超临界乙醇抽提废弃线路板的实验研究

以超临界乙醇为抽提溶剂,在反应温度为280℃、反应压力为7.4MPa、反应时间为60min的条件下对FR-4型溴化环氧树脂基板进行超临界乙醇抽提实验研究,并对其抽提液体和固体产物进行分析,计算其抽提率和结焦率。结果表明,利用超临界乙醇抽提废弃线路板具有高抽提率和低结焦率的特点;抽提反应完成后废弃线路板各材料层之间分离效果明显,且玻璃纤维可以回收利用;液体产物中的主要成分是苯酚及其衍生物和微量的Br、P、S、N等化合物。     

苯酚高效降解菌的筛选及其降解特性研究

从某焦化厂处理废水的活性污泥中筛选到一株苯酚高效降解菌(Wust-C),该菌属革兰氏阴性菌.对Wust-C降解苯酚的特性进行试验研究.结果表明,在初始苯酚浓度为1 000 mg/L的试样中,培养24 h后,Wust-C对苯酚的降解率可达98％;初始苯酚浓度为300 mg/L试样中的苯酚可在8h内完全降解.采用海藻酸钠对菌体进行固定化后,Wust-C的降酚效率进一步得到提高.培养24 h后,固定化Wust-C对初始苯酚浓度为1 200 mg/L试样中的苯酚降解率达到100％,初始苯酚浓度为300 mg/L试样中的苯酚可在4h内完全降解.Wust-C的加入对混合菌群降解苯酚起到了促进作用.     

Study of IMT advanced heterogeneous network

Referring to research on the Heterogeneous Network(Het-Net) application scenario and technique characters in IMT-Advanced(The 4th Generation Mobile Communications) cellular system,this paper provides further analysis on main technique aspects of Heterogeneous Network,discussion on interference issue due to multi-layer building by access points and their corresponding solutions from standardization and engineering implementation. The proposed solution can effectively solve the interference problem in IMT-advanced Het-Net,and also improves the networking performance dramatically for future mobile communication systems.     

宜昌市近59年来的气候变化趋势分析

利用1951年9月～2010年8月宜昌站逐日气象资料,采用气候趋势系数、5a滑动平均法、累积距平和一元线性回归法对宜昌市近59年来的气候变化趋势特征进行了诊断分析,结果表明：宜昌市的年平均气温呈现上升趋势,年平均最低气温的上升速率高于年平均最高气温的上升速率,导致年平均日较差呈现下降的趋势;在季节变化上,除了夏季,其他季节都呈升高趋势,其中春季的上升趋势最为显著.年降水量呈现略微增加的趋势,冬季增加趋势较为显著.该成果对进一步研究和预测宜昌市的气候变化有着重要意义.     

Negation scope detection with a conditional random field model

Identifying negation cues and their scope in a text is an important subtask of information extrac-tion that can benefit other natural language processing tasks, including but not limited to medical da-ta mining, relation extraction, question answering and sentiment analysis.The tasks of negation cue and negation scope detection can be treated as sequence labelling problems.In this paper, a system is presented having two components: negation cue detection and negation scope detection.In the first phase, a conditional random field ( CRF) model is trained to detect the negation cues using a lexicon of negation words and some lexical and contextual features.Then, another CRF model is trained to detect the scope of each negation cue identified in the first phase, using basic lexical and contextual features.These two models are trained and tested using the dataset distributed within the*Sem Shared Task 2012 on resolving the scope and focus of negation.Experimental results show that the system outperformed all the systems submitted to this shared task.     

Research on stateful public key based secure data aggregation model for wireless sensor networks

Data aggregation technology reduces traffic overhead of wireless sensor network and extends effective working time of the network,yet continued operation of wireless sensor networks increases the probability of aggregation nodes being captured and probability of aggregated data being tampered.Thus it will seriously affect the security performance of the network.For network security issues,a stateful public key based SDAM (secure data aggregation model) is proposed for wireless sensor networks (WSNs),which employs a new stateful public key encryption to provide efficient end-to-end security.Moreover,the security aggregation model will not impose any bound on the aggregation function property,so as to realize the low cost and high security level at the same time.     

Image forgery detection using segmentation and swarm intelligent algorithm

Small or smooth cloned regions are difficult to be detected in image copy-move forgery (CMF) detection. Aiming at this problem, an effective method based on image segmentation and swarm intelligent (SI) algorithm is proposed. This method segments image into small nonoverlapping blocks. A calculation of smooth degree is given for each block. Test image is segmented into independent layers according to the smooth degree. SI algorithm is applied in finding the optimal detection parameters for each layer. These parameters are used to detect each layer by scale invariant features transform (SIFT)-based scheme, which can locate a mass of keypoints. The experimental results prove the good performance of the proposed method, which is effective to identify the CMF image with small or smooth cloned region.     

考虑变形影响的钢筋混凝土圆柱受剪承载力计算模型

准确计算钢筋混凝土(RC)圆柱的受剪承载力是进行延性抗震设计的关键,可有效防止脆性剪切和弯剪破坏模式发生。基于已有的RC圆柱拟静力试验结果,分析了RC圆柱的地震破坏模式和受剪承载力确定方法,在理论分析的基础上提出了考虑变形(位移延性)影响的RC圆柱受剪承载力计算模型,并与现有模型进行了比较。研究结果表明,地震作用下RC圆柱的受剪承载力随塑性铰区变形的增加而减小;弯剪破坏模式下,RC圆柱的受剪承载力取决于塑性铰区剪切破坏发生时对应的水平荷载而非骨架曲线上的峰值荷载;所提出的模型能有效反映变形对RC圆柱受剪承载力的影响,计算结果与试验数据吻合较好,可用于不同地震破坏模式RC圆柱受剪承载力计算。     

重庆地区4种不同蜜源原蜜的品质分析

【目的】了解重庆地区未加工原蜜的品质情况。【方法】对来自重庆地区的油菜(Brassica rapa var.oleifera)、五倍子(Rhus chinensis)、洋槐(Robinia pseudoacacia)、荆条(Vitex negundo var.heterophylla)等4种蜜源植物的9个原蜜样品进行了感官、理化、淀粉酶值、羟甲基糠醛(HMF)、微生物、农药残留等项目的检测。【结果】所有原蜜样品中:还原糖质量分数、酸度、淀粉酶值、HMF质量分数、细菌总数和农药残留均符合相关要求;水分质量分数均小于24%,属二级品;蔗糖质量分数均超过5%;霉菌和酵母计数均严重超标,其中酵母计数最高超标20倍。此外在南川油菜蜜的一个样品中检出微量甲萘威和涕灭威的残留。【结论】重庆地区的多种蜜源原蜜都存在水分、灰分及蔗糖质量分数较高,嗜渗酵母和霉菌超标,成熟度偏低等问题。
     

中文网络评论中的产品特征情感倾向提取算法研究

Web中的客户评论信息挖掘是大数据分析中的一项重要内容.分析客户评论中所包含的产品特征情感倾向,不仅可为消费者购买产品提供更具体的决策支持,还能有效帮助企业改进产品质量.针对商业应用的实际需要,提出了一种自动从中文客户评论中抽取产品特征并判断其情感倾向的方案.基于frequent pattern-tree (FP-tree)方法提取产品特征,结合基于语料库的方法和依存句法分析方法识别关于产品特征的主观评论语句、情感词及其情感词的依存关系,综合考虑情感词、否定词、程度词计算产品特征的情感倾向值.采用公开数据中的600篇手机评论作为实验数据,检验了算法的准确性.对比分析的结果说明,算法有很好的应用潜力,能够有效地从网络评论中获取有价值的商业信息.