基于参数辨识的药物代谢动力学的分析

药物代谢动力学是研究体内药量及其代谢物的时间变化,并用数学公式加以描述的一门学科.研究药物代谢动力学的最常用方法是"房室模型"(compartment model)理论.其中房室数目的确定、各房室的关系等是首先要解决的问题,该文通过对临床上取得的11例病例口服药物乙胺碘肤酮的实验数据,进行药物代谢动力学的参数辨识,从而进一步确定此药物的房室模型取三室模型更为合理.     

东北民猪不同生长阶段饥饿代谢的研究

东北民猪是中国东北地区较原始的地方优良品种,很适合当地农户饲养。但对东北民猪不同生长育肥阶段的饥饿代谢的特点以及维持能量需要等研究报道则比较少。确定饥饿代谢的能量代谢和物质消耗,是确定维持能量需要和其它各种生产状态、营养需要的基础。Brody,S.(1945)分析大量不同种类成年动物基础代谢资料,提出了产热量与体重的函数关系式:HP_((R.Q.))=a·w~b,该公式得到普遍承认。许多     

磺胺嘧啶(SD)在东北细毛羊体内的代谢动力学研究

给6只健康东北细毛羊颈静脉一次快速推注20%磺胺嘧啶钠注射液70毫克/公斤,在给药后10小时内的不同时间采血,并用重氮化——偶合比色法测定其血药浓度。将每只东北细毛羊的药——时数据输人已编好程序的 CBM—4032型电子计算机中进行数据处理。数据符合开放型三室模型,则得出磺胺嘧啶在每只羊体内的各药物代谢动力学参数。试验证实:磺胺嘧啶在东北细毛羊体内的生物半衰期为3.45±1.17小时,其血中有效抑菌浓度维持时间为2.4小时。磺胺嘧啶对此羊不为中效,而属短效磺胺。静脉推注70毫克/公斤,其负荷剂量(首次给药突击剂量)为144.88毫克/公斤,给药间隔时间为3小时。     

SNMP三大功能模块的研究和实现

主要介绍了SNMP需要实现的功能模块。通过对三大功能模块的分析 ,提出了实现这三个模块的基本方法 ,并结合具体的实例讨论了方法的可行性。这些方法适用于一般的基于SNMP的管理结构。     

Hyperledger Fabric平台的国密算法嵌入研究

Hyperledger Fabric是为企业级商用区块链项目提供支撑的且可扩展的联盟链平台,密码算法为该平台的核心,保证上链数据的安全和不可篡改,但原始Fabric平台缺乏对国密算法的支持.因此,设计并实现了Fabric平台的国密算法的嵌入和支持.首先,通过分析Fabric平台中组件间交互逻辑和密码算法的调用场景,提出...     

Effect of experimental methodology on the JND of the black level for natural images

Abstract— The effect of experimental methodology on the Just Noticeable Difference (JND) of the black level (BL) is assessed using a set of representative natural images. Two methodologies, known in psychophysics to determine JNDs, are mutually compared: an adapted method of adjustment with a same‐difference task and a one‐up‐two‐down staircase method with a two‐alternative forced‐choice task. Thus far, the literature has shown contradictory results for which of the two methods yields the lower difference thresholds. Experimental results show that the second method yields lower JNDs, but is slightly less efficient. Based on this second method, it was found that the JND of the BL for natural images ranges from 0.2 to 1.0 cd/m², varying with image content significantly.     

嵌入式系统芯片中SM2算法软硬件协同设计与实现

针对现有的椭圆曲线算法系统级设计中开发周期长,以及不同模块的性能开销指标不明确等问题,提出一种基于电子系统级(ESL)设计的软硬件(HW/SW)协同设计方法.该方法通过分析SM2(ShangMi2)算法原理与实现方式,研究了不同的软硬件划分方案,并采用统一建模语言SystemC对硬件模块进行周期精确级建模.通过模块级与系统级两层验证比较软硬件模块执行周期数,得出最佳性能划分方式.最后结合算法控制流程图(CFG)与数据流程图(DFG)将ESL模型转化为寄存器传输级(RTL)模型进行逻辑综合与比较,得出在180 nm CMOS工艺,50 MHz频率下,当算法性能最佳时,点乘模块执行时间为20 ms,门数83 000,功耗约2.23 mW.实验结果表明所提系统级架构分析对基于椭圆曲线类加密芯片在性能、面积与功耗的评估优势明显且适用性强,基于此算法的嵌入式系统芯片(SoC)可根据性能与资源限制选择合适的结构并加以应用.     

Remote sensing of phytoplankton pigment distribution in the United States northeast coast

Phytoplankton pigments constitute many more compounds than chlorophyll a that can be applied to study phytoplankton diversity, populations, and primary production. In this study, field measurements were applied to develop ocean color satellite algorithms of phytoplankton pigments from in-water radiometry measurements. The match-up comparisons showed that the satellite-derived pigments from our algorithms agree reasonably well (e.g. 30-55% of uncertainty for SeaWiFS and 37-50% for MODIS-Aqua) to field data, with better agreement (e.g. 30-38% of uncertainty for SeaWiFS and 39-44% for MODIS-Aqua) for pigments abundant in diatoms. The seasonal and spatial variations of satellite-derived phytoplankton biomarker pigments, such as fucoxanthin, which is abundant in diatoms, peridinin, which is found only in peridinin-containing dinoflagellates, and zeaxanthin, which is primarily from cyanobacteria in coastal waters, revealed that higher densities of diatoms are more likely to occur on the inner shelf and during winter-spring and obscure other abundant phytoplankton groups. However, relatively higher densities of other phytoplankton, such as dinoflagellates and cyanobacteria, are likely to occur on the mid- to outer-continental shelf and during summer. Seasonal variation of riverine discharge may play an important role in stimulating algal blooms, in particular diatoms, while higher abundances of cyanobacteria coincide with warmer water temperatures and lower nutrient concentrations.     

一种基于单纯形法的改进微粒群优化算法及其收敛性分析

针对现有微粒群优化算法难以兼顾进化速度和求解质量这一难题, 提出一种基于单纯形法的改进微粒群优化算法(Simplex method based improved particle swarm optimization, SM-IPSO). 该算法采用多个优化种群, 分别在奇数种群和偶数种群上并行运行微粒群算法和单纯形法, 并通过周期性迁移相邻种群间的最优信息, 达到微粒群算法和单纯形法的协同搜索: 单纯形借助微粒群算法跳出局部收敛点, 微粒群依靠单纯形提高局部开发能力. 为强化两种算法所起作用, 一种改进的微粒速度逃逸策略和Nelder-Mead单纯形法也被提出. 最后, 在Linux集群系统上运行所提算法, 通过优化五个典型测试函数验证了算法的有效性.     

基于TePA的无线传感器网络用户接入认证协议

安全有效的用户接入认证协议是构建无线传感器网络( WSN)系统的核心技术。针对无线传感器网络以数据为中心的特点,结合三元对等鉴别架构( TePA)技术提出了一种无线传感器网络用户接入认证协议。该协议具有灵活的安全配置机制,用户可选择不同的安全策略,能解决用户安全接入和安全需求各不同的问题。最后描述了密钥交换算法的实现,采用了重新分配的 SM2数字签名与验证流程,对数据签名验证的延迟比 SM2算法降低了约12%。     

Parameter Optimization of Interval Type-2 Fuzzy Neural Networks Based on PSO and BBBC Methods

Interval type-2 fuzzy neural networks (IT2FNNs) can be seen as the hybridization of interval type-2 fuzzy systems (IT2FSs) and neural networks (NNs). Thus, they naturally inherit the merits of both IT2FSs and NNs. Although IT2FNNs have more advantages in processing uncertain, incomplete, or imprecise information compared to their type-1 counterparts, a large number of parameters need to be tuned in the IT2FNNs, which increases the difficulties of their design. In this paper, big bang-big crunch (BBBC) optimization and particle swarm optimization (PSO) are applied in the parameter optimization for Takagi-Sugeno-Kang (TSK) type IT2FNNs. The employment of the BBBC and PSO strategies can eliminate the need of backpropagation computation. The computing problem is converted to a simple feed-forward IT2FNNs learning. The adoption of the BBBC or the PSO will not only simplify the design of the IT2FNNs, but will also increase identification accuracy when compared with present methods. The proposed optimization based strategies are tested with three types of interval type-2 fuzzy membership functions (IT2FMFs) and deployed on three typical identification models. Simulation results certify the effectiveness of the proposed parameter optimization methods for the IT2FNNs.      

GSM模块在车辆监控系统无线通信中的应用

介绍了GPS车辆监控系统中运行车辆使用西门子TC35T GSM模块和监控中心之间通过语音和短消息方式进行无线通信的方法，给出了软硬件的设计原则与方法。实验表明此方法满足车辆监控的需要并具有性价比高、数据保密性好等特点。