Automatic Test Research Articles

Non-Destructive Classification of Maize Seeds Based on RGB and Hyperspectral Data with Improved Grey Wolf Optimization Algorithms

Ensuring the security of germplasm resources is of great significance for the sustainable development of agriculture and ecological balance. By combining the morphological characteristics of maize seeds with hyperspectral data, maize variety classification has been achieved using machine learning algorithms. Initially, the morphological data of seeds are obtained from images, followed by the selection of feature subsets using Recursive Feature Elimination (RFE) and Select From Model (SFM) methods, indicating that features selected by RFE exhibit better performance in maize seed classification. For hyperspectral data (350–2500 nm), Competitive Adaptive Re-weighted Sampling (CARS) and the Successive Projections Algorithm (SPA) are employed to extract feature wavelengths, with the SPA algorithm demonstrating superior performance in maize seed classification tasks. Subsequently, the two sets of data are merged, and a Random Forest (RF) classifier optimized by Grey Wolf Optimization (GWO) is utilized. Given the limitations of GWO, strategies such as logistic chaotic mapping for population initialization, random perturbation, and final replacement mechanisms are incorporated to enhance the algorithm’s search capabilities. The experimental results show that the proposed ZGWO-RF model achieves an accuracy of 95.9%, precision of 96.2%, and recall of 96.1% on the test set, outperforming the unimproved model. The constructed model exhibits improved identification effects on multi-source data, providing a new tool for non-destructive testing and the accurate classification of seeds in the future.

Abstract 777: Notch signaling dependent chemoresistance in racial disparity in ER+ breast cancer

Abstract Breast cancer (BCa) is the leading cause of cancer related death in women worldwide. The most common BCa subtype is the Estrogen/Progesterone receptor (ER+/PR+) luminal subtype, comprising up to 75% of all newly diagnosed BCa. Although these patients show initial benefit with chemotherapy and endocrine therapy, however, 40-50% of them eventually don’t respond to treatment due to resistance. Thus, the need for additional targeted therapies for this large subset of ER+ BCa patients is critical. Based on recent studies, it is observed that Afro-American (AA) patients experience substantially higher BCa mortality (40% more) than White American (WA) women in ER+ breast cancer. Unfortunately, the cause behind this difference in mortality in AA patients is not well understood. Notch signaling is a highly conserved intercellular communication mechanism critical for many cellular processes and is composed of several receptors and ligands. Recent data show that Notch receptors are overexpressed in hormone treatment refractory ER− patients of (Afro-American) AA origin, hinting connection of Notch signaling to racial disparity in breast cancer. Notch signaling is also identified in several metabolic disorders involving fatty acids and other lipids. However, function of Notch signaling in context of chemoresistance in AA ER+ breast cancer is still unknown. Using single cell sequencing, we found that chemo-resistant AA ER+ breast cancer patient samples have a distinct Notch signature enriched subpopulations in tumor cells, which was missing in WA patients. Notch signaling happens through juxtacrine signaling of ligand/receptor signaling. Further analysis in tumor microenvironment shows lipid enriched tumor associated macrophages, which are Notch dependent, suggesting potential crosstalk between lipid heavy tumor-macrophages and tumor cells, which may drive the chemoresistance in AA patients. Further analysis using patient derived explants, an attractive new tool for drug efficacy testing in ex vivo, we found that chemotherapy itself increases Notch signaling in the tumors. Ongoing studies involving scRNAseq, untargeted lipidomics and chemo-resistant PDE will delineate the precise mechanism of action between tumor cells and tumor associated lipid heavy macrophages in context of Notch signaling in chemo-resistant AA ER+ breast cancer. Citation Format: Shailesh Singh, Megha Das, Rumela Chakrabarti. Notch signaling dependent chemoresistance in racial disparity in ER+ breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 777.

Digital transformation in public health: a software tool for efficient health record management and improved healthcare delivery

Background In today’s world, the abundance of data in many areas of society has increased the need to use efficient technological tools to analyse, accurately and clearly present information. The objective was to develop a virtual platform to increase efficiency in the control of medical records (MR) and reduce errors in the recording of clinical data. To improve the quality of medical care in public health centres. Method The research used a methodology that follows a four-stage process for the development of the medical records management software. It started with planning where the user stories and their priority were defined. In the design phase, the system architecture and code structure were developed. Subsequently, in the coding phase, pair programming with incremental implementation was emphasised. Finally, in the testing phase, automatic and manual integration tests were carried out, documented by means of acceptance tests to ensure the quality of the developed software. Results The web-based platform has led to a significant increase in the number of patients seen, resulting in significant improvements in resource management at the health centres. In addition, the reduction in the incidence of errors highlights the superior accuracy in recording and tracking medical information, promoting a safer and more efficient care environment for patients. Conclusions The main focus of this study is the management of medical records, with the aim of reducing the time spent on registration, ensuring secure access to information, reducing documentation errors and facilitating instant data retrieval through a web-based platform. The results show the effectiveness of this methodology and its positive impact on the management of medical records.

Nearshore fish diversity changes with sampling method and human disturbance: Comparing eDNA metabarcoding and seine netting along the Upper St. Lawrence River

Aquatic ecosystems are deteriorating, with the most impacted species and populations having insufficient data to inform conservation and management. Monitoring aquatic biodiversity and evaluating anthropogenic impacts typically rely on time-consuming, logistically challenging, and invasive methods (e.g., seining, trawling or electrofishing). Environmental DNA (eDNA) methods have been touted as an important advancement, especially in fish biodiversity assessment. We compare eDNA metabarcoding and seining methods along a 350 km section of the Upper St. Lawrence River (Canada) for: i) mapping the distribution of invasive and threatened fish species, ii) describing species richness and fish community structure, and iii) assessing the effect of habitat type and anthropogenic degradation of riparian zones on fish community composition and richness. eDNA detected more fish species (n = 67) than seining (n = 38) and revealed higher fish diversity in samples adjacent to intact, natural riparian zones. Fish assemblages were influenced by habitat type according to analyses using eDNA, while no effect of any environmental predictor on fish community composition was found using seining. Altogether, our results support eDNA metabarcoding as a powerful, complementary tool in fish monitoring and testing for the impacts of anthropogenic disturbances.

3D Polymer Gel Dosimeters with iCBCT 3D Reading and polyGeVero-CT Software Package for Quality Assurance in Radiotherapy.

Dynamically evolving radiotherapy instruments require advancements in compatible 3D dosimetry systems. This paper reports on such tools for the coincidence test of the mechanical and radiation isocenter for a medical accelerator as part of the quality assurance in routine radiotherapy practice. Three-dimensional polymer gel dosimeters were used in combination with 3D reading by iterative cone beam computed tomography and 3D data processing using the polyGeVero-CT software package. Different polymer gel dosimeters were used with the following acronyms: VIP, PAGAT, MAGIC, and NIPAM. The same scheme was used for each dosimeter: (i) irradiation sensitivity test for the iterative cone beam computed tomography reading to determine the appropriate monitor unit for irradiation, and (ii) verification of the chosen irradiation conditions by a star-shot 2D irradiation of each 3D dosimeter in the direction of performing the test. This work concludes with the optimum monitor unit per beam for each selected 3D dosimeter, delivers schemes for quick and easy determination of the radiation isocenter and performing the coincidence test.

Identifying and Validating Alcohol Diagnostics for Injury-Related Trauma in South Africa: Protocol for a Mixed Methods Study.

The burden of alcohol use among patients with trauma and the relative injury risks is not routinely measured in South Africa. Given the prominent burden of alcohol on hospital trauma departments, South Africa needs practical, cost-effective, and accurate alcohol diagnostic tools for testing, surveillance, and clinical management of patients with trauma. This study aims to validate alcohol diagnostics for injury-related trauma and assess its use for improving national health practice and policy. The Alcohol Diagnostic Validation for Injury-Related Trauma study will use mixed methods across 3 work packages. Five web-based focus group discussions will be conducted with 6 to 8 key stakeholders, each across 4 areas of expertise (clinical, academic, policy, and operational) to determine the type of alcohol information that will be useful for different stakeholders in the injury prevention and health care sectors. We will then conduct a small pilot study followed by a validation study of alcohol diagnostic tools (clinical assessment, breath analysis, and fingerprick blood) against enzyme immunoassay blood concentration analysis in a tertiary hospital trauma setting with 1000 patients. Finally, selected alcohol diagnostic tools will be tested in a district hospital setting with a further 1000 patients alongside community-based participatory research on the use of the selected tools. Pilot data are being collected, and the protocol will be modified based on the results. Through this project, we hope to identify and validate the most appropriate methods of diagnosing alcohol-related injury and violence in a clinical setting. The findings from this study are likely to be highly relevant and could influence our primary beneficiaries-policy makers and senior health clinicians-to adopt new practices and policies around alcohol testing in injured patients. The findings will be disseminated to relevant national and provincial government departments, policy experts, and clinicians. Additionally, we will engage in media advocacy and with our stakeholders, including community representatives, work through several nonprofit partners to reach civil society organizations and share findings. In addition, we will publish findings in scientific journals. DERR1-10.2196/52949.

Development of toluidine red particle agglutination-based turbidimetric immunoassay for anticardiolipin antibody detection in syphilis

IntroductionSerological tests of non-treponemal and treponemal types are the most frequently used for syphilis diagnosis. Nontreponemal tests are used to monitor disease activity. Toluidine red unheated serum test (TRUST), as one of nontreponemal tests, is generally applicable to hospitals at different levels. However, accurate judgment of TRUST results is inseparable from an experienced and accurate operator. To reduce current shortcomings of manual TRUST method, we attempted to convert the manual TRUST test into automatic TRUST test, that is, to determine the degree of aggregation of toluidine red particles by detecting the absorbance value of serum after reaction with toluidine red particles. Methods50 μL of serum sample and 80 μL toluidine red particles were added to 96-well plate. Then, the 96-well plate was placed on a microplate reader at medium grade for 8 min to mix. Then, plasma reagin reacted with toluidine red particles and promoted the aggregation of toluidine red particles to form a large clot, which eventually caused a decrease in the absorbance at 540 nm. ResultsThe results showed that the specificity of the automatic TRUST test was 100%, the sensitivity was 87%. And this method showed 93.5% correlation with manual TRUST test. The developed method is simple and involves less subjectivity in reading results, opening new avenues for syphilis diagnostic testing. ConclusionTurbidimetric immunoassay can avoid the shortcomings of subjective interpretation, time-consuming and manual operation of manual TRUST method, and is more suitable for large-scale screening in health examination.

A Novel IoT-Based Performance Testing Method and System for Fire Pumps

Fire pumps are the key components of water supply in a firefighting system. At present, there is a lack of fire water pump testing methods that intelligently detect faulty states. Existing testing approaches require manual operation, which leads to low efficiency and accuracy. To solve the issue, this paper presents an automatic and smart testing approach that acquires measurements of the flow, pressure, shaft power and efficiency from smart sensors via an IoT network, so that performance curves are obtained in the testing processes. An IoT platform is developed for data conversion, transmission and storage. The Discrete Fréchet Distance is applied to evaluate the similarities between the acquired performance curves and metric performance curves, to determine the working condition of the fire pump. The weights of the measurement dimensions for distance computation are optimized by the Genetic Algorithm to improve the distinction between normal and faulty performance curves. Finally, the experimental results show that the proposed method can completely detect faulty states and prove its high practicality for real firefighting systems.

A Conference Designathon to Spark Innovation: Actionable Ideas to Enhance Sexually Transmitted Disease Control.

Designathons can be used to enhance public health training and spur innovation. A designathon is a 3-stage participatory activity that includes preparation, intensive collaboration, and follow-up activities. We organized a designathon focused on developing actionable sexually transmitted disease (STD) control strategies and examined the content of ideas resulting from an STD designathon. For this designathon, we created four groups: early career researchers, silver group (people with >10 years of experience), travelers (people from low- and middle-income countries and those who received a conference scholarship) and a community group. Each group developed its own plan to consult members, iteratively develop ideas, and aggregate insights. Each group developed STD control strategies that were presented. Cross-cutting themes across these ideas were identified. Designathon participants included a subset of conference participants. Cross-cutting themes from final ideas included cocreating STD interventions with end-users, using sex-positive framing, enhancing open access digital STD resources, and reducing STD stigma. Early career researchers presented a call for community ideas focusing on ending STD epidemics by increasing accessibility to STD care services among all populations. The silver group proposed digital innovations, including an AI-powered tool for testing and treatment and a social game to promote sex positivity. The traveler group conceptualized an information hub to support implementation of STD programs. Community members underscored the importance of a more human-centered approach to STD control, which reduces stigma and normalizes sex and sexual pleasure. Sex positive campaigns and open access digital resources should be considered within STD programs. Implementation research studies are needed to evaluate these ideas.

The Role of Artificial Intelligence in Enhancing Test Automation: Current Trends and Future Directions

The Role of Artificial Intelligence in Enhancing Test Automation: Current Trends and Future Directions

An Improved Particle Swarm Optimization Algorithm for Automated Test Resource Allocation

With the rapid increase of software complexity, automated testing has become the mainstream of software testing. However, the current automated test tools adopt a large number of common test equipment resource. At the beginning of the test, for specific test scenarios, the testers need to plan the test equipment resources according to the requirements of the software under test. An automatic test equipment resource planning and optimization algorithm based on group optimization is proposed IPSO (Improved Particle Swarm Optimization) to solve this problem. This method maps the requirement description to the equipment description to obtain the matching matrix, and then establishes a multi-objective constrained optimization model for test equipment resource planning. The solution is obtained through improved particle swarm optimization algorithm to achieve the optimal planning of test equipment resources. Compared with traditional manual planning methods, this algorithm reduces the workload of testers, and improves the automation and efficiency of testing. Experimental results demonstrate that the optimal solutions found by the algorithm proposed in this paper is superior to those of the PSO (Particle Swarm Optimization)) and Linearly Decreasing Inertia Weight Particle Swarm Optimization (LWPSO) algorithms.

High pre-Delta and early-Omicron SARS-CoV-2 seroprevalence detected in dried blood samples from Kinshasa (D.R. Congo).

Studies on the impact of the COVID-19 pandemic in sub-Saharan Africa have yielded varying results, although authors universally agree the real burden surpasses reported cases. The primary objective of this study was to determine SARS-CoV-2 seroprevalence among patients attending Monkole Hospital in Kinshasa (D.R. Congo). The secondary objective was to evaluate the analytic performance of two chemiluminescence platforms: Elecsys® (Roche) and VirClia® (Vircell) on dried blood spot samples (DBS). The study population (N = 373) was recruited in two stages: a mid-2021 blood donor cohort (15.5% women) and a mid-2022 women cohort. Crude global seroprevalence was 61% (53.9%-67.8%) pre-Delta in 2021 and 90.2% (84.7%-94.2%) post-Omicron in 2022. Anti-spike (S) antibody levels significantly increased from 53.1 (31.8-131.3) U/mL in 2021 to 436.5 (219.3-950.5) U/mL in 2022 and were significantly higher above 45 years old in the 2022 population. Both platforms showed good analytic performance on DBS samples: sensitivity was 96.8% for IgG (antiN/S) (93.9%-98.5%) and 96.0% (93.0%-98.0%) for anti-S quantification. These results provide additional support for the notion that exposure to SARS-CoV-2 is more widespread than indicated by case-based surveillance and will be able to guide the pandemic response and strategy moving forward. Likewise, this study contributes evidence to the reliability of DBS as a tool for serological testing and diagnosis in resource-limited settings.

Energy loss analyses of amorphous magnetic ribbons by multi-frequency single sheet tester

Due to low values of both thickness and conductivity, Fe-based amorphous soft magnetic ribbon (AR) is an attractive alternative to crystalline silicon steel (CS) for elevated frequencies f up to several kHz. On the other hand, for corresponding tests of losses P, the only standardized method is restricted to just 400 Hz. Recently, we reported “Physically Consistent Loss Testing” (CLT) for loss tests of CS for f up to 10 kHz. Here, we describe an adaptation of a corresponding multi-frequency single sheet tester for AR-applications. The CS single sheet is replaced by six 50 cm long and 17 cm wide ARs, loosely inserted into a paper envelope. This “envelope technique” provides (i) simple sample arrangement in an absolutely flat state, (ii) high repeatability, (iii) robust sensor signals, (iv) avoidance of loss increases due to magneto-mechanical effects, and (v) averaging over thickness variations of ARs through as much as 100 g of sample mass. Here, we report the results of frequency analyses for sinusoidal magnetization in the longitudinal direction for induction up to 1.5 T for f < 1 kHz and 0.4 T for 10 kHz, with P up to 50 W/kg. Anisotropy tests confirm a very weak dominance of the transverse direction. In conclusion, CLT proves to be an effective tool for loss tests on both CS and AR as a physically consistent principle. Therefore, for the ongoing standardization of SST with H-coil, we recommend considering the integration of the “envelope technique” in order to establish rapid and universal multi-frequency loss testing.

CIVA Modelling Module for Zonal Discrimination Method Part 2-System Qualification Aspects

Automatic Ultrasonic Testing (AUT) systems for pipeline girth weld inspections are usually subjected to a qualification process. This process consists of assessment of performance capabilities including detection, sizing, temperature range and repeatability. One of the most demanding qualification programmes is described in DNV ST-F101 Appendix E [1]. With the introduction of the AUT module in the 2023 edition of CIVA simulation software, the incorporation of metamodeling allows users to predict detection reliability via probability of detection (POD) and sizing accuracy of the zonal discrimination method (ZDM) using amplitude apportioning. Part 1 of this project demonstrated the ability of CIVA to simulate the calibration block and strip chart output. In Part 2 we illustrate the techniques that can be used to predict POD and sizing accuracy as might be done in a system qualification. Results compare well to field data.

Overall Scheme Design of Fault Diagnosis for Complex Electronic Systems

Traditional manual testing methods are no longer able to meet the maintenance needs of modern shipboard fire control system board-level circuits. Therefore, the development of intelligent and universal automatic test systems has become an important issue for shipboard fire control system fault detection. This article analyzes the performance and functional requirements of the automatic test system, develops the automatic test system based on PXI bus instruments, and designs an overall solution with signal time-frequency analysis capabilities that can carry out intelligent fault diagnosis for a variety of board-level circuits. On this basis, the design of hardware circuit and software solution is completed. The automatic test system was analyzed on hardware indicators and software functions. On the hardware side, the hardware resource selection was completed based on the hardware indicator requirements. On the software side, the overall software architecture design and the design of each functional module were completed based on the system software functional requirements. Finally, the composition and functions of each module of the system software and the overall operation process are introduced.

Design of Fault Diagnosis Method Based on Circuit Frequency Domain Characteristics Fault Dictionary Method

In recent years, with the rapid development of integrated circuits and the widespread application of smart chips, the internal structure of complex electronic systems have become increasingly complex, which greatly increases the difficulty of board-level circuit testing and fault diagnosis of complex electronic systems. At present, traditional manual testing methods are no longer able to meet the maintenance requirements of modern complex electronic system board-level circuit. Therefore, the development of intelligent and universal automatic testing systems has become an important issue in fault detection of complex electronic systems. Based on the testing requirements of the automatic test system(ATS), this paper designs the corresponding overall scheme, software scheme and hardware circuit, and studies the fault diagnosis and test of board-level circuit of complex electronic system, and proposes to apply the traditional Bode diagram to the engineering practice of ATS. Fault detection is realized by utilizing the frequency domain characteristics of the object under test.

AI in Test Automation: Overcoming Challenges, Embracing Imperatives

This scholarly article delves into the intersection of Artificial Intelligence (AI) and Test Automation, thoroughly examining the challenges inherent in implementing AI methodologies and elucidating imperatives critical for successful integration within contemporary software testing frameworks. The research entails a comprehensive exploration of challenges, ranging from intricacies in data quality to algorithmic biases, tool complexities, and integration challenges, drawing on empirical evidence from case studies and real-world scenarios. The paper articulates imperatives essential for overcoming challenges and ensuring the efficacy of AI in test automation. It emphasizes the significance of structured training programs, meticulous data management strategies, and the cultivation of an organizational culture conducive to the seamless integration of AI technologies. Through a rigorous analysis of successful case studies, the article provides a scholarly basis for the formulation of strategies and solutions to surmount challenges faced by organizations adopting AI in testing practices. A visual matrix aligning challenges with corresponding imperatives adds scholarly rigor to the article, offering a comprehensive framework for understanding the intricate relationships between challenges and the imperative strategies required for resolution. Furthermore, the exploration of emerging trends and innovations anticipates the future trajectory of AI-driven test automation, contributing valuable insights for strategic planning in the realm of software testing. This scholarly work underscores the importance of a systematic and informed approach to AI in Test Automation. By addressing challenges with academic rigor and embracing imperative strategies grounded in empirical evidence, organizations can position themselves at the forefront of AIdriven testing practices, advancing the field with a scholarly foundation for continued exploration and innovation.

IMPLEMENTATION OF AUTOMATIC PLANT SPRINKLERS USING SOIL MOISTURE SENSORS

Automatic plant sprinklers aim to replace manual work into automatic, as for the benefits obtained from this tool is that it can facilitate human work in watering onion plants. This tool uses a soil moisture sensor that functions as a soil moisture detector and sends commands to Arduino uno to turn on the relay so that the pump can turn on and splash water according to soil needs automatically. The design of this tool utilizes the nature of water, which is to fill empty space, and is always flat, this automatic plant sprinkler uses a water reservoir before water is splashed on the ground. Output holes applied to water reservoirs of the same height and diameter allow watering of the soil evenly. The results of the automatic plant sprinkler design test obtained after three tests, have a difference in the amount of water released from water hole one and water hole two, which ranges from 0-7%, which means it is still within the tolerance limit for onion plants, onion plants need soil moisture between 70-80%, which means it has a moisture tolerance between 10%.

The effect of attention shifting on Chinese children's word reading in primary school.

This study explored the effects of attention shifting on Chinese children's word reading. The sample consisted of 87 fourth-grade children from Shaoxing City, China. The students completed measures of the attention shifting task, reading accuracy test, reading fluency test, and rapid automatized naming test. The results showed that reading fluency was significantly correlated with attention shifting scores, specifically with tag1 and tag6 (ps < 0.05). The reading accuracy score was also significantly correlated with tag6 (p < 0.05). According to the regression analysis of attention shifting on word reading, even when controlling for rapid automatic naming, attention shifting significantly affected word reading fluency at approximately 600ms (p = .011). Attention shifting did not affect children's word reading accuracy. These findings suggest that attention shifting is significantly associated with children's word reading. Educators should focus on developing children's attention shifting to improve their word reading ability.

Sample-orientation effects in solid-state high-harmonic generation: computational study of GaAs

We report on a large-scale simulation study of the sample-orientation effects in solid-state high-harmonic generation, utilizing a fully three-dimensional GaAs model in conjunction with a solver for semiconductor Bloch equations that faithfully reflects the material symmetry and accounts for the optical response from the entire Brillouin zone. The simulations, qualitatively compared to two sets of independent measurements, demonstrate that the orientation-resolved high-harmonic spectra represent an effective tool for rigorous testing of material models. The results are relevant for the future development of all-optical reconstruction of electronic band-structure from the solid-state high-harmonic generation measurements.