Application Issues for Multiobjective Evolutionary Algorithms

In the talk, various issues of the design and application of multiobjective evolutionary algorithms for real-life optimization problems are discussed. In particular, questions on problem-specific data structures and evolutionary operators and the determination of method parameters are treated. Three application examples in the areas of constrained global optimization (electronic circuit design), semi-infinite programming (design centering problems), and discrete optimization (project scheduling) are discussed

Screening for periodontal disease in research dogs:a methodology study

BACKGROUND: It has been shown that the prevalence of both clinical attachment loss (CAL) ≥1 mm and pocket probing depth (PPD) ≥4 mm is relatively high even in younger dogs, but also that only a minority of the dogs have such clinical signs of periodontal disease (PD) in more than a few teeth. Hence, a minority of dogs carry the major PD burden. These epidemiological features suggest that screening for PD in larger groups of dogs, allowing for rapid assessment of treatment planning, or for the selection of dogs with or without PD prior to be included in experimental trials, should be possible. CAL is the central variable in assessing PD extent and severity while PPD is the central variable used in treatment planning which make these two variables obvious in a screening protocol with the dual aim of disease identification and treatment planning. The main purpose of the present study in 98 laboratory Beagle dogs was to construct a fast, simple and accurate screening tool, which is highly sensitive for the identification of dogs with PD. RESULTS: Examination of the maxillary P4, P3, P2, I1 and C would, in this population, result in the identification of 85.5% of all dogs and 96% of all teeth positive for CAL ≥1 mm, and 58.9% of all dogs and 82.1% of all teeth positive for PD ≥4 mm. Examination of tooth pairs, all C’s, maxillary I2, M2 and the mandibular P4 would, in this population result in identification of 92.9% of all dogs and 97.3% of all teeth positive for PD ≥4 mm, and 65.5% of all dogs and 83.2% of all teeth positive for CAL ≥1 mm. The results presented here only pertain to the present study population. CONCLUSIONS: This screening protocol is suitable for examination of larger groups of laboratory Beagle dogs for PD and our findings indicate that diseased dogs are identified with a high degree of sensitivity. Before this screening can be used in clinical practice, it has to be validated in breeds other than Beagle dogs and in populations with larger age variation

Emerging Networks : A study on learning networks during the Covid-19 lockdown

This paper discusses findings from an investigation of students’ experiences from and participation in different learning networks during the Covid19-lockdown. The investigation is based on empirical data in the form of 32 interviews with students from a variety of University College Programmes (business-, administration-, construction-, technology-, health-, pedagogy- and teacher education). The interviews were collected as part of a larger study, where data also consisted of responses to surveys from, potentially, 84000 students. In the interviews, the students shared their experiences regarding learning and teaching online, respectively. Three cases were singled out aiming to maintain a high degree of complexity and maximum variation. Through the contemporary theories within the field of Networked Learning, we aim to show examples of how the students were networked during the Covid-19 shutdown and the implications that emerging networks had on their participation in online educational activities. Furthermore, we wish to make a suggestion for the use of the applied categorisation of networks for analyzing how students are networked. These categories, presented in this paper, are proposed by researchers within the field. The main findings suggest that online teaching during the lockdown required students to establish new patterns of participation, thus, establishing new structures and ways to collaborate. This led to emerging networks supporting different aspects of their life setting as students and creating opportunities for engaging in new social configurations and learning

Improving Collision Avoidance Behavior of a Target-Searching Algorithm for Kilobots

Collision avoidance in the area of swarm robotics is very important. The lacking ability of such collision avoidance is mentioned as one important reason for the sparse distribution of the small test robots named Kilobots. In this research paper, two new algorithms providing a collision avoidance strategy are presented and compared with previous research results. The first algorithm uses randomness to decide which one of several approaching Kilobots are stopped for a defined time before starting to move again. The second algorithm tries   to determine the assumed position of approaching Kilobots based on its radio signal strength and then to move away in the opposite direction by rotation. The results, especially of the second algorithm, are promising as the number of collisions can be significantly reduced

Resource use in a low-input organic vegetable food supply system in UK - a case study

Use of local renewable resources in a low-input organic vegetable food supply system in UK is evaluated against the use of imported resources in the same system. Despite much focus by the farmer on low-input, the production and distribution system is only supported by 13% local renewable resources based on an emergy assessment. Future sustainability of such systems are discussed