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This special session, within the conference theme of Incorporating Convergence into Programs, Curricula, and Continuing Education, focuses on Curriculum Agility in engineering education. It will introduce the concept of Curriculum Agility and its current trends, as well as further co-develop the concept behind it. This is done following an iterative design thinking approach, by co-creating guiding principles that engineering institutions can use to make their study programs more responsive, dynamic, and flexible. Curriculum Agility is particularly important in engineering education in order to keep pace with the rapid development of new technologies and materials. In addition, the concept aims to meet students' expectations and needs for more individualized study plans, as well as society's need for forward-thinking engineers equipped to contribute to finding solutions to current and future societal challenges. Thus, to anticipate and meet these challenges, institutions for engineering education need to have an organizational and management structure with the capacity to act within a much shorter timeframe than traditionally seen in universities. Curriculum Agility is a framework for introducing necessary changes in operations to be able to act responsibly and rapidly on change and expectations. This work presents seven principles for Curriculum Agility that have emerged from a series of sessions at international conferences and network meetings. The seven principles currently include: Stakeholder Involvement, Organization and Governance, Decision Making, Program and Course Design, Innovation of Education, and Pedagogy and Didactics. This special session brings educators together to discuss the 'what, how and why' with regard to Curriculum Agility. The overall aim is to further develop a shared vision on Curriculum Agility and build upon the intention of assessing it at different levels in the organization of engineering education institutions. The expected outcome

This article discusses the tension between quality assurance and quality enhancement in engineering education at a programme level. It acknowledges that accreditation has evolved for many years, but does not agilely support innovation or implement changes in educational programmes. Existing quality assurance systems, institutional collaboration networks, as well as new innovative quality enhancement models and processes are described, contrasted and synthesised. Quality enhancement is analysed based on its function as a source of inspiration and dissemination of good practice. The article reflects on a novel and more collaborative approach to quality enhancement, built on the foundations of specific pedagogical standards and rubrics (e.g. CDIO). One solution leading to real continuous quality enhancement could be flexible and agile evaluation processes. These are founded on measurement and rating frameworks and complemented with quality assurance for engineering education. Incremental enhancement is based on relevant needs identified collaboratively between programmes.

In Europe, there is a wide variety of curriculum designs in higher engineering education. Several international networks serve the goal of supporting the inherent need of higher education institutions to continuously improve their programmes, without per se offering a formal accreditation standard. In this paper, two such networks are considered: CDIO and SEFI. The curricular landscape across Europe and across the different engineering disciplines is mapped by means of a survey amongst the members of CDIO and SEFI. The results amongst 82 respondents show that the prevailing curriculum structure defined by focus, set-up and design is a fixed curriculum with flexible elements, focused on theory with skills woven in, and with a subject-centred curriculum, followed by another big group having a flexible curriculum with fixed elements, competency-based, and focusing on skills with theory woven in. Configurations vary based on region, engineering discipline and network membership. Curricular changes in the past three years and coming two years focus mostly on assessment and examination, as well as pedagogics, interpersonal skills and curriculum flexibility. Certain engineering disciplines are more prone to curriculum change than others, such as Design Engineering and Information Engineering. Electric engineering currently shows significantly less curriculum change. When changing the curriculum design, learning goals, learning activities and learning vision are typically seen as a priority in engineering education. The most perceived barriers in the curriculum change process are staff competency and engagement for those about to make changes, and development time and costs for those having made recent changes.

På denna workshop kommer vi att jobba med en process för att förbättra ingenjörsutbildning. Kärnan i denna process är en modell för Cross-Sparring där olika utbildningar agerar kritiska vänner. Grunden för Cross-Sparring utgörs av en självvärdering där utbildningsprogrammet identifierar vilka kvalitetskriterier man vill ha hjälp utifrån för att förbättra. En del av processen består i att dokumentera Best Practice som man kan dela med sig av på en Market Place och genom att koppla Best Practice till kvalitetskriterier gör dem effektivt sökbara.Utifrån detta underlag kan man sedan hitta lämpliga partners för Cross-Sparring.

In ensuring the quality of learning and teaching in Higher Education, self-evaluation is an important component of the process. An example would be the approach taken within the CDIO community whereby self-evaluation against the CDIO standards is part of the quality assurance process. Eight European universities (Reykjavik University, Iceland; Turku University of Applied Sciences, Finland; Aarhus University, Denmark; Helsinki Metropolia University of Applied Sciences, Finland; Umeå University, Sweden; Telecom Bretagne, France; Aston University, United Kingdom; Queens University Belfast, United Kingdom) are engaged in an EU funded Erasmus + project that is exploring the quality assurance process associated with active learning.

We demonstrate a technique to improve structural data obtained from Optical Projection Tomography (OPT) using Image Fusion (IF) and contrast normalization. This enables the visualization of molecular expression patterns in biological specimens with highly variable contrast values. In the approach, termed IF-OPT, different exposures are fused by assigning weighted contrasts to each. When applied to projection images from mouse organs and digital phantoms our results demonstrate the capability of IF-OPT to reveal high and low signal intensity details in challenging specimens. We further provide measurements to highlight the benefits of the new algorithm in comparison to other similar methods.

By adapting OPT to include the capability of imaging in the near infrared (NIR) spectrum, we here illustrate the possibility to image larger bodies of pancreatic tissue, such as the rat pancreas, and to increase the number of channels (cell types) that may be studied in a single specimen. We further describe the implementation of a number of computational tools that provide: 1/ accurate positioning of a specimen's (in our case the pancreas) centre of mass (COM) at the axis of rotation (AR)2; 2/ improved algorithms for post-alignment tuning which prevents geometric distortions during the tomographic reconstruction2 and 3/ a protocol for intensity equalization to increase signal to noise ratios in OPT-based BCM determinations3. In addition, we describe a sample holder that minimizes the risk for unintentional movements of the specimen during image acquisition. Together, these protocols enable assessments of BCM distribution and other features, to be performed throughout the volume of intact pancreata or other organs (e.g. in studies of islet transplantation), with a resolution down to the level of individual islets of Langerhans.

Since it was first presented in 2002, optical projection tomography (OPT) has emerged as a powerful tool for the study of biomedical specimen on the mm to cm scale. In this paper, we present computational tools to further improve OPT image acquisition and tomographic reconstruction. More specifically, these methods provide: semi-automatic and precise positioning of a sample at the axis of rotation and a fast and robust algorithm for determination of postalignment values throughout the specimen as compared to existing methods. These tools are easily integrated for use with current commercial OPT scanners and should also be possible to implement in "home made" or experimental setups for OPT imaging. They generally contribute to increase acquisition speed and quality of OPT data and thereby significantly simplify and improve a number of three-dimensional and quantitative OPT based assessments.

This paper describes a classification based tree detection method for autonomous navigation of forest vehicles in forest environment. Fusion of color, and texture cues has been used to segment the image into tree trunk and background objects. The segmentation of images into tree trunk and background objects is a challenging task due to high variations of illumination, effect of different color shades, non-homogeneous bark texture, shadows and foreshortening. To accomplish this, the approach has been to find the best combinations of color, and texture descriptors, and classification techniques. An additional task has been to estimate the distance between forest vehicle and the base of segmented trees using monocular vision. A simple heuristic distance measurement method is proposed that is based on pixel height and a reference width. The performance of various color and texture operators, and accuracy of classifiers has been evaluated using cross validation techniques.