Two-Phase Algorithm for Multi-warehouse and Multi-task Based Logistics Delivery

To a scaled logistic company, assigning is an important part of logistic, and further development will make the optimized assigning of multi-warehouse and multi-task possible. This paper provided a two-phase multi-warehouse and multi-task based algorithm which has two phases. In the first phase, it combines sweep algorithm, saving algorithm and virtual task point to present a method. And in the second phase it provides an algorithm for the arrangement of goods loading which is based on the constraints of time-window and attributes of goods and vehicle. It uses the computing results of the first phase to form more detailed delivery scheme based on the constraints of time-window and attributes of vehicle and goods.

Intelligent Transportation System and Night Delivery Schemes for City Logistics

Intelligent Transportation System （ITS） integrates information and communication technologies with location based technologies into roads, vehicles, traffic and transport management systems. Application of ITS can improve situation in major cities where due to the increasing number of residents and level of motorization traffic congestion represents important issue. Another problem arises from this facts and that is that cities have contradictory needs as grooving need for goods within urban areas as well as need for less vehicles in the same area. The urban logistics activities by private companies within urban areas represent an integral part of city logistics that aims to improve the efficiency of urban freight transportation, reduce traffic congestion, mitigate environmental impacts, reduce costs and fuel consumption. This research presents application of ITS technologies and vehicle routing problem for night delivery scheme planning as one of the core techniques for modelling city logistics.

Multiple vehicle routing problem integrated reverse logistics with fuzzy reverse demands

A new type of vehicle routing problem （VRP）, multiple vehicle routing problem integrated reverse logistics （MVRPRL）, is studied. In this problem, there is delivery or pickup （or both） and uncertain features in the demands of the clients. The deliveries of every client as uncertain parameters are expressed as triangular fuzzy numbers. In order to describe MVRPRL, a multi-objective fuzzy programming model with credibility measure theory is constructed. Then the simulationbased tabu search algorithm combining inter-route and intra-route neighborhoods and embedded restarts are designed to solve it. Computational results show that the tabu search algorithm developed is superior to sweep algorithms and that compared with handling each on separate routes, the transportation costs can be reduced by 43% through combining pickups with deliveries.

Non-Medical Determinants of Caesarean Deliveries in Ghana: A Logistic Regression Approach

This study examined the non-medical factors that influence expectant mothers to opt for caesarean deliveries in Ghana. Data on 395 expectant mothers across the ten regions of Ghana who were located in urban, semi-rural and rural areas, and spanned a period of five years (from 2012 to 2016) were obtained from the Ghana Health Service. In fitting the logistic regression model, data on 355 expectant mothers (i.e. 89.9% of the data) was assigned to the analysis sample while 40 (i.e. 10.1%) was assigned to the hold-out sample. The hold-out sample together with other statistical measures of overall model fit, pseudo R2 measures and classification accuracy were used to validate the results obtained from the analysis sample. Significance was tested at p = 0.05. Determinants including, educational level of expectant mother, parity of expectant mother, baby’s birth weight, previous caesarean delivery, location of expectant mother, age of expectant mother and, period within the year of childbirth had a significant effect on caesarean delivery. The study recommended that health practitioners should be able to foretell expectant mothers who are likely to undergo caesarean delivery in order for them to prepare financially and psychologically to avoid further complications. Due to the significant positive attitude of women towards caesarean delivery rather than normal delivery, it is necessary to inform them about the advantages of normal delivery and the health hazards associated with caesarean delivery to the mother and child.

Influence and Application of Cloud Logistics Mode on Express Service

In this paper, we first introduced the concept of cloud logistics, described the current status of the express delivery and analyzed the impacts of introducing cloud logistics on China’s express delivery industry. Then based on the case of Stars Express, how to introduce the cloud logistics model to the express industry was discussed. Finally, a new model of cloud logistics platform was constructed.

早产预测多因素logistic回归模型的建立及预测价值的评价

目的建立多因素logistic回归模型来预测早产。方法对孕24~35周有先兆早产症状的孕妇检测阴道分泌物中胎儿纤维连接蛋白(fFN),经腹部超声测量宫颈长度,记录妊娠终止的孕周。经单因素logistic回归分析筛选与早产有相关性的因素建立多因素logistic回归模型。结果逐步回归分析得出以双胎妊娠、受孕方式、fFN检测及宫颈长度为自变量的早产预测的logistic回归模型,拟合优度检验P=0.99,ROC曲线下面积为0.97,以P=0.25为分界点预测早产灵敏度为91.3%,特异度为90.3%。结论本研究建立的多因素logistic回归模型对早产具有较好的预测价值。

应用条件Logistic回归分析探讨早产的危险因素

目的采用条件Logistic回归分析方法探讨早产的危险因素。方法回顾性分析112例早产和按1∶1配比选择的足月产的产妇资料,对可能引起早产的危险因素进行单因素分析以及条件Logistic回归分析。结果单因素分析共筛选出25个可能与早产有关的因素,然后经过条件Logistic回归分析,发现产前检查次数、孕期负性事件、孕期体重增加、孕期吸烟(孕妇或丈夫)、胎膜早破、妊娠高血压综合征、前置胎盘和是否臀位等8个因素与早产有关,其中产前检查次数、孕期体重增加为早产的保护因素,余为危险因素。结论早产是多因素综合作用的结果,应针对危险因素尽早采取综合性控制措施以减少早产的发生。

基于Logistic回归模型分析影响产科住院分娩费用的因素

目的探索基于Logistic回归模型对产科住院分娩费用的分析运用方法。方法通过选取2007～2010年产科分娩病例作为研究对象,观察产科分娩费用的影响因素。以Logistic回归模型(多水平模型)对产科住院分娩费用进行分析处理,第一层以住院患者个体,第二层以医疗付款方式,拟合两水平模型对费用影响因素分析。结果 Logistic回归模型适用于分析评价住院费用类的数据。结论产科分娩费用的分析评价基于Logistic回归模型的研究结果会更科学。

头位阴道分娩会阴切开影响因素Logistic回归分析

目的探讨头位阴道分娩会阴切开影响因素,为减少会阴切开率提供科学依据。方法 2016年9—12月选取我院头位经阴道分娩产妇418例,其中会阴切开189例,会阴撕裂228例,对可能引起会阴切开的13项因素进行单因素分析和Logistic回归分析。结果多因素Logistic回归分析显示:经产是会阴切开的保护因素,胎心变异、会阴条件差、第2产程时间延长、产力异常、产妇配合度差、早产、妊娠合并症及胎头较硬8项因素为会阴切开的危险因素(P<0.05),决定系数R^2为0.651。结论经产妇是会阴切开的保护因素,会阴切开危险因素包括胎心变异、会阴条件、第2产程时间、产力、产妇的配合度、孕周、妊娠合并症及胎头硬度。产程中应加强母儿观察,动态评估产程变化,综合分析,权衡利弊,最大程度降低会阴切开率。

早产影响因素的多分类Logistic回归分析

目的 探讨早产儿发生的危险因素。方法 采用病例对照研究法对 2 2 7名早产儿 (孕周 <33周 73人 ,33～ 36周 15 4人 )和 75 0名对照组进行相关因素调查 ,用多分类Logistic回归分析法进行危险因素分析。结果与分娩孕周 <33周早产儿有关的因素是 :母亲孕前体质指数≥ 2 8者、有人工流产史、孕早期发热、母亲文化水平为小学及以下者 ,首次产前检查血红蛋白低于 10 0g/L者、尿蛋白和尿糖阳性等因素是分娩孕周 <33周早产儿的危险因素。与分娩孕周在 33～ 36周早产儿有关的因素有 :母亲分娩年龄大于 35岁、母亲孕期吸烟及饮酒、年家庭收入低及父亲吸烟等因素。父亲职业为农民、多胎妊娠、孕期精神刺激、产前检查次数少、前置胎盘和妊高症等因素是二者的共同危险因素。结论 早产是多种因素联合作用的结果 ,应采取综合性措施降低早产儿的发生率。

基于Logistic模型的电子商务与快递业融合共生模式研究

在分析电子商务和快递业历史发展指标基础上,运用灰色关联理论计算电子商务与快递业关联系数;运用生物学领域中的共生理论,利用Logistic模型对电子商务与快递之间的共生关系进行研究,定量研究电子商务与快递之间的融合共生模式,利用共生模型研究两者之间的相互作用关系。研究表明,目前两者之间更加符合非对称性互惠共生。

Logistic回归及决策树模型在高龄剖宫产产妇产后出血影响因素分析中的应用

目的采用Logistic回归及卡方自动交互检测(chi-squared automatic interaction detector,CHAID)决策树分析高龄剖宫产产妇产后出血的影响因素,并比较两种方法的优缺点。方法选择某三级甲等医院2016年7月—2017年12月的高龄剖宫产产妇共1479例有效病历进行回顾性分析,建立Logistic回归和决策树模型,并比较两种模型的分析结果。结果Logistic回归显示,凝血功能障碍、宫缩乏力、胎盘粘连、年龄>40周岁、前置胎盘等是产后出血的危险因素(OR=10.842,P<0.001;OR=9.997,P<0.001;OR=9.457,P<0.001;OR=6.593,P<0.001;OR=5.881,P=0.003)。CHAID决策树分析结果显示,凝血功能障碍是产后出血的最主要因素,其次是胎盘粘连、宫缩乏力。结论Logistic回归模型及CHAID决策树模型在产后出血影响因素分析中均有一定的应用价值,建议将两种模型结合使用,更好地指导临床实践。

362例剖宫产后再妊娠妇女自然分娩影响因素Logistic回归模型构建及分析

目的分析剖宫产后再妊娠妇女自然分娩影响因素。方法选取郸城县妇幼保健院2019年12月至2021年2月期间收治的剖宫产后再妊娠妇女362例,参考自然分娩成功与否分为失败组(73例)与成功组(289例),收集全部研究对象临床资料,分析自然分娩的影响因素,构建Logistic回归预测模型。结果产前体质量指数、距上次剖宫产时长、家属态度、子宫下段厚度、胎儿体质量、胎头方位、子宫颈Bishop评分为剖宫产后再妊娠妇女自然分娩成功与否的影响因素(P<0.05);Logistic回归预测模型分析,产前体质量指数≥24 kg/m^(2)、距上次剖宫产时长≤3年、子宫下段厚度≤3.9 mm、胎儿体质量≥3.5 kg、枕后位与枕横位的胎头方位、子宫颈Bishop评分<6分为剖宫产后再妊娠妇女成功自然分娩的独立危险因素,试产家属态度为剖宫产后再妊娠妇女成功自然分娩的独立保护因素(P<0.05);似然比χ^(2)检验显示模型建立存在统计学意义;Waldχ^(2)检验显示模型构建有效;Hosmer-Lemeshow拟合优度检验显示模型拟合效果良好;受试者操作特征(ROC)曲线指出,Logistic回归预测模型预测剖宫产后再妊娠妇女成功自然分娩的AUC为0.901,95%CI为0.857~0.948,Z=10.587,P<0.001,敏感度为87.54%,特异度为79.45%。结论剖宫产后再妊娠妇女自然分娩与否与多个因素有关,其中产前体质量指数≥24 kg/m^(2)、距上次剖宫产时长≤3年、子宫下段厚度≤3.9 mm、胎儿体质量≥3.5 kg、枕后位与枕横位的胎头方位、子宫颈Bishop评分<6分为成功自然分娩的独立危险因素,试产家属态度为独立保护因素。

妇产科不同类型早产影响因素的Logistic回归分析

目的探讨妇产科差异性类型早产影响因素的Logistic回归分析。方法选取2018年9月至2019年11月本院收治的160例早产病例作为研究对象,根据早产类型分为自然早产组与干预性早产组,各80例,对其临床资料进行回顾性分析,统计发生早产的高危因素,并行多因素Logistic回归分析。结果自然早产组胎膜早破、宫内感染、阴道炎、不明原因各高危因素比例均高于干预性早产组(P<0.05),干预性早产组前置胎盘、胎儿窘迫、妊娠高血压各高危因素比例均高于自然早产组(P<0.05),两组瘢痕子宫、多胎妊娠、羊水过多、流产史、产次各高危因素比较差异无统计学意义;Logistic回归分析显示胎膜早破、宫内感染、阴道炎、不明原因、流产史、产次为导致自然早产的影响因素(P<0.05),前置胎盘、妊娠高血压、胎儿窘迫、流产史、产次为导致干预性早产的影响因素(P<0.05)。结论导致早产的影响因素较多,常见影响因素包括胎膜早破、前置胎盘、妊娠高血压等,临床应根据不同影响因素采取针对性防范措施,尽可能减少早产发生。

A Delivery Approach Modeling for Urban Freight Restocking

This paper proposes a modeling system developed in order to analyze the urban freight transport and logistics within urban and metropolitan areas. A review of models developed to simulate this segment of mobility is also reported. The review analysis highlights the limits of models for the ex-ante assessment of city logistics measures. For this reason this paper proposes a new modeling system approach for the assessment of city logistics measures. It is made of different steps approaching problems related to quantity OD （Origin-Destination） flows, restocking type OD flows, delivery OD flows, delivery OD flows for time slice and vehicle type, and vehicle OD flows. This modeling system has been specified and calibrated using some surveys carried out in the inner area of Rome where more than 500 truck drivers and more than 600 retailers have been interviewed.

基于Logistic回归的省级中风保健体系效用研究

运用Logistic回归方法分析加拿大安大略省实施的中风保健系统的效用水平.与KAPRAL等的分段线性回归方法相比,Logistic回归考虑到了不同时间点上的死亡率降低速度的不同,并且假设了在实施中风保健系统之后,死亡率最终将稳定在某个值的附近,从而对加拿大安大略省实施的中风保健系统的效用有了新的认识.在文章的实证研究中,与KAPRAL等的分段线性回归方法相比,Logistic回归得到了较好的拟合效果,拟合的Logistic增长曲线通过了统计检验.此外,还得出了与KAPRAL等不同的拐点位置.

基于logistic回归的L企业交货准时性研究

在分析L企业延迟交货率时发现其销售订单是否能按时交货和产品组、购买频次、一次购买数量、顾客初始请求交货期之间存在某种规律性。基于以上分析建立了一个简单可靠的logistic回归模型。模型的意义在于为L企业提供了一个简单易得的量化指标,来判断订单在常规状态下多大程度上会发生延迟交货的情况。

基于多因素logistic回归方程分析前置胎盘的危险因素

目的基于多因素logistic回归方程分析前置胎盘的危险因素。方法选取2018年10月至2021年5月郑州东方女子医院148例前置胎盘患者为观察组进行回顾性研究,另随机选取同期来医院接受孕期体检的145例正常孕妇作为对照组。收集年龄、受教育程度、户口所在地、职业、胎次、分娩史、流产史、盆腔炎史、瘢痕子宫、分娩孕周、剖宫产史等情况,以logistic多元回归方程进行前置胎盘发生的单因素及多因素分析,评价logistic回归模型,并分析其对前置胎盘发生的预测价值。结果观察组年龄、胎次、分娩史、流产史、盆腔炎史、瘢痕子宫、剖宫产史情况与对照组比较,差异有统计学意义(P<0.05);年龄(OR=4.620,95%CI为1.761~12.123,P<0.001)、胎次(OR=5.025,95%CI为2.392~10.555,P<0.001)、分娩史(OR=5.296,95%CI为1.971~14.231,P<0.001)、流产史(OR=6.312,95%CI为3.664~10.875,P<0.001)、盆腔炎史(OR=6.839,95%CI为2.983~15.681,P<0.001)、瘢痕子宫(OR=5.200,95%CI为2.448~11.047,P<0.001)、剖宫产史(OR=3.685,95%CI为1.327~10.235,P<0.001)是前置胎盘的影响因素(P<0.05);似然比χ^(2)=182.49,自由度(DF)=8,P<0.001,提示模型建立具有统计学意义。Waldχ^(2)=119.31,DF=8,P<0.001,提示模型构建有效。采用Hosmer-Lemeshow拟合优度检验,结果显示χ^(2)=9.755,DF=8,P=0.892,提示模型拟合效果较好;采用logistic回归模型统计分析数据集,得到前置胎盘的预测概率P,根据预测值和真实值绘制受试者工作特征(ROC)曲线,曲线下面积(AUC)为0.837(95%CI为0.780~0.921),当logP>3.19时,预测敏感度为81.37%,特异度为70.69%。结论前置胎盘影响因素复杂,与年龄、胎次、分娩史、流产史、盆腔炎史、瘢痕子宫、剖宫产史均有直接关系,为避免前置胎盘导致的不良妊娠结局,临床应及早采取干预措施,加强孕产妇管理,通过早期筛查及治疗降低其对母婴结局的影响。

Enhancement of E-commerce Service by Designing Last Mile Delivery Platform

The revolution of technology and the rapid evolution of the digital world had a significant effect on the development and expansion of e-commerce.Last mile delivery,for which different app-based delivery services have recently emerged,is a new area of research that is not thoroughly addressed.Delivery ser-vice is one of the supporting platforms of e-commerce.One of the delivery issues is that many customers experience difficulties in communicating and coordinating with the logistics companies responsible for the delivery service.This challenge is emphasized in this study which introduces a new system to facilitate communica-tion and coordination between customers and logistics companies by using one identity and one interface.This paper is a programming-based study,as the pro-posed system evaluates a website to serve logistics companies as well as designs an application(app)to serve the customers of logistics companies.Swift,a power-ful open-source and object-oriented programming language,and the mark-up language(HTML)were used to build the last mile delivery system.In addition,Firebase,a cloud-hosted real-time database built on Google infrastructure,were used to develop the system.By increasing the level of customer satisfaction and reducing delivery failure rates,this system will eventually increase the prosperity of e-commerce.

应用logistic回归模型分析孕妇早产的高危因素

目的分析孕妇早产的高危因素。方法回归性分析401例早产孕妇和同期收治的632例足月产孕妇临床资料,采用单因素分析和多因素logistic回归分析孕妇早产的高危因素。结果单因素分析显示,两组妊娠期高血压疾病、妊娠合并糖尿病、生殖系统感染、阴道出血、有产检、有早产史、胎膜早破、宫颈机能不全、羊水异常、外周血淋巴细胞计数比较,差异有统计学意义(χ2分别=195.47、205.55、156.09、95.44、100.13、41.96、106.61、13.12、2.28、22.64,P均<0.05);logistic回归分析显示,妊娠期高血压疾病、妊娠合并糖尿病、生殖系统感染、阴道出血、有产检、有早产史、胎膜早破、外周血淋巴细胞计数是孕妇早产的影响因素(P<0.05)。结论严密观察并积极预防孕妇早产的高危因素,可以降低早产发生率,改善母婴结局。