This article explores the use of social networks by workers in Abidjan, Côte d’Ivoire, with particular emphasis on a descriptive or quantitative analysis aimed at understanding motivations and methods of use. Mo...This article explores the use of social networks by workers in Abidjan, Côte d’Ivoire, with particular emphasis on a descriptive or quantitative analysis aimed at understanding motivations and methods of use. More than five hundred and fifty questionnaires were distributed, highlighting workers’ preferred digital channels and platforms. The results indicate that the majority use social media through their mobile phones, with WhatsApp being the most popular app, followed by Facebook and LinkedIn. The study reveals that workers use social media for entertainment purposes and to develop professional and social relationships, with 55% unable to live without social media at work for recreational activities. In addition, 35% spend on average 1 to 2 hours on social networks, mainly between 12 p.m. and 2 p.m. It also appears that 46% believe that social networks moderately improve their productivity. These findings can guide marketing strategies, training, technology development and government policies related to the use of social media in the workplace.展开更多
薄板自动化焊时产生的光反射、飞溅、粉尘等噪声使焊缝位置信息被遮挡,从而影响特征点的识别与提取。因此,提出了用连通区域的算法对焊缝的特征进行标记,并改进了连通区域算法用于提取焊缝特征点和获取其位置信息。在图像预处理之前,用...薄板自动化焊时产生的光反射、飞溅、粉尘等噪声使焊缝位置信息被遮挡,从而影响特征点的识别与提取。因此,提出了用连通区域的算法对焊缝的特征进行标记,并改进了连通区域算法用于提取焊缝特征点和获取其位置信息。在图像预处理之前,用感兴趣区域(Region of interest,ROI)方法对激光条纹进行图像分割,可滤除大量弧光、飞溅等噪声;在图像预处理的过程中,采用中值滤波和最大类间方差的二值化算法降低激光条纹附近的干扰噪声,将激光条纹与背景分离,使焊缝特征更清晰、明显;在图像预处理后,用连通区域的方法对激光条纹进行标记,通过改进的算法判断出连通区域的位置,从而识别焊缝特征点,获得焊缝特征点的位置信息。该算法不仅保留了焊缝激光条纹的边缘信息,还能在复杂的工作环境中完成焊缝特征的识别。通过对比薄板的实际间隙宽度和试验计算出的间隙宽度,该算法平均误差在0.067 mm以内,满足工业中的精度要求,适合激光视觉的焊缝跟踪过程。展开更多
文摘This article explores the use of social networks by workers in Abidjan, Côte d’Ivoire, with particular emphasis on a descriptive or quantitative analysis aimed at understanding motivations and methods of use. More than five hundred and fifty questionnaires were distributed, highlighting workers’ preferred digital channels and platforms. The results indicate that the majority use social media through their mobile phones, with WhatsApp being the most popular app, followed by Facebook and LinkedIn. The study reveals that workers use social media for entertainment purposes and to develop professional and social relationships, with 55% unable to live without social media at work for recreational activities. In addition, 35% spend on average 1 to 2 hours on social networks, mainly between 12 p.m. and 2 p.m. It also appears that 46% believe that social networks moderately improve their productivity. These findings can guide marketing strategies, training, technology development and government policies related to the use of social media in the workplace.
文摘薄板自动化焊时产生的光反射、飞溅、粉尘等噪声使焊缝位置信息被遮挡,从而影响特征点的识别与提取。因此,提出了用连通区域的算法对焊缝的特征进行标记,并改进了连通区域算法用于提取焊缝特征点和获取其位置信息。在图像预处理之前,用感兴趣区域(Region of interest,ROI)方法对激光条纹进行图像分割,可滤除大量弧光、飞溅等噪声;在图像预处理的过程中,采用中值滤波和最大类间方差的二值化算法降低激光条纹附近的干扰噪声,将激光条纹与背景分离,使焊缝特征更清晰、明显;在图像预处理后,用连通区域的方法对激光条纹进行标记,通过改进的算法判断出连通区域的位置,从而识别焊缝特征点,获得焊缝特征点的位置信息。该算法不仅保留了焊缝激光条纹的边缘信息,还能在复杂的工作环境中完成焊缝特征的识别。通过对比薄板的实际间隙宽度和试验计算出的间隙宽度,该算法平均误差在0.067 mm以内,满足工业中的精度要求,适合激光视觉的焊缝跟踪过程。
