23 papers · ranked by Valyu relevance
Durga Shree Nagabushanam, Sree Dharinya S, V. Sree Dharinya, Nadendla Sai Roopa + 1 more
'Nadendla Sai Roopa' 'Anugu Arun'] Abstract— The requirements in automation, digitalization, and fast computations have loaded the IT sector with expectations of highly reliable, efficient, and cost-effective software. Given that the process of testing, verification, and validation of software products consumes 50-75%…
Zubair Khaliq, Sheikh Umar Farooq, Dawood Ashraf Khan
Artificial Intelligence (AI) is making a significant impact in multiple areas like medical, military, industrial, domestic, law, arts as AI is capable to perform several roles such as managing smart factories, driving autonomous vehicles, creating accurate weather forecasts, detecting cancer and personal assistants…
Fabiano Pecorelli, Giovanni Grano, Fabio Palomba, Harald Gall + 1 more
'Andrea De Lucia'] Unit testing verifies the presence of faults in individual software components. Previous research has been targeting the automatic generation of unit tests through the adoption of random or searchbased algorithms. Despite their effectiveness, these approaches do not implement any strategy that allows…
Marcela G. dos Santos, Sylvain Hallé, Fabio Petrillo, Yann-Gaël Guéhéneuc
Industrial robotic systems (IRS) consist of industrial robots that automate industrial processes. They accurately perform repetitive tasks, replacing or assisting with dangerous jobs like assembly in the automotive and chemical industries. Failures in these systems can be catastrophic, so it is important to ensure…
Vahid Garousi, N. Eneh Joy, Alper Buğra Keleş
evaluation Authors: ['Vahid Garousi' 'N. Eneh Joy' 'Alper Buğra Keleş'] Abstract—Context: Test engineers are looking at more ways to test system more effectively and efficiently. Automated Software testing facilitated a significant advancement in accelerating test processes compared to manual methods. With recent…
Filippo Ricca, Alessandro Marchetto, Andrea Stocco
Methods: We reviewed over 3,600 grey literature sources over five years, including blogs, white papers, and user manuals, and finally filtered 342 documents to develop taxonomies of TA problems and AI solutions. We also cataloged 100 AI-driven TA tools and interviewed five expert software testers to gain insights into…
Yongxiang Hu, Xuan Wang, Yingchuan Wang, Yu Zhang + 4 more
'Chaoyi Chen' 'Xin Wang' 'Yangfan Zhou'] The Graphical User Interface (GUI) is how users interact with mobile apps. To ensure it functions properly, testing engineers have to make sure it functions as intended, based on test requirements that are typically written in natural language. While widely adopted manual…
Emily J. Cartwright, Priti Patel, Saleem Kamili, Carolyn Wester
Current hepatitis C virus (HCV) testing guidance recommends a two-step testing sequence for diagnosis of HCV infection. Performing an HCV RNA test whenever an HCV antibody test is reactive (complete testing) is critical to achieve national HCV elimination goals. When an HCV antibody test is reactive and no HCV RNA test…
Markus Sommer, Martin Arendasy
This article provides a critical review of conceptually different approaches to automatic and transformer-based automatic item generation. Based on a discussion of the current challenges that have arisen due to changes in the use of psychometric tests in recent decades, we outline the requirements that these approaches…
Authors not listed
The development of polymer materials for real-world applications requires careful assessment of material degradation over time and under environmental exposure. Such tests often necessitate frequent monitoring of test specimens, which can become burdensome for researchers. In this study, we present the application of a…
Yiyi Wang, Lei Shi, Jue Zhang, Chen Chen
A fast rate, easy operation, high accuracy and high sensitivity characterise the automatic biochemical analyser. At present, the detection process has essentially been automated. However, IQC still mainly relies on manual operation; therefore, the operators’ human influence will significantly impact the IQC results .…
Vishal Bharti, Debojyoti Chakraborty
Reproducible computational biology depends on statistical decisions that routine workflows often skip: verifying that a differential-expression test’s assumptions hold across all genes, that a strategy-comparison ANOVA is robust to non-normality, or that a meta-analysis is not distorted by publication bias. Surveys…
Daniel Bengs, Ulf Brefeld, Ulf Kroehne, Fabian Zehner
Test items using open-ended response formats can increase an instrument’s construct validity. However, traditionally, their application in educational testing requires human coders to score the responses. Manual scoring not only increases operational costs but also prohibits the use of evidence from open-ended items to…
Authors not listed
Bridging AI and self-driving laboratories, we introduce the first fully-automated, closed-loop molecular discovery cycle, exemplified by the identification of novel JAK inhibitors. With minimal human intervention, we combined AI-driven molecular design and retrosynthesis with IBM’s synthesis automation system RoboRXN…
Robert Shaw, Grant Hill
The basis set used in quantum chemical calculations for molecular applications is vital to the accuracy and efficiency of the calculation, but the development of novel basis sets is hindered by an opaque process and inaccessibility of the tools required. We present here BasisOpt, a tool for the automated optimization…
Authors not listed
Despite the promise of self-driving laboratories to accelerate discovery, their widespread implementation is hindered by prohibitive cost and technical complexity. We introduce BrickSDLab, a fully functional self-driving lab platform built entirely from LEGO® components, designed to bridge this accessibility gap.…
Authors not listed
Automation of experiments in cloud laboratories promises to revolutionize scientific research by enabling remote experimentation and improving reproducibility. However, maintaining quality control without constant human oversight remains a critical challenge. Here, we present a novel machine learning framework for…
Vikas Mishra, Rajkumar Verma, Paruvathanahalli Siddalingam Rajinikanth, Ravinder K. Kaundal
Quantitative analysis of rodent behaviour is fundamental to neuroscience, preclinical drug discovery and neurotoxicology research. Although several commercial and open-source software packages are available for behavioural assessment, some are expensive, some require programming expertise, and some provide limited…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
David Brust, Johannes J. Brust
Grouping samples with low prevalence of positives into pools and testing these pools can achieve considerable savings in testing resources compared with individual testing in the context of COVID-19. We review published pooling matrices, which encode the assignment of samples into pools and describe decoding…
Jansen N. Seheult, Michelle N. Stram, Lydia Contis, Raymond E. Pontzer + 7 more
PittUDT, a recursive partitioning decision tree algorithm for predicting urine culture (UC) positivity based on macroscopic and microscopic urinalysis (UA) parameters, may significantly decrease the number of unnecessary UC. The reflex algorithm derivation included 38,361 paired UA and UC cases; the average patient age…
Bryan Glazer, Jonathan Lifferth, Carlos F. Lopez
Many important processes in biology, such as signaling and gene regulation, can be described using logic models. These logic models are typically built to behaviorally emulate experimentally observed phenotypes, which are assumed to be steady states of a biological system. Most models are built by hand and therefore…
Nathan Zhuang, Jacqueline Howells
This article describes a comprehensive computational pipeline for stratifying autoimmune patient groups using exclusively binary (positive/negative) autoantibody data. The method addresses a significant methodological gap in computational immunology by providing a standardized framework for analyzing categorical…