A Comprehensive Framework for Combined Decision Procedures

2005 ◽  
pp. 1-30 ◽  
Author(s):  
Silvio Ghilardi ◽  
Enrica Nicolini ◽  
Daniele Zucchelli
Keyword(s):  
Decision Procedures ◽  
Comprehensive Framework

Communicating the Value of Design

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
George Edward TORRENS ◽  
Nicholas Samuel JOHNSON ◽  
Ian STORER
Keyword(s):  
Design Decision ◽  
Card Sorting ◽  
Practical Application ◽  
Product Packaging ◽  
Sorting Method ◽  
Packaging Design ◽  
Design Considerations ◽  
Modified Delphi ◽  
Fast Moving Consumer Goods ◽  
Comprehensive Framework

Product packaging design is often produced through the practical application of tacit knowledge, rule of thumb and professional connoisseurship. Stakeholders are becoming increasingly demanding that design practitioners provide clarity of reasoning and accountability for their design proposals. Therefore, a better framework for the design of fast-moving consumer goods (FMCG) is required. This paper proposes a comprehensive taxonomy of ‘design considerations’ to assist the development of low involvement FMCG packaging and aid in rationale communication for design solutions. 302 academic sources were reviewed, inductive content analysis performed to code topics and output validation with academic and industry experts (n=9) through a modified-Delphi card sorting method. The research provides movement towards a comprehensive framework and common dialogue between stakeholders, practitioners and managers to assist in more effectively communicating the value that design can offer to FMCGs. The constructed taxonomy provides a set of 156 ‘design considerations’ to support in objective and informed design decision-making.

Creating autonomous learners in the teaching of English as a second language (ESL) in Zimbabwean secondary schools : a reality or a myth?

2020 ◽  
Vol 1 (3) ◽  
pp. 103-132
Author(s):  
Rungamirai Matiure ◽  
Erick Nyoni
Keyword(s):  
Decision Making ◽  
Second Language ◽  
Multiple Case Study ◽  
Document Analysis ◽  
Learner Autonomy ◽  
Case Study Design ◽  
Midlands Province ◽  
Multiple Case ◽  
Comprehensive Framework

This study explored the utility of the learner autonomy concept in the Zimbabwean O Level English as a Second Language (ESL) classroom focusing on three Gweru urban high schools of the Midlands Province. The researchers intended to establish whether learner autonomy was a reality or just a myth in Zimbabwean classrooms. A qualitative multiple case study design was applied focusing on teaching strategies, availability of resources, challenges faced and ways of optimising it. Questionnaires and document analysis were used for data collection. The findings revealed that the concept did not manifest in explicit terms, the learners did not participate in decision making, and the teachers were not adequately prepared to administer autonomous processes with students. For it to be a reality, the Education Ministry is recommended to establish a comprehensive framework of how autonomous learning should be implemented. Teacher training should explicitly focus on how to develop autonomous learners. Teachers ought to be flexible enough to accommodate learners' contributions towards their learning.

A Comprehensive Framework for Quantitative Stress Tests in Financial Institutions

2013 ◽  
Author(s):  
Yasushi Takano ◽  
Jiro Hashiba ◽  
Rintaro Anraku ◽  
Ryuichi Sato ◽  
Sakae Mizuki ◽  
...  
Keyword(s):  
Financial Institutions ◽  
Stress Tests ◽  
Comprehensive Framework ◽  
Quantitative Stress

Cultural Accommodation of Internet-Based Interventions for Substance Use and Related Disorders: A Proposed Comprehensive Framework (Preprint)

2019 ◽  
Author(s):  
Keren Gueta ◽  
Yossi Harel-Fisch ◽  
Sophie D. Walsh
Keyword(s):  
Substance Use ◽  
Ecological Validity ◽  
Limited Attention ◽  
Diverse Range ◽  
Four Dimensions ◽  
Service Engagement ◽  
Wide Range ◽  
Cultural Accommodation ◽  
Abuse Treatment ◽  
Comprehensive Framework

BACKGROUND Despite the low utilization rates of substance use and related disorders services, and the ability of internet-based interventions for substance use and related disorders (IBIS) to address challenges related to service engagement, limited attention has been placed on the processes for the accommodation of these interventions to diverse cultural settings. OBJECTIVE The purpose of this study was to develop a conceptual framework for the cultural accommodation of IBIS across populations, settings, and countries. METHODS A pilot study of cultural accommodation of an existing internet intervention for alcohol use (Down Your Drink (DYD)), focus groups and daily online surveys of prospective consumers (N=24) and interviews with experts (N=7) in the substance abuse treatment field were conducted. RESULTS Thematic analysis revealed a wide range of themes identified as needing to be addressed in the process of DYD accommodation. It also emphasized that accommodation needs to incorporate both technical and contents themes, shaped by both the general Israeli cultural as well as by the specific Israeli drinking subculture. A combined mixed emic–etic theoretical approach incorporating the pilot findings together with a scoping literature review was employed to develop a framework for cultural accommodation of IBIS. A comprehensive framework for cultural accommodation of IBIS is introduced consisting of five chronological stages of IBIS accommodation and four dimensions of accommodation. CONCLUSIONS The proposed framework can serve as a guide for the cultural accommodation of existing IBIS across a diverse range of cultural and geographical settings thus augmenting the ecological validity of IBIS and reducing health disparities worldwide.

Digging for the truth: the case for active annotation in evaluating the credibility of online medical information (Preprint)

2020 ◽  
Author(s):  
Mikołaj Morzy ◽  
Bartłomiej Balcerzak ◽  
Adam Wierzbicki ◽  
Adam Wierzbicki
Keyword(s):  
Machine Learning ◽  
Medical Information ◽  
Representation Learning ◽  
Training Dataset ◽  
Highly Qualified ◽  
Human In The Loop ◽  
Annotation Process ◽  
Comprehensive Framework ◽  
Online Sources ◽  
The Web

BACKGROUND With the rapidly accelerating spread of dissemination of false medical information on the Web, the task of establishing the credibility of online sources of medical information becomes a pressing necessity. The sheer number of websites offering questionable medical information presented as reliable and actionable suggestions with possibly harmful effects poses an additional requirement for potential solutions, as they have to scale to the size of the problem. Machine learning is one such solution which, when properly deployed, can be an effective tool in fighting medical disinformation on the Web. OBJECTIVE We present a comprehensive framework for designing and curating of machine learning training datasets for online medical information credibility assessment. We show how the annotation process should be constructed and what pitfalls should be avoided. Our main objective is to provide researchers from medical and computer science communities with guidelines on how to construct datasets for machine learning models for various areas of medical information wars. METHODS The key component of our approach is the active annotation process. We begin by outlining the annotation protocol for the curation of high-quality training dataset, which then can be augmented and rapidly extended by employing the human-in-the-loop paradigm to machine learning training. To circumvent the cold start problem of insufficient gold standard annotations, we propose a pre-processing pipeline consisting of representation learning, clustering, and re-ranking of sentences for the acceleration of the training process and the optimization of human resources involved in the annotation. RESULTS We collect over 10 000 annotations of sentences related to selected subjects (psychiatry, cholesterol, autism, antibiotics, vaccines, steroids, birth methods, food allergy testing) for less than $7 000 employing 9 highly qualified annotators (certified medical professionals) and we release this dataset to the general public. We develop an active annotation framework for more efficient annotation of non-credible medical statements. The results of the qualitative analysis support our claims of the efficacy of the presented method. CONCLUSIONS A set of very diverse incentives is driving the widespread dissemination of medical disinformation on the Web. An effective strategy of countering this spread is to use machine learning for automatically establishing the credibility of online medical information. This, however, requires a thoughtful design of the training pipeline. In this paper we present a comprehensive framework of active annotation. In addition, we publish a large curated dataset of medical statements labelled as credible, non-credible, or neutral.

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