• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.843-871
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• 2015

Cloud computing evolve as a cost effective business model for IT companies to focus on their core business without perturbing on infrastructure related issues. Hence, major IT firms and Small & Medium Enterprises (SME) are adopting cloud services on rental basis from cloud providers. Cloud Service level agreements (SLA) act as a key liaison between consumers and providers on renting Anything as a Service (AaaS). Design of such an agreement must aim for greater profit to providers as well as assured availability of services to consumers. However in reality, cloud SLA is not satisfying the parties involved because of its inherent complex nature and issues. Also currently most of the agreements are unilateral to favour the provider. This study focuses on comprehensive, 360-degree survey on different aspects of the cloud service agreements. We detailed the life cycle of SLA based on negotiation, different types of SLA, current standards, languages & characteristics, metrics and issues involved in it. This study will help the cloud actors to understand and evaluate the agreements and to make firm decision on negotiation. The need for standardized, bilateral, semantic SLA has also been proposed.

• Korean Journal of Veterinary Service
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• v.42 no.2
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• pp.73-83
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• 2019

Foot-and-Mouth Disease (FMD) is a highly contagious trans-boundary viral disease caused by FMD virus, which causes huge economic losses. FMDV infects cloven hoofed (two-toed) mammals such as cattle, sheep, goats, pigs and various wildlife species. To control the FMDV, it is necessary to understand the life cycle and the pathogenesis of FMDV in host. Especially, the protein-protein interaction between FMDV and host will help to understand the survival cycle of viruses in host cell and establish new therapeutic strategies. However, the computational approach for protein-protein interaction between FMDV and pig hosts have not been applied to studies of the onset mechanism of FMDV. In the present work, we have performed the prediction of the pig's proteins which interact with FMDV based on RNA-Seq data, protein sequence, and structure information. After identifying the virus-host interaction, we looked for meaningful pathways and anticipated changes in the host caused by infection with FMDV. A total of 78 proteins of pig were predicted as interacting with FMDV. The 156 interactions include 94 interactions predicted by sequence-based method and the 62 interactions predicted by structure-based method using domain information. The protein interaction network contained integrin as well as STYK1, VTCN1, IDO1, CDH3, SLA-DQB1, FER, and FGFR2 which were related to the up-regulation of inflammation and the down-regulation of cell adhesion and host defense systems such as macrophage and leukocytes. These results provide clues to the knowledge and mechanism of how FMDV affects the host cell.