相关论文: CRUD-Capable Mobile Apps with R and shinyMobile: a…
Data collection is an integral part of any citizen science project. Given the wide variety of projects, some level of expertise or, alternatively, some guidance for novice participants can greatly improve the quality of the collected data.…
We consider the problem of generating relevant execution traces to test rich interactive applications. Rich interactive applications, such as apps on mobile platforms, are complex stateful and often distributed systems where sufficiently…
The interAdapt R package is designed to be used by statisticians and clinical investigators to plan randomized trials. It can be used to determine if certain adaptive designs offer tangible benefits compared to standard designs, in the…
Pretrained vision-language models such as CLIP exhibit strong zero-shot generalization but remain sensitive to distribution shifts. Test-time adaptation adapts models during inference without access to source data or target labels, offering…
With growing mobile-network complexity, management and optimization have become increasingly difficult. Centralized algorithms face high control-data overhead and computational load, while distributed approaches often perform far from…
The rise of the programmable web offers new opportunities for the empirically driven social sciences. The access, compilation and preparation of data from the programmable web for statistical analysis can, however, involve substantial…
Reliable parameter extraction from experimental data is central to quantitative analysis in spectroscopy, diffraction, photoluminescence, chromatography, microscopy, and time-resolved measurements. We present FitED, a Python-based desktop…
Human Activity Recognition (HAR) using wearable and mobile sensors has gained momentum in last few years, in various fields, such as, healthcare, surveillance, education, entertainment. Nowadays, Edge Computing has emerged to reduce…
In the past few years, mobile devices have been increasingly replacing traditional computers as their capabilities such as CPU computation, memory, RAM size, and many more, are being enhanced almost to the level of conventional computers.…
A central bottleneck for phone-use agents is that controllable, reproducible environments covering real mobile behavior are hard to build at scale. Existing mobile-agent benchmarks have made important progress on evaluation, but they do not…
The rapid enhancement of central power unit CPU performance enables the development of computationally-intensive healthcare mobile applications for smartphones and wearable devices. However, computationally intensive mobile applications…
Introduction: Despite their applicability, statistical models used for the meta-analysis of test accuracy require specialised knowledge to implement, with the necessary level of expertise having recently increased. This is due to the…
An empirical investigation of active/continuous authentication for smartphones is presented in this paper by exploiting users' unique application usage data, i.e., distinct patterns of use, modeled by a Markovian process. Variations of…
Accurate assessment of adverse event (AE) incidence is critical in clinical cancer research for drug safety evaluation and regulatory approval. While meta-analysis serves as an essential tool to comprehensively synthesize the evidence…
The performance model of an application can pro- vide understanding about its runtime behavior on particular hardware. Such information can be analyzed by developers for performance tuning. However, model building and analyzing is…
With the ever-growing interest in the area of mobile information retrieval and the ongoing fast development of mobile devices and, as a consequence, mobile apps, an active research area lies in studying users' behavior and search queries…
Modern mobile applications are benefiting significantly from the advancement in deep learning, e.g., implementing real-time image recognition and conversational system. Given a trained deep learning model, applications usually need to…
Many models have been proposed for vision and language tasks, especially the image-text retrieval task. All state-of-the-art (SOTA) models in this challenge contained hundreds of millions of parameters. They also were pretrained on a large…
Data depth concept offers a variety of powerful and user friendly tools for robust exploration and inference for multivariate socio-economic phenomena. The offered techniques may be successfully used in cases of lack of our knowledge on…
The synthpop package for R https://www.synthpop.org.uk provides tools to allow data custodians to create synthetic versions of confidential microdata that can be distributed with fewer restrictions than the original. The synthesis can be…