4.13?mg/L, occurring at the downstream end of the modeling domain on August 8, 2001. Additionally removing the impact of all nutrient loads from area agriculture resulted in a predicted minimum DO value of 4.54?mg/L, while also shifting its location significantly upstream and its timing to April 26, 2001. Meeting all prescribed DO standards required establishing a minimum in-stream flow value of 1.81?m3/s (64.0?ft3/s) downstream of Derby Dam.     

Development and Application of a Phosphorus Model for a Shallow Oxbow Lake

A three-dimensional numerical model was developed for simulating the phosphorus concentration in shallow lakes. In this model, the computational domain was divided into two parts: the water column and the bed sediment layer. The processes of mineralization, settling, adsorption, desorption, bed release (diffusion), growth, and death of phytoplankton were taken into account, and the concentration of organic phosphorus, phosphate, and related water quality constituents was simulated. The concentrations of adsorbed (particulate) and dissolved phosphate due to adsorption-desorption were calculated using two formulas derived based on the Langmuir equation. The release rate of phosphorus from the bed sediment layer was calculated by considering the effects of the concentration gradient across the water-sediment interface, pH, temperature, dissolved oxygen concentration, and flow conditions. The adsorption and desorption of phosphate from sediment particles, as well as its release from bed sediment, were verified using laboratory experimental data. The model was calibrated and applied to Deep Hollow Lake in the Mississippi alluvial plain. The simulated trends and magnitudes of phosphorus concentration were compared with field observations. The simulation results show that there are strong interactions between sediment-related processes and phosphorus concentration.     

Statistical Modeling to Forecast Odor Levels of Biosolids Applied to Reuse Sites

Proper use or disposal of wastewater solids is an important responsibility of wastewater treatment plants. At present, there are several options for wastewater solids, including agriculture, forestry, and mine reclamation reuse; production of marketable products such as compost and dried pellets; and disposal in landfills and incinerators. Land application of biosolids products is beneficial as part of recycling efforts on local farms, forests, tree farms, and mines and has gained greater acceptance of late. Coupled with these beneficial aspects are odors, which must be managed relative to the receiving populations. In this paper we present several statistical models that predict biosolids odor levels based on processing and management variables as well as ambient conditions. Such models are useful to managers at advanced wastewater treatment plants in helping them to better forecast the biosolids odors and minimize the “odor footprint,” thus making these biosolids products better received.