bluuebunny/crossref_metadata_2025 huggingface dataset:
There goes the Berimbau: An Africa-Brazil-Germany Musician-Body Trajectory
Authors: Grundner Simone
Published: July 2023

This article presents the partial results of a dissertation entitled The role of music in the internationalization of capoeira: Flows and crossroads Rio-France-Germany (2022). Documents prepared by practitioners of the N'Zinga Capoeira School in Hanover, Germany, published on a platform called Yumpu, provide information on how musical-cultural knowledge of capoeira is understood and passed down in this context. Through the translation of songs and the study of informational texts written by German instructors about capoeira, I observe that musicality (and, by extension, corporeality) are fundamenatal to the consolidation of capoeira culture in Germany. This analysis is influenced by Leda Martins' Performances da Oralitura (2003), which highlights the enduring African root in Afro-diasporic cultural activities, transmitting africanidades ("Africanities") beyond the performance itself. Paul Gilroy's The Black Alantic (1993) also informed my understanding of the relevance of Black culture in critiques of European democracy. German capoeira practitioners gain a deeper understanding of the structural differences imposed on racialized people when they coexist with their mestres and learn of oppression and social difference through the art of capoeira.
PENGARUH PENDIDIKAN KESEHATAN TERHADAP TINGKAT PENGETAHUAN ORANG TUA TENTANG GIZI ANAK USIA SEKOLAH MELALUI MEDIA POSTER
Authors: Kusuma Ratna , Aprilia Nuryanti
Published: July 2023

Background. School age is the age when growth and development is very rapid so that it requires good nutrition so that the growth and development of the body is balanced. The role of parents is very influential on the growth and development of children which will also affect the nutritional state of children. One of the efforts to overcome the incidence of under or over-nutrition of children is through increasing the level of knowledge of parents by increasing understanding regarding the nutrition of school-age children through health education. Provision of health education to parents about the nutrition of school-age children must use appropriate means and methods in order to attract attention so that they can easily absorb the information provided. One of the methods and media used is lectures using media poster.Purpose. To determine the effect of health education on the level of parental knowledge about the nutrition of school-age children through media poster.Methods. The research method uses pre-experimental with one group pre-posttest design. Respondents amounted to 129 parents of elementary school students. Sampling used in this research is total sampling.Result. The effect of health education on the level of parental knowledge about the nutrition of school-age children through media poster shows that the research respondents before carrying out health education on the nutrition of school-age children had an average value of 6.71 and after carrying out health education on the nutrition of school-age children had an average value of 10.88. Statistical test results using the Wilcoxon test value = 0.000.Conclusion. There is an effect of health education on the level of parental knowledge about the nutrition of school-age children through media poster.
La Importancia de la Inteligencia Emocional para los Entrenadores de Tenis
Authors: Van de Braam Merlin
Published: July 2023

Este artículo intenta presentar a los lectores el concepto de Inteligencia Emocional (IE) y cómo se aplica al campo del entrenamiento de tenis. La investigación reciente muestra cómo la IE, dentro de un contexto de entrenamiento, puede tener más consecuencias de satisfacción y éxito en la carrera que otras teorías sobre la inteligencia como la del coeficiente intelectual (CI).
La Formación de las Mejores Tenistas (1968-2012) y la Importancia de un Entrenamiento Bien Planificado
Authors: Królak Adam
Published: July 2023

La formación de las mejores tenistas que ganaron 179 torneos de Grand Slam entre 1968 y -2012 y que escalaron hasta alcanzar los mejores lugares de la clasificación de la WTA indica que el proceso de entrenamiento progresivo basado en obtener los mejores resultados cuando la jugadora madura es superior al programa intensivo caracterizado por una aceleración no natural del entrenamiento y de la competición, con el fin de lograr el éxito inmediato en la categoría junior o incluso en etapas anteriores.
Intervención Multi e Interdisciplinar en Tenis
Authors: Pacharoni Rafael
Published: July 2023

Cuando se emprende un proyecto dirigido hacia el alto rendimiento en el tenis es necesario establecer una comunicación clara y constante entre todo el equipo multidisciplinar, quienes en la situación actual, necesitan realizar un proceso de descentralización que consiste en compartir las tareas y el conocimiento entre los profesionales de las diferentes áreas de trabajo que componen ese equipo interdisciplinar
Un Novedoso Análisis de las Variaciones de la Empuñadura para el Revés a Dos Manos
Authors: Eng Doug , Hagler Dave
Published: July 2023

Este artículo comenta las variaciones de las empuñaduras utilizadas para el revés a dos manos. Presenta un análisis cualitativo y longitudinal de los 100 mejores tenistas profesionales del circuito ATP y WTA. Explica el concepto de los espacios entre las manos, las empuñaduras potentes y de precisión junto con una descripción más tradicional de las mismas. Se comentan también las diferencias individuales y de género.
Circulating Particles and Related Nucleic Acid as Highlighted Biomarker in Prostate Cancer
Authors:   Mashhad University of Medical Sciences, Iran, Ghazizadeh Elham
Published: July 2023

Since prostate cancer (PC) is the second most malignancy in men, the accurate and timely detection is crucial. Presently the gold standard test in prostate cancer detection is about Prostate-specific antigen
O Argumento em Favor da Existência de Deus a partir do Livre Arbítrio
Authors: Ribeiro Fábia Rodrigues
Published: July 2023

O livre-arbítrio e o determinismo são temas centrais na história da filosofia, da religião, do direito, sendo parte de uma das grandes questões da humanidade. Tal debate envolve questões paradoxais que permeiam a mente humana desde tempos remotos até os dias de hoje, retratando causa de tensão e ambiguidade para as quais não se tem respostas concêntricas. Esta pesquisa visa apresentar um argumento em favor da existência de Deus a partir do livre-arbítrio. Mais precisamente, o argumento visa defender que, como o Naturalismo não deixa espaço para o livre-arbítrio, segue-se que tal capacidade só pode ser concedida por alguém como Deus, que é absolutamente livre. Assim, se temos boas razões para pensar que o livre-arbítrio existe, e como somente em uma cosmovisão teísta o livre-arbítrio consegue encontrar espaço, então temos um argumento em favor da existência de Deus. Para isso, primeiramente refletiremos sobre o porquê do Naturalismo não deixar espaço para o livre-arbítrio. Em seguida, levantaremos algumas razões para refletir sobre a possibilidade de que termos livre-arbítrio é mais racionalmente plausível do que o contrário. Ademais, analisaremos alguma possível objeção contra esse argumento.
Interconnected Disaster Risks
Authors:   United Nations University - Institute for Environment and Human Security (UNU-EHS), O'Connor Jack , Eberle Caitlyn , Narvaez Liliana , Higuera Roa Oscar , Oakes Robert , Sparkes Edward , Sebesvari Zita
Published: July 2023

The 2021/2022 edition of the Interconnected Disaster Risks report analyses 10 disasters from around the world and explains that these events are interconnected with each other, with other larger, underlying societal processes, and with our collective behaviors and actions. Through forensic analysis, the key root causes featured among the 10 cases were an Insufficient risk governance, related to laws and practices that perpetuated or created complications in the formation of the disaster, and Undervaluing environmental costs, signifying the tendency to prioritize the economic costs of an endeavor over the potential environmental impacts. The report also identifies solutions that can help to prevent or better manage them in the future. Common solutions included Letting nature work and Innovating, but cannot be implemented in isolation given the interconnected nature of the disasters. To this end, solution packages were designed for each of the ten cases, showing how solutions themselves must be interconnected to make a lasting impact. Improving our understanding of the role of interconnectivity not just in the causes of disasters but also in turn their solutions is key for finding innovative ways to enhance our disaster risk reduction strategies.
Women’s issue in Afghanistan under the Taliban*
Authors: Okimbekov U. V.
Published: July 2023

The article is devoted to the study of the rights and status of women in Afghan society over the past 30 years, after the end of the secular system in the country. A brief overview of the situation since the beginning of the 20th century is given, the place and position of Afghan women in society after the coming to power of the Mujahideen and then the Taliban* is shown, the development of education and the process of involving the female population in socio-economic and political life after 2001 and the change in the situation with the return to power of the Taliban are studied.
The Social Challenges to the New Government of Taliban*
Authors: Zimin I. A.
Published: July 2023

The article is devoted to the measures taken by the new Taliban* Afghan government in social policy to get relative internal legitimacy and at the same time pursue a radical course aimed at the harsh Islamization of Afghan society. It is shown how the Taliban are implementing measures in serious social situation, and the contribution of the new Afghan authorities to the stabilization of the humanitarian situation is analyzed.
Genesis and Evolution of the Taliban*
Authors: Nessar O. M.
Published: July 2023

The article analyzes the main stages of the evolution of the Taliban* movement. Considering the transformation of the military-political activity of the movement, the author identifies five main stages: the birth of the Taliban*, the first reign, a period of calm, a period of revival and re-rule. According to the estimates presented in the article, the main goals and objectives of the Taliban* have not changed much over 20 years, but the composition of the movement has changed, which was reflected in changes in the prohibition policy.
Afghanistan and the “Great Chessboard”
Authors: Slinkin M. M.
Published: July 2023

The article is devoted to US politics in Eurasia in the context of the US claims to a key role in the world and the desire to independently manage the pieces on the “Great Chessboard”. The article examines US policy in the Middle East and the relationship between the military campaign in Iraq and the situation in Afghanistan. The author concludes that at present the United States concentrated attention on the territories around the Russian Federation, forming a belt of unfriendliness.
Sediment’s production in coastal urban watersheds and potential impact to the health of living beings
Authors: Oliveira Lusanira , Matos Alarcon , Santos Rosângela
Published: July 2023

Unplanned populational development is the reason of a huge impact in the environment, especially in urban areas. Production of solid waste has been gradually increased and its disposal usually occurs in inappropriate places, as in the headwater of rivers. With respect to water resources, the presence of pollutants results in a significant damage to water ecosystem by turning into an insanitary environment, and harmful to people’s life quality. Such damage refers to sediments, fertilizers, oils, heavy metals, among others, that are usually thrown in different watersheds, mainly in the urban ones.
Estructura Fractal para el desarrollo de proyectos de ingeniería. Un paradigma emergente ante los retos del Covid-19.
Authors: Minguet Edmundo
Published: July 2023

En el presente artículo de investigación se desarrolla una propuesta de estructura organizacional para la ejecución de proyectos de ingeniería con base en la fractalidad como paradigma emergente, con el propósito de facilitar la ejecución de proyectos en entornos virtuales, caóticos y entrópicos; en respuesta a las restricciones de movilidad y comunicación relacionadas con la pandemia de Covid-19, las cuales han sido parcialmente compensadas por las ventajas de la virtualización del trabajo, una tendencia que parece irreversible, debido a la reducción de costos directos asociados a la infraestructura requerida para el desarrollo de los proyectos. Este proceso de adaptación requiere profundos cambios, tanto en lo metodológico como en lo estructural.
Gerencia ecológica en el contexto de la complejidad del desarrollo sostenible
Authors: Rondón Erivan , Torres Auresnelly
Published: July 2023

La concepción de la temática ambiental y ecológica producida por la relación de la actividad humana con el medio natural, repercute notablemente sobre la conservación y la preservación de la vida y del planeta. En este sentido, la gerencia actual no debe vulnerar la importancia de la interrelación del hombre con el ecosistema, puesto que esta se comprende en términos de complejidad y el principio de autonomía/dependencia. En este contexto, se plantea el siguiente artículo que tiene como propósito general analizar la gerencia ecológica actual en función del desarrollo sostenible, fundamentado desde el punto de vista metodológico en una revisión documental, la cual, con base en referentes teóricos gerenciales, permite realizar un proceso de análisis e interpretación que aporta reflexiones significativas respecto a la alerta ecológica contaminante que se avecina para el futuro de la humanidad y que se trata actualmente de un hecho sin precedentes.
Control interno en la gestión administrativa pública
Authors: Criollo Virginia , Morante Manuel
Published: July 2023

Las entidades públicas deben contar con un proceso que permita detectar a tiempo cualquier desviación que afecte el alcance de sus objetivos, lo cual se conoce administrativamente como control interno. En este contexto, la investigación realizada tuvo como objetivo analizar algunas propuestas teóricas sobre el concepto de control interno, con la finalidad de conocer cómo ha sido enfocado dicho constructo en el ámbito de la gestión pública, en periodos recientes; de esta manera se desarrolló un estudio documental basado en la revisión de literatura primaria de los últimos años sobre el tema o que abordan esta problemática, lo cual se realizó desde un enfoque cualitativo y con un alcance descriptivo. Los resultados muestran similitud de criterios en los enfoques y aportes sobre el término, enfatizando la importancia de que las instituciones públicas establezcan con claridad el funcionamiento de sus dependencias para garantizar la transparencia y la integridad, que devuelva la confianza en la población.
Percepciones del consumidor sobre los bodegones como nuevo canal de ventas. Estudio Empírico
Authors: Baskin Roberto
Published: July 2023

El objetivo de la presente investigación fue explorar la interacción y percepciones básicas del consumidor con respecto a la nueva iniciativa privada de canal de distribución en Venezuela, denominada bodegones. Ciertas condiciones del mercado como despenalización de las transacciones en divisas, arancel cero para cientos de productos importados y relajamiento de los controles de precios, han creado las condiciones desde el año 2019 para el desarrollo de este nuevo canal de distribución. Metodológicamente se recurrió a datos de fuente primaria que provinieron de una investigación propia de enfoque cuantitativo, que utilizó como técnica de recolección de datos una encuesta on-line. Los resultados indicaron que la penetración del canal es alta, pero las visitas muy espaciadas (factor moda), existe dificultades para generar lealtad y recompra, y la experiencia de cliente en relación a la compra fue vista como deficiente.
Comercio informal, los tributos y el derecho al trabajo. Caso de estudio: Provincia El Cantón Ambato, Ecuador
Authors: Masabanda Galo , Arcos Carlos , Noriega María , Aman Alexandra
Published: July 2023

El derecho al trabajo en la República de Ecuador, se encuentra amparado y regulado en el ordenamiento Constitucional, lo que permite el desarrollo de una actividad económica o de producción. En tal sentido la actividad ejercida por los comerciantes debe desarrollarse en apego al Derecho Mercantil y Tributario, razón por la cual, la presente investigación tuvo como objetivo determinar la sujeción a la ética y a las obligaciones tributarias de los comerciantes informales, en la provincia de El Cantón Ambato, de la República de Ecuador. Para lograr el objetivo se aplicó un estudio cuantitativo y de campo, lo que permitió mantener un contacto directo con aquellas personas que desarrollan está actividad económica y con la colectividad, quienes se constituyen como usuarios o consumidores. La muestra estuvo conformada por ciento cincuenta (150) comerciantes informales. Como resultado se obtuvo que la mayoría de los comerciantes informales no cumplen con los deberes fundamentales en el marco del Derecho Tributario regidos en el Estado Ecuatoriano; lo que conllevó a concluir que los comerciantes informales ejercen su actividad en desacuerdo con las leyes, distorsionando el orden público y evadiendo la parte tributaria.
Hacia la sociedad del futuro, del caos a la fractilidad. Una visión prospectiva
Authors: Minguet Edmundo
Published: July 2023

Los venezolanos han sido testigos en los últimos años de la “derrota de la razón”, la sustitución de la calidad de vida por diferentes opciones de supervivencia. Esta situación referida al desmejoramiento de la calidad de vida, no es única en el país. Se puede leer continuamente noticias que reflejan que aún en los países desarrollados prevalece el absurdo en casi todos los ámbitos de la sociedad, lo cual está llevando a una convivencia cada vez más complicada y condicionada. Ante esta situación, cabe reflexionar sobre el papel que juegan dos tipos de insectos en nuestro planeta: las lombrices y los bachacos. Las lombrices de tierra consideradas benefactoras debido a su influencia positiva sobre los ecosistemas. Los bachacos, por el contrario, actúan mayormente durante la noche, cortando el follaje de las plantas, degradando la calidad de los cultivos. Este artículo es una reflexión respecto a las estructuras sociales que facilitarían el desempeño de actores anónimos comprometidos por el bien común y el desarrollo sostenible que requiere la sociedad.
Una mirada ética universitaria en la gerencia andragógica en las ciencias de la salud
Authors: Pernía Dexsi
Published: July 2023

Este artículo fue concebido en el seminario “Generación del Conocimiento”, el cual es parte del pensum de estudio en el Doctorado de Pedagogía, del Núcleo Valle del Mocotíes de la Universidad de Los Andes, Venezuela. En la interacción del seminario, se profundizaron en diversos artículos relacionados con la temática de generación del conocimiento, que conllevó a la realización del artículo titulado Una mirada ética universitaria en la gerencia andragógica en las ciencias de la salud. El propósito del presente artículo es indagar, desde una mirada ética universitaria, en la gestión andragógica de las ciencias de la salud que conlleven a reflexionar sobre el comportamiento del ser en estos espacios educativos universitarios, hacia la implementación del valor ético en los procesos andragógicos acordes a la realidad del ser. Los procesos universitarios, en especial en las ciencias de la salud, tienen una relación inevitable con la gestión andragógica universitaria, llevada a cabo por los gerentes educativos o docentes, sustentados en los principios éticos.
Relationship between Total Flight Hours and Individual Factors with Low Back Pain in Indonesian Military Helicopter Pilots
Authors: Fazlin Khuzaima  , Wibawanti Retno , Sugiharto Agus , Mulyawan Wawan ,  Ilyas  M. , Soemarko  Dewi S.
Published: July 2023

Introduction: Helicopter pilots are potentially at risk of Low Back Pain (LBP) and are twice as likely as fighter pilots to experience it. Helicopter pilots’ LBP is caused by a combination of risk factors: engine and rotor vibration, ergonomic risks due to cockpit design, static seating position due to operations, and individual factors. These factors are incorporated into cumulative aviation risk exposure, which can be measured by total flight hours. The prevalence of LBP in Caucasians is high, at 50.5%-92%. However, there has not been any research on Indonesian military helicopter pilots who have a different posture from Caucasians.Objective: To determine the prevalence of LBP, to analyze the relationship between total flight hours and individual factors (age, height, BMI, exercise habits, and smoking habits) with LBP in Indonesian military helicopter pilots.Methods: The study was conducted at the Indonesian Army and Indonesian Air Force with total sampling method as many as 124 people. An explanation was carried out followed by filling in the consent to become a research subject, filling in personal data, anamnesis, Numeric Rating Scale (NRS), physical examination, neurological examination, and total flight hour data.Results: There were 124 subjects, consisting of 37.9% pilots and 62.1% copilots, 87.9% of pilots operate large helicopters, have average total flight hours of 450 hours, age of 30 years, the height of 172.66 cm, low intensity exercise habits of 61.3%, and smokers as much as 45.2%. A total of 57 people (46%) experienced LBP. Statistical results showed that total flight hours had an association with LBP (p = 0.035) where each 1 unit increase in total flight hours had a 1.02 times greater chance of LBP.Conclusion: The prevalence of LBP is 46% and there is an association between total flying hours and LBP in Indonesian military helicopter pilots.
Media Tracking of Early Sentiments about COVID-19 Vaccine in Africa
Authors:   World Health Organization Office for the Eastern Mediterranean, Nasr City, Cairo, Egypt, Ayodele James , Djoudalbaye Benjamin ,   Division of Health Diplomacy, Policy and Communications, Africa Centers for Disease Control and Prevention, Addis Ababa, Ethiopia, Gweh Nekerwon ,   Division of Health Diplomacy, Policy and Communications, Africa Centers for Disease Control and Prevention, Addis Ababa, Ethiopia
Published: July 2023

Background: Advances in digital technology have made real-time listening and analysis of traditional and social media discussions possible over a selected geographical area. However, the technology is currently not widely available to inform public health risk communication. Aim: This paper reports the use of digital rumor monitoring system to present major sentiments tracked by Africa Centres for Disease Control and Prevention (Africa CDC) over traditional and social media regarding the COVID-19 vaccine during the first 9 months of the COVID-19 pandemic. Methods: Rumors and misinformation about the COVID-19 vaccine were tracked by Africa CDC over the digital rumor monitoring system from March to November 2020. Traditional media analysis was conducted using African media and human-curated aggregation of open-source content from various African sources. Social media analysis was conducted using geo-located African Twitter and Facebook sources, resulting in a set of content from the media. Results: COVID-19 vaccine had the highest traction among COVID-19 rumors monitored in Africa between March and September 2020. Critical narratives were observed mainly in South Africa, Democratic Republic of Congo, Nigeria, and Kenya, where they undermined public views of the COVID-19 vaccine and the vaccine trials. Analysis shows underlying potential for vaccine acceptance is overshadowed by anti-vaccine rhetoric partly influenced by insufficient information about the vaccine in the public domain and the disapproval of “Western vaccine” by Africans. Conclusion: Realtime digital monitoring of rumors and misinformation about public health issues over social and traditional media is now possible. Health authorities and health institutions need transition to this real-time monitoring and build the capacity of their staff to use information from real-time analysis of rumors and misinformation for designing response. Larger scale investment in the technology is critical to make it available for wider use at the national and sub-national levels in Africa.
Using Inverse Dynamics Technique in Planning Autonomous Vehicle Speed Mode Considering Physical Constraints
Authors:   Department of Civil Engineering, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada, Diachuk Maksym , Easa Said M. ,   Department of Civil Engineering, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada
Published: July 2023

The study aims at improving the technique of planning the autonomous vehicles’ (AV) speed mode based on a kinematic model with physical restrictions. A mathematical model relates the derivatives of kinematic parameters with ones of the trajectory’s curvature. The inverse approach uses an expanded vehicle model considering the distribution of vertical reactions, wheels’ longitudinal reactions according to a drive type, and lateral forces ensuring motion stability. For analysis of the drive type, four options are proposed: front-wheel drive (FWD), rear-wheel drive (RWD), permanent engaged all-wheel drive (AWD), and 4-wheel drive with torque vectoring (4WD-TV). The optimization model is also built by the inverse scheme. The longitudinal speed’s higher derivatives are modeled by the finite element (FE) functions with nodal unknowns. The sequential integrations ensure the optimality and smoothness of the third derivative. The kinematic restrictions are supplemented by the tire-road critical slip states. Sequential quadratic programming (SQP) and the Gaussian N-point scheme for quadrature integration are used to minimize the objective function. The simulation results show a significant difference in the mode forecasts between four types of AV drives at the same initial conditions. This technique allows redistributing the traction forces strictly according to the wheels’ adhesion potentials and increases the optimization performance by about 40% compared to using the kinematic model based on the same technique without physical constrains.
Modelling of an Adaptive Network Model for Phishing Website Detection Using Learning Approaches
Authors:   Department of Computer Science and Engineering, Faculty of Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, India, Tenis Aldo ,   Department of Computer Science and Engineering, Faculty of Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, India, R. Santhosh.
Published: July 2023

Phishing links are spread via text messages, social media platforms, and email by phishing attackers. Social engineering skills are used to visit phishing websites to trick the users and enter critical information related to personal data. The confidential data is stolen to defraud legitimate financial institutions or general websites for illegally attaining the benefits. Many machine learning-based solutions are in the enhancements and the technology of machine learning applications to detect the suggested phishing. The rules are used for a solution which depends on the extracted features, and few features require to lies on the services of third-party that, creating time-consuming and instability in the service of prediction. A deep learning-based framework is suggested to detect website of phishing. A framework is established to determine if there is a risk of phishing in real-time during the web page is visited by the user to give a message of warming by the browser plug-in. The prediction service in real-time merges the various techniques for enhancing the accuracy to lower the fake alarm rates and the time of computation which has the filtering whitelist, interception of the blacklist, and prediction of deep learning (DL). Various models of deep learning are compared using the different datasets in the module of machine learning prediction. The greatest accuracy is obtained as 99.18% by the adaptive Recurrent Neural Networks (a−RNN) model from the results of experiments to demonstrate the suggested feasibility solution.
A Short Contribution to Split-Complex Linear Diophantine Equations in Two Variables
Authors:   Department Of Mathematics, Tishreen University, Latakia, Syria, Abobala Mohammad
Published: July 2023

In this work, we study the split-complex integer solutions for the split-complex linear Diophantine equation in two variables where are split-complex integers. An algorithm for generating all solutions will be obtained by transforming the split-complex equation to a classical equivalent system of linear Diophantine equations in four variables.
2D image edge detection enhancement using convolutional neural network
Authors: Lin Gaoming
Published: July 2023

Traditional edge detection operators are usually applied on edge detection in 2D image processing. However, the edge detection system equipped with simple operators has many disadvantages, such as high sensitivity to noise and neglect of significant edge details. This work proposed a method to enhance edge detection with convolutional neural net-work. To overcome the shortcomings of the system using simple edge detection operators in 2D image processing, an edge detection system using convolutional neural network was developed with Python language. In the convolutional neural network, two convolutional layers were designed to extract 2D image features that were relative to edge information. Then a normalization layer was applied to normalize the convoluted output. After that, pre-processing was utilized to denoise and smooth the image input. The final step was edge detection using traditional operators. Experiments were also implemented to verify the improvement of the plugin of the three-layer convolutional neural network in the de-signed edge detection system. Relative frequencies were utilized to quantify the edge de-tection performance. Results showed that the involvement of convolutional neural net-work could strengthen edge detection operators performance obviously in computer vi-sion.
Face detection and recognition of mask wearing in normal environment based on neural network
Authors: Li Yanyan , Xie Shubing , Ren Yifei , Li Xinyu
Published: July 2023

With the outbreak of COVID-19, wearing masks has become a hot topic again. In public places, Not wearing a mask correctly has almost the same harm as not wearing a mask. Mask detection is an extension of face detection. Therefore, it is of great practical signifi-cance to design a system that can correctly identify whether pedestrians wear masks cor-rectly. The face recognition technology based on neural network has been relatively ma-ture, but there is still a lack of work related to mask recognition, especially whether to wear masks correctly. This is not only the promotion of a two-classification problem to a three-classification problem, but also faces many practical problems, including data set acquisition, in this paper, mask recognition is divided into a multi-stage work. In the first link, Yolo network is used to recognize facial areas, and in the second link, RESNET is used to realize mask recognition. Finally, a layer of RESNET network is improved to achieve higher recognition accuracy.
Classifying autism spectrum disorder using machine learning through ABIDE dataset
Authors: Han Wenhao , Shao Wenzhu , Wang Yaluo
Published: July 2023

A neurodevelopmental disorder named autism spectrum disorder (ASD) is challenging to diagnose. The prevailing diagnostic manner is based merely on the behavioral measure-ment with a high tendency of misdiagnosis. People require an advanced method to make more quantitative diagnosis. In this paper, two deep learning architectures were explored with the machine learning methods. The Mixup method was used to augment the original functional Magnetic Resonance Imaging data. Features of the data extracted by two dif-ferent kinds of autoencoders which are Sparse Autoencoder and Variational Autoencoder were used as inputs of two deep neural networks functioning as classifiers respectively. The models can classify patients with ASD from typical control subjects with the accura-cy of 75.5% and 75.2% respectively, which outperformed the other state-of-the-art meth-od by 4.7% and 4.4%. The further significance of this project is to help develop our per-ception of the neurobiological foundation of the ASD.
Wiki-match: A multi-model pipeline for image-caption matching task on Wikipedia dataset
Authors: Chen Yibing , Lei Siyu , Sun Zhouhang
Published: July 2023

We propose a multi-model pipeline for image-caption matching tasks on Wikipedia-based dataset which leverages object-detection technique and attention mechanism to achieve fine-grained matching between textual representation and image representation. Different from the prior research, we not only evaluate our pipeline effectiveness on common benchmark dataset such as MS-COCO and Flickr30k, but also a new dataset that is de-rived from Wikipedia which is rich in natural entities and abstract concepts. Our findings show: 1) our model pipeline improves R@1 by 113.4%, R@3 by 86.1%, and R@5 by 114.4% compared to the original pipeline provided by the Wikipedia-based dataset. 2) our model pipeline has close to the state-of-the-art performance in common benchmark dataset including Flickr30k and MS-COCO. 3) images that are from Wikipedia creates bigger challenges for models to understand compares to MS-COCO or Flickr30k due to the abstract concepts and broad topics covered by Wikipedia.
Using natural language processing and machine learning algorithm for book categorization
Authors: Wang Danrui , Tan Bowen , Wei Muchen , Cui Xuhao , Huang Xingru
Published: July 2023

This research analyzed the relationship between multiple elements of a book's classifica-tion through natural language processing and machine learning. This paper used SVM and KNN to classify books according to the titles and author respectively. Also, books are categorized by summary through Decision Tree, Nave Bayes and BERT. In the end, this work compared effects of these methods. Our findings show that 1) books have different levels of categorical characteristics in various parts of the book 2) through combining the title, author, and summary of the book, more accurate classification results were obtained 3) BERT achieved more accurate recognition compared to a variety of other algorithms used.
Pathological prediction of heart disease based on deep width learning algorithm
Authors: Chew Mon Hian , Yang Po , Zhao Zhengguang , Chen Yuehui
Published: July 2023

As the technology has become more and more advance and massive data has been produced and pre-processed became useful information to become big data so come out a lot of technology like data mining, neural network, deep learning, etc. Each technology has its advantages, this paper put forward the width of the depth of the learning algorithm is to the advantage of two types of deep learning methods This new method is combining of Flexible Neural Tree(FNT) and Broad Learning System(BLS) to become a new deep width network. After several times of experiments, we can confirm that this new hybrid method can increase the accuracy, sensitivity, and specificity of Heart disease prediction. Therefore, having higher accuracy of prediction for heart disease means we can notice more people before having heart disease and start to prevent it and in the end, we can prevent loss of life and economy.
MLStock: Multi-layer model for sentiment analysis based stock price prediction
Authors: Xu Tianyang , Xiang Zongyuan , Lu Bingjian , Chen Nuo , Dai Ziqi
Published: July 2023

In this paper, we address the task of predicting stock prices using the market sentiments extracted from Twitter. We propose MLStock, a multi-layer framework that models the market sentiment with the stock layer, the sector layer, and the market layer using the Gated Recurrent Unit (GRU), and use the sentiment to make directional prediction on stock price. Existing methods consider stocks individually, and might miss the signals in the current market sector which will affect the stock later. In contrast, our model summa-rizes the sector and market states through individual states and shows an improvement over traditional machine learning methods.
Center of darkness: Attacks and defensive strategies on blockchain consensus algorithm
Authors: Fang Liuyi
Published: July 2023

ith the rapid development of blockchain technology, more and more attention has been paid to the core consensus algorithm, and the related security problems have followed. For example, due to the loopholes in the consensus algorithm, the Bitcoin Gold platform lost about 18 million USD. Therefore, how to avoid such attacks against the consensus algorithm is an unavoidable topic for everyone involved in the blockchain platform. Starting from the mainstream consensus algorithm, this paper introduces their evolution process and their respective principles. In addition, we also introduce the possible attack principles and harms from two perspectives. One is general, that is, attacks under this category are not limited to specific consensus algorithm and platforms. The other type is specific, that is, the vulnerability locates in specific consensus algorithm. At the end of this paper, we divide all the personnel involved in the blockchain into three categories, and put forward specific suggestions for each category of personnel to help them better avoid and respond to possible attacks on the consensus algorithm.
A multivariate LSTM-based deep learning model for stock market prediction
Authors: Olotu Samuel Ibukun
Published: July 2023

Stocks represent ownership in a company and a proportionate claim on its assets and earn-ings. Investors trade stocks via an exchange by buying at a price and selling at a higher price. Due to market volatility forecast it is a necessity for trading to determine the direc-tion of the stock price in order to maximize profit and minimize loss. Traditional methods of stock price predictions include technical and fundamental analysis. The technical deals with historical price movement while fundamental analysis uses the relationship between financial information about the company. However, these predictions methods sometimes fail to yield desired result sometimes due to the influence of factors such as national poli-cies, global and regional economics, psychological, human among many. This work propos-es a prediction model for stock market using LSTM algorithm. Multivariate time series stock price data is obtained from Nigerian Stock Exchange Index to implement the model. The experimental result of the technique is measured using MAPE, MAE, MSE and rRMSE performance metrics. The accuracy of the result shows that the proposed system outper-forms existing traditional and deep learning methods.
Cognitive radio: SSDF attack and security
Authors: Song Liangyu , Shen Shuqi , Cao Yujie , Lyu Xiaoming
Published: July 2023

Cooperative spectrum sensing can improve the performance of system detection, but when there are some malicious users in sensors, they will launch spectrum sensing data falsification attack, this is to say they send false sensing result, which will have a great influence on the final decision of fusion center and the primary user. Given that, this paper proposes a basic cooperative spectrum sensing algorithm based on reputation to defend malicious users and then improve that algorithm, advance a new algorithm-reputation weighted cooperative spectrum sensing algorithm.Verified by simulation, our algorithm has achieved the expected effect. The first algorithm can effectively resist attacks especially when the attack probability of malicious users is high. When malicious users are more intelligent, their attack probabilities are different from each other and are uncertain. At this time, the second algorithm can better improve the performance of the final decision of fusion center.
Deep fake detection using deep learning techniques
Authors: S. Gayathri , S. Santhiya , T. Nowneesh , K. Sanjana Shuruthy , S. Sakthi
Published: July 2023

Deep fake is the artificial manipulation and creation of data, primarily through photo-graphs or videos into the likeness of another person. This technology has a variety of ap-plications. Despite its uses, it can also influence society in a controversial way like de-faming a person, Political distress, etc. Many models had been proposed by different re-searchers which give an average accuracy of 90%. To improve the detection efficiency, this proposed paper uses 3 different deep learning techniques: Inception ResNetV2, Effi-cientNet, and VGG16. These proposed models are trained by the combination of Facfo-rensic++ and DeepFake Detection Challenge Dataset. This proposed system gives the highest accuracy of 97%.
Cost-Efficiency Evaluation into the European Union Budget
Authors: Sanchez-Bayon Antonio , Sastre Segovia Fco. Javier , Vega Ricardo Altimira
Published: July 2023

This review is a qualitative study, according to the heterodox approaches, assessed the leading beneficient State under the European Union budget system. For this purpose, the study utilized the Multiannual Financial Framework reports between 2014-2020, which dealt with more than 700 indicators, measuring success against more than 60 general objectives, and more than 220 specific objectives in the performance framework. Therefore, trade globalization, political economy, economic history, social contribution by the European Union budget, and international economics under new-institutional economics have been evaluated in this process. Assessment outcomes found that poorer Member States are the net beneficient regarding the European Union budget’s net balance and financial corrections. However, Germany is the leading beneficient of the European Union budget system as it has extended trade to all along the border of the European Union without tariffs and has become a more cost-effective economy against the outside economies (like the United States of America or China) of the European Union territory. Thus, the current study suggested that nations under the European Union budget system should invest more in sustainable production to get real-time benefit from the European Union integration.
The Impact of Infrastructure Quality on China’s OFDI: A Study Based on RCEP Partners
Authors: Xie Guo-e , Lin Yi-ni
Published: July 2023

Infrastructure plays a crucial role in facilitating economic development and attracting foreign direct investment (FDI) in a country. With the implementation of the Regional Comprehensive Economic Partnership (RCEP) Agreement, trade and investment ties between China and its RCEP partners have been further strengthened. This study investigates the influence of host country infrastructure development on China’s outward FDI (OFDI) within RCEP partners. By analyzing China’s OFDI to RCEP partners and the infrastructure characteristics of member countries, we explore the impact of host country infrastructure quality on China’s OFDI. Using panel data on China’s direct investment stock in 12 RCEP countries from 2008 to 2020, in conjunction with host country infrastructure quality indicators, we apply a fixed-effect regression model to examine the effects of different types of infrastructure quality on China’s OFDI. Our results reveal that transportation, communications, and energy infrastructure in host countries significantly promote Chinese OFDI. Furthermore, we find that a larger market size, population, and higher trade openness in the host country effectively attract FDI from China. Based on these empirical findings, we provide recommendations to optimize the capital flow and enhance the efficiency of China’s OFDI.
On meromorphic solutions of Malmquist type difference equations
Authors: Korhonen Risto , Zhang Yueyang
Published: July 2023

Recently, the present authors used Nevanlinna theory to provide a classification for the Malmquist type difference equations of the form \(f(z+1)^n=R(z,f)\) \((\dagger)\) that have transcendental meromorphic solutions, where \(R(z,f)\) is rational in both arguments. In this paper, we first complete the classification for the case \(\deg_{f}(R(z,f))=n\) of \((\dagger)\) by identifying a new equation that was left out in our previous work. We will actually derive all the equations in this case based on some new observations on \((\dagger)\). Then, we study the relations between \((\dagger)\) and its differential counterpart \((f')^n=R(z,f)\). We show that most autonomous equations, singled out from \((\dagger)\) with \(n=2\), have a natural continuum limit to either the differential Riccati equation \(f'=a+f^2\) or the differential equation \((f')^2=a(f^2-\tau_1^2)(f^2-\tau_2^2)\), where \(a\neq 0\) and \(\tau_i\) are constants such that \(\tau_1^2\neq\tau_2^2\). The latter second degree differential equation and the symmetric QRT map are derived from each other using the bilinear method and the continuum limit method.
Exploring Specialty Selection and Influencing Factors among Medical Students and Postgraduates: An Observational Study
Authors: Arif Muhammad Maaz , Nisar Wardah , Agha Khadija , Qureshi Muzammil Ghaffar , Mansoor Amen , Malik Asad Ullah , Khokhar Muhammad Sohaib , Awan Fatima , Khwaja Sarah Irfan , Parveen Aqsa
Published: July 2023

Medical students are driven by interest and influenced by factors like early exposure, training, environment, teaching, role models, rewards, appreciation, patient feedback, and mentorship. Gender also impacts specialty choices. Students' career choices shape the future workforce. Objective: To explore interests and factors influencing specialty choice among post graduate trainees and final year students, aiming to guide informed career decisions and address inadequate recruitment in specialties. Methods: This study was an observational cross-sectional study conducted at Fatima Memorial Hospital and college. Data were collected from 163 participants via online questionnaire using non-convenience sampling. Analysis was conducted using SPSS software, including frequencies, percentages, averages and t-test to assess statistical significances. Results: Study finds strong preference for clinical subjects among final year and postgraduate students. Divergence among specialty selection was seen as final year students favor general surgery, while postgraduate trainees lean towards pediatrics medicine. Prestige and social responsibility were common influential key factors, with salary benefits impacting more the final year students and specialty prestige, social responsibility and research opportunities weighing on postgraduate trainees were seen. The research also explores that family influence for final year students and teachers and senior doctors for postgraduate trainees in specialty selection. Conclusions: In conclusion, final year and postgraduate trainees prefer clinical specialties like general surgery and pediatrics, driven by considerations of future salary, working hours, and social responsibility. Family, teachers, and senior colleagues play crucial roles in specialty selection decisions.