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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.
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.
Background:
Under the new psychotherapy law in Germany, standardized patients (SPs) are to become a standard component inpsychotherapy training, even though little is known about their authenticity.Objective:The present pilot study explored whether, followingan exhaustive two-day SP training, psychotherapy trainees can distinguish SPs from real patients.
Methods:
Twenty-eight psychotherapytrainees (M= 28.54 years of age,SD= 3.19) participated as blind raters. They evaluated six video-recorded therapy segments of trained SPsand real patients using the Authenticity of Patient Demonstrations Scale.
Results:
The authenticity scores of real patients and SPs did notdiffer (p= .43). The descriptive results indicated that the highest score of authenticity was given to an SP. Further, the real patients did notdiffer significantly from the SPs concerning perceived impairment (p= .33) and the likelihood of being a real patient (p= .52).
Conclusions:
The current results suggest that psychotherapy trainees were unable to distinguish the SPs from real patients. We therefore stronglyrecommend incorporating training SPs before application. Limitations and future research directions are discussed.
Detection of the QRS complex is a long-standing topic in the context of electrocardiography and many algorithms build upon the knowledge of the QRS positions. Although the first solutions to this problem were proposed in the 1970s and 1980s, there is still potential for improvements. Advancements in neural network technology made in recent years also lead to the emergence of enhanced QRS detectors based on artificial neural networks. In this work, we propose a method for assessing the certainty that is in each of the detected QRS complexes, i.e. how confident the QRS detector is that there is, in fact, a QRS complex in the position where it was detected. We further show how this metric can be utilised to distinguish correctly detected QRS complexes from false detections.
When playing violent video games, aggressive actions are performed against the background of an originally neutral environment, and associations are formed between cues related to violence and contextual features. This experiment examined the hypothesis that neutral contextual features of a virtual environment become associated with aggressive meaning and acquire the function of primes for aggressive cognitions. Seventy-six participants were assigned to one of two violent video game conditions that varied in context (ship vs. city environment) or a control condition. Afterwards, they completed a Lexical Decision Task to measure the accessibility of aggressive cognitions in which they were primed either with ship-related or city-related words. As predicted, participants who had played the violent game in the ship environment had shorter reaction times for aggressive words following the ship primes than the city primes, whereas participants in the city condition responded faster to the aggressive words following the city primes compared to the ship primes. No parallel effect was observed for the non-aggressive targets. The findings indicate that the associations between violent and neutral cognitions learned during violent game play facilitate the accessibility of aggressive cognitions.
When playing violent video games, aggressive actions are performed against the background of an originally neutral environment, and associations are formed between cues related to violence and contextual features. This experiment examined the hypothesis that neutral contextual features of a virtual environment become associated with aggressive meaning and acquire the function of primes for aggressive cognitions. Seventy-six participants were assigned to one of two violent video game conditions that varied in context (ship vs. city environment) or a control condition. Afterwards, they completed a Lexical Decision Task to measure the accessibility of aggressive cognitions in which they were primed either with ship-related or city-related words. As predicted, participants who had played the violent game in the ship environment had shorter reaction times for aggressive words following the ship primes than the city primes, whereas participants in the city condition responded faster to the aggressive words following the city primes compared to the ship primes. No parallel effect was observed for the non-aggressive targets. The findings indicate that the associations between violent and neutral cognitions learned during violent game play facilitate the accessibility of aggressive cognitions.
Social networking sites (SNS) are a rich source of latent information about individual characteristics. Crawling and analyzing this content provides a new approach for enterprises to personalize services and put forward product recommendations. In the past few years, commercial brands made a gradual appearance on social media platforms for advertisement, customers support and public relation purposes and by now it became a necessity throughout all branches. This online identity can be represented as a brand personality that reflects how a brand is perceived by its customers. We exploited recent research in text analysis and personality detection to build an automatic brand personality prediction model on top of the (Five-Factor Model) and (Linguistic Inquiry and Word Count) features extracted from publicly available benchmarks. Predictive evaluation on brands' accounts reveals that Facebook platform provides a slight advantage over Twitter platform in offering more self-disclosure for users' to express their emotions especially their demographic and psychological traits. Results also confirm the wider perspective that the same social media account carry a quite similar and comparable personality scores over different social media platforms. For evaluating our prediction results on actual brands' accounts, we crawled the Facebook API and Twitter API respectively for 100k posts from the most valuable brands' pages in the USA and we visualize exemplars of comparison results and present suggestions for future directions.
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.
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.
Prediction is often regarded as a central and domain-general aspect of cognition. This proposal extends to language, where predictive processing might enable the comprehension of rapidly unfolding input by anticipating upcoming words or their semantic features. To make these predictions, the brain needs to form a representation of the predictive patterns in the environment. Predictive processing theories suggest a continuous learning process that is driven by prediction errors, but much is still to be learned about this mechanism in language comprehension. This thesis therefore combined three electroencephalography (EEG) experiments to explore the relationship between prediction and implicit learning at the level of meaning.
Results from Study 1 support the assumption that the brain constantly infers und updates probabilistic representations of the semantic context, potentially across multiple levels of complexity. N400 and P600 brain potentials could be predicted by semantic surprise based on a probabilistic estimate of previous exposure and a more complex probability representation, respectively.
Subsequent work investigated the influence of prediction errors on the update of semantic predictions during sentence comprehension. In line with error-based learning, unexpected sentence continuations in Study 2 ¬– characterized by large N400 amplitudes ¬– were associated with increased implicit memory compared to expected continuations. Further, Study 3 indicates that prediction errors not only strengthen the representation of the unexpected word, but also update specific predictions made from the respective sentence context. The study additionally provides initial evidence that the amount of unpredicted information as reflected in N400 amplitudes drives this update of predictions, irrespective of the strength of the original incorrect prediction.
Together, these results support a central assumption of predictive processing theories: A probabilistic predictive representation at the level of meaning that is updated by prediction errors. They further propose the N400 ERP component as a possible learning signal. The results also emphasize the need for further research regarding the role of the late positive ERP components in error-based learning. The continuous error-based adaptation described in this thesis allows the brain to improve its predictive representation with the aim to make better predictions in the future.
The accelerating climatic changes and new infrastructure development across the Arctic require more robust risk and environmental assessment, but thus far there is no consistent record of human impact. We provide a first panarctic satellite-based record of expanding infrastructure and anthropogenic impacts along all permafrost affected coasts (100 km buffer, approximate to 6.2 Mio km(2)), named the Sentinel-1/2 derived Arctic Coastal Human Impact (SACHI) dataset. The completeness and thematic content goes beyond traditional satellite based approaches as well as other publicly accessible data sources. Three classes are considered: linear transport infrastructure (roads and railways), buildings, and other impacted area. C-band synthetic aperture radar and multi-spectral information (2016-2020) is exploited within a machine learning framework (gradient boosting machines and deep learning) and combined for retrieval with 10 m nominal resolution. In total, an area of 1243 km(2) constitutes human-built infrastructure as of 2016-2020. Depending on region, SACHI contains 8%-48% more information (human presence) than in OpenStreetMap. 221 (78%) more settlements are identified than in a recently published dataset for this region. 47% is not covered in a global night-time light dataset from 2016. At least 15% (180 km(2)) correspond to new or increased detectable human impact since 2000 according to a Landsat-based normalized difference vegetation index trend comparison within the analysis extent. Most of the expanded presence occurred in Russia, but also some in Canada and US. 31% and 5% of impacted area associated predominantly with oil/gas and mining industry respectively has appeared after 2000. 55% of the identified human impacted area will be shifting to above 0 C-circle ground temperature at two meter depth by 2050 if current permafrost warming trends continue at the pace of the last two decades, highlighting the critical importance to better understand how much and where Arctic infrastructure may become threatened by permafrost thaw.
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.
Social networks are currently at the forefront of tools that
lend to Personal Learning Environments (PLEs). This study aimed to
observe how students perceived PLEs, what they believed were the
integral components of social presence when using Facebook as part
of a PLE, and to describe student’s preferences for types of interactions
when using Facebook as part of their PLE. This study used mixed
methods to analyze the perceptions of graduate and undergraduate
students on the use of social networks, more specifically Facebook as a
learning tool. Fifty surveys were returned representing a 65 % response
rate. Survey questions included both closed and open-ended questions.
Findings suggested that even though students rated themselves relatively
well in having requisite technology skills, and 94 % of students used
Facebook primarily for social use, they were hesitant to migrate these
skills to academic use because of concerns of privacy, believing that
other platforms could fulfil the same purpose, and by not seeing the
validity to use Facebook in establishing social presence. What lies
at odds with these beliefs is that when asked to identify strategies in
Facebook that enabled social presence to occur in academic work, the
majority of students identified strategies in five categories that lead to
social presence establishment on Facebook during their coursework.
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.
This article provides some insights into the complex relationships between thinking and behavioral patterns, bio graphical aspects and teaching style. The data was analyzed in the Grounded Theory tradition and with the help of ATLAS.ti. The results presented here offer preliminary findings only since the research is still ongoing. The focus is on the ways teachers deal with mistakes. Based on two case examples, it will be shown how the fear of making mistakes can lead to teacher-centered lessons, and thereby limiting pupils' possibilities to learn autonomously.
To investigate how preschoolers acquire a tool use strategy and how they adapt their tool use to a changed situation, 2- to 4-year-olds were asked to retrieve chips from a transparent box with a rod, either by stabbing and lifting through a top opening or by pushing through a front and a back opening. In both conditions, about 40% of the children acquired effective tool use by individual learning, and 90% of the other children learned this by observing only one demonstration. When confronted with a changed situation (i.e., previous opening covered, alternative opening uncovered), children perseverated with the recently learned, but now ineffective tool use strategy. Neither age nor acquisition type of the first strategy affected preschoolers' perseverations. Results indicate that prior tool use experiences have differential effects in situations that require either transferring known functions to novel objects or using a familiar tool for an alternative purpose.
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.
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.