Part-whole Relations Research Articles

Journalistic translation: A gate at which journalism studies and translation studies meet

This theoretical article focuses on a part-whole relationship between journalistic translation (or news translation) and the overall process of news gatekeeping within and outside of the boundaries of media organizations. The article argues for understanding the part (i.e., journalistic translation) in light of the whole (i.e., news gatekeeping) and the whole in light of the part. In this regard, it approaches journalistic translation in terms of its relationships with other news gatekeeping operations (e.g., information selection and editing) and factors that control the whole process of news gatekeeping (e.g., organizational and social constraints); besides, it touches on the relevance of the inclusion of the concept of translation in theorizing about news gatekeeping and the potential of the findings of research on translation in news production settings to contribute to news gatekeeping scholarship.

Object-oriented marketing theory

Assemblage and actor-network theories explain how markets and consumption are constituted by heterogeneous resources that form part-whole relations at various scales. Marketing and consumer research studies that use these theories, however, often retain human-centred scales and units of analysis, such that objects and forces that exist at unfamiliar (time)scales are overlooked. This paper explains how Object-Oriented Ontology can help to guide ontological, methodological, and analytical considerations in studies of market and consumption assemblages. We offer a framework that helps researchers to consider how far researchers should unpack assemblages into component parts; to what extent studies should trace objects’ effects as part of wider contexts; how ‘objects’ may harbour qualities that are withdrawn from social contexts; and how these hidden features can be encountered through speculative methods. Finally, we critically discuss the place of objects and subjects in socio-material research.

Mathematical connections made during investigative tasks in statistics and probability

<span>The Philippines has undergone a fundamental overhaul of its educational system to highlight basic education and overcome its deficiencies. The educational reform prompts prospective teachers to connect the concepts taught to instill a more profound understanding. As such, the researchers explored the mathematical connections made by prospective secondary mathematics teachers while completing investigative tasks. The study employed a concurrent triangulation mixed-methods design. Data were gathered from 39 prospective secondary mathematics teachers enrolled in the state universities' flagship campuses in Northeastern Philippines. Data were gathered using mathematical connections evaluation, think-aloud strategy, and interviews. Frequency counts, percentages, mean percent scores, Pearson product-moment correlation coefficient, and analysis of the interviews' transcriptions were employed in the study. Results showed that the prospective teachers performed best in making instruction-oriented connections but have difficulty in making implications connection. Also, the prospective teachers' ability to successfully make the mathematical connection is directly linked to their knowledge of the concept, the algorithm, and the part-whole relationship. As such, reform efforts should be made to enhance mathematical connections, emphasizing statistical thinking, and reasoning. Moreover, higher education institutions should incorporate connecting as one of the intended learning outcomes for prospective mathematics teachers.</span>

Consensus and Scientific Classification

Consensus about a classification is defined as agreement on a set of classes (concepts or categories) and their relations (such as generic relations and whole-part relations) for us in forming beliefs. While most research on scientific consensus has focused on consensus about a belief as a mark of truth, we highlight the importance of consensus in justifying shared classificatory language. What sort of consensus, if any, is the best basis for communicating and reasoning with scientific classifications? We describe an often-overlooked coordinative role for consensus that leverage agreement on how to disagree such that actors involved can still achieve one or more shared aims even when they do not agree on shared beliefs or categories. Looking forward, we suggest that investigating structures and methods for coordinative consensus provides an important new direction for research on the epistemic foundations of knowledge organization.

Emotion Recognition with Capsule Neural Network

For human-machine communication to be as effective as human-to-human communication, research on speech emotion recognition is essential. Among the models and the classifiers used to recognize emotions, neural networks appear to be promising due to the network’s ability to learn and the diversity in configuration. Following the convolutional neural network, a capsule neural network (CapsNet) with inputs and outputs that are not scalar quantities but vectors allows the network to determine the part-whole relationships that are specific 6 for an object. This paper performs speech emotion recognition based on CapsNet. The corpora for speech emotion recognition have been augmented by adding white noise and changing voices. The feature parameters of the recognition system input are mel spectrum images along with the characteristics of the sound source, vocal tract and prosody. For the German emotional corpus EMO-DB, the average accuracy score for 4 emotions, neutral, boredom, anger and happiness, is 99.69%. For Vietnamese emotional corpus BKEmo, this score is 94.23% for 4 emotions, neutral, sadness, anger and happiness. The accuracy score is highest when combining all the above feature parameters, and this score increases significantly when combining mel spectrum images with the features directly related to the fundamental frequency.

Parts and Wholes in Scene Processing.

During natural vision, our brains are constantly exposed to complex, but regularly structured, environments. Real-world scenes are defined by typical part-whole relationships, where the meaning of the whole scene emerges from configurations of localized information present in individual parts of the scene. Such typical part-whole relationships suggest that information from individual scene parts is not processed independently, but that there are mutual influences between the parts and the whole during scene analysis. Here, we review recent research that used a straightforward, but effective approach to study such mutual influences: By dissecting scenes into multiple arbitrary pieces, these studies provide new insights into how the processing of whole scenes is shaped by their constituent parts and, conversely, how the processing of individual parts is determined by their role within the whole scene. We highlight three facets of this research: First, we discuss studies demonstrating that the spatial configuration of multiple scene parts has a profound impact on the neural processing of the whole scene. Second, we review work showing that cortical responses to individual scene parts are shaped by the context in which these parts typically appear within the environment. Third, we discuss studies demonstrating that missing scene parts are interpolated from the surrounding scene context. Bridging these findings, we argue that efficient scene processing relies on an active use of the scene's part-whole structure, where the visual brain matches scene inputs with internal models of what the world should look like.

Integrating qualitative and quantitative methods to develop a comprehensive coding manual: Measuring attention to mathematics in play contexts

This coding manual was created to quantify and characterize the ways in which parents and their preschool children attend to mathematical features during play. We operationalized attention to mathematical features as instances during which parents or children made verbal references to quantitative (i.e., number, quantity, part-whole relations) or spatial (e.g., size, shape, spatial location, positional orientation) features. Through analysis of videotapes and transcripts of parent-child play sessions, we coded these verbal communications as questions, responses, mentions, or repetitions; and coded corresponding nonverbal support as either explicit, implicit, or irrelevant to the mathematical features coded. Analyses of independent coding by two coders indicated that we reliably coded instances of attending to mathematical features and the ways in which dyads talked about these features. Codes for nonverbal behaviors were less reliable and may require further development to improve reliability. The reliability analyses on verbal communication also illustrated the Kappa paradox—in our case, the high proportion of feature mentions led to a low value of Cohen's Kappa even when the percent agreement and Gwet's Agreement Coefficient 1 were high. The coding scheme served as a framework for our recent report on the frequency of parents' and children's attention to mathematical features and the association between parents' and children's attention to these features (Chan et al., 2020). This coding manual leverages the benefits of a mixed-methods approach by coding qualitative observations for quantitative analysis, and may provide other researchers with a framework for coding attention to mathematical features in a play context and developing manuals for analyzing other aspects of parent-child interaction. • This mixed-methods coding scheme quantitizes qualitative parent-child interaction. • Utterance-coding reliably quantified dyads’ frequency of attention to math features. • Utterances were reliably coded as questions, responses, mentions, or repetitions. • Actions were also coded but require further development to improve reliability. • Comparison of three inter-rater reliability measures add findings to Kappa paradox.

Aux limites de l’explication : le rôle de la sympathie chez Galien

AbstractThis paper aims to assess the epistemological value of the notion of sympathy in Galen’s thought. It first shows that Galen makes use of two different concepts of sympathy: the ambient concept, according to which the human body manifests a harmonious part-whole relationship, and the technical concept, with which one connects two pathologies on the basis of the fact that the cause of the ailment is elsewhere than where it surfaces. Neither of these sympathies constitutes in itself a causal explanation of reality. The first merely acknowledges an obvious interrelationship, the second acts as an epistemic tool to shift the focus of diagnosis away from the place where the condition manifests itself. However, the two concepts are not absolutely unrelated; and they come together when the sympathetic paradigm is used to understand the unifying action of the psychic and natural faculties. Very significantly, Galen then provisionally defines the cause as a power or faculty (δύναμις) not out of theoretical necessity but for practical reasons.

Bits and pieces: understanding information decomposition from part-whole relationships and formal logic.

Partial information decomposition (PID) seeks to decompose the multivariate mutual information that a set of source variables contains about a target variable into basic pieces, the so-called ‘atoms of information’. Each atom describes a distinct way in which the sources may contain information about the target. For instance, some information may be contained uniquely in a particular source, some information may be shared by multiple sources and some information may only become accessible synergistically if multiple sources are combined. In this paper, we show that the entire theory of PID can be derived, firstly, from considerations of part-whole relationships between information atoms and mutual information terms, and secondly, based on a hierarchy of logical constraints describing how a given information atom can be accessed. In this way, the idea of a PID is developed on the basis of two of the most elementary relationships in nature: the part-whole relationship and the relation of logical implication. This unifying perspective provides insights into pressing questions in the field such as the possibility of constructing a PID based on concepts other than redundant information in the general n-sources case. Additionally, it admits of a particularly accessible exposition of PID theory.

Hierarchical Graph Capsule Network

Graph Neural Networks (GNNs) draw their strength from explicitly modeling the topological information of structured data. However, existing GNNs suffer from limited capability in capturing the hierarchical graph representation which plays an important role in graph classification. In this paper, we innovatively propose hierarchical graph capsule network (HGCN) that can jointly learn node embeddings and extract graph hierarchies. Specifically, disentangled graph capsules are established by identifying heterogeneous factors underlying each node, such that their instantiation parameters represent different properties of the same entity. To learn the hierarchical representation, HGCN characterizes the part-whole relationship between lower-level capsules (part) and higher-level capsules (whole) by explicitly considering the structure information among the parts. Experimental studies demonstrate the effectiveness of HGCN and the contribution of each component. Code: https://github.com/uta-smile/HGCN

A Study on the Comparison of Geometrical-Mechanical Intelligence Games Activities that are Conducted with Concrete Materials and in Computer Environment

In this study it was aimed to determine the effect of geometrical-mechanical intelligence games activities that are conducted with concrete materials and in computer environment on the spatial visualization and mental rotation skills of prospective teachers and to examine the opinions of prospective teachers about the activities. The research was conducted with mixed-method research. The study group consists of 49 prospective teachers. The obtained quantitative data were collected with “Differential Aptitude Test” and “Mental Rotation Test” and qualitative data were collected with “Open-Ended Questionnaire”. In the analysis of obtained quantitative data, paired samples t-test and one-way analysis of covariance were used and in the analysis of qualitative data, content analysis was used. According to the findings in the research, it was determined that the activities that are conducted both with concrete materials and in computer environment significantly increased the spatial visualization and mental rotation skills of prospective teachers. In addition to this, it was determined that there was not a difference between the increases in the spatial visualization and mental rotation skills of prospective teachers after the activities were conducted. Furthermore, prospective teachers stated that they had fun while performing the activities, the activities developed their visual/spatial intelligence, three-dimensional thinking and establishing a part-whole relationship, increased their attention and concentration and thought and decided faster and more accurate in the second time they were answering the spatial ability tests.

Fault Classification for On-board Equipment of High-speed Railway Based on Attention Capsule Network

The conventional troubleshooting methods for high-speed railway on-board equipment, with over-reliance on personnel experience, is characterized by one-sidedness and low efficiency. In the process of high-speed train operation, numerous text-based on-board logs are recorded by on-board computers. Machine learning methods can help technicians make a correct judgment of fault types using the on-board log reasonably. Therefore, a fault classification model of on-board equipment based on attention capsule networks is proposed. This paper presents an empirical exploration of the application of a capsule network with dynamic routing in fault classification. A capsule network can encode the internal spatial part-whole relationship between various entities to identify the fault types. As the importance of each word in the on-board log and the dependencies between them have a significant impact on fault classification, an attention mechanism is incorporated into the capsule network to distill important information. Considering the imbalanced distribution of normal data and fault data in the on-board log, the focal loss function is introduced into the model to adjust the imbalanced data. The experiments are conducted on the on-board log of a railway bureau and compared with other baseline models. The experimental results demonstrate that our model outperforms the compared baseline methods, proving the superiority and competitiveness of our model.

What is to be learnt? Critical aspects of elementary arithmetic skills

In this paper, we present a way of describing variation in young children’s learning of elementary arithmetic within the number range 1–10. Our aim is to reveal what is to be learnt and how it might be learnt by means of discerning particular aspects of numbers. The Variation theory of learning informs the analysis of 2184 observations of 4- to 7-year-olds solving arithmetic tasks, placing the focus on what constitutes the ways of experiencing numbers that were observed among these children. The aspects found to be necessary to discern in order to develop powerful arithmetic skills were as follows: modes of number representations, ordinality, cardinality, and part-whole relation (the latter has four subcategories: differentiating parts and whole, decomposing numbers, commutativity, and inverse relationship between addition and subtraction). In the paper, we discuss particularly how the discernment of the aspects opens up for more powerful ways of perceiving numbers. Our way of describing arithmetic skills, in terms of discerned aspects of numbers, makes it possible to explain why children cannot use certain strategies and how they learn to solve tasks they could not previously solve, which has significant implications for the teaching of elementary arithmetic.

Genitive Alternations of the One’s Own Possessive Construction

Possessive constructions have received considerable attention from researchers who have concentrated exclusively on genitive alternations. This paper aims to introduce a new type of possessive construction, the one’s own construction, focusing, inter alia, on quantitative and statistical analyses of its genitive alternation, as there is still no research in this area. This new type of possessive construction also shows a genitive alternation of the s-genitive own and the of-genitive own, similar to that of regular possessive constructions. The study intends to identify the crucial factors that determine the use of these two alternative genitive forms. Following the conventional wisdom, the study adopts as variables four semantic factors-animacy, abstractness, alienability, and part-whole, and distinguishes the differences among the types. The results show that (1) the more animate the referent of a possessum is, the more likely it is to occur in the of-genitive own construction; (2) the abstract possessum appears more frequently as an s-genitive own construction; (3) the more inalienable the relationship is, the more likely it is to be realized as an of-genitive own construction; and (4) the s-genitive own shows a much stronger part-whole relationship than the of-genitive own construction. These findings prove statistically significant. Focusing on these results, this study concludes that the syntactic distribution of the of-genitive own type is determined by the semantic or pragmatic features, ultimately identifying a distinctive grammatical feature: specifically, the of-genitive own type is a grammatical construction of its own to denote the stronger degree of close possession established between animate entities.

Mereological themes in cuneiform worldmaking

ABSTRACT Taking as a point of departure Nelson Goodman’s idea that it is the frames of reference and the descriptions that refer within those frames that make for ways of worldmaking, this paper considers descriptions of the world attested in Akkadian cuneiform texts as a way to approach the Babylonia literati’s notion of ‘world.’ In this corpus, descriptions of world-parts display mereological themes of complementarity, correspondence, and the relation of counterparts. Meronyms, or names for parts of the one whole (we would say ‘world,’ or ‘universe’), and the part-whole relationships they indicate, are of importance to this inquiry into worldmaking.

A Research on the relationship between problem-solving appraisal, attention, and visuospatial skills of first-year architecture students

The first-year students in architectural education must deal with design exercises and studio processes that involve problems they have not encountered before. It is essential to understand the intellectual and cognitive personal resources students use to deal with the unique problems and issues of the first year. Attention and their appraisal of their own problem-solving skills can be presented as one of the primary personal resources. These resources should be considered in terms of student-centered and personalized, healthy, and sustainable learning. This dimension of learning is of great importance, especially in the emergency distance education process due to the COVID-19 pandemic. The objective of the study is to investigate the relationship between problem-solving appraisal, attention, and visuospatial skills of first-year architecture students. The research is an experimental study. Neuropsychological assessment tools and scales were used. There are Turkish standardization studies for these neuropsychological assessment tools. These tools have norm values on a healthy sample, which were benefited as control group scores. For visuospatial skills, Raven Standard Progressive Matrices test and Benton Judgment of Line Orientation test;for attention, STROOP test TBAG version were administrated. Problem-Solving Appraisal Inventory were given to record the students' their own validation and assessment on their own problem-solving skills. Participants were volunteer first-year architecture students, who complied with the inclusion criteria. The sample was composed of 40 (26, %65.0, female, 14, %35.0, male) students. Age range was 18-22. It was observed that the students participating in the study evaluated their own problem-solving skills positively. It was found that female participants evaluated their problem-solving skills as more advanced regarding to planfulness factor, whereas for male students it was the self-confidence factor. The neuropsychological test performances of the participants who evaluate their own problem-solving skills negatively were lower. Findings suggest that participants whose problem-solving skills are incompatible with the age group need improvement in decision-making, action, part-whole relationship, visual motor speed, and resistance to confounders or distractors. It was concluded that students who evaluated themselves as better problem solvers in evaluative approach, self-confidence and planfulness dimensions performed better in visuospatial assessment. Architectural education raises issues and challenges which might be quite problematic for the first-year students. Students are expected to gain knowledge, skills, and competence in a new field. Design exercise itself is either undefined or ill-defined. Focusing mainly on the non-working, inconsistent, or missed opportunities instead of positive aspects of the design proposal initiates new challenges that the students must encounter. Students are expected to formulate and manage their problem-solving challenge, which is mostly supported with negative feedbacks and criticism. It is possible to claim that the academic performance of a person who is made to feel worthless by reinforcing their negative judgments about their own skills and competencies decreases. Creativity and innovation, critical thinking, problem solving, decision making, learning to learn, metacognitive awareness, communication and collaboration are the 21st century skills which are the key skills preparing the societies and individual to the future. The COVID-19 pandemic and the measures taken to combat the epidemic, especially emergency distance education, have reminded the vital importance of the skills mentioned above. The skills emerge and develop individually on the basis of personal resources and individual's social context. The idea that these skills can be improved by means of architectural design education is not a defensible claim within the scientific framework of learning and development. Studies in the areas of learning and development recommend the understanding, evaluation and appraisal of the student's own personal intellectual and cognitive resources. The design exercise proceeds through processes similar to solving real life problems. The studio environment can be defined as a social learning environment based on problem solving. How first year architecture students appraise their own problem-solving skills has not been studied sufficiently. The benefits of these research can be listed as follows: Students' individual differences can be revealed. Changes in their academic performance can be observed. Students' attitudes towards feedback can be explained. The relationship between students' attitudes towards their own skills and competencies and their academic performance can be observed and studies can be carried out to improve performance. The findings of these and similar studies show that individuals' metacognitive awareness, self-efficacy perceptions of their knowledge, skills and competencies and their self-control over them are the keys to intellectual and academic development.

Residual Vector Capsule: Improving Capsule by Pose Attention

The convolutional neural network has significantly improved the accuracy of image recognition; however, it performs in a fragile manner when we apply viewpoint transformation or add noise to the image. Recent studies have proposed new neural networks named capsule. Capsule build the part-whole relationship in the entity through instantiation parameters, and they cluster instantiation parameters layer by layer through routing-by-agreement; therefore, capsule has stronger representational ability and robustness than convolutional neural networks. However, the routing-by-agreement of the capsule network is limited by the prior probability assumption, which performs in an unstable way in recognition accuracy and robustness. To remove the restriction of the prior probability assumption in the routing-by-agreement, we propose a new capsule named the residual vector capsule (RVC), which constructs the routing-by-agreement with self-attention. The experimental results show that compared with other capsule networks, RVC achieves competitive classification accuracy on MNIST, Fashion-MNIST, CIFAR-10 and SVHN, improves the viewpoint invariance of the model on SmallNorb, and significantly improves the robustness of the model against white box attacks on CIFAR-10 and SVHN.

CapsField: Light Field-Based Face and Expression Recognition in the Wild Using Capsule Routing.

Light field (LF) cameras provide rich spatio-angular visual representations by sensing the visual scene from multiple perspectives and have recently emerged as a promising technology to boost the performance of human-machine systems such as biometrics and affective computing. Despite the significant success of LF representation for constrained facial image analysis, this technology has never been used for face and expression recognition in the wild. In this context, this paper proposes a new deep face and expression recognition solution, called CapsField, based on a convolutional neural network and an additional capsule network that utilizes dynamic routing to learn hierarchical relations between capsules. CapsField extracts the spatial features from facial images and learns the angular part-whole relations for a selected set of 2D sub-aperture images rendered from each LF image. To analyze the performance of the proposed solution in the wild, the first in the wild LF face dataset, along with a new complementary constrained face dataset captured from the same subjects recorded earlier have been captured and are made available. A subset of the in the wild dataset contains facial images with different expressions, annotated for usage in the context of face expression recognition tests. An extensive performance assessment study using the new datasets has been conducted for the proposed and relevant prior solutions, showing that the CapsField proposed solution achieves superior performance for both face and expression recognition tasks when compared to the state-of-the-art.

Mathematics is Ontology? A Critique of Badiou's Ontological Framing of Set Theory

This article develops a criticism of Alain Badiou’s assertion that “mathematics is ontology.” I argue that despite appearances to the contrary, Badiou’s case for bringing set theory and ontology together is problematic. To arrive at this judgment, I explore how a case for the identification of mathematics and ontology could work. In short, ontology would have to be characterised to make it evident that set theory can contribute to it fundamentally. This is indeed how Badiou proceeds in Being and Event. I review his descriptions of the ontological problematic at some length here, only to argue that set theory is a poor fit. Although philosophers working on questions of being were certainly occupied with matters of oneness and the part-whole relationship, I argue that Badiou’s discussion of philosophical sources points towards a mereological treatment, not a set-theoretic one. Finally, I suggest that Badiou’s philosophical interpretations of key set-theoretic results are better understood as some sort of analogising between mathematics, ontology, and philosophical anthropology.

Ein holistischer Design-Based Research-Modellentwurf für die Hochschuldidaktik

Der Beitrag beschreibt und begründet ein holistisvches DBR-Modell für die Hochschuldidaktik, das in fünf Schritten entfaltet wird: Ich bestimme in einem ersten Schritt fünf semantische Felder, welche den Bedeutungsumfang eines DBR-Zyklus abstecken. Ich bezeichne diese bewusst nicht als Phasen oder Prozesse, weil es hier primär um die Bedeutungen des Handelns in DBR geht, die das Wesen von DBR als Ganzes prägen. In einem zweiten Schritt definiere ich darauf aufbauend fünf Handlungsfelder, in die sich Aktivitätsschwerpunkte projizieren lassen. Der Begriff des Handlungsfelds soll verdeutlichen, dass es hier um konkrete Aktivitäten geht, die immer nur ein Teil vom Ganzen sein können, weil jedes Handeln eine gewisse Fokussierung der Aufmerksamkeit braucht. Ich schlage in einem dritten Schritt Spielfelder vor: Diese metaphorisch bezeichnete Brücke zwischen dem Handlungsfokus (als Teil) und dem Wesenskern (als Ganzem) von DBR eignet sich dazu, die vor allem Experten sich eröffnenden Handlungsspielräume zu beleuchten. Diese drei Schritte bilden zusammen den Argumentationsgang für die Beschreibung und Begründung des holistischen DBR-Modellentwurfs. In einem vierten Schritt gehe ich auf die Methodenfrage in DBR ein und prüfe, inwiefern das Modell dazu geeignet ist, typische Schwierigkeiten im Umgang mit Methoden in DBR konstruktiv aufzufangen. Die Rolle von Design-Gegenständen in DBR greife ich in einem fünften und letzten Schritt auf und gehe wiederum der Frage nach, welchen Mehrwert das holistische Modell hierfür haben kann. Der Beitrag endet mit einem zusammenfasenden Fazit.