bluuebunny/crossref_metadata_2025 huggingface dataset:
Princípios de orientação para investigar a própria prática: um modelo para professores da Educação Básica
Authors: Gonçalves Marcel , Ribeiro Alessandro Jacques , Aguiar Marcia
Published: October 2024

Este artículo tiene como objetivo presentar un modelo de principios rectores para que los docentes de Educación Básica realicen investigaciones sobre sus propias prácticas en el aula. El modelo implica el uso de elementos ya presentes en las prácticas docentes comunes (uso de tareas, registros de producciones de los estudiantes y reflexión sobre la práctica), sin embargo, con una propuesta de intencionalidad investigativa que las convierte, a nuestro entender, en prácticas investigativas. Para ilustrar el uso de nuestro modelo de principios rectores, analizamos episodios de práctica genuina de un profesor-investigador que se propuso realizar investigaciones sobre su propia práctica, adoptando la enseñanza exploratoria en sus clases e investigando el concepto de simetría para el álgebra articular y la geometría en una clase de noveno grado de una escuela pública del estado de São Paulo. El análisis de los episodios de la investigación del docente-investigador nos permitió identificar cómo los indicadores presentes en nuestro modelo de principios rectores podrían ser identificados en una investigación de aula, revelando aquellos que tienen potencial para que el modelo sirva a otros docentes. como parámetro para la realización de investigaciones sobre las propias prácticas, favoreciendo la promoción de la sabiduría práctica y el desarrollo profesional a partir de la práctica presencial.
unidade de ensino potencialmente significativa mediada pela sala de aula invertida para ensinar poliedros
Authors: Pereira da Silva Adriana , Nery Ribeiro Tiago , Da Silva Souza Denize , Ricardo Magalhães Andre
Published: October 2024

Poliedros é um objeto de conhecimento da geometria, fundamental ao processo de ensino e aprendizagem de matemática. Para tanto, espera-se que os alunos, ao longo da escolarização, desenvolvam habilidades de visualização espacial, raciocínio lógico e resolução de problemas. Dessa forma, este estudo foi desenvolvido como pesquisa qualitativa e se caracteriza como estudo de caso. É um recorte de uma pesquisa de mestrado que buscou avaliar quais as potencialidades da aplicação de uma Unidade de Ensino Potencialmente Significativa (UEPS) sobre Poliedros em uma turma de Ensino Médio, a partir do trabalho metodológico realizado pela Sala de Aula Invertida. A aplicação ocorreu em uma turma da segunda série do Ensino Médio, no primeiro bimestre de 2023, contando com participação de 14 alunos da rede estadual. Os dados foram produzidos a partir da elaboração, aplicação e análise dos resultados de uma UEPS, considerando, para este trabalho, três das categorias selecionadas, a priori: dimensão tecnológica e recursos aplicados (vídeos, textos, slides, exercícios), atividades diversificadas (games, experimentos de cunho investigativo etc.) e conhecimento dos estudantes sobre Poliedros. Os dados coletados indicam avanços significativos na aprendizagem dos alunos, destacando-se o engajamento, protagonismo, autonomia e a compreensão dos estudantes sobre o tema, para além dos desafios, como a limitação no acesso à internet. Em conclusão, esta pesquisa sugere que a metodologia ativa da Sala de Aula Invertida pode ser uma alternativa eficaz para professores da educação básica minimizarem práticas de ensino tradicional.
Situações para a aprendizagem da prova - em matemática: Estado da pesquisa e questões em aberto
Authors: Balacheff Nicolas , Almouloud Saddo Ag
Published: October 2024

Pesquisas sobre a complexidade epistêmica, lógica e discursiva da aprendizagem de provas têm gerado uma literatura abundante nas últimas duas décadas. Seus resultados contribuem para uma compreensão mais precisa das dificuldades encontradas pelos alunos e do trabalho dos professores. Sustentam a concepção de situações, em particular situações de validação no sentido da Teoria das Situações Didáticas (TSD) (Brousseau,1998), em que a prova funciona como ferramenta de resolução de problemas. No entanto, permanece a dificuldade de apreender a prova como objeto, a fim de reconhecer suas especificidades matemáticas e institucionalizá-la como tal. Este é o problema de que trata este texto. Este texto complementa as apresentações feitas no Seminário Nacional de Didática da Matemática, em 2017, e no [1]CORFEM, em 2019. O objetivo comum a essas três palestras era aprender e ensinar a prova antes da sua introdução [2]como uma forma canônica de prova em matemática. Após uma introdução que recorda o contexto institucional e científico, a primeira parte (secções 2 a 4) é dedicada ao estado da investigação, retomando os relatórios de trabalhos significativos, relacionados com diferentes abordagens; e a segunda parte (secção 5) apresenta propostas para formar uma base para a investigação futura. A conclusão centra-se nas questões abertas pela necessidade de engenharia situacional específica para incentivar e acompanhar a gênese e o reconhecimento dos padrões de prova na sala de aula de matemática, antes do ensino explícito da prova.
A Theoretical Study of Artistic and Mental Experience in the Projection of Art Pedagogy
Authors:   State institution «South Ukrainian National Pedagogical University named after K. D. Ushynsky», Rebrova Olena
Published: October 2024

The monograph examines the essence of artistic mentality, the set of categories through which it is defined: artistic picture of the world, artistic worldview, artistic thinking, interpretation, etc. The essence of these concepts is clarified in the context of mental processes of art education. A set of functions of artistic mentality in the educational process is presented. Cultural, hermeneutical and other approaches to artistic mentality, praxeological and pragmatic approaches to the artistic mentality of the individual, their application in the projection of artistic pedagogy have led to the introduction of the concept of “artistic and mental experience” into scientific circulation. In this regard, the monograph clarifies the basic concepts of “aesthetic experience”, “artistic and aesthetic experience”, “mental experience”. The professional context of artistic mentality allowed us to substantiate the essence and build a component structure of the artistic and mental experience of future teachers and future teachers of artistic disciplines. The second edition is supplemented with a glossary, contains edits, clarifications of some key concepts and phenomena of artistic mentality. The book is addressed to scholars, graduate students, undergraduates, and students of pedagogical and art and pedagogical educational institutions.
Fæðingarferli í sjálfsprottnum leik nokkurra stelpna
Authors: Harðardóttir Guðrún Alda
Published: October 2024

Tilgangur og markmið rannsóknarinnar er að skoða hvernig börn túlka og endurskapa reynslu sína og þekkingu í sjálfsprottnum leik. Um er að ræða tilviksrannsókn sem fór fram í einum leikskóla á höfuðborgarsvæðinu. Rannsóknargögn voru myndbandsskráning. Leitast er við að skilja og túlka leikheim fimm fimm ára stelpna, með áherslu á kyngervi, túlkandi endursköpun, félagslega framsetningu og sameiginlegan spuna stelpnanna í leiknum. Lítið hefur verið rannsakað hvernig ung börn túlka kyngervi og endurskapa slíka þekkingu í leik og hvernig félagsleg framsetning þeirra er þar, líkt og gert er í þessari rannsókn. Niðurstöður sýna yfirgripsmikla þekkingu stelpnanna á viðfangsefninu. Þannig beittu þær mismunandi félagslegri framsetningu í leiknum, svo sem að stjórna á opinn hátt, að stjórna bak við tjöldin og beita fylgjandi framsetningu, og einnig mátti greina áherslur á kvenlæga og karllæga þætti eftir því hvaða hlutverk þær léku
Að byrja í leikskóla
Authors: Pétursdóttir Sigríður Síta
Published: October 2024

Grein þessi fjallar um mikilvægi góðrar aðlögunar og er byggð á áratuga reynslu höfundar, athugunum og uppeldisfræðilegum skráningum um aðlögun með þátttöku foreldra í þremur norskum leikskólum frá 2011 til 2022. Markmiðið er að vekja athygli á mikilvægi aðlögunar við upphaf leikskólagöngu og koma á framfæri ákveðinni leið aðlögunar sem hægt er að fara til að skapa örugg og traust samskipti milli tveggja heima barnsins, heimilis og leikskóla. Fjallað er um mikilvægi þess að byggja upp traust og öryggi strax frá fyrsta degi í aðlögun, um hlutverk umönnunaraðila og áhrif þeirra á félags- og tilfinningaþroska barnanna. Einnig er fjallað um lykilhugtök í aðlögun og þau tengd fræðilega við reynslu höfundar. Sú leið í aðlögun sem hér er lýst, þ.e. að foreldrar eru þátttakendur, er mikilvægur liður í að leggja grunn að góðum og traustum samskiptum milli heimilis og leikskóla og stuðla að vellíðan og öryggi barns við upphaf leikskólagöngu.
Grenndarkennsla og vettangsferðir í nærsamfélagi skóla
Authors: Guðmundsson Bragi , Bjarnadóttir Brynhildur
Published: October 2024

Meginmarkmið þessarar greinar er að skoða hvernig aldagamlar hugmyndir um mikilvægi grenndarnáms í skólum hafa skilað sér inn í menntun kennaranema. Steingrímur Arason var merkur umbótasinni í menntamálum á fyrri hluta tuttugustu aldar. Hann, ásamt fleirum, setti fram skýrar tillögur um mikilvægi þess að í skólakerfinu sé unnið með félagslegt og náttúrulegt umhverfi barnsins og lagði áherslu á útivist og vettvangsferðir í nærumhverfi. Þeim tillögum eru gerð nokkur skil í fyrri hluta þessarar greinar til þess að undirstrika að aðferðir nútímalegs grenndarnáms og grenndarkennslu eru ekki nýjar í íslensku skólaumhverfi. Í seinni hluta greinarinnar er nútíminn viðfangsefnið. Annars vegar er lýsing á nemendaverkefni þar sem sett er fram vettvangsferð fyrir leikskólabörn um nærsvæði Hóla í Hjaltadal og hins vegar lýsing á útikennsluþjálfun kennaranema við HA í námskeiði sem heitir Grenndarkennsla. Báðum lýsingunum er ætlað að opna augu verðandi kennara fyrir þeim ótal tækifærum sem þeir hafa hver í sinni heimabyggð til þess að vinna með þroska nemenda í náttúrulegu, manngerðu og menningarlegu umhverfi. Niðurstaðan er sú að gamlar hugmyndir um mikilvægi grenndarnáms í skólum hafa skilað sér inn í menntun kennaranema nú á dögum.
Að undrast heiminn
Authors: Friðjónsson Ingi Jóhann , Frímannsson Guðmundur Heiðar
Published: October 2024

Í greininni er fjallað um hugmyndir barnaheimspekinnar, hugtökin heimspeki fyrir börn og heimspeki með börnum eru afmörkuð í samræmi við helstu kennismiði. Í framhaldi er fjallað um það hvort barnaheimspeki geti yfir höfuð talist heimspeki. Farið er yfir helstu mótbárur og svör og komist að þeirri niðurstöðu að barnaheimspeki sé heimspeki. Færð eru rök fyrir því af hverju skynsamlegt getur talist að stunda barnaheimspeki í íslenskum leikskólum og fjallað um þann ávinning sem iðjan getur haft í för með sér og rannsóknir hafðar til hliðsjónar. Iðkun barnaheimspeki í íslenskum leikskólum samræmist vel aðalnámskrá leikskóla. Áhersla er lögð á eflingu gagnrýninnar og skapandi hugsunar í menntun ungra barna þar sem virðing er borin fyrir þroska þeirra, reynslu og upplifun.
Assessing And Mitigating The Impact Of Fake News In Nigeria
Authors: Folayan Bolu John , Olubunmi Banjo Bosede , Odenike Omolaso
Published: October 2024

\The high rate fake news - news (presentation) that has been distorted or totally false - in the Nigerian media space is at the moment of concern to communication scholars, journalists, publicists, and political leaders. Like most fake products, fake news is made to look like or to have the characteristics of the original product – magnitude, timeliness, novelty, proximity, etc., thereby having the lethal impact of propaganda. The present study examines the sources, patterns of fake news dissemination, impact of and solutions to fake news in Nigeria. Questionnaires were randomly administered online to 398 heavy users of social media (257 bloggers; 97; regular users of social media who are non-professionals; 37 journalists and 7 others based on their followership ratings. The investigation revealed that most fake news in Nigeria revolve social, entertainment, and religious issues and are reported more often in “text” and “videos” on Facebook, Instagram, and WhatsApp. The main sources of fake news in Nigeria are non-professional journalists and the high rate of fake news has largely been due to the skilful framing by their disseminators, lack of time and skill to fact-check fake news by the audience, and lack of effective enforcement of best journalism practices.
Ultrasonographic approach to visualize the medial shoulder compartment and diagnose medial glenohumeral ligament and subscapularis lesions in dogs
Authors: Porter Ian , Miller Allison , Jennings Carol , Frye Christopher
Published: October 2024

OBJECTIVE

To provide a video tutorial on the diagnostic ultrasound approach to the medial compartment of the canine shoulder and provide comparisons of normal and pathological images with corresponding MRI.

ANIMALS

Dogs undergoing diagnostic ultrasound of the medial shoulder.

METHODS

The medial shoulder was positioned in flexion with external rotation to allow transducer access, clipped, and scrubbed with dilute chlorhexidine. A 2- to 14-MHz linear array probe with a footprint of 50 mm (V8 ultrasound system; Samsung) was used to visualize the medial glenohumeral ligament (MGL), subscapularis, and coracobrachialis with coupling gel, confirmed by cadaveric ultrasound-guided dye injection and dissection. Ultrasound and corresponding MRI were then used to contrast normal anatomy to a live sedated dog with clinical subscapularis tendinopathy and MGL desmopathy. Proton density–weighted MRI sequences (1.5T Vantage Orian; Canon) using a flex coil were able to identify all 3 structures and corresponded to ultrasound findings for normal and pathological anatomy.

RESULTS

Diagnostic ultrasound identified normal and abnormal structures of the medial shoulder (coracobrachialis, subscapularis, and MGL). All imaging correlated well to MRI.

CLINICAL RELEVANCE

Medial compartment disease of the shoulder is a well-described cause of canine lameness, but diagnosis has traditionally relied on MRI or arthroscopy. Prior ultrasound approaches did not distinguish MGL components, failed to consistently identify normal or surgically transected ligaments, and have not been studied in vivo. Our approach is different and can play an important role in diagnosing medial compartment lesions, as it possesses greater anatomical visualization than arthroscopy and is noninvasive, accomplished with sedation, and relatively accessible and affordable.
New Prediction Of Cracks Propagation In Repaired Steel Plate With Bonded Composite Patch At Cyclic Loading
Authors: Maachou Sofiane , Mechab Belaïd , Bouiadjra Bel Abbes Bachir , Salem Mokadem
Published: October 2024

This study presents a numerical prediction of the fatigue life of steel panels repaired by a composite patch. The effect of length cracks, the stress ratio R and properties of the patch is presented. The obtained results show that the bonded composite repair significantly reduces the stress intensity factors at the tip of repaired cracks. The results are in a good agreement with those in the literature. The Monte Carlo method is used to predict the distribution function governing crack propagation in fatigue analysis. In computing the failure probability of the structure, we consider the statistical uncertainty associated with key variables, along with the previously discussed model uncertainty. The results obtained highlight the considerable impact of variations in crack length and stress ratio on the distribution function. Notably, uncertainty in these parameters significantly amplifies the probability of structural failure in plates, thereby diminishing overall structural durability.
Analytical Analysis for Space Fractional Helmholtz Equations by Using The Hybrid Efficient Approach
Authors: Khan Adnan , Liaqat Muhammad Imran , Mushtaq Asma
Published: October 2024

The Helmholtz equation is an important differential equation. It has a wide range of uses in physics, including acoustics, electro-statics, optics, and quantum mechanics. In this article, a hybrid approach called the Shehu transform decomposition method (STDM) is implemented to solve space-fractional-order Helmholtz equations with initial boundary conditions. The fractional-order derivative is regarded in the Caputo sense. The solutions are provided as series, and then we use the Mittag-Leffler function to identify the exact solutions to the Helmholtz equations. The accuracy of the considered problem is examined graphically and numerically by the absolute, relative, and recurrence errors of the three problems. For different values of fractional-order derivatives, graphs are also developed. The results show that our approach can be a suitable alternative to the approximate methods that exist in the literature to solve fractional differential equations.
Mechanical Properties of 3D Printed PLA Scaffolds for Bone Regeneration
Authors: Kundreckaitė Paula , Šešok Andžela , Stonkus Rimantas , Gaidulis Gediminas , Romańczuk-Ruszuk Eliza , Pauk Jolanta
Published: October 2024

The growing interest in biodegradable scaffolds for bone regeneration created a need to investigate new materials suitable for scaffold formation. Poly(lactic acid) (PLA) is a polymer commonly used in biomedical engineering, e.g. in tissue engineering as a biodegradable material. However, the mechanical behavior of PLA along its degradation time is still not explored well. For this reason, the mechanical properties of PLA scaffolds affected by incubation in physiological medium needs to be investigated to show the potential of PLA to be used as a material for biodegradable scaffold formation. The purpose of this research is to determine the mechanical properties of PLA scaffolds before and after incubation, and to apply constitutive material models for further behavior prediction. Two sets of PLA scaffolds were printed by the 3D printer “Prusa i3 MK3S” and sterilized by ultraviolet light and ethanol solution. The first set of specimens was incubated in DMEM (Dulbecco’s Modified Eagle Medium) for 60, 120, and 180 days maintaining 36.5 °C temperature. The mechanical properties of the scaffolds were determined after performing the compression test in the “Mecmesin MultiTest 2.5-i” testing stand with a force applied at two different speed modes. The obtained data was curve fitted with the hyperelastic material models for a model suitability study. The second set of specimens was incubated in PBS (Phosphate Buffered Saline) for 20 weeks and used in a polymer degradation study. The obtained results show that the mechanical properties of PLA scaffolds do not decrease during incubation in physiological medium for a predicted new bone tissue formation period, though hydrolysis starts at the very beginning and increases with time. PLA as a material seems to be suitable for the use in bone tissue engineering as it allows to form biocompatible and biodegradable scaffolds with high mechanical strength, required for effective tissue formation.
Data analysis and modeling study of the relationship between physical activity and sleep disorder intervention for college students
Authors: Shen Delei , Ma Chao
Published: October 2024

Accompanied by the increasing prevalence of sleep disorders among students in colleges and universities, there is an urgent need for colleges and universities to provide a scientific basis and practical guidance for exercise intervention for sleep disorders among students. In this paper, in order to study the relationship between physical exercise and sleep disorder intervention, after analyzing the etiology and pathology of sleep disorders, we first surveyed students of a university in Guangzhou to analyze the differential characteristics of students’ sleep quality under different statistical variables. Then, a logistic linear regression model was established to analyze the influencing factors of college students’ sleep quality by taking the variables with statistically significant results in the one-way analysis as independent variables and college students’ sleep quality as dependent variables. Finally, college students with more serious sleep disorders in the university were subjected to a semester of walking, running, and soccer physical exercise to analyze the role of physical activity in influencing the intervention of sleep disorders in students. It was found that the PSQI scores of the walking group, running group, and soccer group before and after one semester of walking exercise decreased by 2.29, 3.16, and 3.18 points, respectively, and the scores of the rest of the items decreased to different degrees, which reflected the good effect of the physical exercise intervention on the intervention of sleep disorders. Explore the effects of physical exercise intervention on the quality of sleep among college students and provide practical suggestions for improving college students’ sleep quality through exercise.
Evaluating the Teaching Effectiveness of Business English Courses in Colleges and Universities Based on the DPSIR Model
Authors: Wang Ying
Published: October 2024

This paper takes the drive and pressure of teachers and students in the process of English teaching as the basis of evaluation, focuses on the state of the two in the process of teaching and the influence of teaching on teachers and students as well as the feedback of teachers and students on teaching, and constructs a framework for evaluating the effectiveness of business English teaching based on the model of “Drive, Pressure, State, Influence, Response”. After two rounds of expert consultation, the number of evaluation indicators was reduced from 34 to 21. Finally, the evaluation index system was constructed by combining the weight calculation of the hierarchical analysis method. The data show that A3 (state factors) > A1 (driving force factors) > A5 (response factors) > A2 (pressure factors) > A4 (influence factors), and the comprehensive evaluation score of the teaching effectiveness of business English courses in colleges and universities is 3.5944, which indicates that the evaluation grade of the teaching effectiveness of the university is located in the range between medium and good. This study aims to promote digital innovation and reform in the teaching of business English courses in colleges and universities by evaluating their teaching effects.
Semantic Accuracy and Cultural Adaptability in the English-Chinese Translation of Jane Eyre Based on Computational Linguistics and Natural Language Processing Techniques
Authors: Ye Chunbo
Published: October 2024

This paper takes Jane Eyre as an example to study the role of computational linguistics and natural language processing technology on the semantic accuracy and cultural adaptability of English-Chinese translation. We construct an interactive translation system of Jane Eyre, based on the interactive translation model design of computational linguistics and natural language processing technology, to support the application of these technologies in the English-Chinese translation of Jane Eyre. Context-association mapping, semantic retrieval, and semantic ontology structural feature construction methods are employed to evaluate semantic accuracy and cultural adaptability. We empirically analyze the semantic accuracy and cultural adaptability of the English-Chinese translation of Jane Eyre using text data from a Python web crawler. The results show that the semantic accuracy of the English-Chinese translation of Jane Eyre in this paper’s model is the highest compared to SAN (self-attention network) and RNN (recurrent neural network) translation models. Among the 200 students sampled, the translation result achieved a satisfaction rate of 71.5%. The work’s translation of literary sentences is more in line with the effect of Chinese expression, indicating excellent cultural adaptability.
Multi energy complementary optimization scheduling method for wind solar energy storage and charging integrated energy system
Authors: Miao Peng , Hongfei Zhao , Dezhi Dong , Hao Sun
Published: October 2024

IES (The Integrated Energy System), consisting of distributed wind and solar power generation and multiple types of loads for cooling, heating, and electrical systems, is an important application scenario in the current energy configuration. It is not possible to balance multiple objectives like economy, carbon emissions, and wind and solar energy curtailment. Furthermore, there are numerous equipment that have multiple energy flows, complex conversion processes, and multiple scheduling requirements. Therefore, multi-objective optimization and minute-level scheduling strategies are key technologies to improve the utilization efficiency of comprehensive energy systems. This article proposes a comprehensive method for optimizing and scheduling energy systems that is based on multi-objective optimization and multi-time scale decomposition. Firstly, a comprehensive energy system architecture for wind solar storage and charging was constructed, and its operational characteristics were analyzed. Then, a multi-objective optimization scheduling model was established, which comprehensively considered multiple objectives such as system operating cost, minimum carbon emissions, and minimum wind and solar curtailment rate. Through time scale decomposition, the optimization scheduling problem was transformed into multiple subproblems and solved separately. Finally, it was verified through a case study. The simulation results show that the constructed model reduces the total operating cost by 5%, the wind abandonment rate by 7%, and the carbon emissions by 5.6% compared to the system without energy storage and charging piles. This verifies the effectiveness of the constructed model, reduces the system operating cost, and reduces the impact on the environment; compared with the DA-P (Day Ahead Programming), the proposed optimization method reduced the system’s electricity purchase cost by 7.51%, increased renewable energy utilization by 11%, and reduced carbon emissions by 6.1%. This verifies the feasibility of the proposed method in reducing system operating costs, improving system environmental protection, and stabilizing the system.
An improved AO algorithm optimized PID rectification model for wind speed and wind pressure regulation in video cabinet of tobacco sorting machine
Authors: Lu Zhimin , Jiang Lin , Jiang Zhishan , Dong Zixin , Li Huajie , Zhang Wei
Published: October 2024

Sorting and removing impurities is the use of raw materials and light impurities suspended speed differences through the wind to separate the hemp, paper, plastic, and other light materials to remove impurities. Article to tobacco sorting machine video cabinet wind pressure control system principle as a guide, combined with the structure of the sorting and impurity removal machine and the principle of wind speed balance designed to balance the wind speed and wind pressure of the tobacco sorting machine. The control model of wind speed and pressure in the video cabinet system of the tobacco sorting machine is established, and the improved AO algorithm is used for the design of the overall PID controller and optimization of the PID controller’s setting parameters. The IAO algorithm optimizes the parameters of the PID setting controller with a steady state error within 3%, and the introduction of the IAO-PID controller can make the wind speed of the sorting machine system control from 16.4m/s to 11.1m/s within 17ms. When the system detects that the negative pressure of wire feeding changes sharply to about 1.12MPa within 20ms and exceeds the differential pressure start value of 0.9MPa set by the sorter system, the tobacco wire feeding anti-clogging function is activated. The PID controller optimized by the IAO algorithm can achieve precise regulation and control of wind speed and pressure of tobacco sorting machines, improving the sorting efficiency of tobacco production.
Analysis of Film and Television + Professional Cluster Resource Integration Model and Industry Development Dynamics
Authors: Zhang Huixin , Liu Zexi
Published: October 2024

This paper proposes a resource integration model for film and television + professional clusters and builds a corresponding digital platform to realize the effective integration of film and television professional resources. Using XML technology of different modalities of film and television professional resources, the association of film and television professional resources is defined, and a multi-objective integration scheduling algorithm is incorporated to optimize the integration speed to ensure the operational efficiency of the integration model. The integrated film and television professional resources are stored in the digitization platform, the wavelet transform technology is used to decompose the image signals, and the classifiers trained by the learning algorithm and the information entropy are used to complete the classification of film and television professional resources. After applying the design model and platform of this paper in the practical course teaching Film and Television Production for the 2022 undergraduate students majoring in Film and Television Studies at University X, the quality of film and television works created by the students improved by 2.12 and 1.64 in the dimensions of artistry and innovativeness compared with the pre-practice dimension, which showed a significant difference (P<0.05). H Pictures, on the other hand, predicts that in 2024, the cash income security, structural rationality, profitability sustainability, and growth sustainability metrics will improve to 0.6432, 0.9558, 0.00005, 0.4868, and 0.3767.
Computational model design for road to waterway transportation conversion efficiency improvement based on deep learning algorithm
Authors: Fang Zengli , Liang Yali , Di Shuai , Han Mingqi
Published: October 2024

Path planning for combined transportation can improve the irrationality in the carrier task so as to achieve the purpose of cost reduction and efficiency. This study takes economic efficiency as the starting point, takes the transportation time window as a constraint, and constructs the total cost objective function in the transportation process. The objective function of carbon emission in the transportation process is designed to address the green and low-carbon problem. The Ant colony algorithm is used to solve the multi-objective joint transportation model, aiming to obtain a green and efficient transportation path that meets the actual demand. The ACO algorithm shows good convergence performance in the transportation task from starting point O to ending point D. The ACO algorithm is capable of solving the transportation task from starting point O to ending point D after 130 iterations. After 130 iterations of the algorithm, the cost objective function value converged to 3427.8 RMB, and the carbon emission objective function value converged to 5534 kg after 90 iterations of the algorithm. Furthermore, the ACO algorithm’s Pareto solution set exhibits a uniform spatial distribution and excellent ductility and approximation effects. Assigning the same weights to cost, carbon emissions, and transportation time, the optimal solution 4 is obtained. The scheme from the starting point O via nodes 1, 2, and 6 to the end point D, through the joint transportation of road and waterway for 162 hours, a total of 5549 kg CO2, and the cost of transporting each ton of goods is 4093.9 yuan.
A Study of Artificial Intelligence-Driven Educational Intervention Strategies for Students with Special Educational Needs
Authors: Mo Dongxia , Mo Bohai
Published: October 2024

This paper first introduces the intervention path of artificial intelligence in special education. It then takes the deaf and hard-of-hearing people as the research object, adopts artificial intelligence technology, digitizes the speech signal, performs sound-rhyme syncopation, and constructs an interactive speech evaluation system using the HMM model as the evaluation basis. Finally, this paper discusses the effect of an interactive speech recognition model on special education interventions and describes the future development trend of combining artificial intelligence and special education. The results show that the subjects’ passive response to basic interactive speech in the baseline period showed a stable state, the interactive speech ability in the intervention period showed stable progress, and the subjects’ ability in the maintenance period remained at a high level. In the three periods, the posttest error rates of the experimental group testers on semantic recognition were 40%, 30%, and 10%, respectively, whereas the control group was 80%, 70%, and 65%, respectively, which shows that the semantic network training affected the improvement of the speech recognition ability of the 10 subjects. The mean values of the average error rate of the three stages of the experimental group were 7.53%, 2.44%, and 2.07%, and their average recognition times were 1566.73 seconds, 1051.30 seconds, and 463.55 seconds, respectively. The three-stage semantic recognition training significantly improves the subjects’ semantic recognition ability and reduces the recognition time. The integration of artificial intelligence and special education is critical for special education groups’ education and healing.
Research on deep learning-based action recognition and quantitative assessment method for sports skills
Authors: Wang Tao
Published: October 2024

The current sports training lacks data-based scientific training tools, and the use of action recognition technology to collect and mine sports data can effectively identify and evaluate sports skill actions. In this paper, a Transformer-based convolutional neural human action recognition network is proposed, which integrates the C3D convolutional network with the visual Transformer structure, using the 3D convolutional kernel for the extraction of time-domain features and using the Transformer network to accurately classify the feature sequences. The OpenPose algorithm is used to extract the essential points of the skeletal joints to estimate the human action posture. Through the dynamic time regularization algorithm, athletes’ sports movements are matched with standard movements to achieve a quantitative assessment of sports skill movements. The experimental results show that the method in this paper has better performance than similar neural network models in the task of sports action recognition and evaluation, and its class average accuracy mAP value and GFLOPs/V value are 0.9291 and 25.01, respectively, which substantially improves the recognition efficiency of sports skill actions.
Exploring strategies to improve the effectiveness of neurology ideology teaching team building using machine learning techniques
Authors: Wang Ying , Zhang Huakai , Li Tongtong , Yin Dongyan , Li Xiaoting
Published: October 2024

This paper takes the students of neurology specialty in a medical school as the research object and analyzes the current situation of its educational team construction. A machine learning algorithm based on weighted plain Bayes is used to construct an evaluation model, through which different weights are given to each index to explore the effectiveness enhancement strategy of neurology ideology and politics teaching team construction. Finally, the teaching performance and comprehensive ability of Civics and Politics were compared between the two groups of students to explore the effect of infiltrating the course Civics and Politics in neurology teaching. The results showed that 54.65% believed that teaching neuroscience ideology and politics in team construction should be improved as soon as possible. The mean value of “exerting the guiding role of professional teachers of Civics and Politics” was 23.76 points, which was also the furthest away from a perfect score, and was the focus of the subsequent team-building concern. The teaching performance and comprehensive ability of the students in the experimental group were better than that of the reference group (P<0.001), and the full penetration of the relevant elements of the course Civics in the teaching of clinical internships can transform the students’ ideological concepts and conscious behaviors.
Edge Computing in Power IoT Security and Intelligent Monitoring
Authors: Liu Danni , Wang Shengda , Chen Cong , Zhang Yan , Zhao Wei
Published: October 2024

In the context of the rapid development of power IoT, the application of edge computing technology has become the key to improving the level of grid intelligence and enhancing the data processing capability. This paper initially designs the edge computing system for electric power IoT based on the edge computing model. Key-edge computing technologies are combined to process and analyze power IoT data in real-time. Simulation experiments have formed and verified an intelligent security monitoring system for electric power IoT using the LightGBM algorithm. The training convergence speed and effectiveness of this paper’s scheme are better than Stroj’s scheme, and this paper’s scheme can increase the security of power IoT data through key generation and filter de-duplication. This paper’s nodes have an average synchronization time of 9.25 ms. The 128MB data node has an upload time of 57143ms. The data sharing time is about 292~7489 ms faster than the comparison scheme, and in the data search phase, the time overhead of this paper’s scheme is less than the comparison scheme. In summary, this paper’s constructed security monitoring system can offer robust technical support for the advancement of intelligent, efficient, and omnipotent power in the Internet of Things.
Research on the method of eliminating differences between small-sample databases based on cloud computing
Authors: Que Lingyan , Jiang Zhengwei , Zhang Xinxin , Pi Yu , Chen Qi
Published: October 2024

As computer technology continues to advance, more and more people are using databases, leading to variations in data backup and transfer between databases. This paper proposes a small sample inter-database discrepancy data elimination method based on cloud computing architecture as a way to solve the problem of data synchronization discrepancy between different databases. The semantic features of the data in the database are represented in the form of a directed graph, and the semantic Gaussian marginalized data fusion system is constructed by combining the rectangular window function of Gaussian marginalization to realize the fusion filtering processing of discrepant data. Then, the particle swarm discriminant tree algorithm is used to extract the features of the difference data between the small sample databases, and the KL transform is used to compress the difference data to improve its confidence level. The rough weighted average single dependency method is introduced to detect and identify the difference data between small sample databases and combined with the artificial intelligence algorithm to construct the principal component feature set of the difference data in the small sample databases, thus realizing the elimination of the difference data between small sample databases. When the proportion of difference data is increased from 0.05% to 1.00%, the leakage alarm rate and false alarm rate of this paper’s method for the difference data between small sample databases are 0.113% and 0.099%, respectively. When eliminating the inter-database discrepancy data, its time consumption is between 0.06μs and 0.3μs, and the average value of the removal rate of discrepancy data can reach 95.54%. Small sample databases that utilize cloud computing technology can utilize a variety of differential data elimination algorithms to ensure high-quality migration and synchronized backup of inter-database data.
Constructing an AI-driven teacher training model for vocational education: teachers’ information literacy and teaching competence at the same time
Authors: Li Yongmei
Published: October 2024

With the integration of various emerging technologies represented by artificial intelligence into the field of education, the education sector has set off a research boom in wisdom education, forming a series of new forms of education such as wisdom classrooms and wisdom teaching. This paper takes education informatics as the connecting point to sort out the logical connection between teachers’ information literacy and smart education. The intelligent system, various subjects, and complicated knowledge domains are united to form a specific objective relationship and multivariate correlation network to construct a specific field of AI-enabled teacher training. Embedding the training process of vocational education teachers in each stage of the AI-assisted teacher training system, we examined their learning mood, concentration, and the impact on their information literacy ability under AI-driven. AI-driven interactions at all stages could greatly awaken learners’ emotions, which could enable teachers to focus more on training, as shown in the results. In addition, the composite mean value of teachers’ information literacy under AI-driven was 4.10, which was significantly higher than that of 3.42 before use (p<0.001). AI technology-enabled vocational teacher training can be a significant direction for teacher training reform.
Target Detection in Remote Sensing Images Based on Recognition Algorithm
Authors: Zhang Qingrong
Published: October 2024

Aiming at the problem of low target detection accuracy caused by the close arrangement of targets, complex feature information, and numerous small targets in remote sensing images, this paper proposes a target detection algorithm based on the improved Yolov5 algorithm for remote sensing images. Firstly, this paper designs a remote sensing image target detection algorithm C²-YOLO based on multi-level feature fusion. Combined with the attention mechanism module to focus on the spatial location information of the target, which improves the extraction effect of the features of the target of interest. The network uses the CARAFE upsampling operator with a larger sensing field to better utilize the surrounding information. The proposal is to incorporate a predictive header hl that is generated from a low-level, high-resolution feature map to improve the recognition of tiny objects. The problem of large target scales in remote sensing images and poor detection of small targets has been improved. Angular loss is also added to the loss function to improve the detection of rotating targets. Finally, the accuracy comparison and experimental effect visualization are carried out on the dataset, and the experimental results show that the improvement work in this paper achieves better results no matter comparing the original YOLOv5 detection algorithm or other types of detection algorithms. Specifically, the accuracy of C²-YOLO on the NWPU dataset 1-shot recognition task is 78.45%, which is much higher than that of other detection algorithms, and is able to reach a superior performance in the remote sensing image target detection task.
A blended teaching model integrating cognitive science and educational technology: an empirical study to enhance students’ learning effectiveness
Authors: Wang Xiaolian
Published: October 2024

With the continuous development and promotion of blended classrooms in college education and teaching, utilizing quality educational technology to improve learning effectiveness and teaching quality has become an inevitable choice to promote the deep integration of educational technology and cognitive science. In this paper, we construct the student model using Bayesian networks under the blended teaching mode. The improved overlay model is used to abstractly represent the content knowledge learned by the students, track the dynamic learning process of the students, constantly update the knowledge status of the knowledge points learned by the students, and adopt the signal light standard to represent the students’ mastery of the knowledge units. The constructed student model is defined in terms of learning styles and cognitive states, and the learning outcomes under the blended teaching mode are visualized through empirical analysis. The experiment revealed that the students’ style dimensions scores were 23, 16, 11, and 2, and their learning style type was sensory-intuitive. After the experiment, the average value of the integrated water of cognitive ability of the experimental group and the control group is 71.77 and 66.33, respectively, and the p-value is 0 less than 0.05, which indicates that the blended teaching mode effectively improves the cognitive level ability of the learners.
Research on the Design and Application of Intelligent Teaching and Training System for College Basketball Based on 3D Motion Recognition Technology
Authors: Chen Tianyu
Published: October 2024

In this paper, for the problems of traditional 2D convolutional networks in dealing with action recognition in video, a dual-resolution 3D-CNN action recognition network is induced to initialize 3D convolutional weight parameters by using 2D weight parameters of ImageNet, and the weight files are used as the parameters of the model to perform feature extraction on the sequence of technical action frames respectively. After feature extraction, collect the feature vectors that can effectively describe the human body movements, classify the feature vectors with the help of the kernel function in the Support Vector Machine (SVM), and finally determine the technical architecture of the basketball auxiliary training system, and complete the design of the intelligent teaching and training system for basketball in colleges and universities. After analyzing the method of the present paper, it can be seen that the recognition error of the basketball player’s running gait is 3.47%, which accurately reflects basketball sports training footwork trajectory to achieve the effect of intelligent guidance. In addition, the upper and lower limb movement recognition effect based on CNN+SVM is obvious, and the average accuracy rate of its upper and lower limb movements is 93.17% and 98.66%, respectively, which well meets the needs of basketball teaching in colleges and universities. In terms of students’ basketball skills, there is a significant difference between this paper’s system and traditional teaching (P<0.05), and this paper’s system has a higher priority for improving the quality of college basketball teaching than traditional teaching.
Toward an explanation of speech style
Authors: Dolník Juraj
Published: October 2024

The study focuses on the formulation of ideas as a contribution to the explanatory theory of speech style. Ideas relate to the ontological basis of style, the fundamental role of sociocultural meanings, the rationality of stylistic knowledge, and the deep motivation of stylistically relevant linguistic behavior and action in social interaction. The author approaches style from a holistic position based on the belief that speech style is integrated into the ways of human activity as a whole controlled by a pragmatic subject. In the center of attention is the subject of style, who discovered sociocultural meanings tied to the ways of activities, developed the ability of stylistic adaptation to current conditions of social interaction, and learned to deal with stylistic knowledge with appropriate rationality in communication practice. The author also answers the question of what laws and principles underlie the existence of style, its subject and stylistic behavior and actions.