Showing papers by "Media Research Center published in 2018"

Cross-subject workload classification using pupil-related measures

Abstract: Real-time evaluation of a person's cognitive load can be desirable in many situations. It can be employed to automatically assess or adjust the difficulty of a task, as a safety measure, or in psychological research. Eye-related measures, such as the pupil diameter or blink rate, provide a non-intrusive way to assess the cognitive load of a subject and have therefore been used in a variety of applications. Usually, workload classifiers trained on these measures are highly subject-dependent and transfer poorly to other subjects. We present a novel method to generalize from a set of trained classifiers to new and unknown subjects. We use normalized features and a similarity function to match a new subject with similar subjects, for which classifiers have been previously trained. These classifiers are then used in a weighted voting system to detect workload for an unknown subject. For real-time workload classification, our methods performs at 70.4% accuracy. Higher accuracy of 76.8% can be achieved in an offline classification setting.

Heat-assisted magnetic recording media materials

Abstract: Heat-assisted magnetic recording (HAMR) is being developed as the next-generation magnetic recording technology. High anisotropy granular media such as FePt-C have been demonstrated as HAMR media for ∼2 Tbpsi (terabits per in2) recording density. In order for this technology to reach its full potential of 4–5 Tbpsi, more progress and innovations are needed for the key requirements for HAMR media, including microstructure, design, magnetic distribution, and thermal design. Beyond granular media, heated-dot magnetic recording (HDMR) is planned to extend areal density toward 10 Tbpsi. HDMR combines similar advanced recording layer materials with advanced patterning techniques to fabricate <10-nm rectangular dot media.

Emotionalization in Science Communication: The Impact of Narratives and Visual Representations on Knowledge Gain and Risk Perception

Abstract: The communication of scientific information plays an increasingly important role for scientists and scientific institutions. This is especially true of institutions in the field of biodiversity and conservation research, since the transfer of research results to the public is a prerequisite for decision-making, and the success of conservation measures often depends on public acceptance or active contribution. To have the desired impact, science communication in the context of human-wildlife interactions must enable recipients to (1) gain valid knowledge, (2) form an attitude toward the subject matter, and (3) develop an adequate understanding of the risks and dangers associated with human-wildlife interactions, which are usually overestimated by the general public. Using the topic of foxes in urban habitats, we investigated the role of emotionalization in science communication. In a laboratory experiment with 127 university students (91 females), we manipulated textual and visual features in an information brochure about foxes and examined their impact on people’s knowledge gain, attitude development, and modified risk perception. In particular, we compared a narrative presentation to a non-narrative list of facts and examined the use of photographs of young foxes. We found a positive development in all of the outcome variables from the pre- to the posttest (more knowledge, more positive attitude, lower risk perception). We also found an interaction effect of text type and visualization on knowledge gain that highlighted the importance of the fit between text type and visualization. In contrast to our expectations, we did not find any differential effects of specific treatments on attitude development. Finally, we found a main effect of text type on modified risk perception, indicating less reduction of risk perception with a narrative article than with a fact list. We discuss our findings with respect to the role of emotionalization in science communication, stressing that it is particularly important to achieve a suitable fit between textual and visual forms of emotionalization, depending on the goal of communication. We also discuss possible explanations as to why some hypotheses were not supported by the data. In our concluding statements we refer to limitations of the present study and address implications

Gait Estimation from Anatomical Foot Parameters Measured by a Foot Feature Measurement System using a Deep Neural Network Model

Abstract: An accurate and credible measurement of human gait is essential in multiple areas of medical science and rehabilitation. Yet, the methods currently available are not only arduous but also costly. Researchers who investigated the relationship between foot and gait parameters have found that the two parameters are closely interrelated and suggested that measuring foot characteristics can be an alternative to the strenuous quantification currently in use. This study aims to verify the potential of foot characteristics in predicting the actual gait temporo-spatial parameters and to develop a deep neural network (DNN) model that can estimate and quantify the gait temporo-spatial parameters from foot characteristics. The foot features in sitting, standing, and one-leg standing conditions of 42 subjects were used as the input data and gait temporo-spatial parameters at fast, normal, and slow speed were set as the output of the DNN regressor. With the prediction accuracy of 95% or higher, the feasibility of the developed model was verified. This study might be the first in attempting experimental verification of the foot features serving as predictors of individual gait. The DNN regressor will help researchers improve the data pool with less labor and expense when some limitations get properly overcome.

Cloud-Edge Collaboration Framework for IoT data analytics

Abstract: In recent years, big data analysis from Internet of Things (IoT) has been getting more attention. Several cloud platforms have provided machine learning service with a pre-trained model to understand IoT data. However, it is necessary to transfer personal data in order to use the cloud service, and network problems might be preventing the customer from getting analysis results at an appropriate time. To overcome these problems, data and analysis task are moving to the edge platform. However, most edge devices do not have enough capacity to process and train large amounts of data. In this paper, we propose a new framework structure that can analyze IoT data by distributing analysis role. The proposed framework is designed to maximize the resources of the cloud to generate the model and to use the model at the edge to enable immediate and instantaneous actuator operation. And we also present a case study to verify this framework.

Using big data techniques for measuring productive friction in mass collaboration online environments

Abstract: The advent of the social web brought with it challenges and opportunities for research on learning and knowledge construction. Using the online-encyclopedia Wikipedia as an example, we discuss several methods that can be applied to analyze the dynamic nature of knowledge-related processes in mass collaboration environments. These methods can help in the analysis of the interactions between the two levels that are relevant in computer-supported collaborative learning (CSCL) research: The individual level of learners and the collective level of the group or community. In line with constructivist theories of learning, we argue that the development of knowledge on both levels is triggered by productive friction, that is, the prolific resolution of socio-cognitive conflicts. By describing three prototypical methods that have been used in previous Wikipedia research, we review how these techniques can be used to examine the dynamics on both levels and analyze how these dynamics can be predicted by the amount of productive friction. We illustrate how these studies make use of text classifiers, social network analysis, and cluster analysis in order to operationalize the theoretical concepts. We conclude by discussing implications for the analysis of dynamic knowledge processes from a learning sciences perspective.

Accelerated generation of holographic videos of 3-D objects in rotational motion using a curved hologram-based rotational-motion compensation method.

Abstract: A new curved hologram-based rotational-motion compensation (CH-RMC) method is proposed for accelerated generation of holographic videos of 3-D objects moving on the random path with many locally different arcs. All of those rotational motions of the object made on each arc can be compensated, just by rotating their local curved holograms along the curving surfaces matched with the object's moving trajectory without any additional calculation process, which results in great enhancements of the computational speed of the conventional hologram-generation algorithms. Experiments with a test video scenario reveal that average numbers of calculated object points (ANCOPs) and average calculation times for one frame (ACTs) of the CH-RMC-based ray-tracing, wavefront-recording-plane and novel- look-up-table methods have been found to be reduced by 73.10%, 73.84%, 73.34%, and 68.75%, 50.82%, 66.59%, respectively, in comparison with those of their original methods. In addition, successful reconstructions of 3-D scenes from those holographic videos confirm the feasibility of the proposed system.

Neither fish nor fowl: A perceived mismatch in norms and values between oneself, other students, and people back home undermines adaptation to university

Abstract: Students from low social-class background often struggle to adapt to university. Previous research shows that perceived incompatibility between social-class background identity and student identity is one reason, but little is known about the underlying causes of identity incompatibility. In three studies, we expected and found that students with low subjective social-class background perceived their values differently from other students, but also differently from people back home, and both increased identity incompatibility. Identity incompatibility negatively affected the student identity. Additionally, the current research also identifies specific patterns of norm and value differences that are prone to perceived identity incompatibility. The findings demonstrate that perceived differences in values from both groups are important mechanisms for identity incompatibility induced by the transition to university that may affect student identities and potentially their university trajectories.

Positive essentialization reduces prejudice: Reminding participants of a positive human nature alleviates the stigma of Indonesian Communist Party (PKI) descent

Abstract: This study aims to demonstrate and change negative perceptions of descendants of members of the Indonesian Communist Party (Partai Komunis Indonesia/PKI), a stigmatized social group in Indonesia. In Studies 1 and 2, participants were given positive descriptions of an adult (Study 1) and a child (Study 2), and were asked to evaluate them twice, before and after reading information about the target’s family background. In Study 1, targets were described either as descendants of PKI members, members of another Indonesian party or criminals. In Study 2, the target was presented as a descendant of PKI members, of members of another Indonesian party or without information on family background (control condition). The studies showed that whenever people were ‘revealed’ to be descendants of PKI members, the respondents’ judgments became more negative, and their assumptions about commonly shared views of these people became more negative as well. In Studies 3 and 4, participants were again given descriptions of an adult (Study 3) and a child (Study 4), which were both described as descendants of PKI members. Half of the participants were reminded afterwards with a written statement that every human is by nature good and unique (the experimental condition), while the other half did not get any additional information (control group). By making salient a shared and positively valued human ‘essence’, it was possible to alleviate the stigma that still is attached to PKI-affiliations in Indonesian society. We end the study with a discussion of our findings’ political and societal implications.

Developing understanding beyond the given knowledge and new methodologies for analyses in CSCL

Abstract: In schools and educational settings, students increasingly need to learn content and perspectives that are not given as part of the curriculum. When working with digital resources embedded in digital environments and infrastructures, students’ and teachers’ tasks often become more complex and need more social and cognitive framing. The sequential organization of textbooks has historically provided teachers and students with well-established structures for student actions. However, when other resources become more important, designers, teachers, and students need to establish additional forms of supports and scaffolds for learning. The first two papers in this issue address this theme, focusing on how to support students in their work with digital resources. The other two papers look at important methodological issues in computer-supported collaborative learning to analyze and describe collaborative work. The third paper problematizes the coding-and-counting approach in CSCL and provides an alternative method International Journal of Computer-Supported Collaborative Learning (2018) 13:359–364 https://doi.org/10.1007/s11412-018-9291-0

Effects of Contributor Experience on the Quality of Health-Related Wikipedia Articles.

Abstract: Background: Consulting the Internet for health-related information is a common and widespread phenomenon, and Wikipedia is arguably one of the most important resources for health-related information. Therefore, it is relevant to identify factors that have an impact on the quality of health-related Wikipedia articles. Objective: In our study we have hypothesized a positive effect of contributor experience on the quality of health-related Wikipedia articles. Methods: We mined the edit history of all (as of February 2017) 18,805 articles that were listed in the categories on the portal health & fitness in the English language version of Wikipedia. We identified tags within the articles’ edit histories, which indicated potential issues with regard to the respective article’s quality or neutrality. Of all of the sampled articles, 99 (99/18,805, 0.53%) articles had at some point received at least one such tag. In our analysis we only considered those articles with a minimum of 10 edits (10,265 articles in total; 96 tagged articles, 0.94%). Additionally, to test our hypothesis, we constructed contributor profiles, where a profile consisted of all the articles edited by a contributor and the corresponding number of edits contributed. We did not differentiate between rollbacks and edits with novel content. Results: Nonparametric Mann-Whitney U-tests indicated a higher number of previously edited articles for editors of the nontagged articles (mean rank tagged 2348.23, mean rank nontagged 5159.29; U=9.25, P<.001). However, we did not find a significant difference for the contributors’ total number of edits (mean rank tagged 4872.85, mean rank nontagged 5135.48; U=0.87, P=.39). Using logistic regression analysis with the respective article’s number of edits and number of editors as covariates, only the number of edited articles yielded a significant effect on the article’s status as tagged versus nontagged (dummy-coded; Nagelkerke R2 for the full model=.17; B [SE B]=-0.001 [0.00]; Wald c2 [1]=19.70; P<.001), whereas we again found no significant effect for the mere number of edits (Nagelkerke R2 for the full model=.15; B [SE B]=0.000 [0.01]; Wald c2 [1]=0.01; P=.94). Conclusions: Our findings indicate an effect of contributor experience on the quality of health-related Wikipedia articles. However, only the number of previously edited articles was a predictor of the articles’ quality but not the mere volume of edits. More research is needed to disentangle the different aspects of contributor experience. We have discussed the implications of our findings with respect to ensuring the quality of health-related information in collaborative knowledge-building platforms.

Spatial Arrangement and Set Size Influence the Coding of Non-symbolic Quantities in the Intraparietal Sulcus.

Abstract: Performance in visual quantification tasks shows two characteristic patterns as a function of set size. A precise subitizing process for small sets (up to four) was contrasted with an approximate estimation process for larger sets. The spatial arrangement of elements in a set also influences visual quantification performance, with frequently perceived arrangements (e.g. dice patterns) being faster enumerated than random arrangements. Neuropsychological and imaging studies identified the intraparietal sulcus (IPS), as key brain area for quantification, both within and above the subitizing range. However, it is not yet clear if and how set size and spatial arrangement of elements in a set modulate IPS activity during quantification. In an fMRI study, participants enumerated briefly presented dot patterns with random, canonical or dice arrangement within and above the subitizing range. We evaluated how activity amplitude and pattern in the IPS were influenced by size and spatial arrangement of a set. We found a discontinuity in the amplitude of IPS response between subitizing and estimation range, with steep activity increase for sets exceeding four elements. In the estimation range, random dot arrangements elicited stronger IPS response than canonical arrangements which in turn elicited stronger response than dice arrangements. Furthermore, IPS activity patterns differed systematically between arrangements. We found a signature in the IPS response for a transition between subitizing and estimation processes during quantification. Differences in amplitude and pattern of IPS activity for different spatial arrangements indicated a more precise representation of non-symbolic numerical magnitude for dice and canonical than for random arrangements. These findings challenge the idea of an abstract coding of numerosity in the IPS even within a single notation.

Teachers' Perception in the Classroom

Abstract: The ability for a teacher to engage all students in active learning processes in classroom constitutes a crucial prerequisite for enhancing students achievement. Teachers' attentional processes provide important insights into teachers' ability to focus their attention on relevant information in the complexity of classroom interaction and distribute their attention across students in order to recognize the relevant needs for learning. In this context, mobile eye tracking is an innovative approach within teaching effectiveness research to capture teachers' attentional processes while teaching. However, analyzing mobile eye-tracking data by hand is time consuming and still limited. In this paper, we introduce a new approach to enhance the impact of mobile eye tracking by connecting it with computer vision. In mobile eye tracking videos from an educational study using a standardized small group situation, we apply a state-ofthe-art face detector, create face tracklets, and introduce a novel method to cluster faces into the number of identity. Subsequently, teachers' attentional focus is calculated per student during a teaching unit by associating eye tracking fixations and face tracklets. To the best of our knowledge, this is the first work to combine computer vision and mobile eye tracking to model teachers' attention while instructing.

Video Surveillance System Based on 3D Action Recognition

Abstract: Human action recognition using depth-map images from 3D camera for surveillance system is a promising alternative to the conventional 2D video based surveillance. We propose a security-event detection method based on body part classification and human action recognition for more effective video surveillance system. Experimental results show that the body part classification accuracy of 65.0% and security event detection accuracy of 0.878 were achieved for 9 security events.

Semi-automatic image and video annotation system for generating ground truth information

Abstract: Recently, techniques for automatically interpreting images or videos through machine learning based on big data have been actively studied. In this paper, we propose a semiautomatic image and video annotation system to generate ground truth information, which is essential information for machine learning of images or videos. Unlike the conventional methods for generating simple ground truth information manually, the proposed system not only provides various ground truth information such as object information, motion information, and event information, but also uses a semi-automatic image and video annotation method for fast generation of ground truth information. The ground truth information generated by the proposed system is stored in the metadata database as a form of XML. The implementation results show that the proposed system provides not only fast ground truth annotation, but also more various ground truth information compared to the existing methods.

A Study on Face Masking Scheme in Video Surveillance System

Abstract: In this paper, we analyze face masking schemes in the video surveillance system for protecting the personal privacy from videos acquired by CCTV cameras. Existing face masking schemes have a problem that the face of humans can be identified because face masking setting values cannot be applied as an appropriate value. Through implementation results, we found optimal values for face masking to perfectly protect the personal privacy.

The influence of number magnitude on continuous swiping movements

Abstract: There is accumulating evidence that numerical information influences the way in which we perform bodily movements. Specifically, the idea that our cognitive representations of numbers and space interact is supported by systematic associations of space with both number magnitude (SNARC effect) and number parity (MARC effect). However, whether this influence is bound to the left or right side of space or to the hand with which we perform the movement remains debated. One novel and interesting way to disentangle these factors is to use movement responses in which hand and movement direction can be dissociated. In the present study, participants moved a central object to the left or right side on a touchscreen with their index fingers as response to a parity judgment and magnitude classification task. We observed significant SNARC effects in both tasks. Number magnitude and response direction interacted, but magnitude and response hand did not. This indicated that the SNARC effect can be independent of the responding hand. Importantly, however, a MARC effect was observed not only in an interaction between response direction and parity, but also in an interaction between response hand and parity, suggesting that response hand plays a role in the interaction between physical space and parity. Additionally, number magnitude influenced the amplitude of participants’ response movements, with larger numbers eliciting longer movements. These results indicate that space, magnitude and parity interact on different levels that can be unraveled in a paradigm utilizing continuous movements such as swiping.

Revisiting the Kuleshov Effect with First-Time Viewers

Abstract: Researchers have recently suggested that historically mixed findings in studies of the Kuleshov effect (a classic film editing-related phenomenon whereby meaning is extracted from the interaction of sequential camera shots) might reflect differences in the relative sophistication of early vs. modern cinema audiences. Relative to experienced audiences, first-time film viewers might be less predisposed and/or able to forge the required conceptual and perceptual links between the edited shots in order to demonstrate the effect. The current study recreates the conditions that traditionally elicit this effect (whereby a neutral face comes to be perceived as expressive after it is juxtaposed with independent images: a bowl of soup, a gravestone, a child playing) to directly investigate and compare “continuity” perception in first-time and more experienced film viewers. Results confirm the presence of the Kuleshov effect for experienced viewers (explicitly only in the sadness condition) but not the first-time viewers, who failed to perceive continuity between the shots.

The Norm of Neutrality in Collaborative Knowledge Construction

Abstract: Social media enabled collaboration at unprecedented levels. And while research points to the benefits of mass collaboration, it has also revealed challenges and problems. Here we explore biases in collaboratively constructed knowledge. To this end, we compared two online encyclopedias: Wikipedia and the extreme right-wing Metapedia. Both urge users to present topics from a neutral point of view. Using different measures we found that Metapedia articles (vs. Wikipedia articles) are significantly shorter, contain fewer references, contain relatively more anger- and anxiety-related words, rarely present more than one point of view in controversies, and often convey opinions – for inctance, by using pejorative language. Thus, norms might not be very effective in preventing biases – particularly if they largely remain a projection screen.

Condensin controls cellular RNA levels through the accurate segregation of chromosomes instead of directly regulating transcription

Abstract: Condensins are genome organisers that shape chromosomes and promote their accurate transmission. Several studies have also implicated condensins in gene expression, although the mechanisms have remained enigmatic. Here, we report on the role of condensin in gene expression in fission and budding yeasts. In contrast to previous studies, we provide compelling evidence that condensin plays no direct role in the maintenance of the transcriptome, neither during interphase nor during mitosis. We further show that the changes in gene expression in post-mitotic fission yeast cells that result from condensin inactivation are largely a consequence of chromosome missegregation during anaphase, which notably depletes the RNA-exosome from daughter cells. Crucially, preventing karyotype abnormalities in daughter cells restores a normal transcriptome despite condensin inactivation. Thus, chromosome instability, rather than a direct role of condensin in the transcription process, changes gene expression. This knowledge challenges the concept of gene regulation by canonical condensin complexes.

Service Mediation Gateway for Heterogenous IoT Services Harmonization

Abstract: To populate IoT service, having remote control on a smart device is not enough. More complicated IoT services are needed by combining each IoT service, and enabling communication between independent services are essential to them. There are several solutions and services to provide interactivity between IoT services in the market such as IFTTT or Muzzley. However, most of these services are implemented on the cloud, which makes it difficult to get prompt response for application request. In this paper, a Service Mediation Gateway is proposed to improve connectivity between IoT services with less response time. The proposed gateway is located between IoT services and the application, just like an edge or fog device, and works as a data cache for IoT resources on the cloud. The proposed gateway can be implemented both on the cloud and on the edge, so that provide more prompt response to the application. The proposed gateway has been implemented with existing IoT services, and the comparison with existing cloud services is evaluated.