Reduce Test Cost Research Articles

Chisel edge wear measurement of high-speed steel twist drills based on machine vision

Tool wear is usually the most relevant parameter of tool performance detection, which directly affects the product quality and tool life. Online tool condition monitoring can effectively reduce workpiece scrap and machine failure. Chisel edge wear is one of the main wear forms in high-speed steel (HSS) twist drill. A machine vision method for chisel edge wear measurement is proposed in this paper to improve measure accuracy and reduce testing costs. Firstly, Otsu segmentation based on Laplacian edge information is proposed for tool image segmentation. A morphology-based Canny operator is developed to perform edge detection and image registration for rough positioning of the tool wear area. Zernike moment-based sub-pixel edge detection is proposed to improve the measurement accuracy. Finally, principal curve is employed to fit sub-pixel edge points to obtain smooth edge curve of the tool wear. Finally, the chisel edge wear can be detected and measured effectively based on the proposed method. In the real machining process, the test results show that the proposed system shows high response speed and inspecting accuracy, which is more convenient and efficient than manual measurement with an electron microscope. This system can be effectively applied to the real-time monitoring of tool wear in industry.

Research on Dynamic Performance Simulation of In-wheel Motor Electric Vehicle Based on CarSim-Simulink

In order to reduce test costs and improve work efficiency, on the basis of the existing in-wheel-motor electric vehicle platform, CarSim software is used to establish a complete in-wheel-motor electric vehicle model that matches the actual vehicle. Based on Simulink, the dynamic model of the in-wheel motor is established. By defining the interface between the vehicle and the motor drive system, a joint simulation platform for in-wheel motor electric vehicles is established based on CarSim-Simulink, and simulation verification is performed on it. The results show that the established simulation model has high accuracy, can better simulate the existing experimental vehicle, accurately reflect the dynamic performance response of the vehicle, and provide a basis for further research and verification of control algorithms.

Institutional Experience Using a Treatment Algorithm for Electrical Injury.

Electrical injury has low incidence but is associated with high morbidity and mortality. Variability in diagnosis and management among clinicians can lead to unnecessary testing. This study examines the utility of an electrical injury treatment algorithm by comparing the incidence of testing done on a cohort of patients before and after implementation. Demographics, injury characteristics, and treatment information were collected for patients arriving to a regional burn center with the diagnosis of electrical injury from January 2013 to September 2018. Results were compared for patients admitted before and after the implementation of an electrical injury treatment algorithm in July 2015. There were 56 patients in the pre-algorithm cohort and 38 in the post-algorithm cohort who were of similar demographics. The proportion of creatine kinase (82% vs 47%, P < .0006), troponin (79% vs 34%, P < .0001), and urinary myoglobin (80% vs 45%, P < .0007) testing in the pre-algorithm cohort was significantly higher compared to post-algorithm cohort. There were more days of telemetry monitoring (median [IQR], 1 [1-5] vs 1 [1-1] days, P = .009) and greater ICU length of stays (4 [1-5] vs 1 [1-1] days, P = .009), prior to algorithm implementation. There were no significant differences in total hospital lengths of stay, incidence of ICU admissions, in-hospital mortality, or 30-day readmissions. This study demonstrates an electrical injury evaluation and treatment algorithm suggests a mode of triage to cardiac monitoring and hospital admission where necessary. Use of this algorithm allowed for reduction in testing and health care costs without increasing mortality or readmission rates.

Research on Intelligent Cloud Test Platform

With the increasing complexity of software information systems, software quality assurance faces enormous challenges. The software information system is more and more complex, and the quality requirements are getting higher and higher. The traditional automated test methods and tools can not adapt to the changing test requirements. The research on the independent controllable intelligent test platform based on cloud computing and big data will be carried out. The combination of platform and software testing not only reduces test costs, but also improves test efficiency and effectiveness. This paper analyzes the status quo and gaps of the intelligent cloud test platform at home and abroad, and presents the research content and technical solutions of an autonomous and controllable intelligent cloud test platform. First, we make research on the rapid construction technology of large-scale test environment for heterogeneous independent platforms,that is, mirror virtualization and rapid combined deployment technology of software testing tool environment;secondly,we study complex business scenario model generation technologies, including domain analysis and modeling of information systems, formal definition of model-based complex business scenarios and rapid construction technology;finally, we study the automatic generation technology of test cases for complex business scenarios, aiming to make full use of complex business scenario models and full-link historical test data.

Preprocedural Pool Testing Strategy for Dentistry during the COVID-19 Pandemic.

Introduction:Aerosol-generating procedures (AGPs) put the dental health care professionals (DHCPs) at a greater risk for acquiring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In late June 2020, the Centers for Disease Control and Prevention advised elective dental procedures provision to asymptomatic patients while mandating strict infection control protocol and suggested the use of preprocedural testing as an adjunct. A cost-effective method for mass preprocedural testing is pool testing, which has specificity and sensitivity similar to polymerase chain reaction. This article aims to assess the outcomes and utility of incorporating preprocedural testing protocol for SARS-CoV-2 in dental clinics before providing AGPs.Method:The patients who were recommended AGPs where rubber dam placement was not possible were advised to undergo preprocedural testing for SARS-CoV-2. Pool testing strategy was employed, and patients were asked to get tested 48 h before the day of the procedure.Results:Out of a total of 1,000 patients, who presented from June 2020 to late July 2020, 464 were recommended dental procedures. In 194 of 464, AGPs could not be performed under rubber dam isolation; therefore, the patients were advised to get a preprocedural pool test. In total, 111 patients deferred the procedure and testing. Out of 83 who got tested, 7 were positive for SARS-CoV-2, 5 of whom were tested in early June 2020 and 2 in late July 2020.Conclusion:Pool testing within its limitations can be a useful preprocedure test in asymptomatic low-risk patients for AGP in dentistry, especially when the disease prevalence is low or moderate (<10%). It has the potential of reducing testing costs significantly while conserving reagent and other resources. Preprocedure testing, however, also gives rise to certain ethical concerns that also need to be addressed.Knowledge Transfer Statement:The results of this study can be used by clinicians when deciding which preprocedure testing approach they wish to use when performing aerosol-generating procedures in asymptomatic patients with consideration of cost sensitivity and specificity values.

New analytical-modelling method to interpret flexural bending fatigue response of asphalt mixture using the S-VECD theory

ABSTRACT Fully mechanics based solutions are proposed to compute the bending fatigue response of asphalt mixture, based on a combination of the simplified viscoelastic continuum damage (S-VECD) theory, the classical beam theory and numerical modelling. Firstly, an S-VECD-based material constitutive model for ABAQUS is customised and validated against standard uniaxial S-VECD tests. It is able to produce fatigue damage parameters at each cycle with a given strain level. Then, based on the beam theory and strain-dependent fatigue damages at cross-section, new analytical functions are derived to calculate the flexural stiffness and bending moment. For verification, 4PB fatigue tests are conducted at different temperatures, strain levels and rest periods. With the S-VECD constitutive model, 4PB fatigue are also modelled in ABAQUS corresponding to all test conditions. Applying new analytical functions, the resultant flexural stiffness development curves are produced and compared with experimental outcome. The proposed analytical-modelling method demonstrates satisfactory accuracy at predicting flexural stiffness development curves before the initiation of bottom crack, which can also be directly interpreted by the modelling output. The work established a methodology framework for utilization of VECD theory for asphalt's bending fatigue characterization, with potential of reduced testing cost and improved mechanical compatibility.

A Universal Machine-Learning-Based Automated Testing System for Consumer Electronic Products

Consumer electronic manufacturing (CEM) companies face a constant challenge to maintain quality standards during frequent product launches. A manufacturing test verifies product functionality and identifies manufacturing defects. Failure to complete testing can even result in product recalls. In this research, a universal automated testing system has been proposed for CEM companies to streamline their test process in reduced test cost and time. A universal hardware interface is designed for connecting commercial off-the-shelf (COTS) test equipment and unit under test (UUT). A software application, based on machine learning, is developed in LabVIEW. The test site data for around 100 test sites have been collected. The application automatically selects COTS test equipment drivers and interfaces on UUT and test measurements for test sites through a universal hardware interface. Further, it collects real-time test measurement data, performs analysis, generates reports and key performance indicators (KPIs), and provides recommendations using machine learning. It also maintains a database for historical data to improve manufacturing processes. The proposed system can be deployed standalone as well as a replacement for the test department module of enterprise resource planning (ERP) systems providing direct access to test site hardware. Finally, the system is validated through an experimental setup in a CEM company.

Quantitative and specific detection of viable pathogens on a portable microfluidic chip system by combining improved propidium monoazide (PMAxx) and loop-mediated isothermal amplification (LAMP).

An accurate and specific detection of viable Candida albicans (C. albicans) in vaginal discharge is crucial for the diagnosis of vulvovaginal candidiasis (VVC) and assessment of antifungal effects. In this study, improved propidium monoazide (PMAxx) and loop-mediated isothermal amplification (LAMP) were used for the first time to distinguish between viable and dead C. albicans. A portable microfluidic chip system was developed to detect multiple viable pathogens in parallel. The consumption of samples and reagents in per reaction cell were only 0.94 μL, less than 1/25 of the conventional 25 μL Eppendorf tubular test method, both significantly reducing testing cost and greatly simplifying the detection of multiple viable pathogens. The concentration of PMAxx was optimized against C. albicans at 4.0 log CFU mL-1 to 5.0 log CFU mL-1, and 1 μM PMAxx was proven to be suitable for the detection of C. albicans in clinical samples. When testing mixtures containing different ratios of viable to dead C. albicans, PMAxx-LAMP could circumvent the signal arising from dead cells and, therefore, reflected the abundance of viable cells precisely. Furthermore, the suitability of this technique to evaluate the effects of antifungal agents, including clotrimazole, miconazole, and tioconazole, was assessed. Finally, the viability of Escherichia coli (E. coli) and C. albicans were detected on the portable microfluidic chip system. PMAxx-LAMP based portable microfluidic chip system was determined to be a feasible technique for assessing the viability of multiple pathogens in gynecology and might provide insights into new VVC treatment strategies.

Chip test pattern reordering method using adaptive test to reduce cost for testing of ICs

With the continuous drive toward integrated circuits (ICs) scaling, more test patterns are required in testing. However, the large number of patterns continues to increase test time and test costs. Thus, test costs of ICs are becoming more crucial yet more challenging. In this paper, we propose a novel adaptive test strategy to reduce test costs without increasing test escape, and using shortest path first (SPF) algorithm combined with K-Nearest Neighbor (KNN) to reorder the test patterns. The patterns which identify faults earlier are moved forward and applied first so as to save test time. In addition, the optimal test patterns are searched by means of a polynomial regression function and it provides a trade-off between test cost and test escape. Consequently, the optimization problem is converted into a mathematical function, in order to achieve broader applicability and generality. Experimental results demonstrate that the proposed method achieved 54.2 seconds time savings but leads to almost negligible test escapes increasing compared with traditional methods. The test pattern reordering method aims to find defects as early as possible. Furthermore, the proposed algorithm is completely software based and incurs no additional hardware overhead.

Antimicrobial resistance point-of-care testing for gonorrhoea treatment regimens: cost-effectiveness and impact on ceftriaxone use of five hypothetical strategies compared with standard care in England sexual health clinics.

BackgroundWidespread ceftriaxone antimicrobial resistance (AMR) threatens Neisseria gonorrhoeae (NG) treatment, with few alternatives available. AMR point-of-care tests (AMR POCT) may enable alternative treatments, including abandoned regimens, sparing ceftriaxone use. We assessed cost-effectiveness of five hypothetical AMR POCT strategies: A-C included a second antibiotic alongside ceftriaxone; and D and E consisted of a single antibiotic alternative, compared with standard care (SC: ceftriaxone and azithromycin).AimAssess costs and effectiveness of AMR POCT strategies that optimise NG treatment and reduce ceftriaxone use.MethodsThe five AMR POCT treatment strategies were compared using a decision tree model simulating 38,870 NG-diagnosed England sexual health clinic (SHC) attendees; A micro-costing approach, representing cost to the SHC (for 2015/16), was employed. Primary outcomes were: total costs; percentage of patients given optimal treatment (regimens curing NG, without AMR); percentage of patients given non-ceftriaxone optimal treatment; cost-effectiveness (cost per optimal treatment gained).ResultsAll strategies cost more than SC. Strategy B (azithromycin and ciprofloxacin (azithromycin preferred); dual therapy) avoided most suboptimal treatments (n = 48) but cost most to implement (GBP 4,093,844 (EUR 5,474,656)). Strategy D (azithromycin AMR POCT; monotherapy) was most cost-effective for both cost per optimal treatments gained (GBP 414.67 (EUR 554.53)) and per ceftriaxone-sparing treatment (GBP 11.29 (EUR 15.09)) but with treatment failures (n = 34) and suboptimal treatments (n = 706).ConclusionsAMR POCT may enable improved antibiotic stewardship, but require net health system investment. A small reduction in test cost would enable monotherapy AMR POCT strategies to be cost-saving.

An Integrated Decision Approach with Probabilistic Linguistic Information for Test Case Prioritization

This paper focuses on an exciting and essential problem in software companies. The software life cycle includes testing software, which is often time-consuming, and is a critical phase in the software development process. To reduce time spent on testing and to maintain software quality, the idea of a systematic selection of test cases is needed. Attracted by the claim, researchers presented test case prioritization (TCP) by applying the concepts of multi-criteria decision-making (MCDM). However, the literature on TCP suffers from the following issues: (i) difficulty in properly handling uncertainty; (ii) systematic evaluation of criteria by understanding the hesitation of experts; and (iii) rational prioritization of test cases by considering the nature of criteria. Motivated by these issues, an integrated approach is put forward that could circumvent the problem in this paper. The main aim of this research is to develop a decision model with integrated methods for TCP. The core importance of the proposed model is to (i) provide a systematic/methodical decision on TCP with a reduction in testing time and cost; (ii) help software personnel choose an apt test case from the suite for testing software; (iii) reduce human bias by mitigating intervention of personnel in the decision process. To this end, probabilistic linguistic information (PLI) is adopted as the preference structure that could flexibly handle uncertainty by associating occurrence probability to each linguistic term. Furthermore, an attitude-based entropy measure is presented for criteria weight calculation, and finally, the EDAS ranking method is extended to PLI for TCP. An empirical study of TCP in a software company is presented to certify the integrated approach’s effectiveness. The strengths and weaknesses of the introduced approach are conferred by comparing it with the relevant methods.

Prediction Model and Experimental Study on Braking Distance under Emergency Braking with Heavy Load of Escalator

In order to study the relationship between the braking distance and the load of escalator and realize the prediction of the rated load braking distance with a little load, the method of combining theoretical analysis and experimental research is used. First, the dynamic characteristics of the escalator during emergency braking are analyzed, and the prediction model of the braking distance of the escalator under different loads is derived based on the law of conservation of energy. Furthermore, the influence coefficients under different loads were determined through experimental studies, the model was revised, and the concept of equivalent no-load kinetic energy (ENKE) was proposed. The research shows that the braking distance of the escalator increases nonlinearly with the increase in load. When the no-load braking distance and the 25% rated load braking distance change greatly, the braking distance increases faster as the load increases; the escalators with large brake force have a small ENKE and are easy to stop. Otherwise, it is difficult to stop. The test results show that the comparison between the predicted value of the prediction model and the measured value has a maximum error of 2.7%, and the maximum error at rated load is only 2.0%, which fully meets the needs of engineering measurement. And the prediction method reduces test costs, enhances test security, and improves test coverage.

Sample Multiplexing: Increased Throughput for Quantification of Total Testosterone in Serum by Liquid Chromatography-Tandem Mass Spectrometry.

For high-volume assays, optimizing throughput reduces test cost and turn-around time. One approach for liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays is sample multiplexing, wherein the analyte of interest is derivatized in different specimens with reagents of different molecular weight (differential mass tagging). Specimens can then be combined and simultaneously analyzed within a single injection to improve throughput. Here we developed and validated a quantitative, sample-multiplexed LC-MS/MS assay for serum total testosterone (TT) based on this approach. For the sample-multiplexed assay, calibrators, controls, and patient specimens were first extracted separately. After mass tagging with either methoxyamine or hydroxylamine, they were combined and injected into the LC-MS/MS system. To evaluate assay performance, we determined limit of quantification (LOQ), linearity, recovery, and imprecision. A method-comparison study was also performed, comparing the new assay with the standard LC-MS/MS assay in 1574 patient specimens. The method was linear from 2.5 to 2000 ng/dL, with accuracies from 93% to 104% for both derivatives. An LOQ of 1.0 ng/dL was achieved. Intra-assay and total CVs across 4 quality control concentrations were less than 10%. The assay demonstrated good agreement (Deming regression, 1.03x + 6.07) with the standard LC-MS/MS assay for the patient specimens tested (TT, 3 to 4862 ng/dL). Sample multiplexing by differential mass tagging of TT increases LC-MS/MS throughput 2-fold without compromising analytical accuracy and sensitivity.

Service reliability of a heavy-haul wagon coupler body based on the SMOTE-Bootstrap-Bayes method

To obtain structural service reliability for a small sample of failure data, a reliability analysis method for a small sample of failure data based on the SMOTE (Synthetic Minority Oversampling Technique) algorithm, Bootstrap method, Bayesian estimation and hypothetical distribution check was proposed, and the feasibility of the method was verified. Taking the coupler body of a heavy-haul wagon as the research object, first, the fatigue bench test was carried out, and a small sample of the fatigue failure data for the coupler body under the given load spectrum was obtained. Then, the reliability analysis method for a small sample of failure data was used to analyze the coupler body failure data, and the curve of the coupler body reliability with failure mileage was finally obtained. The results show that the accuracy of the reliability curve based on the small sample analysis method is significantly higher than that based on sample size expansion and the empirical reliability of a small sample derived from random sampling based on an average rank calculation. When the reliability is 50%, the service mileage of the coupler body is approximately 2.08 million km; when the reliability is 95%, the service mileage is approximately 1.38 million km; and when the reliability is 99%, the service mileage is approximately 1.15 million km. The service reliability analysis method for a coupler body of a heavy-haul wagon based on the SMOTE-Bootstrap-Bayesian estimation has important theoretical and application value for improving the utilization rate of test data, reducing test costs and effectively evaluating the fatigue life of coupler bodies.

Fine-grained Adaptive Testing Based on Quality Prediction

The ever-increasing complexity of integrated circuits inevitably leads to high test cost. Adaptive testing provides an effective solution for test-cost reduction; this testing framework selects the important test items for each set of chips. However, adaptive testing methods designed for digital circuits are coarse-grained, and they are targeted only at systematic defects. To incorporate fabrication variations and random defects in the testing framework, we propose a fine-grained adaptive testing method based on machine learning. We use the parametric test results from the previous stages of test to train a quality-prediction model for use in subsequent test stages. Next, we partition a given lot of chips into two groups based on their predicted quality. A test-selection method based on statistical learning is applied to the chips with high predicted quality. An ad hoc test-selection method is proposed and applied to the chips with low predicted quality. Experimental results using a large number of fabricated chips and the associated test data show that to achieve the same defect level as in prior work on adaptive testing, the fine-grained adaptive testing method reduces test cost by 90% for low-quality chips and up to 7% for all the chips in a lot.

Theoretical and Empirical Analyses of the Effectiveness of Metamorphic Relation Composition

Metamorphic Relations (MRs) play a key role in determining the fault detection capability of Metamorphic Testing (MT). As human judgement is required for MR identification, systematic MR generation has long been an important research area in MT. Additionally, due to the extra program executions required for follow-up test cases, some concerns have been raised about MT cost-effectiveness. Consequently, the reduction in testing costs associated with MT has become another important issue to be addressed. MR composition can address both of these problems. This technique can automatically generate new MRs by composing existing ones, thereby reducing the number of follow-up test cases. Despite this advantage, previous studies on MR composition have empirically shown that some composite MRs have lower fault detection capability than their corresponding component MRs. To investigate this issue, we performed theoretical and empirical analyses to identify what characteristics component MRs should possess so that their corresponding composite MR has at least the same fault detection capability as the component MRs do. We have also derived a convenient, but effective guideline so that the fault detection capability of MT will most likely not be reduced after composition.

Investigation for the Effects of Newly Designed Hip Prosthesis on Crack Propagation Using Probabilistic Methodology

In orthopedic prosthesis design, finite element method is one of the commonly used mathematical methods for performing structural analyzes and reducing test costs before it is applied to the patient. Surgeons and engineers should work together to design reliable durable and hip replacement. Desirable functional requirements for prosthesis design include high fatigue life, small relative displacement between the prosthesis-cement interface, and reduced stress on the bone and prosthesis. For this purpose, the progression of the fracture was calculated by applying the scenario of the presence of crack in the bone cement of the designed prosthesis using optimization methodology. The same conditions were analyzed in commercially available Charnley type prosthesis and the results were compared. When the obtained results are examined, it is seen that the newly designed prosthesis is more effective than the Charnley type prosthesis.

Community Vs. hospital HIV testing sites in Jerusalem, Israel - who\u2019s tested and who\u2019s at risk?

BackgroundAfter decades of constant increase in HIV diagnoses among men who have sex with men (MSM), a gradual decrease has been reported in recent years. Timely detection of HIV leads to early treatment and behavioral changes which decrease further transmissions. This cross-sectional study aimed to assess demographic and behavioral characteristics of individuals who were tested for HIV in Jerusalem, Israel.MethodsThis study compared individuals who were tested at Hadassah AIDS Center (HAC) with those tested at the Jerusalem Open House (JOH) - an LGBTQ community center. Participants completed anonymous questionnaires regarding their demographic, HIV-testing history, and sexual behaviors. High-risk sexual behavior (HRSB) was defined as a diagnosis of sexually transmitted disease or condomless anal/vaginal sex during the last year.ResultsAmong 863 participants, 104 (12.1%) were tested in HAC and 759 (87.9%) in JOH. Of those, 19 (18.3%) and 227 (29.9%) were HRSB, respectively. Two MSM were tested positive in JOH. JOH received more MSM, HRSB and individuals who were previously tested for HIV, while HAC received more migrants and health-care workers. HRSB-participants were more commonly younger, males, non-Jewish, with lower income, previously tested for HIV, reported more sexual partners, payed for sex or used drugs.ConclusionsMSM and HRSB-individuals were more likely to be tested in JOH, while migrants and health-care workers in HAC, possibly due to the geographic location, reputation and specific atmosphere. In order to encourage HIV-tests among HRSB and non-Jews, additional interventions should be employed, including outreach activities, extending opening hours and reducing testing costs should be employed.

Black-Box Test-Cost Reduction Based on Bayesian Network Models

The growing complexity of circuit boards makes manufacturing test increasingly expensive. In order to reduce test cost, a number of test selection methods have been proposed in the literature. However, only few of these methods can be applied to black-box test-cost reduction. In this article, we propose a novel black-box test selection method based on Bayesian networks (BNs), which extract the strong relationship among tests. First, the problem of reducing the black-box test cost is formulated as a constrained optimization problem. Next, multiple structure learning and transfer learning algorithms are implemented to construct BN models. Based on these BN models, we propose an iterative test selection method with a new metric, Bayesian index, for test-cost reduction. In addition, averaging strategies are applied to enhance the reduction performance. Finally, a robust model selection framework is proposed to select the optimal BN model for test-cost reduction. Two case studies with production test data demonstrate that when no prior information is provided, our proposed approach effectively reduces the test cost by up to 14.7%, compared to the state-of-the-art greedy algorithm. Moreover, our proposed approach further reduces the test cost by up to 7.1% when prior information is provided from similar products.

A Hybrid Cloud Testing System Based on Virtual Machines and Networks

Traditional software testing typically uses many physical resources to manually build various test environments, resulting in high resource costs and long test time due to limited resources, especially for small enterprises. Cloud computing can provide sufficient low-cost virtual resources to alleviate these problems through the virtualization of physical resources. However, the provision of various test environments and services for implementing software testing rapidly and conveniently based on cloud computing is challenging. This paper proposes a multilayer cloud testing model based on cloud computing and implements a hybrid cloud testing system based on virtual machines (VMs) and networks. This system realizes the automatic and rapid creation of test environments and the remote use of test tools and test services. We conduct experiments on this system and evaluate its applicability in terms of the VM provision time, VM performance and virtual network performance. The experimental results demonstrate that the performance of the VMs and virtual networks is satisfactory and that this system can improve the test efficiency and reduce test costs through rapid virtual resource provision and convenient test services.