Mobile App Development & Android Projects for ₹600-1500 INR. My service-based Android app is finished, fully compliant with current Play Store policies, and packaged as a

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PHP & Web Development Projects for $10-1000 USD. I’m ready to launch a ride-hailing service and want a fully functional, ready-made inDrive-style solution that I can depl

Kindlebit offers custom software development, IT solutions and services. Upscale your business with our expertise in software development and digital solutions.

Mobile App Development & Android Projects for ₹600-1500 INR. I have a published Android photo-editing app that needs a quick round of bug fixing. You can preview it here:

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They remember the moment a care team needed a reliable digital tool and the clock was ticking. That pressure shapes how vendors build mission‑critical solutions today. Trusted partners bring certified quality and clear processes to each project. Certified practices — like ISO 27001, ISO 9001, and ISO 13485 — and hands‑on compliance with HIPAA, FDA, GDPR, and other rules form the backbone of safe software.

Mobile App Development & Android Projects for €30-250 EUR. Necesito desarrollar una aplicación de sopa de letras que funcione en iOS y Android. El juego debe abarcar los

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Mobile App Development & Android Projects for ₹37500-75000 INR. 1. Project Overview We are seeking an experienced and security-focused mobile developer or development te

This guide covers the biggest Android app development trends today. It gives developers clear ideas to build apps that meet today's needs and get ready ...

While mobile applications have been a prevalent mode of digital consumption for over a decade, they have become more than just tools of...

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At Kindlebit Solutions, we create powerful and user-friendly mobile apps that help businesses grow. Our expert developers use the latest tools to design apps tailored to your goals and audience. Partn...

Mobile App Development & Android Projects for ₹600-1500 INR. I already have a fully-functional Android companion for my web-based POS. All core features and REST APIs are

Background: The rapid proliferation of #Mobile #Health applications has underscored the need for robust tools to evaluate their quality. The #Mobile #App Rating Scale (MARS) is a widely used framework to assess key #App dimensions—Engagement, Functionality, Aesthetics, and Information—that influence user satisfaction. Despite its utility, limited research has leveraged MARS dimensions to predict user ratings effectively. Objective: This study investigates how K Means clustering, combined with machine learning models, can predict user ratings for #PhysicalActivity apps based on MARS dimensions, with the goal of forecasting ratings prior to production and uncovering insights into user satisfaction drivers. Methods: The dataset comprises MARS-rated #PhysicalActivity apps with user ratings. Initially, exploratory data analysis provided insights into generalized patterns among MARS dimensions. K Means clustering segmented the apps into two clusters, enhancing data homogeneity. Predictive models were then applied to both the unclustered dataset and the clustered subsets, with performance evaluated based on accuracy, mean absolute error (MAE), and R-squared values. The top-performing model from each cluster was selected for combined analysis to further improve prediction reliability. Results: In the unclustered dataset, KNN achieved the highest accuracy (86.36%) with an MAE of 0.26 and R-squared of 0.06. Post-clustering, SVR achieved the highest accuracy in Cluster 1 (88.89%, MAE 0.27, R-squared 0.05), and KNN excelled in Cluster 2 (88.24%, MAE 0.28, R-squared 0.03). Combining the predictions of these models for the two clusters improved overall accuracy to 88.64%, with MAE of 0.27 and R-squared of 0.04. Conclusions: The combined clustering and model approach enhances prediction accuracy and reveals how user satisfaction drivers vary across #App types. This tailored methodology offers insights for #App developers aiming to optimize apps, aligning features with distinct user needs for higher satisfaction and engagement.