基于Multi-class SVM的车辆换道行为识别模型研究

自动安全换道是车辆实现无人驾驶的关键,为精确识别行驶车辆换道状态,保证行车安全,设计了一种基于多分类支持向量机(Multi-class Support Vector Machine,Multiclass SVM)的车辆换道识别模型。从NGSIM数据集中选取美国101公路车辆轨迹数据进行分类处理,并将车辆换道过程划分为车辆跟驰阶段、车辆换道准备阶段和车辆换道执行阶段。采用网格搜索结合粒子群优化算法(Grid Search-PSO)对SVM模型中惩罚参数C和核参数g进行寻优标定,利用多分类支持向量机换道识别模型对样本数据进行训练和测试,模型测试精度达97.68%。研究表明,模型能够很好地识别车辆在换道过程中的行为状态,为车辆换道阶段的研究提供支持。     

A unique intelligent approach for forecasting project completion time in oil refineries

This study presents a hybrid approach for accurate forecasting of project completion time with noisy and uncertain safety factors in oil refineries. The hybrid approach is based on artificial neural network (ANN), fuzzy mathematical programming (FMP) and conventional regression. Three indictors, namely, number of occupational injuries, number of employees and ratio of maximum useful hours over useful hour per month are considered as inputs. Also, project completion time is considered as the main output. To achieve the objective of this study, five sets of data with respect to oil refinery construction projects in various cities of Iran are collected and analyzed through statistical methods. It is shown that for the actual case of this study, ANN presents lowest mean absolute percentage error (MAPE). Also, analysis of variance (ANOVA) is used to verify and validate the results of this study. This is the first study that presents a hybrid approach for accurate estimation and forecasting of project completion time with complex, noisy and uncertain occupational factors.     

矿井突水水源识别的RS-LSSVM模型

为了对矿井突水水源进行准确、高效的判别,综合考虑水化学特征,选取Ca~(2+),Mg~(2+),K~++Na~+,HCO-3,SO2-4,Cl~-和总硬度7个指标的质量浓度(mg/L)作为矿井突水水源的最初判别指标。利用粗糙集(RS)理论的属性约简来筛选水化学特征指标,用以作为水源识别的核心判别指标,建立基于RS的矿井突水水源识别的最小二乘支持向量机(LSSVM)模型。选用约简处理后的13组煤矿数据对模型进行训练,再用训练好的模型对另外12组突水数据进行水源判别,并与未进行属性约简的LSSVM模型及Fisher判别分析法、随机森林方法进行对比。结果表明,利用属性约简方法可以很好地排除原始数据中的冗余信息干扰,因而能有效判别矿井突水水源,使矿井突水水源模型的误判率降低至0;而且指标约简过程可以降低LSSVM运算的复杂度,也能够提高判别效率。     

基于灰色支持向量机组合模型的我国火电NOx排放量预测

区域火电NO_x排放量的预测属于小样本、贫信息的灰色系统. 由于NO_x排放量受多个因素的叠加性影响,单一预测模型难以准确反映NO_x排放量的复杂变化,易产生较大的预测误差. 基于此,利用灰色预测理论和支持向量机预测理论,建立了火电NO_x排放量组合优化预测模型. 采用国家权威部门发布的火电NO_x排放量数据,综合考虑影响我国火电NO_x排放量的主要因素,对我国2008—2010年以及2020年的火电NO_x排放量进行了预测,预测结果与官方公布的实际值基本一致; 同时,预测的时间大大缩短.      

Exploring the influence of lake water chemistry on chlorophyll a: A multivariate statistical model analysis

A multivariate statistical approach integrating the absolute principal components score (APCS) and multivariate linear regression (APCS-MLR), along with structural equation modeling (SEM), was used to model the influence of water chemistry variables on chlorophyll a (Chl a) in Lake Qilu, a severely polluted lake in southwestern China. Water quality was surveyed monthly from 2000 to 2005. APCS-MLR was used to identify key water chemistry variables, mine data for SEM, and predict Chl a. Seven principal components (PCs) were determined as eigenvalues >1, which explained 68.67% of the original variance. Four PCs were selected to predict Chl a using APCS-MLR. The results showed a good fit between the observed data and modeled values, with R² = 0.80. For SEM, Chl a and eight variables were used: NH₄-N (ammonia-nitrogen), total phosphorus (TP), Secchi disc depth (SD), cyanide (CN), arsenic (As), cadmium (Cd), fluoride (F), and temperature (T). A conceptual model was established to describe the relationships among the water chemistry variables and Chl a. Four latent variables were also introduced: physical factors, nutrients, toxic substances, and phytoplankton. In general, the SEM demonstrated good agreement between the sample covariance matrix of observed variables and the model-implied covariance matrix. Among the water chemistry factors, T and TP had the greatest positive influence on Chl a, whereas SD had the largest negative influence. These results will help researchers and decision-makers to better understand the influence of water chemistry on phytoplankton and to manage eutrophication adaptively in Lake Qilu.     

基于自然环境中优选药物的毒性和生态毒理风险研究

在如今超过1 500种在用原料药中,环境中发现几率明确和对环境影响明确的原料药所占比例很小。由于很难监管所有在用原料药,众多先前的研究提议将原料药按照受关注程度排序,从而可以将研究资源集中于那些最受瞩目的药物。然而这些研究都存在局限性,本文从之前优先性方法的实践经验出发,提出了一种更为全面的原料药排序方法。该方法基于对水生生物、土壤生物、鸟类、野生哺乳动物和人类的风险,综合考虑了食物链顶端存在的生态毒理学研究终点和由这些治疗性药物作用机制带来的非顶端效果。对于在英国社区以及医院设置中使用的146种活性药物的分析可以更为详细地说明该方法的运用。根据这一方法,我们将16种化合物列为优先考虑的药物。这些药物包括了抗生素、抗抑郁药、抗炎药、抗糖尿病药、抗肥胖药、雌激素类化合物以及相关的代谢产物。我们建议这种优先性方法在将来可以更广泛地应用于世界上不同的地区。
精选自Jiahua Guo, Chris J. Sinclair, Katherine Selby, Alistair B.A. Boxall. Toxicological and ecotoxicological risk based prioritisation of pharmaceuticals in the natural environment. Environmental Toxicology and Chemistry: Volume 35, Issue 7, pages 1550–1559, July 2016. DOI: 10.1002/etc.3319
详情请见http://onlinelibrary.wiley.com/doi/10.1002/etc.3319/full
     

Relationships between exposure to polyhalogenated aromatic hydrocarbons and organochlorine pesticides and the risk for developing type 2 diabetes: a systematic review and a meta-analysis of exposures to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)

A systematic review was performed to evaluate the association between environmental exposures to polyhalogenated aromatic hydrocarbons (PHAHs) and organochlorine (OC) pesticides and the risk for type 2 diabetes (T2D). Searches of EMbase, Google Scholar, Medline, and Scopus were performed. Reports were included if they were original human studies whose design included a control group and if the sample size was larger than 10 participants per group. The articles were excluded if the type of diabetes was unknown or Type 1. Odds ratios (OR), 95% confidence intervals (CI), and modified Naranjo scores for the effects of environmental contaminants were determined for each study. Of the 35 eligible studies, six were included in the meta-analysis; these focused specifically on 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Meta-analysis of these studies showed no significant increased OR for the development of T2D from exposure to TCDD. However, subgroup analysis showed significant elevated OR for the development of T2D if exposure is repeated and accompanied by exposure to other persistent pesticides (OR?=?1.48; 1.10–1.90) but a decreased odds for T2D with exposure resulting from accidental exposure (OR?=?0.46; 0.39–0.52). Our results suggest that there are significant risks of developing T2D in populations with recurring exposures to TCDD in concert with other persistent chlorinated pesticides. A mean Naranjo score of 2.0 was determined for all 35 articles; this score was 2.5 when examining only TCDD studies and 2.1 when examining studies that looked only at T2D. Each of these Naranjo scores suggests a possible association between the prevalence of T2D and exposure to PHAHs or OC pesticides.     

基于基团贡献法的有机化合物好氧生物降解预测模型研究

从MITI-Ⅰ试验中筛选出587种不同类型有机化合物的可用数据,通过对这些物质的结构进行拆分,随机选择其中50种化合物作为验证集,另外537种作为训练集,利用多元线性回归(MLR)和支持向量机(SVM)2种计算方法分别建立模型。结果表明,芳香酸、醛、芳香碘和叔胺等功能基团对有机化合物的好氧生物降解性影响较大;MLR模型总体预测正确率为81.43%,验证集正确率为82%,SVM模型总体预测正确率为87.90%,验证集正确率为86%。所建立的2种定量结构与生物降解性关系(QSBR)模型有效,可用于化学品的好氧生物降解性评价。     

荧光抗辐射菌的构建及其稳定性

将构建的抗辐射菌属-大肠杆菌间的泛用穿梭表达载体pZTGL2导入抗辐射菌Deinococcus grandis,进行了荧光标识抗辐射菌的构建及其在没有抗生素的非选择性培养基中继代培养后的稳定性分析.结果表明,导入泛用穿梭表达载体pZTGL2后的D.grandis具有荧光活性,荧光标识的D.grandis在没有抗生素的培养基中经14 d继代培养后的最佳培养温度及其生长状况等生物学特性与未标识的D.grandis没有明显差异.进一步对荧光标识D.grandis在非选择性培养基中经14 d继代培养后的稳定性进行了调查,结果表明:荧光标识的D.grandis在没有抗生素的培养基中经过14 d的继代培养后的荧光活性与没有经过继代培养的荧光标识的D.grandis无显著差异,而且也没有改变荧光标识的D.grandis对γ-射线的抗性.由以上结果认为:成功构建了荧光标识的抗辐射菌D.grandis,荧光标识的D.grandis在非选择培养基中继代培养后仍能表现出良好的结构稳定性.图4表1参18     

Ports’ service attributes for ship navigation safety

The purpose of this paper is to discuss the service attributes of ports for ship navigation safety. Based on the relevant literature and the features of ship navigation in ports, the service attributes of ports for ship navigation were first investigated. A fuzzy AHP model was then used to identify those attributes from shipmasters’ perspectives. Finally, a Dissatisfaction Attitude (DA) index was used to determine the attributes’ priorities, by which the port authorities may make policies for improving ship navigation safety. As an empirical study, the shipmasters berthing their ships in Kaohsiung Port were surveyed to validate the model. The result constructs 19 port service attributes (SAs) for ship navigation safety, in which, the shipmasters place more emphasis on the SAs of operators’ professional literacy, including the marine pilot’s professional and English communication abilities, the VTC (Vessel Traffic Center) regulator’s professional and English communication abilities, and the tugboat driver’s skills. While, for Kaohsiung Port, currently, the traffic control of fairway is the most important aspect to be improved. The theoretical and managerial implications of the findings for port authorities in improving ship navigation safety are discussed.