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.

Veterans utilizing a federally qualified health center: a clinical snapshot

Dear Editor,Te Veterans Health Administration(VHA)provides healthcare for over 9 million enrolled veterans with approximately 2.7 million of those residing in rural areas[1].Te MISSION Act of 2018 emphasizes VHA collaboration with Federally Qualifed Healthcare Centers(FQHC)to serve rural residing veterans and nearly all existing collaborations involve arrangement of payment for community-based care by VHA to FQHCs.Unfortunately,there is a paucity of descriptive clinical data on existing cross-system collaborations which may help characterize these veterans and aid understanding of conditions for which they may receive treatment across systems.Such data has implications for workforce training,development,and resource allocation[2].Te objective of this report is to describe diferent clinical profles between two mutually exclusive samples:veterans engaged in FQHC only use,and VHA-enrolled veterans engaged in dual VHA and FQHC use.

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。

职业教育“双师型”教师专业发展的伦理向度及行动策略

在职业教育步入新时代的背景下,教育部将师德考核作为“双师型”教师职业考核的第一标准,突出了职业伦理在“双师型”教师职业标准中的首要地位。发展职业伦理是“双师型”教师专业发展的内在诉求。根据“双师型”教师专业发展要求,从教学伦理、技术伦理和学术伦理三个向度进行深刻剖析,明确“双师型”教师专业发展各伦理向度的要求和内容。通过完善伦理培训体系与评价机制,发展教学伦理;深化校企合作与产教融合,发展技术伦理;加强组织与制度建设,发展学术伦理,从而有效促进“双师型”教师职业伦理发展。

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。

培养创新创业能力的职业教育模式研究

如何更加高效地培养学生创新创业能力,探索出既不烦琐又可操作且广泛适用的职业教育模式,是现阶段各大高职院校亟须解决的重要课题。为进一步促进高职院校培养创新创业能力的职业教育模式改革与发展,对现有高职创新创业教育模式存在的弊端进行分析,提出“厚植学生创新创业观、完善高职院校创新创业教育体系、优化高职院校创新创业实践体系、建立健全创新创业能力培养评价机制”等策略,助力职业教育高质量发展,培养出理念先进、技术扎实、素养过硬的新时代复合型人才。

新时代高职院校“双师型”教师队伍建设研究——基于江苏省相关政策与实践的探索

当前高职院校“双师型”教师队伍建设在师资来源、培训体系、认定标准、考核评价等方面存在一些问题。基于江苏省相关政策与实践探索,提出高职院校“双师型”教师队伍建设的策略:科学规划教师队伍建设,完善“双师型”教师发展顶层设计;规范师资管理政策措施,优化“双师型”教师队伍结构;深化教师考核评价改革,打造“德技双馨”高质量“双师”队伍,持续推进“双师双能”教师队伍建设。

面向国家能源战略需求的卓越工程人才培养新体系构建与实践

行业特色高校由其办学属性决定,在培养卓越工程师等高端人才方面具有得天独厚的优势。中国石油大学(北京)作为一所油气能源特色高校,面对保障国家能源安全和能源战略转型发展双重使命挑战,坚持“强优、拓新、创一流”的学科建设思路,构建了学科发展新格局,以此为龙头,依托产学研合作办学优势,打造“思政引领、创新驱动、融合发展”的工程人才培养新模式,并建立了“内部保证、外部认证、智能赋能”的教育教学质量保障体系,取得了显著的人才培养成效,其创新成果具有较大的应用推广价值。

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。

落实立德树人根本任务 履行教书育人工作职责

党的二十大报告提出,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。教育、科技和人才是相互作用又相互促进的有机整体,教育作为其中的基础环节,是机体良好运行的关键。该文结合高校教师自身岗位职责,探讨立德树人和铸造自身等方面的原则和方法。国家的发展离不开教育,教育的发展和进步离不开教师。身为教师应当听从党的指挥,立足本职工作,强化责任意识,肩负使命责任,踔厉奋发有为。

资历框架视角下我国职业资历认证与认可机制建设

国家资历框架是衡量、沟通、衔接社会成员各类学习成果的通用等级和标准。职业资历是国家资历的重要类型,实现职业资历的认证与等值转换是国家资历框架建设的重要任务。从国际经验看,国家资历框架的建设往往会经历从单一类型到多元类型、从单一区域到跨区域的过程。改革开放以来,我国形成了职业资历框架的基本架构,但是在认证与认可机制构建方面,还存在统一管理缺乏、法律体系薄弱、标准设计不足、学分银行建设滞后等问题。未来应适时探索建立统一的职业资历认证与认可管理体制,从管理制度、法律体系、标准体系和平台体系等方面着手,推动构建职业资历认证与认可机制。

本科护理学专业“双师型”教师队伍建设的探索与实践

健康中国背景下,加强“双师型”护理师资队伍的建设是培养卓越护理人才的基础。苏州大学护理学院通过严格设置“四证”的准入条件,建立“双师型”师资库,优化遴选和启用流程;注重师资队伍的持续发展,完善职前职后一体化培训与发展体系;建立优胜劣汰的管理机制,设置多元化的激励措施,保障师资队伍的活力与竞争力,可为高校护理学专业“双师型”师资队伍建设提供新的思路和参考。

招聘大数据分析在优化人才培养方案中的应用

通过探索开放性、交互性、动态性的分析模式,对招聘大数据进行采集、分析、可视化,追踪人才需求变动趋势,刻画行业企业的需求特征,提炼人才培养的职业素养,以适应经济发展、产业升级和技术进步对人才的需求。依据招聘大数据的特征分析,从发展的角度对人才培养、课程体系、教学内容进行持续性的优化,从而推进专业设置与产业需求对接、教学过程与生产过程对接、课程内容与职业标准对接。

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。

慢性牙周炎对支气管扩张症患者生活质量及严重程度的影响

目的:探讨慢性牙周炎对支气管扩张症患者生活质量和疾病严重程度的影响。方法:随机选择2021年4月—2023年4月长沙市第四医院收治的支气管扩张症患者80例作为研究对象,按照是否伴中重度慢性牙周炎将患者分为2组,分别为支气管扩张伴牙周炎组(n=45)和支气管扩张不伴牙周炎组(n=35)。采用支气管扩张生活质量问卷(QoL-B)调查患者的生活质量,采用支气管扩张严重程度指数(BSI)评估疾病严重程度,并检测患者血清高敏C反应蛋白(hsCRP)、肿瘤坏死因子α(TNF-ɑ)、白细胞介素6(IL-6)的水平。采用SPSS 20.0软件包对数据进行统计学分析。结果:支气管扩张伴牙周炎组QoL-B评分显著低于支气管扩张不伴牙周炎组,BSI评分显著高于支气管扩张不伴牙周炎组(P<0.05)。支气管扩张伴牙周炎组hs-CRP、TNF-ɑ、IL-6水平显著高于支气管扩张不伴牙周炎组(P<0.05)。结论:支气管扩张患者中伴有慢性牙周炎的患者在生活质量和疾病严重程度方面都表现出明显的不利影响,可能与炎症反应在2种疾病之间的共同机制有关。