What Methods can an Organization Utilize to Spur Employees into Exploring New and Innovative Solutions to Organizational Challenges?

There is an overwhelming consensus among researchers that employee innovation can be generated through an organized process. Such a process involves the development of innovation leaders, widening employee access to challenge-pertinent information, and providing employees with adequate resources for experimentation. By implementing each of these steps, an organization can develop an employee innovation engine that will consistently produce innovative solutions to organizational challenges

What Strategies do Companies use to Transform Employees into Social Media Advocates?

There is an overwhelming consensus among researchers that employees have the potential to become excellent social ambassadors for their company. Readers of social media sites believe employees to be credible representatives of their organization, and therefore positive employee social media posts can create the image of a gratifying work environment and attract valuable talent to a particular organization. To capitalize on that recruitment advantage, an organization must initiate a process that enables and encourages employees to speak about the positive aspects of their work environment on social media platforms

What Factors Will Transform the Contemporary Work Environment and Characterize the Future of Work?

There is an overwhelming consensus among researchers that the contemporary work environment is transforming at a rapid pace. Advanced technology, increasing globalization, and the influx of a new generation of workers are all factors that will change the structures that govern the contemporary workplace. To prepare for the future of work, an organization must comprehend the manner in which each of these factors will engender changes in the evaluation of skillsets, the employer value proposition, and the available labor force

Image inpainting based on sparse representations with a perceptual metric

This paper presents an image inpainting method based on sparse representations optimized with respect to a perceptual metric. In the proposed method, the structural similarity (SSIM) index is utilized as a criterion to optimize the representation performance of image data. Specifically, the proposed method enables the formulation of two important procedures in the sparse representation problem, ‘estimation of sparse representation coefficients’ and ‘update of the dictionary’, based on the SSIM index. Then, using the generated dictionary, approximation of target patches including missing areas via the SSIM-based sparse representation becomes feasible. Consequently, image inpainting for which procedures are totally derived from the SSIM index is realized. Experimental results show that the proposed method enables successful inpainting of missing areas

Missing Texture Reconstruction Method Based on Perceptually Optimized Algorithm

<p/> <p>This paper presents a simple and effective missing texture reconstruction method based on a perceptually optimized algorithm. The proposed method utilizes the structural similarity (SSIM) index as a new visual quality measure for reconstructing missing areas. Furthermore, in order to adaptively reconstruct target images containing several kinds of textures, the following two novel approaches are introduced into the SSIM-based reconstruction algorithm. First, the proposed method performs SSIM-based selection of the optimal known local textures to adaptively obtain subspaces for reconstructing missing textures. Secondly, missing texture reconstruction that maximizes the SSIM index in the known neighboring areas is performed. In this approach, the nonconvex maximization problem is reformulated as a quasi convex problem, and adaptive reconstruction of the missing textures based on the perceptually optimized algorithm becomes feasible. Experimental results show impressive improvements of the proposed method over previously reported reconstruction methods.</p