An Interactive Fuzzy Satisficing Method for Multiobjective Stochastic Integer Programming with Simple Recourse

This paper considers multiobjective integer programming problems involving random variables in constraints. Using the concept of simple recourse, the formulated multiobjective stochastic simple recourse problems are transformed into deterministic ones. For solving transformed deterministic problems efficiently, we also introduce genetic algorithms with double strings for nonlinear integer programming problems. Taking into account vagueness of judgments of the decision maker, an interactive fuzzy satisficing method is presented. In the proposed interactive method, after determineing the fuzzy goals of the decision maker, a satisficing solution for the decision maker is derived efficiently by updating the reference membership levels of the decision maker. An illustrative numerical example is provided to demonstrate the feasibility and efficiency of the proposed method.

Interactive Fuzzy Programming for Random Fuzzy Two-Level Integer Programming Problems through Fractile Criteria with Possibility

This paper considers two-level integer programming problems involving random fuzzy variables with cooperative behavior of the decision makers. Considering the probabilities that the decision makers’ objective function values are smaller than or equal to target variables, fuzzy goals of the decision makers are introduced. Using the fractile criteria to optimize the target variables under the condition that the degrees of possibility with respect to the attained probabilities are greater than or equal to certain permissible levels, the original random fuzzy two-level integer programming problems are reduced to deterministic ones. Through the introduction of genetic algorithms with double strings for nonlinear integer programming problems, interactive fuzzy programming to derive a satisfactory solution for the decision maker at the upper level in consideration of the cooperative relation between decision makers is presented. An illustrative numerical example demonstrates the feasibility and efficiency of the proposed method.

Research on menu-typed man-machine interaction system of digital TIG welding machine

A digital man-machine interaction system controlled by communications between two processors of TMS320F240 and AT98C2051 was researched in the paper. The system is easy to set and modify welding process parameters by keyboards, and display information of welding site by LCD (Liquid Crystal Display). As one part of multi-task system about TIG welding machine, the coordination of man-machine interaction system with other tasks is the main point to the stability and reliability of its operation. Experiments result indicates that the system is stable, operation-flexible, high precision, and anti-interfering.

A New Interactive Method to Solve Multiobjective Linear Programming Problems

Multiobjective Programming (MOP) has become famous among many researchers due to more practical and realistic applications. A lot of methods have been proposed especially during the past four decades. In this paper, we develop a new algorithm based on a new approach to solve MOP by starting from a utopian point, which is usually infeasible, and moving towards the feasible region via stepwise movements and a simple continuous interaction with decision maker. We consider the case where all objective functions and constraints are linear. The implementation of the pro-posed algorithm is demonstrated by two numerical examples.

Research on the Man-machine Interactive Environment VR and the Applications on Vocational Education and Training under the Perspective of Interactivity

In this paper, we conduct research on the man-machine interactive environment VR and the applications on vocational educationand training under the perspective of interactivity. With the increase in the general standard of social knowledge level and competition intensifi es,more and more people have a goal to build a lifelong learning system, according to their own hobbies, work and the needs of the marketcompetition. Under this condition, the vocational education is becoming more and more essential. This paper integrates the VR and man-machineinteractive concept to propose the new education paradigm that is innovative.

Efficient Graph-based Genetic Programming Representation with Multiple Outputs

In this work, we explore and study the implication of having more than one output on a genetic programming （GP） graph-representation. This approach, called multiple interactive outputs in a single tree （MIOST）, is based on two ideas. First, we defined an approach, called interactivity within an individual （IWI）, which is based on a graph-GP representation. Second, we add to the individuals created with the IWI approach multiple outputs in their structures and as a result of this, we have MIOST. As a first step, we analyze the effects of IWI by using only mutations and analyze its implications （i.e., presence of neutrality）. Then, we continue testing the effectiveness of IWI by allowing mutations and the standard GP crossover in the evolutionary process. Finally, we tested the effectiveness of MIOST by using mutations and crossover and conducted extensive empirical results on different evolvable problems of different complexity taken from the literature. The results reported in this paper indicate that the proposed approach has a better overall performance in terms of consistency reaching feasible solutions.

RGxE: An R Program for Genotype x Environment Interaction Analysis

Genotype x environmental interaction (GxE) can lead to differences in performance of genotypes over environments. GxE analysis can be used to analyze the stability of genotypes and the value of test locations. We developed an Rlanguage program (RGxE) that computes univariate stability statistics, descriptive statistics, pooled ANOVA, genotype F ratio across location and environment, cluster analysis for location, and location correlation with average location performance. Univariate stability statistics calculated are regression slope (bi), deviation from regression (S2d), Shukla’s variance (σi2), S square Wricke’s ecovalence (Wi), and Kang’s yield stability (YSi). RGxE is free and intended for use by scientists studying performance of polygenic or quantitative traits over multiple environments. In the present paper we provide the RGxE program and its components along with an example input data and outputs. Additionally, the RGxE program along with associated files is also available on GitHub at https://github.com/mahendra1/RGxE, http://cucurbitbreeding.com/todd-wehner/publications/software-sas-r-project/? and http://cuke.hort.ncsu.edu/cucurbit/wehner/software.html.

Towards Sensor-free Academic Emotion Prediction in Programming Environment

he transition from traditional learning to practice-oriented programming learning will bring learners discomfort.The discomfort quickly breeds negative emotions when encountering programming difficulties,which leads the learner to lose interest in programming or even give up.Emotion plays a crucial role in learning.Educational psychology research shows that positive emotion can promote learning performance,increase learning interest and cultivate creative thinking.Accurate recognition and interpretation of programming learners’emotions can give them feedback in time,and adjust teaching strategies accurately and individually,which is of considerable significance to improve effects of programming learning and education.The existing methods of sensor-free emotion prediction include emotion prediction based on keyboard dynamic,mouse interaction data and interaction logs,respectively.However,none of the three studies considered the temporal characteristics of emotion,resulting in low recognition accuracy.For the first time,this paper proposes an emotion prediction model based on time series and context information.Then,we establish a Bi-recurrent neural network,obtain the time sequence characteristics of data automatically,and explore the application of deep learning in the field of Academic Emotion prediction.The results show that the classification ability of this model is much better than that of the original LSTM(Long-Short Term Memory),GRU(Gate Recurrent Unit)and RNN(Re-current Neural Network),and this model has better generalization ability.

重大突发公共卫生事件中的方舱医院建设情景重建研究

方舱医院建设是应对各类重大突发公共卫生事件的一项重要举措。现有研究大多从医学或政府管理视角定性地探讨方舱医院发挥的重要作用,还鲜有从情景重建视角研究方舱医院床位扩容的最优时空分布。本文首先构建针对重大突发公共卫生事件演化的SEIHRD模型,继而将方舱医院床位扩容问题构建为有限应急资源分配组合优化模型并设计免疫优化算法进行求解。测试结果显示,本文所给出的方舱医院床位扩容时空分布优化方案,能够对重大突发公共卫生事件中的方舱医院建设情景进行有效重建。方舱医院床位数量及其时间节点设置对累计感染者人数具有显著影响,这表明在疫情暴发初期尽早设立方舱医院,能够有效提升收治率、减少总感染人数。同时也要注意,应急救援资金投入存在阈值效应,需要设计合理的方舱医院床位扩容方案以避免应急预算资源的过度浪费。

不同结对编程策略对小学生学习效果影响的比较研究

结对编程是一种以协作方式学习编程的教学策略,该研究将结对编程与单独编程相结合,构成混合结对编程策略,采用准实验研究法,从编程总评成绩、结对融洽度、结对互动话语等方面,探究混合结对编程和常规结对编程两种策略对小学生学习编程效果影响的差异。实验结果表明,混合结对编程策略能够增进结对伙伴之间的融洽度,促进学生之间的积极互动,提高小学生的编程能力。教师应正确认识结对编程与单独编程的价值,通过组合应用,提高编程教学实效。

熔融不锈钢与液态钠相互作用的瞬态换热特性研究

钠冷快堆严重事故下,堆芯熔融物会与液态金属钠发生相互作用,如果导致堆芯区域内出现钠沸腾的现象,可能会导致堆芯的再临界,从而导致堆芯的进一步熔化。在重定位过程中,堆芯熔融物与液态钠的换热会导致钠出现沸腾,从而影响熔融物射流碎裂与碎片形成。因此,采用严重事故分析程序ACENA对COSA实验平台上开展的熔融不锈钢与液态钠的相互作用的实验进行分析,验证程序对熔融不锈钢与液态钠相互作用过程的瞬态换热特性的分析能力。验证结果表明:程序会高估熔融不锈钢射流与钠池接触时的换热,且不考虑熔融不锈钢外侧凝固形成的硬壳对换热的影响会导致对换热速率的高估。

大语言模型驱动的交互式建筑设计新范式——基于Rhino7的概念验证

随着社会对建筑设计质量要求越来越高,建筑设计软件也变得越来越专业和复杂。现在的设计软件不仅学习成本高,而且交互模式复杂。大语言模型(LLM)的最新突破使计算机清晰地理解人类自然语言指令,并准确生成代码语言具有可行性,有望为人与软件的交互范式提供新思路。因此,本文提出了LLM驱动的交互式建筑设计新范式--将设计师通过多次键鼠操作与设计软件交互转变为LLM根据设计师自然语言指令生成并执行API调用脚本的方式;提出了技术路线并验证了其在建筑设计场景落地的可能性。该技术路线包括:①LLM根据用户指令从API库中搜索与任务相关的API;②LLM基于指令和候选API摘要信息编写程序脚本并运行;③LLM根据来自软件环境、用户等反馈改进优化所编写的程序脚本。通过Rhino7设计软件、GPT-4和CodeLlaMa完成多个设计任务,测试当前LLM是否具备执行该技术路线各关键环节的能力。测试结果不仅证明了LLM驱动的交互式设计范式在建筑设计场景已初具落地前景,也为技术落地提供经验和建议。该设计范式的落地可以降低软件的使用门槛和学习成本,提高设计师工作效率;有望在未来的建筑设计软件中发挥重要作用。

临床实践前课程线上教学效果及影响因素分析

探究北京协和医学院八年制临床实践前课程线上与线下教学效果的差异及影响因素。妇产科学、皮肤性病学和口腔科学的线上教学成绩显著低于线下,儿科学、神经病学、眼科学、耳鼻咽喉学和中医学线上教学成绩显著高于线下。互动可显著提高线上教学效果。线上教学可以作为临床实践前部分课程的有效教学方式。

一种面向舰船结构毁伤的大变形流固耦合数值计算方法

水下爆炸导致舰船结构毁伤是一个复杂的非线性大变形流固耦合过程,高精度的流固耦合计算是获得高置信模拟结果的关键。基于浸没边界思想,本文提出一种面向大变形壳理论的流固耦合数值方法,可精确刻画流固耦合界面并高效求解流固界面约束方程。基于该方法,本文提出了完整的适用于水下爆炸舰船结构毁伤的大变形流固耦合数值计算方案,并基于大规模并行编程框架,研发形成适用于舰船结构毁伤的流固耦合大规模并行计算软件。与泰勒平板理论解和水下爆炸结构冲击响应实验数据等进行对比表明,本文方法可有效模拟大变形流固耦合工程问题,具备较高数值求解精度。在此基础上,完成了水下爆炸整船结构毁伤过程大规模数值模拟。该方法可有效应用于舰船毁伤等级评估,应用前景广阔。

考虑源荷互动的综合能源系统多目标双层规划

随着综合能源系统建设的不断推进,传统的“源随荷动”模式转向“源荷互动”已成为发展趋势。为此,提出了一种考虑源荷互动的综合能源系统多目标双层规划方法。首先,引入电–热–冷可中断负荷和可转移负荷参与综合需求响应,并制定了一种基于新能源发电与等效负荷相匹配的动态定价策略。然后,构建了含电动汽车充电站的综合能源系统多目标双层规划与运行模型,在上层规划模型中以经济成本、碳排放量、自主性为目标,在下层模型中以综合能源系统和电动汽车充电站的总运行成本最小为目标。最后,利用非支配排序遗传算法(non-dominated sorting genetic algorithm Ⅱ,NSGA-Ⅱ)算法和商业求解器CPLEX求解获得Pareto前沿解集,并利用Topsis法选择最优解。算例表明,该方法可以有效降低经济性成本、减少碳排放量、提高系统自主性。

气动工装夹具通用控制系统的设计

以压缩空气为动力源的气动设备在工业生产和制造业中具有重要应用价值,其中气动工装夹具在工件定位、支承与压紧等方面发挥了关键作用。气动工装夹具控制系统的智能化受到众多学者的关注。通过改进顺序控制设计方法和增加嵌入式组态屏的方式,气动工装夹具控制程序的通用性得以提高,系统人机交互性得以增强,实现了示教编程。企业生产实践测试表明,该方法减少了硬件投入,具有实际应用价值。

游戏场景中三维特效的虚拟交互设计

通过三维特效和虚拟交互设计为研究基础,根据Unity游戏场景设计的原则和流程,运用案例实验的方式,结合C#编程语言,对三维特效在游戏场景中的虚拟交互设计进行创作和探讨,重点分析粒子特效、灯光特效、雾和天气特效、动态物理特效、炫彩特效的设计实践过程,阐述了游戏场景中三维特效的交互设计方法。根据不同场景环境的需求条件,得出了三维特效设计的趣味性和沉浸感,利用视觉影像交互体验的方式,在游戏创作和推广中具有重要的作用和意义。

中医眼保健操联合家庭联动式管理方案对屈光不正儿童青少年用眼习惯及视力的影响

目的观察中医眼保健操联合家庭联动式管理方案对屈光不正儿童青少年用眼习惯及视力的影响。方法将120例屈光不正儿童青少年患者按照随机数字表法分为2组,对照组60例予常规门诊宣教及屈光不正纠正方法干预,观察组60例在对照组基础上予中医眼保健操联合家庭联动式管理方案。2组均干预3个月。比较2组干预前及干预后1、3个月裸眼视力,干预3个月后不良用眼习惯纠正情况、简易应对方式问卷(SCSQ)评分,干预前后儿童抑郁障碍自评量表(DSRS)、儿童焦虑性情绪障碍筛查表(SCARED)评分,并统计家属满意度和临床疗效。结果观察组屈光不正纠正有效率91.67%(55/60),对照组有效率76.67%(46/60),观察组屈光不正纠正有效率高于对照组(P<0.05)。2组干预后1、3个月裸眼视力均较本组干预前提高(P<0.05),且观察组干预后1、3个月裸眼视力均高于对照组(P<0.05)。观察组各种不良用眼习惯纠正率和各项遵医行为评分均高于对照组(P<0.05)。2组干预后SCARED、DSRS评分、SCSQ消极应对评分均较本组干预前降低(P<0.05),且观察组干预后均低于对照组(P<0.05);2组干预后SCSQ积极应对评分均较本组干预前升高(P<0.05),且观察组干预后高于对照组(P<0.05)。观察组患儿家属对干预方案的满意度评分高于对照组(P<0.05)。结论中医眼保健操联合家庭联动式管理方案能够更好地纠正患儿屈光不正症状,提高裸眼视力,改正其不良用眼习惯,提高遵医行为,改善其负性情绪,促使患儿建立积极的疾病应对方式,患儿家属满意度好。

基于语言视角对农业机器人自动操作中的交互系统研究

农业机器人是一种由不同程序软件控制,以适应各种作业,能够感知并适应作物种类或环境变化,有检测(如视觉等)和演算等人工智能的新一代无人自动操作机械。为此,基于三维视觉感知、人机环境交互和自动编程等技术,提出了一种“规则场景”匹配和交互算法,以实现人、农业机器人及环境之间的信息交互,在用户的规则错误或无效时引导用户给出正确的规则,在正确定义规则后,通过自动编程和实现自动操作。田间试验结果表明:提出的基于自然语言交互下的农业机器人自动操作系统可以满足农业操作需求,具有一定的实用性与应用价值,对于实现农业现代化具有一定的推动作用。

一种语音交互智能认知评估小程序的设计与应用

目的研制一款适用于中国老年人的智能语音交互认知功能评估工具,用于早期筛查轻度认知障碍。方法利用微信开发者工具、语音识别技术、机器学习模型,研制一款语音交互的智能认知评估工具(SCS)。招募50~80岁受试者,采用SCS小程序和蒙特利尔认知评估基础版(Montreal Cognitive Assessment Basic,MoCA-B)进行评估,对SCS小程序认知评估的准确性作初步验证。结果SCS支持用户通过语音答题自主完成命名、即刻和延迟回忆、符号数字转换等认知任务,结合答题表现和语音的数字生物标志物对记忆、注意和语言等认知功能进行评估,并即刻生成报告,全程仅7 min。207名受试者的平均SCS分数为(86.80±15.53)分,与MoCA-B有良好的相关性(Pearson’s r=0.615,P<0.001)。结论SCS小程序适用于对中国老年人进行认知功能评估,较传统工具高效便利,值得推广用于社区筛查、远程评估和居家自测。