No abstract

No abstract

No abstract

Theme:This panel brings together technology experts and business leaders and provide first hand insight to the evolution of cloud computing and IT as a Service (ITaaS), from both technology and business model perspectives. The panel will discuss the disruptive nature of Cloud computing and its business model, including the impact to the current enterprise IT industry, to the service provider industry, to the enterprise software industry, to the networking industry, and to the service industry. The panel will also discuss the confluence of SOA paradigm and SaaS paradigm and examine its implication to the enterprise IT architecture. The panel will also help audience understand the limitation and challenges for cloud computing and ITaaS. The audience of this panel is targeted at the technology leaders and business decision makers in enterprise IT, software industry, and networking industry. About the Speakers:Geng Lin has more than 15 years of leadership experience in the hi-tech industry, where he has held a variety of leadership positions spanning business planning, product development and technology strategy with leading companies such as Cisco, Motorola, and Nortel Networks. He has been CTO of Cisco IBM Alliance at Cisco Systems since 2008 where he is responsible for technology strategy of joint Cisco-IBM solutions. Prior to Cisco, he was VP of Software Engineering at Netopia Inc, a Motorola company. Netopia was a leader in digital home and rich media applications and was acquired by Motorola in 2007. Earlier in his career, he worked at Cisco Systems as

Ring artifacts in computed tomography (CT) images, arising from the undesirable responses of detector units, significantly degrade image quality and diagnostic reliability. To address this challenge, we propose a dual-domain regularization model to effectively remove ring artifacts, while maintaining the integrity of the original CT image. The proposed model corrects the vertical stripe artifacts on the sinogram by innovatively updating the response inconsistency compensation coefficients of detector units, which is achieved by employing the group sparse constraint and the projection-view direction sparse constraint on the stripe artifacts. Simultaneously, we apply the sparse constraint on the reconstructed image to further rectified ring artifacts in the image domain. The key advantage of the proposed method lies in considering the relationship between the response inconsistency compensation coefficients of the detector units and the projection views, which enables a more accurate correction of the response of the detector units. An alternating minimization method is designed to solve the model. Comparative experiments on real photon counting detector (PCD) data demonstrate that the proposed method not only surpasses existing methods in removing ring artifacts but also excels in preserving structural details and image fidelity.