bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect Of Audio-Visual Intervention and Cooperative Learning on Keyboard Mastery in Computer Studies Among Junior School Students in Ede, Osun State
Authors:   Lead City University, Ibadan, Nigeria, Adenike Olawale Marufat , Olajumoke Sam-Kayode Christianah ,   Lead City University, Ibadan, Nigeria, Allwell AGADA ,   Federal College of Education(special), Oyo, Nigeria
Published: October 2024

This study examined the effect of audio-visual intervention and cooperative learning on keyboard mastery in computer studies among junior school students in Ede, Osun State. Three, hypotheses guided the study, and a 3×3 factorial quasi-experimental design was adopted which involved pre-test, post-test, non-randomized control and non-equivalent intact groups. The population for the study was all the students in Government Junior Secondary School Two in Ede South Local Government Area, Osun State, Nigeria, which at the time of this study was 965. The sample for the study was 261 from three intact classes; two experimental classes and one control class. Research Instruments consisted of: (i) computer keyboard mastery (CKM), (ii) Video Tutorials, (iii) Interactive Keyboard Simulator (iv) Typing Games and (v) a lesson plan structure provided to facilitate the teaching of computer keyboard mastery. The Computer Keyboard Mastery (CKM) was validated and pilot tested for reliability using Kuder Richardson 20 (KR-20) formula with a result of 0.75 value. Using ANCOVA to test the hypotheses generated for the study, the results revealed that there is a significant main effect of audio-visual intervention on Junior Secondary School Students’ Keyboard mastery level in computer studies in Ede, Osun State (F (1,177) =1137.406, p<0.05, η2=0.865). A significant main effect of cooperative learning exists on Junior Secondary School Students’ Keyboard mastery level in computer studies in Ede, Osun State (F (1,180) =1124.769, p<0.05, η2=0.862). There is a significant interactive effect of audio-visual and cooperative learning intervention on Junior Secondary School Students’ Keyboard mastery level in computer studies in Ede, Osun State (F (1,128) =0.057, p<0.05, η2=0.830). It was recommended that: (i) audio-visual intervention and (ii) cooperative learning should be adopted independently and (iii) in combination of both audio-visual intervention and cooperative learning should be adopted in teaching and learning of computer keyboard mastery at the Junior Secondary Schools for effectiveness.
Educational Technology and e-Learning
Authors:   Yash College of Education, Rurkee, Haryana, Anita Anita
Published: October 2024

This research investigates the historical development, current patterns, and effects of educational technology and e-learning on student involvement, motivation, and academic performance. Its objective is to pinpoint the obstacles and limitations in implementing these technologies and offer suggestions for their successful integration into educational frameworks. Using a qualitative research methodology, the study encompasses an extensive review of existing literature and case study analysis. Information was gathered from academic sources, educational documents, and official websites, with thematic analysis highlighting key issues and trends. Findings reveal that educational technology and e-learning have greatly transformed education, providing numerous advantages alongside challenges that must be addressed. The study offers valuable insights and practical advice for educators and policymakers, such as investing in infrastructure, improving digital literacy, promoting inclusive practices, adopting student centered teaching methods, and ensuring privacy and security, to enhance educational practices through technology.
Psychosocial Impact of Covid-19 Pandemic on Women’s Mental Health
Authors:   NIILM University Kaithal, Haryana, Kumar Sandeep , Simran Simran ,   Imperial College, Hisar, Haryana
Published: October 2024

Women mental health and impact of psychosocial factors on it, is highlighted in various psychological & clinical studies, due to pandemic made it a matter of more focus. Studying the long-term impacts of the coronavirus on society, our mind, body and its analysis perhaps will take more time. Out of the total population, a number of people felt a disrupted sleep as a hallmark of the pandemic, and suffered from depression, insomnia, irritability, violence including domestic violence, distress, work pressure due to online culture of work, and other related negative mental health symptoms as idiosyncratic attributes especially in covid sufferers. Covid-19 pandemic has altered family dynamics. More screen time, unended & fluctuated routines, for working women dissolving boundaries in workplace and personal life altered & flicking habits, all impacted mental health adversely. The human brain is evolved to live in social groups & wired for social interactions, epidemiological studies conducted on covid survivors, convalescents & victims shows altered brain biochemistry due to various psychosocial factors including financial losses, social isolation, intimate partner’s negative mental state, discrimination, disrupted sleep & routines, etc. Pandemic might has altered the romantic and loving relationships, and adversity of such psychosocial factors impacted people. Psychological strengths and resilience mainly depend on social determinants like social support, social culture, respect, engagement at workplace, parenting style in childhood & emotional attachment, society & family bonds, self-regulation & behavior controlling, and collective efficacy, all these determinants are positively associated with self-esteem that have direct impact on enhancing psychological strengths. Population for the study as participants were females in early adulthood & studying, professional and housewives. For data analysis, the statistical tools, descriptive, co-relational and regression analysis is used. The study focuses on effect of adverse aspects of adversity like pandemics financial crises like job losses, allowances or salary deductions, led to economic abuses, and somewhere gender discrimination, sexual abuse, household workload, escalation in family members expectations and responsibilities, adverse impact of these psychosocial factors on women’s mental health and role of education, knowledge, skills, and aptitude i.e. abilities & cognitive competencies in coping and managing the adversities like pandemic.
Empowering Crisis Response Efforts: A Novel Approach to Geolocating Social Media Images for Enhanced Situational Awareness
Authors: Firmansyah Hafiz Budi , Fernandez-Marquez Jose Luis , Mulayim Mehmet Oguz , Gomes Jorge , Ribeiro Joao , Lorini Valerio
Published: October 2024

Social media and online platforms play an important role in assessing the impact of a natural disaster, especially in the immediate aftermath of the event. The information from social media demonstrated the potential to accelerate the response to a crisis. Locating social media images is critically important to help the victims immediately,  mobilize community support, and provide enhanced situational awareness. However, finding the location of relevant social media images still challenges humans and computational processes.
This study introduces a social media image classifier aimed at enhancing crowdsourced geolocation. The model is trained using data annotated by experts in disaster risk management. Its main goal is to reduce the difficulty of geolocating images by detecting those that are ``easy'' to geolocate. We combined the classifier with an ad-hoc crowdsourcing platform and tested it with pictures posted during a crisis. The experimental results indicate that the proposed approach speeds up the geolocation process of social media images while increasing the level of location precision
Homophily in opinion networks affects collective risk perception in heterogeneous populations
Authors: Giardini Francesca , Vilone Daniele , Zino Lorenzo , Cao Ming
Published: October 2024

Understanding how to accurately inform the population about the risks of disasters is key for the well-functioning of our societies. Risk communication is also an essential feature of the disaster cycle, fundamentally contributing to preparedness but also to management. Here, we use an agent-based model (ABM) to investigate such an important problem. Specifically, we study the emergent behavior of a population of individuals who revise their opinion on therisk of a certain event, based on information received from an institution, processed through individual sensitivity, and discussed with peers. Such a complex process may include several biases, e.g., due to heterogeneous risk perception across the population, and homophily, i.e., tendency of individuals to interact with like-minded people.Our ABM, which encapsulates these crucial features, allows us to perform a campaign of numerical simulations towards gaining mathematically-grounded insights into their impact on the emergent behavior of the population and, ultimately, on how accurately institutional information is received and processed by a population. Such insights can be useful to design empirical studies to test them and, in case of empirical support, to use them to design recommendations for policy decision makers.
A Study on The Heterogeneity of Tropical Cyclone Vulnerability Functions in Different Provinces along The Coastal Areas in China
Authors: Pan Chenning , Ni Xiaoyong , Shen Xifan , Peng Ziyi
Published: October 2024

Coastal regions in China have long been plagued by tropical cyclone (TC) disasters, and TC vulnerability function for disaster-bearing bodies is a widely used quantitative vulnerability assessment method in face of TCs. TC vulnerability functions may vary across different regions due to geographical heterogeneity, hindering this method from universal use. This study systematically collects a 15-year-long dataset from 12 provinces in China. Six alternative TC vulnerability functions are comprehensively investigated by province, and a library of the optimal TC vulnerability functions for three kinds of disaster-bearing bodies, that is, economic, population, and crop in different provinces is developed. The heterogeneity of TC vulnerability in different provinces along the coastal areas in China is then thoroughly analyzed. This paper provides a deeper understanding of the spatial heterogeneity characteristics of disasters and disaster-bearing bodies, and provides good references for local departments to carry out more targeted disaster prevention and reduction work.
Human Values for Responsible Decision-Support for Fire Services
Authors: Mioch Tina , Aldewereld Huib , Neerincx Mark A.
Published: October 2024

Artificial Intelligence systems are more and more being introduced into first response; however, this introduction needs to be done responsibly. While generic claims on what this entails already exist, more details are required to understand the exact nature of responsible application of AI within the first response domain. The context in which AI systems are applied largely determines the ethical, legal, and societal impact and how to deal with this impact responsibly. For that reason, we empirically investigate relevant human values that are affected by the introduction of a specific AI-based Decision Aid (AIDA), a decision support system under development for Fire Services in the Netherlands. We held 10 expert group sessions and discussed the impact of AIDA on different stakeholders. This paper presents the design and implementation of the study and, as we are still in process of analyzing the sessions in detail, summarizes preliminary insights and steps forward.
Forced Displacement Situation Awareness with Large Language Models: Ukrainian Refugees in Poland Case Study
Authors: Tomaszewski Brian , Shakhovska Nataliya , Emery Harley , Śniatała Paweł
Published: October 2024

We evaluated the utility of the large language model (LLM) ChatGPT to develop situation awareness related to the forced displacement of Ukrainian refugees into Poland. Utilizing text messages derived from the Help for Ukrainians in Poland Telegram message group, we used ChatGPT to translate messages in multiple languages into English and identify message topics and themes. Topics and themes from beginning of the war in Ukraine in 2022 were analyzed and visualized using K-means clustering and word clouds. The language identification and translation capabilities of the LLM were evaluated by two human evaluators and measured using Kappa (0.86) and BLUE scores (0.46) with the LLM performing effectively. We conclude that the ability of LLM using carefully developed language prompts for large data volume analysis with no need for manual human analysis shows promise for humanitarian analytics focused on rapidly identifying potential key trends, needs, and locations of displaced people.
Understanding Crisis Preparedness: Insights from Personal Values, Beliefs, Social Norms, and Personal Norms
Authors: Haunschild Jasmin , Burger Felix , Reuter Christian
Published: October 2024

In disasters and crises, crisis preparation at the household level is crucial for societal resilience. However, motivating citizens to take personal responsibility and to implement preparedness measures remains challenging. This study investigates the impact of values, beliefs and norms on preparedness. Through a survey in Germany on resource-oriented crisis preparedness and participants’ values, a group of more prepared and less prepared individuals was differentiated. We quantitatively analyzed the correlation between values and crisis preparedness. A quantitative analysis revealed a significant association between the value of benevolence and higher preparedness. Follow-up interviews (N=30) explored participants' beliefs and norms, showing minimal group differences. Although crisis preparedness is generally viewed positively, strong negativity exists towards perceived “hoarders”. The study discusses implication for crisis communication and the design of nudges and persuasive systems, emphasizing intervention that can trigger benevolence to foster preparedness and appeal to the social benefits to counter the narrative of anti-social crisis preparedness.
Knowledge on demand: the future of decision support systems?
Authors: Chasseray Yohann , Congès Aurélie , Fertier Audrey , Barthe-Delanoë Anne-Marie
Published: October 2024

The availability and quality of the information system supporting crisis management depends on the existence of up-to-date, comprehensive and reliable knowledge bases, despite the multidisciplinary nature of the information to be exchanged, the actions, and the decisions to be taken. This article proposes a method to benefit from pre-trained language models to automatically update these knowledge bases at both design time and run time. We offer a model-based extraction process and a dedicated automated validation process. These two contributions are illustrated and discussed around a case study: an emergency decision support system used to prepare for and respond to an unexpected mass gathering at an abandoned French aerial base.
Food grade nanostructures of pumpkin leaves protein/pullulan blend as a potential carrier for cobalamin
Authors: Salević-Jelić Ana , Knežević-Jugović Zorica , Bugarski Branko , Marković Smilja , Nedović Viktor , Đorđević Verica , Balanč Bojana
Published: October 2024

Nowadays, nanostructures made of biopolymers, such as proteins and polysaccharides, have gathered the growing attention of food scientists. In this study, pumpkin leaves from field crop side streams were processed to produce the protein isolate. The leaf protein isolate was investigated given the ability to encapsulate cobalamin (vitamin B12) in a blend with pullulan by electrospinning method. The starting blend solutions were characterized regarding the key factors that influence the formation of the fibers: viscosity, charge density carried by the jet, and surface tension. The results showed that the addition of the protein isolate (1% w/v) increased the conductivity of the pullulan solution (5% w/v), from 0.163 mS/cm to 1.420 mS/cm and the viscosity from 1.74±0.07 to 8.34±0.09 mPas. Cobalamin (at a concentration of 0.3 mg/mL) decreased the conductivity (0.978 mS/cm) and slightly increased the surface tension and viscosity of the final solution. SEM micrographs showed the formation of beads-on-fiber structures after the electro-hydrodynamic processing of the solutions. The protein caused the reduction of the beads compared to the beads obtained from neat pullulan (176.68 nm vs. 357.52 nm), while the mean fiber diameter was not affected (~22.5 nm). The combination of biopolymer pullulan and protein-rich pumpkin leaf extract has shown the properties of a potential carrier for the model vitamin.
The impact of pain intensity on the functional ability of patients with rheumatoid arthritis
Authors: Karadžov-Nikolić Aleksandra
Published: October 2024

Introduction: Rheumatoid arthritis is a chronic autoimmune inflammatory disease with progressive joint damage, leading to functional impairment of the locomotor system, including disability. Aim: The study aimed to examine the correlation between disease severity, pain intensity and functional capacity of patients with rheumatoid arthritis (RA). Material and methods: An observational, analytical, cross-sectional study that included 30 adult (≥ 18 years) subjects, who had been suffering from RA for two years or more. Data were collected by interviewing subjects, clinical examinations, using available medical documentation and specific questionnaires that are applied in RA. We determined the current disease activity (severity) using the Clinical Disease Activity Index, CDAI. To assess functional (in)capacity, we used the Health Assessment Questionnaire (HAQ). A Visual Analogue Scale (VAS) was used to assess the intensity of pain, which classifies the intensity of pain from 0 to 10. Descriptive statistical methods, methods for testing statistical hypotheses and methods for testing addiction were used for statistical data analysis. Statistical hypotheses were tested at a statistical significance level (alpha level) of 0.05. Results: Out of a total of 30 subjects, 13.3% were male and 86.7% were female. The average age of the subjects was 58.9 ± 8.0 years. In terms of occupation, the majority were retirees, and in terms of education, most subjects had a secondary vocational education. The average duration of the disease was 14 years. Our subjects most often had low and moderate disease activity (33.3% each). Regarding pain intensity, most participants experienced moderate pain (43.3%), the fewest had mild pain (26.7%), and 30.0% of participants reported severe pain. The VAS pain score median of all subjects was 5. The most common was a moderate to severe disturbance of functional ability (56.7%). It was found that there was a statistically significant association between pain intensity and functional disability (rs = 0.618; p = 0.001). There was also a statistically significant association between the degree of disease activity (CDAI) and functional disability (HAQ) (rs = 0,377; p = 0,040). No statistically significant correlation was shown between the duration of the disease and the degree of functional disability (rs = -0.037; p = 0.845). Conclusion: It is necessary to pay special attention to the treatment of pain in patients with RA, because its presence and intensity are closely related to the degree of functional disability.
Diclofenac: The impact of different routes of administration on the efficiency of the drug
Authors: Kvolik Slavica
Published: October 2024

Diclofenac is a non-steroidal anti-inflammatory drug, which has been on the market for many years. During its clinical use, it has been confirmed as an effective analgesic for the treatment of acute post-traumatic pain, postoperative pain, and chronic pain conditions such as chronic back pain and rheumatoid arthritis. In addition to its analgesic effects, it has also been confirmed as an anti-inflammatory drug and antipyretic. Diclofenac is available on the market in various formulations that allow for its systemic use intravenously, intramuscularly, orally, rectally, or topically on the skin and mucous membranes. This review article aims to present the main methods of diclofenac administration and the results of some studies comparing its efficacy with other non-steroidal anti-inflammatory drugs. The most common side effects and strategies for avoiding them are also presented.
The mediating role of the glass-ceiling phenomenon in the relationship between career opportunities and employee engagement within the hospitality
Authors: Lukić-Nikolić Jelena , Labus Pero
Published: October 2024

Purpose - The main purpose of this paper is to examine and analyze the relationship between career opportunities and employee engagement, as well as the mediating effect of the glass-ceiling phenomenon within the hospitality. Methodology - Beside desk research, this paper employs the empirical research undertaken by use of a specially prepared online questionnaire. Research was conducted between October 2023 and April 2024 with participation of 567 women employed in the hospitality, while proposed relationships were tested by using the partial least squares method for structural equation modeling (PLS-SEM, SmartPLS software). Findings - The research results showed the existence of a positive relationship between broken glass-ceiling and employee engagement, that career opportunities are positively related to employee engagement and elimination of the glassceiling effect, and that the glass-ceiling effect mediates the relationship between career opportunities and employee engagement within the hospitality. Implications - This is one of the first studies which addresses the topics of glass-ceiling, career opportunities and employee engagement in the hospitality by using specific methodology (questionnaire and PLS-SEM). The research findings may be used as a basis for decision making process for retaining employees in the hospitality on the long run by eliminating glass-ceiling effects, improving career opportunities and employee engagement.
The state and perspectives of the Zlatibor rural tourism development from the aspect of sociological indicators of sustainability
Authors: Stojanović Emilija , Vujko Aleksandra , Knežević Miroslav
Published: October 2024

Through the examination of social phenomena within a community, sociological indicators of sustainability represent an important area for tourism. The work is based on the analysis of answers in survey of the local population of the municipality of Čajetina regarding the development of tourism on the mountain and the impact that tourism has on the local population. The aim and purpose of the research is to examine and determine the impact of sociological indicators of sustainability on the development of tourism itself, using the example of Zlatibor. Indicators are means used to select existing information and collect new data on a specific topic that is examined through the work. Sociological indicators represent the integrity of the local community from the aspect of the subjective well-being of the local population in the tourist destination. Based on the conducted research and survey results, the importance and application of sociological indicators of sustainability will be determined on the example of rural tourism in Zlatibor. The conclusion is that the development of tourism has a positive effect on the local population, which represents a "push-up" effect of the further development of rural destinations.
Forensics of network attacks: Analysis of techniques, simulations and program solutions for protection
Authors: Salkić Hadžib
Published: October 2024

This paper explores the application of programming code in computer network forensics, with a focus on methods for collecting, analyzing and preserving network data. We discuss various techniques and tools for detecting network threats, monitoring network traffic, and identifying anomalies that may indicate security incidents. The goal is to show how programming code can improve the efficiency of forensic investigations and enable more accurate analyses.
Toplumsal İklim Krizi Algısının İklim Politikaları Üzerindeki Etkisi
Authors: Tan Gülcan Duygu
Published: October 2024

Son yıllarda gerçekleşen doğal felaketlerin artışı, bölgesel aşırı yağışlar, yangınlar ve kuraklık gibi faktörler, iklim krizinin toplum gözünde bir uyarı niteliğinden çıkarak somut bir gerçek halini almasına neden olmuştur. Bireyler önceki on yıllara oranla çok daha sık bir biçimde doğa olayları ve doğal felaketlerle yüzleşmiş veya bunları iletişim teknolojileri vasıtasıyla izleme, gözlemleme şansı yakalamıştır. Buna bağlı olarak, iklim krizinin varlığına ve insan kaynaklı olduğuna dair şüphelerin önemli ölçüde azaldığı görülmektedir. Bu çalışmada, küresel ısınmanın neden olduğu iklim krizinin varlığının artık küresel ölçekte ve toplumsal anlamda kabul edilmesinin doğurduğu ve yakın gelecekte doğuracağı tahmin edilen sonuçlar irdelenmektedir. Çalışma toplumsal kriz algısının gelişmesi sonucu kamu yönetiminden aksiyon beklentisinin artacağını ileri sürmektedir. Çalışmanın amacı kamu tarafından izlenen ve geliştirilmesi planlanan iklim politikalarının toplumsal taleple ne derecede örtüşeceğinin irdelenmesidir. Nedenleri yüzyıllara dayanan bir sorunun kısa erimli ve kolay bir çözümü olmayacağı açıktır. Çalışma, toplumsal taleplerin karşılanması pahasına çözüm odaklı politikalardan uzaklaşılmaması gerektiğini ileri sürmektedir. Uzun vadeli, bilimsel veriler ışığında, katılımcı ve kararlı politikaların benimsenmesi ve kararlılıkla uygulanmasının gerekliliği ortaya konulmaktadır. Çalışmanın önemi iklim krizine yönelik yeni ortaya çıkan eko-kaygı ve eko-keder gibi kavramları siyasal bilimler perspektifinden ele almasıdır. Bu konuda uluslararası yayınlar son birkaç yılda artmakta olsa da Türkçe literatürde konunun henüz yeterince çalışılmadığı görülmektedir.
Challenges in Maintaining Quality Assessments in Higher Learning Institutions: Experiences from Selected Tanzanian Universities
Authors: Meney Deodath
Published: October 2024

This study was conducted to assess the extent to which universities in Tanzania ensure quality in assessments and identify challenges facing the whole assessment process. Literature showed a poor linkage between university graduates and industry whereby some graduates were reported to be lacking essential skills expected of them beside of having good results. This situation motivated the researcher to conduct this study being guided by TQM theory. The study adopted a convergent parallel design which allowed a collection of both qualitative and quantitative at a go. The study targeted lecturers, examination officers, heads of departments and quality assurance directors from universities offering teacher education in Tanzania. Stratified convenience and purposeful sampling techniques were used to select 48 lecturers, 4 examination officers, 4 heads of departments and 4 quality assurance directors from four universities. Questionnaires and in-depth interview guides were used to collect data. Quantitative data were analyzed in frequencies and percentages while the analysis of qualitative data was done in themes and its presentation was done narratively being supported by direct quotations. The study found out universities to be striving to improve quality in final examinations but doing less in formative assessments. Large classes and workloads on the other side were found to be the challenges facing the assessment process. The study recommended for universities to extend the moderation process to the continuous assessments and develop policies that will make lecturers maintain quality in the assessment process.
The Role of Workplace Communication on Employees’ Performance in Tanzania: A Case of Tanzania Electric Supply Company (TANESCO)
Authors: Rodrick Filbert
Published: October 2024

Effective workplace communication is pivotal in enhancing employee performance, particularly in today's global business environment characterized by diversity and remote work dynamics. This study aimed to examine the role of workplace communication on employee performance within Tanzania Electric Supply Company Limited (TANESCO), focusing on how communication influences job correctness, decision-making, planning, and overall employee productivity. The study utilized a descriptive research design to collect data. A total of 36 participants were sampled using simple random. Data were gathered through questionnaires and analyzed using SPSS for quantitative data insights. The findings indicate a significant correlation between effective communication and enhanced employee performance. Specifically, open communication with supervisors was strongly linked to increased job correctness and performance (mean = 4.81). Communication was also found to facilitate decision-making and planning (mean = 3.53), and there was a recognized relationship between effective communication and overall employee performance (mean = 3.97). However, the traditional top-down communication approach was noted, with a mean score of 3.65, suggesting areas for improvement in adopting more inclusive communication practices. The study confirms the critical role of effective workplace communication in enhancing employee performance at TANESCO. Open and transparent communication, particularly with supervisors, significantly contributes to job accuracy and employee productivity. The study recommends that TANESCO implements structured programs to foster open dialogue, develops comprehensive communication strategies that balance hierarchical and inclusive approaches, and invests in regular training and assessment of communication practices. Additionally, adopting an 'open door' policy and engaging in active listening are suggested to enhance the communication framework within the organization.
O mordomo do poeta: o processo de invisibilização do artista plástico Luiz Raphael Domingues Rosa, guardião da memória de Augusto dos Anjos
Authors: Ferreira Leonardo Gonçalves , Julião Letícia
Published: October 2024

Este artigo discute o papel decisivo desempenhado pelo artista plástico Luiz Raphael Domingues Rosa (1945-2007) no processo de identificação do poeta paraibano Augusto dos Anjos (1884-1914) como patrimônio da cidade de Leopoldina, Minas Gerais. É analisada sua atuação como colecionador do poeta e da própria história de Leopoldina, tanto quanto a apropriação que faz da casa onde Augusto dos Anjos residiu naquela cidade, em 1914, ao lhe conferir o sentido de memorial, inaugurando ali “Espaço dos Anjos”, em 1983. O “Espaço dos Anjos” funcionou como um misto de museu, ateliê e escola de arte, encerrando suas atividades em 2007 com a morte de Luiz Raphael. A casa foi reaberta ao público em 2012, sob a gestão da administração municipal, como “Museu Espaço dos Anjos”, exibindo exclusivamente o acervo do poeta paraibano. Neste momento de transição, em que se opera a institucionalização do museu dedicado a Augusto dos Anjos, se observa um processo de apagamento da figura do colecionador Luiz Raphael, fato que é problematizado considerando a hipótese de ser resultado de preconceitos em relação ao artista, seja pela sua persona dissidente ou por sua atuação artístico-cultural insurgente.
Arquivos: relações de poder e sensibilidades
Authors: Artières Philippe , Borges Viviane , Salla Fernando
Published: October 2024

Philippe Artières é historiador e pesquisador do CNRS no Institut Interdisciplinaire d’Anthropologie du Contemporain (IIAC) da École des Hautes Etudes en Sciences Sociales (EHESS). Defendeu sua tese de doutorado em 1996 sob a orientação de Michelle Perrot e desde então tem se dedicado ao estudo dos escritos ordinários de pessoas comuns dos séculos XIX e XX. Presidente do Centro Michel Foucault desde 1995, é um dos maiores especialistas no pensamento foucaultiano. Os “arquivos” tornaram-se seu objeto de estudo, e especialmente as práticas arquivísticas comuns dos anônimos, que ele chamou de “arquivos menores”. Dedica-se à história contemporânea da escrita, investigando as diferentes formas de escrever a história, em colaboração com outros colegas. Seus estudos problematizam a relação entre narrativa histórica e literatura, a extensão das fontes à escrita autobiográfica e o trabalho de alguns pesquisadores que experimentam outras formas de escrever a história: narrativa, experiências de escrita, publicação de arquivos, exposições e documentários radiofônicos.
Folias de Reis: entre recortes e colagens
Authors: Martins Fábio , Duarte Ana Helena da Silva Delfino
Published: October 2024

O presente ensaio visual é resultado de um processo de pesquisa realizado entre os anos de 2004 e 2008 no curso de Artes Visuais da Universidade Federal de Uberlândia, cuja temática está atrelada à figura dos palhaços presentes nas Folias de Reis de Carmo do Rio Claro - Minas Gerais. Nesse ínterim, apresenta-se o registro de um trabalho poético-visual pautado na técnica de recortes e colagens em que as representações dos palhaços se constroem intercaladas entre linhas arabescas, tecido chitão, elementos florais, instrumentos musicais e outros adereços presentes nessas manifestações de religiosidade popular. Contexto de distintos cruzamentos entre materialidades, procedimentos e suportes expandem-se até o momento sublime de encontro entre os trabalhos artísticos e sua fonte de referência imagética-cultural, as Folia de Reis.
Modeling and optimization of two-stage emergency supply chain network under uncertain environment
Authors: Hai Dong , Xiuxiu Gao , Mingqi Wei
Published: October 2024

In order to formulate an effective emergency supply chain network planning scheme, improve the efficiency of emergency organization rescue and realize the reasonable allocation of resources and materials, considering the uncertainty of supply and demand, a distribution mode combining multiple transportation modes is adopted, and the optimization objectives are to minimize network response time, cost and carbon emissions. A two-stage emergency supply chain mixed integer programming model is constructed. At the same time, an adjustable robust optimization model is constructed based on robust optimization theory to enhance the network's ability to cope with uncertain factors, and the constraints with uncertain parameters are transformed through linear duality theory. In order to improve the solution effect of the model, an optimize cuckoo search (OCS) algorithm is proposed, and a benchmark example is introduced to verify the superiority and applicability of the OCS algorithm in solving multi-objective functions. Finally, the emergency material distribution data during the COVID-19 epidemic in Wuhan is used to study the emergency supply chain network decision-making problem with uncertain parameters, and the effective suppression of the robust control coefficient on uncertain disturbances is proved through sensitivity analysis.
Construction of virtual test scenarios for intelligent car-pedestrian interaction
Authors: Hongyan Guo , Jiaming Zhang , Jun Liu , Yunfeng Hu
Published: October 2024

Aiming at the needs of intelligent car and pedestrian interaction testing under urban conditions, this paper proposes a scenario generation method that comprehensively considers the frequency of scenarios in the real world and the degree of challenge to human-vehicle interaction performance. First, according to the key features of intelligent car and pedestrian interaction, the original scene data of pedestrians crossing the road is extracted from the natural driving dataset; then, according to the needs of accelerated testing, a key scenario extraction method based on importance sampling theory is designed to extract and construct important scenarios for intelligent car-pedestrian interaction testing from the original scenes; finally, by comparing the data distribution of important scenarios with original scenarios, it is shown that this method can effectively screen out scenarios that may challenge safety performance during driving, thereby realizing accelerated testing, while taking into account the statistical characteristics of the test scenarios.
Visual object detection model integrating deep active learning
Authors: Yudong Cao , Zhenlin Liao , Lu Chen , Xu Jia
Published: October 2024

The perception of surrounding objects by vehicle autonomous driving is an important means to ensure traffic safety. Object detection models based on deep learning are widely used, but they require a large amount of labeled data for training. This paper proposes an active visual object detection model that uses Gaussian mixture distribution to estimate the uncertainty of unlabeled images, reducing the dependence of model training on labeled data. First, a mixed density network is used as the detection head, and the image features extracted by the deep neural network are used as input to estimate the probability distribution of the classification and positioning of the target prediction box. Secondly, the classification score value of the target prediction box is mapped to the probability space, and the classification uncertainty of the target is calculated using the edge uncertainty; the positioning uncertainty of the target is measured using the prediction box positioning variance. Finally, the most unstable samples are selected for labeling. Compared with other typical active learning sampling strategies on the VOC dataset, the proposed method achieves the best performance, and the 54%data annotation amount can reach the performance of YOLOX supervised learning 98.8%, saving nearly 45% of the data annotation amount.
Modeling of CNC machine tool line rail assembly accuracy and its control method
Authors: Zhifeng Liu , Jimin Chen , Wong Philip , Davis Jessica , Xing Yan
Published: October 2024

Aiming at the linear guide assembly process, due to the preload load caused by the assembly deformation mechanism is not clear resulting in the guide assembly straightness is difficult to predict the problem. In this paper, based on the establishment of linear guide assembly deformation model, the ideal and actual conditions of the guide assembly deformation is discussed. Secondly, considering the influence of manufacturing error of the guide rail mounting surface on the guide rail assembly accuracy, it puts forward the integrated assembly deformation and manufacturing error of the guide rail assembly straightness error prediction model, and puts forward the control method of the guide rail assembly accuracy based on the assembly deformation and the inverse repair manufacturing error. Finally, the experimental bench is built and the accuracy of the theoretical model and accuracy control method is verified through experiments , and the results show that the straightness error of the guideway assembly is reduced by .
Characteristics analysis and safety evaluation of vehicles turning over long distances
Authors: Zhaowei Qu , Lin Li , Yongheng Chen , Changjian Wu
Published: October 2024

In order to explore the motion and safety characteristics of the U-turn vehicles at long-range U-turn intersections, based on the measured data of the U-turn vehicles at typical locations, we analyzed the characteristics of the U-turn vehicle's trajectories and traffic parameters with the help of probability theory and statistical knowledge, and established the U-turn trajectory model. We used Traffic Conflict Technology (TCT) and take Post Encroachment Time (PET) as the indicator to study the feature of vehicles security of - turn vehicles. Three conclusions are drawn from this study. First, there is a significant difference in the headway between long-range -turn vehicles and those at intersections without opening: the stability of the headway of long-range -turn vehicles is weak, and the release of vehicles is seriously disturbed by the turning flow; Secondly, when turning around at a long interval u-turn intersection, the starting position of vehicle turning is dispersed and the distribution of U-turn trajectories is quadratic distribution. Third, the setting of long interval turning lanes will increase the interference between traffic flows at intersections, thus increasing the number of conflicts with vehicles in the opposite direction. Cross-conflict accounts for the majority of conflicts in long interval U-turn intersections, and rear-end collision is the main conflict type in U-turn intersections without opening. The above research conclusions are helpful to improve the safety of long interval U-turn intersections.
Adaptive content-aware spatial regularized correlation filter tracking algorithm
Authors: Fasheng Wang , Bing He , Fuming Sun , Hui Zhou
Published: October 2024

In order to solve the annoying boundary effects in correlation filter (CF) trackers induced by cyclic shift when sampling training patches, and improve the tracking performance, an adaptive content aware spatially regularized correlation filter (ACSRCF) is proposed. Firstly, real negative samples are generated from the background area around the target object, so as to alleviate the filter degradation by the fake negative samples induced from the circularly shifted object patches. Secondly, the locality sensitive histogram (LSH) based foreground feature is extracted and incorporated with the spatial regularization weight which is updated adaptively according to the varied object-oriented appearances. Thereafter, the CF model is optimized using the alternative direction method of multipliers (ADMM) in which the model is decomposed into two sub-problems and the LSH-based features are used in iteration for obtaining the optimal solutions. Finally, the proposed method is evaluated on 5 public benchmarks. The experimental results show that the accuracy and success rate scores of our method on OTB 50 dataset are 90.3%and 66.1%, respectively, exceeding the other CF trackers .The data on the OTB100 dataset is 92.2%and 69.2%, and the accuracy first ranks among all the trackers, while the success rate is ahead of other CF trackers.
Travel pattern recognition of urban rail passengers based on spatiotemporal sequence similarity
Authors: Na Zhang , Feng Chen , Jianpo Wang , Yadi Zhu
Published: October 2024

Understanding passenger travel patterns is helpful for the allocation of passenger resources in urban rail transit. Based on rail transit smart card data, this paper proposes a method to identify travel patterns by modeling individual spatiotemporal sequences. First, all the stations visited by individual passengers are extracted, and the similarity of the stations is calculated by the frequency of inter-station travel, the distance between stations and the activity duration of the stations. The main spatial activity area of the individual is divided using a hierarchical clustering algorithm. Then, the spatiotemporal sequence is inferred based on the individual's travel order. The sequence is a set of discrete values that characterize the spatiotemporal state. PCA-KL and K-Means++ are used to extract the similarity sequence structure to identify the passenger travel pattern. Finally, the rail transit smart card data of Xi'an in a certain month is taken as an example to identify its passenger travel pattern. The results show that complex passenger flow has 5 travel modes, of which 3 typical modes are commuting travel in a macro sense, accounting for 79% of the passenger flow. It can be seen that the pattern recognition based on the similarity of individual spatiotemporal sequences in this paper fully reflects the particularity and versatility of the research method, and is highly operational for different cities.
Facial expression recognition based on convolutional network attention mechanism
Authors: Xingang Guo , Ang Alfredo , Martinez Daniel , Chao Cheng , Ziqi Shen
Published: October 2024

Aiming at the problems of large number of parameters and weak recognition ability in expression recognition, a method of facial expression recognition based on convolutional network is proposed. An improved residual module is introduced to reduce the number of parameters while enhancing the attention to the expression area; the channel-space attention mechanism is used to realize the weight distribution of different dimensions and positions of the expression area extracted by the network, focusing on the subtle difference feature information in the key points of the expression; the detail module is used to further extract the deep feature information. In order to obtain higher accuracy, a joint loss function is introduced to increase the out-of-class distance and reduce the intra-class distance to improve the accuracy of expression recognition. This paper applies this network to the datasets FER2013 and CK+. The experimental results show that the average recognition rate of this algorithm is respectively and 63.91%，97.98%the number of parameters is 11.34 M. Compared with VGG network, residual network, etc., this model not only improves the recognition rate but also reduces the redundant parameters.
TrafficPro: A road speed prediction framework for urban signal-controlled road networks
Authors: Xiaoyue Wen , Guomin Qian , Barros Oscar , Castro Isidora , Dianhai Wang
Published: October 2024

In view of the problem that traditional deep learning models do not consider the active time-varying characteristics of traffic flow (signal control information) when predicting the speed of urban road networks, and have low prediction accuracy, this paper proposes a speed prediction framework based on generative adversarial networks and graph neural networks. In this framework, the generator network simultaneously encodes the road network traffic flow and signal control information through active and passive prediction modules to generate prediction results, and then uses the discriminator network to improve the generalization of the prediction results. This framework can obtain higher prediction accuracy than traditional time series models and deep learning models. In the real road network speed prediction scenario, this framework can reduce the prediction error compared to the best benchmark model 3%-4%.
Analysis of causes of traffic accidents for taxi drivers based on MIMIC and machine learning
Authors: Hengyan Pan , Wenhui Zhang , Tingting Liang , Zhipeng Peng , Wei Gao , Yonggang Wang
Published: October 2024

Through questionnaire survey, information on individual attributes, physical fatigue perception, work pressure, risky driving behavior and traffic accident experience of 2391 taxi drivers was collected. The multi-indicator multi-cause (MIMIC) model was used for path analysis to explore the inducing effect of physical fatigue perception and risky driving behavior on traffic accidents, and to verify the influence of gender, age and work pressure on physical fatigue perception and distracted driving behavior. Four machine learning algorithms, logistic regression, naive Bayes, support vector machine and random forest, were selected to predict taxi accidents. The results show that the increase of physical fatigue perception, negligent driving behavior, aggressive driving behavior and distracted driving behavior can lead to an increase in accident rate, and gender, age and work pressure will affect the frequency of physical fatigue perception and distracted driving behavior. The accident prediction model based on machine learning has excellent effect, among which the random forest has the best prediction effect. The prediction accuracy of using single feature variables "risky driving behavior", "distracted driving behavior" and "physical fatigue perception" is acceptable. When the personal attribute indicators of "work pressure", "age" and "gender" are introduced, the prediction accuracy is further improved.