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.

Analysis of the Digital Skill Gap of Agricultural Extension Personnel in South-East, Nigeria

The study analysed the digital skill gap of agricultural extension personnel on the use of digital technologies for extension services delivery in South-East, Nigeria. The specific objectives were to describe the socioeconomic characteristics of agricultural extension personnel in South-East Nigeria and identify the digital skill gaps among agricultural extension personnel in the area of study. Purposive sampling technique was used to select 364 Agricultural Extension personnel for the study. Data were collected through the use of structured questionnaire and were analysed using simple descriptive statistical tools such as percentages, mean score, and standard deviation. Findings indicated that most of the personnel were male (57.8%), within the age bracket of 38 - 47 years (62.9%), had B.Sc./HND as their highest educational qualification (74.7%), married (86.3%), and had a household size of 6 - 10 Persons (57.7%). It was further revealed that the majority (70.1%) were members of professional organization, earned a monthly income of N50,001.00 - N100,000.00 (65.7%), had a work experience of 11 - 15 years (51.1%), and owned a smartphone/ iPad/laptop (91.5%). Findings further indicated that they had moderate skill gap in Basic Computer skills (Mean = 4.32), and digital communication and collaboration skills (Mean = 4.26). Findings also showed that they had a high skill gap in digital technical skills (Mean = 2.46), digital data analysis skills (Mean = 2.09), digital content creation skills (Mean = 2.43), digital ethical skills (Mean = 2.79), multimedia production skills (Mean = 2.81), and video library management skills (Mean = 2.39). The study concluded that though there exists a high digital skill gap among agricultural extension personnel in South-East, Nigeria, their socioeconomic characteristics are capable of supporting the implementation of digital extension services in the area. The study recommended that the management of Agricultural Development Programs in South-East, Nigeria, should provide digital training for extension personnel to close the digital skill gap that currently exists among the personnel.

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.

Hazardous Attitude Factors Influence Risk Perception in General Aviation Pilots

This manuscript presents a research proposal to investigate how hazardous attitudes among general aviation pilots influence pilot performance in aviation accidents. General aviation pilots train to maintain safe flying conditions, but accidents still occur, and human factors figure prominently among the causes of aviation accidents. The levels of hazardous attitudes among pilots may influence the likelihood of engaging in risky flight behaviors that can lead to accidents. This quantitative study aims to determine whether dangerous attitudes impact risk perception in general aviation pilots. The study will focus on two specific hazardous attitudes, “Anti-Authority” and Macho” behaviors. Among the hazardous attitudes identified by the Federal Aviation Administration (FAA), the two attitudes often stand out in accident investigations and pilot narratives. While all hazardous attitudes have inherent dangers, these two attitudes tend to be more frequently cited in accident reports and investigations. Despite rigorous training in safe flying conditions, general aviation accidents still transpire due to human factors. This research hypothesizes that the five attitudes from the hazardous attitude model, particularly Anti-Authority and Macho, significantly shape pilots’ risk perception. The insights from this study would benefit stakeholders, like the Aircraft Owners and Pilots Association (AOPA), Air Safety Institute, and aviation training programs, in creating training modules tailored to reduce such attitudes.

Research on the Improvement of Incentive Mechanism for Pharmaceutical Sales Personnel - Taking Company A as an Example

Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensation incentive,performance appraisal,welfare benefit,training incentive,promotion motivation and enterprise cultural inspiration were explored through questionnaires,telephone interviews and in-person interviews.Results and Conclusion This company’s incentive mechanism has problems in two aspects:Material incentives and spiritual incentives.As to the company’s characteristics and strategic development,the optimization countermeasures of incentive mechanism are proposed from the following three aspects:constructing a reasonable incentive system,establishing an efficient spiritual incentive mechanism,and implementing the dynamic incentive and differentiated incentive simultaneously.

Low PAPR Channel Estimation for OTFS with Scattered Superimposed Pilots

Orthogonal time frequency space(OTFS)modulation has been proven to be superior to traditional orthogonal frequency division multiplexing(OFDM)systems in high-speed communication scenarios.However,the existing channel estimation schemes may results in poor peak to average power ratio(PAPR)performance of OTFS system or low spectrum efficiency.Hence,in this paper,we propose a low PAPR channel estimation scheme with high spectrum efficiency.Specifically,we design a multiple scattered pilot pattern,where multiple low power pilot symbols are superimposed with data symbols in delay-Doppler domain.Furthermore,we propose the placement rules for pilot symbols,which can guarantee the low PAPR.Moreover,the data aided iterative channel estimation was invoked,where joint channel estimation is proposed by exploiting multiple independent received signals instead of only one received signal in the existing scheme,which can mitigate the interference imposed by data symbols for channel estimation.Simulation results shows that the proposed multiple scattered pilot aided channel estimation scheme can significantly reduce the PAPR while keeping the high spectrum efficiency.

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.

我国结核病关爱行动试点项目基线调查分析

目的:分析“我国结核病关爱行动试点项目”首批40个试点县(区)实施前的结核病防治工作基本情况,为后续实施效果的评估及相关措施的推广提供基线数据。方法:2023年4—6月,中国疾病预防控制中心结核病控制中心向首批实施试点项目的15个省的40个试点县(区)结核病防治机构发放统一的半结构化电子版调查问卷,了解并分析项目开始前一年(即2022年)试点县(区)结核病定点医疗机构的服务能力、结核病患者人文关怀和重点人群筛查等措施的开展情况。结果:40个试点县(区)定点医疗机构以综合医院为主[23家(57.50%)],其次是专科医院[8家(20.00%]和疾病预防控制机构[6家(15.00%)]。共有结核病防治人员1017名,每家配备专业人员范围[中位数(四分位数)]为3~64名[19.5(12.5,34.0)名],以门诊和住院医生、护理人员为主[分别为326名(32.05%)和225名(22.12%)],其次为影像科医生和实验室人员[分别为187名(18.39%)和134名(13.18%)]。共报告结核病患者10123例,包括9980例(98.59%)肺结核[包括病原学阳性患者6326例(63.39%)]和143例(1.41%)肺外结核,病原学阴性肺结核的诊断总符合率为85.69%(629/734),但对气管支气管结核的诊断符合率仅有17.86%(5/28)。40个试点县(区)均开展了抗酸杆菌涂片显微镜检查和结核菌素皮肤试验(PPD试验),开展分枝杆菌分离培养、结核分枝杆菌核酸检测和抗结核药物耐药筛查的县(区)分别有39个(97.50%)、37个(92.50%)和32个(80.00%),但开展重组结核分枝杆菌融合蛋白和γ-干扰素释放试验的仅分别有16个(40.00%)和19个(47.50%);开展X线摄影检查、CT检查、人工智能诊断阅片和远程会诊等技术的分别有39个(97.50%)、31个(77.50%)、14个(35.00%)和23个(57.50%)。17个(42.50%)县(区)应用了信息化手段管理患者,15个(37.50%)县(区)提供了交通或营养补助,但开展营养评估和支持治疗、心理支持的均不足30%;36个(90.00%)县(区)将结核病纳入门诊特殊病种,分别有26个(65.00%)县(区)将耐药结核病纳入大病保障和分子生物学检测纳入报销范围。HIV感染者/AIDS患者和结核病患者密切接触者的胸部影像学总体筛查率均较高[分别为96.06%(17105/17807)和92.81%(46884/50515)],但65岁及以上老年人和糖尿病患者的总体筛查率均较低[分别为13.48%(377436/2800877)和12.27%(93808/764416)]。新生入学结核病筛查开展率不高[60.00%(24/40)~80.00%(32/40)],托养机构和福利机构开展率偏低[分别为20.69%(6/29)和25.00%(8/32)]。结论:各试点县(区)试点前均已具备结核病诊断所需的基本硬件条件,但尚需在病原学阴性肺结核规范诊断、信息化管理手段的应用、患者人文关怀措施和医疗保障政策的落实,以及重点人群的筛查方面进一步提升。

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。

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。

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。

我国数字乡村试点的政策工具偏好及区域差异——基于全国72个试点县域的扎根分析

以数字技术赋能乡村建设是推动农业农村现代化转型的必然要求,也是实现乡村振兴、推动共同富裕的重要战略目标。自2020年中央一号文件首次提出数字乡村试点以来,全国各试点地积极推进数字乡村建设实践。已有研究或从乡村发展与变迁视角来阐释数字化建设对于乡村高质量发展的战略意义,或从数字治理视角呈现数字化驱动乡村治理的过程和机制,而较少关注“试点”政策本身,更缺乏政策工具的类型学归纳和分析。基于政策工具视角,研究对全国72个数字乡村试点县域的一、二手资料进行扎根分析,最终提炼出能力建设型、协同治理型和创新激励型三类政策工具,并在此基础上构建数字乡村建设的“价值实践张力—动力机制—政策工具选择—政策目标实现”分析框架。研究表明,以政府主导为依托的能力建设型工具处于绝对优势地位,在此基础上叠加协同治理型与创新激励型两类政策工具,共同促进数字乡村建设的纵深发展。具体而言,东部沿海及部分中部地区因其自身物质基础较好,偏重多种政策工具的组合运用,西部及东北地区则更偏好能力建设型工具的运用。然而政策工具的选取并非一成不变,而是随着情境的变化由单一转向动态化与多样化。本研究可为数字乡村试点的深入推进提供工具借鉴,也可为相关部门的决策提供参考。

以制度型开放创新为核心 高标准高质量推进中国(新疆)自贸试验区建设

在我国自贸试验区建设十周年之际,2023年10月国务院印发了《中国(新疆)自由贸易试验区总体方案》,正式批准设立中国(新疆)自由贸易试验区,使新疆成为我国第22个自贸试验区,也是我国西北边境地区首个自贸试验区。文章深入研究分析了新疆自贸试验区设立的重大意义,并就自贸试验区在拉动我国经济增长和实现高质量发展中的作用,制度创新在自贸试验区打造一流营商环境、提升现代产业国际竞争力等方面所发挥的作用和影响,以及制度型开放创新与逆全球化背景下深入实施自贸试验区提升战略的关系等问题进行了全面分析与思考。在此基础上,就如何以高水平开放为引领,以制度创新为核心,高标准高质量建设新疆自贸试验区提出了思路与对策建议。

绿色金融试点政策对新能源企业技术创新的影响研究

绿色金融试点政策作为促进我国经济绿色低碳发展的重要途径,可以有效解决新能源行业技术创新资金瓶颈问题。选取2012—2021年A股上市新能源企业为研究对象,以2017年作为绿色金融试点政策实施的时间节点,构建双重差分模型实证研究了绿色金融试点政策对新能源企业技术创新的影响。结果表明:(1)绿色金融试点政策促进了新能源企业技术创新;(2)绿色金融试点政策可以缓解新能源企业融资约束,进而促进新能源企业技术创新;(3)在企业异质性分析方面,国有产权性质、社会责任意识较好、较高金融发展水平和较高绿色金融水平地区的新能源企业技术创新受绿色金融试点政策的促进效果更明显。研究结论可以为新能源企业制定技术创新策略和融资策略提供一定的决策支持。

AIGC时代学生设计思维培养的挑战与应对

以ChatGPT为代表的AIGC对学生设计思维的培养提出了新的挑战。从主体性的回归、艺术性的呼唤与创造性的提升3个角度对学生设计思维培养的困境进行解析,并通过理论阐释与教学,探讨对AIGC时代学生设计思维的培养进行批判性的思考。一味追随智能技术并不能有效培养学生的设计思维,而技术依赖则容易导致设计教学中主体性的消解、艺术性的背离和创新性思维能力的减退。面向AIGC时代应当正视学生设计思维培养的多元价值,通过人文教育加强学生的主体性,并以美育教育为基础,聚焦批判性思维的提升,以实现设计创新人才培养的可能。

稠油化学复合冷采技术研究与应用

我国稠油储量可观,其中60%的是深层稠油,而主流的蒸汽吞吐等热采技术采收率不足20%;稠油资源开发潜力极大,积极探索新的开采方式以提高采收率是石油领域高质量发展的必然选择。本文着重阐述稠油化学复合冷采技术体系构建及其现场应用,为中深层稠油的新型绿色低成本接替技术发展提供有效方案。在分析稠油组分的基础上,细致剖析稠油结构致黏机理,包括化学降黏机理、降低启动压力梯度机理、提高驱油效果机理在内的提高采收率机理,以丰富理论认识。面向工程应用亟需,从水溶性降黏剂分子设计与合成、自组装调堵剂研发两方面出发,突破稠油绿色化学驱油体系。基于发展的稠油化学复合冷采技术,完成了3个稠油油田示范工程应用,在提高产油量、控制含水率方面取得了良好成效。进一步梳理了分子采油理论与技术、渗流理论与数值模拟技术等方面的后续发展要点,以为深层稠油的绿色高效开发接替技术研究、稠油化学复合冷采技术推广应用研究等提供启发和参考。

科技金融驱动地区创新——基于“促进科技和金融结合试点”的自然实验

党的二十大报告强调,必须坚持科技是第一生产力,加快营造有利于实施创新驱动发展战略的良好环境。本文以2004-2019年城市为样本,检验“促进科技和金融结合”试点政策对城市创新水平的影响。研究发现,“促进科技和金融结合”试点政策显著提升了地区的创新水平。影响机制分析表明,“促进科技和金融结合”试点政策的实施加强了试点地区金融载体和创新载体两类载体的建设,进而提升了地区创新水平。进一步检验发现,“促进科技和金融结合”试点政策的创新促进效应主要存在于初始发展水平和人力资本水平更高的地区。研究结果还发现,“促进科技和金融结合”试点政策能够通过缓解企业融资约束提升企业的创新水平。本文的研究结果有助于为进一步推动科技和金融结合、加快实现我国高水平科技自立自强提供理论依据和政策参考。

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。