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As AI technology is increasingly used in production systems, different approaches have emerged from highly decentralized small-scale AI at the edge level to centralized, cloud-based services used for higher-order optimizations. Each direction has disadvantages ranging from the lack of computational power at the edge level to the reliance on stable network connections with the centralized approach. Thus, a hybrid approach with centralized and decentralized components that possess specific abilities and interact is preferred. However, the distribution of AI capabilities leads to problems in self-adapting learning systems, as knowledgebases can diverge when no central coordination is present. Edge components will specialize in distinctive patterns (overlearn), which hampers their adaptability for different cases. Therefore, this paper aims to present a concept for a distributed interchangeable knowledge base in CPPS. The approach is based on various AI components and concepts for each participating node. A service-oriented infrastructure allows a decentralized, loosely coupled architecture of the CPPS. By exchanging knowledge bases between nodes, the overall system should become more adaptive, as each node can “forget” their present specialization.
Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available.
Honeybees, Apis mellifera, can differ considerably in their birth weights but the consequences of these weight differences for behaviour are unknown. I investigated how these birth weight differences affected their cognitive skills when the bees reached foraging age. Individual sucrose responsiveness measured by the proboscis extension response is a strong determinant of appetitive olfactory learning performance in honeybees. Most of the observed learning differences between individuals or between genetic bee strains correlate with differences in their sucrose responsiveness. My second aim was therefore to investigate whether the sucrose responsiveness of newly emerged bees could predict the learning behaviour of the bees 3 weeks later. Both birth weight and sucrose responsiveness measured at emergence could predict olfactory learning scores as demonstrated by significant positive correlations. Heavy bees and bees with high sucrose responsiveness later learned better than lighter individuals or bees with lower responsiveness to sucrose at emergence. These results demonstrate for the first time a fundamental relationship between sensory responsiveness and morphology at emergence and later cognitive skills in insects. Because sensory responsiveness is closely linked to division of labour in honeybees, differences in weight and sucrose responsiveness at emergence might be involved in regulating division of labour.
Purpose: The acquisition of skills is essential to the conceptualization of cognitive-behavioural therapy. Yet, what experiences are encountered and what skills actually learned during therapy, and whether patients and therapists have concurrent views hereof, remains poorly understood.
Method: An explorative pilot study with semi-structured, corresponding interview guides was conducted. Pilot data from our outpatient unit were transcribed and content-analyzed following current guidelines.
Results: The responses of 18 participants (patients and their psychotherapists) were assigned to six main categories. Educational and cognitive aspects were mentioned most frequently and consistently by both groups. Having learned Behavioural alternatives attained the second highest agreement between perspectives.
Conclusions: Patients and therapists valued CBT as an opportunity to learn new skills, which is an important prerequisite also for the maintenance of therapeutic change. We discuss limitations to generalizability but also theoretical and therapy implications.
Purpose: The acquisition of skills is essential to the conceptualization of cognitive-behavioural therapy. Yet, what experiences are encountered and what skills actually learned during therapy, and whether patients and therapists have concurrent views hereof, remains poorly understood. Method: An explorative pilot study with semi-structured, corresponding interview guides was conducted. Pilot data from our outpatient unit were transcribed and content-analyzed following current guidelines. Results: The responses of 18 participants (patients and their psychotherapists) were assigned to six main categories. Educational and cognitive aspects were mentioned most frequently and consistently by both groups. Having learned Behavioural alternatives attained the second highest agreement between perspectives. Conclusions: Patients and therapists valued CBT as an opportunity to learn new skills, which is an important prerequisite also for the maintenance of therapeutic change. We discuss limitations to generalizability but also theoretical and therapy implications.
Spatial abilities have been found to interact with the design of visualizations in educational materials in different forms: (1) spatial abilities enhanced learning with optimized visual design (ability-as-enhancer) or (2) spatial abilities compensated for suboptimal visual design (ability-as-compensator). A brief review of pertinent studies suggests that these two forms are viewed as mutually exclusive. We propose a novel unifying conceptualization. This conceptualization suggests that the ability-as enhancer interaction will be found in the low-medium range of a broad ability continuum whereas the ability-as-compensator interaction will be found in the medium-high range. The largest difference in learning outcomes between visual design variations is expected for medium ability. A corresponding analytical approach is suggested that includes nonlinear quadratic interactions. The unifying conceptualization was confirmed in an experiment with a consistent visual-spatial task. In addition, the conceptualization was investigated with a reanalysis of pooled data from four multimedia learning experiments. Consistent with the conceptualization, quadratic interactions were found, meaning that interactions depended on ability range. The largest difference between visual design variations was obtained for medium ability, as expected. It is concluded that the unifying conceptualization is a useful theoretical and methodological approach to analyze and interpret aptitude-treatment interactions that go beyond linear interactions.
This article presents the design and a first pilot evaluation of the computer-based training program Calcularis for children with developmental dyscalculia (DD) or difficulties in learning mathematics. The program has been designed according to insights on the typical and atypical development of mathematical abilities. The learning process is supported through multimodal cues, which encode different properties of numbers. To offer optimal learning conditions, a user model completes the program and allows flexible adaptation to a child's individual learning and knowledge profile. Thirty-two children with difficulties in learning mathematics completed the 6-12-weeks computer training. The children played the game for 20 min per day for 5 days a week. The training effects were evaluated using neuropsychological tests. Generally, children benefited significantly from the training regarding number representation and arithmetic operations. Furthermore, children liked to play with the program and reported that the training improved their mathematical abilities.
Language skills and mathematical competencies are argued to influence each other during development. While a relation between the development of vocabulary size and mathematical skills is already documented in the literature, this study further examines how children's ability to map a novel word to an unknown object as well as their ability to retain this word from memory may be related to their knowledge of number words. Twenty-five children were tested longitudinally (at 30 and at 36 months of age) using an eye-tracking-based fast mapping task, the Give-a Number task, and standardized measures of vocabulary. The results reveal that children's ability to create and retain a mental representation of a novel word was related to number knowledge at 30 months, but not at 36 months while vocabulary size correlated with number knowledge only at 36 months. These results show that even specific mapping processes are initially related to the acquisition of number words and they speak for a parallelism between the development of lexical and number-concept knowledge despite their semantic and syntactic differences.
In this communication the development of an online course on the topic organic chemistry for nonmajor chemistry students is described and discussed. For this online course, the existing classroom course was further developed. New elements such as podcasts, task navigators, and a forum for discussing the solving of tasks or problems with the content were added. This new online course was evaluated. Therefore, a questionnaire was developed. This consists of questions with regard to the longtime learning behavior of the students and to the online learning. The results of this evaluation show that a preference for online learning and a preference for classroom teaching can be measured separately in two scales. Students values on the scale representing a preference for online learning correlate positively and significantly with confidence in the choice of the study subject, enthusiasm about the subject, and the ability to organize their learning, learning environment, and time management. They correlate also with the satisfaction concerning the materials provided. Students values for one of those teaching methods also correlate with their rating with regard to their exam preparation. Values representing a preference for online teaching correlate positively with students better feeling of exam preparation. Values representing a preference for classroom teaching show negative correlations with the values representing students similar or even better preparation for the exams as a result of online teaching. It is therefore not surprising that the ratings for the two scales correlate with the wish for a combination of online teaching and classroom teaching in the future. As a solution, a new course concept for the time after the corona virus crisis that suits all students is outlined in the outlook.
In the time of digitalization the demand for organizational change is rising and demands ways to cope with fundamental changes on the organizational as well as individual level. As a basis, learning and forgetting mechanisms need to be understood in order to guide a change process efficiently and successfully. Our research aims to get a better understanding of individual differences and mechanisms in the change context by performing an experiment where individuals learn and later re-learn a complex production process using a simulation setting. The individual’s performance, as well as retentivity and prior knowledge is assessed. Our results show that higher retentivity goes along with better learning and forgetting performances. Prior knowledge did not reveal such relation to the learning and forgetting performances. The influence of age and gender is discussed in detail.