Art Approaches Research Articles

Modeling Minimum Cost Network Flows With Port‐Hamiltonian Systems

AbstractWe give a short overview of advantages and drawbacks of the classical formulation of minimum cost network flow problems and solution techniques, to motivate a reformulation of classical static minimum cost network flow problems as optimal control problems constrained by port‐Hamiltonian systems (pHS). The first‐order optimality system for the port‐Hamiltonian system‐constrained optimal control problem is formally derived. Then we propose a gradient‐based algorithm to find optimal controls. The port‐Hamiltonian system formulation naturally conserves flow and supports a wide array of further modeling options as, for example, node reservoirs, flow dependent costs, leaking pipes (dissipation) and coupled sub‐networks (ports). They thus provide a versatile alternative to state‐of‐the art approaches towards dynamic network flow problems, which are often based on computationally costly time‐expanded networks. We argue that this opens the door for a plethora of modeling options and solution approaches for network flow problems.

Attitude in Motion: Constraints Aided Accurate Vehicle Orientation Tracking in Harsh Environment

Accurate vehicle orientation tracking in 3 dimensions or 3D attitude tracking, is an essential requirement for various vehicle stability and safety applications. In this paper, we consider the problem of vehicle attitude tracking along with its external acceleration estimation using low cost inertial measurement units. The current state of the art approaches are unable to estimate orientation when the body is in motion for a prolonged period, as the accelerometer measurements are corrupted by external accelerations that are produced due to body movements. In this paper, a novel filtering framework is proposed to eliminate the acceleration induced uncertainty for body observing severe and prolonged external acceleration, which is based on linear Kalman filter. We show that the sensor constraints allow the removal of external acceleration from all all of its axes. This approach is unique and superior from current state of the art as it estimates the acceleration without using any information from additional sensors such as wheel encoder, GPS, and/or camera. A unique state formulation is proposed which incorporate magnetometer to compliment accelerometer in rotation matrix frame work. Simulations and real world experimental tests are conducted to verify the performance of the proposed algorithm in various dynamic conditions.

Thinking through Environmental Sustainability of Waste Plastic Bottles: A Creative Art Approach

The study used a creative art approach to investigate solid waste such as plastic bottles and convert them into an artistic sofa as part of contributing to Ghana’s national development of the Millennium Development Goals (7th goal) to ensure environmental sustainability. The practice-based research inquiry was employed with the recycling method of assemblage and construction technique to expose this artistic outcome. Through a descriptive analysis tool, the study revealed that the practicability and viability of waste plastic bottles could be an effective way to raise awareness and promote change in the way society uses and disposes of plastic. Based on the outcome of the study, artists should collaborate with civil engineers on the production of waste plastic bottles as viable materials for construction by exploring their artistic values, strengths, and techniques.

A STEAM Experience in the Mathematics Classroom: The Role of a Science Cartoon

A multidisciplinary team collaborated on the development of a learning experience involving 10th grade students using a Science, Technology, Engineering, Arts, and Mathematics (STEAM) approach. The experience was based on the development (conception, implementation, and evaluation) of a science cartoon that aimed to highlight different scientific and technological dimensions related to the diversity of marine worms (Phylo Annelida, class Polychaeta) present in the continental shelf off the coast of Aveiro, Portugal (NE Atlantic coast). The study was implemented in a Portuguese high school in the Aveiro region, involving 24 10th grade students, emphasizing a social context close to the students’ lives. All pedagogical interventions occurred in face-to-face sessions during the 2020/21 school year and were oriented by the following research question: What is the role of science cartoons in establishing STEAM connections for solving real-world problems presented to 10th grade students? Following a qualitative and interpretative research methodology, with a design-based research focus, data were collected through a questionnaire, observations, and students’ written records. The content analysis shows that most students learned new concepts related to STEAM areas. Evaluating the impact of the science cartoon reveals that it can be considered an innovative science communication resource due to its educational potential in stimulating a STEAM approach within the students’ learning process.

3D-Sensitive Encoding of Pharmacophore Features.

In the presence of structural data, one sometimes need to compare 3D ligands. We design an overlay-free method to rank order 3D molecules in the pharmacophore feature space. The proposed encoding includes only two fittable parameters, is sparse, and is not too high dimensional. At the cost of an additional parameter, to delineate the binding site from a protein-ligand complex, the method can compare binding sites. The method was benchmarked on the LIT-PCBA data set for ligand-based virtual screening experiments and the sc-PDB and a Vertex data set when comparing binding sites. In similarity searches, the proposed method outperforms an open-source software doing optimal superposition of ligand-based pharmacophores and RDKit's 3D pharmacophore fingerprints. When comparing binding sites, the method is competitive with state of the art approaches. On a single CPU core, up to 374,000 ligand/s or 132,000 binding site/s can be rank ordered. The "AutoCorrelation of Pharmacophore Features" open-source software is released at https://github.com/tsudalab/ACP4.

Deep Neural Networks for Direction of Arrival Estimation of Multiple Targets With Sparse Prior for Line-of-Sight Scenarios

Received signal Direction of Arrival (DOA) estimation represents a significant problem with multiple applications, ranging from wireless communications to radars. This problem presents significant challenges, mainly given by a large number of closely located transmitters being difficultly separable. Currently available state of the art approaches fail in providing sufficient resolution to separate and recognize the DOA of closely located transmitters, unless using a large number of antennas and hence increasing the deployment and operation costs. In this paper, we present a deep learning framework for DOA estimation under Line-of-Sight scenarios, which able to distinguish a number of closely located sources higher than the number of receivers' antennas. We first propose a formulation that maps the received signal to a higher dimensional space that allows for better identification of signal sources. Secondly, we introduce a Deep Neural Network that learns the mapping from the receiver antenna space to the extended space to avoid relying on specific receiver antenna array structures. Thanks to our approach, we reduce the hardware complexity compared to state of the art solutions and allow reconfigurability of the receiver channels. Via extensive numerical simulations, we demonstrate the superiority of our proposed method compared to state-of-the-art deep learning-based DOA estimation methods, especially in demanding scenarios with low Signal-to-Noise Ratio and limited number of snapshots.

Implementasi Pendekatan Seni Kolase Dalam Menstimulasi Keterampilan Abad Ke-21 pada Anak Usia Dini

Developing children's 21st century skills through an arts approach is a creative and effective way to broaden horizons and experiences. Art can involve visuals, music, dance, theatre and various forms of creative expression. This study aims to analyse the collage art approach in stimulating 21st century skills at the kindergarten level. In this study using a field research method with a descriptive analysis qualitative approach. The results found in this study are 1). Visual communication skills, Collaboration, Building critical skills, Technology skills, Multidisciplinary skills, Social and emotional skills development. 2). The implications are creativity and innovation, problem solving and critical thinking, collaboration and communication, technological skills in the digital era, multidisciplinary understanding, Improved social and emotional skills. 3). The obstacles are limited resources, lack of time, lack of teacher knowledge and skills, and challenges in proper assessment.

Learning semantic ambiguities for zero-shot learning

AbstractZero-shot learning (ZSL) aims at recognizing classes for which no visual sample is available at training time. To address this issue, one can rely on a semantic description of each class. A typical ZSL model learns a mapping between the visual samples of seen classes and the corresponding semantic descriptions, in order to do the same on unseen classes at test time. State of the art approaches rely on generative models that synthesize visual features from the prototype of a class, such that a classifier can then be learned in a supervised manner. However, these approaches are usually biased towards seen classes whose visual instances are the only one that can be matched to a given class prototype. We propose a regularization method that can be applied to any conditional generative-based ZSL method, by leveraging only the semantic class prototypes. It learns to synthesize discriminative features for possible semantic description that are not available at training time, that is the unseen ones. The approach is evaluated for ZSL and GZSL on four datasets commonly used in the literature, either in inductive or transductive settings, with results on-par or above state of the art approaches. The code is available at https://github.com/hanouticelina/lsa-zsl.

The foundations of a personality-oriented approach in art pedagogy

Introduction. The article deals with the psychophysiological aspects of the personality-oriented approach in art pedagogy. A person-centered approach is a broader concept than an individual approach to learning, but the former is unthinkable without the latter.Purpose setting. The individual approach is based on differences in the motor profiles of students. Individual motor profile is a system of relations of individual motor levels in the student»s motor skills, according to the concept of N. A. Bernstein. This concept has been further elaborated in the works of modern researchers. According to this approach, human activity is a hierarchical system, at the head of which is the symbolic level, and at the base – the lower motor levels. In different individuals, the development of certain motor levels can vary significantly. Taking into account these differences should form the basis for the formation of an individual approach in art education.Methodology and methods of the study. The study uses a systematic approach. One circumstance that was not taken into account by N. A. Bernstein at the time is being investigated. According to his classical concept, the highest motor level in the hierarchy acts consciously, and the subordinate levels work outside the actual consciousness. But the motor hierarchy has the same properties as other complex hierarchies. It is capable to generate systemic inversions, as a result of which the lower motor level takes precedence in this system. This is evident in many areas of fine art.Results. System inversions are especially evident in those areas of art that can be called marginal; for example, abstract expressionism or hyperrealism. In such art movements, the highest symbolic coordination level acts as a service level; it only supplies material to the lower motor levels, through which the artistic intent is carried out. But marginal artistic trends are only an example that demonstrates the potential diversity of motor skills in visual art activity.Conclusion. The described diversity of motor inclinations allows students with a variety of motor skills profiles to achieve self-realization in the visual arts.

Psychotherapeutic and Psychosocial Interventions with Unaccompanied Minors: A Scoping Review.

Unaccompanied minors (UAMs) are considered a particularly vulnerable population, facing severe threats regarding their physical and mental health. As their number has increased in recent years worldwide, research on mental health interventions has become necessary. The implementation of psychotherapeutic interventions has been documented, but psychosocial interventions seem to not have been consistently studied. In this review, we summarize the psychotherapeutic and psychosocial interventions with UAMs that have been studied up to now. Following the PRISMA guidelines for scoping reviews, we searched four databases and included studies and practice papers; there were no restrictions on publication date, geographical region, language, or method. We identified 46 studies on psychotherapeutic interventions and 16 studies on psychosocial interventions that met the inclusion criteria. Psychotherapeutic interventions were mainly based on cognitive behavioural, psychodynamic, narrative, art and transcultural approaches and aimed at improving UAMs' trauma, mental health and wellbeing, as well as professionals' skills and therapeutic protocols. Several studies showed promising results, with the cognitive behavioural approaches being the most researched. However, more research is needed in order to draw conclusions in terms of effectiveness. Psychosocial interventions followed various approaches and aimed at UAMs' empowerment, wellbeing, support and integration, as well as at improving caregivers' skills. Nonetheless, they seem not only very heterogeneous but also understudied, and we believe that a focus on them would be very useful. Methodological limitations and their implications for future research are discussed.

How the ‘Lejabys’ Came into Being: Artists and Workers in Struggle. A Spatio-Temporal Odyssey between ‘Mobilising’ and ‘Organising’

Art and other creative approaches can be a resource or a mobilising strategy for activists and artists. Little work has been done, however, on what happens in the interactions between artists and activists in the daily life of a conflict. We suggest that social mobilisations may be seen as organising processes as well as mobilising actions, and we analyse how creative and artistic approaches may contribute to this organising/mobilising reciprocal relationship. Based on an analysis of the conflict that accompanied the announcement of the Lejaby plant closure in Yssingeaux in 2012, which inspired several artists, we show that these approaches, by their capacity to grasp sensitive dimensions, favour spatio-temporal episodes that structure the struggle: some constitute protected spaces, which can correspond to an intimate reflexive time or to a collective moment of synchronisation of subjective temporalities; others correspond to hybridised spaces, which can be sometimes empowering and sometimes theatrical. We thus contribute both to the field of social movement analysis and to the role of art and creativity in the organisation and mobilisation within these movements; we also contribute to a relational reading of the spatial and temporal dimensions of organisation and collective action, in the tradition of Lefebvre and Massey.

Persistent homology of coarse-grained state-space networks.

This work is dedicated to the topological analysis of complex transitional networks for dynamic state detection. Transitional networks are formed from time series data and they leverage graph theory tools to reveal information about the underlying dynamic system. However, traditional tools can fail to summarize the complex topology present in such graphs. In this work, we leverage persistent homology from topological data analysis to study the structure of these networks. We contrast dynamic state detection from time series using a coarse-grained state-space network (CGSSN) and topological data analysis (TDA) to two state of the art approaches: ordinal partition networks (OPNs) combined with TDA and the standard application of persistent homology to the time-delay embedding of the signal. We show that the CGSSN captures rich information about the dynamic state of the underlying dynamical system as evidenced by a significant improvement in dynamic state detection and noise robustness in comparison to OPNs. We also show that because the computational time of CGSSN is not linearly dependent on the signal's length, it is more computationally efficient than applying TDA to the time-delay embedding of the time series.

How to Market the Arts: A Practical Approach for the 21st Century by Anthony Rhine and Jay Pension

Reviewed by: How to Market the Arts: A Practical Approach for the 21st Century by Anthony Rhine and Jay Pension James Filippelli How to Market the Arts: A Practical Approach for the 21st Century. Anthony Rhine and Jay Pension. New York: Oxford University Press, 2022; pp. 269. Anthony Rhine and Jay Pension's How to Market the Arts: A Practical Approach for the 21st Century complements Rhine's previous monograph, Theatre Management: Arts Leadership for the 21st Century (2018). This coauthored text provides the reader with valuable information on how to effectively market a theatre in the twenty-first century and will benefit a plethora of undergraduate and graduate students enrolled in performing arts, business, management, or leadership programs. The text is divided into five parts: Marketing versus Engagement, Education, Experience, Environment, and Ease of Access. Rhine and Pension begin each part with a brief overview of the chapters therein. They propose a new paradigm using visual models and case studies of several arts organizations to better explain how nonprofit arts marketing can and should work. They harmonize the four Ps (product, price, place, and promotion) of marketing with the four Es (education, experience, environment, and ease of access) of engagement. Theatre managers and producers will appreciate the importance of marketing and engagement. Rhine and Pension define the process of engagement "as one in which both parties mutually control the interaction and receive roughly equivalent benefits of value" (23). They elaborate on a need to develop a model that is sustainable and successful. Part I, "Marketing versus Engagement," strives to identify shifts in traditional marketing. Chapter 1 highlights researchers and practitioners incorporating different marketing mix concepts. According to Rhine and Pension, engagement is more closely associated with the nonprofit arts and their market exposure than aspects of the conventional marketing mix would suggest. In chapter 2, they discuss the concept of engagement and the connection within the arts and offer practical examples. One illustrative example of engagement is the "Talk Back," which the authors argue needs to be guided and structured. They suggest that a clear understanding of the difference between events that create involvement and those that create engagement is beneficial to arts leaders. In Part II, "Education," Rhine and Pension address the need for theatres to engage with and educate their audiences rather than merely to promote them. Chapter 3 discusses promotion and education. The authors indicate to the reader how important promotion is in the nonprofit sector. This chapter lays the foundation for chapters 4 and 5. In chapter 4, Rhine and Pension present a case study of an arts organization that followed strict promotional methodology without developing any engagement through education. Sadly, after twenty-four years, the arts organization closed its doors. In other words, what not to do! Chapter 5 concludes Part II with highlighting the need for education and the arts. Similarities between education and the arts exist in identifying targets and needs, objectives, and implementation. When one completes reading Part II, it is obvious that education is the key to understanding the audience and the arts organization. Part III, "Experience," explores the difference between experience and the physical product. Chapter 6 describes Jerome McCarthy's framework around the four Ps (product, price, place, and promotion). McCarthy's work demonstrates that both products and services satisfy the needs of individuals; however, Rhine and Pension argue that John Dewey's approach in Art as Experience is "more collaborative and beneficial" (103). Chapter 7 outlines the concept of product relative to arts organizations. The authors elevate experience over product; consequently, "art only occurs in the presence of participation" (138). Chapter 8 clearly and succinctly presents the importance of experience and its appropriateness to the arts. The authors emphasize customer experience, not product, as most important. Part IV, "Environment," investigates the ideas of "place" and "environment." Chapter 9 begins by contrasting the two, with Rhine and Pension arguing that "place has to do with the location where [the] product is being distributed," while environment is meant to convey the "places or surroundings in which arts consumers interact" (159). Though important, this chapter is somewhat dry. Chapter 10 discusses place from interaction to objective, arguing...

Fast and stable schemes for non-linear osmosis filtering

We consider a non-linear variant of the transport-diffusion osmosis model for solving a variety of imaging problems such as shadow/soft-light removal and compact data representation. The non-linear behaviour is encoded in terms of a general scalar function g with suitable properties, which allows to balance the diffusion intensity on the different regions of the image while preventing smoothing artefacts. For the proposed model, conservation properties (intensity and non-negativity) are proved and a variational interpretation is showed for specific choices of g. Upon suitable spatial discretisation, both an explicit and a semi-implicit iterative scheme are considered, for which convergence restrictions and unconditional stability are proved, respectively. To validate the proposed modelling and the computational speed of the numerical schemes considered, we report several results and comparisons for the problem of shadow/light-spot removal and compact data representation, showing that artefact-free and computationally efficient results are obtained in comparison to standard linear and anisotropic models, and state-of-the art approaches.

The Effect of the Steam Approach on Student Social Science Learning Outcomes in Elementary School

Community intelligence efforts can be pursued by continuing education. In Indonesia, it is very sophisticated for educators in choosing a creative and effective learning approach. One of them uses the STEAM (Science, Technology, Engineering, Arts, and Mathematics) approach. The purpose of this study is to determine the influence of this STEAM (Science, Technology, Engineering, Arts, and Mathematics) approach on the learning outcomes of grade IV elementary school students. This STEAM (Science, Technology, Engineering, Arts, and Mathematics) approach has a positive impact on student learning outcomes because there is a significant influence on the learning of Social Sciences using this approach. Student learning outcomes using the STEAM (Science, Technology, Engineering, Arts, and Mathematics) approach are higher than learning outcomes with conventional approaches.
 
 Keywords: STEAM Approach, Learning Outcomes, Social Sciences, Elementary School.

The Humble Chair: Fostering Culturally Humble Collaborations

The authors recount a collaborative art-making journey centered on self-reflexivity to sustain a partnership across racial, social, and cultural differences. The image of a chair, re-imagined as a Humble Chair, was a symbol to anchor critical inquiry. The authors’ explorations provide a pragmatic and artful approach to fostering cultural humility.

Early anomaly detection in time series: a hierarchical approach for predicting critical health episodes

The early detection of anomalous events in time series data is essential in many domains of application. In this paper we deal with critical health events, which represent a significant cause of mortality in intensive care units of hospitals. The timely prediction of these events is crucial for mitigating their consequences and improving healthcare. One of the most common approaches to tackle early anomaly detection problems is through standard classification methods. In this paper we propose a novel method that uses a layered learning architecture to address these tasks. One key contribution of our work is the idea of pre-conditional events, which denote arbitrary but computable relaxed versions of the event of interest. We leverage this idea to break the original problem into two hierarchical layers, which we hypothesize are easier to solve. The results suggest that the proposed approach leads to a better performance relative to state of the art approaches for critical health episode prediction.

Multigranular rough set model based on robust intuitionistic fuzzy covering with application to feature selection

Fuzzy and intuitionistic fuzzy β covering has attracted the interest of many researchers recently. However, some of the factors namely 1. the lack of inclusion relationship between lower and upper approximation, 2. Inability to fit real valued dataset i.e. misclassification, hinder its application in decision making. Also, majority of these approaches are affected by noise. All these factors have created the need for a robust model. This paper proposes a novel intutitionistic fuzzy β covering model which is robust, combining intuitionistic fuzzy set, β covering and multigranulation rough sets. A new intuitionistic fuzzy β covering based multigranulation model is proposed which satisfies inclusion relationship between two approximations. This robust model is used to formulate dependency degree, which is evaluated at various granularity levels and is thereby employed for feature subset selection. Series of experiments are conducted on real valued datasets to illustrate the robustness and effectiveness of the underlying model. Furthermore, a comparative analysis with state of art approaches followed by statistical test lays down the superiority of the proposed model.

Healing, Empowering, Engaging, Learning, and Decolonizing Through Culture: Living Wellness, Resilience, and Resurgence in the Classroom Through Creative Arts

Art and Indigenous culture are inseparable. From the immaculately decorated lodges and war shirts of thousands of years to contemporary mixed and digital media images, Indigenous arts are expressions of survivance. Creative arts have sustained Indigenous ways of knowing, being, doing, and healing through attempted cultural genocide. Research has shown that art engages youth in life skill-building, learning, emotional regulating, and spiritual healing, supporting art as an intervention for wellness. Culturally-based artistic expression and the process of creating promotes wellness among Indigenous youth. As primary sites of assimilation and colonialism, educational institutions have a responsibility to enact reconciliation through culturally-rooted arts-based approaches to wellness. School psychologists are wellpositioned to support these approaches. This study took place in Kainaiwa in Southern Alberta and explored Niitsitapi artists’ and educators’ perspectives on the impacts of culturally-rooted arts-based interventions with Niitsitapi middle school students in the classroom. Over 2 days, professional Indigenous artists shared their art practices with students at a middle school in Kainai First Nation in Alberta. We had research conversations with 12 Niitsitapi community members involved in the event using a decolonizing, community-based approach. Indigenous storywork was used to understand research conversations, highlighting information and guidance for school psychologists to inform their engagement with Indigenous students and community members in schools. Findings emphasized art as healing, particularly given its connection to culture. Further, cultural engagement through art supports student wellness and educational engagement. Art can be used to empower voice, overcome deficit narratives, create new stories, and cope with disharmony. Art can also engage youth in discovery and learning, providing an alternative to a lecture style of learning, increasing enjoyment in the classroom experience. These findings have practical implications for future interventions and the integration of art pedagogically. This paper offers recommendations that highlight stark distinctions between culturally-rooted art practice and conventional Eurocentric art approaches in education.

A Spatio-Temporal Approach For Determining Individual's Covid-19 Risks

Current state of art approaches such as the susceptible-infected-removed model and machine learning models are not optimized for modeling the risks of individuals and modeling the effects of local restrictions. To improve the drawback of these approaches, the feedback processing framework is proposed where previously accumulated global statistics and the model estimates generated from the spatial-temporal data are combined to improve the performance of the local prediction. The proposed framework is evaluated in three processing stages: generation of the simulation dataset, feedback analysis, and evaluation for the spatial-temporal and real-time pandemic analysis. In the data generation stage, the corresponding state of the illness for each person is modeled by a Markov stochastic process. In this stage, the parameters such as the reproduction rate, symptomatic rate, asymptomatic rate, population count, infected count, and the average mobility rate are used to update the individual's Covid-19 status and the individual's movements. The movement data of each person is generated randomly for several places of interest. In the feedback analysis stage, both the aggregated statistics and the local event data are combined in a linear model to infer a score for the Covid-19 probability of the person. In this respect, a stochastic model can be used to approximate the local statistics. In the evaluation stage, the result of the feedback analysis for all the interactions is used to classify the state of the individuals periodically. Later the accuracy of the evaluation for each person is obtained by comparing the individual's prediction with the real data generated in the same time interval. The Kappa scores independent from different populations, locations, and mobility rates obtained for every interaction indicate a significant difference from the random statistics.