bluuebunny/crossref_metadata_2025 huggingface dataset:
Modelling Working Memory Capacity: Is the Magical Number Four, Seven, or Does it Depend on What You Are Counting?
Authors: Morra Sergio , Patella Paola , Muscella Lorenzo
Published: July 2024

Limited attentional capacity is essential to working memory. How its limit should be assessed is a debated issue. Five experiments compare Cowan’s 4-units and Pascual-Leone’s 7-units models of limited working memory capacity, with presentation time and attention to operative schemes as potential explanations of this discrepancy. Experiments 1a–1c used the Compound Stimuli Visual Information (CSVI) task, with long versus brief presentation. Capacity was estimated with the Bose-Einstein model, assuming a different number of attending acts in each condition. Participants’ k estimates in both conditions were highly correlated and the means were not different, indicating that the same capacity is assessed in both conditions. Experiments 2 and 3 used the 5000-msec CSVI, and the Visual Array Task (VAT) in two conditions (5000- vs. 120-msec presentation). Capacity in the VAT was estimated with Morey’s Bayesian method. Participants’ k estimates in both VAT conditions were correlated, but the mean was higher with long presentation, suggesting that the long condition benefits from recoding or chunking. The k estimate in the CSVI correlated with the short VAT and (to a lesser degree in Exp.2) with the long VAT. The mean estimate of k in the CSVI was one unit more than in the short VAT. We conclude that the CSVI and the short VAT tap the same capacity, one unit of which in the short VAT is allocated to an operative scheme; we discuss how Cowan’s and Pascual-Leone’s views on limited capacity can be reconciled.
Quid per prius datur. La doctrina tomasiana del doble orden de prioridad entre el don creado y el Don increado
Authors: Juárez Guillermo
Published: July 2024

La comunicación a la creatura racional del don de la gracia santificante y del Don del Espíritu Santo, siendo simultánea, comporta cierto orden e incluso diversos modos de orden. Esta doctrina de santo Tomás de Aquino es de enorme importancia para una comprensión más acabada de algunas de las grandes temáticas teológicas que caracterizan su pensamiento, como las referidas a la inhabitación trinitaria y a la justificación. En el presente estudio nos proponemos profundizar dicha enseñanza desde el trasfondo de la ofrecida en la Suma Halesiana por Juan de la Rochela, su predecesor inmediato más importante e influyente en esta materia. Siguiendo el orden de exposción del Comentario a las Sentencias, obra en la que el Angélico expone más ampliamente esta temática, consideramos sucesivamente el hecho de la donación conjunta del don creado y el Don increado, y el orden entre ellos, temáticas que suponen respectivamente las doctrinas filosóficas de la relación de razón y del principio, el orden y sus modos.
Hybridity in the Novel “The Lowland” by Jhumpa Lahiri
Authors: Badjak Miya Gina Fatah , Majid Bakhtiar , Magfirah Sulmi
Published: July 2024

This research discuss about the Hybridity in the novel “The Lowland” by Jhumpa Lahiri viewed from Postcolonial Theory. The research focused on the hybridity culture in the novel and the impact of hybridity culture that reflected to the character in the novel. The method of this research used descriptive analysis method to describe problems in the forms of narration and analysis. This research used postcolonial theory of Hommi Bhaba hybridity to help on understanding the hybridity, or mix of two or more culture in the primary data, then to match with the real condition in India from the library research and internet search about the important events that related to postcolonialism theory about the postcolonial era that effected into the Indian culture in the novel then caused a hybridity culture. The result of this research is, the researcher finds the forms of hybridity which is reflected through the character in the novel. The forms of hybridity in the mix of British and Indian culture are hybridity culture, hybridity language, and hybridity in race and between three forms of hybridity the researcher found the dominant one is hybridity culture. The researcher also found the impact of hybridity culture that created the blurred copy of first and second culture, and then, make the domination position of one another and inferior culture Alienation and discriminate on the “third space”.
Toponymy Analysis of Village Naming in Ternate
Authors: Fajrhi Nur , Mahmud Fitriningsih Pratiwi , Sailuddin Sartika Putri , Talaohu Ahmad Rifani , Magfirah Sulmi
Published: July 2024

Ternate is one of the cities in North Maluku, located right beneath Gamalama Mountain. Ternate was once a trade center in the 13th century and became a melting pot for people from different countries with different purposes. There were Portuguese, Dutch, and Spanish with the aim of colonizing, and there were Arabian, Chinese, and locals outside Ternate, such as people from Halmahera, Sulawesi, Maluku, Sumatra, and Java, who came for trading. The arrival of these people contributes not only to language adaptation but also to place names known as toponymy. There are several relevant studies concerning toponymy in Indonesia, but they have yet to be done in Ternate. Hence, this research aims to: 1) analyze the morphological process of the villages naming in Ternate and 2) provide toponyms classification of the villages naming in Ternate. The primary data are taken from Ternate Dalam Angka, a statistical data from BPS Ternate, which contains 59 villages/sub-districts named in Ternate. The data was then analyzed and triangulated through in-depth interviews and literature studies. The data are presented both formally and informally. The analysis results show morphological processes concerning zero derivation, reduplication, compounding, abbreviation, back-formation, combination, borrowing, and phrases that occurred in the villages named in Ternate. The findings also attest to a theory proposed by George R. Stewart (2012) regarding toponymy classification of village naming in Ternate, in which there are descriptive, incident, possessive, commemorative, euphemistic, folk etymologies, manufactured, shift, mistake, descriptive + manufactured, euphemistic + manufactured, euphemistic + manufactured, and unknown.
Propuesta de prototipo de mapa interactivo para la operación segura de RPAS en Honduras
Authors: Amaya Carías Omri Alberto , Matamoros Alex Geovanny , Locandro Antonio , Stefan Allister
Published: July 2024

Con la presente investigación se hace una primera aproximación a un prototipo de mapa interactivo alimentado con información oficial, de los espacios no autorizados para la operación de Sistemas Aéreos de Pilotaje Remoto (RPAS por sus siglas en inglés), de acuerdo con la Circular de Obligatorio Cumplimiento COC- ATL-002-2018. Metodológicamente se dieron tres fases de trabajo: primero se hizo una revisión bibliográfica y de las páginas webs relacionadas, seguidamente se categorizaron y localizaron los espacios indicados por la COC antes mencionada, haciendo uso de herramientas de geolocalización disponibles en línea; en un tercer momento, se hizo el levantamiento de una base de datos geoespaciales aplicando herramientas de acceso abierto. Entre los resultados visibles de la presente investigación se incluyen, 1) la elaboración de una primera categorización de espacios con restricciones para la operación de RPAS en Honduras según la circular antes mencionada; 2) una validación de la información disponible en la publicación de información aeronáutica sobre 131 aeródromos en Honduras; 3) la primera aproximación a un prototipo de mapa web para la operación segura de drones en Honduras. Las conclusiones de la investigación ratifican la importancia de contar en el país con un mapa interactivo de diseño amigable que indique los lugares en donde está permitida la operación segura de RPAS, en qué lugares esta operación se permite con restricciones y en cuáles está prohibida.
Relación de la cobertura de suelos y deslizamientos en área urbana Las Vegas, Santa Bárbara 2014-2018
Authors: Kafati Vásquez Liza Mariel
Published: July 2024

En este trabajo de investigación se analiza la influencia de los cambios y dinámica en la cobertura de suelo sobre la susceptibilidad a los eventos de deslizamientos de tierra para escenarios pasados y futuros en el área urbana del Municipio de Las Vegas, municipio que ha tenido crecimiento urbano significativo y descontrolado en los últimos años. Con este propósito se pretenden elaborar inventarios de deslizamientos y mapas de cobertura de suelos para los años 2014 y 2016 y poder determinar los años de mayor deterioro y/o degradados en escenarios de periodos futuros, identificando las áreas más y menos boscosas del Municipio de Las Vegas, Departamento de Santa Bárbara. Se pretende analizar los eventos de probabilidad de deslizamientos de tierra en dos periodos de seis años hasta el año 2018, y algunos datos relevantes entre el mismo periodo de tiempo. Todos estos avances nos permitirán conocer si, en áreas menos boscosas, con cambios de usos de suelo, ganadería extensiva e intensiva, crecimiento urbano y actividades antropogénicas las cuales provocan un impacto en las condiciones del suelo y sus propiedades, se genera un aumento en la susceptibilidad a los deslizamientos. Los datos de los resultados pueden utilizarse como apoyo para los lineamientos del ordenamiento territorial, zonificación urbana y gestión de riesgos y amenazas naturales para reducir el riesgo a deslizamientos en el área urbana del Municipio de Las Vegas.
Análisis de cobertura de servicios de redes de negocio en barrios informales, Distrito Central Honduras
Authors: Antúnez Williams Brenda Itzel
Published: July 2024

La informalidad urbana se manifiesta de múltiples formas y con ella emergen mecanismos de subsistencia. Los estados de crisis o emergencia asociadas a riesgos a desastres representan un reto que aumenta la vulnerabilidad y escasez de alimentos. Las experiencias han comprobado la importancia de involucrar al comercio informal como apoyo al gobierno local en zonas de difícil acceso en momentos de crisis. Este nuevo planteamiento exige el análisis de la relación entre la movilidad de los habitantes y los servicios en espacios informales. Este artículo tiene como objetivo plantear un modelo para el análisis de la cobertura territorial de los servicios ofrecidos por negocios resilientes ubicado en barrios informales. El modelo se aplicó a una red de negocios resilientes en Villanueva Norte, Distrito Central, Honduras. Para desarrollar la metodología se utilizó el enfoque de movilidad del peatón, evaluando su experiencia durante el recorrido hacia la obtención de los servicios y posteriormente un análisis mediante procesos de interpolación espacial a través de Sistemas de Información Geográfica. Las principales variables de análisis son accesibilidad, vulnerabilidad y atracción del cliente contextualizando a un asentamiento informal. Los resultados reflejan la importancia de realizar procesos integrados interactivos que reflejen el comportamiento de intervenciones urbanas para generar recomendaciones de mejora, fortalecimiento y ampliación de negocios resilientes. Este trabajo se deriva de la tesis de Maestría en Ordenamiento y Gestión del Territorio “Caracterización de Barrio con enfoque en Reducción de Riesgos a Desastres: Un aporte a la reconfiguración de barrios informales en el Distrito Central, Honduras”.
Índice compuesto para determinar el riesgo de inseguridad alimentaria a nivel municipal en El Salvador: Índice de Flores-Romero
Authors: Flores Romero Roberto Alejandro
Published: July 2024

La falta de acceso a alimentos seguros y nutritivos puede llevar a problemas de salud graves; y la inseguridad alimentaria puede afectar la productividad, la educación y la capacidad de inversión de la población, lo que puede tener un impacto negativo en el crecimiento económico a largo plazo. Por lo tanto, es crucial contar con una herramienta para evaluar la situación de seguridad alimentaria en un país y tomar medidas adecuadas para abordar las brechas identificadas, tanto a nivel nacional como subnacional.
El artículo trata sobre la construcción y desarrollo del Índice Compuesto de Inseguridad Alimentaria llamado Índice FloresRomero en El Salvador; una herramienta esencial para la toma de decisiones informadas y la promoción de la seguridad alimentaria a nivel subnacional(municipal). El Índice Flores-Romero utiliza un modelo econométrico-sanitario de pronóstico de producción; específicamente un modelo multivariante de Vectores Autorregresivos para estimar qué municipios estarán en déficit o superávit de producción, de maíz y/o frijol, para un año específico; y luego calcula el Índice en cuestión, utilizando variables que conforman una Matriz de Priorización Municipal.
Los resultados permiten jerarquizar qué municipios poseen mayor riesgo de inseguridad alimentaria, en función de un mayor Índice Flores-Romero, lo que informa a los tomadores de decisiones. El índice también puede ser utilizado como un marco de referencia para medir el progreso en la implementación de políticas y programas destinados a mejorar la seguridad alimentaria a lo largo del tiempo.
A A participação militar brasileira no Haiti sob as lentes do jornalismo para a paz
Authors: Bigatão Puig Juliana de Paula , Alexandre Winand Érica Cristina , Santos da Cruz Aanne Karolinne
Published: July 2024

Neste artigo, analisamos a participação militar do Brasil na Missão de Estabilização das Nações Unidas no Haiti (MINUSTAH), entre 2004 e 2017, marcada pelo emprego das forças armadas sob um mandato de imposição da paz, enquadrado no Capítulo VII da Carta da ONU. A contribuição deste trabalho está na ferramenta teórico-metodológica proposta para analisar a experiência brasileira no Haiti – o jornalismo para a paz – e nas fontes mobilizadas para tal – o material publicado pela grande imprensa brasileira, especialmente o jornal Folha de S. Paulo. A partir da análise de conteúdo do referido material, argumentamos que a cobertura midiática priorizou fontes oficiais e deu maior destaque aos elementos de contextualização da crise haitiana do que à atuação militar brasileira sob mandato robusto. O papel do Brasil na MINUSTAH foi amplamente abordado e na maioria das vezes estava associado à posição de comando que pretensamente garantiria maior projeção internacional ao país. Os desdobramentos da MINUSTAH no cenário doméstico brasileiro, especialmente no tocante às operações de segurança pública amparadas pelos dispositivos constitucionais de garantia da lei e da ordem, receberam pouca atenção do periódico.
FORCE DEGRADATION AND STABILITY STUDY OF 7-HYDROXY COUMARIN
Authors: Agrawal Sneha ,   Department of Pharmacognosy, Bharati Vidyapeeth’s College of Pharmacy, Sector-8, C.B.D., Belapur, Navi Mumbai - 400 614, Maharashtra, India, Dhamne Sagarika , Shinde Pradum
Published: July 2024

The research investigates the stability of 7-hydroxy coumarin i.e. umbelliferone, a compound with diverse applications, through forced degradation studies under various conditions. These investigations aim to comprehend its susceptibility to degradation and provide insights crucial for its safe handling and formulation. Umbelliferone displays differing degrees of vulnerability to distinct stressors: it exhibits higher susceptibility to alkali-induced and photolytic degradation, signaling the necessity for cautious management under these conditions. Conversely, it demonstrates moderate susceptibility to acid and water-induced degradation. The findings underscore the importance of handling umbelliferone carefully, particularly in environments, where it is more prone to degradation. Furthermore, the study suggests future explorations to elucidate the structures of degradation products, potentially enhancing our understanding of its stability profile. This comprehensive analysis not only elucidates umbelliferone’s stability nuances but also accentuates the significance of forced degradation studies in evaluating the inherent stability of pharmaceutical compounds, offering crucial insights for formulation and storage practices.
Hydrodynamic assessment of body exposure in drainage stairways: a numerical study
Authors: Simões André Luiz Andrade , Schulz Harry Edmar , Porto Rodrigo de Melo , Luz Lafayette Dantas da , Mangieri Lúcio Sérgio Garcia , Matos Jorge Eurico Ribeiro
Published: July 2024

This work presents advances in the study of nappe flows in stepped chutes, focusing on scenarios without the formation of hydraulic jumps on the steps. The dynamics of flows in "drainage ladders", which are structures that serve as both pedestrian pathways and open channel for surface waters, was analyzed using the k- turbulence model, multiphase inhomogeneous model, and high-resolution numerical schemes. Two aspects were focused: the drainage capacity of the ladder and the resultant force exerted on a foot/leg-like obstacle located on a step of the flow. Calculation domains in two and three-dimensions were used. The two-dimensional simulations allowed quantifying the energy dissipation of the nappe flow regime without the sequential hydraulic jumps. The results include dimensionless relationships between the residual specific energy and the depth of the flow, which show adherence to experimental data from the literature and points to the suitability of the proposed methodology for the numerical modeling of the problem. Furthermore, due to the allowed partial channel flow, the numerical results show that the drainage use of the ladders significantly reduces the horizontal forces acting on the human-form obstacles on the steps, with 31.9% of reduction for the studied scenarios.
Pobreza menstrual e saúde: construção de conhecimento por meio de uma revisão de literatura
Authors: Santos Mariana Carvalho dos , Bortoto Giullia Camila , Elias Maria Ligia Ganacim Granado Rodrigues
Published: July 2024

A pobreza menstrual é um entrave multidimensional que afeta todos os países, envolvendo questões como infraestrutura, renda e falta de informação, podendo causar problemas sociais e físicos nas mulheres e pessoas que menstruam. Nesse sentido, o objetivo geral deste trabalho é analisar as iniciativas públicas voltadas para a promoção da dignidade e educação menstrual no Brasil, a fim de identificar e gerar conhecimento sobre seus principais avanços, limitações e desafios. A metodologia aplicada é a de revisão bibliográfica e documental, por meio de uma busca sistematizada e voltada à análise das iniciativas públicas direcionadas para a promoção da dignidade e da educação menstrual no Brasil. A coleta de dados da literatura científica permitiu uma análise das iniciativas públicas existentes no Brasil voltadas para a pobreza menstrual, bem como a identificação dos avanços dessas campanhas, suas limitações e seus principais desafios. Como resultado e contribuição, o artigo apresenta um panorama sobre o tema, constituindo um passo inicial para integrar conhecimento sobre esta questão que é cientificamente e socialmente relevante.
Políticas de formação de professores em Educação Especial para atuação na sala de aula comum e no Atendimento Educacional Especializado
Authors: Souza Vanilda Aparecida de , Silva Lázara Cristina da
Published: July 2024

O presente artigo tem como objetivo discutir sobre a formação de professores em Educação Especial tanto para o atendimento na sala de aula comum como no Atendimento Educacional Especializado. A temática do processo de escolarização do público da Educação Especial remete repensar na formação dos professores. Sendo assim, faz-se necessária uma reflexão sobre algumas questões relacionadas à formação do docente para atuar na Educação Inclusiva, tanto no atendimento educacional especializado como na sala de aula comum.   Utilizou-se a pesquisa documental e a entrevista semiestruturada. Pode-se inferir que ainda há muitas dificuldades das políticas para incluir e oferecer atendimento adequado aos alunos da Educação Especial. Isso implica, por um lado, a necessidade de ações comprometidas com a concepção de Educação Inclusiva para além dos serviços do AEE e, por outro, a necessidade de políticas de formação de professores na perspectiva da inclusão que considerem as reais demandas da escola pública e de todos os profissionais que nela atuam.As análises evidenciaram a importância da formação continuada dos docentes que atuam na sala de aula comum, de acordo com o descompasso entre o trabalho pedagógico realizado no contexto do AEE e o trabalho conduzido na sala de aula pelo professor regente. As percepções dos professores que atuam na escola confirmam que a formação dos docentes geralmente tem implicações no processo de escolarização do público da Educação Especial, e que esse processo de escolarização não pode ser compreendido como um processo fragmentado constituído por momentos estanques e desconexos entre o AEE e a sala de aula comum. Por fim, a formação do professor na perspectiva da Educação Inclusiva precisa se pautar não só na formação de especialista, mas de todos os profissionais da educação, com o intuito de reestruturar as práticas pedagógicas que visem o processo de inclusão educacional.
Instrumentos de avaliação do processo ensino-aprendizagem
Authors: Melo Junior Madson Fernandes de , Santos José Leonardo Diniz de Melo , Farias Artunho de Araujo , Silva Caio Vinicius da , Gomes Antonio José Ferreira , Lima Mariel Wágner Holanda , Araújo Laylles Costa , Almeida Frairon Cesar Gomes , Paixão Flavia Juliana Dourado , Soares Dlayne Giordana Pereira , Almeida Claudimar Paes de , Godoi Edileide de Souza , Silva Carla Michelle da , Silva Antônio Veimar da
Published: July 2024

Este artigo explora diversos instrumentos de avaliação utilizados no processo ensino-aprendizagem, destacando suas características, potencialidades e limitações. A pesquisa se baseia em uma revisão bibliográfica de artigos científicos publicados em bases de dados reconhecidas, como SciELO, ERIC e Periódicos CAPES. Foram selecionados estudos que abordassem práticas avaliativas em diferentes contextos educacionais, considerando critérios de relevância e aderência ao tema. A análise focou nos principais tipos de avaliação: diagnóstica, formativa, comparativa e somativa. A avaliação diagnóstica é essencial para identificar os conhecimentos prévios dos alunos, permitindo ao professor planejar suas aulas de maneira mais eficaz. A avaliação formativa, por sua vez, acompanha o desenvolvimento contínuo dos alunos, proporcionando feedbacks constantes que possibilitam ajustes no processo de ensino. A avaliação comparativa oferece parâmetros para analisar o desempenho relativo dos alunos em relação a normas ou padrões estabelecidos, enquanto a avaliação somativa verifica a aquisição de conhecimentos ao final de um período ou unidade de ensino. Além das modalidades tradicionais, o artigo destaca a importância de diversificar os instrumentos de avaliação, utilizando observações, questionários, autoavaliações e portfólios. Essa abordagem permite uma visão mais abrangente e detalhada do processo de aprendizagem, facilitando a identificação de dificuldades e potencialidades dos alunos.Conclui-se que a combinação de diferentes métodos de avaliação contribui significativamente para uma educação mais eficaz e inclusiva. A diversificação dos instrumentos avaliativos promove um entendimento mais profundo do desenvolvimento dos estudantes, auxiliando na implementação de práticas pedagógicas que atendam às necessidades individuais e coletivas, e promovendo, assim, um ambiente de aprendizagem mais enriquecedor e equitativo.
Digital transformation of real estate industry: opportunities, challenges and strategic suggestions
Authors: Qian Zhen
Published: July 2024

After more than 20 years of rapid development, China's real estate industry has changed from an incremental market to a stock market with a gradual slowdown in growth. As the 14th Five-Year Plan for national information states that China will insist on the strategy of digital transformation, it is the right time for real estate industry to carry on a digital revolution. This paper illustrates the current challenges confronted by real estate enterprises, including the confusion of digital transformation, complex data sources, the lack of professional talents and duplicated organization systems. Also, to overcome these challenges, this paper provides practical suggestions on how the real estate industry can conduct digital transformation. This paper aims to provide significant insights into current situation of real estate industry and give guidance to help the industry process digital transformation.
Research of the development of Green Central Bank Digital Currency, CBDC
Authors: Becerra Jesus Ramon Jaimes , Chaglla Jimena Alexandra Campaa , Valencia Nuvia Maribel Renteria , Alcivar Josselin Magdalena Intriago
Published: July 2024

The idea of a green central bank digital currency (CBDC) has been mentioned by some institutions such as the Congress of the United States and private companies, but it has not been explained. It is intuitive that this concept refers to a way of issuing or using CBDCs by taking the environment into consideration. In this research, it is explored a way that this could work by limiting the CBDC issuance to the total renewable energy production. The paper shows a list of the 40 countries that produce the most renewable energy and compares it with a well-established economic standard, the Total Reserves of Central Banks. For 2018, it was found a correlation among the percentage of the total energy that is produced with green sources and the percentage that could be backed by international reserves if it were the same thing. This correlation is presented as a patron that can be use by Central Banks in order to take environment in to consideration and to calculate how much of a CBDC can be issued by central banks as a standard.
Marketing Strategy Analysis for Mobile Phone Brands Based on The Marketing Mix
Authors: Tang Runyu , Wu Jiakun
Published: July 2024

Based on the 4p model, this paper analyzes the marketing strategies of mobile phone enterprises by taking Xiaomi and Apple as examples. The results show that Xiaomi mainly uses low - and medium-end mobile phones, closely connect with users through the network, and maintains its market share through its high-cost performance and high user stickiness. Apple, which focuses on high-end phones, provides users with high-quality services and high positioning to attract high-income groups to buy its products, which can serve as a reference for the marketing strategies of different mobile phone brands.
Analysis of the Development Strategy of SMIC
Authors: Ding Xinyi
Published: July 2024

As the most advanced and largest chip foundry in mainland China, SMICs development strategy is of great research value and reference significance. This paper first gives a brief introduction of SMIC, including the company's development history and the current problems and challenges it faces. Then, it analyzes the strategic environment of SMIC and analyzes its external environment (PEST analysis) in terms of political, economic, policy and technological environment. Next, SMICs internal resources and capabilities were analyzed in terms of finance, human resources, technology and R&D capabilities, production capacity, and customer and market resources. Finally, a SWOT analysis was conducted based on the above, and strategic recommendations were made by summarizing SMICs strengths, weaknesses, opportunities and threats. SMICs current scale of development and operations are good, so it should plan more for future growth. The political, economic and social environment in mainland China has created positive support for SMICs development. SMIC should take this opportunity to secure its current market share while striving for more mainland markets, seeking external cooperation and, most importantly, making technological breakthroughs as soon as possible to catch up with the industry leaders.
Analysis of the Impact of the Epidemic on Consumption Patterns
Authors: Wang Xuerong
Published: July 2024

Due to the epidemic's spread, people are now more dependent on online shopping and their consumption pattern have changed. Which might have an effect on the business environment and economic growth. Using linear regression models and related data analysis, this paper studies user online consumption data from 2018 to 2021 and finds that there has been a significant increase in online consumption gains during this period. In other words, the epidemic partially contributes to the modernization of consumption practices and the increase of online shopping. Overall, this paper highlight how changing consumption patterns have affected social and economic advancement and offer crucial insights for economic recovery in the post-epidemic period.
Personalized medical recommendation system supported by medical data
Authors: Wang Winston
Published: July 2024

A personalized medical recommendation system is an intelligent system that utilizes medical data to provide targeted medical advice and services to individuals. With the lack of accumulation and development of medical data, personalized medical recommendation systems have great potential in improving medical effectiveness and saving medical resources. This article aims to explore the principles, methods, and applications of personalized medical recommendation systems based on medical data.
Research on recommendation algorithm based on user sentiment analysis
Authors: Gong Yuan
Published: July 2024

With the development of Internet technology, the recommendation system is becoming an essential part of major e-commerce platforms, social media platforms and other application fields. The main purpose of the recommendation algorithm is to provide users with personalized and accurate recommendations of goods, services and information. Traditional recommendation algorithms are mainly based on information such as users historical behavior to recommend similar items to users. However, only considering the historical behavior of users cannot fully reflect the individual needs of users because the emotions and interests of users are dynamic. Therefore, introducing user emotion is an important direction of a personalized recommendation system. Based on user emotional analysis,a recommendation algorithm aims to understand user preferences and interests by analyzing their emotional reactions. It utilizes emotional data to generate personalized recommendations, considering the sentimental factors that influence consumer purchasing decisions. By incorporating emotional intelligence into the recommendation process, this algorithm aims to improve the accuracy and effectiveness of product suggestions, ultimately enhancing user satisfaction. This paper will discuss the introduction of the user emotion recommendation algorithm and explore its implementation and application scenarios.
Research on predicting Ames housing price based on forward selection regression and principal component regression
Authors: Wang Ziwen
Published: July 2024

This study aimed to predict home prices in Ames, Iowa, using two regression techniques: forward selection regression and principal component regression. The research began with exploratory data analysis and several pre-processing steps. Features are classified, overlapping features are merged, missing values are processed appropriately, and predictors of zero or near-zero variance are removed. The data is then scaled to solve the problem of data fragmentation. The results indicated that the forward selection regression method had higher prediction accuracy and a lower root mean square error (RMSE) value, suggesting its superiority in predicting home prices. The findings of this study have practical implications for various stakeholders in the real estate market. By focusing on the identified areas that contribute significantly to the value of real estate, stakeholders can make informed decisions to enhance their investments. This research provides valuable guidance for homeowners, real estate agents, and property developers in understanding the factors influencing home prices in Ames, Iowa.
The application of Rasa framework in the interaction between players and game NPCs
Authors: Yao Huangao
Published: July 2024

In the current era of thriving electronic games, some players have articulated a novel requirement for electronic games the need for greater freedom and autonomy within the gaming experience. In traditional electronic games interaction methods, there often exist issues of low engagement and insufficient immersion due to the limited narrative approach. At the same time, Rasa technology has made significant progress in the field of open-source dialogue systems. Rasa has the ability to understand and process multiple rounds of conversations, supports multilingual and multi-channel applications, and provides rich tools and components to enable developers to quickly build intelligent dialogue systems which is likely to be applied within the game industry. In the future, Rasa will continue to develop and provide people with a more intelligent and personalized conversation experience. This paper will explore a new application of Rasa platform for players to interact with non-player characters (NPCs) in electronic games which contributes to solving the issues.
A review of research on the control of quadrotor UAVs based on deep learning PID algorithm
Authors: He Xuanchen
Published: July 2024

As a flexible and reliable flying platform, the Quadrotor Unmanned Aerial Vehicle (UAV) has the advantages of convenient operation, simple structure and strong maneuverability. It is widely used in different fields and has great military and civilian value. In todays increasingly complex application environment and situations, it is more difficult to achieve precise control of quadrotor UAVs. The conventional Proportional-Integral-Derivative (PID) algorithm is often unsatisfactory for external disturbances and system nonlinearities during flight. The PID algorithm based on deep learning has better control accuracy, dynamic performance and stability for quadrotor UAVs. Good control effect, so it can be better applied to the current situation. The article mainly summarizes the research status of the control of quadrotor drones based on deep learning PID algorithm, aiming to provide useful reference for researchers, developers and industry stakeholders. In terms of content, the three parts of deep learning quadrotor UAV control, PID algorithm optimization research, and quadrotor UAV control system design are reviewed and summarized, and finally possible improvement schemes and future research directions are proposed.
Principle analysis of five prominent large image classification models
Authors: Shi Maier
Published: July 2024

Deep learning models, based on transformer architectures, have opened up new possibilities for computer vision missions such as object detection, image generation, and image classification. By encoding global context information from an image and capturing long-range dependencies these models achieve state-of-the-art performance in many benchmark datasets. This article focuses on five prominent image classification methods based on deep learning: Contrastive Captioner (Coca), Pathways Language and Image (PaLI) model, EvoLved Sign Momentum (Lion), A Large-scale Image and Noisy-text embedding (ALIGN), and ONE-PEACE. Each of these methods is briefly introduced and the general principles behind them are explained. Additionally, their practical performance in various applications is also reviewed. Most of these methods involve integrating existing datasets to train the model and focusing on the characteristics of the dataset to improve classification accuracy. This work also analyses the advantages and disadvantages of each method, as well as the functions implemented by their individual designs.
Combining CycleGAN and perceptual loss for image style transfer: Double training process
Authors: Li Hanjun
Published: July 2024

Image style transfer is an important field within the broader area of image processing. While existing style transfer models have addressed certain challenges, there remains room for improvement in areas such as color restoration, edge detection, and the ability to effectively transform lighting conditions. Additionally, there is a lack of research exploring the features and properties of these models. To address these limitations, this paper proposes a double training method that combines CycleGAN with the minimization of perceptual loss for style transfer. The proposed method is tested and compared to existing models, resulting in impressive performance improvements, particularly when the style image background is white. These comparative results not only validate the effectiveness of the double training method with CycleGAN, but also provide valuable qualitative insights into CycleGAN and perceptual loss. Drawing from these conclusions, this work further proposes a new model hypothesis that builds upon the double training method and includes background-object segmentation and background whitening. This novel approach aims to enhance the effectiveness of style transfer by allowing objects to maintain their original forms while transferring the style of the source image to the target image.
Utilizing machine learning for sales forecasting in urban supermarkets
Authors: Ma Yining
Published: July 2024

In contemporary society, the proliferation of supermarkets in densely populated urban areas is providing consumers with an abundance of choices and at the same time put supermarket companies into a highly competitive environment. In order to thrive in this market environment, it is of great importance for supermarket corporations to trace, record, and analyse their sales data so that they could have a better understanding of their customer behaviours. And machine learning is commonly applied in this sort of scenarios. By leveraging the insights generated through predictive analysis, machine-learning models can help companies to optimize inventory management, refine pricing strategies, and create effective marketing campaigns. This article applies three machine-learning algorithms to train and test the same data in order to find the model generating the best prediction of quantity sold for the target dataset. Linear Regression, Random Forest, and XGBoost are the three methods used to create three different machine-learning models. After evaluating the R-squared scores generated by three models, it turns out that the Random Forest Model displays the most precise prediction of the target variable, which generates an R-squared score of 99.27%. Thus, the Random Forest Model is the best model for sales prediction in this case.
Optimization of algorithmic efficiency in AI: Addressing computational complexity and scalability challenges
Authors: Meng Xianghui
Published: July 2024

This study explores the efficiency and scalability challenges present in artificial intelligence (AI) algorithms, with particular consideration given to computational complexity issues and optimization strategies. This guide reviews key algorithms such as gradient descent and genetic algorithms in depth to highlight their roles in increasing AI efficiency. Through an exhaustive literature review, this paper highlights significant advancements in algorithmic design - parallelization and optimized data structures are among those highlighted - while their application can be seen in diverse situations like image recognition and predictive maintenance. This study introduces a maturity model for AI algorithms that assesses their sophistication, efficiency, adaptability and robustness. This model aligns with emerging AI trends, such as developing compact resource-efficient models and combining AI with blockchain and quantum computing technologies. Furthermore, this paper emphasizes a shift toward advanced AI algorithms. Future research should place particular focus on computational sustainability, specifically with respect to energy use and environmental impacts. Additionally, this research suggests examining AI potential in edge computing as well as integration between AI with quantum computing and blockchain technology. This forward-focused research approach seeks to address evolving AI challenges while opening new opportunities for novel applications.
Real-time face recognition method based on MTCNN-Inception-ResNet-v2-SVM model
Authors: Zhang Hongyi
Published: July 2024

With the widespread use of smart devices such as smartphones, facial recognition applications have experienced rapid growth. Additionally, breakthroughs in deep learning algorithms have led to the development of facial recognition technology based on deep convolutional networks, greatly improving recognition speed and accuracy. Therefore, this study proposes a real-time face recognition method based on the MTCNN-Inception-ResNet-v2-SVM model. In the facial detection phase, the MTCNN algorithm, which offers better overall performance compared to face detection algorithms such as OpenCV and Dlib, is utilized. Data augmentation and other methods are employed in the image preprocessing phase to enhance data diversity. The Inception-ResNet-v2 deep convolutional neural network is used as the backbone network for feature extraction in the facial recognition backbone network section. In the final classification stage, an SVM classifier is employed for the ultimate facial classification. Comparative analyses with models such as Inception-ResNet-v1, Inception-v3, and Inception-v4 are conducted in the backbone network section, determining that the Inception-ResNet-v2 model exhibits the best overall performance. The final result is a real-time face recognition model, MTCNN-Inception-ResNet-v2-SVM, with a high accuracy of 98.79% and fast processing speed.
Deep learning methods and corresponding applications in medical imaging
Authors: Han Yanjie
Published: July 2024

Deep learning is a subfield of artificial intelligence and machine learning, and it is becoming a popular topic in recent years. It is a powerful tool in solving complex tasks and achieve state-of-the-art results in many areas, including language processing, computer vision, and more. This paper briefly introduced two main deep learning models, Convolutional Neural Networks (CNNs) and Generative Adversary Networks (GANs) and their applications in medical imaging. CNNs are often used in image recognition tasks, like separating different organs in one medical image. While GANs are better doing medical image generation tasks, like creating an X-ray image of chest. This study introduced some deep learning methods for image segmentation, image classification and image generation. Not only are the basic CNNs and GANs architectures used, but also some improvements and modification involved. These methods greatly expand the existing medical image datasets. They also save lots of time for doctors and radiologists from labeling and recognizing those medical images. Deep learning methods are super strong in processing complex and numerous medical images. However, there are still some limitations caused by the lack of training datasets and learning models.
Enhancing medical image classification based on super-resolution techniques: A comparative study
Authors: Deng Xiangning
Published: July 2024

This paper explores the application of super-resolution techniques in the context of medical image classification, focusing on the impact of various super-resolution models on classification model performance. With the burgeoning influence of deep learning in the field of medical image analysis. This research discusses the potential of image super-resolution to enhance the precision of medical image categorization. This paper compares three super-resolution methods: bicubic interpolation, Super Resolution Residual network (SRResnet), and Super Resolution Generative Adversarial Networks (SRGAN), using the OCT2017 dataset for optical coherence tomography (OCT) images. The experiments reveal that deep learning-based super-resolution methods surpass bicubic interpolation in boosting classification model accuracy. Notably, SRResnet stands out as the preferred choice for enhancing classification accuracy, despite yielding less visually appealing results compared to SRGAN. This suggests that while Generative Adversarial Networks (GANs) and perceptual loss functions hold promise in super-resolution, their translation to improved classification model performance may vary. This papers findings provide guidance for practitioners and researchers in the field, emphasizing that selecting an appropriate super-resolution method could optimize classification models for medical image analysis.
Comparison of deep learning-based models for retinal vessels segmentation
Authors: Bi Zhuorui
Published: July 2024

With the trend of social diversification and the rapid popularization of information, more and more people use mobile phones to deal with matters in life, study and work, as well as a place of entertainment in their leisure time. People use their eyes at high intensity for a long time. In addition, Low eye care attention greatly increases the chance of developing eye diseases. Such lesions are closely linked to eye diseases such as glaucoma and diabetes, and these lesions are the main cause of blindness. The retina has a complex structure, diverse shapes, and high curvature. It is time-consuming and difficult to diagnose diseases from retinal images. Doctors subjective judgments on images account for a large proportion. In order to make segmentation performance more efficient and reduce manual segmentation errors, an intelligent system that can automatically extract retinal blood vessels from fundus images has become an urgent problem. Medical picture segmentation and the merging of machine learning have gained popularity as a study area with the growth and attention of deep learning. Various models are applied to accurate segmentation of the retina. Through computer feature extraction and sample training of images, it can be directly learned from many data samples. The development of this technology saves time and cost, and at the same time meets the medical needs in remote areas. Doctors can efficiently screen and diagnose through the vascular status of the fundus to determine diabetic retinopathy, glaucoma, microaneurysms and other eye disease fundus manifestations.
Comparing the influencing factors of M/G/1 performance indices in queuing theory across different scheduling approaches
Authors: Chen Yu
Published: July 2024

The M/G/1 queue holds significant research value within the realm of queuing theories and systems due to its broad applicability. However, the multifaceted nature of the M/G/1 queue makes its characteristics and scheduling challenges particularly intricate. Key performance metrics include the average response time, average waiting time, system expectancy, and queue expectancy. This study predominantly concentrates on the average response time, average waiting time, and the increasingly emphasized metric, average slowdown. These metrics provide a more holistic view of system performance, unhindered by system size variations. Appropriate scheduling can do more than just decrease the average response and wait times; it holds a specific relevance to achieving equitable scheduling. Among the myriad metrics employed to gauge system efficiency, the fairness index is gaining traction. The crux of this investigation centers on this metric, aiming to delineate the discrepancies in average slowdown between non-preemptive and preemptive scenarios. Furthermore, a delve into the z-transform within the M/G/1 system will unravel the intricacies of the update-reward mechanism, illuminating the performance oscillations of the M/G/1 system across varied timelines.