A Method of Gene-Function Annotation Based on Variable Precision Rough Sets

It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotation of new biological sequences is presented by using the variable-precision rough set theory. The proposed method is applied to the real data in GO database to examine its effectiveness. Numerical results show that the proposed method has better precision, recall-rate and harmonic mean value compared with existing methods.

Variable precision rough set for multiple decision attribute analysis

A variable precision rough set (VPRS) model is used to solve the multi-attribute decision analysis (MADA) problem with multiple conflicting decision attributes and multiple condition attributes. By introducing confidence measures and a β-reduct, the VPRS model can rationally solve the conflicting decision analysis problem with multiple decision attributes and multiple condition attributes. For illustration, a medical diagnosis example is utilized to show the feasibility of the VPRS model in solving the MADA problem with multiple decision attributes and multiple condition attributes. Empirical results show that the decision rule with the highest confidence measures will be used as the final decision rules in the MADA problem with multiple conflicting decision attributes and multiple condition attributes if there are some conflicts among decision rules resulting from multiple decision attributes. The confidence-measure-based VPRS model can effectively solve the conflicts of decision rules from multiple decision attributes and thus a class of MADA problem with multiple conflicting decision attributes and multiple condition attributes are solved.

PRECISE ASYMPTOTICS IN SELF-NORMALIZED SUMS OF ITERATED LOGARITHM FOR MULTIDIMENSIONALLY INDEXED RANDOM VARIABLES

In the case of Z＋^d（d ≥ 2）-the positive d-dimensional lattice points with partial ordering ≤, {Xk,k∈ Z＋^d} i.i.d, random variables with mean 0, Sn =∑k≤nXk and Vn^2 = ∑j≤nXj^2, the precise asymptotics for ∑n1/｜n｜（log｜n｜dP（｜Sn/Vn｜≥ε√log log｜n｜） and ∑n（logn｜）b/｜n｜（log｜n｜）^d-1P（｜Sn/Vn｜≥ε√log n）,as ε↓0,is established.

PRECISE INTEGRAL ALGORITHM BASED SOLUTION FORTRANSIENT INVERSE HEAT CONDUCTION PROBLEMSWITH MULTI-VARIABLES

By modeling direct transient heat conduction problems via finite element method (FEM) and precise integral algorithm, a new approach is presented to solve transient inverse heat conduction problems with multi-variables. Firstly, the spatial space and temporal domain are discretized by FEM and precise integral algorithm respectively. Then, the high accuracy semi-analytical solution of direct problem can be got. Finally, based on the solution, the computing model of inverse problem and expression of sensitivity analysis are established. Single variable and variables combined identifications including thermal parameters, boundary conditions and source-related terms etc. are given to validate the approach proposed in 1-D and 2-D cases. The effects of noise data and initial guess on the results are investigated. The numerical examples show the effectiveness of this approach.

Product Approximation of Grade and Precision

The normal graded approximation and variable precision approximation are defined in approximate space. The relationship between graded approximation and variable precision approximation is studied, and an important formula of conversion between them is achieved The product approximation of grade and precision is defined and its basic properties are studied.

Cotton Response to Variable Nitrogen Rate Fertigation through an Overhead Irrigation System

Recent increases in irrigated hectares in the Southeastern US have enabled growers to obtain higher yields through applying nutrients through irrigation water. Therefore, many growers apply nutrients through irrigation systems, known as fertigation. Currently, there are no practical decision-making tools available for variable-rate application of nitrogen (N) through overhead sprinkler irrigation systems. Therefore, field tests were conducted on cotton (Gossypium hirsutum L.) during the 2016 and 2017 growing seasons to 1) adapt the Clemson sensor-based N recommendation algorithms from a single side-dress application to multiple applications through an overhead irrigation system;and 2) to compare sensor-based VRFS with conventional nutrient management methods in terms of N use efficiency (NUE) and crop responses on three soil types. Two seasons of testing Clemson N prediction algorithms to apply multiple applications of N were very promising. The multiple applications of N compared to the grower’s conventional methods (even though less N was applied) had no impact on yields in either growing season. There was no difference in cotton yields between 101 and 135 kg/ha N applications in either management zone. Also, there were no differences in yield between sensor-based, multiple N applications and conventional N management techniques. In relation to comparisons of the sensor methods only applying N in three or four applications, statistically increased yields compared to single or split applications in 2016. Applying N in four applications, statistically increased yields compared to single, split or triple applications in 2017. When the sensor-based methods were compared to the grower’s conventional methods averaged over four treatments, the sensor-based N applications reduced fertilizer requirement by 69% in 2016 and 57% in 2017 compared to grower’s conventional methods. When comparing N rates among the four sensor-based methods (three or four) applications, increased N rates by 22 kg/ha in 2016 and 26 kg/ha in 2017 compared to single or split applications but increased the cotton lint yields by 272 and 139 kg/ha, for 2016 and 2017, respectively.

Development and Testing of a Variable Rate Nitrogen Application System through an Overhead Irrigation System

Nutrients are injected through overhead irrigation systems at a uniform rate in a process known as fertigation. The highly variable soils in the Southeastern US pose challenges for effective fertigation. Currently, there is no variable-rate fertigation system available to apply the correct amount of N within a field through an overhead irrigation system. Therefore, the objective of this study was to develop and test a variable-rate N application system that works independently of irrigation water flow for site-specific N application. The variable-rate fertigation system (VRFS) was designed to apply different rates N using a pulse width modulation technique. The VRFS utilized the Clemson Lateral Irrigation Control software which controlled the solenoids in each zone by turning the N supply on and off (pulsing) for each zone. In this study, four tests were conducted to determine the uniformity of the VRFS. In test # 1, the pump output showed a linear slope relationship and was the same for water and N. In test # 2, nozzle flow and uniformity were determined using four different irrigation system travel speeds at N application rates of 31, 59, 88, and 113 kg/ha. There was a strong correlation (R2 = 0.9998) between irrigation system speed and N rate. In test # 3, the uniformity across the length of the irrigation system was determined. The nozzles produced an average flow of 31.1, 58.7, 87.6, and 112.7 kg N/ha with an overall average error of 0.1% across all N rates. Results also showed the system was capable of accurately applying N based on prescription maps with an error of less than 1.8%. Test # 4 was conducted to determine the accuracy of the map-based controller system for applying variable rate N. There was a strong correlation between target N and actual N rates (R2 = 0.9999). In summary, the VRFS applied the correct amounts of N within each zone by either manually controlling the pulsing mechanism or utilizing a prescription map to apply different rates throughout the field.

Identification of Soil Management Factors from Spatially Variable Soil Properties of Coastal Plain Sands in Southeastern Nigeria

Variability in soil properties is a critical element across wide areas of researches especially in several aspects of agriculture and environment including sewage disposal and global climate change. Particle size fraction (sand, silt, and clay), effective cation exchange capacity, base saturation, pH, organic carbon, total nitrogen, carbon nitrogen ratio, available phosphorus, exchangeable bases (calcium, magnesium, sodium, potassium) and acidity are frequently used in agriculture for soil management. The objective of this study therefore was to identify soil management factors from these set of 15 soil properties and spatial distribution of representative soil management properties. The study was carried out in the University of Uyo Teaching and Research Farm measuring 8.19 hectares in University of Uyo Annex, Uyo in Akwa Ibom State of Nigeria. Nine and ten traverses were made horizontally and vertically respectively at 40 meters intervals. A total of 58 soil samples were collected at 0 - 15 cm depth on the grid nodes of the traverses. Particle size distributions, exchangeable bases and acidity, effective cation exchange capacity (ECEC), available phosphorus (avail. P), base saturation (BS), organic carbon, total nitrogen, carbon nitrogen ratio (CNR) and pH of the samples were determined in the laboratory. Coefficient of variation indicated that 26.6% of the soil properties (sand content, pH, CNR and sodium) were least variable, 40.1% comprising silt, clay contents, ECEC, base saturation, phosphorus and magnesium were moderately. Whereas 33.3% of the soil properties comprising clay content, organic carbon, total nitrogen, exchangeable Ca, K and acidity (i.e.) were highly variable. There were significant correlation (p < 0.05) in 26.6% of the soil properties, the strongest negative significant (p < 0.01) correlations were between sand and clay (r = –0.85), exchangeable acidity and base saturation (r = –0.85), whereas the strongest positive significant correlations were between ECEC and Ca (r = 0.80), Ca and BS (r = 0.74), organic carbon and total nitrogen (r = 0.80). Principal component analysis indicated the existence of six factors including mineralogical or weathering, soil organic matter, cation exchange activity, soil texture, and dispersion and soil phosphorus based on either management or pedological considerations. Semivariance statistics showed that sand and clay contents, ECEC, BS and total N were moderately (≥25.7% ≤47.3%), while silt content, pH, organic carbon, CNR, avail. P, exchangeable Ca, Mg, Na and acidity (≥0.18% ≤22.8%) were strongly spatially dependent. The variability observed was primarily incident upon factors of soil formation. Therefore, the utilization of spatial structure of organic matter and texture factors in the management of nutrient and soil water will facilitate planning of crop production scheme on coastal plain sands soils.

A Regression Type Estimator with Two Auxiliary Variables for Two-Phase Sampling

This paper is an extension of Hanif, Hamad and Shahbaz estimator [1] for two-phase sampling. The aim of this paper is to develop a regression type estimator with two auxiliary variables for two-phase sampling when we don’t have any type of information about auxiliary variables at population level. To avoid multi-collinearity, it is assumed that both auxiliary variables have minimum correlation. Mean square error and bias of proposed estimator in two-phase sampling is derived. Mean square error of proposed estimator shows an improvement over other well known estimators under the same case.

Real-Time, Variable-Depth Tillage for Managing Soil Compaction in Cotton Production

Cotton root growth is often hindered in the Southeastern U.S. due to the presence of root-restricting soil layers. Tillage must be used to temporarily remove this compacted soil layer to allow root growth to depths needed to sustain plants during periods of drought. However, the use of a uniform depth of tillage may be an inefficient use of energy due to the varying depth of this root-restricting layer. Therefore, the objective of this project was to develop and test equipment for controlling tillage depth “on-the-go” to match the soil physical parameters, and to determine the effects of site-specific tillage on soil physical properties, energy requirements, and plant responses in cotton production. Site-specific tillage operations reduced fuel consumption by 45% compared to conventional constant-depth tillage. Only 20% of the test field required tillage at recommended depth of 38-cm deep for Coastal Plain soils. Cotton taproot length in the variable-depth tillage plots was 96% longer than those in the no-till plots (39 vs. 19.8 cm). Statistically, there was no difference in cotton lint yield between conventional and the variable-depth tillage. Deep tillage (conventional or variable-rate) increased cotton lint yields by 20% compared to no-till.

应用于半导体激光器的高精度温控系统设计

面向半导体激光器温控系统的高精度、高速与高集成化的需求,设计了一款高精度、快速响应、高集成化、低成本的数模混合架构温控系统。该系统以FPGA为控制核心,硬件部分包括由三线制惠斯通电桥、仪表放大器、模数转换器组成的温度信号采集与调理模块,全桥降压电路驱动模块,热电制冷器模块等。针对热敏电阻和电桥的非线性误差,提出了一种可变控温零点的温度信号调理方法,该方法基于迭代与多目标最优化算法,提高了控温精度,同时降低了仪表放大器与模数转换器的指标要求,从而降低了系统成本。针对温度滞后大、延迟高的特点,控温策略采用了抗饱和积分的PID(AWPID)自动控制方法,从而降低超调,加快收敛速度。测试结果表明,该温控系统在-45~75℃的温度范围内,实现了±0.02℃的控温精度,相较于固定控温零点的温控系统最大0.1951℃的控温精度提高了89.7%。与传统PID控制算法相比,AWPID控制算法将超调从9.13%降低到1.5%,将稳定时间从41 s降低到30 s。稳定性测试表明,该温控系统能够在长时间内保持±0.02℃的控温精度,满足稳定性要求。该系统具有高精度、快速响应、高集成化、低成本的特点,为半导体激光器的复杂应用场景提供了高精度的温度保障。

精准变量全幅式物料施撒装置的设计与仿真分析

为进一步解决风沙土改良作业机械化率低的问题,提高改土材料机械化铺施效率,提出了一种精准可控变量的固体物料施撒方案,设计了一种精准变量全幅式物料施撒装置。通过对物料施撒过程的受力和运动分析,以物料颗粒为研究对象,建立其在幅板上运动的动力学模型。基于离散元法对物料施撒过程进行仿真试验研究,建立试验因素与试验指标之间的二次回归模型,并进行单因素影响分析、方差分析及目标参数优化。结果表明:各因素对分布变异系数影响大小的先后顺序分别为调量板、排肥轮轴转速、幅板个数;经过中心组合响应曲面试验设计进行参数优化可知:当幅板个数为7、调量板位置为0mm、排肥轮轴转速为40r/min时,分布变异系数最小为7.36%,铺料最均匀,厚度最大,满足施撒作业的要求。研究结果可为风沙土改良机械及农业固体施肥机械设计提供参考。

基于对象阈值变精度概念的启发式推荐方法

针对启发式概念推荐方法进行优化,提出一种基于对象阈值变精度概念的启发式推荐方法。将模糊形式背景转化为对象阈值可变的变精度形式背景,在此形式背景的基础上定义概念构造的启发式信息;利用内涵约束,在保证群组相似度的基础上,构造当前加权面积最大的概念,将这些概念组成强概念集合;在这个概念集合中利用组推荐方法对所有用户进行推荐。实验在MovieLens系列数据集和FilmTrust数据集上的一系列结果验证这种优化是有效的,能够大幅加强推荐的精度和性能。

基于农药喷施溯源的精准变量喷药监控系统设计与试验

针对现有大田精准施药系统主要以药量变量控制为主,缺乏农药喷施作业数据远程监测与溯源管理等问题,本文设计了基于农药喷施溯源的精准变量喷药监控系统,可实现农药精准变量喷施,作业地块、作业时间、作业面积、农药种类与配比、喷施药量、喷雾压力、实时流量和作业速度等信息的在线监测、实时显示和溯源管理。基于该系统分别开展了施药量计算精度、作业面积计算精度、物联网数据传输稳定性、变量调控系统动态响应、变量调控精度和农药喷施均匀性等试验。试验结果表明,北斗定位测速最大误差为1.33%,平均误差为0.82%,施药量计算误差为1.73%,作业面积计算误差为2.61%,数据丢失率为3.51%;速度连续变化下系统稳定调节时间为4~5 s;不同设定施药量和作业速度下,变量调控精度误差为2.45%;雾滴沉积点密度大于20滴/cm^(2)下,在喷雾机行走和喷雾方向上的喷雾覆盖率变异系数均小于10%,满足精准变量作业要求。本研究可在实现药量变量调控下对农药喷施数据进行溯源管理,为后续开展大田作物农药残留风险评估提供支撑。

一种两级螺旋精准变量自动对靶遥控施肥装置的研究与试验

针对目前螺旋施肥装置在果园施肥过程中排肥脉动较大导致排肥均匀性差和排肥稳定性低等问题,研制了一种两级螺旋施肥装置.采用EDEM仿真软件进行了侧面排肥口开口角度的优化,研究了该施肥装置上下两级螺杆不同转速比对排肥均匀性和稳定性的影响;室内台架试验标定了复合肥、尿素、有机肥的单圈排肥量,并建立了排肥控制模型;设计了以STM32F103RCT6单片机为核心的精准变量自动对靶遥控施肥控制系统;通过室外大棚果园试验检验了该装置的对靶精度与排肥性能.仿真结果表明:排肥口开口角度和上下两级螺杆不同转速比会影响该施肥装置的排肥均匀性和稳定性,且最佳开口角度为50°,最佳转速比为1∶1.5,其排肥均匀性变异系数的均值为7.35%,肥料填充系数方差为0.009.室内台架试验结果表明:当电机转速在120 r/min内时,3种肥料实际单圈排肥量与理论单圈排肥量相对误差最大为3.37%,单圈排肥稳定性变异系数最大为2.83%,该装置排肥准确且单圈排肥量稳定.室外大棚果园试验结果表明:单棵柑橘树实际排肥量与给定排肥量相对误差最大为4.35%;自动对靶起点误差最大为0.17 m,终点误差最大为0.08 m,且肥料掉落位置均在柑橘树冠层直径内;排肥稳定性变异系数最大为7.22%;3种肥料中排肥均匀性变异系数最大为6.41%.该装置有效减小了排肥脉动,提高了排肥性能,且对靶误差小,满足果园精准变量自动对靶遥控施肥要求.该研究以期为两级螺旋施肥装置排肥脉动问题的优化提供理论依据,并为精准变量施肥提供技术参考.

传递矩阵法在计算输流管路高频振动时的稳定性改进

传递矩阵法(transfer matrix method,TMM)是研究结构振动时常用的计算方法,但在计算大跨度输流管路高频横向振动时,TMM存在数值不稳定的现象,制约了其进一步应用。基于无量纲化计算结果得到的子单元划分准则的全局传递矩阵法(global transfer matrix method,GTMM)、混合能传递矩阵法(hybrid energy transfer matrix method,HETMM)和结合变精度算法的传递矩阵法(variable precision algorithm-transfer matrix method,VPA-TMM)等三种方法解决了这一问题。GTMM是最常用的TMM计算稳定性改进方法;HETMM系首次从层状介质中的波传播计算扩展到管路系统的振动分析领域,计算矩阵的维度和形式不随子单元数的变化而变化,计算时间最短;VPA-TMM无需进行子单元划分,可以看作是从根源上解决了TMM的长跨度高频计算失稳问题,但计算时间会大幅度增加。

覆盖变精度粗糙区间直觉模糊集模型探究

概述区间直觉模糊集的基本理论,利用所定义的平均隶属度、平均非隶属度,建立基于覆盖的变精度粗糙区间直觉模糊集的4种模型,并讨论这4种模型的一些相关性质、与现有模型的关系以及4种模型之间的关系;最后,对4种模型进行实例分析。

PRECISE ASYMPTOTICS IN THE BAUM-KATZ AND DAVIS LAW OF LARGE NUMBERS FOR POSITIVELY ASSOCIATED SEQUENCES

Let {X_i;i≥1} be a strictly stationary sequence of associated random variables with mean zero and let σ2=EX2_1+2∞_~j=2 EX_1X_j with 0<σ2<∞.Set S_n=n_~i=1 X_i,the precise asymptotics for _~n≥1 n^rp-2 P(|S_n|≥εn^1p ),_~n≥1 1nP(|S_n|≥εn^1p ) and _~n≥1 (log n)δnP(|S_n|≥εnlogn) as ε0 are established.