Contribution of the MERISE-Type Conceptual Data Model to the Construction of Monitoring and Evaluation Indicators of the Effectiveness of Training in Relation to the Needs of the Labor Market in the Republic of Congo

This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.

Monitoring and Evaluation of Present Situation of Environmental Quality in the Sea Area near the Aojiang Estuary in Wenzou

Based on the monitoring results of environmental quality in the sea area near the Aojiang estuary in Wenzou during 2010-2012,the present situation of environmental quality in the sea area was analyzed and evaluated. The results show that p H,DO,CODMn,petroleum,and heavy metals( Cu,Pb,Zn,Cd,Hg,As and Cr) in the sea area near the Aojiang estuary did not exceed the second-class standard of Seawater Quality Standard( GB 3097-1997),but both inorganic nitrogen and reactive phosphate in the sea area exceeded the second-class standard seriously,and the water quality of the sea area was in an eutrophic state; domestic sewage and fertilizer loss were the main sources of nitrogen and phosphorus. The standard index of most evaluation factors of sediment quality except for Zn was smaller than 1,meeting the demands of sediment quality for environmental protection.

Using Grey Target Theory for Power Quality Evaluation Based on Power Quality Monitoring Data

Smart grid puts forward higher requirements for power quality.Power quality evaluation can provide a decision-making basis for quality improvement.Based on power quality monitoring data,a grey target method is proposed for power quality evaluation.The grey target is composed of power quality evaluation standard and power quality monitoring data to be evaluated.Combining with the characteristics of each power quality evaluation index,the target center of the whole grey target system is found.Then,the power quality monitoring data to be evaluated and the power quality standard mode are compared and analyzed to construct the power quality grey correlation difference information space.Finally,the target center coefficient and target degree of power quality are calculated to realize the comprehensive evaluation of power quality,and the evaluation grade of power quality monitoring data to be evaluated is obtained.Compared with the evaluation results of the existing literature,the effectiveness of the proposed method is verified,which shows that grey target theory is reasonable in the comprehensive evaluation of power quality.

The safety parameters monitoring system for the coal mine based on CAN bus communication and intelligent data acquisition

In this paper,a monitoring and controlling system for the safety in production and environmental parameters of a small and medium-sized coal mine has been developed after analyzing the current domestic coal production and security conditions. The client computer can convert the analog signal about the safety in production and environmental parameters detected from the monitoring terminal into digital signal,and then,send the signal to the coal mine safety monitoring centre. This information can be analyzed,judged,and diagnosed by the monitoring-management-controlling software for helping the manager and technical workers to control the actual underground production and security situations. The system has many advantages including high reliability,better performance of real-time monitoring,faster data communicating and good practicability,and it can effectively prevent the occurrence of safety incidents in coal mines.

RELIABILITY EVALUATION MODEL BASED ON DATA FUSION FOR AIRCRAFT ENGINES

Reliability evaluation for aircraft engines is difficult because of the scarcity of failure data. But aircraft engine data are available from a variety of sources. Data fusion has the function of maximizing the amount of valu- able information extracted from disparate data sources to obtain the comprehensive reliability knowledge. Consid- ering the degradation failure and the catastrophic failure simultaneously, which are competing risks and can affect the reliability, a reliability evaluation model based on data fusion for aircraft engines is developed, Above the characteristics of the proposed model, reliability evaluation is more feasible than that by only utilizing failure data alone, and is also more accurate than that by only considering single failure mode. Example shows the effective- ness of the proposed model.

Comprehensive evaluation method of urban air quality statistics based on environmental monitoring data and its application

Air quality monitoring is effective for timely understanding of the current air quality status of a region or city.Currently,the huge volume of environmental monitoring data,which has reasonable real-time performance,provides strong support for in-depth analysis of air pollution characteristics and causes.However,in the era of big data,to meet current demands for fine management of the atmospheric environment,it is important to explore the characteristics and causes of air pollution from multiple aspects for comprehensive and scientific evaluation of air quality.This study reviewed and summarized air quality evaluation methods on the basis of environmental monitoring data statistics during the 13th Five-Year Plan period,and evaluated the level of air pollution in the Beijing-Tianjin-Hebei region and its surrounding areas(i.e.,the“2+26”region)during the period of the three-year action plan to fight air pollution.We suggest that air quality should be comprehensively,deeply,and scientifically evaluated from the aspects of air pollution characteristics,causes,and influences of meteorological conditions and anthropogenic emissions.It is also suggested that a threeyear moving average be introduced as one of the evaluation indexes of long-term change of pollutants.Additionally,both temporal and spatial differences should be considered when removing confounding meteorological factors.

Information Monitoring Technology for Support Structure of Railway Tunnel During Operation

In the process of railway construction, because of the inconvenience ofgeological condition, water bursting and mud surging happen frequently, and the laterdeformation of support structure on the happening geology section would threaten thenormal running of railway. The limit difference of deformation control value of thesupport structure section where geological accidents frequently happen, is small, andartificial half-automatic supervisory technology cannot get the health condition of tunnelin time, resulting many cars speed-down accidents due to deformation of supportstructure. Through design innovation, we introduce TGMIS in the later period ofYanzishan railway construction to quickly capture the deformation of support structure,the strain of lining concrete, the strain of steel frame, stress of surrounding soil, stress ofsurrounding water, strain of second lining steel bar and other situ data. Also we setobservation prism and measuring robot device in specific position inside tunnel, androbot laser locator laser spot is projected onto reflection target surface, by graphicprocessing algorithm, the receiver calculates the measured value and standard value ofthe 3D coordinates of the laser spot. Then the information is transmitted throughtransmitting device, transducer and USB-485 to computer to predict and evaluate thehealth condition of the support structure of the tunnel so as to provide safety warninginformation. Provide timely and reliable data for the operation company to avoid theoccurrence of vicious accidents.

Research on Wireless Monitoring Technology of the Well Site Environment

Based on the characteristics of wireless communication technology and Wireless Sensor Network, this paper studies the well site environmental monitoring system. The relevant hardware and software of the system are designed to monitor the well site environment, thus preventing downhole accidents. The system uses the wireless ZigBee technology as the transmission mode, and combines the virtual instrument technology to design the upper machine interface. The test results show that the system can monitor the outdoor environment in real time. When the environmental parameters exceed the set value, the corresponding location of the LabVIEW interface will send an alarm.

Monitoring Land Use and Infrastructure Changes in Industrial Complex Using Geo-Informatics Technology in Gujarat State, India

In the present study, detailed investigations have been carried out in Petroleum, Chemicals and Petrochemical Investment Region (PCPIR) area in Vygra and Bharuch Talukas in Bharuch district of Gujarat State. Indian Remote Sensing Satellite (IRS-P6) LISS-III, LISS-IV and CARTOSAT digital data covering PCPIR area in Bharuch district for the period of January & February of 2011, 2012 and 2013 was analyzed for land use/land cover mapping and monitoring the changes in land use. Various thematic land use/land cover maps were prepared and GIS database for various thematic layers have been generated using satellite and ground based information. The results indicate that the major land use in the PCPIR area is agriculture with crop lands ranging from 61 to 63 per cent of the total area. Crop land has decreased from 64.7% during 2011 to 62.7% during 2013 in the PCPIR region. Area under plantations in PCPIR area has also decreased from 5.5% during 2011 to 5.2% during 2012. The industrial area has increased from 6.0% to 7.6% of the total area of the PCPIR region. The total built-up area (industries & village area) has increased from 7.1% during 2011 to 8.7% during 2013. Tree plantations in the area of around 42 ha were carried out by GIDC during 2012 and 2013 to increase the green cover in the PCPIR area.

露天矿边坡稳定性的层次分析-模糊综合评价耦合分析

露天煤矿台阶所构成的边坡对矿山资源生产及运输发挥着重要的作用,也承载着煤炭外运的任务,其稳定性对矿山连续生产具有重要意义。文章在边坡地质调查和监测信息分析的基础上,充分考虑边坡几何形态、地质信息、气象水文信息、现场监测信息等指标,以层次分析法确定边坡稳定性分析的指标权重,基于隶属度最大原则确定边坡稳定性状态,建立了多源信息融合的边坡层次分析-模糊综合评价模型。将该模型应用于扎哈淖尔露天煤矿北帮边坡稳定性分析中,最后基于数值模拟对模型进行了验证。研究表明,北帮边坡基本稳定,基于数值模拟得出扎哈淖尔露天煤矿北帮边坡滑移面安全系数为1.121,模型结果与数值模拟结果所得到的边坡稳定性状态吻合度较好,验证了模型的有效性。该模型可以充分考虑多重信息对边坡稳定性分析的贡献,从而更全面准确分析边坡稳定性。

基于红外成像技术的城乡局部环境监测与分析研究

结合红外探测成像技术在复杂环境监测中的独特优势,研制了基于连续变焦中波红外成像技术的城乡局部环境监测系统,对城乡局部地区燃煤情况开展实时监测,并完成数据处理分析,为研究城乡地区燃煤趋势和特点、实施监控管理提供有力技术和数据支撑。经过在某市城乡结合地区开展的实地监测试验验证,证明该系统运行稳定、成像清晰,可实现对燃煤地区全局和重点位置的全天候在线监测,数据处理准确有效,该系统具有良好的工程应用价值。

智慧引领、数据赋能--全国城市交通跟踪监测与评估

通过智慧化和数据驱动的方式,提升我国城市交通基础设施监测和评估水平。首先,分析我国城市交通基础设施规模庞大但监测和管理水平有待提高的现状,并强调利用大数据技术进行城市交通监测的重要性。其次,回顾国内外城市交通监测理论与实践的发展,包括城市交通年报的编制和大范围城市群的交通状况监测报告。介绍全国主要城市交通监测技术方面的探索,包括技术路线、数据来源、指标筛选、算法优化和效果回顾等。结果显示,报告发布引起了社会各界对城市交通问题的广泛关注,大量城市也出台了相应改善措施,全国层面的交通监测让交通设施水平和服务水平透明化,进而推动城市交通治理。最后,提出未来的研究方向,从监测走向决策支持,开展精细化交通治理研究等。通过智慧化和数据化手段提升城市交通监测评估水平,为我国城市交通治理提供了科学支撑。

高校智慧教育环境中网络数据安全防护面临的挑战与应对策略

随着智慧教育的发展,高校网络数据面临着前所未有的安全挑战。围绕数据治理、技术基础设施的安全性、混合式教学环境下的网络边界防护、高级持续性威胁(APT)的网络防御,以及校园网络安全文化和行为管理等关键问题,提出了一系列综合性防护策略。这些策略涉及加强数据治理体系、提升技术基础设施安全、优化混合教学环境中的网络边界防护措施、有效应对高级持续性威胁(APT),以及培育校园网络安全文化和行为管理。强调构建持续监控与评估的策略体系,动态调整安全措施,以确保高校智慧教育系统的稳定运行。

基于高通量监测数据的PMF源解析数据输入量研究

为探究数据输入量的变化对源解析结果的影响,以上海某工业区的大气重金属高通量监测数据为例,按不同数据量将监测数据分别输入至正定矩阵因子分解(Positive Matrix Factorization, PMF)模型中,通过考察模型中Q理论值(Qtheo)与Q计算值(Qtrue)的接近程度、源分类以及源贡献与研究区污染源分布特点的吻合情况,分析数据输入量对源解析结果的影响。结果显示:该区域大气重金属污染受工业生产主导(64.44%),其次是扬尘(19.60%)和交通运输(15.96%)。通过对数据量的考察,发现输入量为60~120时能够得出研究区域的污染源数量与贡献率,但考虑到测试成本、获取数据的时间,认为输入量为60~80时,也能得出合理的源解析结果。短期高通量的分钟级数据集,有益于PMF模型输出高精密度、高时效性的源解析结果,是解决应急污染监控的最佳手段。

浅谈数据资产化对推进生态环境监测数据共享利用的影响

传统生态环境监测数据共享利用存在共享意愿不高、权益不对称、低效率和数据权益不清等问题。数据资产化为解决生态环境监测数据共享难题提供了新思路。本文首先梳理了生态环境监测领域数据共享存在数据孤岛、数据质量等问题及面临的挑战。其次,从推动资产收益、培育监测市场、服务政府管理决策、推进数据共享及技术变革等角度对生态环境监测数据资产化潜在影响进行了讨论。最后,对生态环境监测领域如何推进数据资产化、促进监测数据资源高效共享利用进行了策略分析和展望。

基于长短时记忆的农作物生长环境数据预测

针对传统温室农作物生长监控系统控制灵活性差且精确度低等问题,设计了一个面向智慧农业的农作物生长闭环监控系统.引入单变量长短时记忆(long short-term memory,LSTM)网络模型,对土壤含水率、土壤温度和土壤电导率3个农作物生长环境数据进行预测研究.在优化时间步长参数的基础上,分析不同预测步长对单变量LSTM模型预测准确性的影响,采用不同时间段的测试集数据对模型的预测性能和稳定性进行验证.分别采用单变量LSTM模型、最小绝对值收敛和选择算法、随机森林回归、双向LSTM模型和编解码LSTM模型进行预测对比,结果表明,单变量LSTM模型预测的平均绝对误差值和均方根误差值均为最小,模型具有更好的准确性和稳定性.本研究设计的农作物生长闭环监控系统能有效预测农作物的生长环境数据,为农作物监控系统的智能控制提供有效数据支撑.

基于大数据赋能的重大科技项目监测评估新模式研究

监测评估作为重大科技项目组织实施的重要抓手,在推动完善项目管理、提升管理绩效、构建科技大监督格局方面发挥了重要作用。但是,目前仍存在数字化评估手段有限、对科技决策支撑作用不充分和监测评估效能尚未充分释放等问题。为进一步优化重大科技项目组织实施模式,让数字化、信息化工具更大程度赋能科技评估,以重大科技项目为研究对象,研究了国内外重大科技项目监测评估的模式,围绕中国现阶段重大科技项目监测评估面临的挑战,探讨了大数据赋能监测评估的理论依据、主要特点,探索构建了重大科技项目数据治理新路径,并提出了建立重大科技项目管理新机制、新方法、新模式等有关政策建议。

大数据时代皮革行业环境监测技术应用及发展探讨

皮革生产加工过程中不仅涉及多种化学物质的使用,还因为“三废”的排放对环境造成了潜在的风险。大数据时代的到来给皮革行业的环境监测提供了更为有效的手段。本文在分析皮革行业环境监测现状及挑战的基础上,介绍了大数据环境检测技术概念及关键技术应用,并对技术的未来应用进行前景展望,以期为我国皮革行业环保提供借鉴。

基于生成对抗网络的驾驶行为风险监测方法

针对真实驾驶场景下驾驶行为风险难以准确判断的问题,提出一种基于生成对抗网络的生成序列评估框架,旨在通过车辆行驶状态数据与驾驶场景信息匹配度评估来提高驾驶行为风险判断的准确性。构建真实驾驶场景数据匹配序列框架,利用生成对抗网络增加不同驾驶场景的数据量,提出一个驾驶员个性化情景感知样本数据集,对比分析真实数据和生成数据,并验证生成对抗网络检索与生成框架在匹配车辆行驶状态数据与驾驶场景信息方面的有效性和准确性。采用无监督学习生成评估框架,结合自回归模型中的监督训练控制策略来解决数据扩增问题,并通过迭代更新样本序列进行策略集成以保持模型鲁棒性。实验结果表明,相较于现有方法,所提研究框架在识别危险驾驶状态方面具有明显优势,为车辆行驶状态数据与驾驶场景信息的匹配评估提供了一种新的视角。

基于大数据的混合式教学质量监控与评估实施路径研究

教学质量是民办高职院校的立身之本,是改革与发展的生命线。综合利用现代化教育技术的混合式教学,通过线上资源、线下活动、过程评估,成功带动民办高职院校在教学质量上产生变化,为建构和实施基于大数据的混合式教学质量监控与评估体系,强化对“教”与“学”的监督、控制和指导,创造必要条件,成功形塑以提升教学质量为导向的混合式教学质量监控预评估工作机制。研究以基于大数据的混合式教学质量监控与评估体系为锚定点,分析民办高职院校实施混合式教学质量监控与评估的现实路径,实现在一定范围内,教学质量监控与评估体系下可持续发展的示范引领,对民办高职院校科研、管理、教学、服务产生影响,推进数字化教学的同时,实现对教学质量的全流程实时监控、反馈与评价。