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U ovom radu obrađena je tematika testiranja softvera. Opisano je što je softver, proces razvoja softvera, i značaj kvalitete softvera. Predstavljeno je nekoliko metoda testiranja softvera s naglaskom na metodu testiranja ortogonalnim nizovima. Opisano je što su ortogonalni nizovi, neka njihova svojstva i proces testiranja ortogonalnih nizovima. Uz rad izrađena je i aplikacija za testiranje softvera s malim brojem ulaznih parametara. This thesis covers the area of software testing. It describes software in general, the process of developing software, and the importance of software quality. Several methods of software testing are covered, with emphasis on the orthogonal array testing method. The concept of orthogonal arrays is described, as well as some of their properties and the process of orthogonal array testing. Also, an application for testing software with a small number of input parameters is developed.

The building envelope considerably influences building energy consumption. To enhance the energy efficiency of buildings, this paper proposes an approach to predict building energy consumption based on the design of the building envelope. The design parameters of the building envelope include the comprehensive heat transfer coefficient and solar radiation absorption coefficient of exterior walls, comprehensive heat transfer coefficient and solar radiation absorption coefficient of the roof, comprehensive heat transfer coefficient of outer windows, and window-wall ratio. The approach is applied to optimize the design parameters of the building envelope structure of a university teaching building in northern China. First, a building information model of a teaching building is established in Revit and imported into DesignBuilder energy consumption analysis software. Subsequently, a data set of the abovementioned 6 parameters is obtained by performing orthogonal testing and energy consumption simulations. On this basis, an RF model is used to predict building energy consumption and rank the importance of each parameter, and the Pearson function is used to evaluate the corresponding correlations. The results show that the most important parameters with the highest correlations to building energy consumption are the comprehensive heat transfer coefficients of the exterior walls and outer windows and the window-wall ratio. Finally, the RF prediction results are compared to the prediction results of a BP artificial neural network (BP-ANN) and support vector machine (SVM). The findings indicate that the RF model exhibits notable advantages in building energy consumption prediction and is the optimal prediction model among the compared models. Published version This work was supported by the Zhongnan Hospital of Wuhan University Science, Technology and Innovation Seed Fund, Project CXPY2020013, the Construction of Science and Technology Plan Project of Hubei Province (Grant No. 202041), and the National Natural Science Foundation of China (Grant No. 72031009).

Though gravel cushions are used worldwide in open-pit mines and railway slopes to control the impact of rolling stones, no universal technical standards have been put in place to guide engineers in their correct design, and few laboratory test results are available with which to characterize collisions between rolling stones and a gravel cushion. We carried out a large number of experiments in which rolling stones made of the same material but differently shaped were dropped from various heights onto cushions with various particle sizes and thicknesses. We investigated the characteristics of the resulting collisions, and the relationships between coefficients of restitution (CORs) of blocks with different shape and release height H, cushion thickness h and particle diameter d are obtained through linear fitting method. Orthogonal testing reveals the relative influence of block shape, release height, and the particle size and thickness of the cushion on the collision characteristics, which can assist engineers in designing a gravel cushion suitable to the distribution and weathering characteristics of rolling stones in a specific area.

Objectives Serologic testing for SARS-CoV-2 is an important element in the fight to slow the COVID-19 pandemic. This study aimed to validate two serologic tests for total (IgM, IgG, IgA) SARS-CoV-2 antibodies, (i) the Ortho-Clinical Diagnostics Anti-SARS-CoV-2 Total Antibody assay for the Vitros 5600 analyzers and (ii) a manual laboratory developed ELISA (FDA EUA pending), for use in parallel orthogonal testing of asymptomatic healthcare workers and affiliates of the University of Maryland Medical System. Design and Methods Validation and verification of the two tests was performed using samples from hospitalized patients that were found to be PCR positive for SARS-CoV-2, samples pre-COVID-19, and samples from individuals with current/previous infections with other viruses. Healthcare workers and affiliates from across the University of Maryland Health System were provided testing free of charge and their results were reported as reactive or non-reactive if the two tests were concordance, or indeterminate if the results were discordant. Results Validation testing found the Ortho Vitros test to be 100% (73/73) sensitive, and 99.3% (152/153) specific, while the UMMC ELISA was found to be 97.6% (204/209) sensitive and 100% (288/288) specific. Real world testing among 8399 healthcare workers found that 2.9% (247/8399) of healthcare workers were positive for anti- SARS-CoV-2 antibodies by both tests. An indeterminate rate of 1.1% (91/8399), in which one test reported reactive results, and one as non-reactive was also seen. Conclusions Parallel orthogonal testing improves the positive and negative predictive value of serologic testing in populations with low prevalence. The use of an indeterminate result from parallel orthogonal testing allows for the follow-up and re-testing, which helps resolve discrepancies between assays.

To determine the influences of the main structural parameters on open-design vortex pump performance, optimize the vortex pump performance, and reduce the running vibration and improve stability, orthogonal testing method was introduced in this paper. The selected main factors included impeller outer diameter (D2), impeller outlet width (b2), outlet setting angle of impeller (β2), and inlet setting angle of impeller (β1), and the nine types of impellers were coded according to orthogonal table. After obtaining the preliminarily optimum value range for each factor through range analysis, comprehensive analysis was employed based on the orthogonal test to investigate the main factors and identify the primary and secondary influencing factors affecting the performance of the vortex pump. An optimization scheme was obtained for further design. The results show that the numerical calculation results of the optimization scheme pump are in good agreement with the test results, and it shows the feasibility of the numerical calculation method. The testing results showed that efficiency and head of the optimal model were 4.2% and 9 m higher than those of the prototype model, respectively. Improved efficiency and head met the design requirements. The orthogonal testing method proved the feasibility of performance optimization of the vortex pump. The backflow occurs at the pump entrance and rotates in the same direction with impeller. It moves along the pipe wall from the lateral cavity to the inlet and encourters with the approaching flow.

HighlightsA discrete element simulation model was used to improve the performance of a corn silage crushing and throwing device.Feed rate, crushing speed, and dial speed were used as the test factors, and the average cutting force and average energy loss were used as the evaluation indexes in orthogonal testing.The order of significance of the factors was crushing speed > feed rate > dial speed for average cutting force and crushing speed > dial speed > feed rate for average energy loss.Abstract. To improve the performance of a corn silage crushing and throwing device and address the problems of low crushing quality and high power consumption, a discrete element simulation model of a corn silage crushing and throwing device and granular straw was established based on discrete element theory using EDEM, a general-purpose CAE software program designed with modern discrete element model technology to simulate and analyze particle processing and production operations. The average cutting force and average energy loss of the particles were the evaluation indexes, and the influence of feed rate, crushing speed, and dial speed on the evaluation indexes was analyzed using single-factor simulation tests. The order of significance was crushing speed > feed rate > dial speed for the average cutting force and crushing speed > dial speed > feed rate for the average energy loss. Using multi-objective optimization, the optimal combination of feed rate, crushing speed, and dial speed was 3.52 kg s-1, 892.06 rpm, and 1502 rpm, respectively. With the optimal parameters, the average cutting force was 58.20 N and the average energy loss was 0.85 J. To verify the feasibility of the EDEM simulation, field tests were conducted using a trial-produced device, with the acceptability of straw crushing and power consumption as the test indicators. During the field tests, the feed rate, crushing speed, and dial speed were set to 3.52 kg s-1, 890 rpm, and 1500 rpm, respectively. The field tests showed that the acceptability of straw crushing and the power consumption were 93.60% and 6.73 kW·h, respectively, with the optimal parameters, which satisfied the corn silage crushing standard and provides a theoretical and scientific basis for the design and optimization of the device. Keywords: Corn silage, Crushing and throwing device, Discrete element simulation, Motion simulation, Multi-objective optimization method.

Increased wind power penetration and induction loads have deteriorated the voltage stability performance of the power system. This study proposes a multi-stage multi-objective dynamic VAR source placement method for wind energy power system, where three sub-objectives are optimised simultaneously: (i) investment cost and operational control cost; (ii) steady-state voltage stability index; (iii) short-term voltage stability index. This method coordinates the dynamic VAR allocation decisions with preventive and corrective stability controls, including wind power curtailment, modification of the line drop compensation, and load shedding, to improve both steady-state and short-term voltage stability of the system. A robust parameter design technique called Taguchi's Orthogonal Array Testing is used to model the wind power uncertainty. Pareto optimal solutions are obtained for flexible decision-making. The computation burden is mitigated by candidate buses selection and critical contingency identification. The proposed model is demonstrated on the New England 39-bus test system using PSS®E. Compared with conventional approaches, it can achieve higher voltage stability level with less overall cost and moderate wind power curtailment, and at the same time avoid the conservativeness of planning decisions.

Retrofitting existing buildings to be a nearly zero energy building (nZEB) is an effective solution for greenhouse gas emissions and primary energy consumption reduction. A hybrid approach that integrates the building energy simulation method and orthogonal array testing (OAT) to renovate buildings to nZEB is proposed in this paper. Within a residential building in Changchun, Jilin of China, the total energy consumption index (TECI) and CO2 emission factor for heating are used as evaluation criteria. The reliability of the building energy model is validated and adopted to forecast the energy performance of different building renovation strategies. According to OAT, four passive measures can be ranked by their influence on TECI in descending order as follows: external wall heat transfer coefficient, airtightness, window heat transfer coefficient, and roof heat transfer coefficient. The optimal renovation solution of the studied building can reduce the TECI by 43.18% by only reducing the external wall heat transfer coefficient from 0.5 to 0.2 W/m2·K and the infiltration N50 from 3.6 to 0.4 ac/h. Besides, combined heat and power (CHP) utilities emit less CO2 than heat pumps in providing heating under the current CO2 emission factor of the power grid in China, making it impossible to give up district heating systems until carbon emissions of electricity generation have declined significantly. The results can provide a reference for the application of the nZEB standard in actual retrofitting projects.

BackgroundQuick, cheap and accurate point-of-care testing is urgently needed to enable frequent, large-scale testing to contain COVID-19. Lateral flow tests for antigen and antibody detection are an obvious candidate for use in community-wide testing, because they are quick and cheap relative to lab-processed tests. However, their low accuracy has limited their adoption. We develop a new methodology to increase the diagnostic accuracy of a combination of cheap, quick and inaccurate index tests with correlated or discordant outcomes, and illustrate its performance on commercially available lateral flow immunoassays (LFIAs) for Sars-CoV-2 antibody detection.Methods and FindingsWe analyze laboratory test outcomes of 300 serum samples from health care workers detected with PCR-confirmed SARS-Cov-2 infection at least 21 days prior to sample collection, and 500 pre-pandemic serum samples, from a national seroprevalence survey, tested using eight LFIAs (Abbott, Biosure/Mologic, Orientgene-Menarini, Fortress, Biopanda I, Biopanda II, SureScreen and Wondfo) and Hybrid DABA as reference test. For each of 14 two-test combinations (e.g., Abbott, Fortress) and 16 three-test combinations (e.g., Abbott, Fortress, Biosure/Mologic) used on at least 100 positive and 100 negative samples, we classify an outcome sequence – e.g., (+,–) for (Abbott, Fortress) – as positive if its combination positive predictive value (CPPV) exceeds a given threshold, set between 0 and 1. Our main outcome measures are the sensitivity and specificity of different classification rules for classifying the outcomes of a combination test. We define testing possibility frontiers which represent sensitivity and false positive rates for different thresholds. The envelope of frontiers further enables test selection.The eight index tests individually meet neither the UK Medicines and Healthcare Products Regulatory Agency’s 98% sensitivity and 98% specificity criterion, nor the US Center for Disease Control’s 99.5% specificity criterion. Among these eight tests, the highest single-test LFIA specificity is 99.4% (with a sensitivity of 65.2%) and the highest single-test LFIA sensitivity is 93.4% (with a specificity of 97.4%). Using our methodology, a two-test combination meets the UK Medicines and Healthcare Products Regulatory Agency’s criterion, achieving sensitivity of 98.4% and specificity of 98.0%. While two-test combinations meeting the US Center for Disease Control’s 99.5% specificity criterion have sensitivity below 83.6%, a three-test combination delivers a specificity of 99.6% and a sensitivity of 95.8%.ConclusionsCurrent CDC guidelines suggest combining tests, noting that “performance of orthogonal testing algorithms has not been systematically evaluated” and highlighting discordant outcomes. Our methodology combines available LFIAs to meet desired accuracy criteria, by identifying testing possibility frontiers which encompass benchmarks, enabling cost savings. Our methodology applies equally to antigen testing and can greatly expand testing capacity through combining less accurate tests, especially for use cases needing quick, accurate tests, e.g., entry to public spaces such as airports, nursing homes or hospitals.

The performance of Styrene-butadiene-styrene (SBS) modified asphalt is closely related to the content of SBS modifier. In the production process of modified asphalt, a certain amount of additive such as sulfur and rubber oil may be added to reduce the segregation and promote the swelling of the polymer, but the effect of these additives on determining SBS content in asphalt is not yet clear. This paper presents the calibration curves of SBS content based on rutting factor and creep slope and points out its defects according to the temperature scanning test and the bending beam rheometer test. Subsequently, using Fourier transform infrared spectroscopy (FTIR) for rapid determination of polymer content in SBS modified asphalt based on orthogonal test and then the effects of additives such as asphalt type, SBS content, rubber oil and sulfur on the accuracy of polymer content determination by FTIR were investigated. Moreover, in the orthogonal tests of adding sulfur and rubber oil, the multivariate analysis of variance (MANOVA) was firstly used to analyze the additives influence on the test accuracy of FITR. Results indicated that the influencing degree of different additives is different. The influence of sulfur on the determination accuracy is greater than that of rubber oil. Therefore, the rapid determination method needs further improvement.

The thermal state of iron ore pellets during traveling-grate processes is complex, and sintering is a complex coupling process involving multiple physical factors. In this study, the temperature distribution during updraught drying (UDD) is investigated using computational fluid dynamics (CFD) and orthogonal testing. Based on the calculated temperature profiles and temperature increase at different positions, the temperature distribution for industrial parameters is presented. Moreover, multifactor analysis is then applied using four-factor three-level orthogonal tests to understand the influence of each factor on the pellet bed temperature. The results indicate that the temperature of the inlet gas has the greatest influence on the pellet bed, followed by the height of the pellet bed, consistent with the experimental results. The proposed computational framework could also be used to evaluate and design the thermodynamic parameters of traveling-grate processes.

The quantification of cannabinoids is an essential part of cannabis profiling and testing, whether for medical or recreational use. As regulatory bodies continue to increase testing requirements for these products, it is crucial that alternative and effective analytical methods be developed. Herein, we describe the use of benchtop NMR instruments for the quantification of Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) in a variety of cannabis concentrates and compare the values to those obtained using HPLC, the most common approach for the quantification of cannabinoids. Based on the discrepancies observed in test values from different laboratories using only HPLC, the value of orthogonal testing methods has been identified and is increasingly desired.

Disposable blood collection needles become severely intertwined and hooked during stacking, and thus individually feeding disposable blood collection needles during mechanical packaging is difficult. Based on the physical characteristics of the blood collection needles during the stacking state, this study designed an automatic tidying and sorting mechanism by combining compound vibration, sorting, and conveying. During the feeding process, the compound vibration-type material-tidying mechanism tidies 20‒30 blood collection needles first; then, the material sorting and conveying mechanism transports the tidied blood collection needles individually. The orthogonal testing of the automatic material tidying process shows that various experimental factors are ranked by the significance level of the effect on the tidying process and the significance ranking is as follows: vertical vibration frequency > horizontal amplitude > vertical amplitude > horizontal vibration frequency. Experiments were performed after analyzing the optimal combination. The results demonstrate that when the horizontal vibration frequency is 1.7 Hz, the horizontal amplitude is 150 mm, vertical vibration frequency is 1.3 Hz, vertical amplitude is 30 mm, and material length after tidying is 265 mm. The automatic sorting and conveying experiment shows the effect of various experimental factors on the feed rate of the material, where the significance level of the effect is ranked as follows: vibration frequency > material quantity > channel dip angle. The experimental results show that when the number of materials is 25, the channel dip angle is 12°, and vibration frequency is 52.5 Hz. The material delivery efficiency reaches 0.51 s/root, meeting the requirement of five channels for 80000 root/day feeding efficiency. The study can provide reference for the realization of automatic feeding of large aspect ratio flexible materials in similar stacking state.

PurposeThis paper aims to prepare an associative thickener base on two polyacrylate-based copolymers, which can be used for digital printing of nylon carpet with enhanced performance.Design/methodology/approachAn associative thickener was prepared by compounding two polyacrylate-based copolymers, cationic starch and polyacrylic acid; and mediated by polyethylene glycol and polyacrylamide crosslinker. The formulation of the associative thickener was optimized by using the orthogonal array testing strategy. The stability of the associative thickener was investigated by measuring effects of temperature, electrolytes, storage time and auxiliaries on viscosity. The associative thickener was compared with a commercial thickener by evaluating their performance in digital printing of nylon carpet.FindingsThe associative thickener provided same color strength and fastness in the printing of nylon carpet as the commercial one, but was more easily washed off for a better hand feeling of the printed carpet.Practical implicationsThe prepared associative thickener can be applied for digital printing of nylon carpet.Originality/valueThe associative thickener can be facilely prepared from commercially available chemicals and suitable for digital printing of nylon carpet.

Voltage/VAR regulation (VVR) implemented by capacitor banks (CBs), on-load tap changers (OLTCs), and photovoltaic (PV)-associated inverters is effective to enhance voltage stability and reduce power loss. On the other hand, conservation voltage reduction (CVR) has been widely adopted in distribution networks to reduce load demand. Existing works mainly focus on each of them. This paper proposes a VVR method with CVR, forming a multi-objective optimisation problem which minimises (i) voltage collapse proximity indicator (VCPI), (ii) load demand, and (iii) power loss. Besides, PV power generation as uncertainty significantly impairs the VVR results. To deal with the uncertainty issue, this paper proposes a rolling-horizon framework to determine VVR and applies Taguchi's orthogonal array testing (TOAT) to model the uncertain PV power generation, achieving rolling-horizon-based multi-objective robust VVR. The proposed model is tested and demonstrated on the IEEE 33-bus and 69-bus systems, and simulation results verify that the proposed method can support robust solutions of the multi-objective VVR problem for decision-making.

The quality of compaction of unbound aggregate materials with permeable gradation plays a vital role in their field performance, however, there are currently few unanimously accepted techniques or quality control criteria available for ensuring adequate compaction of such materials in either laboratory or field applications. This paper presented testing results of a laboratory gyratory compaction study where the combinations of gyratory parameters were properly designed using the orthogonal array theory. Innovative real-time particle motion sensors were employed to record particle movement characteristics during the compaction process and provide a meso-scale explanation about compaction mechanisms. Particle abrasion and breakage were also quantified from particle shape digitized from the three-dimensional (3D) laser scanner before and after compaction. The optimal combination of gyratory parameters that yields the best compaction performance was determined from the orthogonal testing results with the relative importance of major influencing parameters ranked accordingly. Meso-scale particle movement at the upper center and center side positions of the specimen are promising indicators of compaction quality. The gyratory compaction process can be consistently divided into three distinct stages according to both macro-scale performance indicators and meso-scale particle movement characteristics. A statistically significant bi-linear relationship was found to exist between relative breakage index and maximum abrasion depth, whereas the quality of compaction and the extent of particle breakage appear to be positively correlated, thus necessitating the cost-effective balance between them. The results of this study could provide technical insights and guidance to field compaction of unbound permeable aggregates.

Marine centrifugal pumps are mostly used on board ship, for transferring liquid from one point to another. Based on the combination of orthogonal testing and numerical simulation, this paper optimizes the structure of a drainage trough for a typical low-specific speed centrifugal pump, determines the priority of the various geometric factors of the drainage trough on the pump performance, and obtains the optimal impeller drainage trough scheme. The influence of drainage tank structure on the internal flow of a low-specific speed centrifugal pump is also analyzed. First, based on the experimental validation of the initial model, it is determined that the numerical simulation method used in this paper is highly accurate in predicting the performance of low-specific speed centrifugal pumps. Secondly, based on the three factors and four levels of the impeller drainage trough in the orthogonal test, the orthogonal test plan is determined and the orthogonal test results are analyzed. This work found that slit diameter and slit width have a large impact on the performance of low-specific speed centrifugal pumps, while long and short vane lap lengths have less impact. Finally, we compared the internal flow distribution between the initial model and the optimized model, and found that the slit structure could effectively reduce the pressure difference between the suction side and the pressure side of the blade. By weakening the large-scale vortex in the flow path and reducing the hydraulic losses, the drainage trough impellers obtained based on orthogonal tests can significantly improve the hydraulic efficiency of low-specific speed centrifugal pumps.

Background Serological tests are widely used in various medical disciplines for diagnostic and monitoring purposes. Unfortunately, the sensitivity and specificity of test systems is often poor, leaving room for false positive and false negative results. However, conventional methods used to increase specificity decrease sensitivity and vice versa. Using SARS-CoV-2 serology as an example, we propose here a novel testing strategy: the "Sensitivity Improved Two-Test" or "SIT2" algorithm. Methods SIT2 involves confirmatory re-testing of samples with results falling in a predefined retesting-zone of an initial screening test, with adjusted cut-offs to increase sensitivity. We verified and compared the performance of SIT2 to single tests and orthogonal testing (OTA) in an Austrian cohort (1,117 negative, 64 post-COVID positive samples) and validated the algorithm in an independent British cohort (976 negatives, 536 positives). Results The specificity of SIT2 was superior to single tests and non-inferior to OTA. The sensitivity was maintained or even improved using SIT2 when compared to single tests or OTA. SIT2 allowed correct identification of infected individuals even when a live virus neutralization assay could not detect antibodies. Compared to single testing or OTA, SIT2 significantly reduced total test errors to 0.46% (0.24-0.65) or 1.60% (0.94-2.38) at both 5% or 20% seroprevalence. Conclusion For SARS-CoV-2 serology, SIT2 proved to be the best diagnostic choice at both 5% and 20% seroprevalence in all tested scenarios. It is an easy to apply algorithm and can potentially be helpful for the serology of other infectious diseases.

Uniaxial compressive strength (UCS) and peak strain (PS) are essential indices for studying the mechanical properties of coal and rock masses, and they are closely related to mechanical parameters such as the elastic modulus (E), Poisson’s ratio (υ), cohesion (C) and internal friction angle (Φ) of coal and rock masses. This study took the No. 2-1 coal seam of Zhaogu No. 2 Mine, in Henan Province, China, as the research object. An RMT-150B servo testing machine was used to test all mechanical parameters, including the E, υ, C and Φ of coal and rock masses. Based on the principle of orthogonal testing, Three Dimensions Fast Lagrangian Analysis of Continua (FLAC3D) was used to select E, υ, C, Φ, tensile strength (Rm) and dilation angle (Ψ) as initial participation factors. Using these six parameters and a five-level combination scheme (L25 (56)), the influence of coal mechanical parameters on UCS and PS was investigated, using the software SPSS for stepwise regression analysis, and a uniaxial pressure-resistant regression prediction equation was established. The research showed that, under uniaxial compression conditions, the main parameters controlling UCS of coal masses are C and Φ; conversely, the main parameters controlling PS are E and C. UCS and PS exhibit significant linear relationships with these main controlling parameters. Here, a stepwise regression prediction equation was established through reliability verification analysis using the main controlling parameters. This prediction method produces very small errors and a good degree of fit, thus allowing the rapid prediction of UCS. The precision of the stepwise regression model depends on the number of test samples, which can be increased in the later stages of a design project to further improve the precision of the projection model.

With the rapid development of modern agriculture facilities, agricultural fans have been widely used due to their low pressure and large airflow characteristics. However, existing agricultural fans have large flow losses and low energy efficiencies. To increase the airflow and energy efficiency of these fans, optimization designs based on skewed and swept blades were carried out. First, a “DDZ” agricultural fan (a leaf model agricultural fan commonly used in China) was chosen as the archetype fan. Its performance curves and flow field distribution were obtained by performance testing and numerical simulation. Second, the stack lines of the skewed blade and swept blade were designed based on the original blade, 3 skewed blade parameters (skewed angle a, x direction control parameter kx, and y direction control parameter ky), and 3 swept blade design parameters (swept angle ß, z direction control parameter kz, and r direction control parameter kr). Finally, the optimal skewed blade design parameters (a = 16.8°, kx = 1.65, and ky = 0.5) and optimal swept blade design parameters (ß = 10.6°, kz = -0.33, and kr =0.6) were obtained using numerical simulations and orthogonal testing, which is a response surface method. The numerical simulation results showed that the airflow and energy efficiency ratios of the optimal skewed blade fan were increased by 4.3% and 20.5%, and those of the optimal swept blade fan were increased by 4.5% and 15.4%, respectively, in comparison with those of the original fan. The flow fields showed that the optimal skewed blade mainly reduced the radial flow at the blade root and the leakage flow. The optimal swept blade mainly reduced the leakage flow by changing the distribution of the static pressure on the blade surfaces. Keywords: Agricultural fan, Skewed-Swept blade, Numerical simulation, Optimization.

Combinatorial testing can test software that has various configurations for multiple parameters efficiently. This method is based on a set of test cases that guarantee a certain level of interaction among parameters. Mixed covering array (MCA) can be used to represent a test-suite. Each row of the array corresponds to a test case. In general, a smaller size of MCA does not necessarily imply less testing time. There are certain combinations of parameter values which would take much longer time than other cases. Based on this observation, it is more valuable to construct MCAs that are better in terms of testing effort characterization other than size. We present a method to find cost-aware MCAs. The method contains two steps. First, simulated annealing algorithm is used to get an MCA with a small size. Then we propose a novel nested differential evolution algorithm to improve the solution with its testing effort. The experimental results indicate that our method succeeds in constructing cost-aware MCAs for real-world applications. The testing effort is significantly reduced compared with representative state-of-the-art algorithms.

Deacidification plays an important role in the conservation of paper-based cultural heritage objects. Herein, a novel approach for the conservation of scale paper-based cultural heritage objects is proposed using a mixture of argon and ethylene oxide (EO-Ar) for the first time. The optimum process conditions for deacidification of ethylene oxide and argon mixture system are determined by orthogonal testing. To evaluate the stabilization effect of paper treated with EO-Ar, the degradation of the mechanical properties (tensile strength, folding endurance and tearing strength tests) of paper after artificial aging was evaluated. The results show that the treated paper had better durability with respect to tensile strength, folding endurance and tearing strength. Additionally, thermal stability, crystallinity and fiber wall thickness increased after EO-Ar treated, which was determined by scanning electron microscope (SEM), diffraction of X-rays (XRD), and thermo gravimetric (TG) analysis. Some compounds, such as polyethylene glycol, organic acids, esters, were detected by GC-MS after treatment with EO-Ar. Two hundred and forty books including acidic, weak acidic and alkaline books were successfully deacidified, resulting in pH values of paper ranges suitable for paper preservation. Finally, a possible mechanism of deacidification of EO-Ar was proposed.

Background/Objectives: This research paper presents how Genetic algorithm is efficiently used in random test case generation during functional software testing. Methods/Statistical Analysis: Different hybridized Genetic Algorithms are used to generate test data automatically and optimized those test cases to solve many complex problem related to software testing. Findings: Genetic Algorithms are successfully used in software testing with increasing number of test case generation and provides a means of an automatic test case generator. Applications/Improvements: This study gives us a brief idea to implement Genetic Algorithms in software testing for optimum results and also it can be used with the neural networks and fuzzy systems for different types of testing to improve the performance.

Objective: An electronic system developed for specific application with the integration of hardware and software is known as Embedded System. Due to complexity of hardware and software in a single system, it requires specific technique for testing before deployment of the device. This paper proposes the comparative study of testing techniques of embedded system. Methods/Analysis: In this paper, a test methodology of embedded system using PCBA has been proposed, that covers all the testing aspects of the embedded system from electrical board level hardware to the embedded system software. Three tests namely power rail test, interconnect test and the infrastructure tests are used for hardware functionality for stuck at and bridging faults. The functionality test has been used for programming validation using port interface. Findings: This paper proposed automatic testing of embedded board, which reduces manual errors, increases test coverage and reduces the test time in the production line. The proposed method showed that it can be applied to any board in any form with the same test hardware barring the input-output cables. The software in host machine has been used for testing purpose of different boards. This testing technique is useful for embedded systems implemented in control systems.

Static testing is used to detect software defects in the earlier phases of the software development lifecycle, which makes the total costs caused by defects lower and the software development project less risky. Different types of static testing have been introduced and are used in software projects. In this paper, we focus on static testing related to data consistency in a software system. In particular, we propose extensions to contemporary static testing techniques based on CRUD matrices, employing cross-verifications between various types of CRUD matrices made by different parties at various stages of the software project. Based on performed experiments, the proposed static testing technique significantly improves the consistency of Data Cycle Test cases. Together with this trend, we observe growing potential of test cases to detect data consistency defects in the system under test, when utilizing the proposed technique.

A computing method for simulating the energy consumption in an injection molding process using the Moldflow MPI analysis software is proposed. Considering such factors as product structure, processing parameters, and mold structure, it was shown by orthogonal testing that the melt temperature, product diameter, product wall thickness, and gate diameter are the four largest factors impacting on the injection energy consumption. Based on the MATLAB curve fitting toolbox, the relationship between the four main factors and the injection energy consumption was established, and a calculation model for the injection energy consumption was proposed.The accuracy of the model was above 95%. Finally, by using an experimental system of injection energy consumption to research the relationship between energy consumption and actual injection power, and by verifying the calculation accuracy of injection energy consumption of the established model, the results show that the established model can be an excellent p...

Software testing being one of the major phases of the software development life cycle is critical in delivering reliable software products. Traditional manual GUI testing has severe limitations like insufficient test coverage, labor intensiveness, complexity involved and cost ineffectiveness. “How much testing is enough or sufficient?” still remains a challenging question. Coverage analysis helps to guide the test engineers regarding test coverage and is used extensively to determine the effectiveness of selected testing methodology. The problems mentioned above related to manual GUI testing prompted the need for automation of GUI testing and coverage analysis. With the rapid emergence of GUI based context free applications, automated testing tools seems less effective. Recently, it has been learnt that concurrent and distributed machines based cluster can be used to reduce the required effort to test GUI in context of time. Proposed system use two different evolutionary algorithms concurrently to gain multiple objectives, based on the fitness functions of maximization of GUI test path coverage (measured as the number of events in an event sequence tested by a particular test case) and simultaneously minimizing the number of test cases. For coverage analysis, two of the very well-known multi objective algorithms; NSGA II and MOPSO from evolutionary domain have been employed. Experiments results of coverage analysis show that accuracy to the tune of 85% was achieved in MOPSO and NSGA II. This high level of accuracy is an indicator of usefulness of proposed fitness function. Both algorithms execute more than 90% of test paths.

Random testing (RT) has been identified as one of the most popular testing techniques, due to its simplicity and ease of automation. Adaptive random testing (ART) has been proposed as an enhancement to RT, improving its fault-detection effectiveness by evenly spreading random test inputs across the input domain. To achieve the even spreading, ART makes use of distance measurements between consecutive inputs. However, due to the nature of object-oriented software (OOS), its distance measurement can be particularly challenging: Each input may involve multiple classes, and interaction of objects through method invocations. Two previous studies have reported on how to test OOS at a single-class level using ART. In this study, we propose a new similarity metric to enable multiclass level testing using ART. When generating test inputs (for multiple classes, a series of objects, and a sequence of method invocations), we use the similarity metric to calculate the distance between two series of objects, and between two sequences of method invocations. We integrate this metric with ART and apply it to a set of open-source OO programs, with the empirical results showing that our approach outperforms other RT and ART approaches in OOS testing.

The test oracle —a judge of the correctness of the system under test (SUT)—is a major component of the testing process. Specifying test oracles is challenging for some domains, such as real-time embedded systems, where small changes in timing or sensory input may cause large behavioral differences. Models of such systems, often built for analysis and simulation, are appealing for reuse as test oracles. These models, however, typically represent an idealized system, abstracting away certain issues such as non-deterministic timing behavior and sensor noise. Thus, even with the same inputs, the model's behavior may fail to match an acceptable behavior of the SUT, leading to many false positives reported by the test oracle. We propose an automated steering framework that can adjust the behavior of the model to better match the behavior of the SUT to reduce the rate of false positives. This model steering is limited by a set of constraints (defining the differences in behavior that are acceptable) and is based on a search process attempting to minimize a dissimilarity metric. This framework allows non-deterministic, but bounded, behavioral differences, while preventing future mismatches by guiding the oracle—within limits—to match the execution of the SUT. Results show that steering significantly increases SUT-oracle conformance with minimal masking of real faults and, thus, has significant potential for reducing false positives and, consequently, testing and debugging costs while improving the quality of the testing process.

Ti-6Al-4V is widely utilized to manufacture airframe component structures with curvature, because of its excellent strength to weight ratio, outstanding resistance to corrosion, and inherent thermal and electrical compatibility with carbon fiber composite. Hot stretch bending (HSB) is an effective technology to manufacture these kinds of structures. When comparing the thin-walled extrusion with the thick-walled one, however, it is more difficult to form. The reason is that the local temperature of extrusion decreases more because of the heat transfer between extrusion and die. In this study, the material properties of Ti-6Al-4V were measured experimentally, such as the tensile property within the temperatures from 873 to 1023 K and the strain rates from 0.0005 to 0.005 s−1, the stress relaxation behavior in a wide range of temperatures (773–973 K) and prestrains (0.7–10%), as well as the heat transfer rule between Ti-6Al-4V (extrusion material) and asbestos cement (die material) under different pressures (8–25 MPa). The heat transfer coefficients (HTCs) were determined by an inverse analysis procedure, which was based on the comparison between measured and calculated temperature. Then, the coupled thermomechanical finite element (FE) model considering the effect of heat transfer was established. The influence of preheating temperature of die, initial temperature of extrusion, and dwell time on spring-back was researched based on orthogonal array testing strategy (OATS). The optimized parameters were verified by process test. It was showed that the established FE model could be used to predict spring-back within a relative deviation of 8.05%.

Video games comprise a multi-billion-dollar industry. Companies invest huge amounts of money for the release of their games. A part of this money is invested in testing the games. Current game test...

To solve the issues of serious wear, blockage, and poisoning of the catalyst in the denitration process of industrial furnaces such as glass furnaces and cement kiln, it was proposed to integrate the high-temperature dual-layer granular bed filter and the selective catalytic reduction (SCR) reactor into a device to realize the denitration of the SCR catalyst in a dust-free state. In the device, the upper part was a dual-layer granular bed filter and the lower part was a V2O5-WO3/TiO2 honeycomb ceramic catalyst. In the self-built dust removal and denitration integrated test equipment with an inner diameter of 100 mm, the effects of flue gas temperature, flue gas flow rate, nitric oxide (NO) concentration, and catalyst height on the denitration efficiency of the catalyst were investigated by orthogonal testing under dust-free conditions. The results show that the flue gas flow rate had the greatest influence on the denitration efficiency of the catalyst. With an increase in flue gas flow rate, the denitration efficiency first increased and then decreased. When the flue gas flow rate was 0.3 m/s, the denitration efficiency reached a maximum. The denitration test was carried out using flue gas with a dust concentration of 15 g/m3. The results show that the denitration efficiency continued to decrease with the deposition of dust on the catalyst surface (from an initial value of 96.51 to 80.59% at the 140th min), and the pressure drop correspondingly increased from 100 to 630 Pa. Additional integration testing of dust removal and denitration showed that the average dust removal efficiency of the integrated device for dust removal and denitration using a dual-layer granular bed filter could reach 99.84%, and the average denitration efficiency could reach 95.07%.

Retrofitting building envelopes is regarded as an effective solution that can help commercial and individual investors offset daily power usage. However, it is worthwhile to explore a highly efficient approach to seek optimum retrofitting strategies. A novel hybrid approach that integrates energy simulation, Orthogonal Array Testing (OAT), and Data Envelopment Analysis (DEA) is developed in this research to discover optimal solutions for building retrofit. A commercial high-rise building is chosen as a case study, and five parameters are considered, including the exterior envelope fabric, exterior window type, sunshade type, window-to-wall ratio, and airtightness. The energy consumption is first simulated and verified as a baseline. OAT is then employed to conduct experiments and explore potential solutions to the energy optimisation problem, based on which the most efficient strategy is obtained through DEA benchmarking. The identified optimal solution is able to save an annual operation energy of 7.01 kWh/m2, which is also cost-effective. It is also found that the window type and airtightness are significant factors with regard to the energy performance of building envelope retrofit. The study benefits designers and construction managers in determining the optimal solution of retrofitting building envelope for achieving energy-efficient building operations. Ministry of Education (MOE) Nanyang Technological University The National Natural Science Foundation of China (Grant No.51708282), the Start-Up Grant at Nanyang Technological University, Singapore (No. M4082160.030), and the Ministry of Education Grant, Singapore (No. M4011971.030) are acknowledged for their financial support of this research.

Thermoplastic elastomer (TPE) is a kind of new automotive interior material with high elasticity and strength. Traditional TPE materials were difficult to meet the new requirements of large-scale automotive interior parts with complex shape. In this study, the TPE material was prepared using different mass ratios with homopolymer polypropylene (PP), styrene-ethylene/butene-styrene copolymer (SEBS), naphthene oil (NO), magnesium stearate (MGST), and polytetrafluoroethylene (PTFE). A quality-prediction and multiobjective optimization method based on a genetic algorithm was applied. The parameters that had an important effect on the forming quality were selected using an orthogonal testing method. Results showed that using the proposed method, a new TPE material is obtained with excellent scratch resistance ability and high MFI. The mechanisms of the addition of PTFE and MGST were analysed according to SEM images. The peel strength of the optimized part was measured to prove the coating quality of TPE material.

The main aim of this work was to screen, isolate, and identify a probiotic selenium (Se)-resistant strain of Bacillus subtilis, using the 16S rDNA sequencing approach and subsequently optimize conditions. Initially, conditions were enhanced in two univariate optimization environments: shakings flask and a bioreactor. After solving optimization for selected variables, conditions were further optimized using orthogonal array testing. The results were further evaluated by the analysis of variance, in support of Se enrichment. In a bioreactor, based on R and F values, the order of effect of selected conditions on Se enrichment was stirring speed > initial pH > temperature > Se addition time. The stirring speed of the bioreactor was most significant, due to the suspension of reduced Se, as it formed. After absolute optimization, strain BSN313 was able to enrich Se up to 2,123 µg/g of dry weight, which is 7.58 times greater than the baseline Se-resistance. PRACTICAL APPLICATIONS: Systematic studies of selenium enrichment conditions will facilitate the successful development of an organic selenium source and the safe use of Bacillus subtilis strain (BSN313) as a food supplement. Selenium-enriched probiotic bacteria are reported to provide many health benefits to the host, due to antipathogenic, antioxidative, anticarcinogenic, antimutagenic, and anti-inflammatory activities.

HIV-1 protease is a crucial enzyme in the HIV life cycle and serves to cleave the polyprotein that is involved in the formation of mature viruses. Due to its sensitivity and important function in virion creation, predicting cleavage classification can aid in the development of HIV-1 protease inhibitors that can improve antiretroviral therapy. Currently available methods are less effective at maintaining high prediction accuracy and consistency when applied to data with class bias and can be simplified and optimized. A prediction method that focused solely on sequential data was proposed and used in this study. A simplified swarm optimization (SSO) algorithm was applied to classifying HIV-1 protease cleavage data, which consisted of octamers that would be cleaved between the fourth and fifth amino acid, and orthogonal array testing was incorporated to improve efficiency. The prediction accuracy was assessed by applying the SSO algorithm to datasets found in the UCI Machine Learning Repository. Our experimental results show that SSO is an effective predictor of HIV-1 protease cleavage, exhibiting prediction accuracy that compared favorably to existing methods for both data with little class bias and data that contains class bias. Additionally, our prediction accuracy results suggest that the use of physicochemical features, as opposed to solely sequential features, does not improve performance.

Forced degradation studies are crucial for the evaluation of the stability and biosimilarity. Here, adalimumab was subjected to oxidation, pH, temperature, agitation and repeated freeze-thaw in order to generate all possible degradation products. An orthogonal stability-indicating testing protocol comprising SE-HPLC, RP-HPLC, TapeStation gel electrophoresis, dynamic light scattering (DLS), and functional receptor binding assay was developed and validated. The assay protocol was used for the assessment of the pattern and kinetics of aggregation/degradation of adalimumab. SE-HPLC and DLS were used to show the formation of aggregates/fragments of adalimumab under nondenaturing conditions. TapeStation electrophoresis was performed under denaturing conditions to reveal the nature of aggregates. Results of the receptor binding assay agreed to those of SE-HPLC and DLS which indicated that it can be used as an activity-indicating assay for adalimumab. RP-HPLC demonstrated excellent selectivity for adalimumab in the presence of its oxidized forms. The kinetics of degradation was studied in each case and the results showed that it followed the first-order reaction kinetics. Correlation between the results supported the quality assessment of the tested product in industrial and clinical settings. This orthogonal protocol is a useful tool in stability assessment of monoclonal antibodies and a key criterion for the biosimilarity assessment.

The growth of China's aluminum industry makes more and more waste aluminum dross, although there are some ways for recycling aluminum dross, but still cannot absorb its output. This paper attempts to develop an effective concrete curing agent with high content of aluminum ash so as to effectively solve the problems of waste residue accumulation. The properties of a new aluminum dross cement-curing agent based on industrial solid wastes combined with an activator are evaluated through orthogonal testing using standard testing methods for compressive strength, bending strength, setting time, soundness, and the water requirement of standard consistency. The influence of the curing conditions and the water to cement ratio on the strength obtained with the aluminum dross curing agent was also studied along with the durability to water erosion, resistance to sulfate attack and stability when subjected to dry/wet cycles or high temperature. The results obtained demonstrate that this new clinker-free aluminum ash curing agent provides good mechanical properties and a high resistance to water and sulfate attack. This material was also found to be suitable for use as a curing agent in soil solidification.

Acorus tatarinowii Schott is a traditional Chinese medicine used to treat memory and cognitive dysfunction. Because of their efficacy and lower toxic effects, research on α- and β-asarone, the phytoconstituents, has attracted attention owing to their remarkable pharmacological activities. Silver ion coordination complexation high-speed counter-current chromatography was used to separate these isomers from A. tatarinowii extract, coupled with accelerated solvent extraction. Accelerated solvent extraction parameters were investigated with single-factor and orthogonal testing. A two-phase solvent system composed of n-hexane-ethyl acetate-ethanol-water (2:1:2:1, v/v) with 0.50 mol/L silver ions was selected for separation. From 2.0 g crude extract, 1.4 g of β-asarone and 0.09 g of α-asarone were obtained with purities over 98% by sequential sample loading in 20 h. The isolated compounds were identified by electrospray ionization mass spectrometry, 1H and 13C NMR. Silver ions significantly increased the separation factor and retention of the stationary phase. The chromatographic behavior indicated that cis-configuration was more strongly complexed with the silver ion. This was further demonstrated with the help of computational analysis. In conclusion, the established method could be employed to separate other cis-trans or E/Z isomers that form coordination complexes.