基于数据挖掘技术的BBS的安全管理

随着万维网WWW的发展，BBS在为广大网络用户提供自由交流空间的同时也带来了对用户言论的安全管理问题。在BBS的安全管理中引入数据挖掘技术，详细分析BBS的功能和分类，并给出数据挖掘技术在BBS安全管理中应用的简要过程。     

高职护生早期接触临床的实践与思考

目的让高职护理专业一、二年级学生提前接触临床,培养学生的临床思维能力和动手能力,调动其学习积极性,尽早进入职业角色。方法对高职护理专业2008级学生260人、2009级学生340人分批到教学医院进行见习,发放回顾性评价表进行效果评价。结果 72.49%的学生认为早期接触临床使他们各方面受益匪浅;通过见习、观摩等,及早熟悉医院环境,尽早熟悉专业及职业特点,对学习专业课有促进作用。结论合理安排时间让学生提前进入临床,及早培养临床综合素质,对提高高职护生的职业能力及培养高素质的技能型应用型人才具有重要意义。     

基于风险值自动计算—信息多维采集的农药残留大数据评估市售果蔬安全水平

采用食品安全指数和风险系数模型,初步建立了农药残留膳食暴露风险和预警风险评估体系。开发"风险值自动计算—信息多维采集与分析"定制软件,基于2012—2015年我国市售果蔬农残检测大数据,从农药种类、限量标准、果蔬种类、地域等多个维度,分别对果蔬中残留农药之于人体的膳食暴露风险、预警风险进行了评估和解析。结果显示,气相色谱-四极杆-飞行时间质谱(GC-Q-TOF/MS)和液相色谱-四极杆-飞行时间质谱(LC-Q-TOF/MS)技术侦测的9 823例和12 551例市售果蔬,绝大多数膳食风险为可接受,但仍有0.56%和0.54%为风险不可接受。禁用农药膳食暴露风险不可接受比例是非禁用农药的20倍(GC-Q-TOF/MS组)和55倍(LC-Q-TOF/MS组);禁用农药高度预警风险比例是非禁用农药的17倍(GC-Q-TOF/MS组)和23倍(LC-Q-TOF/MS组),可见农药残留风险亟需控制,尤其应严格监管"禁药禁用"。文章据以上评估给出了高风险排名前10的农药和果蔬。另外,还发现欧盟的农药最大残留限量标准(MRLs)明显严于我国,我国相关标准建立亟待加快。研究结果可作为果蔬等食品风险水平实时诊断和风险农药精准监管的重要依据,以减少食源性农药残留风险,保障食品安全。     

我国人工智能政策特征与PMC模型量化评价研究

探讨我国人工智能政策特征以优化政策设计思路，以中央部委与地方政府印发的31份人工智能政策文件为研究样本，综合运用文本挖掘、内容分析和PMC指数模型等方法，提炼人工智能领域的研究前沿与热点分布、人工智能的政策特征以及评价结果。研究发现：我国人工智能政策以智能化为主要目标，重点关注科技研发与创新环节，并对“卡脖子”的芯片、机器人产品提出政策规范；政策工具应用不平衡，对政府采购、对外贸易管制、反他国管制、购置补贴四项需求型政策工具重视度不够；总体政策效力较好，但政策之间具有效力差异性，相关政策条款亟待加强和完善。基于以上特征和问题，建议进一步促进人工智能前沿政策的设计与前瞻，加大需求端政策工具的组合性和灵活性应用、优化供需政策工具包，加强对人工智能领域的监管政策力度，开展人工智能政策系统的整体性评估。     

News-based business sentiment and its properties as an economic index

This paper presents an approach to measuring business sentiment based on textual data. Business sentiment has been measured by traditional surveys, which are costly and time-consuming to conduct. To address the issues, we take advantage of daily newspaper articles and adopt a self-attention-based model to define a business sentiment index, named S-APIR, where outlier detection models are investigated to properly handle various genres of news articles. Moreover, we propose a simple approach to temporally analyzing how much any given event contributed to the predicted business sentiment index. To demonstrate the validity of the proposed approach, an extensive analysis is carried out on 12 years’ worth of newspaper articles. The analysis shows that the S-APIR index is strongly and positively correlated with established survey-based index (up to correlation coefficient $r=0.937$) and that the outlier detection is effective especially for a general newspaper. Also, S-APIR is compared with a variety of economic indices, revealing the properties of S-APIR that it reflects the trend of the macroeconomy as well as the economic outlook and sentiment of economic agents. Moreover, to illustrate how S-APIR could benefit economists and policymakers, several events are analyzed with respect to their impacts on business sentiment over time.