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Recent advances in sensor design, embedded systems, and communication networks allow us to collect valuable biomedical data effectively. The new biomedical data acquisition systems make significant contributions to life quality as well as support healthcare and diagnostic procedures. This book presents several innovative applications of data acquisition technology for monitoring patient activity, assisted living, diagnosing osteoarthritis, recognizing disorders of the cardiovascular system, and designing prostheses for amputees.

Automatic data collection systems.

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Data acquisition systems have numerous applications. This book has a total of 13 chapters and is divided into three sections: Industrial applications, Medical applications and Scientific experiments. The chapters are written by experts from around the world, while the targeted audience for this book includes professionals who are designers or researchers in the field of data acquisition systems. Faculty members and graduate students could also benefit from the book.

Automatic data collection systems. --- Data collection systems, Automatic --- Factory data acquisition systems, Automatic --- Factory monitoring systems, Automatic --- In-plant data collection systems, Automatic --- Automation --- Communication in management --- Data transmission systems --- Cybernetics & systems theory

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In radiation oncology as in many other specialties clinical trials are essential to investigate new therapy approaches. Usually, preparation for a prospective clinical trial is extremely time consuming until ethics approval is obtained. To test a new treatment usually many years pass before it can be implemented in the routine care. During that time, already new interventions emerge, new drugs appear on the market, technical & physical innovations are being implemented, novel biology driven concepts are translated into clinical approaches while we are still investigating the ones from years ago. Another problem is associated with molecular diagnostics and the growing amount of tumor specific biomarkers which allows for a better stratification of patient subgroups. On the other side, this may result in a much longer time for patient recruiting and consequently in larger multicenter trials. Moreover, all of the relevant data must be readily available for treatment decision making, treatment as well as follow-up, and ultimately for trial evaluation. This challenges even more for agreed standards in data acquisition, quality and management. How could we change the way currently clinical trials are performed in a way they are safe and ethically justifiable and speed up the initiation process, so we can provide new and better treatments faster for our patients? Further, while we rely on various quantitative information handling distributed, large heterogeneous amounts of data efficiently is very important. Thus data management becomes a strong focus. A good infrastructure helps to plan, tailor and conduct clinical trials in a way they are easy and quickly analyzable. In this research topic we want to discuss new ideas for intelligent trial designs and concepts for data management.

Cancer --- Oncology, Experimental. --- Radiotherapy --- Data processing. --- Study Management --- Clinical trials --- Data Collection --- Radiation Oncology --- Clinical Study design

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In response to a request from the Central Statistical Bureau (CSB) of Kuwait, a government finance statistics (GFS) technical assistance (TA) mission visited Kuwait City, Kuwait during April 29–May 3, 2018. This first GFS TA mission from the IMF’s Statistics Department (STA) aimed to assist the CSB staff in compiling fiscal data according to the Government Finance Statistics Manual 2014 (GFSM 2014) and help them to issue this year’s GFS bulletin according to the GFSM 2014 classification. In addition, the mission discussed with the Ministry of Finance (MoF) the possibility of resuming the reporting of the GFS data to the Fund for surveillance and dissemination in Government Finance Statistics Yearbook (GFSY).

Statistics --- Data Collection and Data Estimation Methodology --- Computer Programs: Other --- Econometrics & economic statistics --- Government finance statistics --- Economic and financial statistics --- Finance --- Kuwait

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This paper suggests a way forward in the effort to measure statistical capacity building by combining features of two tools – the Project Management System, a logical framework methodology that the IMF Statistics Department uses to plan, monitor, and evaluate technical assistance projects, and the Data Quality Assessment Framework, a methodology for assessing data quality that brings together best practices and internationally accepted concepts and definitions in statistics.

Macroeconomics --- Statistics --- Data Transmission Systems --- Databases --- Other Special Topics: General --- Data Collection and Data Estimation Methodology --- Computer Programs: General --- Methodology for Collecting, Estimating, and Organizing Macroeconomic Data --- Data Access --- General Aggregative Models: General --- Data capture & analysis --- Data Quality Assessment Framework (DQAF) --- Data dissemination --- Data collection --- Special Data Dissemination Standard (SDDS) --- National accounts --- Economic statistics --- Data transmission systems --- National income