Multi‐agent collaboration based on enhanced cognitive awareness: an architecture for agents' profiling on the semantic web

This paper applies cognitive models, inspired by cognitive science, with the aim to propose architectural and knowledge‐based requirements to structure ontological models for the cognitive profiling of agents. The proposed architecture aims to address the lack of flexibility that most agent‐based collaborations are affected by. The resulting agents, equipped with advanced cognitive profiling, have an increased cognitive awareness of themselves and are more capable of interacting with other agents in a multi‐agents based environment. In this research, cognitive awareness identifies the ability of the web agents to diagnose their processing limitations and to establish interactions with the external environment. The outcome is the enhanced flexibility, reusability and predictability of the agent behaviour; thus contributing towards minimizing human cognitive demands. The concept of cognitive profiling presented in this paper considers the semantic web as an action mediating space, where ontological models provide affordances for improving cognitive awareness through shared knowledge‐base. The conceptual model for the cognitive profile architecture is developed with Protégé Ontology editor to generate OWL Ontology and evaluated through a proof of concept. The results show that agents equipped with cognitive awareness can undertake complex tasks more dynamically.     

基于负载分布的路由算法(LPR)

给出基于路由分布的路由算法,将有效带宽分散于候选路由集中,以匹配到达的虚电路请求服务质量的分布特点。这一方案与传统的负载均衡化和负载打包相比,具有高效的负载公布,较好地支持了应用的实时服务质量。     

Statistical Analysis and Modeling of Jobs in a Grid Environment

The existence of good probabilistic models for the job arrival process and the delay components introduced at different stages of job processing in a Grid environment is important for the improved understanding of the Grid computing concept. In this study, we present a thorough analysis of the job arrival process in the EGEE infrastructure and of the time durations a job spends at different states in the EGEE environment. We define four delay components of the total job delay and model each component separately. We observe that the job inter-arrival times at the Grid level can be adequately modelled by a rounded exponential distribution, while the total job delay (from the time it is generated until the time it completes execution) is dominated by the computing element’s register and queuing times and the worker node’s execution times. Further, we evaluate the efficiency of the EGEE environment by comparing the job total delay performance with that of a hypothetical ideal super-cluster and conclude that we would obtain similar performance if we submitted the same workload to a super-cluster of size equal to 34% of the total average number of CPUs participating in the EGEE infrastructure. We also analyze the job inter-arrival times, the CE’s queuing times, the WN’s execution times, and the data sizes exchanged at the kallisto.hellasgrid.gr cluster, which is node in the EGEE infrastructure. In contrast to the Grid level, we find that at the cluster level the job arrival process exhibits self-similarity/long-range dependence. Finally, we propose simple and intuitive models for the job arrival process and the execution times at the cluster level.     

指导cache静态划分的程序性能profiling优化技术

对于共享cache的多核处理器,如何管理好各个核对cache的利用,对于充分发挥多核处理器性能是很关键的问题.目前采用的cache替换方法程序间会出现性能干扰,cache静态划分技术则是通过为同时运行的程序分配不同的空间来解决性能干扰问题.为了给程序分配合适大小的cache空间,需要对程序进行性能profiling,即事先多遍运行收集程序在各种cache容量下的性能数据,这种性能profiling方法开销巨大,影响实用.为了解决性能profiling需要多遍运行程序的问题,提出了只需单遍运行的程序性能profiling优化技术.该技术利用在线的phase分析技术识别程序的运行阶段,避免对相同阶段的重复profiling;同时分析程序各phase的性能同cache容量变化的关系趋势,对于性能不敏感的容量变化则不进行profiling,降低开销.在程序运行结束后通过程序各phase在cache各种容量下的性能来估计程序在各容量下的整体性能,以指导cache静态划分.实验表明,该技术的开销仅为7%,而该方法指导的cache划分比未划分时有8%的性能改进,同多遍运行的程序性能profiling指导的cache划分性能相比仅有1%的下降.     

Effect of lipids on soy protein isolate solubility

Reduced-lipid soy protein isolate (SPI), prepared from soy flour treated so that most of the polar lipids have been removed, exhibited an increase in protein solubility of 50% over that of the control SPI prepared from hexane-defatted flour. Adding lipids from a commercial SPI during processing of reduced-lipid SPI decreased SPI solubility by 46%. The 19% decreased solubility caused by the lipids (primarily phospholipids) was largely recovered by treating the protein with a reducing agent (2-mercaptoethanol). The balance of protein insolubility, caused by the lipids, was attributed to a smaller lipid fraction (approximately 5% of the total lipids). Adding lipids during SPI processing contributed to both the formation of oxidized protein sulfhydryls, incapable of being reduced by 2-mercaptoethanol, and to oxidative deterioration of protein as determined by protein carbonyl contents.     

NOTE The Application of Surface Analysis Techniques in the Adhesive Bonding of Oily Automotive Steel

There are fewer papers on the adhesive bonding of steel for structural applications than for aluminum and titanium alloys. However, the approach to the adhesive bonding of all three adherends has been similar, that is, the surfaces are pretreated prior to bonding. Trawinski, et al.^1,2,3 reviewed several conversion coatings or etching processes used for steel. Haak and Smith⁴ selected two surface treatments among nineteen based on minimal cost, simplicity and good durability. Smith⁵ has reported work on stainless steel-epoxy bonds under hydrothermal stress. Bischof, et al.⁶ investigated the effect of surface pretreatment of steel on bonding strength obtained with polyvinyl chloride. Ziane, et al.⁷ identified four fracture zones resulting from shear loading of epoxy bonded galvanized steel following four different surface pretreatments. But in some cases, as in the automotive industry, there is a need to bond oily steel directly without surface pretreatment. Rosty, et al.⁸ have reported a study of the role of fillers and cure temperature on the shear strength of oily steel bonded with epoxy. None of the reported research utilizes both microscopic and spectroscopic techniques to analyze the fracture surfaces.     

Study of Quintic Spline Interpolation and Generated Velocity Profile for High Speed Machining

Modern high speed machining (HSM) machine tools often operates at high speed and high feedrate with high ac- celerations,in order to deliver the rapid feed motion.This paper presents an interpolation algorithm to generate continuous quintic spline toolpaths,with a constant travel increment at each step,while the smoother accelerations and jerks of two-order curve are obtained.Then an approach for reducing the feedrate fluctuation in high speed spline interpolation is presented.The presented ap- proach has been validated to quickly,reliably and effective with the simulation.     

辐射诱导冷却肉脂肪氧化机理与抑制方法研究

探讨了辐照剂量、贮藏效应、氧气含量和抗氧化剂等因素对辐照冷却肉脂肪氧化的影响，提出了抑制辐照冷却肉脂肪氧化的技术方法。结果表明，辐照冷却肉的过氧化值与辐照剂量存在极显著的正相关关系（p〈0．01），随着贮藏时间的延长表现为先升后降；在包装实验中，真空包装和无氧包装（N2＋CO2）可以咀显降低贮藏期间辐照冷却肉的过氧化值和TBARS值（硫代巴比妥酸反应物）；添加抗氧化剂后，辐照冷却肉的脂肪氧化明显降低，其过氧化值和TBARS值在贮藏期间不超过3meq／kg和0．4mgMDA／kg，而对照达到29meq／kg和1．13mgMDA／kg，其中抗氧化剂茶多酚和维生素E起主导作用。     

基于犯罪画像的计算机取证分析方法研究

犯罪嫌疑人的画像分析已经引起了广泛的关注,在各种媒体领域都得到了广泛的应用,计算机领域也已经开始了这方面的研究内容。犯罪嫌疑人画像的分析主要是对犯罪现场分析和犯罪行为调查的心理分析。通过对传统物理取证分析方法和现有的计算机取证分析方法的总结,将传统犯罪取证研究中的犯罪轮廓构建技术应用于计算机犯罪取证研究中,缩小取证调查范围,协助工作人员办案,从而锁定罪犯,提高案件的侦破效率。提出用数据挖掘的方法进行取证。