bluuebunny/crossref_metadata_2025 huggingface dataset:
El rol del obstetra en política: Propuesta hacia dónde apuntalar como gremio obstétrico
Authors: Rivera-Felix Lauro , Ramos-Cárdenas Mayra
Published: July 2024

El presente artículo es una síntesis de la ponencia titulada “el rol del Obstetra en Política”, realizada en el X Congreso Internacional, Salud Sexual y Reproductiva con enfoque de curso de vida, genero, derechos y aplicación de nuevas tecnologías. Organizado por el Colegio Regional de Obstetras III Lima – Callao los días 13 y 14 de octubre de 2017; ésta, nace de una investigación operativa sistemática y sostenible de los últimos años, acerca de la coyuntura política electoral regional y local del país. En un principio, nos propondremos discernir ¿quiénes somos dentro de este contexto político?, ¿Dónde estamos situados?, ¿Cuál es nuestro rol hasta el momento?, para luego ser explícito en ¿Cuál es nuestro potencial? y finalmente, ¿hacia dónde debemos de apuntalar como Gremio? El desarrollo del trabajo permitirá hacer un análisis de como los Obstetras desde el espacio en salud empoderados, podemos adentrarnos en política y actuar frente a ello. Proyectándonos a los comicios del futuro.
Reacciones adversas por uso del misoprostol en gestantes, Perú: Una revisión
Authors: Ramirez-Arche Diana , Quispe-Flores Alexandra , Quijada-León Ernesto , Ramos-Leguia Cecilia , Quispe-Salazar Yasser
Published: July 2024

Objetivo: Determinar la frecuencia de las reacciones adversas por uso del misoprostol en gestantes. Material y métodos:Se utilizó un método observacional como recolección de datos de este informe, por ello, se emplea herramientas digitales para la búsqueda de información en páginas verídicas y científicas como Pubmed y Scielo que incluyen estadísticas y datos objetivos para la elaboración de este informe en relación con los efectos adversos del uso del misoprostol. Resultados: En los 17 artículos revisados, las reacciones adversas maternas por uso de misoprostol fueron: Taquisistolia, Atonia Uterina, Endometritis, resfriado, mareos, náuseas, vómitos, pirexia, diarrea y el Síndrome de hiperestimulación uterina; y las reacciones adversas perinatales fueron: Síndrome de aspiración meconial (SAM), distrés fetal y sufrimiento fetal. Conclusiones: Las complicaciones maternas más comunes son presentadas con la taquisistolia que varía entre un 15,2% y 22,2% de tasa de incidencia en gestantes, mientras que en gestantes de 41 semanas de gestación se observa un 2.5% de casos de endometritis y un 13.5% de las gestantes presentó casos de síndrome de hiperestimulación uterina; entre las complicaciones perinatales se presenta SAM en un 1.3% de los casos revisados y distrés fetal a un total de 3.3% de gestantes de 41 semanas de gestación.
Efectos adversos de los anticonvulsivantes de última generación en gestantes con diagnóstico de epilepsia: Una revisión
Authors: Soto-Quispe Valeria , Sulca-Huaman Alisson , Urbina-Huayanca Madeleine , Vasquez Del Solar Andrea , Velasquez-Rivera Ana , Ramirez-Wong Fernando
Published: July 2024

Objetivo: Determinar los efectos adversos de los anticonvulsivantes de última generación en gestantes con diagnóstico de epilepsia. Material y métodos: Artículo de revisión. Estudio descriptivo con enfoque mixto de tipo exploratorio. La recolección de información se realizó mediante las búsqueda en PubMed, Scopus (Recursos científicos FECYT), DIGEMID, Revista Peruana de Investigación Materno Perinatal y la Revista Peruana de Ginecología y Obstetricia. Resultados: Mediante una revisión sistematizada de artículos, se obtuvo respecto al uso de Topiramato una asociación a malformaciones bucales. Y en cuanto a los fármacos Lacosamida y Perampanel no se puede concluir su efectos adversos debido a la limitada y escasa información. Conclusiones: Se encontró asociación entre el uso Topiramato y malformaciones congénitas bucales durante la gestación, así mismo, respecto al Perampanel se evidenció efectos adversos tales como pérdida post implantación; sin embargo, la falta de información no permite ser concluyente. Respecto al uso de Lacosamida se evidenciaron algunos efectos relacionados con la viso-motricidad, sin embargo existe limitada información.
Conocimientos, prácticas y actitudes sobre el anticonceptivo oral de emergencia en las estudiantes de pregrado de una facultad de medicina peruana, 2021
Authors: Miranda-Huamani Wendy , Melgarejo-Escobar Julia , Mendoza-Gutierrez Lizeth , Miranda-Velásquez Teresa , Naucapoma-Manrique Thaira
Published: July 2024

Objetivo: Determinar la relación entre el nivel de conocimientos, prácticas y actitudes sobre el anticonceptivo oral de emergencia (AOE) que poseen las estudiantes de pregrado de la Facultad de Medicina de la Universidad Nacional Mayor de San Marcos en el año 2021. Material y métodos: Estudio de enfoque cuantitativo, de tipo observacional descriptivo correlacional retrospectivo de corte transversal. Se empleó un cuestionario validado que consta de cuatro apartados, aplicado a 41 estudiantes. Los datos fueron procesados e interpretados a través de un análisis univariado, por tablas de frecuencias y porcentajes, y un análisis bivariado mediante la aplicación del estadístico de prueba Chi Cuadrado. Resultados: El 97.6% obtuvo un nivel de conocimientos bueno; mientras que el 2.4%, malo. Además, el 100% de las estudiantes mostró tener un actitud favorable y prácticas adecuadas. De las estudiantes que iniciaron su vida sexual (68.3%, 28), el 64.2% (18) usaron alguna vez en su vida el AOE y el 39% recibió información del personal médico. Asimismo, con un nivel de significación de 0.05, se halló relación entre conocimientos vs actitudes, conocimientos vs prácticas, y actitudes vs prácticas. Conclusiones: Se halló relación significativa entre conocimientos, actitudes y prácticas en las estudiantes de pregrado de la Facultad de Medicina de la Universidad Nacional Mayor de San Marcos en el año 2021.
Farmacología de los antihistamínicos y su uso en el embarazo
Authors: Gutierrez-Cristobal Milagros , Huamanchahua-Trujillo Liz , Huillca-Huamani Patricia , Huamani-Toro Maela , Inga-Cahuana Kimberly
Published: July 2024

Objetivo: Identificar los fármacos antihistamínicos recomendados en el embarazo. Material y métodos: Mediante la revisión de artículos basados en títulos y resúmenes de la base de datos de PubMed. En los criterios de inclusión encontramos la restricción de resultado a los últimos 5 años, alergia, embarazo, antihistamínicos y embarazo; los cuales son los descriptores MESH. En la extracción tomamos en consideración los artículos que nos proporcionaron información sobre los antihistamínicos, su mecanismo de acción de los antihistamínicos, sus generaciones dentro de los cuales encontramos los fármacos y su categoría en embarazo. Resultados: La administración de antihistamínicos durante la gestación debe darse solamente cuando el beneficio es mayor que el aparente riesgo. Es importante que durante los primeros o en el tercer trimestre de gestación no se utilice ningún antihistamínico, porque se ha demostrado anormalidades en estudios de animales. Conclusiones: Los antihistamínicos se utilizan para tratar alergias mediante el bloqueo del efecto de la histamina. Tienen diferentes presentaciones para su uso, los cuales van a depender del tratamiento más eficaz según el caso clínico. Antes de la administración de antihistamínicos en embarazadas se debe investigar su etiología.
Factores sociodemográficos asociados al abandono del control prenatal en gestantes del Perú
Authors: Timoteo-Barrantes Pierre , Castillo-Velarde Edwin
Published: July 2024

Objetivo: Determinar los factores sociodemográficos asociados al abandono del control prenatal en gestantes del Perú durante el año 2020 Material y Métodos: Es un estudio observacional, transversal, retrospectivo y analítico, la información se obtuvo mediante la base de la encuesta nacional de demografía y salud familiar (ENDES) 2020 del Instituto Nacional de Estadística e Informática. El tamaño de la muestra fue de 4464 gestantes la información fue analizada en el software estadístico SPSS versión 26, se realizó la prueba F corregida para muestras complejas y un nivel de significancia de 0,05.Resultados: Se determino una prevalencia 11.3% (n=470) de Abandono de Control Prenatal, en el análisis multivariado se encontró asociación con las variables edad materna de 15-19 años (Rpa :4,47, IC :2.35 -8.49) ,nivel educativo primaria a menos (Rpa:1,7, IC:1.11- 2.59) ,multiparidad (Rpa:2.33, IC95%: 1.73 – 3.14) , estado civil soltera (Rpa: 1.85 , IC95% :1.26 – 2.70) dentro de los factores institucionales se determinó que la atención por el personal de la salud es factor protector del abandono de control prenatal. Conclusiones: Se identificaron de las variables sociodemográficas la edad materna de 15 a 19 años, el nivel educativo primaria a menos, multiparidad y el estado civil soltera son factores de riesgo para el abandono de control prenatal.
Evolución de cesáreas en el Perú, un elemento a evaluación
Authors: Munares-García Oscar
Published: July 2024

En el Perú, como en otras partes del mundo, la proporción de partos por cesárea, es considerada como alta, con respecto al patrón de referencia de la Organización Mundial de la Salud (OMS) de 15%. Por ejemplo en Paraguay, se encontró 36,28%, En un hospital público de Lima, llegó al 50,2%, y en España, en una comunidad autónoma de Andalucía llegó al 24,8%. Las razones por las cuales, las tasas de cesáreas han aumentando en el mundo son variables, se han determinado varios factores entre ellos tenemos, los embarazos múltiples, cesárea previa, estrato socioeconómico más alto, entre otros. El objetivo es evaluar algunas características de los partos por cesárea en el Perú y cómo han evolucionado en un quinquenio.
Consulta Preconcepcional: Un servicio de salud aun desconocido en el Perú
Authors: Ormachea-Yabar Jiene , Puma-Conde Shery
Published: July 2024

La consulta preconcepcional es poco demandada en el Perú, siendo un servicio que en muchas ocasiones no cuenta con su propio consultorio, por el hecho de no ser promovido por los servicios de salud peruanos, resultando contraproducente para las mujeres en edad reproductiva no conocer la existencia de esta consulta para tener una información y guía previa a la concepción.
Estudio comparativo: Indicadores hospitalarios en el Hospital Nacional Docente Madre Niño San Bartolomé dentro del servicio gineco-obstetricia, 2017-2021
Authors: Cruz-Calderón Melany , Gamboa-Marín Leyla , Gargate-Chavez Rosa , Ibañez-Torres Katia , Alatrista-Gutierrez María , Vela-Ruiz Manuel , Lama-Morales Ricardo
Published: July 2024

Objetivo: Realizar un estudio comparativo de ocho indicadores de salud del Hospital Nacional Docente Madre Niño San Bartolomé dentro del Servicio Gineco-Obstetricia en los últimos 5 años. Material y métodos: se realiza un estudio de tipo retrospectivo, descriptivo, analítico y cuantitativo. Se realizó una búsqueda de la información estadística anual del Hospital Docente Madre Niño San Bartolomé desde enero del 2017 hasta septiembre del 2021. Resultados: Los indicadores de Ingresos Hospitalarios, Ingresos por Transferencia entre Servicios, Altas Hospitalarias, Pacientes por día y Promedio de permanencia, presentaron una disminución en el año 2020. Mientras que el indicador Estancia Hospitalaria, presentó un incremento durante el año 2020. Conclusiones: La pandemia del COVID-19 ocasionó una restricción al acceso de ciertos servicios hospitalarios, siendo uno de ellos el Servicio Gineco-Obstetricia del Hospital Nacional Docente Madre Niño San Bartolomé. Es por ello que, gran parte de nuestros indicadores presentó una disminución de sus cifras en el año 2020.
Diagnóstico de satisfacción de infraestructura y equipamiento en las Facultades de la Universidad Autónoma de Chihuahua
Authors: Ortega-Rodríguez Anabel , Villalobos-Pérez Elizabeth , García-Muñoz Silvia Amanda , Piña-Ramírez Francisco Javier , Leyva-Chávez Arwell Nathán
Published: July 2024

La presente investigación tiene como objetivo identificar la influencia de los programas presupuestarios dirigidos a la comunidad universitaria de la Universidad Autónoma de Chihuahua en las áreas de infraestructura y equipamiento. La población estuvo constituida por los estudiantes de licenciatura de 1° y 2° semestre, estudiantes de licenciatura de 3° a 8° semestre, estudiantes de posgrado, personal administrativo y personal académico de la Universidad Autónoma de Chihuahua. Se realizó el muestreo estratificado proporcional en marzo del 2018, obteniendo como resultado las poblaciones necesarias a encuestar en las facultades y extensiones de Artes, Ciencias Agrícolas y Forestales, Ciencias Agrotecnológicas, Ciencias de la Cultura Física,
Ciencias Políticas y Sociales, Ciencias Químicas, Contaduría y Administración, Derecho, Economía Internacional, Enfermería y Nutriología, Filosofía y Letras, Ingeniería, Medicina y Ciencias Biomédicas, Zootecnia y Ecología. Dichas encuestas se encuentran codificadas y los datos obtenidos se procesaron por medio del programa Statistical Package for the Social Sciences (SPSS) versión 2.0. Esta investigación pretende obtener conclusiones y recomendaciones que serán de utilidad para generar propuestas que ayuden al mejoramiento de la institución.
Efectividad de la aplicación de fertilizantes sintéticos y Biol en el crecimiento y producción de biomasa de caña de azúcar (Saccharum officinarum L.)
Authors: Sánchez-Ramón Claudia Itzel , Hernández-Chontal Mario Alejandro , Rodríguez-Orozco Nereida , Parada-Molina Paulo César , Bautista-Aguilar José Roberto
Published: July 2024

En México, la caña de azúcar (Saccharum officinarum L.) es uno de los principales cultivos que tiene una gran relevancia en el desarrollo agrícola y rural. Sin embargo, el esquema utilizado para su producción representa una fuerte problemática sobre la degradación del suelo, principalmente por el uso de productos químicos. En este sentido, el uso de biofertilizantes y diversas prácticas orgánicas representan fuertes alternativas para la mejora de la fertilidad del suelo. Por lo anterior, el presente trabajo tuvo como objetivo evaluar la efectividad de la aplicación de fertilizantes sintéticos y bioles en el crecimiento y producción de biomasa de caña de azúcar (S. officinarum) en La Candelaria, Tierra Blanca, Veracruz. Se evaluaron 6 tratamientos: Tratamiento 1, fertilización tradicional 20-10-20 ha-1 de N-P-K al momento de la siembra. Tratamiento 2, fertilización tradicional 20-10-20 ha-1 de N-P-K a 30 días después de la siembra. Tratamiento 3 fertilización tradicional al 50% 20-10-20 de NPK al momento de la siembra. Tratamiento 4 fertilización tradicional + biol a 30 días después de la siembra. Tratamiento 5 biol a 30 días después de la siembra y tratamiento 6 testigo sin aplicación. Los resultados muestran que no hay diferencias significativas entre las dosis de fertilización. Por lo tanto, el uso del biol puede ser una alternativa fertilizante para los productores de caña de azúcar y puede contribuir a la transición agroecológica del cultivo.
Efecto de la somatotropina bovina en el desempeño reproductivo de vacas sincronizadas para inseminación artificial y transferencia de embriones en condiciones tropicales
Authors: Lammoglia-Villagómez Miguel Ángel , García-Suárez Alejandro , Rojas-Ronquillo Rebeca , Marini Pablo Roberto , Chagoya-Fuentes Jorge Luis
Published: July 2024

Las necesidades de proteína de origen animal crecen exponencialmente. La productividad de la ganadería bovina está basada en la eficiencia reproductiva. El objetivo de este estudio fue determinar el efecto de la somatotropina bovina en el desempeño reproductivo en vacas sincronizadas para inseminación artificial (IA) y transferencia de embriones (TE). El estudio se realizó al norte del estado de Veracruz, en los municipios de Tamiahua y Tuxpan. Se utilizaron 38 vacas multíparas beefmaster sin becerro para el estudio de IA y 80 vacas F1 (Brahman x suizo) con y sin becerro para TE. Las vacas fueron asignadas: 1) Control y 2) Somatotropina (500.0 mg). Las vacas para IA fueron inseminadas a tiempo fijo y las receptoras fueron transferidas el día 7 después del estro sincronizado, si presentaban cuerpo lúteo (CL). La presencia de CL y el diagnóstico de gestación se realizó utilizando ultrasonografía. Para el análisis estadístico se utilizó STATISTICA 7. Las vacas IA con somatotropina tuvieron mayor (P<0.05) porcentaje de gestaciones (80.0%) que las control (66.7%). En las TE se encontró una interacción significativa (P<0.05) en tratamiento con presencia de becerro en porcentajes de CL y gestaciones. Las vacas con somatotropina y becerro tuvieron mayores porcentajes de CL (79.2%) y gestaciones (57.9%) que las vacas control (50.0% y 36.4%, respectivamente). No hubo diferencias entre grupos en vacas sin becerro. En conclusión, la somatotropina bovina utilizadas en vacas sincronizadas en condiciones tropicales para IA y TE mejoró su desempeño reproductivo, principalmente en el grupo de vacas para TE con becerro.
El diagnóstico como base de la intervención educativa
Authors: Amaro Yepez Adilene , Juárez Lucas Placido , Rodríguez Rico Rocío , Soni Guillermo Eutiquio , Enríquez García Fabián
Published: July 2024

El presente artículo aborda la importancia del diagnóstico en la planeación e intervención educativa, por medio de las variantes conceptuales, las cuales determinan la pretensión del estudio y el alcance de este. En el centro de análisis se encuentran los propósitos del diagnóstico educativo como los fines de su realización. Se sostiene que los estudios son tan complejos como la claridad y amplitud de sus propósitos, en consecuencia, los medios más apropiados para la realización del diagnóstico educativo deben ser congruentes con los propósitos, las variantes de análisis y el nivel espacial donde trabajan los actores educativos. Dadas las características del estudio diagnóstico, se puede enriquecer con varias herramientas metodológicas que permitan conclusiones más asertivas para la intervención educativa.
End-to-End Data Flows Management in the Decentralized 5G/6G Mobile Networks
Authors: Dumych Stepan , Krasko Olena , Andrushchak Volodymyr , Brych Mykola , Pyrih Yaroslav , Hnatchuk Alina , Maksymyuk Taras
Published: July 2024

The evolution of 5G and the anticipated emergence of 6G networks demand significant enhancements in optical backhaul infrastructure to support higher bandwidth, low latency, and increased reliability. Considering a wide range of feasible applications with different quality requirements, the key challenge for the underlying backhaul and optical transport network is in the high load variance in the optical switching nodes and complicated data flows management. In this paper, a novel approach is proposed for end-to-end data flows management in decentralized 5G/6G mobile networks, which are interconnected by the optical burst switching transport infrastructure. The key idea is to train a deep recurrent neural network over a real network statistic obtain at the different network segments and service slices. Then, predictions made by deep neural network are used for predictive resource allocation in each node of the optical burst switching network to ensure a target quality of service for each end-to-end data flow. The experimental results show that proposed approach provides 90% accuracy of predictions and allows to effectively utilize the resources of optical network.
Determination of the Best Feature Subset for Learner Migration in Limpopo
Authors: Ramphele Frans , Wang Zenghui , Yusuff Adedayo
Published: July 2024

The South African Education Management Information Systems (EMIS) hosts longitudinal data on school inventory, learners, and educators. One of the most prevailing and yet ignored phases in machine learning is Feature Selection (FS). Neglecting this phase can adversely impact the outcome of the machine-learning exercise. This study seeks to explore informative features from the EMIS system which can predict the possibility of learners prematurely transitioning to alternative learning spaces in the Limpopo education system. The Ravenstein migration theory was used to assemble the initial features which were then subjected to Boruta, RPART, Adaboost.M1, and J48 algorithms. The feature subsets generated by the FS algorithms were compared with filter-based statistical methods such as Spearman Correlation and Mutual Information to aid in the final selection of the best feature subset for the study. All machine learning FS methods performed well. Feature subset generated by  Boruta was considered optimal due to relatively low importance score variance among the selected features compared to RPART, J48, and Adaboost.M1. It is believed that the low variance in the feature set will improve the model's stability and its ability to generalize with previously unseen data.
Values Spiral Development Method in the Implementation of Digitalization Projects in Syncretic Methodology
Authors: Bushuyev Sergey D. , Ivko Andrii V.
Published: July 2024

The article is devoted to the formulation of the method of spiral development of values in the implementation of digitalization projects of self-managed organizations, which was developed within the syncretic methodology of project management. The application of the proposed method is considered in the field of infrastructure restoration projects of Ukraine. A scientific problem regarding the availability of a project management methodology that meets modern challenges has been formulated. The gap between the practical needs of project-oriented organizations in a new unique methodology and the availability of established standards for solving typical project management tasks is revealed. A review of literary sources was carried out, modern project management trends were highlighted, including: increasing complexity of modern corporate project management methodologies, application of value-oriented management approaches, models of self-managed teams. The principles of value-oriented management for infrastructure restoration projects implemented by self-managed organizations within the syncretic methodology have been formulated. The method of values spiral development of a project-oriented organization, which uses models of self-management, through the implementation of digitalization projects within the syncretic methodology, is proposed. Within the scope of the method: a value model for digitalization projects of self-managed organizations is proposed; the concept of "stellarator project" is introduced, the definition of such a project is given. The results of the approbation of the method in a project-oriented organization working in the field of infrastructure restoration of Ukraine are presented and analyzed. Areas of improvement of the project-oriented activities of the specified organization have been determined. A SWOT analysis of the proposed method was carried out. Conclusions based on the research are formulated, prospects for further research in the chosen direction are outlined.
Method for Assessing Noise Quality Based on Entropy Quality Factor
Authors: Seilova Nurgul A. , Gnatyuk Sergiy O. , Batyrgaliyev Askhat A. , Dzhangozin Zhanibek A. , Baibatchayeva Dana A. , Nurgabylov Nurbol , Ibraev Renat
Published: July 2024

The work analyzes the existing approaches to solving the problem of a comprehensive study of the qualitative characteristics of side electromagnetic emission generators. In addition, methods and means of information leakage through the channels of side electromagnetic emission are considered, which make it possible to evaluate the effectiveness of noise generators. Electromagnetic emission can propagate in almost all environments. Side electromagnetic emission is one of the effective ways to protect computer equipment from information leakage through the channel of side electromagnetic emissions and interference. The masking noise is generated by the noise generator, and the quality factor of the masking noise is the quality factor of the entropy noise. In addition, measurements of masking noise interference using a spectrum analyzer and an oscilloscope are carried out and a method for estimating the entropy noise quality coefficient (ENQC) is proposed. The calculated value of the entropy noise quality factor is compared with the normalized value set for this type of noise generator. The novelty of the work is the development of a new method for assessing the quality of masking noise interference, based on the calculation of the entropy quality coefficient, as well as the development of software for automating the calculation. The study of the quality characteristics of the noise generator (NG) taking into account the design of a mock-up sample of the device, which is a complex work. In turn, based on the results obtained, it is possible to develop specialized automated tools for assessing the quality of masking noise interference.
Full Diversity Space Time Codes for Next Generation Wireless Sensor Networks
Authors: Abouzeid Mohamed S. , El-Khobby Heba A. , Ali Mahmoud A. A. , Nasr Mohamed E.
Published: July 2024

For the next generation of wireless sensor networks, this research paper proposes two distinguished, robust space-time codes with low complexity and full diversity. The channel is constructed using Quasi-deterministic radio channel generation (Quadriga), which pursues a geometric stochastic model. This paper discusses an uplink perspective on an industrial communication system. A master node design with four distributed antennas is suggested. Two antennas are available on slave nodes, where the proposed space time coding can be used. Additionally, zero-forcing (ZF) and minimum mean squared error (MMSE)-based low-complexity decoders are designed. The proposed codes outperform the Alamouti code under identical circumstances, according to simulation data. The simulation results show that a coding gain of about 5dB in comparison to Alamouti code is achieved. A high coding gain is attained, which results in a more reliable transmission, according to the bit error rate (BER). This research paper significantly contributes to the standardization of the next-generation wireless sensor networks.
Deep Learning-Based Echo State Neural Network for Cyber Threat Detection in IoT-Driven IICS Networks
Authors: Singaravelan S. , Velayutha Perumal P. , Arun R.
Published: July 2024

The advent of Software-Defined Networking (SDN) has ushered in a new era in network architecture, providing unprecedented levels of flexibility and adaptability. However, this advanced flexibility exposes SDN to security risks, particularly Distributed Denial of Service (DDoS) attacks. Detecting and mitigating DDoS attacks in SDN environments poses a critical challenge. This study introduces an innovative DDoS detection approach leveraging Echo State Networks (ESN) tailored specifically for SDN. This approach is based on two core assumptions: firstly, routine network operations primarily exhibit normal behavior, and secondly, there are discernible differences in data characteristics between normal and abnormal network conditions. These assumptions hold true in the realm of everyday network dynamics. To validate the efficacy of the ESN algorithm, we augment this approach by incorporating flow features to enhance DDoS detection capabilities. This study underscores the effectiveness of ESN in identifying and mitigating Distributed Denial of Service (DDoS) attacks, DDoS threats, achieving an impressive average success rate of 97.78%. By harnessing the potential of Echo State Networks, this work makes a substantial contribution to ongoing efforts in fortifying network security, providing a proactive defense against disruptive DDoS attacks.
Comparison of Direct and Indirect Methods of Speech Transmission Index Assessment
Authors: Prodeus Arkadiy , Dvornyk Oleksandr , Naida Anton
Published: July 2024

In this paper, direct and indirect methods of speech transmission index (STI) estimation are compared. Two versions of the indirect method of the STI estimating are considered. In the first version of the indirect method, a pair of signals is used as a test signal. It is a Maximum Length Sequence (MLS) signal with a uniform spectrum and a noise signal with a speech spectrum. In the second version of the indirect method, the test signal is an MLS signal with a speech spectrum. The comparison is carried out by means of computer modeling and by carrying out a field experiment in a medium sized university auditorium. Both versions of the indirect method use the same basic computer programs for STI calculating. It is shown that for the second version of the indirect method, the average values of the STI estimates differ from ones for the direct method by no more than 0.06 for signal-to-noise ratios from minus 20 dB to plus 20 dB. For the first version of the indirect method, this difference is significantly larger and reaches 0.24.
Machine Transliteration of Handwritten MODI Script to Devanagari using Deep Neural Networks
Authors: Joseph Solley , George Jossy
Published: July 2024

The transliteration process involves transcribing words from the source language into the target language that uses a different script. Language and scriptural hurdles can be overcome via transliteration systems. There is a demand for automated transliteration systems due to the existence of several languages and the growing number of multilingual speakers. This study focuses on the Machine Transliteration of handwritten MODI script to Devanagari. MODI script was the official script for Marathi till 1950. Although Devanagari has, since then, taken over as the Marathi language's official script, the MODI script has historical significance as large volumes of its manuscripts are preserved in libraries across different parts of India. However, MODI into Devanagari transliteration is a difficult task because MODI script documents are complex in nature and there is no standard dataset available for the experiment. Machine Transliteration can be approached either as a Natural Language Processing task or as a pattern recognition task. In this research work, the transliteration task is carried out using the pattern recognition technique. The transliteration of MODI script to Devanagari is implemented using Convolutional Recurrent Neural Network (CRNN) based Calamari OCR, which is open-source software. An accuracy of 88.14% is achieved in character level matching of each word in the MODI to Devanagari transliteration process. When considering the entire word matching, the accuracy achieved is 61%. Machine Transliteration of
Classification of Plant Disease using a State-of-the Art Deep learning Algorithm on a Tesla GPU
Authors: Jaiswal Manjit , Nagwanshi Kapil Kumar , Kumar Rishikesh , Gaurav Shreyash , Watti Yukta
Published: July 2024

This paper proposes a study conducted on various techniques that can be employed for the early detection of plant diseases. With exponential growth in the global population, there is a dire need for the detection and prevention of various types of plant diseases such as Mosaic virus in Solanum Lycopersicon (tomato), bacterial spot in Fragaria Ananassa (strawberry), late and early blight in Solanum Tuberosum (potato), huanglongbing in Citrus sinensis (orange), and Isariopsis leaf spot in Vitis vinifera (grapes). These diseases generally lead to lower yields and hence less profit. In the last two decades, there has been rapid development in the fields of image processing and deep learning. Various models of deep learning can be used for plant disease detection. The main objective is that as soon as plant leaf disease appears, there should be one device to monitor the symptoms and detect them over a large field with as much accuracy as possible. This study compares the deep learning models Resnet, MobileNet, and inceptionV3 that are implemented on a large dataset taken from the Kaggle repository. We implemented the models using Google Colaboratory tools, which provide us with Python’s Jupyter notebook that runs on the Google cloud server. The GPU “Tesla T4” and CPU “Intel Xenon” were used during training, validation, and testing respectively. The training and validation accuracy of the InceptionV3 model was 98.78% and 93.94%, respectively. MobileNet classified various plant diseases with training and validation accuracies of 99.57% and 97.31. Similarly, for ResNet, the training accuracy was found to be around 99.62% and the validation accuracy was 97.16%. We hope that this work will provide a helpful resource for other researchers working in the field of agriculture to detect various types of crop diseases. Future work and some challenges still faced are also discussed in this study.
Reconstruction of Tomographic Size Using a Filtered Back Projection Algorithm
Authors: Alrufaye Faiez Musa Lahmood , Hashem Seham Ahmed
Published: July 2024

Due to their widespread use, image processors are among the most essential computer processors. FBP technique is one of the most widely used tomographic reconstruction methods. Images from a computed tomography (CT) scanner with 512x512 pixels of raw data for parallel beam projections are the metadata to which this approach is applied. This work is divided into three parts. Several projections are created from an input test picture termed Shepp-Logan phantom in the first section, utilizing radon transformation. The picture is rebuilt from the projection of a parallel beam in the second section to minimize reconstruction time. Finally, the proposed system filters the projections using the Ram Lak filter and the Hann window in the third section to refine the picture and then recombine the projections to generate the reconstructed image. The reconstruction procedure is performed on CT images using a filtered back-projection algorithm in this article for image optimization and then projection recombination to generate the rebuilt picture. Since CT can accurately depict anatomical elements like bones and organs and may pick slides in any orientation, it is frequently used in biological applications and diagnostics. It also offers a great spatial resolution and soft tissue contrast. We develop, create, and run computer programs when we work with MATLAB. After projecting the 2D image onto a CT scanner, a very good result in reconstructing the image is received.
Improved Intrusion Detection in the Internet of Things: A Multi-Layered Neural Network Approach and Analysis
Authors: Farooq Mansoor , Ahmad Faheem
Published: July 2024

The (IoT) Internet of Things is a complex notion that refers to the interconnection of several individual devices over a network (IoT). The data gathered by these interconnected devices have the potential to have far-reaching consequences for human society, the economy, and the environment. The IoT is especially vulnerable to a variety of vulnerabilities in hostile environments like the internet. High-end security solutions are not adequate to safeguard an IoT system due to adequate storage and less processing capabilities. This emphasizes the need for ascendable, strewn, and robust smart security solutions. In this study, IoT networks are safeguarded depleting a multiple-layered security strategy centered on deep learning. The proposed architecture employs the use of three intrusion detection datasets CIC-IDS, BoT-IoT, and ToN-IoT to weigh the performance of the insinuated multiple-layered approach. Irrevocably, compared to 92% accuracy for the existing methodologies, the new layout obtained 98% accuracy.
Ensemble-based Disease Outbreak Detection: Comparative Analysis of Health News Information Retrieval Techniques
Authors: Joy Manju , Krishnaveni M.
Published: July 2024

In India, Kerala is the first state to report a COVID-19 infection case, in January 2020, in a medical student, who returned from Wuhan, China. More recently, in June 2022, Kerala also reported India's first case of monkeypox disease. News websites often publish articles dedicated to reporting disease occurrences and live updates of outbreaks. Through the utilization of data gathered from online digital resources, early detection of outbreaks is possible, and this potential is already identified by the research community. As webpages give a comprehensive collection of reports covering a wide range of themes through hyperlinks, precisely categorizing news articles based on their headlines and retrieving health news is a tedious operation. Hence, this paper proposes a novel and efficient news retrieval technique grounded on an ML-based classification method with an ensemble learning approach to identify reports of disease occurrences from web pages by focusing specifically on the health context of Kerala and a comparison with baseline methods for information retrieval such as keyword-based, phrase-based, and content-based latent semantic analysis method is made.
An Intelligent System for Thyroid Dysfunction Prediction
Authors: Abd Al-Kareem Elaf A. , Saba Samah J.
Published: July 2024

The prediction of thyroid diseases has become increasingly important in recent years. The feature engineering part is generally less studied in existing approaches than model optimization. To circumvent these restrictions, feature engineering for machine learning (ML) and deep learning models are examined in our research. This paper proposes a system to predict thyroid dysfunction. A model comprises three stages: preprocessing of the data, selection of features, and classification. A standard scalar normalizes the data after filling missing values with mean values. A Deep Neural Network (DNN) is utilized for classification, and the Improved Salp Swarm Algorithm (ISSA) is used for feature selection. Finally, accuracy is utilized to estimate the system proposed. The UCI thyroid illness datasets are used in our investigation.  In experiments with the DNN model, deep learning classifiers based on selected features produce the highest accuracy of 99.68%. The model proposed has superior performance compared to state-of-the-art methods.
Adaptive Learning Modified Great Deluge Hyper-Heuristics
Authors: Hutama Rizal Risnanda , Muklason Ahmad
Published: July 2024

The International Timetabling Competition (ITC) 2021 focuses on sports scheduling, a domain intricately connected to optimizing combinatorics problems. Within the framework of the ITC 2021 challenge, a crucial task is to precisely allocate matches to their designated time slots. Addressing this challenge involves the utilization of the Adaptive Learning Modified Great Deluge (ALMGD) algorithm, which belongs to the realm of hyper-heuristics. This algorithm represents an evolutionary step from the foundational great deluge algorithm, incorporating an acceptance mechanism intricately woven with self-adaptive learning. To assess its efficacy, the performance of the ALMGD algorithm is scrutinized through a comparative analysis with the hill climbing and great deluge algorithms. As a result, the proposed algorithm can produce a solution that is superior to the comparison algorithm. The modified great deluge algorithm can reduce the penalty by 36%, while the hill climbing algorithm can only reduce the penalty by 29% and the great deluge algorithm reaches 34%.
The Influence of Language Contact on Creole Formation
Authors: Shelley Veronica
Published: July 2024

Purpose: The general objective of this study was to examine the influence of language contact on creole formation.
Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.
Findings: The findings reveal that there exists a contextual and methodological gap relating to influence of language contact on creole formation. Preliminary empirical review revealed a complex and dynamic process involving interactions between diverse linguistic groups, often in contexts of colonization, slavery, and migration. It showed that creole languages, emerging from pidgins, incorporated elements from both substrate and superstrate languages, evolving into sophisticated systems reflecting their socio-cultural realities. The study highlighted the ongoing evolution of creole languages influenced by modern socio-political and economic factors, presenting both opportunities and challenges for preservation. The findings provided valuable insights for linguists, educators, policymakers, and cultural preservationists, emphasizing the importance of recognizing and supporting linguistic diversity.
Unique Contribution to Theory, Practice and Policy: The Language Bioprogram Hypothesis, Substrate Theory and Superstrate Theory may be used to anchor future studies on the influence of language contact on creole formation. The study recommended interdisciplinary research to advance theoretical understanding, the incorporation of creole languages into educational curricula, and the development of teacher training programs. It advocated for the formal recognition and preservation of creole languages through supportive language policies, cultural heritage programs, and public awareness initiatives. The study also emphasized the importance of ongoing research and monitoring to evaluate policy effectiveness and recommended establishing advisory bodies for sustainable support of creole languages. These recommendations aimed to enhance the appreciation and support of linguistic diversity and cultural heritage.
Surpassing $1 to $3 Million Revenue Threshold: Analyzing why Small Businesses Miss the Mark
Authors: Chukwuelue Azukaego
Published: July 2024

Purpose: Despite the crucial role small businesses play in driving economic growth and innovation, a significant majority fail to surpass the $3,000,000 revenue mark. This article aims to examine the prevalent reasons behind this high failure rate.
Methodology: The analysis focuses on five key areas: lack of strategic planning, insufficient financial management, inadequate marketing and sales strategies, poor time management and delegation, and an inability to adapt to change. The article uses real-world examples and data from reputable sources to explore these factors.
Findings: The research identifies that small businesses often fail due to a lack of strategic direction, poor financial oversight, ineffective marketing efforts, inefficient time management, and resistance to change. Each of these elements contributes to business stagnation and eventual failure.
Unique Contribution to Theory, Policy and Practice: This article provides valuable insights for small business owners, policymakers, and researchers by highlighting critical areas for improvement. By addressing these challenges, small businesses can improve their chances of achieving sustainable growth. The findings can inform policy decisions aimed at supporting small business development and provide a theoretical framework for further academic research.
O uso de fitoterápicos tópicos associados a drenagem linfática manual e ILIB como terapias coadjuvantes no tratamento do lipedema – Estudo de caso
Authors: Mota Lidiane
Published: July 2024

O lipedema é caracterizado como acúmulo desproporcional de gordura bilateralmente em regiões específicas. Esse acúmulo exacerbado de gordura vem acompanhado de edema e fibrose especialmente no terço inferior do corpo. Estima-se que 11 a 19% da população feminina sofram com a doença. Esse estudo de caso, pretendeu avaliar o uso da terapia combinando fitoterápicos tópicos a drenagem linfática manual e ILIB no tratamento coadjuvante do Lipedema. Participou da pesquisa uma mulher que apresenta lipedema em Membros Inferiores. A paciente foi submetida a uma única intervenção associando ILIB 30 minutos e Drenagem Linfática Manual utilizando fitoterápicos tópicos diluídos em creme neutro como deslizante. A participante foi avaliada antes e após uma única intervenção. A avaliação foi feita através de documentação fotográfica das regiões tratadas, teste do Godet, perimetria e aplicação do questionário de Escala Visual Analógica de Dor – EVA. O registro fotográfico evidencia mudança na coloração da pele, diminuição discreta do edema e melhora do aspecto geral da região após procedimento, a perimetria indica redução nas medidas das regiões avaliadas (MMII), já o teste de Godet não apresentou diferença antes e após procedimento. A avaliação da escala analógica de Dor – EVA demonstrou redução significa da dor em membros inferiores imediatamente após procedimento. Conclui-se que a associação do ILIB, DLM e fitoterápicos tópicos foi uma terapia coadjuvante efetiva no tratamento de lipedema da participante com lipedema estágio II e classificação III (morfologia). Contudo, sugere-se que estudos randomizados e com número maior de pacientes sejam realizados para avaliar a eficácia das terapias associadas e isoladas no tratamento do lipedema.
DEVELOPMENT OF AN EXFOLIATING DERMOCOSMETIC FORMULATION WITH BABASSU FIBERS TO HELP ON THE TREATMENT OF ANDROGENETIC ALOPECIA
Authors: Bastos Gonçalves Anna Vitória , Mohmoud Mourad Amouni , A. P. C. Brícola Solange , Guimarães Marcelo
Published: July 2024

Androgenetic alopecia is a condition characterized by hair loss associated with exposure to androgens, occurring in genetically predisposed individuals. It causes terminal hair to be replaced by vellus hair, miniaturizing the hair shaft and decreasing hair density. The removal of the stratum corneum of skin due to mechanical exfoliation facilitates the penetration of active ingredients into the scalp by stimulating blood circulation, which can help hair growth. Society's consumption patterns are constantly changing, being the search for sustainability and ESG (Environment, Social and Governance) trends a very popular topic. The aim of this study was to develop an exfoliating dermocosmetic formulation with babassu fibers to help on the treatment of androgenetic alopecia, using the part of the babassu coconut that was originally discarded by the industry. An oil-in-water emulsion was developed with the surfactants lauryl glucoside and cocoamidopropyl betaine, and the emulsifiers cetostearyl alcohol and glyceryl monostearate. The formulation was then analyzed for organoleptic parameters (color, smell and appearance), density, pH and centrifugation. The formulation showed instability in the presence of direct sunlight and heat, indicating possible impasses for its commercialization, since storage in the bathroom may trigger instability. In this way, it can be assumed that storing the product in a refrigerator or even at room temperature (<25°C) will maintain its stability. Based on the results, future studies are needed to assess the stability of the scrub, and the optimization of the formulation will make it possible to obtain an innovative product.
Creative Writing as an Effort to Improve Children's Emotional Intelligence
Authors: Puspitoningrum Encil , Khan Rosa Imani , Swanjaya Daniel
Published: July 2024

Emotional intelligence is an essential ability for every individual from an early age. This study explores the potential of creative writing as an alternative method in improving children's emotional intelligence. Through creative writing activities, children are expected to express their emotions and feelings more openly and develop empathy and self-recognition skills. This research utilizes a qualitative method. Data was collected through a literature review of similar studies. The results showed that creative writing was effective in helping children identify and manage their emotions better. In addition, this activity also improves children's ability to understand others' perspectives and develop critical social skills. This research provides new insights into the potential of creative writing to develop children's emotional intelligence and its implications in education and parenting.