Improved Scatter Search Algorithm for Multi-skilled Personnel Scheduling of Ship Block Painting

This paper focuses on the optimization method for multi-skilled painting personnel scheduling.The budget working time analysis is carried out considering the influence of operating area,difficulty of spraying area,multi-skilled workers,and worker’s efficiency,then a mathematical model is established to minimize the completion time. The constraints of task priority,paint preparation,pump management,and neighbor avoidance in the ship block painting production are considered. Based on this model,an improved scatter search(ISS)algorithm is designed,and the hybrid approximate dynamic programming(ADP)algorithm is used to improve search efficiency. In addition,the two solution combination methods of path-relinking and task sequence combination are used to enhance the search breadth and depth. The numerical experimental results show that ISS has a significant advantage in solving efficiency compared with the solver in small scale instances;Compared with the scatter search algorithm and genetic algorithm,ISS can stably improve the solution quality. Verified by the production example,ISS effectively shortens the total completion time of the production,which is suitable for scheduling problems in the actual painting production of the shipyard.

Comparative Study of the Socioeconomic Characteristics and Digital Literacy Level of Agricultural Extension Personnel in Imo and Ebonyi States, South-East, Nigeria

The study comparatively analysed the socioeconomic characteristics and digital literacy level of Agricultural Extension personnel (AEP) in Ebonyi and Imo States, South-East, Nigeria. The specific objectives were to describe the socioeconomic characteristics of agricultural extension personnel in Ebonyi and Imo States, and to ascertain the digital literacy level of AEP in the studied states. Purposive sampling technique was used to select 312 Agricultural Extension personnel (132 from Ebonyi State Agricultural Development Program and 180 from Imo State Agricultural Development Program) for the study. Data were collected through the use of validated and structured questionnaire, and administered through the help of well-trained enumerators. Data were analysed using simple descriptive statistical tools such as percentages mean score, standard deviation and weighted mean. Findings indicated that they were more male in the both States (55.3% and 57.8%) for Ebonyi and Imo State respectively and that the average age of AEP in Ebonyi and Imo States were 44.7 years and 49.2 years respectively. It was further revealed that the majority (77.3% and 82.8%) had B.Sc./HND as their highest academic qualifications, belonged to professional organisations (62.1% and 75%), and were earning an average monthly income of N58,798 and N62,648 for Ebonyi and Imo State respectively. Also, it was revealed that their mean years of service were 12.4 years and 13.4 years for Ebonyi and Imo State respectively. Almost all of them (87.9% and 95.0%) own a smartphone, had access to the internet (80.3% and 90.0%), but do not own a laptop/ipad (82.6% and 72.8%) for Ebon-yi and Imo State respectively. Results further revealed that Agricultural extension personnel in both Ebonyi and Imo State respectively had low digital literacy level ( = 2.41 and 2.32). The study concluded that AEP in Ebonyi and Imo State respectively had similar socioeconomic characteristics and low level of digital literacy. The study recommended that the management of ADPs in both Ebonyi and Imo State should ensure the training of AEP in digital skills to enhance their digital literacy level to enable them use digital technologies in their work.

Detection Algorithm of Laboratory Personnel Irregularities Based on Improved YOLOv7

Due to the complex environment of the university laboratory,personnel flow intensive,personnel irregular behavior is easy to cause security risks.Monitoring using mainstream detection algorithms suffers from low detection accuracy and slow speed.Therefore,the current management of personnel behavior mainly relies on institutional constraints,education and training,on-site supervision,etc.,which is time-consuming and ineffective.Given the above situation,this paper proposes an improved You Only Look Once version 7(YOLOv7)to achieve the purpose of quickly detecting irregular behaviors of laboratory personnel while ensuring high detection accuracy.First,to better capture the shape features of the target,deformable convolutional networks(DCN)is used in the backbone part of the model to replace the traditional convolution to improve the detection accuracy and speed.Second,to enhance the extraction of important features and suppress useless features,this paper proposes a new convolutional block attention module_efficient channel attention(CBAM_E)for embedding the neck network to improve the model’s ability to extract features from complex scenes.Finally,to reduce the influence of angle factor and bounding box regression accuracy,this paper proposes a newα-SCYLLA intersection over union(α-SIoU)instead of the complete intersection over union(CIoU),which improves the regression accuracy while increasing the convergence speed.Comparison experiments on public and homemade datasets show that the improved algorithm outperforms the original algorithm in all evaluation indexes,with an increase of 2.92%in the precision rate,4.14%in the recall rate,0.0356 in the weighted harmonic mean,3.60%in the mAP@0.5 value,and a reduction in the number of parameters and complexity.Compared with the mainstream algorithm,the improved algorithm has higher detection accuracy,faster convergence speed,and better actual recognition effect,indicating the effectiveness of the improved algorithm in this paper and its potential for practical application in laboratory scenarios.

Personnel Localization Method in Transformer Substation Based on Factor Graph

A SINS/GNSS location method based on factor diagram is proposed to meet the requirement of accurate location of substation construction personnel. In this paper, the inertial autonomous positioning, carrier motion information acquisition and satellite positioning technologies are integrated. The factor graph method is adopted to abstract the measurement information received by inertial navigation and satellite into factor nodes, and the state information into variable nodes, so as to construct the SINS/GNSS construction personnel positioning fusion factor graph model. The Gauss-Newton iterative method is used to implement the recursive updating of variable nodes, and the optimal estimate of the location information of the construction personnel is calculated, which realized the high precision location of the construction personnel. The factor graph method is verified by pedestrian navigation data. The results show that the factor graph method can continuously and stably output high-precision positioning results, and realize non-equidistant fusion of SINS and GNSS. The positioning accuracy is better than Kalman filter algorithm, and the horizontal positioning accuracy is less than 1 m. Therefore, the factor graph method proposed can provide accurate location information for substation construction personnel.

Visualization Techniques viaMLBS for Personnel Management in Major Events

Mobile location-based services(MLBS)refer to services around geographic location data.Mobile terminals use wireless communication networks(or satellite positioning systems)to obtain users’geographic location coordinate information based on spatial databases and integrate with other information to provide users with required location-related services.The development of systems based on MLBS has significance and practical value.In this paper a visualization management information system for personnel in major events based on microservices,namely MEPMIS,is designed and implemented by using MLBS.The system consists of a server and a client app,and it has some functions including map search and query,personnel positioning and scheduling,location management,messaging,and location service.Managers of the events can quickly search and locate the staff on the specific area of the map in real-time,and make broadcasting messages to the staff,and manage the staff.The client app is developed on the Android system,by which staff users can send the positions information to the server timely.The client users can search fuzzily near their peers and list their locations,and also call near peers through sending messages or query the history record of staff locations.In the design of the system,several new proposed techniques,including visual annotation method for overlapping locations,correcting trajectory drift algorithm,microservices-based overall system architecture methodology and other new techniques,which are applied to the implementation of the system.Also,HTML5,JQuery,MLBS APIs(Application Program Interfaces)related programming techniques have been used and combined with loading Ajax asynchronously and Json data encapsulation,map marker optimization techniques,that can improve the positioning accuracy and the performance of the system.The developed system with practical functions can enhance the efficiencies of the organization and management of major events.

陆军飞行人员领悟社会支持与疲劳、焦虑的相关性研究

目的探讨陆军飞行人员领悟社会支持与疲劳、焦虑发生的相关性,为精准干预研究奠定基础。方法于2022年7月10-13日随机抽取某部飞行人员,采用领悟社会支持、多维疲劳和焦虑量表进行问卷调查(n=88);利用座谈和个别交流方式补充了解陆军飞行人员领悟社会支持现状及其与疲劳、焦虑状态的关系;通过SPSS 20.0软件对该人群上述指标进行相关分析,计量资料采用描述性分析,计数资料采用频率分析,Pearson分析变量间的相关性。结果纳入分析问卷85份(每份含领悟社会支持、多维疲劳和焦虑量表)。其中男性83人(97.65%),女性2人(2.35%);飞行员80人(94.11%),领航员2人(2.35%),空中机械师3人(3.53%)。20~39岁82人(96.47%)。高社会支持(分值61~84)人数占比为68.23%(58/85),低、中焦虑度(分值<30分)人数占比为100%(85/85),非显著疲劳状态(55.71±8.48)人数占比为98.82%(84/85)。领悟社会支持程度(62.22±14.67)与焦虑(14.44±3.86)呈显著负相关(P<0.01),但与疲劳无显著相关性(P>0.05),焦虑与疲劳之间相关性也不显著(P>0.05)。结论陆军飞行人员领悟社会支持程度可能会引发焦虑,进而影响作业能力和健康水平;应对该人群领悟社会支持进行精准干预以完善航卫保障。

涉农高校助力乡村振兴的新型组织模式探索与实践——以吉林农业科技学院为例

乡村振兴战略是党的十九大提出的解决“三农”问题、加快农业农村现代化发展的重要举措。涉农高校在乡村振兴战略实施中具有独特优势,且肩负着重要使命。以吉林农业科技学院为例,提出涉农高校助力乡村振兴战略实施“五结合”新型组织模式,即“线上+线下”“集中+分散”“学校+企业”“项目+成果”“工作站+产业学院”,可为涉农高校服务乡村振兴战略提供借鉴,为乡村振兴发展提供新的思路和方法。

服务四川省食品饮料产业的工商专业群人才培养模式探索

依据“双高计划”要求,专业群的人才培养应与产业人才需求精准对接。面向先进制造业、现代农业和现代服务业等重点产业,服务于重点产业转型升级,以体现职业教育为生产劳动服务的功能。工商专业在组群中没有特色,常常被边缘化。因此,要跨专业组群,面向重点产业,兼顾培养懂技术的管理人才,懂管理的技术人才。通过“技术+管理”“工科+商科”,跨专业跨领域交叉融合,服务四川省食品饮料产业。目标是培养“懂管理、善操作、精技术”的复合型技术技能人才和“懂技术、会经营、擅管理”的技术技能型管理人才。

工程教育背景下化工应用型人才培养模式的探讨

新一轮科技革命和产业变革深入发展的大背景下,专业建设依据工程教育认证标准来进行是工程教育发展的必然趋势。担负着提供化学工程领域高素质应用型人才职责的化学工程与工艺专业,通过工程教育认证,构建以学生为中心的应用型人才培养模式,建立工程教育认证背景下创新创业应用型人才培养课程体系,在培养学生创新意识的同时,加强学生在实践过程中创业能力,发挥培养符合国际工程教育认证标准及新时代发展要求的高素质应用型人才积极作用。

“双碳”背景下建环专业人才培养模式研究

“双碳”战略的确立,为建筑环境与能源应用工程专业的人才培养提出了新的要求。传统的人才培养模式已经不能满足“双碳”战略的需求,有必要探索适应“双碳”背景的建环专业新型人才培养模式。通过分析“双碳”背景下建环专业人才的具体要求,制订了人才培养目标,总结了课程设置及质量、教学方法以及实践教学三方面的改进措施。提出的优化建议对加强建环人才培养,推动实现“双碳”战略具有重要意义。

人工智能背景下大数据与会计专业技能型人才培养模式研究

随着人工智能时代的到来,财会领域也面临着前所未有的挑战和机遇,新技术引起财会岗位及财会人员技能需求发生不同程度的变化。面对当前大数据与会计专业技能人才培养存在的问题,文章从技能人才培养模式、专业课程体系、教学资源整合、师资队伍建设、案例研究和实训项目教学等多方面提出改革路径与实践方法,以期提高职业院校大数据与会计专业技能型人才培养质量。

面向双创教育的高校档案人才的培养体系建构

创新创业教育是高等教育改革发展的重要方向,也是培养高素质档案专门人才的必然要求。在数字经济时代背景下,档案工作面临数字化转型与创新发展的新形势、新挑战,迫切需要一批具有创新意识、创业精神和实践能力的复合型档案人才。基于创新创业教育理念,围绕档案学专业人才培养体系,提出亟须通过更新人才培养理念,优化专业课程体系,创新人才培养模式,强化实践教学环节,完善人才培养评价来统筹推进档案学专业创新创业教育教学改革。

狭长通航隧洞船舶火灾人员应急疏散仿真研究

通航隧洞是一类为船舶穿越高山峡谷提供通航条件的新型通航建筑物,发生火灾时有害气体易于堆积、人员逃生路径狭窄、应急疏散难度大。针对待建的贵州乌江思林通航隧洞构建典型船舶火灾和人员疏散逃生模型,分析火灾事故发展过程中的特征参数变化情况,基于有毒有害气体和温度的安全限值,对横通道间距、船舶编队等因素影响下的人员疏散安全风险进行评估。结果表明:横通道间距为200 m时,3艘货船、2艘货船和1艘客船的编队情况符合人员疏散安全评估;横通道间距为300 m和400 m时,所有编队情况均无法满足人员疏散安全评估,其主要危险因素为持续吸入有毒有害气体。因此,在保障安全前提下,隧洞不宜设置300 m及以上横通道间距,客船疏散难度大,应采取下船翻坝运输的方式过坝。

分类评价:高校管理干部评价改革新探索

高校管理干部队伍是推动高校事业蓬勃发展的坚实基础,科学有效的评价体系是加强高素质、专业化管理干部队伍建设的基础性工程。传统评价方式“千人一面”、评价内容“简单趋同”,容易引起不同区域管理干部的同质化竞争。分类评价凸显了新时代高校管理干部的治理使命,推动了专业化人才培育、精细化分类治理和长效化效能提升。作为高校管理干部评价体系改革的新探索,可结合高校治理诉求,针对高校类型的不同、干部岗位类型的不同、干部分级类型的不同开展高校管理干部评价。

拔尖创新人才培养的现实困境与路径优化——以“强基计划”为例

拔尖创新人才培养既是实现教育强国和高水平科技自立自强的必然要求,也是贯彻落实科教兴国战略的迫切需要,更是强化社会主义建设人才支撑的重要举措。立足“强基计划”的战略背景与目标要求,从拔尖创新人才的培养现状及态势入手,剖析总结人才培养阶段衔接性不足、创新能力培养不足及交叉学科设置不合理等问题。结合拔尖创新人才培养的目标定位,积极探索科教深度融合的拔尖创新人才培养模式,提出了“二三三四五”拔尖创新人才培养路径,即以双轮驱动配合“三类整合”课程体系,注重三大能力培养与四阶段科研训练,构建五方支撑培养体系,以优化拔尖创新人才培养路径,保证拔尖创新人才培养质量。

构建“1+1>2”公立专科医院党管人才的“生态圈”

人才是医院发展的根本。某三甲儿童专科医院自独立运行以来,面临人才梯队建设不完善、人才需求缺口大、人才引进经费不足、人才培养力度不强等困难。医院党委坚持党管人才,在完善人才引进、培养、激励机制的基础上,针对人才队伍建设的难点、盲点,构建党管人才“1+1>2生态圈”,着重在人才引进与培养、数量与质量、产能输入与输出上发力,促使人才建设“引育留用”取得实效,为医院高质量发展奠定人才基础。

巴林特小组活动对护理人员职业倦怠感负性情绪及自我效能的影响

目的探讨巴林特小组活动对呼吸与危重症医学科护理人员职业倦怠感、负性情绪及自我效能的影响。方法将64名护理人员随机均分为对照组和试验组。对照组护理人员给予心理健康讲座,试验组护理人员在对照组基础上给予巴林特小组活动。采用相应的量表评估两组护理人员干预前后的职业倦怠感、负性情绪及自我效能状况。结果干预后试验组护理人员中文版职业倦怠量表(MBI)总分及情绪衰竭、去个性化维度评分均低于干预前和对照组,个人成就感维度评分高于干预前和对照组(P<0.01);干预后试验组护理人员焦虑自评量表(SAS)和抑郁自评量表(SDS)评分均低于干预前和对照组,一般自我效能感量表(GSES)评分高于干预前和对照组(P<0.01)。结论巴林特小组活动能够提高呼吸与危重症医学科护理人员的自我效能感,改善其职业倦怠感及负性情绪状况。

本科生导师制助推拔尖创新人才培养的探索与实践——以中南大学物理学院为例

导师制在世界高等教育发展与高校人才培养模式及博雅教育理念施行中扮演着非常重要的角色。本科生导师制在以“一制四化”为重点的拔尖创新人才培养模式改革与综合环境构筑中发挥了巨大作用。针对当前导师制实施过程中存在的问题和高校传统教学模式对拔尖创新人才培养的不尽如人意,探讨了本科生导师制结合思政教育贯穿、创新创业能力提升、学赛相长、科教融合及本-硕协同育人来助推拔尖创新人才培养,为拔尖创新人才培养模式的理性回归与培养质量的全面提升提供参考。

基于改进YOLOv7的矿井人员检测算法

矿井人员的实时检测是建设智慧矿山必不可少的内容,通过视频监测井下人员,从而实现危险区域预警及联动控制,对于矿井安全生产具有重要意义。现阶段可见光图像识别技术针对井下昏暗环境中人员的辨识还有待完善。针对井下光照不均、煤尘干扰严重导致监控视频存在噪声多、图像模糊等问题,提出一种改进YOLOv7的矿井人员检测算法。首先,针对ELAN模块直接拼接形成通道隔离的问题,提出基于通道重组与特征关注的复杂场景检测方式;其次,针对特征融合结果未侧重预期目标且模型缺乏针对性策略提升小目标检测性能,在颈部多尺度融合网络添加ACmix模块,兼顾全局特征和局部特征,提升了算法对小目标的检测能力;最后,引入Efficient IOU Loss提升算法收敛速度的同时减小目标框及先验框高度和宽度的差值,实现更加精准的定位。通过公开行人数据集及自建矿井人员检测数据集验证表明:该算法较YOLOv7模型相比,检测精度提升了3.1%,达到89.4%;召回率提升了3.8%,达到86.4%;速度提升了15.8%,达到68.8FPS;满足矿井人员实时检测的工作要求。

基于服务乡村振兴的农业专业硕士人才培养改革与实践

农业硕士研究生人才培养目标是为农业技术研究、应用、开发及推广等培养具有农业综合职业技能的应用型高层次人才。培养具有创新意识的新型农业技术人员对于加快我国农业现代化进程、推动农业农村经济建设至关重要。结合近些年的实践教学,从农业硕士研究生人才培养目标、课程设置、导师队伍建设以及实践环节等方面分析了全日制农业专业硕士人才培养过程中存在的问题,并探讨解决对策,以期为农业专业硕士人才培养提供经验,提高专业研究生人才培养质量。