A Unified Framework for Specifying Cost Models of IT Service Offerings

2018 ◽  
pp. 151-160
Author(s):  
Kugmoorthy Gajananan ◽  
Aly Megahed ◽  
Shubhi Asthana ◽  
Taiga Nakamura
Keyword(s):  
Cost Models ◽  
Unified Framework ◽  
It Service

The Development of Not-For-Profit Hospital Cost Models

1988 ◽  
Vol 6 (1) ◽  
pp. 35-48
Author(s):  
Greg M. Thibadoux ◽  
Nicholas Apostolou ◽  
Ira S. Greenberg
Keyword(s):  
Hospital Cost ◽  
Cost Models ◽  
For Profit ◽  
Not For Profit

Medizintechnik: Das Geschäft mit den Daten beginnt

2016 ◽  
Vol 21 (09) ◽  
pp. 36-38
Author(s):  
Romy König
Keyword(s):  
It Service

Siemens hat einen neuen IT-Service für die Bildgebung entwickelt: In einer Cloud können Radiologen Untersuchungsdaten sammeln, auswerten und mit Referenzwerten abgleichen. Es ist der Einstieg in ein Geschäftsfeld mit großem Wachstumspotenzial.

Immigration and the tech industry: As a labour shortage remedy, for innovation, or for cost savings?

2013 ◽  
Vol 10 (2) ◽  
pp. 201-227 ◽  
Author(s):  
Norman Matloff
Keyword(s):  
Immigration Policy ◽  
Brain Drain ◽  
Cost Savings ◽  
Foreign Workers ◽  
Service Firms ◽  
It Service ◽  
Labour Shortage ◽  
Labour Costs ◽  
Using Data ◽  
The U.S

The two main reasons cited by the U.S. tech industry for hiring foreign workers--remedying labour shortages and hiring "the best and the brightest"--are investigated, using data on wages, patents, and R&D work, as well as previous research and industry statements. The analysis shows that the claims of shortage and outstanding talent are not supported by the data, even after excluding the Indian IT service firms. Instead, it is shown that the primary goals of employers in hiring  foreign workers are to reduce labour costs and to obtain "indentured" employees. Current immigration policy is causing an ‘Internal Brain Drain’ in STEM.

A unified framework for automated person re-indentification

2020 ◽  
Vol 71 (7) ◽  
pp. 868-880
Author(s):  
Nguyen Hong-Quan ◽  
Nguyen Thuy-Binh ◽  
Tran Duc-Long ◽  
Le Thi-Lan
Keyword(s):  
Deep Learning ◽  
Video Analysis ◽  
Camera Network ◽  
Unified Framework ◽  
Person Detection ◽  
Practical Applications ◽  
Detection And Tracking ◽  
Analysis System ◽  
Bounding Boxes

Along with the strong development of camera networks, a video analysis system has been become more and more popular and has been applied in various practical applications. In this paper, we focus on person re-identification (person ReID) task that is a crucial step of video analysis systems. The purpose of person ReID is to associate multiple images of a given person when moving in a non-overlapping camera network. Many efforts have been made to person ReID. However, most of studies on person ReID only deal with well-alignment bounding boxes which are detected manually and considered as the perfect inputs for person ReID. In fact, when building a fully automated person ReID system the quality of the two previous steps that are person detection and tracking may have a strong effect on the person ReID performance. The contribution of this paper are two-folds. First, a unified framework for person ReID based on deep learning models is proposed. In this framework, the coupling of a deep neural network for person detection and a deep-learning-based tracking method is used. Besides, features extracted from an improved ResNet architecture are proposed for person representation to achieve a higher ReID accuracy. Second, our self-built dataset is introduced and employed for evaluation of all three steps in the fully automated person ReID framework.

Technology Support and Post-Adoption IT Service Use: Evidence from the Cloud

MIS Quarterly ◽  
2018 ◽  
Vol 42 (3) ◽  
pp. 961-978 ◽  
Author(s):  
German F. Retana ◽  
◽  
Chris Forman ◽  
Sridhar Narasimhan ◽  
Marius Florin Niculescu ◽  
...  
Keyword(s):  
Service Use ◽  
Technology Support ◽  
It Service

A Unified Model for Photophysical and Electro-Optical Properties of Green Fluorescent Proteins

2019 ◽  
Author(s):  
Chi-Yun Lin ◽  
Matthew Romei ◽  
Luke Oltrogge ◽  
Irimpan Mathews ◽  
Steven Boxer
Keyword(s):  
Driving Force ◽  
Fluorescent Protein ◽  
Charge Transfer Band ◽  
Photophysical Properties ◽  
Polymethine Dyes ◽  
Emission Rates ◽  
Unified Framework ◽  
Underlying Factor ◽  
Green Fluorescent ◽  
Protein Environment

Green fluorescent protein (GFPs) have become indispensable imaging and optogenetic tools. Their absorption and emission properties can be optimized for specific applications. Currently, no unified framework exists to comprehensively describe these photophysical properties, namely the absorption maxima, emission maxima, Stokes shifts, vibronic progressions, extinction coefficients, Stark tuning rates, and spontaneous emission rates, especially one that includes the effects of the protein environment. In this work, we study the correlations among these properties from systematically tuned GFP environmental mutants and chromophore variants. Correlation plots reveal monotonic trends, suggesting all these properties are governed by one underlying factor dependent on the chromophore's environment. By treating the anionic GFP chromophore as a mixed-valence compound existing as a superposition of two resonance forms, we argue that this underlying factor is defined as the difference in energy between the two forms, or the driving force, which is tuned by the environment. We then introduce a Marcus-Hush model with the bond length alternation vibrational mode, treating the GFP absorption band as an intervalence charge transfer band. This model explains all the observed strong correlations among photophysical properties; related subtopics are extensively discussed in Supporting Information. Finally, we demonstrate the model's predictive power by utilizing the additivity of the driving force. The model described here elucidates the role of the protein environment in modulating photophysical properties of the chromophore, providing insights and limitations for designing new GFPs with desired phenotypes. We argue this model should also be generally applicable to both biological and non-biological polymethine dyes.<br>

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