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 struct...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.展开更多
Latent variable models can effectively determine the condition of essential rotating machinery without needing labeled data.These models analyze vibration data via an unsupervised learning strategy.Temporal preservati...Latent variable models can effectively determine the condition of essential rotating machinery without needing labeled data.These models analyze vibration data via an unsupervised learning strategy.Temporal preservation is necessary to obtain an informative latent manifold for the fault diagnosis task.In a temporalpreserving context,two approaches exist to develop a condition-monitoring methodology:offline and online.For latent variable models,the available training modes are not different.While many traditional methods use offline training,online training can dynamically adjust the latent manifold,possibly leading to better fault signature extraction from the vibration data.This study explores online training using temporal-preserving latent variable models.Within online training,there are two main methods:one focuses on reconstructing data and the other on interpreting the data components.Both are considered to evaluate how they diagnose faults over time.Using two experimental datasets,the study confirms that models from both training modes can detect changes in machinery health and identify faults even under varying conditions.Importantly,the complementarity of offline and online models is emphasized,reassuring their versatility in fault diagnostics.Understanding the implications of the training approach and the available model formulations is crucial for further research in latent variable modelbased fault diagnostics.展开更多
We present a temperature monitoring and warning system, which is based on wireless communi- cation technology and applied in train switchgear in this paper. The system is consists of three parts, including wireless te...We present a temperature monitoring and warning system, which is based on wireless communi- cation technology and applied in train switchgear in this paper. The system is consists of three parts, including wireless temperature detection module, inter-vehicle transmission networks module and?remote monitoring server. The switchgear contact temperature data are collected via the wireless temperature detection module and exchanged in inter-vehicle wireless networking by Zigbee modules. Then the temperature of train switchgear cabinets can be monitored remotely through the GPRS wireless communication.展开更多
The monitoring of flue gas of the thermal power plants is of great significance in energy conservation and environmental protection.Spectral technique has been widely used in the gas monitoring system for predicting t...The monitoring of flue gas of the thermal power plants is of great significance in energy conservation and environmental protection.Spectral technique has been widely used in the gas monitoring system for predicting the concentrations of specific gas components.This paper proposes flue gas monitoring system with empirically-trained dictionary(ETD)to deal with the complexity and biases brought by the uninformative spectral data.Firstly,ETD is extracted from the raw spectral data by an alternative optimization between the sparse coding stage and the dictionary update stage to minimize the error of sparse representation.D1,D2 and D3 are three types of ETD obtained by different methods.Then,the predictive model of component concentration is constructed on the ETD.In the experiments,two real flue gas spectral datasets are collected and the proposed method combined with the partial least squares,the background propagation neural network and the support vector machines are performed.Moreover,the optimal parameters are chosen according to the 10-fold root-mean-square error of cross validation.The experimental results demonstrate that the proposed method can be used for quantitative analysis effectively and ETD can be applied to the gas monitoring systems.展开更多
Background: In the context of the fight against HIV, a lack of skills in monitoring and evaluating the personnel in charge of activities has been identified at the national level. It was the subject of a priority axis...Background: In the context of the fight against HIV, a lack of skills in monitoring and evaluating the personnel in charge of activities has been identified at the national level. It was the subject of a priority axis of the national plan for monitoring and evaluating the fight against HIV (2006-2010) that was aimed at strengthening the capacities of actors in this area. To increase the critical mass of competent human resources in the short term, the National Institute of Public Health (NIPH) of Côte d’Ivoire organized monitoring and evaluation training sessions for healthcare professionals from 2011 to 2016. Methods: A single case study with multiple levels of analysis was carried out, combining a qualitative survey and a literature review. An evaluation was carried out six months after each training session. In addition, the results of the pre- and post-tests and of the daily and final evaluations that accompanied the various training sessions were used to provide further information. The qualitative data collected were analyzed using INVIVO 15 software. Results: Some 89 health professionals (69% men and 31% women) working at the national level (51% at the central level, including 58% in health programs) and in development partner agencies (37%) participated in this capacity building program. Most participants were senior health managers (56%), data managers (23%), and statisticians and computer scientists (10%). Almost all the trainings were financed by 16 technical and financial partners (85%), mainly the MEASURE Evaluation project (27%). Conclusion: M&E training, despite all its imperfections, has made it possible to identify M&E training needs at the national level and to increase the critical mass of national skills and to have some culture in M&E.展开更多
Objectives: The study was to determine the impact of using the FreeStyle Libre<sup>TM</sup> flash glucose monitoring system on glycemic control and the rate of events due to diabetes in people with diabete...Objectives: The study was to determine the impact of using the FreeStyle Libre<sup>TM</sup> flash glucose monitoring system on glycemic control and the rate of events due to diabetes in people with diabetes from different types and age groups. Methods: a retrospective cohort chart review study was carried out at three centers in the Taif region in the Kingdom of Saudi Arabia: The study was approved by an accredited centralized institutional review board. Paper or electronic medical records were included for individuals of any age with diabetes (type 1, type 2, gestational diabetes) managed with diet, insulin therapy, or/and oral antihyperglycemic medication and/or non-insulin injection therapy. The primary outcome measure was the laboratory HbA1c level as well as reduction. Secondary outcome measures were frequency of severe hypoglycemia, admission to hospital or ER visit related to diabetes complications, and severe hyperglycemia (DKA or HHS). Results: Data was analyzed from 1695 patients. The average HbA1c before using the flash glucose monitoring system was 9.60% ± 1.44% and 3 months HbA1c after using the FreeStyle Libre<sup>TM</sup> flash glucose monitoring system was 8.70% + 1.45% for a difference of -0.90% ([95% CI -0.92: -0.88];p 65 years, (p-values Conclusion: The benefits of using the FreeStyle Libre<sup>TM</sup> flash glucose monitoring system are self-evident in reducing HbA1c and events due to hyperglycemia or hypoglycemia.展开更多
针对三维人体姿态估计的便捷性与准确性提升需求,提出一种基于TM-Net网络估计算法。该算法以MediaPipe为中心,融合帧率计算、动作检测、动作计数和真实坐标解析等多功能模块,实现对人体运动的精准检测与计数。针对公共数据集LSP(Leeds S...针对三维人体姿态估计的便捷性与准确性提升需求,提出一种基于TM-Net网络估计算法。该算法以MediaPipe为中心,融合帧率计算、动作检测、动作计数和真实坐标解析等多功能模块,实现对人体运动的精准检测与计数。针对公共数据集LSP(Leeds Sports Pose)和自建校园健身房运动数据集使用关键点的正确性概率(Probability of Correct Keypoint,PCK)、关节位置误差平均值(Mean Per Joint Position Error,MPJPE)和普罗克鲁斯对齐后的平均关节位置误差(Procrustes-Aligned Mean Per Joint Position Error,PA-MPJPE)等指标对该算法进行评估,并与目前先进的TP-3D网络估计算法进行对比。结果表明,TM-Net具有更高的准确率。此外,以开合跳为例进行消融实验,结果表明,TM-Net具有更强的泛化能力,能适应不同个体及拍摄角度的变化,满足了运动监测的实际需求。展开更多
文摘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.
文摘Latent variable models can effectively determine the condition of essential rotating machinery without needing labeled data.These models analyze vibration data via an unsupervised learning strategy.Temporal preservation is necessary to obtain an informative latent manifold for the fault diagnosis task.In a temporalpreserving context,two approaches exist to develop a condition-monitoring methodology:offline and online.For latent variable models,the available training modes are not different.While many traditional methods use offline training,online training can dynamically adjust the latent manifold,possibly leading to better fault signature extraction from the vibration data.This study explores online training using temporal-preserving latent variable models.Within online training,there are two main methods:one focuses on reconstructing data and the other on interpreting the data components.Both are considered to evaluate how they diagnose faults over time.Using two experimental datasets,the study confirms that models from both training modes can detect changes in machinery health and identify faults even under varying conditions.Importantly,the complementarity of offline and online models is emphasized,reassuring their versatility in fault diagnostics.Understanding the implications of the training approach and the available model formulations is crucial for further research in latent variable modelbased fault diagnostics.
文摘We present a temperature monitoring and warning system, which is based on wireless communi- cation technology and applied in train switchgear in this paper. The system is consists of three parts, including wireless temperature detection module, inter-vehicle transmission networks module and?remote monitoring server. The switchgear contact temperature data are collected via the wireless temperature detection module and exchanged in inter-vehicle wireless networking by Zigbee modules. Then the temperature of train switchgear cabinets can be monitored remotely through the GPRS wireless communication.
基金supported by the National Natural Science Foundation of China(61375055)the Program for New Century Excellent Talents in University(NCET-12-0447)+2 种基金the Natural Science Foundation of Shaanxi Province of China(2014JQ8365)the State Key Laboratory of Electrical Insulation and Power Equipment(EIPE16313)the Fundamental Research Funds for the Central University
文摘The monitoring of flue gas of the thermal power plants is of great significance in energy conservation and environmental protection.Spectral technique has been widely used in the gas monitoring system for predicting the concentrations of specific gas components.This paper proposes flue gas monitoring system with empirically-trained dictionary(ETD)to deal with the complexity and biases brought by the uninformative spectral data.Firstly,ETD is extracted from the raw spectral data by an alternative optimization between the sparse coding stage and the dictionary update stage to minimize the error of sparse representation.D1,D2 and D3 are three types of ETD obtained by different methods.Then,the predictive model of component concentration is constructed on the ETD.In the experiments,two real flue gas spectral datasets are collected and the proposed method combined with the partial least squares,the background propagation neural network and the support vector machines are performed.Moreover,the optimal parameters are chosen according to the 10-fold root-mean-square error of cross validation.The experimental results demonstrate that the proposed method can be used for quantitative analysis effectively and ETD can be applied to the gas monitoring systems.
文摘Background: In the context of the fight against HIV, a lack of skills in monitoring and evaluating the personnel in charge of activities has been identified at the national level. It was the subject of a priority axis of the national plan for monitoring and evaluating the fight against HIV (2006-2010) that was aimed at strengthening the capacities of actors in this area. To increase the critical mass of competent human resources in the short term, the National Institute of Public Health (NIPH) of Côte d’Ivoire organized monitoring and evaluation training sessions for healthcare professionals from 2011 to 2016. Methods: A single case study with multiple levels of analysis was carried out, combining a qualitative survey and a literature review. An evaluation was carried out six months after each training session. In addition, the results of the pre- and post-tests and of the daily and final evaluations that accompanied the various training sessions were used to provide further information. The qualitative data collected were analyzed using INVIVO 15 software. Results: Some 89 health professionals (69% men and 31% women) working at the national level (51% at the central level, including 58% in health programs) and in development partner agencies (37%) participated in this capacity building program. Most participants were senior health managers (56%), data managers (23%), and statisticians and computer scientists (10%). Almost all the trainings were financed by 16 technical and financial partners (85%), mainly the MEASURE Evaluation project (27%). Conclusion: M&E training, despite all its imperfections, has made it possible to identify M&E training needs at the national level and to increase the critical mass of national skills and to have some culture in M&E.
文摘Objectives: The study was to determine the impact of using the FreeStyle Libre<sup>TM</sup> flash glucose monitoring system on glycemic control and the rate of events due to diabetes in people with diabetes from different types and age groups. Methods: a retrospective cohort chart review study was carried out at three centers in the Taif region in the Kingdom of Saudi Arabia: The study was approved by an accredited centralized institutional review board. Paper or electronic medical records were included for individuals of any age with diabetes (type 1, type 2, gestational diabetes) managed with diet, insulin therapy, or/and oral antihyperglycemic medication and/or non-insulin injection therapy. The primary outcome measure was the laboratory HbA1c level as well as reduction. Secondary outcome measures were frequency of severe hypoglycemia, admission to hospital or ER visit related to diabetes complications, and severe hyperglycemia (DKA or HHS). Results: Data was analyzed from 1695 patients. The average HbA1c before using the flash glucose monitoring system was 9.60% ± 1.44% and 3 months HbA1c after using the FreeStyle Libre<sup>TM</sup> flash glucose monitoring system was 8.70% + 1.45% for a difference of -0.90% ([95% CI -0.92: -0.88];p 65 years, (p-values Conclusion: The benefits of using the FreeStyle Libre<sup>TM</sup> flash glucose monitoring system are self-evident in reducing HbA1c and events due to hyperglycemia or hypoglycemia.
文摘针对三维人体姿态估计的便捷性与准确性提升需求,提出一种基于TM-Net网络估计算法。该算法以MediaPipe为中心,融合帧率计算、动作检测、动作计数和真实坐标解析等多功能模块,实现对人体运动的精准检测与计数。针对公共数据集LSP(Leeds Sports Pose)和自建校园健身房运动数据集使用关键点的正确性概率(Probability of Correct Keypoint,PCK)、关节位置误差平均值(Mean Per Joint Position Error,MPJPE)和普罗克鲁斯对齐后的平均关节位置误差(Procrustes-Aligned Mean Per Joint Position Error,PA-MPJPE)等指标对该算法进行评估,并与目前先进的TP-3D网络估计算法进行对比。结果表明,TM-Net具有更高的准确率。此外,以开合跳为例进行消融实验,结果表明,TM-Net具有更强的泛化能力,能适应不同个体及拍摄角度的变化,满足了运动监测的实际需求。
