An Image-Based Diagnostic Expert System for Corn Diseases

The annual worldwide yield losses due to pests are estimated to be billions of dollars. Integrated pest management （IPM） is one of the most important components of crop production in most agricultural areas of the world, and the effectiveness of crop protection depends on accurate and timely diagnosis of phytosanitary problems. Accurately identifying and treatment depends on the method which used in disease and insect pests diagnosis. Identifying plant diseases is usually difficult and requires a plant pathologist or well-trained technician to accurately describe the case. Moreover, quite a few diseases have similar symptoms making it difficult for non-experts to distinguish disease correctly. Another method of diagnosis depends on comparison of the concerned case with similar ones through one image or more of the symptoms and helps enormously in overcoming difficulties of non-experts. The old adage ＇a picture is worth a thousand words＇ is crucially relevant. Considering the user＇s capability to deal and interact with the expert system easily and clearly, a webbased diagnostic expert-system shell based on production rules （i.e., IF 〈 effects 〉 THEN 〈 causes 〉） and frames with a color image database was developed and applied to corn disease diagnosis as a case study. The expert-system shell was made on a 32-bit multimedia desktop microcomputer. The knowledge base had frames, production rules and synonym words as the result of interview and arrangement. It was desired that 80% of total frames used visual color image data to explain the meaning of observations and conclusions. Visual color image displays with the phrases of questions and answers from the expert system, enables users to identify any disease, makes the right decision, and chooses the right treatment. This may increase their level of understanding of corn disease diagnosis. The expert system can be applied to diagnosis of other plant pests or diseases by easy changes to the knowledge base.     

空间数据挖掘及其发展研究

探讨了空间关联规则,利用移动计算中基于Apriori算法的空间关联规则提取的例子,详细介绍了经典算法Apriori算法在空间关联规则中的应用,并对空间数据挖掘的发展进行了展望。     

大青沟自然保护区生态脆弱性系统诊断

本文通过样地调查、问卷调查,利用系统诊断技术对内蒙古大青沟国家级自然保护区生态脆弱性进行了诊断分析,针对影响该保护区脆弱性的58个相互关联的问题组成的“问题堆”,构建了问题间影响关系层次递阶结构图,使“问题堆”层次化、结构化和模块化,确诊了影响该保护区脆弱性的主要“病根”问题、基本问题、核心问题及问题间影响关系和解决途...     

布鲁氏菌病诊断方法的研究进展

近年来,布鲁氏菌病疫情在人、畜间呈逐年上升的趋势。不仅严重地威胁着人类健康,还影响着国民经济持续快速发展,成为世界性公共卫生问题。文章概述了目前中国动物布鲁氏菌病主要的实验室诊断方法以及国内外在本病诊断技术方面所取得的新进展,为中国研究更为快速、敏感、易于操作的布鲁氏菌病诊断技术提供参考,为快速、精确地诊断本病提供技术支持,以有效地防控本病。     

Three level direct torque predictive controlbased on fast virtual vector modulation

A novel scheme based on voltage prediction and fast virtual vector modulation algorithm for direct torque control of a permanent magnet synchronous motor fed by diode clamped multi level inverter is proposed.The system is based on diode clamped three level inverter,which is widely applied to middle high voltage speed regulation.Combined with space vector modulation,the reference voltage vector for direct torque control is obtained by voltage predictive control algorithm,then zero vector and two adjacent virtual vectors are used to synthesize reference voltage vector based on non orthogonal 60° coordinate.The neutral point potential is controlled by using the neutral point current characteristics of small vectors,the desired basic voltages and their dwelling time can be easily obtained and fast space vector modulation is achieved.Simulation results verify the feasibility of the proposed control scheme,that dv/dt of output voltage and neutral point potential of three level inverter are restrained effectively,and high dynamic and steady performances are obtained.     

基于分布式数据入侵检测模型研究

在数据挖掘技术应用于入侵检测的研究中,分布式环境下的全局频繁项目集的更新算法尚不多见。为改善入侵数据增加后,更新算法的效率问题,提出一种基于分布式入侵检测的关联规则快速更新算法TDUA(Trivial Distributed Update of Association rules)。算法引入强频繁项目集概念,有效地修剪候选项目集数目,采用共享模式的体系结构,具有通信代价较小,挖掘效率较高的特点。并从理论与实验两个方面验证了算法适应在高速大流量的分布式网络环境下快速准确地建立入侵检测模型。     

B型超声显像技术在实验猕猴繁殖中的应用

采用MEDISON SA-600型超声实时显像仪,以妊娠囊作为主要的判断依据,对658只配种实验猕猴进行早期妊娠诊断的探索。结果表明:妊娠15d诊断准确率为95.5%,20d诊断准确率为100%。同时对猕猴妊娠各期B超影像的特征及猕猴检测的操作特点进行论述。     

Cytologic,histologic, and immunohistochemical features of maxillofacial alveolar rhabdomyosarcoma in a juvenile dog

Abstract: A 15‐month‐old castrated male dog with a history of intermittent epistaxis and sneezing was admitted for the examination of a maxillofacial mass. An impression smear of a biopsy sample from the cauliflower‐shaped gingival mass contained numerous round cells, 5–25 μm in diameter, which contained a moderate amount of clear to pale blue cytoplasm and resembled lymphoid cells. Mitotic figures were frequently observed. The mass was diagnosed as malignant round cell neoplasia. On histologic examination the tumor was composed of diffusely arranged, small, atypical round cells with a small amount of fibrovascular stroma. Immunohistochemically, the cells were negative for CD3, CD18, CD20, CD79α, cytokeratin, melan‐A, chromogranin A, α‐smooth muscle actin, and myoglobin but positive for vimentin and desmin. The cells also had strong positive nuclear staining for myogenin and MyoD1. A diagnosis of solid‐pattern alveolar rhabdomyosarcoma was made on the basis of morphologic and immunohistochemical results. Alveolar rhabdomyosarcoma should be considered in the differential diagnosis of tumors in juvenile dogs, especially when cytologic findings reveal round, undifferentiated cells.     

肠侵袭性大肠杆菌感染野猪的诊断和药敏试验

无菌取病死野猪的心脏、肝脏、肺脏、脾脏及肾脏等组织病料,进行细菌的分离培养与PCR鉴定,分离出肠侵袭性大肠杆菌。结合临床症状、剖检病变和实验室诊断,从而确诊野猪病死于肠侵袭性大肠杆菌感染。并对分离菌株进行药敏试验,为野猪的肠侵袭性大肠杆菌感染疾病的诊断和防治提供参考。     

基于近红外技术的落叶松木材密度预测模型

运用近红外光谱对落叶松(Larix gemelinii Rupr)样品密度进行了研究,分别运用偏最小二乘法及主成分回归建立预测模型,并用建立的模型分别对每一个样品进行了预测。基于偏最小二乘法的校正模型及验证模型相关系数分别为0.964和0.918,校正标准误差及预测标准误差分别为0.016和0.021,模型预测值与实测值决定系数为0.93;主成分回归模型中,校正模型及验证模型相关系数分别为0.954和0.911,校正标准误差及预测标准误差分别为0.017和0.023,模型预测值与实测值决定系数为0.91。研究表明:基于主成分回归法与偏最小二乘法的近红外光谱分析建模,都可以实现对落叶松木材密度的有效预测,但相比较而言,偏最小二乘法略优于主成分回归法,所建立的模型对落叶松木材密度预测更加准确可靠。