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Axis, HMS and Sectra are three Swedish companies whose managers argue that you should never be radical on two fronts: creating new products for new markets at the same time. This paper aims to show however that while Axis’ managers claim not to be radical on two fronts, they still perform horizontal diversification, but they do so by disguising it as product development. Just like certain animals disguise themselves for protection, Axis’ managers disguise diversification as a defense mechanism, to protect themselves. In so doing, they have learned to manage the dynamics of innovation, by shifting between periods of focus and diversification.

This study was based on an inductive research approach influenced by grounded theory. In total, 32 interviews were performed with top and middle-line managers from three Swedish companies: Axis, Sectra and HMS. A total of 91 A4 transcript pages, 66 A4 e-mail pages, 52 annual reports (from 1999 to 2017) and 256 company presentations and newspaper articles (from 1988 to 2015) were collected and analyzed. Open and selective coding yielded 105 sub-categories, which were grouped into four main categories and presented as detailed descriptions. The results were based on the interpretation of those descriptions and related to disguise as a defense mechanism in psychology.

Innovation is a difficult process often met with hostility. Axis’ managers however have found a way to go beyond their existing business domain, while still protecting themselves from internal and external opposing forces that would go against such a risky strategy. To do so, they first expand their existing business domain. Then they perform horizontal diversification and disguise it as product development, as a defense mechanism to protect their desire to create innovation from managers who would oppose their risky strategy. In so doing, they convince other stakeholders that innovation through diversification is the best strategy for their company.

This study was only performed at three Swedish technological companies. For future research, other Swedish companies could be included, and not only technological companies either, to explore whether diversification is considered a strategy that needs to be disguised in other businesses as well, and how managers from those businesses deal with internal and external forces.

Managers from Axis, Sectra and HMS are fully aware that innovation as well as diversification is difficult. Ideas that seem interesting and full of potential for some people may seem too risky and dangerous for others. To protect diversification as a strategy for innovation, Axis’ managers have found a way to disguise diversification, and make it seem less dangerous. In so doing, they are able to diversify and create innovation. A strategy for disguising diversification therefore has practical managerial implications of how managers can deal with internal and external forces that would go against such a strategy.

This study connects defense mechanisms in psychology with innovations strategy and innovation management and solves a practical dilemma that managers often struggle with: how to create innovation despite barriers that exists and oppose such a strategy. Managers will most likely always face different barriers to innovation, and perhaps solving them is not possible. This study shows how Axis’ managers have found a way to go around this problem, when solving it is not possible. This strategy thus shows originality and value for both theory and practice related to innovations strategy and innovation management.

The COVID-19 pandemic stressed the health care sector's longstanding pain points, including the poor quality of frontline work and the staffing challenges that result from it. This has renewed interest in technology-centered approaches to achieving not only the “Triple Aim” of reducing costs while raising access and quality but also the “Quadruple Aim” of doing so without further squeezing wages and abrading job quality for frontline workers.

How can we leverage technology toward the achievement of the Quadruple Aim? I view this as a “grand challenge” for health care managers and policymakers. Those looking for guidance will find that most analyses of the workforce impact of technological change consider broad classes of technology such as computers or robots outside of any particular industry context. Further, they typically predict changes in work or labor market outcomes will come about at some ill-defined point in the medium to long run. This decontextualization and detemporization proves markedly problematic in the health care sector: the nonmarket, institutional factors driving technology adoption and implementation loom especially large in frontline care delivery, and managers and policymakers understandably must consider a well-defined, near-term, i.e., 5–10-year, time horizon.

This study is predicated on interviews with hospital and home health agency administrators, union representatives, health care information technology (IT) experts and consultants, and technology developers. I detail the near-term drivers and anticipated workforce impact of technological changes in frontline care delivery. With my emergent prescriptions for managers and policymakers, I hope to guide sectoral actors in using technology to address the “grand challenge” inherent to achieving the Quadruple Aim.

Reviews some of the improvements in image sensor technology that are yielding applications in the medical field.

Discusses the characteristics and gives examples of cameras and imaging sensors used in endoscopy, microscopy, pharmaceutical label inspection and X‐radiography. Reviews some innovative camera‐based products for endoscopy, skin imaging and health monitoring.

Improvements in camera resolution, miniaturisation and interfacing are widening the applications in medical imaging and enabling the development of some exciting new products addressing the needs of patients and medical staff.

Identifies some suppliers of medical imaging devices and their applications.

Hundreds of thousands of deaths each year in the world are caused by breast cancer (BC). An early-stage diagnosis of this disease can positively reduce the morbidity and mortality rate by helping to select the most appropriate treatment options, especially by using histological BC images for the diagnosis.

The present study proposes and evaluates a novel approach which consists of 24 deep hybrid heterogenous ensembles that combine the strength of seven deep learning techniques (DenseNet 201, Inception V3, VGG16, VGG19, Inception-ResNet-V3, MobileNet V2 and ResNet 50) for feature extraction and four well-known classifiers (multi-layer perceptron, support vector machines, K-nearest neighbors and decision tree) by means of hard and weighted voting combination methods for histological classification of BC medical image. Furthermore, the best deep hybrid heterogenous ensembles were compared to the deep stacked ensembles to determine the best strategy to design the deep ensemble methods. The empirical evaluations used four classification performance criteria (accuracy, sensitivity, precision and F1-score), fivefold cross-validation, Scott–Knott (SK) statistical test and Borda count voting method. All empirical evaluations were assessed using four performance measures, including accuracy, precision, recall and F1-score, and were over the histological BreakHis public dataset with four magnification factors (40×, 100×, 200× and 400×). SK statistical test and Borda count were also used to cluster the designed techniques and rank the techniques belonging to the best SK cluster, respectively.

Results showed that the deep hybrid heterogenous ensembles outperformed both their singles and the deep stacked ensembles and reached the accuracy values of 96.3, 95.6, 96.3 and 94 per cent across the four magnification factors 40×, 100×, 200× and 400×, respectively.

The proposed deep hybrid heterogenous ensembles can be applied for the BC diagnosis to assist pathologists in reducing the missed diagnoses and proposing adequate treatments for the patients.

This chapter summarises the role of EU actions in supporting healthcare policies in the EU Member States, both looking at implemented actions and describing current priorities for the future. It argues that these coordinated actions can be beneficial for EU Member States by helping them to avoid duplication of effort and to attain economies of scale. Moreover, data sharing with proper safeguards can unleash vast amount of ‘learning what works’ both for medical treatments and for healthcare sustainability measures. The need for this common learning appears ever more urgent while facing the health and economic consequences of the present pandemic.

This paper aims to present a novel DSpace-based medical image repository system planned explicitly for storing and retrieving clinical images using digital imaging and communication in medicine (DICOM) metadata standards. DSpace institutional repository software is widely used in an academic environment for accessing and mainly storing text-related files. DICOM images are particular types of images embedded with much system-generated metadata and organised using DICOM metadata standards.

The present paper talks about institutional repository software (DSpace) in archiving DICOM images. In the current study, the authors have tried to integrate the DICOM metadata standard with DSpace, which was compatible with Dublin Core (DC) and open archives initiative – protocol for metadata harvesting (OAI-PMH). After combining the DICOM standard with DSpace and the repository tested with a sample of 5,000 images, the retrieval results using various DICOM tags was very satisfactory. This study paves for the use of open source software (OSS) in storing and retrieving medical images.

The author has provided the DSpace software to recognised DICOM (.dcm) files in the first stage. In the second stage, a patch was developed to identify the DICOM metadata standard in Dspace, which has inbuilt DC metadata standards. Finally, in the third stage, retrieval efficiency was tested with a 5,000 .dcm image using the DICOM tag and the results were very fruitful.

A major limitation of this study was the size of the data (5,000 DICOM images) with which the authors have tested the system. The system scalability has to be tested on various fronts like on cloud and local servers with different configurations, for which a separate study has to be done.

Once this system is in place, DICOM users can stock, retrieve and access the image from the Web platform. Furthermore, this proposed repository will be the warehouse of various DICOM images with reasonable storage costs.

In addition to exploring the opportunities of free open source software (FOSS) implementation in medical science, this study includes issues related to the performance of an open-source repository for retrieving and preserving medical images. It created and developed Open Source DICOM Medical Image Library with DICOM metadata standard with the help of DSpace. Thus, the study will generate value for library professionals and medical professionals and FOSS vendors to understand the medical market in the context of FOSS.

This paper aims to provide an optimization method of workflow for publishing houses and electronic book (e-book) studies in the field of digital publishing.

Based on the studies of publishing houses in Beijing, the present conversion workflow is illustrated using a functional modeling methodology. Then, the workflow is analyzed using 5W1H (why, who, what, where, when, how) methodology and optimized using ECRSI (eliminate, combine, rearrange, simplify and increase) principles. To validate the optimization effect, the workflow before and after optimization are generated and implemented by the ExtendSim® simulation software.

The simulation results show that under similar circumstances, both quantity and quality of the products are improved after optimization, which indicate that the optimization method is effective.

Electronic PUBlication (EPUB) has significant requirements to satisfy the needs of the mobile reading market and to earn increased profits, whereas some e-books are still preserved in a portable document format (PDF). This study results in the enhanced EPUB quality and production efficiency of the PDF-to-EPUB format conversion workflow in publishing houses. Publishing houses around the world can refer to this study to make a similar optimization when handling PDF-to-EPUB.

This research introduces the traditional industrial engineering analytical techniques to the workflow optimization of e-book conversion. Compared with the most of other methods used to optimize workflow, this method is simpler, more efficient and more suitable for e-book format conversion.

In recent years, a large number of data repositories have been built and used. However, the extent to which scientific data are re-used in academic publications is still unknown. The purpose of this paper is to explore the functions of re-used scientific data in scholarly publication in different fields.

To address these questions, the authors identified 827 publications citing resources in the Dryad Digital Repository indexed by Scopus from 2010 to 2015.

The results show that: the number of citations to scientific data increases sharply over the years, but mainly from data-intensive disciplines, such as agricultural, biology science, environment science and medicine; the majority of citations are from the originating articles; and researchers tend to reuse data produced by their own research groups.

Dryad data may be re-used without being formally cited.

The conservatism in data sharing suggests that more should be done to encourage researchers to re-use other’s data.