三苯基2-吡啶乙酸脂硫氰酸根离子电极的研究

该文首次研究以三苯基2-吡啶乙酸脂为中性载体,制备了一种呈现出反Hofmeister选择性行为的PVC膜电极,其对硫氰酸根离子(SCN-)具有优良的电位响应特性,该电极在pH 5.0的磷酸盐缓冲体系中具有最佳的电位响应,在1.0×10-1-5.0×10-5moVL SCN-浓度范围呈近能斯特响应,斜率为52.7 mY/dec(25℃),检测下限为2.0×10-5mol/L.采用交流阻抗和光谱分析技术初步研究了载体与SCN-之间的作用关系.     

数控机床之数控系统的诊断与维护

通过对数控机床的构成与特点的概述,进而对数控系统的常见故障进行了分析,并对数控系统的故障诊断与维护方法,以及应注意的事项作了较为详细的阐述。     

"机器学习"的研究步骤--简述科学研究的一般过程

提出了一般基础科学的过程,然后以计算机科学中人工智能领域的机器学习的研究进程中为例,阐述阐述了一般科学研究的5个基本步骤,最后加以总结,认为进行科学研究时,不能忽略科学研究的本质,应具体情况具体分析。     

Study on hydrogen sulfide removal based on bench-scale experiment by bio-trickling filter

A bench-scale experiment for control of hydrogen sulfide (H2S) emissions was carried out continuously for nearly four months by using bio-trickling filter packed with ZX01 stuffing. The results suggested that the bio-trickling filter had proven excellent performance over substantial operational periods. Removal efficiency of H2S was nearly 100% when volumetric loading of the bio-trickling filter varied from 0.64 g/(m3·h) to 38.20 g/(m3·h) and metabolism products of H2S were mainly composed of SO42–. When inlet concentration of H2S was 250 mg/m3, the optimum gas retention time was 30 s and the optimum spray water flow rate was 0.005 9~0.012 L/(cm2·h). The bio-trickling filter had good ability to resist shock of high volumetric loading, and was not blocked during experiments for nearly four months during which resistance was maintained at relatively lower value, so that the bio-trickling filter need not carry out back washing frequently and can be operated steadily for long-term.     

A new optimization algorithm based on chaos

INTRODUCTION Chaos (Wang et al., 2002) is a common nonlin- ear phenomenon, whose action is complex and similar to that of randomness. The characteristics of chaos being highly sensitive to the initial value of chaos make a world of differences due to the ergodic prop- erty of the phase space—chaos can go through all states in certain ranges without repetition; the inher- ent randomness of the system—means that chaos behavior is similar to randomness which is disorderly; but at the same t…     

现代农业企业机器选型配套决策框架模型及其应用

本文在认识现代农业企业机器造型配套重要性的基础上,详细分析了其中5个主要的决策目标和依靠这些目标所建立的相应的决策框架模型,并用此模型解决了一个基本的决策问题。     

基于主成分分析的人耳识别系统研究

针对人耳识别技术的研究现状,采用主成分分析提取人耳图像特征,在此基础上建立一个人耳识别系统。实验结果验证了利用主成分分析提取人耳图像特征的可行性与高效性,为解决该类问题提供了一个有效的新途径。     

基于语义的启发式病毒检测引擎研究

对形式化语义在启发式病毒检测引擎上的应用进行了研究,分析了基于虚拟机技术的反病毒检测引擎的效率问题及启发式病毒检测引擎,发现其规则的选取对病毒判断的准确率影响很大。提出基于形式化语义的启发式病毒检测引擎．进行了计算机病毒语义关系框架及数据结构的设计,通过深入剖析不同病毒程序传染部分的代码结构,总结出病毒程序的典型语义特征,形成描述其典型语义特征的语义关系框架;在检测时抽取蕴涵在待检程序中的语义,进而建立描述程序语义关系框架;计算二者的匹配程度来确定程序是否含有恶意程序,从而达到检测未知病毒的目的．     

基于改进谱聚类算法的生物制药产业专利价值评估研究

有效评估药物专利价值有必要考虑制药基础技术细节以及新药专利保护期限较长的特殊性等有关实际，同时，利用机器学习方法开展专利价值评估的研究仍有待进一步完善，因此，针对生物制药产业专利价值评估准确性问题，结合产业技术因素及其专利特点，以及专利价值评估的共性指标和生物制药产业特征与专利技术特点的个性指标，引入自编码器（AE）模型和谱聚类算法（SC）构建专利价值评估算法模型，以药智专利通数据库的相关专利数据为样本进行实证分析，通过提取专利指标特征、专利聚类来进行专利价值评估，并运用支持向量机方法对专利价值进行分类，以验证AE-SC评估模型的有效性。结果表明：AE-SC评估模型通过自编码器提取专利特征后的专利价值聚类准确度优于谱聚类和传统K-means聚类；专利存在年数、药物专利类型、适应证类别等是评价生物制药产业专利价值必要考虑因素。     

Assessing behavioral data science privacy issues in government artificial intelligence deployment

In today's global culture where the Internet has established itself as the main tool for communication and commerce, the capability to massively analyze and predict citizens' behavior has become a priority for governments in terms of collective intelligence and security. At the same time, in the context of novel possibilities that artificial intelligence (AI) brings to governments in terms of understanding and developing collective behavior analysis, important concerns related to citizens' privacy have emerged. In order to identify the main uses that governments make of AI and to define citizens' concerns about their privacy, in the present study, we undertook a systematic review of the literature, conducted in-depth interviews, and applied data-mining techniques. Based on our results, we classified and discussed the risks to citizens' privacy according to the types of AI strategies used by governments that may affect collective behavior and cause massive behavior modification. Our results revealed 11 uses of AI strategies used by the government to improve their interaction with citizens, organizations in cities, services provided by public institutions or the economy, among other areas. In relation to citizens' privacy when AI is used by governments, we identified 8 topics related to human behavior predictions, intelligence decision making, decision automation, digital surveillance, data privacy law and regulation, and the risk of behavior modification. The paper concludes with a discussion of the development of regulations focused on the ethical design of citizen data collection, where implications for governments are presented aimed at regulating security, ethics, and data privacy. Additionally, we propose a research agenda composed by 16 research questions to be investigated in further research.