Diseño de una metodología basada en principios ágiles para la implementación de un nuevo CRM de clase mundial en un laboratorio farmacéutico de la República del Paraguay.
Tesis Materias > Ciencias Sociales Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español A través de este trabajo de tesis se expone el diseño de una metodología basada en principios ágiles, para la implementación de un CRM (Customer Relationship Management) en un laboratorio farmacéutico de la república del Paraguay. El fin que se busca para el diseño de esta metodología basada en principios ágiles para la implementación de un CRM (Customer Relationship Management), es que las empresas que la adopten puedan transitar un proceso ágil, robusto y concreto, que les permita reducir los tiempos de implementación gracias a la eficiencia de la misma, y esto les brinde una ventaja competitiva. Esta ventaja competitiva puede darse en primer lugar, por salir al mercado con un sistema estratégico de apoyo al área comercial en un menor tiempo, y en segundo lugar, por una reducción sustancial de las horas dedicadas al proyecto, por parte de las personas involucradas a este. Para la elaboración de esta guía metodológica, se ha empleado en primer lugar y como metodología para fomentar la creatividad y la innovación, el Design Thinking, y como metodología ágil para el proceso de ejecución de la metodología en sí, se ha empleado Scrum, junto con sus roles, sus artefactos y sus ceremonias. El diseño de investigación elegido para elaborar este trabajo ha sido el Diseño de Investigación Descriptiva, debido a que se ha utilizado el instrumento del tipo encuesta para recabar información sobre del grado de conocimiento y penetración acerca de los CRM (Customer Relationship Management) y las metodologías ágiles, con foco en Scrum y en Design Thinking. Se ha tomado como población al área comercial de un laboratorio farmacéutico y la muestra fue de aproximadamente el 18% de la población. La estructura utilizada para el diseño de la metodología fue establecida en cinco fases, las cuales son: relevamiento, capacitación, segmentación, targeting e implementación. Los resultados logrados han sido satisfactorios considerando la ejecución del piloto dentro de la fase de prototipado. Técnicamente es un proyecto de diseño viable. Así mismo, los indicadores financieros dan cuenta que la metodología es financieramente viable también. Y a nivel de riesgos, los mismos han sido analizados y los tres riesgos detectados con nivel alto, han sido considerados y mitigados. metadata Sabatini Barragán, Germán Alberto mail german.sabatini@fapasapl.com.py (2022) Diseño de una metodología basada en principios ágiles para la implementación de un nuevo CRM de clase mundial en un laboratorio farmacéutico de la República del Paraguay. Masters thesis, SIN ESPECIFICAR.
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A través de este trabajo de tesis se expone el diseño de una metodología basada en principios ágiles, para la implementación de un CRM (Customer Relationship Management) en un laboratorio farmacéutico de la república del Paraguay. El fin que se busca para el diseño de esta metodología basada en principios ágiles para la implementación de un CRM (Customer Relationship Management), es que las empresas que la adopten puedan transitar un proceso ágil, robusto y concreto, que les permita reducir los tiempos de implementación gracias a la eficiencia de la misma, y esto les brinde una ventaja competitiva. Esta ventaja competitiva puede darse en primer lugar, por salir al mercado con un sistema estratégico de apoyo al área comercial en un menor tiempo, y en segundo lugar, por una reducción sustancial de las horas dedicadas al proyecto, por parte de las personas involucradas a este. Para la elaboración de esta guía metodológica, se ha empleado en primer lugar y como metodología para fomentar la creatividad y la innovación, el Design Thinking, y como metodología ágil para el proceso de ejecución de la metodología en sí, se ha empleado Scrum, junto con sus roles, sus artefactos y sus ceremonias. El diseño de investigación elegido para elaborar este trabajo ha sido el Diseño de Investigación Descriptiva, debido a que se ha utilizado el instrumento del tipo encuesta para recabar información sobre del grado de conocimiento y penetración acerca de los CRM (Customer Relationship Management) y las metodologías ágiles, con foco en Scrum y en Design Thinking. Se ha tomado como población al área comercial de un laboratorio farmacéutico y la muestra fue de aproximadamente el 18% de la población. La estructura utilizada para el diseño de la metodología fue establecida en cinco fases, las cuales son: relevamiento, capacitación, segmentación, targeting e implementación. Los resultados logrados han sido satisfactorios considerando la ejecución del piloto dentro de la fase de prototipado. Técnicamente es un proyecto de diseño viable. Así mismo, los indicadores financieros dan cuenta que la metodología es financieramente viable también. Y a nivel de riesgos, los mismos han sido analizados y los tres riesgos detectados con nivel alto, han sido considerados y mitigados.
| Tipo de Documento: | Tesis (Masters) |
|---|---|
| Palabras Clave: | CRM, Metodologías Ágiles, Scrum, Design Thinking. |
| Clasificación temática: | Materias > Ciencias Sociales |
| Divisiones: | Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster |
| Depositado: | 03 May 2024 23:30 |
| Ultima Modificación: | 03 May 2024 23:30 |
| URI: | https://repositorio.unib.org/id/eprint/3077 |
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Novel hybrid transfer neural network for wheat crop growth stages recognition using field images
Wheat is one of the world’s most widely cultivated cereal crops and is a primary food source for a significant portion of the population. Wheat goes through several distinct developmental phases, and accurately identifying these stages is essential for precision farming. Determining wheat growth stages accurately is crucial for increasing the efficiency of agricultural yield in wheat farming. Preliminary research identified obstacles in distinguishing between these stages, negatively impacting crop yields. To address this, this study introduces an innovative approach, MobDenNet, based on data collection and real-time wheat crop stage recognition. The data collection utilized a diverse image dataset covering seven growth phases ‘Crown Root’, ‘Tillering’, ‘Mid Vegetative’, ‘Booting’, ‘Heading’, ‘Anthesis’, and ‘Milking’, comprising 4496 images. The collected image dataset underwent rigorous preprocessing and advanced data augmentation to refine and minimize biases. This study employed deep and transfer learning models, including MobileNetV2, DenseNet-121, NASNet-Large, InceptionV3, and a convolutional neural network (CNN) for performance comparison. Experimental evaluations demonstrated that the transfer model MobileNetV2 achieved 95% accuracy, DenseNet-121 achieved 94% accuracy, NASNet-Large achieved 76% accuracy, InceptionV3 achieved 74% accuracy, and the CNN achieved 68% accuracy. The proposed novel hybrid approach, MobDenNet, that synergistically merges the architectures of MobileNetV2 and DenseNet-121 neural networks, yields highly accurate results with precision, recall, and an F1 score of 99%. We validated the robustness of the proposed approach using the k-fold cross-validation. The proposed research ensures the detection of growth stages with great promise for boosting agricultural productivity and management practices, empowering farmers to optimize resource distribution and make informed decisions.
Aisha Naseer mail , Madiha Amjad mail , Ali Raza mail , Kashif Munir mail , Aseel Smerat mail , Henry Fabian Gongora mail henry.gongora@uneatlantico.es, Carlos Eduardo Uc Ríos mail carlos.uc@unini.edu.mx, Imran Ashraf mail ,
Naseer
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Client engagement solution for post implementation issues in software industry using blockchain
In the rapidly advanced and evolving information technology industry, adequate client engagement plays a critical role as it is very important to understand the client’s concerns, and requirements, have the records, authorizations, and go-ahead of previously agreed requirements, and provide the feasible solution accordingly. Previously multiple solutions have been proposed to enhance the efficiency of client engagement, but they lack traceability, trust, transparency, and conflict in agreements of previous contracts. Due to the lack of these shortcomings, the client requirement is getting delayed which is causing client escalations, integrity issues, project failure, and penalties. In this study, we proposed the UniferCollab framework to overcome the issues of collaboration between various teams, transparency, the record of client authorizations, and the go-ahead on previous developments by implementing blockchain technology. We store the data on the permissible network in the proposed approach. It allows us to compile all the requirements and information shared by clients on permissible blockchain to secure a large amount of data which enhances the traceability of all the requirements. All the authorizations from the client generate push notifications for any changes in their current system executed through smart contracts. It removes the ambiguity between various development teams if the client has only shared the requirement with one team. The data is stored in the decentralized network from where information is gathered which resolves the traceability, transparency, and trust issues. Lastly, evaluations involved a total of 800 hypertext transfer protocol (HTTP) requests tested using Postman with blockchain block sizes ranging from 0.568 KB to 550 KB and an average size increase of 280 KB was observed as new blocks were added. The longest chain in the network was observed during 800 repetitions of blockchain operations. Latency analysis revealed that delays in processing HTTP requests were influenced by decentralized node processing, local machine response times, and internet bandwidth through various experiments. Results show that the proposed framework resolves all client engagement issues in implementation between all stakeholders which enhances trust, and transparency improves client experience and helps us manage disputes effectively.
Muhammad Shoaib Farooq mail , Khurram Irshad mail , Danish Riaz mail , Nagwan Abdel Samee mail , Ernesto Bautista Thompson mail ernesto.bautista@unini.edu.mx, Daniel Gavilanes Aray mail daniel.gavilanes@uneatlantico.es, Imran Ashraf mail ,
Farooq
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This Special Issue of Diet and Nutrition: Metabolic Diseases showcases cutting-edge research exploring the intersection between nutrition, dietary patterns, and public health. The contributions in this collection involve both fundamental and applied research, offering new insights into how nutrition can combat the growing global burden of non-communicable diseases [1]. The studies in this issue emphasize the critical role that diet plays in promoting metabolic health, preventing chronic diseases, and improving overall quality of life. In recent years, nutrition has become a central focus in global health efforts, with a growing body of evidence demonstrating its impact on both individual and population-level outcomes [2,3]. This Special Issue encompasses several key themes, including the role of dietary interventions in managing metabolic disorders, the importance of nutrient timing and quality, and the broader implications of sustainable dietary practices.
Iñaki Elío Pascual mail inaki.elio@uneatlantico.es,
Elío Pascual
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Background: Scientific research should be carried out to prevent sports injuries. For this purpose, new assessment technologies must be used to analyze and identify the risk factors for injury. The main objective of this systematic review was to compile, synthesize and integrate international research published in different scientific databases on Countermovement Jump (CMJ), Functional Movement Screen (FMS) and Tensiomyography (TMG) tests and technologies for the assessment of injury risk in sport. This way, this review determines the current state of the knowledge about this topic and allows a better understanding of the existing problems, making easier the development of future lines of research. Methodology: A structured search was carried out following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines and the PICOS model until November 30, 2024, in the MEDLINE/PubMed, Web of Science (WOS), ScienceDirect, Cochrane Library, SciELO, EMBASE, SPORTDiscus and Scopus databases. The risk of bias was assessed and the PEDro scale was used to analyze methodological quality. Results: A total of 510 articles were obtained in the initial search. After inclusion and exclusion criteria, the final sample was 40 articles. These studies maintained a high standard of quality. This revealed the effects of the CMJ, FMS and TMG methods for sports injury assessment, indicating the sample population, sport modality, assessment methods, type of research design, study variables, main findings and intervention effects. Conclusions: The CMJ vertical jump allows us to evaluate the power capacity of the lower extremities, both unilaterally and bilaterally, detect neuromuscular asymmetries and evaluate fatigue. Likewise, FMS could be used to assess an athlete's basic movement patterns, mobility and postural stability. Finally, TMG is a non-invasive method to assess the contractile properties of superficial muscles, monitor the effects of training, detect muscle asymmetries, symmetries, provide information on muscle tone and evaluate fatigue. Therefore, they should be considered as assessment tests and technologies to individualize training programs and identify injury risk factors.
Álvaro Velarde-Sotres mail alvaro.velarde@uneatlantico.es, Antonio Bores-Cerezal mail antonio.bores@uneatlantico.es, Josep Alemany Iturriaga mail josep.alemany@uneatlantico.es, Julio Calleja-González mail ,
Velarde-Sotres
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In the rapidly evolving landscape of artificial intelligence (AI) and the Internet of Things (IoT), the significance of device diagnostics and prognostics is paramount for guaranteeing the dependable operation and upkeep of intricate systems. The capacity to precisely diagnose and preemptively predict potential failures holds the potential to considerably amplify maintenance efficiency, diminish downtime, and optimize resource allocation. The wealth of information offered by telemetry data gathered from IoT devices presents an opportunity for diagnostics and prognostics applications. However, extracting valuable insights and making well-timed decisions from this extensive data reservoir remains a formidable challenge. This study proposes a novel AI-driven framework that integrates forward chaining and backward chaining algorithms to analyze telemetry data from IoT devices. The proposed methodology utilizes rule-based inference to detect real-time anomalies and predict potential future failures, providing a dual-layered approach for diagnostics and prognostics. The results show that the diagnostics engine using forward chaining detects real-time issues like “High Temperature” and “Low Pressure,” while the prognostics engine with backward chaining predicts potential future occurrences of these issues, enabling proactive prevention measures. The experimental results demonstrate that adopting this approach could offer valuable assistance to authorities and stakeholders. Accurate early diagnosis and prediction of potential failures have the capability to greatly improve maintenance efficiency, minimize downtime, and optimize cost.
Muhammad Shoaib Farooq mail , Rizwan Pervez Mir mail , Atif Alvi mail , Kilian Tutusaus mail kilian.tutusaus@uneatlantico.es, Eduardo García Villena mail eduardo.garcia@uneatlantico.es, Fadwa Alrowais mail , Hanen Karamti mail , Imran Ashraf mail ,
Farooq