Decision-Making and Management of Self-Care in Persons with Traumatic Spinal Cord Injuries: A Preliminary Study

Patients and physicians understand the importance of self-care following spinal cord injury (SCI), yet many individuals with SCI do not adhere to recommended self-care activities despite logistical supports. Neurobehavioral determinants of SCI self-care behavior, such as impulsivity, are not widely studied, yet understanding them could inform efforts to improve SCI self-care. We explored associations between impulsivity and self-care in an observational study of 35 US adults age 18 - 50 who had traumatic SCI with paraplegia at least six months before assessment. The primary outcome measure was self-reported self-care. In LASSO regression models that included all neurobehavioral measures and demographics as predictors of self-care, dispositional measures of greater impulsivity (negative urgency, lack of premeditation, lack of perseverance), and reduced mindfulness were associated with reduced self-care. Outcome (magnitude) sensitivity, a latent decision-making parameter derived from computationally modeling successive choices in a gambling task, was also associated with self-care behavior. These results are preliminary;more research is needed to demonstrate the utility of these findings in clinical settings. Information about associations between impulsivity and poor self-care in people with SCI could guide the development of interventions to improve SCI self-care and help patients with elevated risks related to self-care and secondary health conditions.

Research on the self-defence electronic jamming decision-making based on the discrete dynamic Bayesian network

The manner and conditions of running the decision-making system with self-defense electronic jamming are given. After proposing the scenario of applying discrete dynamic Bayesian network to the decision making with self-defense electronic jamming, a decision-making model with self-defense electronic jamming based on the discrete dynamic Bayesian network is established. Then jamming decision inferences by the aid of the algorithm of discrete dynamic Bayesian network are carried on. The simulating result shows that this method is able to synthesize different targets which are not predominant. In this way, various features at the same time, as well as the same feature appearing at different time complement mutually; in addition, the accuracy and reliability of electronic jamming decision making are enhanced significantly.

Decision-making competency, self-determination, and health lifestyle in nursing students

Introduction: This study identifies and analyzes the levels of relations between decision-making competency, self-determination, and health lifestyle in nursing students. Methods: This study was designed as a descriptive research to identify the relations of nursing students’ decision-making competency, self-determination, and health lifestyle. The subjects were 187 nursing students. Data were collected using a structured questionnaire and were analyzed by the IBM SPSS Statistics 19 program. Results: Decision-making competency of nursing students was 3.38 ± 0.41 points, and self-determination was 3.07 ± 0.38 points. Stress and physical exercise were the general and health-related lifestyle factors that contributed to the differences in decision-making competency. There were no differences in self-determination according to these factors. Conclusion: The results of the study showed that the levels of decision-making competency and self-determination in nursing students were moderate. Further studies are recommended for the development of these core abilities in nursing students.

Group training on the improvement of college students'career decision-making self-efficacy

A group training was conducted on 17 college students to improve their career decision-making self-efficacy (CDMSE). The result showed that there was significant difference between the pre-test and the post-test for the experimental group (n = 17), whereas no significant difference was found between the pre-test and the post- test for the control group (n = 17). In the pre-test, there was no significant difference between the experimental group and the control group, and obvious difference between the two groups was found in the post-test. This indicated that the group training was effective on improving the CDMSE of the college students whose scores of CDMSE were below 27% point of the total students.

Study of Product Quality Information and Construction of Its Decision-Making Support System and Measures to Improve People's Quality Concept

The 21th century is a "quality century". Facing the s evere challenge about quality, all the developed industry countries attach impor tance to the research and education about quality project. With the deepening of the reform of China and it’s joining to WTO, many industries and enterprises wi ll be confronted with severe challenge while being offered the opportunity to wa lk up to the world. The arrival of knowledge economy and web time has provided t he space for the innovation on enterprise management. It has also provided new m ethod and model for enterprise management, that is online management based on th e internet. The online management use an enterprise model including the goal of the enterprise and the scheme to carry out it to represent the whole operational of all the work. The online management is constructed on the integration of exp ert system, database, software and other technical models. How to scientifically manage the entire system of product, precisely master the condition of quantity and quality and analyze the rules of the change of produc t quality in order to carry out the overall control of quality, guarantee the go od condition of product as well as improve product quality and prolong it’s se rvice life was discussed in this thesis. Based on the above research the thesis also discussed how to develop the study on product quality information and const ruct it’s decision making support system. The concrete measures to improve peopl e’s concept of quality are also raised. Based on the type analysis, scientific management of product quality information should start from dynamic information of quality, instruction information as we ll as the information about the use, maintain, management and conservation of pr oduct, and induce them and further propose a design scheme of feedback system on product quality information, and then set up the blueprint of the information s ystem of product quality. This thesis included 7 chapters:1.the type of quality information;2.the content of quality information;3.the construction of the se nsitive web for transfering information, and collecting and transfering quality information rapidly and effectively;4.the way and procedure to transfer informa tion;5.the construction of quality information library for all phases; 6.the d isposal of quality information;7.the decision making support system of the mana gement of quality information;8.attach importance to three key factors on impro ving quality concept.

The Development of the Generation Expansion Planning System Using Multi-Criteria Decision Making Rule

The power expansion planning is large and capital intensive capacity planning. In the past, the expansion planning was established with the proper supply reliability in order to minimize social cost. However, such planning cannot be used in the power markets with many market participants. This paper proposed the power expansion planning process in the power markets. This system is composed of Regulator and Generation Company （GENCO）＇s model. Multi-criteria decision making rule is used for regulator model and several scenarios for GENCO model are applied.

Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Many scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated ambiguity.The goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site selection.The characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these uncertainties.To tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s method.Following this,an intelligent algorithm is suggested.The steps of the suggested algorithm are explained with an example that explains itself.The compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their viability.This study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,respectively.It uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior literature.It is simpler for the decisionmakers to look at each option separately because the decision is uncertain.Comparing the computed results,it is discovered that they are consistent and dependable because of their preferred properties.

The Impact of Simulation Education on Self-Efficacy in Pre-Registration Nursing Students

This literature review primarily aims to explore and synthesise the previous studies in simulation education research conducted over the past five years related to the effects of simulation training on the self-efficacy of undergraduate pre-registration nursing students. The second aim of this study is to explore additional outcome variables that were examined in the previous studies. Five electronic databases were searched systematically. These databases were MEDLINE, CINAHL Plus, Scopus, Embase and PsycINFO. The PICO model was employed to identify the search terms, with a thesaurus being used to provide synonyms. Reference lists of relevant articles were examined and hand searches of journals were also undertaken. The quality of each study was assessed using the Simulation Research Rubric (SRR). A total of 11 studies were included. All studies explored the impact of simulation education on undergraduate pre-registration nursing. Six studies explored nursing students’ competence and performance and two papers examined their critical thinking. Problem solving, learning motivation, communication skills and knowledge acquisition were examined once. The majority of studies indicated that simulation training has a positive impact on pre-registration nursing students’ self-efficacy and other outcome variables. Furthermore, the study results indicate that simulation training is more dependable than traditional training, and students were extremely satisfied with the simulation training. However, most of the studies included in this review had several gaps, including study design, sample size and dissimilarities between the scales used. Further research with large samples, reliable and valid instruments, and outcomes measures (such as critical thinking and transferability of skills) is required to provide better insight into the effectiveness of simulation in undergraduate nursing education. .

Significance of Live Streaming in Shaping Business: A Critical Review and Analytical Study

With the rise of live streaming on social media, platforms like Facebook, Instagram, and YouTube have become powerful business tools. They enable users to share live videos, fostering direct connections between businesses and their customers. This critical literature review paper explores the impact of live streaming on businesses, focusing on its role in attracting and satisfying consumers by promoting products tailored to their needs and wants. It emphasizes live streaming’s crucial role in engaging customers, a key to business growth. The study also provides viable strategies for businesses to leverage live streaming for growth and customer engagement, underscoring its importance in the business landscape.

基于S型曲线的指标非线性标准化研究

目前,数据标准化处理通常采用的是线性变换方法,然而在处理非均匀分布的指标数据集合时,尤其是对局部集中分布数据的处理存在一定局限性,例如无法有效地将数据划分层级,缺乏辨识性等。利用Logistic曲线函数的特性构建S型曲线模型,可对指标数据进行非线性标准化处理。该方法能够在不改变数据序列及整体分布的前提下对各数据点的取值进行非线性放缩,在将数据稠密的区间进行扩大的同时将数据稀疏的区间进行压缩;同时,针对包含正负值的指标数据集合可以有效地将负值数据突显出来,并且是对特定领域指标数据非线性标准化的补充。

D-S证据理论中的基本概率赋值转换概率方法研究

D-S证据理论的基本概率赋值(BPA)能够有效地表示和处理不确定信息,在不确定信息处理中得到了越来越多的应用。但是如何基于BPA做出决策依然是一个有待解决的问题,将BPA转化为概率函数进行决策是一个简单可行的方法。文章基于证据理论中命题的信度函数和似真函数提供的信息,提出了一种新的基本概率赋值转换概率方法,该方法相比于现有经典TBM模型中Pignistic概率转换和基于似真函数的转换,可以更有效地利用系统已知的信息,实现基本概率赋值到概率分布的合理转换。算例表明了所提出方法的有效性。

多属性决策及D-S证据理论在底板突水决策中的应用

针对煤矿底板突水包含很多不确定因素和时空随机性的特点,探索多属性决策理论在底板突水预测中应用研究。采用案例统计与专家分析相结合的方法,赋予影响底板突水各种因素的权重,建立突水概率指数法的融合规则,提出突水概率指数法预测采场工作面底板突水的新方法。在获得底板突水概率指数的基础上,基于D-S证据理论,建立由突水、临界、不突水、不确定组成的识别框架,构建以富水性指数、构造指数、隔水层指数、水压指数、矿压指数为证据体的突水融合决策模型。通过在肥城煤田实例应用,说明经证据体的多次融合,能够提高突水概率的可信度,降低不确定性,证明基于多属性决策和D-S证据理论建立的工作面底板突水两级融合决策模型的有效性和可行性。

基于距离测度的D-S证据融合决策方法

针对多源信息融合结果并依据D-S证据结构进行决策的问题,提出一种基于距离测度的D-S证据决策方法·该方法结合决策基元和非决策基元的属性进行决策,将依据D-S证据的决策问题分解成两个层面:属性层面、证据层面·属性层面上,给出候选决策从证据焦元获得支持度的方法;证据层面上,基于辨识框架幂集的元素,构造一个证据焦元向量空间,引入候选决策的理想状态向量,定义距离测度,构建决策模型·最后,对多源水质监测信息融合结果进行决策分析,结果表明该方法是合理、有效的,且具有处理冲突或非冲突证据的优点·

基于3S的湿地监测与空间决策支持系统研究--以扎龙国家级湿地保护区为例

湿地具有重要的保护价值,传统的湿地管理和决策方法面临挑战。要提高湿地的保护和管理水平,不仅需要先进的管理模式,更需要先进的技术手段。建立高效实用的扎龙湿地监测与决策支持系统,将湿地管理和决策过程实时化和科学化,以加强对湿地的监控和管理,成为亟待解决的问题。以扎龙湿地为研究对象,以RS、GIS、GPS和Web技术为技术支撑,开展湿地监测与决策支持系统研究与开发,为扎龙湿地的保护提供及时、有效的辅助决策支持,并为其它湿地的管理提供借鉴。

基于D-S证据理论的数据融合井下监测方法分析

针对矿井单传感器监测系统监测数据单一、不确定性较高的缺陷,利用基于D-S证据理论的多传感器信息融合技术,在对原始数据分析处理的基础上,把多种参数通过数据融合模块实现对井下工作环境安全性的评估、决策。同时,可根据各参数间的相关性获得更多单传感器监测系统所无法获得的井下环境信息,极大地提高了数据采集的可靠性、全面性和矿井监测系统的有效性。

基于灰色关联分析和D-S证据理论的区间直觉模糊决策方法

针对方案的指标值为区间直觉模糊数的决策问题,提出了一种基于灰色关联分析和D-S证据理论的决策方法.定义了区间记分函数和区间数点算子,并通过其将区间直觉模糊数转化为记分函数;利用记分函数以及灰色关联方法确定各指标的不确信度,进而构建出不同指标下各方案的Mass函数,通过D-S合成法则进行信息融合,确定最优方案.最后,通过算例表明,本文提出的方法可得到满意结果并显著降低决策的不确定性.

基于D-S证据理论的地震应急救援群决策

为解决地震应急救援群决策中专家偏好冲突问题,提出一种基于登普斯特-沙弗尔(DS)证据理论的专家偏好型应急救援群决策方法。首先,考虑方案执行时间和方案资源的客观属性以及专家的主观偏好,在传统地震救援群决策过程基础上,设计改进的专家偏好型群决策过程;然后,借鉴应急协商模型,设计考虑方案执行时间和资源的偏好函数,基于三角模糊数定义专家主观偏好程度,并运用D-S证据理论综合专家偏好度作方案选择;最后,以2017年九寨沟地震为试验算例,开展方法对比性试验和偏好敏感性试验。结果表明:与仅考虑方案执行时间和资源或基于三角模糊偏好相比,考虑方案执行时间和资源偏好的决策方案更能满足实际地震应急救援需求,且专家的平衡性偏好更有利于地震应急救援方案的正确选择。

基于D-S理论的企业安全绩效综合评定研究

为客观评定企业安全绩效,提出一种基于D-S证据理论的企业安全绩效综合评定方法。在确定安全绩效评定指标的基础上,利用模糊函数和群决策方法处理评价过程中的不确定信息,将多源决策信息转换为同一框架下的评价信息,然后根据各决策信息的重要度,通过D-S证据理论的mass函数和证据合成方法对安全绩效评价群决策中的不确定性信息逐层融合。实例表明,该方法能够克服D-S冲突问题,保证企业安全绩效综合评定信息融合结果的准确度,企业安全管理的优劣势的表征更为直观。

Research on self-adaptive decision-making mechanism for competition strategies in robot soccer

In the robot soccer competition platform, the cur- rent confrontation decision-making system suffers from dif- ficulties in optimization and adaptability. Therefore, we pro- pose a new self-adaptive decision-making （SADM） strategy. SADM compensates for the restrictions of robot physical movement control by updating the task assignment and role assignment module using situation assessment techniques. It designs a self-adaptive role assignment model that assists the soccer robot in adapting to competition situations similar to how humans adapt in real time. Moreover, it also builds an accurate motion model for the robot in order to improve the competition ability of individual robot soccer. Experimental results show that SADM can adapt quickly and positively to new competition situations and has excellent performance in actual competition.

基于D-S证据理论的空中目标威胁度排序模型

将数据融合领域的D-S证据推理理论应用于空袭目标威胁程度的评估。先针对各决策者关于相应方案在某属性上的评语集,利用证据组合公式进行信息融合,形成该方案在属性上的群体偏好信息,接着求出关于该方案在属性上的确定性评价值,最后针对得到的确定性多属性决策问题,利用加权法或理想点法进一步对方案进行最终的排序。