针对等矩柱状投影(equirectangular projection,ERP)全景视频多功能视频编码(versatile video coding,VVC)帧内编码复杂度过高的问题,提出一种编码单元(coding unit,CU)快速划分算法。根据ERP采样特性,将编码帧分为不同纬度区域。基于...针对等矩柱状投影(equirectangular projection,ERP)全景视频多功能视频编码(versatile video coding,VVC)帧内编码复杂度过高的问题,提出一种编码单元(coding unit,CU)快速划分算法。根据ERP采样特性,将编码帧分为不同纬度区域。基于不同纬度区域CU四叉树深度的分布特性和相邻CU的相关性,对当前CU的划分模式进行提前终止决策;利用梯度差异评估当前CU纹理特性,跳过冗余的水平或垂直划分模式。针对纹理模糊CU,通过纬度采样权重加权的二次比较,判断是否跳过垂直划分模式;利用二维哈尔小波变换系数评估当前CU子块间的差异,判断是否跳过三叉树划分模式。实验结果表明,在全帧内模式下,与VVC官方测试平台相比,所提算法能节省43.85%的编码时间,码率仅增加0.85%,视频质量没有明显下降。展开更多
Traditional Enterprise Resource Planning (ERP) systems with relational databases take weeks to deliver predictable insights instantly. The most accurate information is provided to companies to make the best decisions ...Traditional Enterprise Resource Planning (ERP) systems with relational databases take weeks to deliver predictable insights instantly. The most accurate information is provided to companies to make the best decisions through advanced analytics that examine the past and the future and capture information about the present. Integrating machine learning (ML) into financial ERP systems offers several benefits, including increased accuracy, efficiency, and cost savings. Also, ERP systems are crucial in overseeing different aspects of Human Capital Management (HCM) in organizations. The performance of the staff draws the interest of the management. In particular, to guarantee that the proper employees are assigned to the convenient task at the suitable moment, train and qualify them, and build evaluation systems to follow up their performance and an attempt to maintain the potential talents of workers. Also, predicting employee salaries correctly is necessary for the efficient distribution of resources, retaining talent, and ensuring the success of the organization as a whole. Conventional ERP system salary forecasting methods typically use static reports that only show the system’s current state, without analyzing employee data or providing recommendations. We designed and enforced a prototype to define to apply ML algorithms on Oracle EBS data to enhance employee evaluation using real-time data directly from the ERP system. Based on measurements of accuracy, the Random Forest algorithm enhanced the performance of this system. This model offers an accuracy of 90% on the balanced dataset.展开更多
Industry 4.0, or the Fourth Industrial Revolution, is based on digitized the manufacturing process and makes use of all digital tools so its combination of various digital technologies computers, ERP software, IoT, ma...Industry 4.0, or the Fourth Industrial Revolution, is based on digitized the manufacturing process and makes use of all digital tools so its combination of various digital technologies computers, ERP software, IoT, machine learning and AI techniques, Manufacturing Execution Systems (MES), and big data analytics to create a new, fully digitized manufacturing system. The Critical Success Factors (CSFs) of MES adoption are both a quantitative and qualitative measurement. We use the case of ready-made garments to improve each of the three Overall Equipment Efficiency (OEE) factors: Availability, Performance, and Quality. In this study, we adopt real-time management of production activities on the shop floor from order receipt to finished products, then measure the improvement.展开更多
文摘针对等矩柱状投影(equirectangular projection,ERP)全景视频多功能视频编码(versatile video coding,VVC)帧内编码复杂度过高的问题,提出一种编码单元(coding unit,CU)快速划分算法。根据ERP采样特性,将编码帧分为不同纬度区域。基于不同纬度区域CU四叉树深度的分布特性和相邻CU的相关性,对当前CU的划分模式进行提前终止决策;利用梯度差异评估当前CU纹理特性,跳过冗余的水平或垂直划分模式。针对纹理模糊CU,通过纬度采样权重加权的二次比较,判断是否跳过垂直划分模式;利用二维哈尔小波变换系数评估当前CU子块间的差异,判断是否跳过三叉树划分模式。实验结果表明,在全帧内模式下,与VVC官方测试平台相比,所提算法能节省43.85%的编码时间,码率仅增加0.85%,视频质量没有明显下降。
文摘Traditional Enterprise Resource Planning (ERP) systems with relational databases take weeks to deliver predictable insights instantly. The most accurate information is provided to companies to make the best decisions through advanced analytics that examine the past and the future and capture information about the present. Integrating machine learning (ML) into financial ERP systems offers several benefits, including increased accuracy, efficiency, and cost savings. Also, ERP systems are crucial in overseeing different aspects of Human Capital Management (HCM) in organizations. The performance of the staff draws the interest of the management. In particular, to guarantee that the proper employees are assigned to the convenient task at the suitable moment, train and qualify them, and build evaluation systems to follow up their performance and an attempt to maintain the potential talents of workers. Also, predicting employee salaries correctly is necessary for the efficient distribution of resources, retaining talent, and ensuring the success of the organization as a whole. Conventional ERP system salary forecasting methods typically use static reports that only show the system’s current state, without analyzing employee data or providing recommendations. We designed and enforced a prototype to define to apply ML algorithms on Oracle EBS data to enhance employee evaluation using real-time data directly from the ERP system. Based on measurements of accuracy, the Random Forest algorithm enhanced the performance of this system. This model offers an accuracy of 90% on the balanced dataset.
文摘Industry 4.0, or the Fourth Industrial Revolution, is based on digitized the manufacturing process and makes use of all digital tools so its combination of various digital technologies computers, ERP software, IoT, machine learning and AI techniques, Manufacturing Execution Systems (MES), and big data analytics to create a new, fully digitized manufacturing system. The Critical Success Factors (CSFs) of MES adoption are both a quantitative and qualitative measurement. We use the case of ready-made garments to improve each of the three Overall Equipment Efficiency (OEE) factors: Availability, Performance, and Quality. In this study, we adopt real-time management of production activities on the shop floor from order receipt to finished products, then measure the improvement.
