DECISION-MAKING OF SLICING SCHEME IN FUSED DEPOSITION MODELING PROCESS BASED ON ANALYTICAL HIERARCHICAL PROCESS

Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.

Study on group air to ground attack-defends hierarchical dynamic decision-making

As to oppositional, multi-objective and hierarchical characteristic of air formation to ground attackdefends campaign, and using dynamic space state model of military campaign, this article establishes a principal and subordinate hierarchical interactive decision-making way, the Nash-Stackelberg-Nash model, to solve the problems in military operation, and find out the associated best strategy in hierarchical dynamic decision-making. The simulating result indicate that when applying the model to air formation to ground attack-defends decision-making system, it can solve the problems of two hierarchies, dynamic oppositional decision-making favorably, and reach preferable effect in battle. It proves that the model can provide an effective way for analyzing a battle,

Modeling and TOPSIS-GRA Algorithm for Autonomous Driving Decision-Making Under 5G-V2X Infrastructure

This paper is to explore the problems of intelligent connected vehicles(ICVs)autonomous driving decision-making under a 5G-V2X structured road environment.Through literature review and interviews with autonomous driving practitioners,this paper firstly puts forward a logical framework for designing a cerebrum-like autonomous driving system.Secondly,situated on this framework,it builds a hierarchical finite state machine(HFSM)model as well as a TOPSIS-GRA algorithm for making ICV autonomous driving decisions by employing a data fusion approach between the entropy weight method(EWM)and analytic hierarchy process method(AHP)and by employing a model fusion approach between the technique for order preference by similarity to an ideal solution(TOPSIS)and grey relational analysis(GRA).The HFSM model is composed of two layers:the global FSM model and the local FSM model.The decision of the former acts as partial input information of the latter and the result of the latter is sent forward to the local pathplanning module,meanwhile pulsating feedback to the former as real-time refresh data.To identify different traffic scenarios in a cerebrum-like way,the global FSM model is designed as 7 driving behavior states and 17 driving characteristic events,and the local FSM model is designed as 16 states and 8 characteristic events.In respect to designing a cerebrum-like algorithm for state transition,this paper firstly fuses AHP weight and EWM weight at their output layer to generate a synthetic weight coefficient for each characteristic event;then,it further fuses TOPSIS method and GRA method at the model building layer to obtain the implementable order of state transition.To verify the feasibility,reliability,and safety of theHFSMmodel aswell as its TOPSISGRA state transition algorithm,this paper elaborates on a series of simulative experiments conducted on the PreScan8.50 platform.The results display that the accuracy of obstacle detection gets 98%,lane line prediction is beyond 70 m,the speed of collision avoidance is higher than 45 km/h,the distance of collision avoidance is less than 5 m,path planning time for obstacle avoidance is averagely less than 50 ms,and brake deceleration is controlled under 6 m/s2.These technical indexes support that the driving states set and characteristic events set for the HFSM model as well as its TOPSIS-GRA algorithm may bring about cerebrum-like decision-making effectiveness for ICV autonomous driving under 5G-V2X intelligent road infrastructure.

Studies on Multi-Criteria Decision-Making-Based Healthcare Systems Using the Machine Learning

There is a lot of information in healthcare and medical records.However,it is challenging for humans to turn data into information and spot hidden patterns in today’s digitally based culture.Effective decision support technologies can help medical professionals find critical information concealed in voluminous data and support their clinical judgments and in different healthcare management activities.This paper presented an extensive literature survey for healthcare systems using machine learning based on multi-criteria decision-making.Various existing studies are considered for review,and a critical analysis is being done through the reviews study,which can help the researchers to explore other research areas to cater for the need of the field.

Shared Decision-Making after Implementation of the Chronic Care Model (CCM)—An Evaluative Approach

Background: In paternalistic models, healthcare providers’ responsibility is to decide what is best for patients. The main concern is that such models fail to respect patient autonomy and do not promote patient responsibility. Aim: To evaluate mental healthcare team members’ perceptions of their own role in encouraging elderly persons to participate in shared decision-making after implementation of the CCM. The CCM is not an explanatory theory, but an evidence-based guideline and synthesis of best available evidence. Methods: Data were collected from two teams that took part in a focus group interview, and the transcript was analysed by means of qualitative thematic analysis. Results: One overall theme emerged—Preventing the violation of human dignity based on three themes, namely, Changing understanding and attitudes, Increasing depressed elderly persons’ autonomy and Clarifying the mental healthcare team coordinator’s role and responsibility. The results of this study reveal that until recently, paternalism has been the dominant decision-making model within healthcare, without any apparent consideration of the patient perspective. Community mental healthcare can be improved by shared decision-making in which team members initiate a dialogue focusing on patient participation to prevent the violation of human dignity. However, in order to determine how best to empower the patient, team members need expert knowledge and intuition.

现代口腔医院高水平人才队伍建设的研究

教育、科技、人才是全面建设社会主义现代化国家的基础性、战略性支撑。人才作为发展的根基,实现高水平人才队伍的建设与发展,为现代口腔医院的发展和行业技术的提升起到了促进作用。而针对口腔医院的人才管理、人才队伍建设目前处于不断发展阶段,仍存在较多的不足和弊端,需积极采取相关措施,如通过不断完善人才队伍考核评价机制及奖励机制,创建分层分类管理、分类与综合评价、人才年薪制激励方案等,实现以职称管理为主的人才管理模式的逐步转化为人才梯队建设管理体系,进一步完善口腔医院的高水平人才队伍构建,保障口腔医院健康、高效和可持续性发展。

隧道工人群体安全行为对个体安全行为的影响

针对隧道工程施工安全问题,从隧道工人行为角度出发,结合问卷调查数据,建立分层线性模型(hierarchical linear model,HLM),从微观上解释了安全行为关联因素影响过程。利用信效度评价检验了309份有效数据的可靠性,通过假设检验依次分析了隧道工人群体安全行为对个体安全行为、安全氛围以及团队效能的影响作用。结果表明,群体安全行为对个体安全行为具有显著正向影响;安全氛围在群体安全行为与个体安全行为之间具有中介作用;团队效能在安全氛围与个体安全行为之间具有正向调节作用。以上结果为更好地发挥安全行为在隧道施工安全管理中的作用提供了指导。

基于专科医师态度和建议的“专科—全科团队”建设模式探索

目的调研专科医师对“专科—全科团队”(专全团队)的态度和建议,为完善专全团队建设提供参考。方法对北京市某医院医联体核心和成员单位的348名专科医师进行问卷调查,采用SPSS 19.0软件进行数据统计分析。结果专科医师对分级诊疗和专全团队的态度较为积极。超过九成的专科医师愿意下转患者及接收上转患者;接近九成的专科医师认为专全团队可以完全或部分解决全科医师医疗服务能力不足问题。专科医师更愿意按照专业组建专全团队,更愿意同期参加一个到两个专全团队,更愿意获得一定的劳动报酬,更愿意进行学科进展、最新诊疗指南解读和病例讨论等培训,更愿意进行定期线上或线下例会总结,更愿意担任兼职领导者,带领5人~10人的专全团队。结论专科医师对分级诊疗和专全团队模式的态度有利于专全团队模式进一步发展。以学科为基础组建专全团队,以适中的团队规模和工作强度为主,以一定的劳动报酬支持为主,进一步加强专全团队沟通,是完善专全团队建设模式的工作重点。

地理科学实验教学中心管理的一些思考

地理科学实验教学中心是培养学生地理实验技能和专业创新意识的重要场所。对实验教学中心的各类实验教学条件和资源的有效管理,是发挥其作用的基础。立足于地理科学实验教学中心,以点带面,从各类实验教学资源的分层、分类管理,管理团队建设,及信息化管理建设等方面提出了一些思考和建议。认为可以将支持不同教学目的的实验室进行分类,吸引专业人才参加野外实习基地建设和管理,利用好联合建设的实验(实训)基地。在人力资源有限的情况下,引入学生助管和返聘督导,切实提高教学实验室的管理水平和开放力度。通过开展信息化管理建设和虚拟实验项目建设,进一步提高实验教学中心的服务水平。

Hierarchical under frequency load shedding scheme for inter-connected power systems

Severe disturbances in a power network can cause the system frequency to exceed the safe operating range.As the last defensive line for system emergency control,under frequency load shedding(UFLS)is an important method for preventing a wide range of frequency excursions.This paper proposes a hierarchical UFLS scheme of“centralized real-time decision-making and decentralized real-time control”for inter-connected systems.The centralized decision-layer of the scheme takes into account the importance of the load based on the equivalent transformation of kinetic energy(KE)and potential energy(PE)in the transient energy function(TEF),while the load PE is used to determine the load shedding amount(LSA)allocation in different loads after faults in real-time.At the same time,the influence of inertia loss is considered in the calculation of unbalanced power,and the decentralized control center is used to implement the one-stage UFLS process to compensate for the unbalanced power.Simulations are carried out on the modified New England 10-generator 39-bus system and 197-bus system in China to verify the performance of the proposed scheme.The results show that,compared with other LSA allocation indicators,the proposed alloca-tion indicators can achieve better fnadir and td.At the same time,compared with other multi-stage UFLS schemes,the proposed scheme can obtain the maximum fnadir with a smaller LSA in scenarios with high renewable energy sources(RES)penetration.

老年专科护士兼护理组长的管理价值分析

目的分析在护士分层级管理中,老年专科护士兼护理组长的实施效果及价值。方法选取2020年3月—2023年2月南华大学附属长沙中心医院的20名老年科护士作为研究对象,2020年3月—2021年10月实施常规管理措施为对照组,2021年11月—2023年2月实施老年专科护士兼护理组长的分层管理措施为研究组,对不同管理措施实施后护士的护理工作质量、风险防控意识、老年病康复管理能力以及对管理措施的满意度进行对比。结果研究组护理工作质量各指标评分均高于对照组,研究组风险防控意识比对照组更高,研究组老年病康复管理能力高于对照组,研究组对管理措施的满意度比对照组高,差异有统计学意义(P<0.05)。结论老年专科护士兼护理组长管理价值高,可以帮助护士提升工作质量及风险防控意识,在护士分层级管理中优势显著,满意度高,可加强老年病康复管理能力。

组长负责制分层管理模式在急诊护理管理中的应用效果评价

目的分析组长负责制分层管理模式在急诊护理管理中应用效果。方法选取2021年3月—2023年3月麻城市人民医院的40名急诊护理人员作为研究对象,按照管理模式分为对照组和观察组,各20名。对照组采取的是常规管理模式,观察组采取的是组长负责制分层管理模式,对比分析两组护理人员应用效果。结果观察组护理人员在病情掌握度、考核成绩以及护理基础技术能力评估中明显优于对照组,差异有统计学意义(P<0.05);观察组护理人员管理满意度明显高于对照组,差异有统计学意义(P<0.05)。结论对急诊护理管理措施中实施组长负责制分层管理模式,可将其整体的基础水平以及工作质量进行提升,增加护理管理效果,提高护理人员满意度,并且促进患者痊愈。

组长负责制分层管理模式在神经外科护理管理中的应用

目的分析组长负责制分层管理模式在神经外科护理管理中的应用效果。方法选取2021年9月—2022年9月山东颐养健康集团滕南医院神经外科的30名护士为观察对象,以数字法均分为对照组、观察组,每组15名。两组分别采取常规护理管理措施、组长负责制分层管理模式,比较两组的护理管理效果。结果观察组护理差错发生率低于对照组,差异有统计学意义(P<0.05)。观察组服务态度(9.23±0.31)分、文书写作(9.11±0.34)分、护理技术(9.26±0.28)分、突发情况处理(9.14±0.25)分及危重症处理(9.33±0.19)分高于对照组,差异有统计学意义(P<0.05)。观察组理论考核(92.53±3.23)分、实践考核(91.63±3.15)分及工作考核(94.01±2.11)分高于对照组,差异有统计学意义(P<0.05)。结论在神经外科的护理管理中,采取组长负责制分层管理模式,对于提升护理质量有积极作用,且能够提升护士的理论功底、实践及工作能力,有效减少护理差错。

分层分组责任制小组管理模式在肿瘤科护士中的应用研讨

目的研究分层分组责任制小组管理模式在肿瘤科护士中的应用效果。方法选取2022年1月—2023年5月永州市第三人民医院肿瘤科在职护理人员14名,依照对护理人员实施不同管理分为管理前和管理后两组,2022年1—8月实施常规管理模式为管理前,2022年9月—2023年5月实施分层分组责任制小组管理模式为管理后,对比管理前后护士护理质量得分、护士综合素质、护士核心能力以及护士职业认同感。结果管理后,肿瘤科护士护理质量得分、护士综合素质、护士核心能力以及护士职业认同感均高于管理前,差异有统计学意义(P<0.05)。结论分层分组责任制小组管理模式运用肿瘤科护士管理中,可提升护士护理质量、核心能力、综合能力以及职业认同感。

医疗联合体模式下基层卫生人才队伍建设实践与体会

医疗联合体是实现分级诊疗的有效形式,在基层卫生人才队伍建设中具有招聘平台高、途径多、专业性强和培训成效好等优势。以"盛泽医疗联合体"为例介绍了一体化管理下基层卫生人才队伍建设的实践经验,探讨符合新医改精神的基层医学人才培养与引进模式。

分层-团队-导师法用于急诊科护士科研培训研究

目的提高急诊科护士护理科研培训效果。方法对急诊科45名临床护士开展为期1年的分层-团队-导师式科研培训,包括分层理论培训、定期读书报告交流、团队项目设计及实施、老师全程指导;与常规培训方法比较培训效果及护士满意度。结果与常规培训方法比较,护士科研能力自评得分及对培训的满意度显著提高(均P<0.01),发表论文数、科研课题及新技术、学术大会交流人次相应增加。结论分层-团队-导师培训法有利于提高科研培训效果,从而护高护士培训满意度。

虚拟团队共享心理模型与团队效能的关系

通过对62个虚拟团队的调研,检验了虚拟团队认同式共享心理模型与分布式共享心理模型构思,并运用多层线性建模技术,对团队特征变量、共享心理模型与虚拟团队效能间的关系进行了分析。结果表明:两类共享心理模型与团队效能间存在显著正相关;团队时间会影响共享心理模型与虚拟团队任务效能间的关系,团队时间会削弱认同式共享心理模型对任务效能的正向关系,但能加强分布式共享心理模型对任务效能的正面影响;团队规模则主要影响共享心理模型对合作效能的效应,团队规模增加会加强认同式共享心理模型与合作效能间的相关,却会削弱分布式共享心理模型与合作效能间的关系。

创新公立医院多学科联合会诊服务供给模式

目的:为推进分级医疗,更好地履行国家对公立医院的功能定位,提高医院多学科联合会诊服务工作。方法:对医院2013-2015年多学科联合会诊服务中心2331例患者信息,采用卡方检验及趋势卡方检验进行资料分析,总结医院创新多学科联合会诊服务供给模式,会诊后通过随访疗效及满意度评价。结果:3年中医院多学科联合门诊患者数呈逐年增加势态,不同年度多学科会诊患者的年龄分布差异有统计学意义(χ~2=22.57,P=0.001)。申请多学科联合门诊目的:要求明确诊断664例(28.5%);诊断已明确寻求治疗方案1667例(71.5%)。会诊后随访治疗效果:痊愈418例(17.9%);好转1473例(63.2%);无明显改善123例(5.3%);死亡37例(1.6%);失去随访280例(12.0%)。医院多学科联合会诊中心病种数量逐年增加,且不同年度间多学科联合门诊病种数量差异有统计学意义(χ~2=746.44,P<0.001)。不同年度患者对多学科联合会诊的满意度差异有统计学意义,并呈逐年上升趋势,从2013年的90.1%增加到2015年的97.1%(χ~2=30.51,P_(fortrend)<0.001)。结论:优化多学科联合会诊服务供给模式,有效推动了双向转诊、分级诊疗和区域医疗协作;拓展了医院疑难重症医疗、教学和科学研究工作。

团队学习行为、个体社会资本与学习倾向:个体创新行为的多层次模型

本文以研发团队及成员为样本,实证研究测试团队学习行为对个体社会资本、个体学习倾向与其创新行为关系的跨层次影响.结果显示:个体社会资本、个体学习倾向对其创新行为都具有显著的正向影响;团队学习行为对其成员创新行为有直接显著的正向影响;团队学习行为可强化其成员互动频率与创新行为之间的正相关关系,且对其成员学习倾向与创新行为之间正相关关系具有调节作用.研究结论为有效管理研发团队、促进成员的创新行为提供新的视角和参考建议.

共享心智模式、过程敏捷性与团队绩效关系研究——以软件开发团队为例

团队共享心智模式的构建有利于提高团队绩效,是增强科研团队综合实力的关键因素。以团队过程敏捷性为中介变量,以团队互依性为调节变量,探索共享心智模式对团队绩效的作用机制。以238名软件开发行业人员为研究对象,运用层级回归分析法以及基于拔靴法的结构方程模型对理论框架进行实证分析。研究结果表明:过程敏捷性在共享心智模式与团队绩效之间具有完全中介作用,团队互依性在共享心智模式与过程敏捷性之间具有正向调节作用,但在共享心智模式、团队互依性、过程敏捷性和团队绩效关系模型中,有调节的中介效应并不显著。