Critical analysis of vendor lock-in and its impact on cloud computing migration: a business perspective

Vendor lock-in is a major barrier to the adoption of cloud computing, due to the lack of standardization. Current solutions and efforts tackling the vendor lock-in problem are predominantly technology-oriented. Limited studies exist to analyse and highlight the complexity of vendor lock-in problem in the cloud environment. Consequently, most customers are unaware of proprietary standards which inhibit interoperability and portability of applications when taking services from vendors. This paper provides a critical analysis of the vendor lock-in problem, from a business perspective. A survey based on qualitative and quantitative approaches conducted in this study has identified the main risk factors that give rise to lock-in situations. The analysis of our survey of 114 participants shows that, as computing resources migrate from on-premise to the cloud, the vendor lock-in problem is exacerbated. Furthermore, the findings exemplify the importance of interoperability, portability and standards in cloud computing. A number of strategies are proposed on how to avoid and mitigate lock-in risks when migrating to cloud computing. The strategies relate to contracts, selection of vendors that support standardised formats and protocols regarding standard data structures and APIs, developing awareness of commonalities and dependencies among cloud-based solutions. We strongly believe that the implementation of these strategies has a great potential to reduce the risks of vendor lock-in

An exploration of the determinants for decision to migrate existing resources to cloud computing using an integrated TOE-DOI model

Migrating existing resources to cloud computing is a strategic organisational decision that can be difficult. It requires the consideration and evaluation of a wide range of technical and organisational aspects. Although a significant amount of attention has been paid by many industrialists and academics to aid migration decisions, the procedure remains difficult. This is mainly due to underestimation of the range of factors and characteristics affecting the decision for cloud migration. Further research is needed to investigate the level of effect these factors have on migration decisions and the overall complexity. This paper aims to explore the level of complexity of the decision to migrate the cloud. A research model based on the diffusion of innovation (DOI) theory and the technology-organization-environment (TOE) framework was developed. The model was tested using exploratory and confirmatory factor analysis. The quantitative analysis shows the level of impact of the identified variables on the decision to migrate. Seven determinants that contribute to the complexity of the decisions are identified. They need to be taken into account to ensure successful migration. This result has expanded the collective knowledge about the complexity of the issues that have to be considered when making decisions to migrate to the cloud. It contributes to the literature that addresses the complex and multidimensional nature of migrating to the cloud

Wireless technology in the evolution of patient monitoring on general hospital wards

The evolution of patient monitoring on general hospital wards is discussed. Patients on general wards are monitored according to the severity of their conditions, which can be subjective at best. A report by the Commission for Healthcare Audit and Inspection in 2008 indicated dissatisfaction with patient monitoring. Commitment to providing quality health service by healthcare organizations encourages the implementation of other mechanisms for patient care. Remote patient monitoring (RPM), by supplementing the role of nurses, can improve efficiency and patient care on general wards. Developments in technology made it possible for wireless sensors to measure and transmit physiological data from patients to a control room for monitoring and recording. Two approaches in the application of wireless ZigBee sensor networks are discussed and their performances compared in a simulation environment. The role of RPM in early detection of deteriorating patients' conditions, reducing morbidity and mortality rates are also discussed

Smartphone-Based Digital Biomarkers for Parkinson’s Disease in a Remotely-Administered Setting

Smartphone-based digital biomarker (DB) assessments provide objective measures of daily-life tasks and thus hold the promise to improve diagnosis and monitoring of Parkinson’s disease (PD). To date, little is known about which tasks perform best for these purposes and how different confounds including comorbidities, age and sex affect their accuracy. Here we systematically assess the ability of common self-administered smartphone-based tasks to differentiate PD patients and healthy controls (HC) with and without accounting for the above confounds. Using a large cohort of PD patients and healthy volunteers acquired in the mPower study, we extracted about 700 features commonly reported in previous PD studies for gait, balance, voice and tapping tasks. We perform a series of experiments systematically assessing the effects of age, sex and comorbidities on the accuracy of the above tasks for differentiation of PD patients and HC using several machine learning algorithms. When accounting for age, sex and comorbidities, the highest balanced accuracy on hold-out data (73%) was achieved using random forest when combining all tasks followed by tapping using relevance vector machine (67%). Only moderate accuracies were achieved for other tasks (60% for balance, 56% for gait and 53% for voice data). Not accounting for the confounders consistently yielded higher accuracies of up to 77% when combining all tasks. Our results demonstrate the importance of controlling DB data for age and comorbidities

Stimulus-responsive liposomes as smart nanoplatforms for drug delivery applications

Liposomes are known to be promising nanoparticles (NPs) for drug delivery applications. Among the different types of self-assembled NPs, liposomes stand out for their non-toxic nature and their possession of dual hydrophilic-hydrophobic domains. The advantages of liposomes include the ability to solubilize hydrophobic drugs, the ability to incorporate different hydrophilic and lipophilic drugs at the same time, lessening the exposure of host organs to potentially toxic drugs and allowing modification of the surface by a variety of different chemical groups. This modification of the surface, or of the individual constituents, may be used to achieve two important goals. First, ligands for active targeting can be attached that are recognized by cognate receptors overexpressed on the target cells of tissues. Second, modification can be used to impart a stimulus-responsive or “smart” character to the liposomes, whereby the cargo is released on demand only when certain internal stimuli (pH, reducing agents, specific enzymes) or external stimuli [light, magnetic field, or ultrasound (US)] are present. Here, we review the field of smart liposomes for drug delivery applications

Noble metal nanostructures in optical biosensors: Basics, and their introduction to anti-doping detection

Nanotechnology has illustrated significant potentials in biomolecular-sensing applications; particularly its introduction to anti-doping detection is of great importance. Illicit recreational drugs, substances that can be potentially abused, and drugs with dosage limitations according to the prohibited lists announced by the World Antidoping Agency (WADA) are becoming of increasing interest to forensic chemists. In this review, the theoretical principles of optical biosensors based on noble metal nanoparticles, and the transduction mechanism of commonly-applied plasmonic biosensors are covered. We review different classes of recently-developed plasmonic biosensors for analytic determination and quantification of illicit drugs in anti-doping applications. The important classes of illicit drugs include anabolic steroids, opioids, stimulants, and peptide hormones. The main emphasis is on the advantages that noble metal nanoparticles bring to optical biosensors for signal enhancement and the development of highly sensitive (label-free) biosensors. In the near future, such optical biosensors may be an invaluable substitute for conventional anti-doping detection methods such as chromatography-based approaches, and may even be commercialized for routine anti-doping tests. © 2017 Elsevier B.V