Problem Of Representation Research Articles

Too Close to Nature: On the Representational Problems of Death Masks and Life Casts

Abstract While historians of art have found death masks and life casts conceptually problematic, it is also noteworthy that these objects have received scant attention from philosophers of art. In this paper, I begin to redress this omission by offering examples of how the philosophy of art can help us understand these images. Two problems stand out: the problem of representation, for example, what type of representation a death mask is; and the problem of style and historicity, for example, whether images imprinted from nature can indicate styles, and whether these images can evolve and transform along art-historical lines. After considering these problems, I conclude that these images are constrained in what they can and cannot represent. While there is a long tradition of imprinting from nature, this practice shows little discernible change over time. An unchanging tradition cannot claim to exhibit a history, a least in a narrative sense familiar to art history. The following investigation opens a dialog between Arthur Danto’s philosophy of art and practitioners of theoretical art history, including Ernst Gombrich and Georges Didi-Huberman, both of whom offer differing views on how these images can be treated.

Creative programming in architecture: a computational thinking approach

The creative programming language Processing can be used as a generative architectural design tool, which allows the designer to write design instructions (algorithms) and compute them, obtaining graphical outputs of great interest. This contribution addresses the inclusion of this language in the architecture curriculum, within the context of digital culture and alternative approaches to how digital tools are used and learned. It studies the different processes related to Computational Thinking that are triggered in the prototyping of computer applications and that lead to creativity. The similarity between architectural design and programming is analysed, both in problem solving (abstraction, decomposition, iterative revisions -debugging-, etc.) and in the use of mechanisms of a digital nature (loops, randomness, etc.). The results of the design and testing of a pilot course are shown, in which the way of teaching, learning and using this programming language is based on the graphical representation of problems through sketches.

Gym-flp: A Python Package for Training Reinforcement Learning Algorithms on Facility Layout Problems

Reinforcement learning (RL) algorithms have proven to be useful tools for combinatorial optimisation. However, they are still underutilised in facility layout problems (FLPs). At the same time, RL research relies on standardised benchmarks such as the Arcade Learning Environment. To address these issues, we present an open-source Python package (gym-flp) that utilises the OpenAI Gym toolkit, specifically designed for developing and comparing RL algorithms. The package offers one discrete and three continuous problem representation environments with customisable state and action spaces. In addition, the package provides 138 discrete and 61 continuous problems commonly used in FLP literature and supports submitting custom problem sets. The user can choose between numerical and visual output of observations, depending on the RL approach being used. The package aims to facilitate experimentation with different algorithms in a reproducible manner and advance RL use in factory planning.

Review Essay

Scott Cook, Exploring Commodities. An Anthropologist on the Trails of Malinowski and Traven in Mexico. Oxford: Peter Lang, pp. 246. 2021. Stephen Gudeman, Enlightening Encounters. The Journeys of an Anthropologist. New York: Berghahn, pp. 144. 2022. Keith Hart, Self in the World. Connecting Life's Extremes. New York: Berghahn, pp. 314. 2022.

Markers of social status in Polish printers' signatures (1501-1545)

The article raises the problem of status representation in the signatures of book printers of the Kingdom of Poland. First of all, the study concerns the identified features in the publications of I. Vietor and J. Haller; to a lesser extent - S. Giber, K. Hochfeder, F. Ungler and M. Scharfenberg. Although the publisher's signature form did not undergo significant changes during the 1st half of the 16th century, we find specific markers of social status among the listed printers. These markers are not characteristic of previous and subsequent Polish book publishers, but are characteristic, firstly, of a certain circle of printers outside the Kingdom of Poland, and secondly, of the social environment that existed at that time, in which certain epithets conveyed information about a person’s place in the hierarchy. The focus on the readership demand of intellectuals and connections with the University of Krakow were also reflected in the publishing signatures: printers classified their activities in the field of sciences and arts ("ars"), and also presented themselves in terms accepted in the scientific community ("egregius vir", "spectabilis vir dominus"). This part of the self-representation of entrepreneurs once again testifies to their involvement in the structure of European humanist printers, who, like their Polish colleagues, sought to declare in their signatures their connections with the scientific community and Renaissance culture. At the same time, the appearance of the epithets identified in the structure of the publisher's signature has not only a linguistic connection, but also a chronological one: the concepts under study disappear in the middle of the 16th century from Polish publications and is reduced to a minimum in publications of other European lands.

Slow Violence and the California Central Valley Prison in Rachel Kushner’s The Mars Room

Abstract: This essay interrogates the carceral geography of the California Central Valley by examining Rachel Kushner’s novel The Mars Room (2018), which unfolds the life and limiting circumstances of a woman serving two life sentences. With capitalism as the driving force and background of this novel, this article examines the problem of representation posed by the prison in American society. Does the novel allow for a sharper perception of the loss wrought by the carceral state? I argue that Kushner uses the novel form to represent the slow violence of incarceration, which is a biopolitical project of the United States.

Arte, laboratorio y corpo-subversión: reseña de un libro fundamental de Miroslava Salcido


 
 
 The book reviewed is an investigation about the interstitial zone between performance and philosophy. It is a work that explores action art as a practice that fundamentally attempts to challenge the dominant discourses of the time through a corporeal-thinking and subversive manifesto. One of the author’s objectives is to think about the problems of representation and, from a philosophy of the body, to reflect on the scenic fact and the possibilities of the appearance of the “event”. 
 
 

A dynamic fuzzy rule-based inference system using fuzzy inference with semantic reasoning

The challenge of making flexible, standard, and early medical diagnoses is significant. However, some limitations are not fully overcome. First, the diagnosis rules established by medical experts or learned from a trained dataset prove static and too general. It leads to decisions that lack adaptive flexibility when finding new circumstances. Secondly, medical terminological interoperability is highly critical. It increases realism and medical progress and avoids isolated systems and the difficulty of data exchange, analysis, and interpretation. Third, criteria for diagnosis are often heterogeneous and changeable. It includes symptoms, patient history, demographic, treatment, genetics, biochemistry, and imaging. Symptoms represent a high-impact indicator for early detection. It is important that we deal with these symptoms differently, which have a great relationship with semantics, vary widely, and have linguistic information. This negatively affects early diagnosis decision-making. Depending on the circumstances, the diagnosis is made solo on imaging and some medical tests. In this case, although the accuracy of the diagnosis is very high, can these decisions be considered an early diagnosis or prove the condition is deteriorating? Our contribution in this paper is to present a real medical diagnostic system based on semantics, fuzzy, and dynamic decision rules. We attempt to integrate ontology semantics reasoning and fuzzy inference. It promotes fuzzy reasoning and handles knowledge representation problems. In complications and symptoms, ontological semantic reasoning improves the process of evaluating rules in terms of interpretability, dynamism, and intelligence. A real-world case study, ADNI, is presented involving the field of Alzheimer’s disease (AD). The proposed system has indicated the possibility of the system to diagnose AD with an accuracy of 97.2%, 95.4%, 94.8%, 93.1%, and 96.3% for AD, LMCI, EMCI, SMC, and CN respectively.

ETHNOMATHEMATICS IN CACI DANCE OF MANGGARAI COMMUNITY AND ITS INTEGRATION IN MATHEMATICS LEARNING

Purpose: The purpose of this research is to describe the history and philosophy of the Caci Dance and describe the ethnomathematics contained in the Caci dance and develop learning tools for some of the mathematical concepts found. Theoretical reference: Ethnomathematics explores the relationship between mathematics and the diversity of human cultures, exploring the ways in which different groups of people use, understand and develop mathematical concepts in the context of their daily lives (Orey, 2011). It is important to understand that mathematics is not only an objective universal entity, but can also be influenced by the cultural context in which it develops (Bishop, 1988). Ethnomathematics seeks to overcome the traditional view of mathematics, which is often understood as a science that is neutral and separate from everyday life (François, 2010). One of the main aspects of ethnomathematics is the exploration of how different cultural groups develop systems of counting, number representation and mathematical problem solving in the context of their everyday lives (Rosa & Shirley, 2016). By understanding how to think about mathematics in a cultural context, ethnomathematics can provide deeper insights into the wealth of mathematical knowledge held by different communities (Stathopoulou et al., 2015). Teachers can use examples from students' culture to explain mathematical concepts, thus making learning more meaningful and relevant. This not only improves students' understanding of math but also helps them see the value and relevance of math in their daily lives (Polman et al., 2021). As technology and globalization evolve, ethnomathematics can also help in addressing the challenge of mathematical diversification (Orey, 2021). Many communities in the world have traditional mathematical systems that are rich in local knowledge and wisdom (Abas et al., 2022). Ethnomathematics provides a platform to document, value and preserve this knowledge from extinction. This approach is inspired by the belief that mathematics is not only universal, but can also be understood and taught through the lens of different cultures (Brandt & Chernoff, 2014). By incorporating cultural elements into mathematics learning, students can more easily relate mathematical concepts to their daily life experiences, thus making learning more meaningful and relevant (Acharya et al., 2021). Method:This research is a qualitative study using an ethnographic approach with four research subjects. The research instruments were interviews, observations and documentation and the data were analyzed by ethnography model. Results and Conclusion: The results of this study show that there are ethno mathematical activities in Caci Dance which include counting, localizing, designing, playing, and explaining activities. These activities are in accordance with mathematical concepts, namely addition, multiplication, number patterns, arithmetic sequence, geometry, mathematical logic, relations and functions. Thus, the concepts of school mathematics found in Caci Dance can be developed by designing appropriate learning tools to be applied in school learning. Implications of research: Mathematical concepts can be explained with cultural concepts found around students. The explanation of learning concepts with this cultural approach is better known as ethnomathematics. This approach emphasizes student culture-based learning related to mathematics. This can help teachers and students in understanding a certain concept that is considered difficult. In addition, students can easily understand the material because they know the problems presented by the teacher are related to their surroundings. Ethnomathematics can be applied in schools through the preparation of teaching materials. Originality/value: The novelty of this research is the formation of an ethnomathematics model of caci dance that can be integrated in mathematics learning in schools so that it can provide input for decision makers, in this case teachers and government or education observers to be more pro-active in implementing learning that is in accordance with the culture around students.

Uncovering the interplay between drawings, mental representations, and arithmetic problem-solving strategies in children and adults.

There is an ongoing debate in the scientific community regarding the nature and role of the mental representations involved in solving arithmetic word problems. In this study, we took a closer look at the interplay between mental representations, drawing production, and strategy choice. We used dual-strategy isomorphic word problems sharing the same mathematical structure, but differing in the entities they mentioned in their problem statement. Due to the non-mathematical knowledge attached to these entities, some problems were believed to lead to a specific (cardinal) encoding compatible with one solving strategy, whereas other problems were thought to foster a different (ordinal) encoding compatible with the other solving strategy. We asked 59 children and 52 adults to solve 12 of those arithmetic word problems and to make a diagram of each problem. We hypothesized that the diagrams of both groups would display prototypical features indicating either a cardinal representation or an ordinal representation, depending on the entities mentioned in the problem statement. Joint analysis of the drawing task and the problem-solving task showed that the cardinal and ordinal features of the diagrams are linked with the hypothesized semantic properties of the problems and, crucially, with the choice of one solving strategy over another. We showed that regardless of their experience, participants' strategy use depends on their problem representation, which is influenced by the non-mathematical information in the problem statement, as revealed in their diagrams. We discuss the relevance of drawing tasks for investigating mental representations and fostering mathematical development in school.

The problem of implementing the concept of maximum integration of heterogeneous data in practical navigation

The topic of the work is the research of the problem of the practical realization of opportunistic navigation, which actually consists in the fact that the “signals of opportunity” are not optimized for global navigation according to their original purpose. A hypothesis about the possibility of strategic application of the navigation concept based on the principles of data integration with the objective existence of tactically surmountable difficulties is put forward. In the conditions of vulnerability of the global satellite system, an approach to use an additional source of combined signals in order to continuously ensure accurate geolocation of water transport vehicles is proposed. The comparative assessment confirms the comparability of the positioning error of alternative navigation with the data of classical satellite observations of mobile objects. An assumption about the effectiveness of spline modeling of the cartographic standard of informativeness for the practical organization of the basic principle of opportunistic positioning by analogy with the paradigm of correlation-extreme navigation is made. A computer visualization of a fixed fragment of the ocean gravitational field based on spline approximation is performed in order to optimize the problem of simultaneous localization and three-dimensional representation of the ship movement in a graphical environment unaffiliated with foreign software. A hybrid algorithm for mathematical synthesis of the navigational isosurface has been tested as a harmonized support for the navigation staff to implement the “terrain-referenced procedure” in the landscape coordinate space. The variants of the “ambiguity resolution” problem implementation in the issue of maximum integration of heterogeneous navigation data are considered. The probability of practical use of the opportunistic navigation postulates in marine applications, taking into account the “navigation gap” factor for leveling local satellite incapacity with a real possibility of countering malicious interception of ship control, is estimated. The expediency of using the factor of observational reckoning of the vessel path as an additional condition for navigation safety in the aspect of packet processing of the “signals of opportunity” slot is substantiated.

A Schematic Representation of the Social Problem vis-à-vis Social Impact regarding the High-Priced Orphan Drug Nusinersen

A Schematic Representation of the Social Problem vis-à-vis Social Impact regarding the High-Priced Orphan Drug Nusinersen

Data-Driven Field Representations and Measuring Processes

Natural mathematical objects for representing spatially distributed physical attributes are 3D field functions, which are prevalent in applied sciences and engineering, including areas such as fluid dynamics and computational geometry. The representations of these objects are task-oriented, which are achieved using various techniques that are suitable for specific areas. A recent breakthrough involves using flexible parameterized representations, particularly through neural networks, to model a range of field functions. This technique aims to uncover fields for computational vision tasks, such as representing light-scattering fields. Its effectiveness has led to rapid advancements, enabling the modeling of time dependence in various applications. This survey provides an informative taxonomy of the recent literature in the field of learnable field representation, as well as a comprehensive summary in the application field of visual computing. Open problems in field representation and learning are also discussed, which help shed light on future research.

A critical review of GenAI policies in higher education assessment: a call to reconsider the “originality” of students’ work

This study offers a critical examination of university policies developed to address recent challenges presented by generative AI (GenAI) to higher education assessment. Drawing on Bacchi’s ‘What’s the problem represented to be’ (WPR) framework, we analysed the GenAI policies of 20 world-leading universities to explore what are considered problems in this AI-mediated assessment landscape and how these problems are represented in policies. Although miscellaneous GenAI-related problems were mentioned in these policies (e.g. reliability of AI-generated outputs, equal access to GenAI), the primary problem represented is that students may not submit original work for assessment. In the current framing, GenAI is often viewed as a type of external assistance separate from the student’s independent efforts and intellectual contribution, thereby undermining the originality of their work. We argue that such problem representation fails to acknowledge how the rise of GenAI further complicates the process of producing original work and what it means by originality in a time when knowledge production becomes increasingly distributed, collaborative and mediated by technology. Therefore, a critical silence in higher education policies concerns the evolving notion of originality in the digital age and a more inclusive approach to address the originality of students’ work is required.

Using Student Reflections to Develop Deep Teaching

National studies continue to indicate that the graduating STEM student body is not representative of the diversity of the U.S. population. In addition to, or in the absence of, institutional change, instructors must learn how to implement equity-focused pedagogical changes in order to better support their students. This article describes my experience introducing a weekly reflection protocol in a proof-based mathematics course with the dual goals of promoting metacognition and opening an additional communication channel with my students. Towards these goals, this intervention was largely successful and I provide examples of how I was able to use what I learned from my students to better support them throughout the semester. Drawing on the “Deep Teaching Model” for faculty development, I share how this experience continues to be a critical component of my evolving teaching practice. Though this intervention on its own may not solve the representation and equity problems in our field, the self-awareness I developed through this experience has positioned me as a more effective instructor, mentor, and advocate.

The Aha! experience is associated with a drop in the perceived difficulty of the problem.

The study investigated the correlation between the intensity of the Aha! experience and participants' subjective difficulty ratings of problems before and after finding their solutions. We assumed that the Aha! experience arises from a shift in processing fluency triggered by changing from an initially incoherent problem representation to a coherent one, which ultimately leads to the retrieval of a solution with unexpected ease and speed. First, we hypothesized that higher Aha! experience ratings would indicate more sudden solutions, manifesting in a reduced correlation between the initial difficulty ratings and solution times. Second, we hypothesized that higher Aha! experience ratings would correspond to a greater shift in the subjective difficulty ratings between the initial and retrospective assessments. To test our hypotheses, we developed a novel set of rebus puzzles. A total of 160 participants solved rebuses and provided initial (within 5 s of problem presentation) and retrospective difficulty ratings (following the generation or presentation of a correct solution). They also rated their Aha! experience (after solution generation or presentation), confidence in solutions, and the likability of each rebus. Our findings revealed that the initial ratings of the problem's subjective difficulty were positively correlated with the solution time and that this correlation decreased in the case of a stronger Aha! experience. Aha! experience ratings were positively correlated with the differences between initial and retrospective difficulty ratings, confidence, solution accuracy, and rebus likability. We interpreted our results to be in line with the processing fluency and metacognitive prediction error accounts.

Dictionary learning with cone atoms and application to anomaly detection

We propose a variant of dictionary learning (DL) for sparse representations where the atoms are cones instead of simple vectors. The most convenient vector from a cone, called actual atom, is used to build the linear sparse representation of a given signal. We present a DL algorithm suited for cone atoms, which can update the dictionary without storing all the actual atoms that are used in the representations of the training signals. Also, the algorithm ensures that the cone atoms are disjoint and thus the representation problem is well posed. We use the proposed cone DL for anomaly detection. On a specific type of anomaly, called “dependency”, the DL methods involving cone atoms are better than those from a reputed benchmark. They are also better than standard DL.

Envelopes created by circle families in the plane

In this paper, on envelopes created by circle families in the plane, all four basic problems (existence problem, representation problem, problem on the number of envelopes, problem on relationships of definitions) are solved.

Depression Detection from Social Media Text Analysis using Natural Language Processing Techniques and Hybrid Deep Learning Model

Depression is a kind of emotion that negatively impacts people's daily lives. The number of people suffering from long-term feelings is increasing every year across the globe. Depressed patients may engage in self-harm behaviors, which occasionally result in suicide. Many psychiatrists struggle to identify the presence of mental illness or negative emotion early to provide a better course of treatment before they reach a critical stage. One of the most challenging problems is detecting depression in people at the earliest possible stage. Researchers are using Natural Language Processing (NLP) techniques to analyze text content uploaded on social media, which helps to design approaches for detecting depression. This work analyses numerous prior studies that used learning techniques to identify depression. The existing methods suffer from better model representation problems to detect depression from the text with high accuracy. The present work addresses a solution to these problems by creating a new hybrid deep learning neural network design with better text representations called “Fasttext Convolution Neural Network with Long Short-Term Memory (FCL).” In addition, this work utilizes the advantage of NLP to simplify the text analysis during the model development. The FCL model comprises fasttext embedding for better text representation considering out-of-vocabulary (OOV) with semantic information, a convolution neural network (CNN) architecture to extract global information, and Long Short-Term Memory (LSTM) architecture to extract local features with dependencies. The present work was implemented on real-world datasets utilized in the literature. The proposed technique provides better results than the state-of-the-art to detect depression with high accuracy.

Light-front puzzles

Light-front formulations of quantum field theories have many advantages for computing electroweak matrix elements of strongly interacting systems and other quantities that are used to study hadronic structure. The theory can be formulated in Hamiltonian form so non-perturbative calculations of the strongly interacting initial and final states are in principle reduced to linear algebra. These states are needed for calculating parton distribution functions and other types of distribution amplitudes that are used to understand the structure of hadrons. Light-front boosts are kinematic transformations so the strongly interacting states can be computed in any frame. This is useful for computing current matrix elements involving electroweak probes where the initial and final hadronic states are in different frames related by the momentum transferred by the probe. Finally in many calculations the vacuum is trivial so the calculations can be formulated in Fock space. The advantages of light front-field theory would not be interesting if the light-front formulation was not equivalent to the covariant or canonical formulations of quantum field theory. Many of the distinguishing properties of light-front quantum field theory are difficult to reconcile with canonical or covariant formulations of quantum field theory. This paper discusses the resolution of some of the apparent inconsistencies in canonical, covariant and light-front formulations of quantum field theory. The puzzles that will be discussed are (1) the problem of inequivalent representations (2) the problem of the trivial vacuum (3) the problem of ill-posed initial value problems (4) the problem of rotational covariance (5) the problem of zero modes and (6) the problem of spontaneously broken symmetries.