Implementation Of Platform Research Articles

Implementation and Evaluation of an E-Commerce Platform Using the MERN Stack

Implementation and Evaluation of an E-Commerce Platform Using the MERN Stack

Assessing the relevance and requirement of a prostate cancer passport: A patient-centric survey.

e23037 Background: Prostate cancer, a prevalent malignancy among men worldwide, necessitates a multifaceted approach to its management, encompassing diagnosis, treatment, and post-treatment care. The absence of a consolidated and accessible cancer information for prostate cancer patients prompts an exploration into the necessity and potential benefits of a dedicated Prostate Cancer Passport. This survey-based study seeks to elucidate patient perspectives and assess the demand for it. Methods: We Surveyed prostate cancer patients attending St James Hospital Medical Oncology OPD and day ward. The survey methodology integrated a diverse cohort of individuals representing varying demographics, encompassing age groups and socio-economic backgrounds. Questions were structured to gauge patient awareness, preferences, and perceived benefits associated with the adoption of a Prostate Passport. The survey was structured to gauge patient awareness levels regarding existing health record systems, preferences for a specialized Prostate Cancer Passport, and anticipated benefits associated with its implementation Furthermore, the survey seeked to elucidate potential concerns, barriers to adoption, and the anticipated impact on patient-provider interactions. Results: The survey’s findings indicate a significant interest among participants in the implementation of a specialized platform like the Prostate Passport, with more than 65% expressing enthusiasm about its potential benefits in improving healthcare management. However, 20% of patients reported not receiving any prostate cancer information booklet from their healthcare providers. Additionally, 30% of participants expressed dissatisfaction with communication with their medical team, while over 40% lacked confidence in their understanding of prostate cancer. Nevertheless, concerns related to data security were raised by more than 25% of patients, and approximately 23% identified potential barriers to adoption, such as interoperability with existing healthcare systems and ease of access across different healthcare settings. However, concerns regarding data security were highlighted by over 25% of patients and about 23% of patients identified interoperability with existing healthcare systems, and ease of access across various healthcare settings as potential barriers to adoption. Conclusions: The survey outcomes offer valuable perspectives on the distinct requirements and preferences of individuals facing prostate cancer. This data is crucial for customizing the Prostate Cancer Passport's design and functionalities to effectively cater to those needs. Our initial iteration of the prostate cancer passport has been completed and will be distributed to our oncology patients in the upcoming week. We plan to conduct a feedback survey in six months to gather insights and further enhance the passport based on user experiences.

MCA NOTES WEBSITE

Abstract— In the contemporary educational landscape, the accessibility and availability of study materials play a pivotal role in enhancing the learning experience for students pursuing Master of Computer Applications (MCA). This research paper presents a comprehensive examination of the design, development, and implementation of an innovative online platform tailored specifically for MCA students. The platform serves as a repository of semester-wise previous question papers and subject notes, offering a centralized hub for students to access valuable resources essential for their academic success. Utilizing cutting-edge technologies such as React JS, Tailwind CSS, MongoDB, and Node.js, the website provides an intuitive and user-friendly interface, ensuring seamless navigation and efficient content retrieval. Through meticulous curation and organization, the platform categorizes study materials according to semesters, enabling students to effortlessly locate pertinent resources relevant to their academic progression. Moreover, the incorporation of features such as downloadable notes and interactive contact us page further enriches the user experience, facilitating streamlined communication between students and administrators. Index Terms – Educational Technology, React JS, Tailwind CSS, MongoDB, Node.js, Study Materials, Previous Question Papers, User Interface Design.

Implementation and Exploration of a Collaborative Platform for Art Creation and Design Based on Multimodal Perception

Implementation and Exploration of a Collaborative Platform for Art Creation and Design Based on Multimodal Perception

Elevating Online Shopping Using MERN Stack

Abstract: This project presents the design, development, and implementation of an online shopping platform aimed at enhancing the retail experience for both consumers and businesses. The rapid growth of e-commerce has revolutionized the way consumers shop, creating a need for robust and efficient online shopping platforms. This research paper explores the potential of the MERN stack (MongoDB, Express.js, React.js, and Node.js) in developing a comprehensive and user-friendly online shopping solution. By leveraging the strengths of these modern technologies, we aim to elevate the online shopping experience, addressing key challenges such as performance, scalability, and seamless user interactions. Through a combination of theoretical analysis and practical implementation, we demonstrate the effectiveness of the MERN stack in creating a responsive, secure, and featurerich online shopping platform.

Usability and effectiveness of a telehealth artificial-intelligence powered platform: perspectives from patients and providers in a mixed-methods study.

Telemedicine has revolutionized healthcare by significantly enhancing accessibility. However, the acceptability and uptake of tele-medicine is prone to various hindering factors. Studies have shown that both patients and healthcare providers appreciate the aspect of convenience. However, healthcare providers' limited understanding of or inability to leverage the technology involved can be a barrier. With advancements in telemedicine technologies, understanding the viewpoints of patients and providers is crucial for an effective and acceptable telemedicine service. This study reports findings from a usability study of HelixVM™, a telemedicine platform that uses an Artificial Intelligence (AI)-powered triage for healthcare delivery. We discuss aspects of asynchronous medicine, healthcare accessibility, saving time, productivity, data exchange, security, privacy, AI-powered triage and quality of care. To assess the usability and effectiveness of the HelixVM marketplace platform. We recruited 102 patients and 12 providers in a mixed-methods study design involving surveys, and in-depth structured interviews with a subset of the providers only. The survey questionnaires are a modified version of the telehealth utility questionnaire. We analyzed the patient's data using descriptive statistics and factor analysis to identify latent demographic patterns. For the providers data, we used a deductive thematic analysis approach to identify key themes from the interviews and interpreted overall sentiments of the providers for negative, neutral or positive. We also calculated percentages of different responses for the providers from the surveys and interviews, where applicable. Patients: Overall, 86% of patients are satisfied with HelixVM and 89% will use the services again. More than 90% of patients agreed that HelixVM improves access to healthcare, saves time and that the platform is an acceptable way to receive healthcare. Chi-square tests demonstrate statistical significance for all the survey questions (p-value <.001). Results from factor analysis show a higher propensity of female gender in middle age groups whose encounter type is fast-track, self-report medium level of tech-savviness and residing in the South regions of US rate the platform more positively. Providers: Thematic analysis identified themes of asynchronous medicine in terms of accessibility and quality of care, time and productivity, integration within the workflow, data exchange and AI-triage. Certain challenges of incomplete data in patient chart and its impact on provider time are cited. Suggestions for improvements include options to ensure completeness of patient questionnaires and better screening to ensure that only asynchronous 'qualified' patients get through to the provider. Overall, our study findings indicate a positive experience for patients and providers. The use of fast-track prescription is favorable as compared to traditional telemedicine. Some concerns on data completeness, gaps and accuracy exist. Suggestions are provided for improvement. This study adds to the knowledgebase of existing literature and provides for a detailed analysis into the real-world implementation of a telemedicine market-place platform.

Encouraging the effectiveness of philanthropic institutions: Implementation of digital fundraising platform for Lazismu Medan City

The use of information technology in fundraising has brought about a significant transformation in the operations of charitable organizations, enabling the expansion of reach and increasing the effectiveness of activities. Lazismu Medan City, a philanthropic institution in Indonesia, faces challenges in optimizing fundraising activities due to limited digital technology capacity and less effective marketing strategies. This community service aims to develop and implement a digital platform to enhance Lazismu's capacity in managing fundraising efficiently and transparently, accessible via lazismumedan.org. Methods for implementing the service include developing a platform, conducting comprehensive training for Lazismu administrators and volunteers, as well as enhancing skills in using digital technology to raise funds. The results of this service show a significant increase in the number of donations collected and the level of donor satisfaction, indicating increased capacity and transparency in Lazismu's fundraising activities.

ENSEÑANZAS DE LA PANDEMIA COVID-19. EXPERIENCIA DE UN COMITÉ ÉTICO-CIENTÍFICO UNIVERSITARIO

This presentation communicates the lessons learned by the COVID-19 epidemic during the op­eration of the Human Research Ethics Committee,Faculty of Medicine,University of Chile during the first three years of the pandemic. Between 2020 and 2022 we received 806 projects,which meant an increase of 20% compared to the 672 projects of the pre-pandemic triennium (2017­2019). Additionally, it was necessary to keep the committee operating completely telematically to avoid contagion and giving priority to COVID-19 projects,without affecting the rigor of its analysis. To this end, the length and frequency of the sessions were increased,adapting instru­ments and procedures. Among the lessons learned from this operation,the following stand out: 1) Management of digital document, telematic and recorded sessions, approval certificates and proceedings of sessions sent by email and use of electronic signatures. 2) Adaptation of procedures to prevent contagion: application of remote informed consent, dispatch of docu­ments via the internet, replacement of visits by video-calls, use of individualized transport and personal protection elements in face-to-face activities. 3) Improvement in computer capacity and security, to safeguard the confidentiality of meetings, resolutions and communications. 4) Increase of the memory of the computers,to increase the storage capacity of the committee. 5) Implementation of an electronic platform for the management of processed projects. Most of these changes implemented in pandemic are durable and can be expected to become mastered over the course of their repeated application.

Development of a platform for state online education services: Design concept based on meta-universe

AbstractThe incorporation of metaverse technology in education, particularly within standardized state educational frameworks, holds promise for significant improvements in learning outcomes. This study aimed to assess the effectiveness of integrating an online metaverse platform into state educational services, thereby fostering the development of digital environments. A total of 278 students from middle and high school levels in China participated in the study. Academic achievement tests, alongside the Engagement Level Scale (ELS) and Motivation Level Scale (MLS), were employed as measurement tools. The utilization of the metaverse platform, hosting the state-approved curriculum for seventh and tenth grades, resulted in notable enhancements in students’ academic performance, engagement, and motivation. Among seventh graders, the most significant improvements in academic performance were observed in mathematics (5.897), literature (5.101), and history (5.767). For tenth graders, enhancements were noted in Chinese language (7.500), literature (5.800), and chemistry (5.650). Moreover, improvements in engagement and motivation were statistically significant. Seventh graders in the experimental group exhibited higher levels of intrinsic motivation (6.45), extrinsic motivation (5.28), and self-regulation (7.18) compared to the control group. For tenth graders, the respective increases were 5.70, 4.00, and 4.65 for each subscale. The practical and scientific significance lies in demonstrating the potential of enhancing educational outcomes and student motivation through the implementation of an online metaverse platform, which could be integrated into state school curricula.

Development and usability testing of an online platform for provider training and implementation of cognitive-behavioral therapy guided self-help for eating disorders.

Most individuals with eating disorders (EDs) do not receive treatment, and those who do receive care typically do not receive evidence-based treatment, partly due to lack of accessible provider training. This study developed a novel "all-in-one" online platform for disseminating training for mental health providers in cognitive-behavioral therapy guided self-help (CBTgsh) for EDs and supporting its implementation. The aim of the study was to obtain usability data from the online platform prior to evaluating its effects on provider training outcomes and patient ED symptom outcomes in an open pilot trial. Nine mental health provider participants (n = 4 in Cycle 1; n = 5 in Cycle 2) and 9 patient participants (n = 4 in Cycle 1; n = 5 in Cycle 2) were enrolled over two cycles of usability testing. In Cycle 1, we recruited providers and patients separately to complete brief platform testing sessions. In Cycle 2, we recruited provider-patient dyads; providers completed training using the platform and subsequently delivered CBTgsh to a patient for three weeks. Usability was assessed using the System Usability Scale (SUS), the Usefulness, Satisfaction, and Ease of Use Questionnaire (USE), and semi-structured interviews. Interview feedback converged on two themes for providers (applicability of program for real-world use, platform structure and function) and two themes for patients (barriers and facilitators to engagement, perceived treatment effects). SUS and USE scores were in the "average" to "good" ranges across cycles. Findings from this study demonstrate preliminary feasibility and acceptability of the online platform. Data collected in this study will inform further refinements to the online platform. The platform's effects on provider training outcomes and patient ED symptom outcomes will be evaluated in an open pilot trial. Given the wide treatment gap for EDs and barriers to dissemination and implementation of evidence-based treatments, the online platform represents a scalable solution that could improve access to evidence-based care for EDs.

Digital Sort-Enabled Counting Allows Absolute Electrical Quantification of Target Nucleic Acid.

Quantitative nucleic acid amplification tests are of great importance for diagnostics, but current approaches require complex and costly optical setups that limit their nonlaboratory applications. Herein we describe the implementation of a microfluidics platform that can perform binary DNA-amplification-activated droplet sorting. The digital sort-enabled counting (DISCO) platform enables label-free absolute quantification of the nucleic acid. This is achieved by provoking a pH change in droplets through a loop-mediated isothermal amplification (LAMP) reaction, followed by using sorting by interfacial tension (SIFT) to direct positive and negative droplets to different outlets. With the use of on-chip electrodes at both outlets, we demonstrate that the digital electrical counting of target DNA and RNA can be realized. DISCO is a promising approach for realizing sensitive nucleic acid quantification in point-of-care settings.

Digital Transformation in Real Estate Services: Development and Implementation of the Housing Selection Platform

This article provides a detailed elaboration on the design and development of the Housing Selection Platform, an online platform that responds to current real estate market demands and integrates modern technologies. The paper comprehensively introduces the platform's system modules, including online housing rental, buying and selling, as well as related shopping mall experiences. The platform adopts a front-end/back-end separation and microservices architecture, making development efficient and the system easy to maintain. It also emphasizes performance optimization through technologies like Redis and has adopted the latest authentication and authorization measures for security. The article widely discusses the implementation of the system and the technical challenges faced, providing solutions such as API gateways and event-driven architectures. The conclusion revisits key learned points and successful experiences, predicting that the introduction of innovative technologies like artificial intelligence and machine learning will drive the platform's development. The importance of user experience throughout the developmental process is emphasized, looking forward to how the Housing Selection Platform will continue to lead the industry in the future.

Cervical cancer prevention in Burkina Faso: a stakeholder's collaboration for the development of awareness messaging.

Cervical Cancer stands as the second leading cause of both incident female cancers and deaths in Burkina Faso. Unfortunately, the prevention, early detection, and care of cervical cancers are suboptimal at individual, institutional, and national levels. In October 2023, we organized a stakeholder's workshop to develop cervical cancer awareness messaging for disease control in the country. A one-text workshop was organized with stakeholders working toward improving health in general or women's health and well-being. A participatory, learning, and adaptive approach was used to facilitate discussions and activities, ensuring the contribution of all participants. Contextual evidence-based and empirical elements about cervical cancer burden and preventive strategies were presented to the participants by key informants. These served as the foundation for a collaborative formulation of messaging content that aimed at raising awareness about cervical cancer. Sixty-two participants from 28 organizations attended the workshop. They work mainly at local and international non-governmental organizations, civil society organizations, universities, university hospitals, research centers, and the Ministry of Health. During the first and second days of the workshop, the participants explored cervical cancer data, its preventive and treatment options available in Burkina Faso, communication strategies for behavioral change, and determinants of the use of prevention and health promotion services. During the following three days, 3 working groups were formed to define strategies, and key messages adapted to diverse tools and targeted audiences. All information was validated during plenary sessions before the end of the workshop and available to all participants and their organizations for cancer awareness activities. Upon conclusion of the workshop, the participants provided insightful information for the development of cervical awareness messaging in Burkina Faso. They formed the first community of practice to serve as a dynamic platform for implementation, monitoring, evaluation, and continued learning activities.

Age-of-Information based Multi-UAV Trajectories Using Deep Reinforcement Learning

The use of unmanned aerial vehicles (UAVs) as a unified platform for sensing and communication is especially relevant in environments with inadequate infrastructure. In this paper, a multi-UAV system is constructed for dynamic data collection in a resource-constrained environment. The devised approach involves the implementation of an access platform referred to as the Access UAV (A_UAV). This A_UAV orchestrates the data collection process from Inspection-UAVs (I_UAVs), each equipped with a visual sensor, facilitating the relay of collected data to the cloud. Our approach jointly considers the trajectory scheduling of A_UAV and I_UAV to collect data from specific points in a decentralized manner. Specifically, a Deep Reinforcement Learning framework utilizing an actor-critic network is formulated for A_UAV, aiming to generate an equitable access schedule for I_UAVs. Moreover, trajectory scheduling of A_UAV ensures dynamic data collection while minimizing total system energy and the Age of Information (AoI) of data arriving from I_UAVs. The simulation results validate the performance of our proposed approach against several baselines under different parameter settings.

An open-source research platform for mechanical ventilation based on Simulink® and STM32 nucleo

Abstract Gain in knowledge in experimental fields of research is mostly achieved using commercial hardware platforms. The linked costs however can limit a broad access by scientists and in the specific case of mechanical ventilation the pandemic demonstrated that further and collective research is essential and necessary. This contribution presents the modular design and implementation of a research platform which is based on STM32 Nucleo boards and Simulink®. The hardware required such as the pneumatic circuit are covered as well as the software architecture in which clinician related settings are processed for control references. The core functionality of mandatory volume controlled (VCV) and pressure controlled ventilation (PCV) while ensuring a positive end-expiratory pressure for the patient ( PEEP ) $(\text{PEEP})$ is evaluated and the foundational software models are published in a repository.

A novel STPA approach to software safety and security in autonomous maritime systems

With higher autonomy in maritime systems, tasks and responsibilities are moved from the human operator to software, increasing the complexity and the importance of safe and reliable functionality. Software failures, however, may be introduced from the early life cycle phases intentionally or unintentionally, and these must therefore be mitigated by safe and secure design approaches. A challenge is that existing methods are not particularly well-suited for analyzing software risks. Thus, the objective of this paper is to propose a systematic and efficient software failure identification approach by extending the Systems-Theoretic Process Analysis (STPA) with a software failure taxonomy and the System Modeling Language (SysML). This enables the control structure in STPA to cover both the dynamic and static aspects of the software functions. Combined with an implementation platform independent questionnaire, this gives a more systematic and guided search for potential software failures than existing approaches. To demonstrate the proposed approach, a case study on a ferry's navigation system that operates in manual control or semi-autonomous mode is performed. In the case study, the focus is on creating an avoidance map data structure, including both moving and static obstacles to be avoided by the ferry, and the subsequent process of collision risk warning calculation. Software failures are identified and evaluated in collision scenarios where the ferry operates under foggy conditions. The paper shows that the proposed systematic approach provides an improved process for identifying and analyzing critical software failures. This facilitates enhanced risk mitigation in the design and testing phases contributing to autonomous systems' safety and security.

“FIT FUEL: A Diet Planner Platform Using Web Technology”

Abstract: In today's fast-paced world, maintaining a healthy lifestyle has become a significant concern for many individuals. The "FIT FUEL" project introduces a cutting-edge solution in the form of a web-based diet planner platform that leverages modern technology to assist users in achieving their fitness goals. By incorporating user-provided data such as height, weight, and desired weight management goals (gain, lose, or maintain weight), the platform calculates Basal Metabolic Rate (BMR) and suggests personalized diet plans for breakfast, lunch, and dinner. One of the key innovations of FIT FUEL is its integration of Application Programming Interfaces (APIs) to fetch a diverse range of recipes, ensuring that users have access to a wide variety of meal options that align with their nutritional requirements and preferences. This platform not only facilitates calorie tracking but also promotes balanced nutrition and dietary diversity. The research paper discusses the design, implementation, and functionality of the FIT FUEL platform, highlighting its usercentric approach and the utilization of web technology to deliver a seamless and engaging experience. Additionally, the paper explores the potential impact of such digital tools on promoting healthy eating habits and overall wellness among individuals. Through this research, FIT FUEL aims to contribute to the growing field of digital health technologies, offering a practical solution for individuals seeking a personalized and effective approach to managing their diet and fitness journey in today's digital age.

MapReduce Algorithm on a Serverless Platform

Using the MapReduce (MR) programming technique, large-scale data processing tasks can be divided into tasks that are easier to manage and independent. The serverless implementation's performance is better than the non-serverless MR model when the model parameters are altered in the experiment. Optimizing the use of the MR model on the serverless platform can be achieved by taking into account the relationship between implementation efficiency and platform settings. Additionally, it can act as a source of inspiration for future serverless hardware support configurations. Also, the serverless platform demonstrates how it improves the effectiveness of resource utilization in machine learning training. The intended result can then be achieved by combining the results of these concurrently operating jobs on server clusters. This work adapts MR, a popular big data processing framework, to the serverless platform, emphasizing realization simulation principles and services, and then uses the results in a word count experiment. The experiment uses a word count of about eleven thousand words to evaluate how well MR is implemented on Alibaba Cloud. It is validated for execution time on the platform with varying Central Processing Unit (CPU) core counts, memory configurations, and worker counts. By testing several platform configurations, it is found that the memory configuration has very little impact on the model's execution time, while the size of the CPU core has a considerable impact on reaction time relative to the number of workers.

An ultra energy-efficient hardware platform for neuromorphic computing enabled by 2D-TMD tunnel-FETs

Brain-like energy-efficient computing has remained elusive for neuromorphic (NM) circuits and hardware platform implementations despite decades of research. In this work we reveal the opportunity to significantly improve the energy efficiency of digital neuromorphic hardware by introducing NM circuits employing two-dimensional (2D) transition metal dichalcogenide (TMD) layered channel material-based tunnel-field-effect transistors (TFETs). Our novel leaky-integrate-fire (LIF) based digital NM circuit along with its Hebbian learning circuitry operates at a wide range of supply voltages, frequencies, and activity factors, enabling two orders of magnitude higher energy-efficient computing that is difficult to achieve with conventional material and/or device platforms, specifically the silicon-based 7 nm low-standby-power FinFET technology. Our innovative 2D-TFET based NM circuit paves the way toward brain-like energy-efficient computing that can unleash major transformations in future AI and data analytics platforms.

Measuring and Clustering Heterogeneous Chatbot Designs

Conversational agents, or chatbots, have become popular to access all kind of software services. They provide an intuitive natural language interface for interaction, available from a wide range of channels including social networks, web pages, intelligent speakers or cars. In response to this demand, many chatbot development platforms and tools have emerged. However, they typically lack support to statically measure properties of the chatbots being built, as indicators of their size, complexity, quality or usability. Similarly, there are hardly any mechanisms to compare and cluster chatbots developed with heterogeneous technologies. To overcome this limitation, we propose a suite of 21 metrics for chatbot designs, as well as two clustering methods that help in grouping chatbots along their conversation topics and design features. Both the metrics and the clustering methods are defined on a neutral chatbot design language, becoming independent of the implementation platform. We provide automatic translations of chatbots defined on some major platforms into this neutral notation to perform the measurement and clustering. The approach is supported by our tool Asymob , which we have used to evaluate the metrics and the clustering methods over a set of 259 Dialogflow and Rasa chatbots from open-source repositories. The results open the door to incorporating the metrics within chatbot development processes for the early detection of quality issues, and to exploit clustering to organise large collections of chatbots into significant groups to ease chatbot comprehension, search and comparison.