Investigation of Pre-Service Teachers’ Metaphorical Images towards the Concepts of “Teacher Candidate” and “Teacher Educator”

The purpose of this study was to describe the metaphorical images of the prospective teachers, who were employed in different teaching programs of education faculties, regarding themselves and their educators, and to evaluate the standard teacher education program in a critical manner. Even though prospective teachers’ metaphorical images pertaining learning, teaching, school and so forth were extensively examined in the previous studies, their personal theories for themselves and their educators have not been subjected to any research study. The current study was designed and conducted as a single survey study. The study was carried out with the participation of 1130 prospective teachers studying at the education faculty of a foundation-supported (private) university in Istanbul. Metaphorical images were taken from all participants towards themselves and their educators. As a result of the interpretive and inductive analysis, the prospective teachers generated metaphorical images for themselves such as: something that needs to be cultivated, leader of future, a fixed-static object, the candidate of the molder, something deceptive, something needs to be shaped, obedient, knowledge receiver, racer, etc. The prospective teachers also produced metaphorical images for their educators in the following manner: bridge function, organic growers, knowledge transmitter, a valuable object, competitors. In general, it was observed that pre-service teachers held a considerably pedagogically subjectcentred or teacher-centred or authority-centred “self ” and “educator” perception. Recommendations were offered regarding pre-service teacher education

Context-Based Structure Mining Methodology for Static Object Re-Identification in Broadcast Content

Technological advancement, in addition to the pandemic, has given rise to an explosive increase in the consumption and creation of multimedia content worldwide. This has motivated people to enrich and publish their content in a way that enhances the experience of the user. In this paper, we propose a context-based structure mining pipeline that not only attempts to enrich the content, but also simultaneously splits it into shots and logical story units (LSU). Subsequently, this paper extends the structure mining pipeline to re-ID objects in broadcast videos such as SOAPs. We hypothesise the object re-ID problem of SOAP-type content to be equivalent to the identification of reoccurring contexts, since these contexts normally have a unique spatio-temporal similarity within the content structure. By implementing pre-trained models for object and place detection, the pipeline was evaluated using metrics for shot and scene detection on benchmark datasets, such as RAI. The object re-ID methodology was also evaluated on 20 randomly selected episodes from broadcast SOAP shows New Girl and Friends. We demonstrate, quantitatively, that the pipeline outperforms existing state-of-the-art methods for shot boundary detection, scene detection, and re-identification tasks.

Unsettling intimacies:Re-cognizing ecological relations with the work of Jean Clandinin

For Jean Clandinin, narrative inquiry is not about being but becoming and as such posits knowledge as a continuous, non-teleological process rather than a static object. Experiential knowledge, for Clandinin, then, is intimately bound up with the vicissitudes of lived experience. If stories make meaning from experience, they open up an imaginative space through which researchers can come to understand experience as well as the knowledge that emerges from it or re-cognize such. Inquiring into experiential knowledge through narratives is valuable for research, and particularly for research that engages ecological crises, because it enables a more robust, nuanced view of life—both human and nonhuman—to emerge. Further, as Clandinin’s work reconfigures the role of the researcher, it unsettles hierarchical assumptions within the research space, allowing for collaboration, polyphonic texts, and reconfigured understandings to emerge. Clandinin’s work troubles dominant narratives about knowledge that presuppose conceptual reification and mastery. As such, narrative inquiry has the potential to support research that is interested in reconfiguring relationships between human and non-human “nature” in ways that do not necessarily fit into dominant narratives about knowledge in education. Using a framework informed by contemporary eco-criticism and trauma theory, I consider how narrative inquiry might offer reparative methods for educational research that engages ecological crises. As narrative inquiry aims to honour the particularity of experience and promote growth without assimilating plurality into an objective singularity, its methods have the capacity to provide insights into ecological relations that are critical, self-reflexive, and ethically responsive.

Motion disrupts dynamic visual search for an orientation change

Visual search in dynamic environments, for example lifeguarding or CCTV monitoring, has several fundamentally different properties to standard visual search tasks. The visual environment is constantly moving, a range of items could become targets and the task is to search for a certain event. We developed a novel task in which participants were required to search static and moving displays for an orientation change thus capturing components of visual search, multiple object tracking and change detection paradigms. In Experiment 1, we found that the addition of moving distractors slowed participants’ response time to detect an orientation changes in a moving target, showing that the motion of distractors disrupts the rapid detection of orientation changes in a moving target. In Experiment 2 we found that, in displays of both moving and static objects, response time was slower if a moving object underwent a change than if a static object did, thus demonstrating that motion of the target itself also disrupts the detection of an orientation change. Our results could have implications for training in real-world occupations where the task is to search a dynamic environment for a critical event. Moreover, we add to the literature highlighting the need to develop lab-based tasks with high experimental control from any real-world tasks researchers may wish to investigate rather than extrapolating from static visual search tasks to more dynamic environments.

HUMANNET-a Two-Tiered Deep Neural Network Architecture for Self-Occluding Humanoid Pose Reconstruction

Majority of current research focuses on a single static object reconstruction from a given pointcloud. However, the existing approaches are not applicable to real world applications such as dynamic and morphing scene reconstruction. To solve this, we propose a novel two-tiered deep neural network architecture, which is capable of reconstructing self-obstructed human-like morphing shapes from a depth frame in conjunction with cameras intrinsic parameters. The tests were performed using on custom dataset generated using a combination of AMASS and MoVi datasets. The proposed network achieved Jaccards’ Index of 0.7907 for the first tier, which is used to extract region of interest from the point cloud. The second tier of the network has achieved Earth Mover’s distance of 0.0256 and Chamfer distance of 0.276, indicating good experimental results. Further, subjective reconstruction results inspection shows strong predictive capabilities of the network, with the solution being able to reconstruct limb positions from very few object details.

Motivational-imagery component of the meaning of some verbal phraseological units with the abstract substantive ‘thought’ in the modern Russian language

This research is dedicated to the analysis of some verbal phraseological units, in which an object is expressed by the abstract substantive 'thought', from the perspective of motivational-imagery component. The article presents the results of study of the motivational-imagery component in the semantics of a number of verbal phraseological units with the abstract name 'thought', which is based on linguoculturological method developed by V. N. Telia and her supporters and presented in the “Large Phraseological Dictionary of the Russian Language”. The author explores the phraseological units within the framework of Chinese linguoculture for more determining the characteristics the Russian units. For this analysis, the author filtered out the phraseological units contained in the Russian National Corpus (https://ruscorpora.ru/new/), which include the abstract noun ‘thought’ that performs the function of the object of action, and the verbs “come / reach / run into / lead / point. The following conclusions were formulated: 1) the considered phraseological units reflect the metaphorical understanding of thought as a static object that outside the human body, the move towards which is performed by an individual, especially active is in relation to thought; 2) all phraseological units analyzed in the article demonstrate that thought is described as an intellectual product acquired by a human either through targeted mental activity, or influenced by external circumstances; 3) in general, the phraseological units under review act as a stereotypical representation on thought process of a person under the influence of certain external or internal factors.

Moving Object Segmentation Using Level Set Algorithm with GWO-KFCM Clustering

Video analytics is widely used to automatically analyze the videos to extract the required information and detect the various events object identification and traffic analysis. The segmentation of the image is referring to extracting the required region from an image. The major objective of the segmentation process is to cluster the images without being affected by the noises. The detection of the moving objects is a challenging task in video analysis due to the dynamic background of the video. The major drawback of the existing Kernel Fuzzy C-Means (KFCM) clustering is initialization of random centroids which increases the execution time to identify the segmented portions. In this research, the Grey Wolf Optimization (GWO) algorithm used to initialize the centroids of required clusters in KFCM and Level Set (LS) Algorithm is used to segment the objects in video sequence. The proposed KFCM-GWO-LS is implemented for moving and static object detection in the videos obtained from SBM-RGBD dataset. For object detection, determining central clusters are important which is performed by using KFCM. GWO helps in finding the best centroids clusters by matching with KFCM. The centroids clusters are segmented by using LS algorithm which undergoes over segmentation problem that is overcome by GWO. As all the three techniques are dependent on one another hybrid of all these techniques obtains better results. The proposed KFCM-GWO-LS is evaluated in terms of Recall, Specificity, Precision and F-measure and the experimental results showed that the proposed method improved the system performance from 0.3 % to 14.35 % compared to existing methods Multi-Sensor Scheduler Algorithm and Statistical Inference Theory model.

Structure of the compact astrophysical objects in the conformally-unimodular metric

A spherically symmetric solution for a gravitational field is considered in the conformally-unimodular metric. The reason for the study of this particular gauge (i. e., conformally-unimodular metric) is its relation to the vacuum energy problem. That aim connects it to other physical phenomena (including black holes), and one could argue that they should be considered in this particular class of metrics. As the vacuum solutions, so the incompressible liquid ones are investigated. In the last case, the nonsingular «eicheon» appears as a non-point compact static object that possessed different masses and structures. Such objects are a final product of the stellar collapse, with the masses exceeding the Tolman – Oppenheimer – Volkoff limit. The term «eicheon» refers to the fundamental G. Weyl’s paper «Gravitation und Elektrizität», published, in particular in the book «Das Relativitätsprinzip. Eine Sammlung von Originalarbeiten zur Relativitätstheorie Einsteins» (Berlin, 2018), where he introduced the concept of gauge invariance (German Eichtheorie) firstly in its relation to the unified field theory. Using this term to describe the compact nonsingular astrophysical objects emphasizes the decisive role of the gauge fixing by the unimodular metric. Besides, the connotation with Eichel (acorn) stresses the twofold internal structure of an object: as a point-like in the unimodular metric and a surface in the Schwarzschild one. The radial geodesic lines are investigated in the conformally-unimodular metric, as well.