bluuebunny/crossref_metadata_2025 huggingface dataset:
Virtual Driving Simulation for Pedal Error Study
Authors: Zulkifli Aidisyahrul Hanif , Mohd Khairuddin Ismail , P. P. Abdul Majeed Anwar , Mohd Razman Mohd Azraai , Abdullah Muhammad Amirul , Mohd Isa Wan Hasbullah
Published: June 2023

This paper is about the development of a virtual driving simulation for the pedal error study among Malaysian drivers. The project is in collaboration with the Malaysian Institute of Road Safety (MIROS) and The New Car Assessment Program for Southeast Asia (ASEAN NCAP) research grant. Instead of conducting the naturalistic driving test, the virtual driving simulation will be used in the current driving simulator developed for this project. Therefore, the aim of this study is to develop the virtual driving simulation which contain some emergency braking situations, determine the foot placement on the pedal (using video observation) and to measure the total pressure on the pedals during the normal driving and emergency braking situation among Malaysian drivers. This study is focused on automatic transmission car by Malaysian drivers who aged around 20 to 50 years old that have minimum two years driving experience. A questionnaire was also given to participants, asking them about their personal information, their driving behavior, infrastructure, and safety, as well as pedal misapplication. The virtual driving simulator was equipped with some devices such as camera, pressure sensor, screen monitor, steering wheel and driver’s pedal. A study was completed successfully to determine the position of the Malaysian driver's foot on the brake pedal during emergency braking. It has been discovered that roughly 6.67% of participants in a driving research use both legs while driving and use their left foot to hit the brake pedal during emergency braking. The study also found that about 26.67% of participants feel dizzy while driving and around 96.67% of participants were surprised by the obstacles.
Analysis of Stock Market Reaction in Malaysia During Covid-19 Pandemic via ARIMA
Authors: Mohd Rosli Nor Aziyatul Izni , Saruchi Sarah 'Atifah , Tajuddin Nur Ilyana Ismarau , Ulaganathan Puvarasan , Awtar Singh Gurpreet Singh , Yunus Nurul Azhani
Published: June 2023

Investment has become a major money-making business in this world through investment in financial markets, stock markets, and forex. There is uncertainty about which stocks to buy during a pandemic like Covid-19. Poor investment choices will affect the profitability of the investors, shifting their risk appetite to be more defensive. Thus, this research is carried out to study the movement of stocks for the year 2020 in Malaysia based on the data obtained from Yahoo Finance. The objective is to provide investors with a guide to investing efficiently during a pandemic. This study investigates how Covid-19 impacts the rate of growth or reduction of stocks so that the performance of the stocks can be forecasted in the future. The moving average method is used to analyze the trend of the stock by comparing the top gainers against the top losers during the periods of pre Covid-19 and Covid-19. The Autoregressive Integrated Moving Average (ARIMA) model studies the autocorrelation function (ACF) graph of selected stocks to further understand the movement of the stocks and compare it to the closing prices of the selected stocks. Based on the findings, it was demonstrated that the quantitative method used could be used to study the effects of a pandemic, as well as the severity of the losses incurred, and profits earned by the industries. The industries that are essential to the country, like pharmaceuticals and rubber manufacturing, are able to maintain their businesses. Moreover, these sectors have profited from the pandemic. The tourism and aviation industries have been hit the hardest by the pandemic, as evidenced by falling stock prices. Thus, it would be wise for investors to invest in an essential sector company during the Covid-19 pandemic.
Analisis Kelayakan Isi dan Bahasa pada Buku Teks Bahasa Sunda Gapura Basa Kelas VII SMP
Authors: Mayasari Yuliani , Haerudin Dingding , Nurjanah Nunuy
Published: June 2023

The feasibility of the content and language of the Sundanese language textbook must be in accordance with the applicable curriculum, besides the content itself must be related with the core competencies of the learning. The purpose of this study was to determine the feasibility of content and appropriateness of the language in 2017 revised edition of Sundanese Gapura Basa textbook for SMP class VII. The research method used a qualitative method. The data in the form of words and sentences. The results showed that the appropriateness of the content and language of the Sundanese Gapura Basa textbook for class VII SMP was in accordance with the instruments set by the BSNP which included the suitability of the material and the curriculum and the applicable basic competencies, the accuracy of the material in the book, and supporting material used. The feasibility of the language includes communication, straightforwardness, coherence, conformity with the correct Sundanese language rules and the use of terms, pictures, or symbols according to the development of students. The results of the research also show that the Sundanese language textbook Gapura Basa SMP grade VII revised 2017 edition is feasible to use. by educators in the teaching and learning process.
Poetic Emergence and Insight from the Trace of the “Line”: A Reading on Carlo Scarpa s Castelvecchio Museum Drawings
Authors: Asar Hande
Published: June 2023

This study aims to trace the line and to conduct a discussion about poetics as it arises from the trace or drawing of that line. The study, therefore, considers the act of drawing as a thinking practice and explores the dynamic relationship between “line”, “the act of drawing”, and “drawing” through sketches. This study is based on the qualitative research method that discusses the conceptual relationship between language and poetry. This relationship is crossed with not-language and not-poetry and is explained through the approach of “poetic emergence” and “poetic insight”. A sample analysis is made through the concepts of “dream, image, and affectivity”, which are generated from this approach. The study’s sample group is the selected sketches of Carlo Scarpa’s Castelvecchio Museum. These sketches have been evaluated using the content analysis technique. The tracking of the line reveals a personal journey that includes the image, dream, and affectivity. Although Scarpa’s dialogue with the designer of the Castelvecchio Museum sketches has ended, their dialogue with its observer continues. At the end of the sketches’ reading, one makes inferences on emotions. These emotions, which derive from an ambiguous world of dreams and images, have created moments of “poetic emergence”, while poetic emergence and its moments of emergence have created the “poetic understanding”, which is personally internalized. Since the moments of poetic emergence and understanding arose from each other, they have not been revealed themselves in a specific order, but in a reticulated cycle flowing into each other. Subjecting the study to a subjective evaluation process has created limitations in the context of the content of the qualitative research method. The study, which unfolds over the poetics, is valuable as it discusses the intangible dimensions of architecture through the line standing at the intersection of the material and the immaterial.
Lesbianas y gais marroquíes en espacios de confinamiento temporal. El caso de Melilla
Authors: Cros-Puig Xavier
Published: June 2023

Los Centros de Estancia Temporal para Inmigrantes (CETI) son dispositivos de primera acogida donde se gestionan la llegada y derivación hacia otros procedimientos de extranjería tanto de los demandantes de asilo como de los migrantes en situación irregular. Por sus especiales características, el territorio de Melilla y su CETI, se convierte para las personas demandantes de asilo por orientación sexual y/o identidad de género en un espacio de doble confinamiento. Este trabajo aborda las dificultades y problemáticas derivadas de la estancia a menudo prolongada de las personas gais y lesbianas de origen marroquíes en este espacio de control, exclusión y represión, y de cómo, paradójicamente, los dispositivos de protección hacia este colectivo son contraproducentes.
Escalada para Conectar: De Proyecto de ApS a Comunidad de Práctica, Aprendizaje y Afecto
Authors: Arribas-Cubero Higinio Francisco , Cano Sanz Javier , Frutos-de Miguel Jonatan , García González Alba
Published: June 2023

Este artículo trata de comprender las posibilidades de la escalada deportiva como espacio de encuentro formativo entre personas con malestar psíquico y estudiantes universitarios, a lo largo de un proyecto desarrollado a través del método de Aprendizaje-Servicio (ApS). Partiendo de una metodología cualitativa de investigación basada en el estudio de casos, en el que se otorga voz a todos los participantes, este trabajo se centra en analizar el potencial de la escalada y profundizar en el impacto del ApS, valorando sus posibilidades para la creación de comunidades de práctica inclusivas. Los resultados nos muestran la necesidad de plantear proyectos comunitarios como prioridad en el trabajo con colectivos vulnerados y reconocer el derecho a la participación social en prácticas de actividad física como acto de justicia social. En este sentido, la escalada se ha convertido en un espacio compartido y valioso, que ha generado seguridad emocional y sentido de pertenencia. Las necesidades colectivas emergen a través de procesos reflexivos, que han contribuido a la comprensión de los proyectos de ApS como experiencia comunitaria de práctica, aprendizaje y afecto, en el que los roles entre personas se funden y se confunden.
Prácticas de Liderazgo Democrático para la Justicia Social. Un Estudio Cualitativo desde la Perspectiva de la Comunidad Educativa
Authors: Cerrillo Rosario , López-Bueno Helena , Hidalgo Nina
Published: June 2023

Uno de los estilos de liderazgo escolar más comprometido con la lucha contra las desigualdades sociales es el liderazgo democrático para la Justicia Social. A pesar de que los conceptos de democracia y justicia social van inexorablemente de la mano, enfatizarlo en el estilo liderazgo refleja una forma clara de entender la gobernanza y la escuela. El objetivo de este estudio es comprender las acciones que definen un liderazgo democrático para la Justicia Social. Para alcanzarlo, se ha llevado a cabo un estudio de casos instrumental investigando en profundidad tres equipos directivos. Los participantes han sido diferentes miembros de la comunidad educativa de los tres centros escolares. La recogida de información se ha realizado a través de entrevistas semiestructuradas y grupos de discusión. Los resultados reflejan que cinco son las prácticas que caracterizan a los equipos directivos democráticos que orientan su práctica a la Justicia Social: a) promueven una cultura democrática y critica que lucha contra las desigualdades, b) distribuyen los recursos y oportunidades entre las personas que más lo necesitan, c) reconocen los valores culturales y la diversidad, d) promueven un currículum inclusivo y participativo y e) promueven una gobernanza escolar democrática.
Development of a new kenaf bast fiber-reinforced thermoplastic polyurethane composite
Authors: El-Shekeil Yousuf Ali , Salit Mohd Sapuan , Abdan Khalina , Zainudin Edi Syams
Published: June 2023

A composite of themoplastic polyurethane (TPU) reinforced with short kenaf (Hibiscus Cannabinus L.) fiber (KF) was prepared by a melt-mixing method. Mixing was followed by compression molding to produce sheets for specimen cutting. Five samples were cut from the composite sheet. A mean value was taken for each sample according to ASTM standards. The aims of this study were to optimize the processing parameters and fiber size of TPU/KF composite. The method used to develop this composite consisted of two main steps. First, the influence of processing parameters such as temperature, time, and speed on tensile properties was studied. Second, effects of different fiber size on tensile properties, flexural properties, and impact strength were tested. The optimum blending parameters were 190°C, 11 min, and 40 rpm for temperature, time and speed, respectively. TPU/KF composites with different fiber sizes were prepared, namely, <125, 125-300, and 300-425 µm. Tensile and flexural strength and modulus were best for fiber size range between 125 and 300 µm. Impact strength showed a slight increasing trend with an increase in fiber size.
Morphological, spectroscopic, and thermal properties of alkali-treated and chemically modifed oil palm empty fruit bunch fibers and oil palm frond fibers: A comparative study
Authors: Bhat Irshad-ul-Haq , Abdul Khalil H. P. S. , Ismail H. , Alshammari Turki
Published: June 2023

The effect on morphological, spectroscopic, and thermal properties of oil palm empty fruit bunch fibers (OPEFB fibers) and oil palm frond fibers (OPF fibers) following treatment and modification with sodium hydroxide and succinic anhydride, respectively, were investigated. The evidence of treatment was observed by weight gain and FT-IR. The effect of the treatment upon the fiber surfaces was examined using scanning electron microscopy (SEM), which indicated that succinic anhydride treatment led to smoother surfaces as compared to the sodium hydroxide. The thermal degradation was carried out by thermal gravimetric analysis, which exhibited a different degree of mass loss due to different treatments.
Implementation of ESC QI Initiative in Neonatal Unit Setting and Adaptation During the Pandemic
Authors: Small Sarah , Pham Rachel , Turbenson Meghan , Coleman Zoe , Manuel Vinit , Muniraman Hemananda
Published: June 2023

OBJECTIVES

To improve outcomes in infants with neonatal opioid withdrawal syndrome (NOWS) admitted to NICU by implementing a quality improvement (QI) initiative incorporating “eat, sleep, console” (ESC) as a withdrawal evaluation tool and promotion of nonpharmacological interventions. Secondarily, we evaluated the impact of the coronavirus disease 2019 pandemic on QI initiative and outcomes.

METHODS

We included infants born ≥ 36 weeks gestation and admitted to NICU with a primary diagnosis of NOWS between December 2017 and February 2021. (preintervention; December 2017–January 2019, postintervention; February 2019–February 2021). We compared cumulative dose, duration of opioid treatment, and length of stay (LOS) as our primary outcomes.

RESULTS

The average duration of opioid treatment decreased from 18.6 days in the preimplementation cohort (n = 36) to 1.5 days in the first-year postimplementation (n = 44) with a reduction in cumulative opioid dose from 5.8 mg/kg to 0.6 mg/kg and decrease in the proportion of infants treated with opioids from 94.2% to 41.1%. Similarly, the average LOS decreased from 26.6 to 7.6 days. In the second-year postimplementation during the coronavirus disease 2019 pandemic (n = 24), there was an increase in average opioid treatment duration and LOS to 5.1 and 12.3 days respectively, but cumulative opioid dose (0.8 mg/kg) remained significantly lower than the preimplementation cohort.

CONCLUSIONS

ESC-based quality improvement initiative led to a significant decrease in LOS and opioid pharmacotherapy in infants with NOWS in NICU setting. Despite the impact of the pandemic, some of the gains were sustained with adaptation to ESC QI initiative.
A Comprehensive Theory of Spirituality: Humanistic, Theist, and Theotic
Authors: Helminiak Daniel A.
Published: June 2023

Especially among the Abrahamic religions, quite regularly spirituality implies a relationship with God or else some other supposed “sacred” entities or forces. This starting point precludes a fully psychological explanation of spirituality since appeal to God exceeds the methodology of the social or human sciences: Psychology is not theology. In contrast, a traditional Christian axion holds that "grace builds on nature." Accordingly, recognize that a dimension of the human mind itself—consciousness or human spirit—is first and foremost the source and object of spiritual experiences. Then the natural becomes fundamental, theoretically the essential, and at its roots spirituality lies within the competence of human study, and religious accounts are further elaborations. This proposition is the thesis of this article. Following the trenchant analyses of Bernard Lonergan, this account recognizes human consciousness or spirit as a dynamic dimension of the mind, self-present, out-going, self-transcending, open-ended, geared to reality, and normative: These requisites inherent in consciousness orient a person toward the true and the good. Then personal integration and spiritual growth coincide—in this way: Psychotherapeutic healing frees the spirit to increasingly take the lead and guide one’s living, constituting one as “a spiritual person.” The specification of consciousness/spirit contrasts with other mental content—emotions, memory, imagery—and suggests a tripartite human model (organism, psyche, and consciousness) in place of the standard bipartite model (body and mind). Such a naturalistic starting point easily supports religious elaboration, seeing God as Creator (theology) and envisioning union with God (theotics). This theory foresees the collaboration of the world's religions in acknowledging a common spiritual foundation for themselves and for our pluralistic secular society.
Faithful Resilience: Profit and Support Strategies of Religious Institutions amidst the COVID-19 Crisis
Authors: Joob Beuy , Wiwanitkit Viroj
Published: June 2023

This article presents an analysis of the observation on making a profit for religious institutions and providing social support during the COVID-19 pandemic in a tropical country in Indochina. The study utilizes a descriptive approach, combining a literature review and a case study to explore the specific situation in the region. The article begins with an introduction to the concept of social marketing and then focuses on a unique form of religiously related social marketing: the production and sale of amulets. The potential benefits for religious establishments in terms of both financial gain and social support are highlighted. Furthermore, a detailed case study on ritual amulet marketing during the COVID-19 outbreak crisis is provided, shedding light on the strategies employed and the outcomes achieved. The findings suggest that social marketing by religious institutions can be a valuable advertising tool even during times of public crisis. The article concludes by emphasizing the potential of social marketing as an effective means for religious institutions to address societal needs and generate positive impacts. This research contributes to the understanding of the role of religious organizations in the promotion of social welfare and offers insights for practitioners seeking innovative approaches to navigate challenging circumstances.
Discourses of faith: popular religiosity in the work of Jorge Hidalgo and José Emilio Leyva
Authors: Zaldívar Yuricel Moreno
Published: June 2023

The article deals with the representation of popular religiosity in the work of the artists Jorge Hidalgo Pimentel and José Emilio Leyva Azze. From engraving, painting, drawing and sculpture, both have recreated deities, various symbolic elements, orality, among other aspects that are part of the social imaginary in Cuba. The text chooses representative works of stages in which the artists assume the theme with greater permanence within their work. The examination has been carried out from a qualitative perspective that overlaps the formal analysis of the works and the hermeneutic method, as a generalizing interpretative framework. With different trajectories, motivations and poetics, Jorge Hidalgo and José Emilio Leyva contribute visions that demonstrate the survival of cultural practices rooted in the Cuban people, since they form an intrinsic part of their identity. The works contribute to the safeguarding of these manifestations of intangible cultural heritage. The evaluations given in the text also provide elements that enrich the critical body on this matter within the Holguín visual arts.
Derecho «canónico y litúrgico» en las «actas» de la redacción del Codex Iuris Canonici
Authors: Gandía-Barber Juan-Damián
Published: June 2023

En la redacción de la parte de los otros actos de culto, los lugares y tiempos sagrados del Código actual, se tuvo que describir y determinar qué era Derecho canónico y litúrgico para tomar decisiones sobre los cánones que no habían de ser desechados y a partir de los cuales comenzar la redacción del nuevo texto codicial. El escrito pretende mostrar los documentos que tratan de este tema, de los que ya se tiene noticia por la publicación de las actas y, también, presentar algunos fragmentos de otros documentos que no son conocidos y que se encuentran en la parte de las “actas” no publicadas del proceso, del archivo del Dicasterio para los Textos Legislativos.
Coworking como Ambiente para a Exploração de Buracos Estruturais
Authors: Junior Luiz Oliveira , Costa Danilo De Melo
Published: June 2023

O objetivo da presente pesquisa é investigar a predisposição para exploração de buracos estruturais em ambientes de coworking. No que se refere à metodologia, apresenta abordagem qualitativa e quantitativa. Na pesquisa quantitativa, os dados foram coletados por meio de questionários e usou-se de estatística descritiva, procedimentos de análise univariada e método de Bonferroni com alfa = 0.05. Em relação à pesquisa qualitativa, foram realizadas entrevistas semiestruturadas junto aos gestores de empresas instaladas em um ambiente de coworking localizado na cidade de Belo Horizonte, Minas Gerais e adotou-se a análise de conteúdo categorial. Os resultados evidenciaram a existência de buracos estruturais com oportunidade de exploração para empresas instaladas em um espaço de coworking. Assim, recomenda-se que gestores de espaços de coworking que busquem desenvolver estratégias gerenciais que visem incentivar contatos mais efetivos, especialmente os interorganizacionais, de forma a intensificar as relações, promover mais trocas de informações e, por consequência, superar os possíveis buracos estruturais existentes.
Avaliando a qualidade dos serviços na formação de jovens aprendizes por uma entidade sem fins lucrativos (ESFL)
Authors: Nascimento Natalia Figueira do , Maia Leonardo Caixeta de Castro
Published: June 2023

Este trabalho tem como objetivo avaliar a qualidade dos serviços prestados por uma entidade sem fins lucrativos (ESFL), que atua no ramo da aprendizagem profissional e, simultaneamente, busca apresentar um instrumento de pesquisa. Para tanto, avalia-se as expectativas e as percepções dos clientes, que neste caso são os financiadores do projeto e não os jovens aprendizes, acerca da qualidade da prestação do serviço. O instrumento passou pela validação de professores especialistas, coordenadores, diretores e ex-parceiros da entidade estudada e enviado a 93 clientes do Instituto Alfa na cidade de Uberlândia, MG. Por fim, foram obtidas 22 respostas. A partir dos dados obtidos, foram realizados os testes estatísticos não paramétricos, que atestaram a robustez e a relevância do instrumento de pesquisa desenvolvido. Ademais, os constructos responsividade, empatia e aspectos psicossociais não apresentaram diferenças estatísticas relevantes entre expectativas e percepções
Modelos de Negócios Sustentáveis: O Estado da Arte do Flourishing Business Canvas
Authors: Pellin Alecxandro , Stocker Lago Sandra Mara
Published: June 2023

Este artigo tem por objetivo apresentar uma revisão sistemática da literatura nacional e internacional para entender o estado da arte da pesquisa sobre o Flourishing Business Canvas, uma ferramenta de modelagem de negócios voltados para a sustentabilidade. Trata-se de uma pesquisa bibliográfica exploratória com abordagem qualitativa, na qual foram realizadas buscas nas principais bases indexadoras, portais de revistas científicas e em bancos de teses e dissertações dos últimos cinco anos, desde a criação da ferramenta em 2016. Os resultados encontrados revelaram que por meio de aplicações práticas e abordagens teóricas da ferramenta, existe uma grande potencialidade do Flourishing Business Canvas na elaboração de modelos de negócios sustentáveis por empresas e organizações. Este artigo traz contribuições práticas e teóricas ao ser um dos estudos precursores sobre esta ferramenta, apresentando uma análise do atual panorama das publicações acadêmicas sobre o desenvolvimento da ferramenta e por consequência sua aplicabilidade para o desenvolvimento e aprimoramento de modelos de negócios sustentáveis.
Entendendo a relação entre estratégias, capabilidades operacionais e gestão da cadeia de suprimentos
Authors: Domenek Antonio Carlos , Moori Roberto Giro , Santos Mario Roberto
Published: June 2023

O objetivo do artigo foi o de examinar o efeito mediador das capabilidades operacionais entre as estratégias empresariais e o desempenho operacional e entre a gestão da cadeia de suprimentos e o desempenho operacional. Para tanto, utilizou-se de uma pesquisa de natureza descritiva do tipo quantitativa junto a uma amostra de 138 gestores da cadeia de suprimentos da indústria manufatureira brasileira. Foram empregadas técnicas da análise fatorial para definir uma estrutura subjacente à matriz de dados coletados e a modelagem em equações estruturais para examinar a significância estatística das relações de dependência entre os constructos. Os resultados indicaram que as capabilidades operacionais medeiam, parcialmente, a relação entre as estratégias empresariais e o desempenho operacional; e entre a gestão da cadeia de suprimentos e o desempenho operacional. O estudo teve como contribuições uma melhor compreensão da integração da estratégia empresarial e a gestão da cadeia de suprimentos, bem como a elucidação do efeito mediador das capabilidades operacionais na relação entre a integração dos constructos, estratégia empresarial e gestão da cadeia de suprimentos, com o desempenho operacional.
Maeotian Gray Clay Cups of the 4th – 3rd Centuries BC
Authors:   Kuban State University, Limberis Natalya , Marchenko Ivan ,   Kuban State University
Published: June 2023

The article is devoted to the typology and chronology of gray clay cups from the Maeotian burial grounds on the right bank of the Kuban river. Type 1 refers to biconical cups with a high, narrow neck widening upwards (30 items). A little over half of the studied vessels come from assemblages with a wide chronological range dating back to the 4th and early 3rd centuries BC, where they are accompanied by swords of the Sindian-Maeotian type or sets of pottery characteristic of this period. The remaining burials with cups can be dated more precisely by the finds of container amphorae from different centers (Heraclea, Thasos, Ikos, Mende, Sinope, etc.). The wide chronological framework of the existence of type 1 cups among the Maeotians can be determined within the first half of the 4th century BC, but their narrow chronology is limited to the second quarter of this century. Two versions of the origin of cups of this shape are put forward: the first one is from imported red clay vessels; the second one is from hand-made cups of the 6th–5th centuries BC. Type 2 is truncated conical cups widening upwards (13 items). There are not enough strong chronological references for a narrow dating of this type of cups. Furthermore, apart from the cups, imported vessels were found in the three assemblages including amphorae of Rhodes, a black glazed plate and a fish plate. As the analysis of the assemblages shows, type 2 cups existed among the Maeotians for a rather limited period from the late 3rd century BC up until the beginning of the next century.
Television News from 1989 to 2021: Timing, Film Frame, Shot, Camera Motion (Based on Czech News Broadcast)
Authors:   Lomonosov Moscow State University, Lapuk Ekaterina V.
Published: June 2023

One of the reasons for the transformation of media systems is the increase in information made possible by the development of new technologies and the Internet. In this context, the habits of media consumption change, the journalistic content changes too. The main purpose of the article is to identify changes in the form of television news over the past 30 years. This paper applies the content analysis to study 1608 video news of the Czech TV in three periods — 1989, 2005, and 2021. Firstly, over the years the average time of the TV news and the number of film frames in one news story has increased. On the other hand, the average duration of the frame has decreased. Besides, over the years, the number of lead paragraphs increases, which to some extent indicates the increase in PR­component in broadcast news. Secondly, despite the increasing trend of using smartphones for news consumption, there was no significant increase in the use of close­up shots by 2021. Thirdly, there is an increase not only in the number of frames and the average duration of video news, but also in the use of such a method of shooting as a panorama, which also creates movement and adds dynamics.
Transformation of the teacher’s image in Soviet and Russian Cinematography: Intracultural Dialogue
Authors:   Tomsk State Pedagogical University, Bernatonite Ada K.
Published: June 2023

This article examines the structure of the teacher’s image and its semantic content in Soviet and Russian cinema. In the 30s, it appeared to be of a generalizing nature; in the 40s, the teachers were idealized, in the cinema of the “Thaw” period a teacher appears as a person with the entire spectrum of human feelings. In cinematography, the specifics of the teacher’s activity and the demonstration of his awareness of his place in the pedagogical process depended on social attitudes. Thus, each decade has demonstrated a new approach. The relationship between the teacher and the student in the cinema of the 70s–80s of the 20th century was especially complex and multifaceted. In the era of perestroika, in the context of the decline in universal human values, the attitude towards the teacher changed. In most films, a teacher is either the cause of the conflict, or the object on which the student takes out his dissatisfaction with the world.
Developed subjectivity of students as a factor in the formation of a “pedagogical polylogue”
Authors:   Ural Federal University, Yurlova Svetlana V.
Published: June 2023

The article explores the problem of subjectivity in education, focusing on the specifics of interaction with an audience that possesses developed subjectivity. Based on the analysis of specific pedagogical experience, the most effective methods of a teacher’s work with a competent and highly motivated audience are considered. In this regard, the author relies on the concept of the “inner form of personality” formulated by P. Shchedrovitsky. The principle of self­construction underlying the “inner form of personality” presupposes the presence of a wide information field within which students must build their own strategy and the basis for systematization of the material, taking into account the research paradigm formulated by the teacher. Based on the methodology of M. Bakhtin, the author, introduces the concept of “pedagogical polylogue”. The presence of developed subjectivity among students necessarily entails interaction in the format of a “pedagogical polylogue”, where the teacher and students are equal acting, thinking, speaking and evaluating subjects. The active realization of subjectivity of both the student and the teacher generates a situation of mutual learning.
Reducing ANN-SNN Conversion Error through Residual Membrane Potential
Authors: Hao Zecheng , Bu Tong , Ding Jianhao , Huang Tiejun , Yu Zhaofei
Published: June 2023

Spiking Neural Networks (SNNs) have received extensive academic attention due to the unique properties of low power consumption and high-speed computing on neuromorphic chips. Among various training methods of SNNs, ANN-SNN conversion has shown the equivalent level of performance as ANNs on large-scale datasets. However, unevenness error, which refers to the deviation caused by different temporal sequences of spike arrival on activation layers, has not been effectively resolved and seriously suffers the performance of SNNs under the condition of short time-steps. In this paper, we make a detailed analysis of unevenness error and divide it into four categories. We point out that the case of the ANN output being zero while the SNN output being larger than zero accounts for the largest percentage. Based on this, we theoretically prove the sufficient and necessary conditions of this case and propose an optimization strategy based on residual membrane potential to reduce unevenness error. The experimental results show that the proposed method achieves state-of-the-art performance on CIFAR-10, CIFAR-100, and ImageNet datasets. For example, we reach top-1 accuracy of 64.32% on ImageNet with 10-steps. To the best of our knowledge, this is the first time ANN-SNN conversion can simultaneously achieve high accuracy and ultra-low-latency on the complex dataset. Code is available at https://github.com/hzc1208/ANN2SNN_SRP.
Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse
Authors: Huang Liwei , Ma Zhengyu , Yu Liutao , Zhou Huihui , Tian Yonghong
Published: June 2023

Deep artificial neural networks (ANNs) play a major role in modeling the visual pathways of primate and rodent. However, they highly simplify the computational properties of neurons compared to their biological counterparts. Instead, Spiking Neural Networks (SNNs) are more biologically plausible models since spiking neurons encode information with time sequences of spikes, just like biological neurons do. However, there is a lack of studies on visual pathways with deep SNNs models. In this study, we model the visual cortex with deep SNNs for the first time, and also with a wide range of state-of-the-art deep CNNs and ViTs for comparison. Using three similarity metrics, we conduct neural representation similarity experiments on three neural datasets collected from two species under three types of stimuli. Based on extensive similarity analyses, we further investigate the functional hierarchy and mechanisms across species. Almost all similarity scores of SNNs are higher than their counterparts of CNNs with an average of 6.6%. Depths of the layers with the highest similarity scores exhibit little differences across mouse cortical regions, but vary significantly across macaque regions, suggesting that the visual processing structure of mice is more regionally homogeneous than that of macaques. Besides, the multi-branch structures observed in some top mouse brain-like neural networks provide computational evidence of parallel processing streams in mice, and the different performance in fitting macaque neural representations under different stimuli exhibits the functional specialization of information processing in macaques. Taken together, our study demonstrates that SNNs could serve as promising candidates to better model and explain the functional hierarchy and mechanisms of the visual system.
Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-network
Authors: Bae Sangmin , Kim Sungnyun , Ko Jongwoo , Lee Gihun , Noh Seungjong , Yun Se-Young
Published: June 2023

Contrastive loss has significantly improved performance in supervised classification tasks by using a multi-viewed framework that leverages augmentation and label information. The augmentation enables contrast with another view of a single image but enlarges training time and memory usage. To exploit the strength of multi-views while avoiding the high computation cost, we introduce a multi-exit architecture that outputs multiple features of a single image in a single-viewed framework. To this end, we propose Self-Contrastive (SelfCon) learning, which self-contrasts within multiple outputs from the different levels of a single network. The multi-exit architecture efficiently replaces multi-augmented images and leverages various information from different layers of a network. We demonstrate that SelfCon learning improves the classification performance of the encoder network, and empirically analyze its advantages in terms of the single-view and the sub-network. Furthermore, we provide theoretical evidence of the performance increase based on the mutual information bound. For ImageNet classification on ResNet-50, SelfCon improves accuracy by +0.6% with 59% memory and 48% time of Supervised Contrastive learning, and a simple ensemble of multi-exit outputs boosts performance up to +1.5%. Our code is available at https://github.com/raymin0223/self-contrastive-learning.
Deconstructed Generation-Based Zero-Shot Model
Authors: Chen Dubing , Shen Yuming , Zhang Haofeng , Torr Philip H.S.
Published: June 2023

Recent research on Generalized Zero-Shot Learning (GZSL) has focused primarily on generation-based methods. However, current literature has overlooked the fundamental principles of these methods and has made limited progress in a complex manner. In this paper, we aim to deconstruct the generator-classifier framework and provide guidance for its improvement and extension. We begin by breaking down the generator-learned unseen class distribution into class-level and instance-level distributions. Through our analysis of the role of these two types of distributions in solving the GZSL problem, we generalize the focus of the generation-based approach, emphasizing the importance of (i) attribute generalization in generator learning and (ii) independent classifier learning with partially biased data. We present a simple method based on this analysis that outperforms SotAs on four public GZSL datasets, demonstrating the validity of our deconstruction. Furthermore, our proposed method remains effective even without a generative model, representing a step towards simplifying the generator-classifier structure. Our code is available at https://github.com/cdb342/DGZ.
Tracking and Reconstructing Hand Object Interactions from Point Cloud Sequences in the Wild
Authors: Chen Jiayi , Yan Mi , Zhang Jiazhao , Xu Yinzhen , Li Xiaolong , Weng Yijia , Yi Li , Song Shuran , Wang He
Published: June 2023

In this work, we tackle the challenging task of jointly tracking hand object poses and reconstructing their shapes from depth point cloud sequences in the wild, given the initial poses at frame 0. We for the first time propose a point cloud-based hand joint tracking network, HandTrackNet, to estimate the inter-frame hand joint motion. Our HandTrackNet proposes a novel hand pose canonicalization module to ease the tracking task, yielding accurate and robust hand joint tracking. Our pipeline then reconstructs the full hand via converting the predicted hand joints into a MANO hand. For object tracking, we devise a simple yet effective module that estimates the object SDF from the first frame and performs optimization-based tracking. Finally, a joint optimization step is adopted to perform joint hand and object reasoning, which alleviates the occlusion-induced ambiguity and further refines the hand pose. During training, the whole pipeline only sees purely synthetic data, which are synthesized with sufficient variations and by depth simulation for the ease of generalization. The whole pipeline is pertinent to the generalization gaps and thus directly transferable to real in-the-wild data. We evaluate our method on two real hand object interaction datasets, e.g. HO3D and DexYCB, without any fine-tuning. Our experiments demonstrate that the proposed method significantly outperforms the previous state-of-the-art depth-based hand and object pose estimation and tracking methods, running at a frame rate of 9 FPS. We have released our code on https://github.com/PKU-EPIC/HOTrack.
Amodal Instance Segmentation via Prior-Guided Expansion
Authors: Chen Junjie , Niu Li , Zhang Jianfu , Si Jianlou , Qian Chen , Zhang Liqing
Published: June 2023

Amodal instance segmentation aims to infer the amodal mask, including both the visible part and occluded part of each object instance. Predicting the occluded parts is challenging. Existing methods often produce incomplete amodal boxes and amodal masks, probably due to lacking visual evidences to expand the boxes and masks. To this end, we propose a prior-guided expansion framework, which builds on a two-stage segmentation model (i.e., Mask R-CNN) and performs box-level (resp., pixel-level) expansion for amodal box (resp., mask) prediction, by retrieving regression (resp., flow) transformations from a memory bank of expansion prior. We conduct extensive experiments on KINS, D2SA, and COCOA cls datasets, which show the effectiveness of our method.
Take Your Model Further: A General Post-refinement Network for Light Field Disparity Estimation via BadPix Correction
Authors: Chen Rongshan , Sheng Hao , Yang Da , Wang Sizhe , Cui Zhenglong , Cong Ruixuan
Published: June 2023

Most existing light field (LF) disparity estimation algorithms focus on handling occlusion, texture-less or other areas that harm LF structure to improve accuracy, while ignoring other potential modeling ideas. In this paper, we propose a novel idea called Bad Pixel (BadPix) correction for method modeling, then implement a general post-refinement network for LF disparity estimation: Bad-pixel Correction Network (BpCNet). Given an initial disparity map generated by a specific algorithm, we assume that all BadPixs on it are in a small range. Then BpCNet is modeled as a fine-grained search strategy, and a more accurate result can be obtained by evaluating the consistency of LF images in this limited range. Due to the assumption and the consistency between input and output, BpCNet can perform as a general post-refinement network, and can work on almost all existing algorithms iteratively. We demonstrate the feasibility of our theory through extensive experiments, and achieve remarkable performance on the HCI 4D Light Field Benchmark.
Improving Dynamic HDR Imaging with Fusion Transformer
Authors: Chen Rufeng , Zheng Bolun , Zhang Hua , Chen Quan , Yan Chenggang , Slabaugh Gregory , Yuan Shanxin
Published: June 2023

Reconstructing a High Dynamic Range (HDR) image from several Low Dynamic Range (LDR) images with different exposures is a challenging task, especially in the presence of camera and object motion. Though existing models using convolutional neural networks (CNNs) have made great progress, challenges still exist, e.g., ghosting artifacts. Transformers, originating from the field of natural language processing, have shown success in computer vision tasks, due to their ability to address a large receptive field even within a single layer. In this paper, we propose a transformer model for HDR imaging. Our pipeline includes three steps: alignment, fusion, and reconstruction. The key component is the HDR transformer module. Through experiments and ablation studies, we demonstrate that our model outperforms the state-of-the-art by large margins on several popular public datasets.
Tagging before Alignment: Integrating Multi-Modal Tags for Video-Text Retrieval
Authors: Chen Yizhen , Wang Jie , Lin Lijian , Qi Zhongang , Ma Jin , Shan Ying
Published: June 2023

Vision-language alignment learning for video-text retrieval arouses a lot of attention in recent years. Most of the existing methods either transfer the knowledge of image-text pretraining model to video-text retrieval task without fully exploring the multi-modal information of videos, or simply fuse multi-modal features in a brute force manner without explicit guidance. In this paper, we integrate multi-modal information in an explicit manner by tagging, and use the tags as the anchors for better video-text alignment. Various pretrained experts are utilized for extracting the information of multiple modalities, including object, person, motion, audio, etc. To take full advantage of these information, we propose the TABLE (TAgging Before aLignmEnt) network, which consists of a visual encoder, a tag encoder, a text encoder, and a tag-guiding cross-modal encoder for jointly encoding multi-frame visual features and multi-modal tags information. Furthermore, to strengthen the interaction between video and text, we build a joint cross-modal encoder with the triplet input of [vision, tag, text] and perform two additional supervised tasks, Video Text Matching (VTM) and Masked Language Modeling (MLM). Extensive experimental results demonstrate that the TABLE model is capable of achieving State-Of-The-Art (SOTA) performance on various video-text retrieval benchmarks, including MSR-VTT, MSVD, LSMDC and DiDeMo.
DUET: Cross-Modal Semantic Grounding for Contrastive Zero-Shot Learning
Authors: Chen Zhuo , Huang Yufeng , Chen Jiaoyan , Geng Yuxia , Zhang Wen , Fang Yin , Z. Pan Jeff , Chen Huajun
Published: June 2023

Zero-shot learning (ZSL) aims to predict unseen classes whose samples have never appeared during training. One of the most effective and widely used semantic information for zero-shot image classification are attributes which are annotations for class-level visual characteristics. However, the current methods often fail to discriminate those subtle visual distinctions between images due to not only the shortage of fine-grained annotations, but also the attribute imbalance and co-occurrence. In this paper, we present a transformer-based end-to-end ZSL method named DUET, which integrates latent semantic knowledge from the pre-trained language models (PLMs) via a self-supervised multi-modal learning paradigm. Specifically, we (1) developed a cross-modal semantic grounding network to investigate the model's capability of disentangling semantic attributes from the images; (2) applied an attribute-level contrastive learning strategy to further enhance the model's discrimination on fine-grained visual characteristics against the attribute co-occurrence and imbalance; (3) proposed a multi-task learning policy for considering multi-model objectives. We find that our DUET can achieve state-of-the-art performance on three standard ZSL benchmarks and a knowledge graph equipped ZSL benchmark. Its components are effective and its predictions are interpretable.
Neural Architecture Search for Wide Spectrum Adversarial Robustness
Authors: Cheng Zhi , Li Yanxi , Dong Minjing , Su Xiu , You Shan , Xu Chang
Published: June 2023

One major limitation of CNNs is that they are vulnerable to adversarial attacks. Currently, adversarial robustness in neural networks is commonly optimized with respect to a small pre-selected adversarial noise strength, causing them to have potentially limited performance when under attack by larger adversarial noises in real-world scenarios. In this research, we aim to find Neural Architectures that have improved robustness on a wide range of adversarial noise strengths through Neural Architecture Search. In detail, we propose a lightweight Adversarial Noise Estimator to reduce the high cost of generating adversarial noise with respect to different strengths. Besides, we construct an Efficient Wide Spectrum Searcher to reduce the cost of adjusting network architecture with the large adversarial validation set during the search. With the two components proposed, the number of adversarial noise strengths searched can be increased significantly while having a limited increase in search time. Extensive experiments on benchmark datasets such as CIFAR and ImageNet demonstrate that with a significantly richer search signal in robustness, our method can find architectures with improved overall robustness while having a limited impact on natural accuracy and around 40% reduction in search time compared with the naive approach of searching. Codes available at: https://github.com/zhicheng2T0/Wsr-NAS.git