Reducing Radiation Dose to the Female Breast during CT Coronary Angiography: A Simulation Study Comparing Breast Shielding, Angular Tube Current Modulation, Reduced kV, and Partial Angle Protocols Using an Unknown-location Signal-detectability Metric

Purpose: The authors compared the performance of five protocols intended to reduce dose to the breast during computed tomography (CT) coronary angiography scans using a model observer unknown-location signal-detectability metric. Methods: The authors simulated CT images of an anthropomorphic female thorax phantom for a 120 kV reference protocol and five “dose reduction” protocols intended to reduce dose to the breast: 120 kV partial angle (posteriorly centered), 120 kV tube-current modulated (TCM), 120 kV with shielded breasts, 80 kV, and 80 kV partial angle (posteriorly centered). Two image quality tasks were investigated: the detection and localization of 4-mm, 3.25 mg/ml and 1-mm, 6.0 mg/ml iodine contrast signals randomly located in the heart region. For each protocol, the authors plotted the signal detectability, as quantified by the area under the exponentially transformed free response characteristic curve estimator (AˆFE), as well as noise and contrast-to-noise ratio (CNR) versus breast and lung dose. In addition, the authors quantified each protocol\u27s dose performance as the percent difference in dose relative to the reference protocol achieved while maintaining equivalentAˆFE. Results: For the 4-mm signal-size task, the 80 kV full scan and 80 kV partial angle protocols decreased dose to the breast (80.5% and 85.3%, respectively) and lung (80.5% and 76.7%, respectively) withAˆFE= 0.96, but also resulted in an approximate three-fold increase in image noise. The 120 kV partial protocol reduced dose to the breast (17.6%) at the expense of increased lung dose (25.3%). The TCM algorithm decreased dose to the breast (6.0%) and lung (10.4%). Breast shielding increased breast dose (67.8%) and lung dose (103.4%). The 80 kV and 80 kV partial protocols demonstrated greater dose reductions for the 4-mm task than for the 1-mm task, and the shielded protocol showed a larger increase in dose for the 4-mm task than for the 1-mm task. In general, the CNR curves indicate a similar relative ranking of protocol performance as the correspondingAˆFEcurves, however, the CNR metric overestimated the performance of the shielded protocol for both tasks, leading to corresponding underestimates in the relative dose increases compared to those obtained when using theAˆFEmetric. Conclusions: The 80 kV and 80 kV partial angle protocols demonstrated the greatest reduction to breast and lung dose, however, the subsequent increase in image noise may be deemed clinically unacceptable. Tube output for these protocols can be adjusted to achieve a more desirable noise level with lesser breast dose savings. Breast shielding increased breast and lung dose when maintaining equivalentAˆFE. The results demonstrated that comparisons of dose performance depend on both the image quality metric and the specific task, and that CNR may not be a reliable metric of signal detectability

Three Essays on Firm Innovation Strategy: Innovation of Internet of Things and Green Technologies

The last few decades have seen an accelerating pace of fundamental transformations in the business environment driven by digital technologies and the emergence of the green agenda. These are known as the digital and green transitions, largely pushed by technological advancements and innovation. Given the profound impact of such two transitions on the business operations and environment, it is crucial for both researchers and policy makers to improve their understanding of what these big trends mean for businesses and how market players should strategise for responding to these technological transformations to maximise the benefits and mitigate the risks. We attempt to tackle these big problems by probing into the fundamental technological trends underlying these two transitions. This thesis is developed to investigate how companies react to the ongoing economic and societal challenges during the digital and green transitions by searching for answers to three related research questions. In particular, we intend to understand how businesses develop their technological competence or capacity for creating ground-breaking innovation within Industry 4.0 as well as environmental innovation under the current global endeavour to achieve SDGs. We also propose to analyse how the wave of green technology influences economic performance of businesses in the wider economy through the diffusion of green innovation. The work is composed of three empirical chapters, mainly drawing upon patent information from the Bureau van Dijk’s Orbis Intellectual Property (Orbis IP) database, Environmental, Social and Governance (ESG) practices from the Thomson Reuters ASSET4 database, and firm-level information from the Orbis database

Data anonymization patent landscape

The omnipresent, unstoppable increase in digital data has led to a greater understanding of the importance of data privacy. Different approaches are used to implement data privacy. The goal of this paper is to develop a data anonymization patent landscape, by determining the following: (i) the trend in data anonymization patenting, (ii) the type of technical content protected in data anonymization, (iii) the organizations and countries most active in patenting data anonymization know-how; and (iv) the topics emerging most often in patent titles. Patents from the PatSeer database relating to data anonymization from 2001 to 2015 were analyzed. We used the longitudinal approach in combination with text mining techniques to develop a data anonymization patent landscape. The results indicated the following. The number of single patent families is growing with a high increase after 2010, thus indicating a positive trend in the area of patenting data anonymization solutions. The majority of patenting activities relate to the G Physics section. Organizations from the USA and Japan assigned the majority of patents related to data anonymization. The results of text mining indicate that the most often used word in titles of data anonymization patents are “anonym*, “method”, “data” and “system”. Several additional words that indicated the most frequent topics related to data anonymization were: “equipment”, “software”, “protection”, “identification”, or “encryption”, and specific topics such as “community”, “medical”, or “service”

Apps de salut

En l'actual moment de pandèmia, les apps es consoliden com un recurs crucial dels sistemes de salut, però també plantegen dilemes.. Les Apps de Salut són programes informàtics per a plataformes mòbils, sovint connectats a dispositius mèdics, que gestionen informació que contribueix a l'eficiència en la prevenció, el diagnòstic, el tractament i el seguiment dels usuaris del sistema de salut. La connectivitat que promouen entre gestors, metges i pacients, així com l'actualitat de les dades que maneguen, permet optimitzar -i inclús personalitzar- l'atenció als malalts. Malgrat els seus avantatges, aquestes aplicacions plantegen considerables dilemes relacionats amb la propietat i la seguretat de les dades. En el transfons d'aquesta temàtica prevalen aspectes tècnics (estàndards tecnològics), normatius (certificacions) i socioculturals (compromís dels usuaris, empreses i administracions)

Technology Roadmapping Using Text Mining: A Foresight Study for the Retail Industry

Technology roadmapping is a widely accepted method for offering industry foresight as it supports strategic innovation management and identifies the potential application of emerging technologies. While roadmapping applications have been implemented across different technologies and industries, prior studies have not addressed the potential application of emerging technologies in the retail industry. Furthermore, few studies have examined service-oriented technologies by a roadmapping method. Methodologically, there are limited roadmapping studies that implement both quantitative and qualitative approaches. Hence, this article aims to offer a foresight for future technologies in the retailing industry using an integrated roadmapping method. To achieve this, we used a sequential method that consisted of both text mining and an expert review process. Our results show clear directions for the future of emerging technologies as the industry moves toward unmanned retail operations. We generate eight clusters of technologies and integrate them into a roadmapping model, illustrating their links to the market and business requirements. Our study has a number of implications and identifies potential bottlenecks between the integration of front- and back-end solutions for the future of unmanned retailing

Novel Processing and Transmission Techniques Leveraging Edge Computing for Smart Health Systems

L'abstract è presente nell'allegato / the abstract is in the attachmen

Using the new methods in forecasting of technology diffusion

Forecasting the development of new technologies and technology diffusion contains uncertainties. Making an investment decision includes risks and timing the decision without information is usually based on former experiences or mere opinions. This study examines the uncertainty in technical forecasting, and seeks to find solutions to improve forecasting accuracy in order to time investment decisions better. The purpose of this thesis is to investigate the issues to consider when predicting technologies and the requirements for measuring technology diffusion, and to find suitable methods for predicting the development of technology diffusion. As research methods, a literature research and a quantitative study based on various sources were conducted on predicting the development of technology diffusion. In the literature research, appropriate sources, prediction models and theory were compiled to predict the development of emerging technologies. A suitable calculation method and calculation model were selected for prediction. The results from the literature research were applied in a quantitative study. In quantitative terms, the developmental trend of technology diffusion was implemented in predicting a phenomenon that was subject of the study. As a result of this study, a suitable forecasting method for the development of the technology diffusion of emerging technologies was developed. The method integrates several different prediction sources with the Bass diffusion model. The calculation model integrates the parameters of the behavior of data of different prediction sources into the key calculation parameters of the Bass calculation model. This method is suitable for evaluating the development of emerging technologies. The integrated Bass computation model can be used to evaluate technology development or decline, and to evaluate timely business decisions before major technology diffusion.Uusien teknologioiden ja teknologidiffuusion kehityksen ennustaminen varhaisessa vaiheessa sisältää epävarmuustekijöitä. Investointipäätös sisältää riskin ja päätöksen ajoitus ilman tietoa perustuu usein kokemuksiin tai mielipiteisiin. Työssä tutkittiin teknologiaennustamisen epävarmuutta ja pyrittiin löytämään ratkaisuja ennustamistarkkuuden parantamiseen sekä parempaan investointipäätökseen ja -ajoitukseen. Tämän diplomityön tarkoituksena oli selvittää huomioitavia asioita teknologioiden ennustamisessa ja vaatimuksia teknologiadiffuusion mitattaville asioille sekä löytää teknologiadiffuusion kehittymisen ennustamiseen sopivia menetelmiä. Tutkimusmenetelmänä oli kirjallisuustutkimus sekä kvantitatiivinen tutkimus eri aineistoihin perustuvasta teknologiadiffuusion kehittymisen ennustamisesta. Kirjallisuustutkimuksessa koottiin orastavien teknologioiden kehittymisen ennustamiseksi sopivia lähteitä, ennustusmalleja sekä teoriaa. Kirjallisuustutkimuksen perusteella valittiin ennustettavalle kohteelle sopivat lähteet, laskentamenetelmä ja -malli. Kirjallisuustutkimuksen tuloksia sovellettiin kvantitatiivisessa tutkimuksessa. Kvantitatiivisessa osuudessa toteutettiin teknologiadiffuusion kehittymisennuste tutkimuksen kohteena olevaan ilmiöön. Tutkimustuloksena kehitettiin orastavien teknologioiden teknologiadiffuusion kehittymiseen sopiva ennustemenetelmä. Menetelmässä integroidaan useita eri ennustuslähteitä sekä hyödynnetään Bassin diffuusiolaskentamallia. Laskentamallissa integroidaan eri ennustuslähteiden datan käyttäytymistä kuvaavat parametrit Bassin laskentamallin keskeisiin laskentaparametreihin. Menetelmä sopii orastavien teknologioiden kehittymisen arviointiin. Integroidulla Bassin laskentamallilla voidaan arvioida teknologian kehittymistä tai taantumista sekä arvioida oikea-aikaisia liiketoimintapäätöksiä ennen merkittävää teknologiadiffuusiota