基于Excel测试模板的变频器自动测试程序设计

变频器作为微波信号发射端和接收端的重要器件,对收发系统性能具有较大影响,因此,需对相关参数进行测试。本文针对其种类、测试参数和测试仪器设备多,以及测试人员要求高、人工测试效率低,开发设计变频器自动测试程序,并基于Excel测试模板,实现定制化测试。

Excel支持的匀变速运动位移公式的探究教学

匀变速直线运动的位移公式是教学中的难点。在分析人教版新教材编写设计和高一学生学情后,提出以Excel软件作为技术支持的科学探究教学改进方案。通过v-t图像围成的面积和真实位移的数据对比,得到匀变速直线运动v-t图像围成的面积表示位移的结论。

应用型本科高校“Excel人力资源管理工具应用”课程建设研究

数据分析技术在人力资源管理行业中的应用越来越广泛,但目前人力资源管理专业学生的数据分析能力相对薄弱。通过对应用型本科高校“Excel人力资源管理工具应用”课程建设进行研究,找出原有课程教学中存在的主要问题,对课程内容进行重构和设计,注重Excel工具应用的教授及数据分析素养的提升,培养高素质的应用型人力资源数据分析人才。

VBA结合Excel在施工进度横道图制图软件开发中的应用研究

施工进度计划是建设项目施工组织设计中的重要内容,横道图是水利水电项目设计阶段施工总进度计划的主要表示方法。本文依托Microsoft Office Excel内嵌的VBA语言简单、方便、高效的特点和优势,探索研发了一款符合水利水电行业设计习惯的施工进度横道图制图软件,可以减少人力投入,提高设计效率,满足行业设计需求。软件具有自动进行工程量汇总、强度累计、制作强度曲线图、绘制施工总进度横道图并标注线条强度、分期分幅出图、进度线条批量平移(含部分项目跨停工时段平移)等功能,在诸多水利水电项目设计中得到良好应用。

Excel软件在医学统计学课程中的教学应用探讨

在医学数据统计处理中,常用的统计软件包括SAS、SPSS和R。此外,掌握Excel软件中的统计功能对于提高数据处理能力也是一个极佳的选择。文章以《卫生统计学》教材为例,展示了数据处理的过程,并探讨了计量资料的均数、标准差、配对设计资料的t检验、两个独立样本的t检验以及单因素方差分析在统计分析中的应用方法。Excel软件可以作为医学统计学课程的辅助教学软件。

List of winners of excellent papers of Baosteel Technical Research in 2023

According to the three-tiered review opinions of the editorial office of Baosteel Technical Research and the expert review opinions,the following papers were selected as the excellent papers of Baosteel Technical Research in2023.

Optimal search path planning of UUV in battlefeld ambush scene

Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.

Integration of Excellent Chinese Traditional Culture into the Training and Education of Acupuncture and Massage Professionals

By reflecting on the current situation of the integration of excellent Chinese traditional culture into the training of acupuncture and massage professionals,this paper aims to carry out the research on the integration of excellent Chinese traditional culture into the training and education of acupuncture and massage.The specific implementation path includes early investigation and analysis,establishment of research objectives,formulation of teaching strategies,means and methods,empirical research on the process of teaching practice,teaching measurement and evaluation,and so on.Finally,it summarizes the connotation of the integration of excellent Chinese traditional culture into the training of acupuncture and massage professionals,in order to provide new ideas and methods for the integration of excellent Chinese traditional culture into the training and education of acupuncture and massage professionals.

Efficient Route Planning for Real-Time Demand-Responsive Transit

Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.

基于EXCEL的供应链物流选址决策分析

随着企业经营规模的扩大,如何通过降低成本提升企业价值,已成为企业竞争力提升的关键。在物流行业中,基于供应链的物流选址问题是影响企业物流成本的重要因素。如何科学地做好供应链物流选址决策,将直接影响企业的经济效益。本文以石油公司为研究对象,结合线性规划的相关理论,构建基于供应链的物流选址决策模型,运用EXCEL工具,进行选址决策分析,以实现企业资源的优化配置,从而降低企业运营成本。

Research on the Transmission of Chinese Excellent Traditional Culture in Confucius Classroom at Sabaragamuwa University of Sri Lanka Under the Background of“the Belt and Road”Cooperation Initiative

“The Belt and Road”cooperation initiative contains Chinese excellent traditional cultural ideas,and is deeply rooted in Chinese excellent traditional culture.The proposal of“the Belt and Road”cooperation initiative is not only the strategic need to implement the“going out”of Chinese culture,but also the need to promote cultural exchanges and mutual learning among countries along“the Belt and Road”,and more importantly,the practical consideration of building a community of shared future for mankind with cultural identity.Confucius classroom,as one of the important platforms to realize the“going out”of Chinese culture,shows the“image of China”and enhances the“soft power”of Chinese culture,integrates and configures Chinese teaching and Chinese cultural resources through cooperation,and plays an important role in telling Chinese stories,spreading Chinese voice,enhancing cultural mutual trust and people-to-people contacts as well as the awareness of a community of shared future for mankind.Taking the Confucius classroom jointly built by Huanggang Normal University in China and Sabaragamuwa University in Sri Lanka as an example,this paper explores some effective transmission ways for spreading Chinese excellent traditional culture in Sri Lankan Confucius classroom under the background of“the Belt and Road”cooperation initiative,aiming to give full play to the role of Confucius classroom in cultural exchanges and enhance inter-school exchanges and cooperation between China and Sri Lanka in terms of cultural mutual trust and respect.

Motion Planning for Autonomous Driving with Real Traffic Data Validation

Accurate trajectory prediction of surrounding road users is the fundamental input for motion planning,which enables safe autonomous driving on public roads.In this paper,a safe motion planning approach is proposed based on the deep learning-based trajectory prediction method.To begin with,a trajectory prediction model is established based on the graph neural network(GNN)that is trained utilizing the INTERACTION dataset.Then,the validated trajectory prediction model is used to predict the future trajectories of surrounding road users,including pedestrians and vehicles.In addition,a GNN prediction model-enabled motion planner is developed based on the model predictive control technique.Furthermore,two driving scenarios are extracted from the INTERACTION dataset to validate and evaluate the effectiveness of the proposed motion planning approach,i.e.,merging and roundabout scenarios.The results demonstrate that the proposed method can lower the risk and improve driving safety compared with the baseline method.

Stochastic programming based coordinated expansion planning of generation,transmission,demand side resources,and energy storage considering the DC transmission system

With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.

A Reverse Path Planning Approach for Enhanced Performance of Multi-Degree-of-Freedom Industrial Manipulators

In the domain of autonomous industrial manipulators,precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance,such as handling,heat sealing,and stacking.While Multi-Degree-of-Freedom(MDOF)manipulators offer kinematic redundancy,aiding in the derivation of optimal inverse kinematic solutions to meet position and posture requisites,their path planning entails intricate multiobjective optimization,encompassing path,posture,and joint motion optimization.Achieving satisfactory results in practical scenarios remains challenging.In response,this study introduces a novel Reverse Path Planning(RPP)methodology tailored for industrial manipulators.The approach commences by conceptualizing the manipulator’s end-effector as an agent within a reinforcement learning(RL)framework,wherein the state space,action set,and reward function are precisely defined to expedite the search for an initial collision-free path.To enhance convergence speed,the Q-learning algorithm in RL is augmented with Dyna-Q.Additionally,we formulate the cylindrical bounding box of the manipulator based on its Denavit-Hartenberg(DH)parameters and propose a swift collision detection technique.Furthermore,the motion performance of the end-effector is refined through a bidirectional search,and joint weighting coefficients are introduced to mitigate motion in high-power joints.The efficacy of the proposed RPP methodology is rigorously examined through extensive simulations conducted on a six-degree-of-freedom(6-DOF)manipulator encountering two distinct obstacle configurations and target positions.Experimental results substantiate that the RPP method adeptly orchestrates the computation of the shortest collision-free path while adhering to specific posture constraints at the target point.Moreover,itminimizes both posture angle deviations and joint motion,showcasing its prowess in enhancing the operational performance of MDOF industrial manipulators.

Trajectory planning for multi-robot coordinated towing system based on stability

Given the unconstrained characteristics of the multi-robot coordinated towing system,the rope can only provide a unidirectional constraint force to the suspended object,which leads to the weak ability of the system to resist external disturbances and makes it difficult to control the trajectory of the suspended object.Based on the kinematics and statics of the multi-robot coordinated towing system with fixed base,the dynamic model of the system is established by using the Newton-Euler equations and the Udwadia-Kalaba equations.To plan the trajectories with high stability and strong control,trajectory planning is performed by combining the dynamics and stability of the towing system.Based on the dynamic stability of the motion trajectory of the suspended object,the stability of the suspended object is effectively improved through online real-time planning and offline manual adjustment.The effectiveness of the proposed method is verified by comparing the motion stability of the suspended object before and after planning.The results provide a foundation for the motion planning and coordinated control of the towing system.

Ground threat prediction-based path planning of unmanned autonomous helicopter using hybrid enhanced artificial bee colony algorithm

Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.

Multi-UAVs Collaborative Path Planning in the Cramped Environment

Due to its flexibility and complementarity, the multiUAVs system is well adapted to complex and cramped workspaces, with great application potential in the search and rescue(SAR) and indoor goods delivery fields. However, safe and effective path planning of multiple unmanned aerial vehicles(UAVs)in the cramped environment is always challenging: conflicts with each other are frequent because of high-density flight paths, collision probability increases because of space constraints, and the search space increases significantly, including time scale, 3D scale and model scale. Thus, this paper proposes a hierarchical collaborative planning framework with a conflict avoidance module at the high level and a path generation module at the low level. The enhanced conflict-base search(ECBS) in our framework is improved to handle the conflicts in the global path planning and avoid the occurrence of local deadlock. And both the collision and kinematic models of UAVs are considered to improve path smoothness and flight safety. Moreover, we specifically designed and published the cramped environment test set containing various unique obstacles to evaluating our framework performance thoroughly. Experiments are carried out relying on Rviz, with multiple flight missions: random, opposite, and staggered, which showed that the proposed method can generate smooth cooperative paths without conflict for at least 60 UAVs in a few minutes.The benchmark and source code are released in https://github.com/inin-xingtian/multi-UAVs-path-planner.

Research on Evacuation Path Planning Based on Improved Sparrow Search Algorithm

Reducing casualties and property losses through effective evacuation route planning has been a key focus for researchers in recent years.As part of this effort,an enhanced sparrow search algorithm(MSSA)was proposed.Firstly,the Golden Sine algorithm and a nonlinear weight factor optimization strategy were added in the discoverer position update stage of the SSA algorithm.Secondly,the Cauchy-Gaussian perturbation was applied to the optimal position of the SSA algorithm to improve its ability to jump out of local optima.Finally,the local search mechanism based on the mountain climbing method was incorporated into the local search stage of the SSA algorithm,improving its local search ability.To evaluate the effectiveness of the proposed algorithm,the Whale Algorithm,Gray Wolf Algorithm,Improved Gray Wolf Algorithm,Sparrow Search Algorithm,and MSSA Algorithm were employed to solve various test functions.The accuracy and convergence speed of each algorithm were then compared and analyzed.The results indicate that the MSSA algorithm has superior solving ability and stability compared to other algorithms.To further validate the enhanced algorithm’s capabilities for path planning,evacuation experiments were conducted using different maps featuring various obstacle types.Additionally,a multi-exit evacuation scenario was constructed according to the actual building environment of a teaching building.Both the sparrow search algorithm and MSSA algorithm were employed in the simulation experiment for multiexit evacuation path planning.The findings demonstrate that the MSSA algorithm outperforms the comparison algorithm,showcasing its greater advantages and higher application potential.

Combing and Discussion of Modern Urban Planning Ideas

Since the emergence of utopian socialism and other modern urban planning ideas,as well as the proposing of“garden cities”by Howard,modern urban planning theory has experienced a variety of planning ideas,and these ideas play a great role in guiding urban construction and planning.In this century,cities have ushered in many industrial revolutions,and urban life,economy,and ecology have changed greatly.Planning scholars in various countries are actively looking for“medicine”to save cities in the“sick”.In this paper,modern urban planning ideas were sorted out,and how to learn from the current territorial spatial planning that is being compiled around the country was thought about.

An integrated spatial planning of the mountainous landscapes for ski sports in a case area at the eastern Türkiye

Mountainous regions have disadvantages in economic development because of harsh physical and climatic conditions.However,winter tourism activities are one of the key components for supporting economic development in the highlands.Establishing a ski resort area supports direct and indirect employment in a region,and it stops immigration from mountainous regions to other places.This research aimed to assess the potential ski areas using a multi criteria evaluation technique in the Van region which is located in the eastern part of Türkiye.In this context,snow cover duration,sun effect,slope,slope length,elevation,population density,distance from main roads and lake visibility were used as input factors in the decision making process.Each factor was standardized using a fuzzy technique based on existing well-known ski centers in Türkiye.The weight of inputs was defined by applying a survey to the professional skiers.The most important factors were detected as transportation opportunities and snow covers whereas,the least important factors were elevation and population density.Additionally,lake visibility was very important to make a difference from other existing facilities in the region.Therefore,it was included as constraints and lake visible areas were extracted at the final stage of the research.Potential ski areas were mapped in three levels as professional,intermediate and beginner skiers.One of the suitable areas was selected as a sample projection and for the 3D simulation of the ski investment area.Potential costs and benefits were discussed.It was found that a ski tourism area investment can be amortized in 3 years in the region.