A multi-layer cellular automata approach for algorithmic generation of virtual case studies: VIBe

2010 ◽  
Vol 61 (1) ◽  
pp. 37-45 ◽  
Author(s):  
R. Sitzenfrei ◽  
S. Fach ◽  
H. Kinzel ◽  
W. Rauch
Keyword(s):  
Boundary Conditions ◽  
Case Studies ◽  
Real World ◽  
New Technologies ◽  
Single Case ◽  
Software Tool ◽  
Simulation Software ◽  
Data Availability ◽  
Study Results

Analyses of case studies are used to evaluate new or existing technologies, measures or strategies with regard to their impact on the overall process. However, data availability is limited and hence, new technologies, measures or strategies can only be tested on a limited number of case studies. Owing to the specific boundary conditions and system properties of each single case study, results can hardly be generalized or transferred to other boundary conditions. virtual infrastructure benchmarking (VIBe) is a software tool which algorithmically generates virtual case studies (VCSs) for urban water systems. System descriptions needed for evaluation are extracted from VIBe whose parameters are based on real world case studies and literature. As a result VIBe writes Input files for water simulation software as EPANET and EPA SWMM. With such input files numerous simulations can be performed and the results can be benchmarked and analysed stochastically at a city scale. In this work the approach of VIBe is applied with parameters according to a section of the Inn valley and therewith 1,000 VCSs are generated and evaluated. A comparison of the VCSs with data of real world case studies shows that the real world case studies fit within the parameter ranges of the VCSs. Consequently, VIBe tackles the problem of limited availability of case study data.

Dynamic virtual infrastructure benchmarking: DynaVIBe

2010 ◽  
Vol 10 (4) ◽  
pp. 600-609 ◽  
Author(s):  
R. Sitzenfrei ◽  
S. Fach ◽  
M. Kleidorfer ◽  
C. Urich ◽  
W. Rauch
Keyword(s):  
Case Studies ◽  
Distribution Systems ◽  
Water Distribution ◽  
New Technologies ◽  
Study Data ◽  
Data Availability ◽  
Urban Structure ◽  
Real World Data ◽  
Virtual Infrastructure

In environmental engineering, identification of problems and their solutions as well as the identification of the relevant processes involved is often done by means of case study analyses. By researching the operation of urban drainage and water distribution systems, this methodology is suited to evaluate new technologies, strategies or measures with regard to their impact on the overall processes. However, data availability is often limited and data collection and the development of new models are both costly and time consuming. Hence, new technologies, strategies or measures can only be tested on a limited number of case studies. In several environmental disciplines a few virtual case studies have been manually developed to provide data for research tasks and these are repeatedly used in different research projects. Efforts have also been invested in tackling limited data availability with the algorithmic generation of virtual case studies having constant or varying boundary conditions. The data provided by such tools is nevertheless only available for a certain instance in time. With DynaVIBe (Dynamic Virtual Infrastructure Benchmarking), numerous virtual case studies are algorithmically generated with a temporal development of the urban structure (population and land use model) and infrastructure. This provides a methodology that allows for the analysis of future scenarios on a spatio-temporal city scale. By linking a population model with DynaVIBe's infrastructure models, socio-economics impacts on infrastructure and system coherences can be investigated. The problematic of limited case study data is solved by the algorithmic generation of an unlimited number of virtual case studies, which are dynamic over time. Additionally, this methodology can also be applied on real world data for probabilistic future scenario analysis.

scholarly journals Can We Generalize from Case Studies?

2015 ◽  
Vol 15 (3) ◽  
pp. 152-175 ◽  
Author(s):  
Paul F. Steinberg
Keyword(s):  
Case Studies ◽  
Single Case ◽  
Case Study Research ◽  
Political Systems ◽  
Ceteris Paribus ◽  
Large N ◽  
Climate Change Politics ◽  
The Comparative Study

This article considers the role of generalization in comparative case studies, using as exemplars the contributions to this special issue on climate change politics. As a research practice, generalization is a logical argument for extending one’s claims beyond the data, positing a connection between events that were studied and those that were not. No methodological tradition is exempt from the requirement to demonstrate a compelling logic of generalization. The article presents a taxonomy of the logics of generalization underlying diverse research methodologies, which often go unstated and unexamined. I introduce the concept of resonance groups, which provide a causeway for cross-system generalization from single case studies. Overall the results suggest that in the comparative study of complex political systems, case study research is, ceteris paribus, on par with large-N research with respect to generalizability.

scholarly journals Valuing new medicines in the early 21:st century

2017 ◽  
Vol 5 (1) ◽  
pp. 7-22
Author(s):  
Katarina Steen Carlsson ◽  
Bengt Jönsson
Keyword(s):  
Health Care ◽  
Clinical Practice ◽  
Real World ◽  
Patent Protection ◽  
New Technologies ◽  
New Technology ◽  
Treatment Strategies ◽  
Real World Data ◽  
Study Results ◽  
Pricing And Reimbursement

What is the actual value of new medicines? The answer to this question is the key to rational use of new technologies in health care and for design of appropriate incentives for innovation. In this paper we present methods, data and study results for valuing new medical technologies in a life cycle perspective, relevant for development of a new approach to contract and payment for innovation that can replace present systems for pricing and reimbursement.   Focus is on value in clinical practice, and on the data needs and methods needed for the development of outcome-based payment systems that balances risks and rewards for innovation in health care. We provide an overview of studies from the Swedish context on the value of new medicines introduced in the treatment of diabetes, cancer, cardiovascular disease and rheumatoid arthritis. These studies using national health data and quality registers emphasise the importance of continuing efforts to collect relevant data for assessment of value after a medicine reaches the market and starts to be used in clinical practice. It is only when medicines are used in clinical practice that the benefits for real-world patient populations can be identified, measured and valued. Analyses of real-world data will also assist further development and tailoring of treatment strategies to optimize the value of the new technology. While an effective patent system rewards innovation for a limited period of time, many innovations may continue to provide value to society long after patent protection, and these values must be included in the assessment of value of innovation.

Case Studies Using Program Evaluation to Drive Evidence-Based Practices

2018 ◽  
pp. 109-131
Author(s):  
Julie Q. Morrison ◽  
Anna L. Harms
Keyword(s):  
Early Literacy ◽  
Case Studies ◽  
Behavioral Interventions ◽  
Single Case ◽  
Pilot Project ◽  
Evidence Based Practices ◽  
First Case ◽  
Single Case Designs ◽  
The Cost

This chapter consists of three case studies that illustrate how the evaluation approaches, methods, techniques, and tools presented in Chapters 1 to 5 can be translated into practice. The first case study describes an evaluation of the Dyslexia Pilot Project, a statewide multi-tier system of supports (MTSS) initiative targeting early literacy. In this evaluation, special attention was paid to the evaluating the cost-effectiveness of serving students in kindergarten to grade 2 proactively. The second case study features the use of single-case designs and corresponding summary statistics to evaluate the collective impact of more than 500 academic and behavioral interventions provided within an MTSS framework as part of the annual statewide evaluation of the Ohio Internship Program in School Psychology. The third case study focuses on efforts to evaluate the fidelity of implementation for teacher teams’ use of a five-step process for data-based decision making and instructional planning.

Adoption and implementation of new technologies in hospitals: a network perspective

IMP Journal ◽  
2018 ◽  
Vol 12 (2) ◽  
pp. 368-391
Author(s):  
Olga Mikhailova
Keyword(s):  
New Technologies ◽  
Single Case ◽  
Limited Resources ◽  
Content Type ◽  
Advanced Medical Technology ◽  
Adoption And Implementation ◽  
Challenges And Opportunities ◽  
Danish Hospital ◽  
Innovation Processes

Purpose The purpose of this paper is to address challenges and opportunities that smaller hospitals with limited resources may face when they are adopting and implementing innovative technologies. Design/methodology/approach Based on a single case study with interviews and document analysis, this paper focuses on the recombination of resources, actors and activities during the process of technology adoption and implementation at a Danish hospital. Theoretically, it takes an interaction perspective for exploring the interplay between inner and outer networking during the innovation processes. Findings This study illustrates how the adoption and implementation of advanced medical technology requires significant investment, which is particularly burdensome for smaller hospitals. Constrained by limited resources, they have to develop creative combinations of resources through negotiation and embrace collaborative approaches to join and sustain themselves in the user-producer network. Originality/value This paper contributes to the innovation field by suggesting ways in which practitioners at smaller hospitals can align with technology providers’ strategies and succeed by positioning their hospitals in relation to extended user-producer networks. This study further emphasizes the necessity of a broader discussion regarding the importance of user-producer interactions during innovation processes in health care settings.

Effects of delays in the adoption of cancer innovation: Case studies of six landmark medications.

2017 ◽  
Vol 35 (5_suppl) ◽  
pp. 27-27 ◽  
Author(s):  
Jason Shafrin ◽  
Jin Joo Shim ◽  
Seanna Vine ◽  
Caroline Huber ◽  
Beata Korytowsky ◽  
...  
Keyword(s):  
Overall Survival ◽  
Case Studies ◽  
Real World ◽  
Physician Education ◽  
Cancer Treatments ◽  
Patient Health ◽  
The Difference ◽  
New Treatment ◽  
Access Policies

27 Background: Although new oncology treatments have the potential to improve patient health, these innovations take time to reach to real-world patients. In this study, we estimated how delays in the uptake of novel oncology treatments affect real-world patient survival. Methods: This retrospective cohort study used 1991-2013 data from a cancer-registry linked to health care claims (SEER-Medicare). Our endpoint of interest was patient overall survival. We used variability in the adoption of new cancer treatments across aggregated Metropolitan Statistical Areas (MSAs) (n = 50) as a “natural experiment” that assigned treatments randomly across patients, depending entirely on where they live. This approach recovers the effect of the new treatment on the overall survival of the “marginal patient,” who received treatment solely because she resides in an area with faster uptake. This framework was applied to six case studies: trastuzumab (breast), bevacizumab (colorectal), bevacizumab (lung), erlotinib (lung), bortezomib (myeloma) and lenalidomide (myeloma). Results: Among the 92,496 patients in the study, the difference between adoption rates among eligible patients for MSAs at the 90th percentile and those at the 10th percentile was 20.1 percentage points, with the largest differences being for bevacizumab (colorectal) (51.2% at the 90th percentile MSA vs. 20.9% at the 10th percentile), and smallest for erlotinib (10.3% vs. 2.8%). Median OS among eligible patients gaining access to these landmark therapies increased by 9.6 months. Survival improvements were largest for the lenalidomide case study (33.4 months OS improvement, p < 0.005) followed by erlotinib (21.2 mo., p < 0.001), trastuzumab (19.2 mo., p = 0.016), bevacizumab for lung (7.4 mo., p = 0.002), bevacizumab for colorectal cancer (4.0 mo., p = 0.062), and bortezomib (2.9 mo., p = 0.630). Conclusions: Improving the speed at which landmark treatments are adopted in practice—through physician education and outreach or more generous health insurance access policies—has the potential to improve real-world survival for cancer patients.

Case Study Research

2014 ◽  
pp. 454-470
Author(s):  
Helen Simons
Keyword(s):  
Case Studies ◽  
Policy Making ◽  
Single Case ◽  
Case Study Research ◽  
Ways Of Knowing ◽  
Ethical Practice ◽  
Multiple Perspectives ◽  
Study Research ◽  
Political Interests

This chapter explores case study as a major approach to research and evaluation. After first noting various contexts in which case studies are commonly used, the chapter focuses on case study research directly Strengths and potential problematic issues are outlined and then key phases of the process. The chapter emphasizes how important it is to design the case, to collect and interpret data in ways that highlight the qualitative, to have an ethical practice that values multiple perspectives and political interests, and to report creatively to facilitate use in policy making and practice. Finally, it explores how to generalize from the single case. Concluding questions center on the need to think more imaginatively about design and the range of methods and forms of reporting requiredto persuade audiences to value qualitative ways of knowing in case study research.

Automation of CMOS technology migration illustrated by RGB to YCrCb analogue converter

2013 ◽  
Vol 21 (3) ◽  
Author(s):  
M. Naumowicz ◽  
M. Melosik ◽  
P. Katarzynski ◽  
A. Handkiewicz
Keyword(s):  
Computer Software ◽  
Image Data ◽  
Software Tool ◽  
Current Mode ◽  
Cmos Technology ◽  
Simulation Software ◽  
Vision Sensor ◽  
Colour Space ◽  
Technology Migration

AbstractThe paper illustrates a practical example of technology migration applied to the colour space converter realized in CMOS technology. The element has analogue excitation and response signals expressed in current mode. Such converter may be incorporated into an integrated vision sensor for preconditioning acquired image data. The idea of a computer software tool supporting the automated migration and design reuse is presented as the major contribution. The mentioned tools implement the Hooke-Jeeves direct search method for performing the multivariable optimization. Our purpose is to ensure transferring the circuit between usable fabrication technologies and preserving its functional properties. The colour space converter is treated as the case study for performance evaluation of the proposed tool in cooperation with HSPICE simulation software. The original CMOS technology files for Taiwan semiconductor (TSMC) plant were utilized for the research. The automated design migration from 180 nm into 90 nm resulted with obtaining compact IC layout characterized by a smaller area and lower power consumption. The paper is concluded with a brief summary that proves the usability of the proposed tool in designing CMOS cells dedicated for low power image processing.

MARKET ORIENTATION, TECHNOLOGY ORIENTATION AND PRODUCT INNOVATION SUCCESS: INSIGHTS FROM CoPS

2014 ◽  
Vol 18 (04) ◽  
pp. 1450020 ◽  
Author(s):  
JING LIU ◽  
JINGQIN SU
Keyword(s):  
Market Orientation ◽  
Product Innovation ◽  
Empirical Test ◽  
Single Case ◽  
High Tech ◽  
Fuzzy Front End ◽  
Front End ◽  
Study Results ◽  
Technology Orientation

This study explores how market orientation and technology orientation within fuzzy front end phases affect product innovation success in complex products and systems (CoPS) industry research and development (R&D) organisations. A sequential qualitative–quantitative mixed method was used with a single case study and a questionnaire survey. The case study results show mix effects of market orientation and technology orientation on CoPS innovation success within fuzzy front end phases. The empirical test results show that a market orientation facilitates both low-tech and high-tech CoPS innovation success and offer great benefits to mainstream customers. A technology orientation is beneficial to high-tech CoPS innovation success but has no impact on low-tech CoPS innovation success. The results have significant implications for CoPS firm strategies to facilitate product innovations and achieve competitive advantages.

Using process tracing to evaluate unique events: The case of EXPO Milano 2015

Evaluation ◽  
2017 ◽  
Vol 23 (3) ◽  
pp. 256-273 ◽  
Author(s):  
Simone Busetti ◽  
Bruno Dente
Keyword(s):  
Social Sciences ◽  
Case Studies ◽  
Causal Attributions ◽  
Relevant Literature ◽  
Process Tracing ◽  
Mega Events ◽  
Causal Contribution ◽  
The Social ◽  
Study Results

In the social sciences, there is an emerging interest in process tracing as a method for improving rigour and transparency in within-case inferences. Recently, the method has been proposed as a possible enhancement of theory-based approaches to evaluation, but applications of the method remain rare. In an attempt to fill this gap, process tracing was used to evaluate the Universal Exposition held in Milano in 2015 (EXPO2015). Mega-events of this kind are perfect candidates for ‘testing’ the method; although their effects have been widely discussed in the relevant literature, claims about the causal contribution of mega-events are not straightforward, and a number of ambiguities complicate any clear assessment of their consequences. Two in-depth case studies of projects related to EXPO2015 – the East External Highway and Refettorio Ambrosiano – demonstrate the advantages and feasibility of process tracing and of the application of Bayesian logic to evidence search, collection and assessment. In particular, case study results show that Bayesian scrutiny may reveal unexpected weakness in apparently obvious inferences and increase reliability in assessing less straightforward causal attributions.

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