A Collaborative Evaluation Examining Tattoos in the Funeral Profession

A collaborative evaluation project has been carried out by fourteen UK and European organisations, both industrial and public sector, to compare information resources and searching techniques for chemical toxrcology information. The project had two objectives: to improve the participants' own expertise in this area, and to allow an objective evaluation of searching methods. Eight test queries were designed and searched by the participants, and the results evaluated semi-qualitatively, with an extensive failure analysis. Printed sources, online data-bases, data-banks, and in-house files were included in the evaluation. The results are presented and discussed, including both comments on strengths and weaknesses of sources and search techniques, and recommenda tions for future improvements to facilitate access to chemical toxicology information.

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Collaborative evaluation and management of students’ health-related physical fitness: applications of cluster analysis and the classification tree

International Journal of Adolescent Medicine and Health ◽

10.1515/ijamh.2012.023 ◽

2012 ◽

Vol 24 (2) ◽

Cited By ~ 2

Author(s):

Jou-An Chen ◽

Chi-Chuan Shih ◽

Pay-Fan Lin ◽

Jin-Jong Chen ◽

Kuan-Chia Lin

Keyword(s):

Cluster Analysis ◽

Physical Fitness ◽

Classification Tree ◽

Metabolic Risk ◽

Tree Model ◽

School Year ◽

Classification Tree Model ◽

Health Related ◽

Risk Approach ◽

Collaborative Evaluation

Abstract Health-related physical fitness has decreased with age; this is od immense concern to adolescents. School-based health intervention programs can be classified as either population-wide or high-risk approach. Although the population-wide and risk-based approaches adopt different healthcare angles, they all need to focus resources on risk evaluation. In this paper, we describe an exploratory application of cluster analysis and the tree model to collaborative evaluation of students’ health- related physical fitness from a high school sample in Taiwan (n=742). Cluster analysis show that physical fitness can be divided into relatively good, moderate and poor subgroups. There are significant differences in biochemical measurements among these three groups. For the tree model, we used 2004 school-year students as an experimental group and 2005 school-year students as a validation group. The results indicate that if sit-and-reach is shorter than 33 cm, BMI is >25.46 kg/m2, and 1600 m run/walk is >534 s, the predicted probability for the number of metabolic risk factors ≥2 is 100% and the population is 41, both results are the highest. From the risk-based healthcare viewpoint, the cluster analysis can sort out students’ physical fitness data in a short time and then narrow down the scope to recognize the subgroups. A classification tree model specifically shows the discrimination paths between the measurements of physical fitness for metabolic risk and would be helpful for self-management or proper healthcare education targeting different groups. Applying both methods to specific adolescents’ health issues could provide different angles in planning health promotion projects.

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Whose futures need crafting? A collaborative evaluation of the British Council/Crafts Council Crafting Futures 5K grant scheme

Art Design & Communication in Higher Education ◽

10.1386/adch_00032_1 ◽

2021 ◽

Vol 20 (1) ◽

pp. 103-114 ◽

Cited By ~ 1

Author(s):

Rachel Kelly ◽

Sandra Fruebing

Keyword(s):

Education Research ◽

Radio Signal ◽

The Philippines ◽

Project Work ◽

Higher Education Research ◽

Research And Practice ◽

British Council ◽

Grant Scheme ◽

Collaborative Evaluation

Sandra Fruebing and Rachel Kelly were recipients of 2018–19 British Council/Crafts Council Crafting Futures 5k grants. A dialogue between Fruebing and Kelly started when they both returned from their project work in Egypt and the Philippines respectively. Both participants related their experiences through their conversations and this led them to discuss and reflect through regular online exchanges stretching from 2019 to 2020. They both are now considering how their experiences of working with marginalized craft communities have become a position from which to consider the role of development in Art & Design Higher Education research and practice. The spectrum of collaboration and companionship that is emerging from their work, both individually and through online meetings and conversations, become like a radio signal, which is tuning and making audible their similar experiences and understandings.

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Retroperitoneal sarcoma perioperative risk stratification: A United States Sarcoma Collaborative evaluation of the ACS‐NSQIP risk calculator

Journal of Surgical Oncology ◽

10.1002/jso.26071 ◽

2020 ◽

Vol 122 (4) ◽

pp. 795-802

Author(s):

Patrick B. Schwartz ◽

Christopher C. Stahl ◽

Cecilia Ethun ◽

Nicholas Marka ◽

George A. Poultsides ◽

...

Keyword(s):

United States ◽

Risk Stratification ◽

Perioperative Risk ◽

Retroperitoneal Sarcoma ◽

Risk Calculator ◽

Acs Nsqip ◽

Collaborative Evaluation

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Combinations of Methods for Collaborative Evaluation of the Usability of Interactive Software Systems

Advances in Human-Computer Interaction ◽

10.1155/2016/4089520 ◽

2016 ◽

Vol 2016 ◽

pp. 1-16 ◽

Cited By ~ 6

Author(s):

Andrés Solano ◽

César A. Collazos ◽

Cristian Rusu ◽

Habib M. Fardoun

Keyword(s):

Relevant Information ◽

Evaluation Methods ◽

Usability Evaluation ◽

Quality Characteristic ◽

Interactive System ◽

Software Systems ◽

Interactive Software ◽

Combination Of Methods ◽

Collaborative Evaluation ◽

Usability Evaluation Methods

Usability is a fundamental quality characteristic for the success of an interactive system. It is a concept that includes a set of metrics and methods in order to obtain easy-to-learn and easy-to-use systems. Usability Evaluation Methods, UEM, are quite diverse; their application depends on variables such as costs, time availability, and human resources. A large number of UEM can be employed to assess interactive software systems, but questions arise when deciding which method and/or combination of methods gives more (relevant) information. We proposeCollaborative Usability Evaluation Methods, CUEM, following the principles defined by the Collaboration Engineering. This paper analyzes a set of CUEM conducted on different interactive software systems. It proposes combinations of CUEM that provide more complete and comprehensive information about the usability of interactive software systems than those evaluation methods conducted independently.

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