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Journal articles on the topic 'OPTIMAL TEST SUITES'

Author: Grafiati

Published: 11 September 2023

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1

Gladston, Angelin, and Niranjana Devi N. "Optimal Test Case Selection Using Ant Colony and Rough Sets." International Journal of Applied Evolutionary Computation 11, no. 2 (2020): 1–14. http://dx.doi.org/10.4018/ijaec.2020040101.

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Test case selection helps in improving quality of test suites by removing ambiguous, redundant test cases, thereby reducing the cost of software testing. Various works carried out have chosen test cases based on single parameter and optimized the test cases using single objective employing single strategies. In this article, a parameter selection technique is combined with an optimization technique for optimizing the selection of test cases. A two-step approach has been employed. In first step, the fuzzy entropy-based filtration is used for test case fitness evaluation and selection. In second

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Hasan, Imad H., Bestoun S. Ahmed, Moayad Y. Potrus, and Kamal Z. Zamli. "Generation and Application of Constrained Interaction Test Suites Using Base Forbidden Tuples with a Mixed Neighborhood Tabu Search." International Journal of Software Engineering and Knowledge Engineering 30, no. 03 (2020): 363–98. http://dx.doi.org/10.1142/s0218194020500151.

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To ensure the quality of current highly configurable software systems, intensive testing is needed to test all the configuration combinations and detect all the possible faults. This task becomes more challenging for most modern software systems when constraints are given for the configurations. Here, intensive testing is almost impossible, especially considering the additional computation required to resolve the constraints during the test generation process. In addition, this testing process is exhaustive and time-consuming. Combinatorial interaction strategies can systematically reduce the

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Sugave, Shounak Rushikesh, Yogesh R. Kulkarni, and Balaso. "Multi-Objective Optimization Model and Hierarchical Attention Networks for Mutation Testing." International Journal of Swarm Intelligence Research 14, no. 1 (2023): 1–23. http://dx.doi.org/10.4018/ijsir.319714.

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Mutation testing is devised for measuring test suite adequacy by identifying the artificially induced faults in software. This paper presents a novel approach by considering multiobjectives-based optimization. Here, the optimal test suite generation is performed using the proposed water cycle water wave optimization (WCWWO). The best test suites are generated by satisfying the multi-objective factors, such as time of execution, test suite size, mutant score, and mutant reduction rate. The WCWWO is devised by a combination of the water cycle algorithm (WCA) and water wave optimization (WWO). Th

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Diniz, Thomaz, Everton L. G. Alves, Anderson G. F. Silva, and Wilkerson L. Andrade. "Reducing the Discard of MBT Test Cases." Journal of Software Engineering Research and Development 8 (August 15, 2020): 4–1. http://dx.doi.org/10.5753/jserd.2020.602.

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Model-Based Testing (MBT) is used for generating test suites from system models. However, as software evolves, its models tend to be updated, which may lead to obsolete test cases that are often discarded. Test case discard can be very costly since essential data, such as execution history, are lost. In this paper, we investigate the use of distance functions and machine learning to help to reduce the discard of MBT tests. First, we assess the problem of managing MBT suites in the context of agile industrial projects. Then, we propose two strategies to cope with this problem: (i) a pure distan

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Fadhil, Heba Mohammed, Mohammed Najm Abdullah, and Mohammed Issam Younis. "TWGH: A Tripartite Whale–Gray Wolf–Harmony Algorithm to Minimize Combinatorial Test Suite Problem." Electronics 11, no. 18 (2022): 2885. http://dx.doi.org/10.3390/electronics11182885.

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Today’s academics have a major hurdle in solving combinatorial problems in the actual world. It is nevertheless possible to use optimization techniques to find, design, and solve a genuine optimal solution to a particular problem, despite the limitations of the applied approach. A surge in interest in population-based optimization methodologies has spawned a plethora of new and improved approaches to a wide range of engineering problems. Optimizing test suites is a combinatorial testing challenge that has been demonstrated to be an extremely difficult combinatorial optimization limitation of t

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He, Hongmei, Ana Sălăgean, Erkki Mäkinen, and Imrich Vrt’o. "Various heuristic algorithms to minimise the two-page crossing numbers of graphs." Open Computer Science 5, no. 1 (2015): 22–40. http://dx.doi.org/10.1515/comp-2015-0004.

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AbstractWe propose several new heuristics for the twopage book crossing problem, which are based on recent algorithms for the corresponding one-page problem. Especially, the neural network model for edge allocation is combined for the first time with various one-page algorithms. We investigate the performance of the new heuristics by testing them on various benchmark test suites. It is found out that the new heuristics outperform the previously known heuristics and produce good approximations of the planar crossing number for severalwell-known graph families. We conjecture that the optimal two

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De Groff, Dolores, Roxana Melendez, Perambur Neelakanta, and Hajar Akif. "Optimal Electric-Power Distribution and Load-Sharing on Smart-Grids: Analysis by Artificial Neural Network." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 18 (January 24, 2019): 7431–39. http://dx.doi.org/10.24297/ijct.v18i0.8059.

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This study refers to developing an electric-power distribution system with optimal/suboptimal load-sharing in the complex and expanding metro power-grid infrastructure. That is, the relevant exercise is to indicate a smart forecasting strategy on optimal/suboptimal power-distribution to consumers served by a smart-grid utility. An artificial neural network (ANN) is employed to model the said optimal power-distribution between generating sources and distribution centers. A compatible architecture of the test ANN with ad hoc suites of training/prediction schedules is indicated thereof. Pertinent

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Wang, Zhendong, Jianlan Wang, Dahai Li, and Donglin Zhu. "A Multi-Strategy Sparrow Search Algorithm with Selective Ensemble." Electronics 12, no. 11 (2023): 2505. http://dx.doi.org/10.3390/electronics12112505.

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Aiming at the deficiencies of the sparrow search algorithm (SSA), such as being easily disturbed by the local optimal and deficient optimization accuracy, a multi-strategy sparrow search algorithm with selective ensemble (MSESSA) is proposed. Firstly, three novel strategies in the strategy pool are proposed: variable logarithmic spiral saltation learning enhances global search capability, neighborhood-guided learning accelerates local search convergence, and adaptive Gaussian random walk coordinates exploration and exploitation. Secondly, the idea of selective ensemble is adopted to select an

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Sung, Tien-Wen, Baohua Zhao, and Xin Zhang. "Quasi-Affine Transformation Evolutionary with Double Excellent Guidance." Wireless Communications and Mobile Computing 2021 (April 17, 2021): 1–15. http://dx.doi.org/10.1155/2021/5591543.

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The Quasi-Affine Transformation Evolutionary (QUATRE) algorithm is a swarm-based collaborative optimization algorithm, which has drawn attention from researchers due to its simple structure, easy implementation, and powerful performance. However, it needs to be improved regarding the exploration, especially in the late stage of evolution, and the problem of easy falling into a local optimal solution. This paper proposes an improved algorithm named Quasi-Affine Transformation Evolutionary with double excellent guidance (QUATRE-DEG). The algorithm uses not only the global optimal solution but al

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10

Aggarwal, Sakshi, and Krishn K. Mishra. "Multi-operator Differential Evolution with MOEA/D for Solving Multi-objective Optimization Problems." Journal of Telecommunications and Information Technology 3, no. 2022 (2022): 85–95. http://dx.doi.org/10.26636/jtit.2022.161822.

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In this paper, we propose a multi-operator differentia evolution variant that incorporates three diverse mutation strategies in MOEA/D. Instead of exploiting the local region, the proposed approach continues to search for optimal solutions in the entire objective space. It explicitly maintains diversity of the population by relying on the benefit of clustering. To promowe convergence, the solutions close to the ideal position, in the objective space are given preference in the evolutionary process. The core idea is to ensure diversity of the population by applying multiple mutation schemes and

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Wang, Xilu, and Yaochu Jin. "Knowledge Transfer Based on Particle Filters for Multi-Objective Optimization." Mathematical and Computational Applications 28, no. 1 (2023): 14. http://dx.doi.org/10.3390/mca28010014.

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Particle filters, also known as sequential Monte Carlo (SMC) methods, constitute a class of importance sampling and resampling techniques designed to use simulations to perform on-line filtering. Recently, particle filters have been extended for optimization by utilizing the ability to track a sequence of distributions. In this work, we incorporate transfer learning capabilities into the optimizer by using particle filters. To achieve this, we propose a novel particle-filter-based multi-objective optimization algorithm (PF-MOA) by transferring knowledge acquired from the search experience. The

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Darvish, Arman, and Shahryar Rahnamayan. "Optimal Parameter Setting of Active-Contours Using Differential Evolution and Expert-Segmented Sample Image." Journal of Advanced Computational Intelligence and Intelligent Informatics 16, no. 6 (2012): 677–86. http://dx.doi.org/10.20965/jaciii.2012.p0677.

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Generally, tissue extraction (segmentation) is one of the most challenging tasks in medical image processing. Inaccurate segmentation propagates errors to the subsequent steps in the image processing chain. Thus, in any image processing chain, the role of segmentation is in fact critical because it has a significant impact on the accuracy of the final results, such as those of feature extraction. The appearance of variant noise types makes medical image segmentation a more complicated task. Thus far, many approaches for image segmentation have been proposed, including the well-known active con

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Wang, Yule, Wanliang Wang, Ijaz Ahmad, and Elsayed Tag-Eldin. "Multi-Objective Quantum-Inspired Seagull Optimization Algorithm." Electronics 11, no. 12 (2022): 1834. http://dx.doi.org/10.3390/electronics11121834.

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Objective solutions of multi-objective optimization problems (MOPs) are required to balance convergence and distribution to the Pareto front. This paper proposes a multi-objective quantum-inspired seagull optimization algorithm (MOQSOA) to optimize the convergence and distribution of solutions in multi-objective optimization problems. The proposed algorithm adopts opposite-based learning, the migration and attacking behavior of seagulls, grid ranking, and the superposition principles of quantum computing. To obtain a better initialized population in the absence of a priori knowledge, an opposi

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Jin, Xin, and Fulin Wang. "A Multioffspring Genetic Algorithm Based on Sorting Grouping Selection and Combination Pairing Crossover." Mathematical Problems in Engineering 2022 (March 28, 2022): 1–20. http://dx.doi.org/10.1155/2022/4203082.

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A multi-offspring genetic algorithm based on sorting grouping selection and combination pairing crossover was proposed in this paper. First, individuals in the population were sorted according to their objective function values, and the remaining individuals were divided into several groups after eliminating the worst. Then, the selection operation, which has the advantage of a simplified calculation that can be easily performed, was implemented. Second, a combination pairing crossover operator was designed. Individuals from different groups were selected for new combinations. In a combination

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BAER, CHARLES F., and MICHAEL LYNCH. "Correlated evolution of life-history with size at maturity in Daphnia pulicaria: patterns within and between populations." Genetical Research 81, no. 2 (2003): 123–32. http://dx.doi.org/10.1017/s0016672303006098.

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Explaining the repeated evolution of similar sets of traits under similar environmental conditions is an important issue in evolutionary biology. The extreme alternative classes of explanations for correlated suites of traits are optimal adaptation and genetic constraint resulting from pleiotropy. Adaptive explanations presume that individual traits are free to evolve to their local optima and that convergent evolution represents particularly adaptive combinations of traits. Alternatively, if pleiotropy is strong and difficult to break, strong selection on one or a few particularly important c

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Bandi, Chaithanya, and Diwakar Gupta. "Operating Room Staffing and Scheduling." Manufacturing & Service Operations Management 22, no. 5 (2020): 958–74. http://dx.doi.org/10.1287/msom.2019.0781.

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Problem definition: We consider two problems faced by an operating room (OR) manager: (1) how many baseline (core) staff to hire for OR suites, and (2) how to schedule surgery requests that arrive one by one. The OR manager has access to historical case count and case length data, and needs to balance the fixed cost of baseline staff and variable cost of overtime, while satisfying surgeons’ preferences. Academic/practical relevance: ORs are costly to operate and generate about 70% of hospitals’ revenues from surgical operations and subsequent hospitalizations. Because hospitals are increasingl

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17

Cheng, Christine T. "The test suite generation problem: Optimal instances and their implications." Discrete Applied Mathematics 155, no. 15 (2007): 1943–57. http://dx.doi.org/10.1016/j.dam.2007.04.010.

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Chen, Hao, Shu-Yan Wang, and Xiao-Ying Pan. "Construction Optimal Combination Test Suite Based on Ethnic Group Evolution Algorithm." Research Journal of Applied Sciences, Engineering and Technology 6, no. 2 (2013): 309–15. http://dx.doi.org/10.19026/rjaset.6.4078.

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19

Bharathi, M. "Optimum Test Suite Using Fault-Type Coverage-Based Ant Colony Optimization Algorithm." International Journal of Applied Metaheuristic Computing 13, no. 1 (2022): 1–23. http://dx.doi.org/10.4018/ijamc.2022010106.

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Software Product Lines(SPLs) covers a mixture of features for testing Software Application Program(SPA). Testing cost reduction is a major metric of software testing. In combinatorial testing(CT), maximization of fault type coverage and test suite reduction plays a key role to reduce the testing cost of SPA. Metaheuristic Genetic Algorithm(GA) do not offer best outcome for test suite optimization problem due to mutation operation and required more computational time. So, Fault-Type Coverage Based Ant Colony Optimization(FTCBACO) algorithm is offered for test suite reduction in CT. FTCBACO algo

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Sheoran, Snehlata, Neetu Mittal, and Alexander Gelbukh. "Artificial bee colony algorithm in data flow testing for optimal test suite generation." International Journal of System Assurance Engineering and Management 11, no. 2 (2019): 340–49. http://dx.doi.org/10.1007/s13198-019-00862-1.

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21

M, Bharathi, and Sangeetha V. "Fault-type coverage based ant colony optimization algorithm for attaining smaller test suite." IAES International Journal of Artificial Intelligence (IJ-AI) 9, no. 3 (2020): 507. http://dx.doi.org/10.11591/ijai.v9.i3.pp507-519.

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<table width="0" border="1" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="593"><p>In this paper, we proposed Fault-Type Coverage Based Ant Colony Optimization (FTCBACO) technique for test suite optimization. An algorithm starts with initialization of FTCBACO factors using test cases in test suite. Then, assign separate ant to each test case called vertex. Each ant chooses best vertices to attain food source called objective of the problem by means of updating of pheromone trails and higher probability trails. This procedure is repeated up to t

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22

Chen, Lu Lu, and Ling Zhang. "Study of Test Cases Prioritization Based on Ant Colony Algorithm." Applied Mechanics and Materials 263-266 (December 2012): 2168–72. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.2168.

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Regression testing is an important activity to ensure the quality of software. In order to improve the efficiency of regression testing, in this paper, the author proposes to reorder test suite based on ant colony algorithm in regression testing, and compare the result with other common sort results. Through experiment, it shows that the method can get the optimal sequence of test cases under the time limit and it has been proven a superior method in both effectiveness and efficiency for test cases prioritization.

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23

Geckeler, Ralf D. "ESAD Shearing Deflectometry: A Primary Flatness Standard with Sub-Nanometer Uncertainty." Key Engineering Materials 381-382 (June 2008): 543–46. http://dx.doi.org/10.4028/www.scientific.net/kem.381-382.543.

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To overcome the limitations of conventional interferometry, a technique has been developed which allows the absolute topography measurement of near-plane and slightly curved optical surfaces of arbitrary size with low measurement uncertainty. The Extended Shear Angle Difference (ESAD) method combines deflectometric and shearing techniques in a unique way to minimize measurement errors and to optimize measurand traceability. A device for the topography measurement of optical surfaces up to 500 mm in diameter, achieving sub-nanometer repeatability, reproducibility and uncertainty, was built at t

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Younis, Mohammed I., and Kamal Z. Zamli. "A Strategy for Automatic Quality Signing and Verification Processes for Hardware and Software Testing." Advances in Software Engineering 2010 (February 2, 2010): 1–7. http://dx.doi.org/10.1155/2010/323429.

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We propose a novel strategy to optimize the test suite required for testing both hardware and software in a production line. Here, the strategy is based on two processes: Quality Signing Process and Quality Verification Process, respectively. Unlike earlier work, the proposed strategy is based on integration of black box and white box techniques in order to derive an optimum test suite during the Quality Signing Process. In this case, the generated optimal test suite significantly improves the Quality Verification Process. Considering both processes, the novelty of the proposed strategy is the

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Harikarthik, S. K., V. Palanisamy, and P. Ramanathan. "Optimal test suite selection in regression testing with testcase prioritization using modified Ann and Whale optimization algorithm." Cluster Computing 22, S5 (2017): 11425–34. http://dx.doi.org/10.1007/s10586-017-1401-7.

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Fisal, Nagwa R., Abeer Hamdy, and Essam A. Rashed. "Search-Based Regression Testing Optimization." International Journal of Open Source Software and Processes 12, no. 2 (2021): 1–20. http://dx.doi.org/10.4018/ijossp.2021040101.

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Regression testing is one of the essential activities during the maintenance phase of software projects. It is executed to ensure the validity of an altered software. However, as the software evolves, regression testing becomes prohibitively expensive. In order to reduce the cost of regression testing, it is mandatory to reduce the size of the test suite by selecting the most representative test cases that do not compromise the effectiveness of the regression testing in terms of fault-detection capability. This problem is known as test suite reduction (TSR) problem, and it is known to be an NP

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Ping, Ping, Feng Xu, and Zhi Jian Wang. "Generating High-Quality Random Numbers by Next Nearest-Neighbor Cellular Automata." Advanced Materials Research 765-767 (September 2013): 1200–1204. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.1200.

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Cellular automaton (CA) has been widely investigated as random number generators (RNGs). However, the CA rule and the number of neighbors must be chosen carefully for good randomness. In Ref. [11], non-uniform CA with next nearest neighborhood was applied to generate a pseudo-random sequence. Considering that non-uniform CA has more complex implementation in hardware and needs lager memory to store different rules than uniform CA. In this paper, we propose new RNGs based on uniform CA with next nearest neighborhood. Time spacing technique and NIST statistical test suite are used to find optima

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Rossi, Mauro, Txomin Bornaetxea, and Paola Reichenbach. "LAND-SUITE V1.0: a suite of tools for statistically based landslide susceptibility zonation." Geoscientific Model Development 15, no. 14 (2022): 5651–66. http://dx.doi.org/10.5194/gmd-15-5651-2022.

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Abstract. In the past 50 years, a large variety of statistically based models and methods for landslide susceptibility mapping and zonation have been proposed in the literature. The methods, which are applicable to a large range of spatial scales, use a large variety of input thematic data, different model combinations, and several approaches to evaluate the models' performance. Despite the numerous applications available in the literature, a standard approach for susceptibility modeling and zonation is still missing. The literature search revealed that several software program and tools are a

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Khaleel, Shahbaa I., and Raghda Anan. "A review paper: optimal test cases for regression testing using artificial intelligent techniques." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 2 (2023): 1803. http://dx.doi.org/10.11591/ijece.v13i2.pp1803-1816.

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<span lang="EN-US">The goal of the testing process is to find errors and defects in the software being developed so that they can be fixed and corrected before they are delivered to the customer. Regression testing is an essential quality testing technique during the maintenance phase of the program as it is performed to ensure the integrity of the program after modifications have been made. With the development of the software, the test suite becomes too large to be fully implemented within the given test cost in terms of budget and time. Therefore, the cost of regression testing using

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Santo, D. D., A. O’Neill, L. Franconi, et al. "Test of the Optosystem for the ATLAS ITk data transmission chain." Journal of Instrumentation 18, no. 03 (2023): C03021. http://dx.doi.org/10.1088/1748-0221/18/03/c03021.

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Abstract After Run III the ATLAS detector will undergo a series of upgrades to cope with the harsher radiation environment and increased number of proton interactions in the High Luminosity LHC. One of the key projects in this suite of upgrades is the ATLAS Inner Tracker (ITk). The pixel detector of the ITk must be read out accurately and with extremely high rate. The Optosystem performs electrical-to-optical conversion of signals from the pixel modules. We present a general overview on the design of the Optosystem and recent results related to the performance of the data transmission chain, p

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Panda, S., D. Munjal, and D. P. Mohapatra. "A Slice-Based Change Impact Analysis for Regression Test Case Prioritization of Object-Oriented Programs." Advances in Software Engineering 2016 (May 8, 2016): 1–20. http://dx.doi.org/10.1155/2016/7132404.

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Test case prioritization focuses on finding a suitable order of execution of the test cases in a test suite to meet some performance goals like detecting faults early. It is likely that some test cases execute the program parts that are more prone to errors and will detect more errors if executed early during the testing process. Finding an optimal order of execution for the selected regression test cases saves time and cost of retesting. This paper presents a static approach to prioritizing the test cases by computing the affected component coupling (ACC) of the affected parts of object-orien

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Mitchell, Rory, Daniel Stokes, Eibe Frank, and Geoffrey Holmes. "Bandwidth-Optimal Random Shuffling for GPUs." ACM Transactions on Parallel Computing 9, no. 1 (2022): 1–20. http://dx.doi.org/10.1145/3505287.

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Linear-time algorithms that are traditionally used to shuffle data on CPUs, such as the method of Fisher-Yates, are not well suited to implementation on GPUs due to inherent sequential dependencies, and existing parallel shuffling algorithms are unsuitable for GPU architectures because they incur a large number of read/write operations to high latency global memory. To address this, we provide a method of generating pseudo-random permutations in parallel by fusing suitable pseudo-random bijective functions with stream compaction operations. Our algorithm, termed “bijective shuffle” trades incr

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Grandison, Alexandra, Michael Franjieh, Lily Greene, and Greville G. Corbett. "Optimal categorisation." Cadernos de Linguística 2, no. 1 (2021): e393. http://dx.doi.org/10.25189/2675-4916.2021.v2.n1.id393.

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The debate as to whether language influences cognition has been long standing but has yielded conflicting findings across domains such as colour and kinship categories. Fewer studies have investigated systems such as nominal classification (gender, classifiers) across different languages to examine the effects of linguistic categorisation on cognition. Effective categorisation needs to be informative to maximise communicative efficiency but also simple to minimise cognitive load. It therefore seems plausible to suggest that different systems of nominal classification have implications for the

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Guan, Gui Xia, Yu Zhang Han, Min Hua Wu, and Jian Guo Han. "On Anti-Noise-Algorithm of Optical-Polarization-Sensing Localization." Applied Mechanics and Materials 190-191 (July 2012): 126–32. http://dx.doi.org/10.4028/www.scientific.net/amm.190-191.126.

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the noise problem met during sensing-measurement hasn’t been adequately discussed. In this paper, the calculation errors caused by the noises are demonstrated. A practical optical sensing-localization algorithm based on specially organized Genetic Algorithm is proposed, and application-test experiments of this algorithm are described. Moreover, a parallel-operation scheme suited for Cloud-Computing supporting is introduced. Developments of the algorithm mentioned above provide an effective approach for the rapidly growing field, independent-localization, which would benefit the fields such as

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Mishra, Deepti Bala, Biswaranjan Acharya, Dharashree Rath, Vassilis C. Gerogiannis, and Andreas Kanavos. "A Novel Real Coded Genetic Algorithm for Software Mutation Testing." Symmetry 14, no. 8 (2022): 1525. http://dx.doi.org/10.3390/sym14081525.

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Information Technology has rapidly developed in recent years and software systems can play a critical role in the symmetry of the technology. Regarding the field of software testing, white-box unit-level testing constitutes the backbone of all other testing techniques, as testing can be entirely implemented by considering the source code of each System Under Test (SUT). In unit-level white-box testing, mutants can be used; these mutants are artificially generated faults seeded in each SUT that behave similarly to the realistic ones. Executing test cases against mutants results in the adequacy

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Trojovská, Eva, Mohammad Dehghani, and Víctor Leiva. "Drawer Algorithm: A New Metaheuristic Approach for Solving Optimization Problems in Engineering." Biomimetics 8, no. 2 (2023): 239. http://dx.doi.org/10.3390/biomimetics8020239.

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Metaheuristic optimization algorithms play an essential role in optimizing problems. In this article, a new metaheuristic approach called the drawer algorithm (DA) is developed to provide quasi-optimal solutions to optimization problems. The main inspiration for the DA is to simulate the selection of objects from different drawers to create an optimal combination. The optimization process involves a dresser with a given number of drawers, where similar items are placed in each drawer. The optimization is based on selecting suitable items, discarding unsuitable ones from different drawers, and

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Bartram, Peter, and Alexander Wittig. "Terrestrial exoplanet simulator: an error optimal planetary system integrator that permits close encounters." Monthly Notices of the Royal Astronomical Society 504, no. 1 (2021): 678–91. http://dx.doi.org/10.1093/mnras/stab896.

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ABSTRACT We present Terrestrial Exoplanet Simulator (tes), a new n-body integration code for the accurate and rapid propagation of planetary systems in the presence of close encounters. tes builds upon the classic Encke method and integrates only the perturbations to Keplerian trajectories to reduce both the error and runtime of simulations. Variable step size is used throughout to enable close encounters to be precisely handled. A suite of numerical improvements is presented that together make tes optimal in terms of energy error. Lower runtimes are found in the majority of test problems cons

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Wolfe, Stephen A., David J. Huntley, and Jeff Ollerhead. "Optical Dating of Modern and Late Holocene Dune Sands in the Brandon Sand Hills, Southwestern Manitoba*." Géographie physique et Quaternaire 56, no. 2-3 (2004): 203–14. http://dx.doi.org/10.7202/009106ar.

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Abstract For any suite of optical dating samples two issues that must be considered are: do zero-age samples yield an optical age of zero, and are the optical ages consistent with independent stratigraphic and chronologic information? A test of the zero-age of dune sands was performed by dating samples from the crest, lee slope and stoss slope of an active dune in southwestern Manitoba. Three surface samples showed that, using 1.4 eV (infrared) excitation of K-feldspars, the equivalent dose, and hence “age”, depended on whether the bleach used for the thermal transfer correction was infrared/r

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Pegau, W. Scott, Jessica Garron, Leonard Zabilansky, et al. "Detection of oil in and under ice." International Oil Spill Conference Proceedings 2017, no. 1 (2017): 1857–76. http://dx.doi.org/10.7901/2169-3358-2017.1.1857.

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ABSTRACT (2017-147) In 2014, researchers from ten organizations came to the U.S. Army Corps of Engineers, Cold Regions Research and Engineering Laboratory (CRREL) in New Hampshire to conduct a first of its kind large-scale experiment aimed at determining current sensor capabilities for detecting oil in and under sea ice. This project was the second phase of the Oil Spill Detection in Low Visibility and Ice research project of the International Association of Oil and Gas Producers (IOGP), Arctic Oil Spill Response Technology - Joint Industry Programme. The objectives of the project were to:Acqu

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Xu, Gaowei, Huimin Fang, Yumin Song, and Wensheng Du. "Optimal Design and Analysis of Cavitating Law for Well-Cellar Cavitating Mechanism Based on MBD-DEM Bidirectional Coupling Model." Agriculture 13, no. 1 (2023): 142. http://dx.doi.org/10.3390/agriculture13010142.

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A variable velocity parallel four-bar cavitating mechanism for well-cellar can form the well-cellar cavitation which suits for well-cellar transplanting under a continuous operation. In order to improve the cavitating quality, this paper analyzed the structural composition and working principle of the cavitating mechanism and established the bidirectional coupling model of multi-body dynamics and the discrete element between the cavitating mechanism and soil through Recurdyn and EDEM software. Based on the model, a three-factor, five-level quadratic orthogonal rotational combination design tes

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Singh, Lakshman, and Sachin Singh. "Mathematical Modeling of Thermal Lensing effect on Nd-Yag Laser Rod in Trans-Receiver Optoelectronics Avionics Assembly and its Interferometric Measurement." International Journal of Computational Physics Series 1, no. 1 (2018): 65–76. http://dx.doi.org/10.29167/a1i1p65-76.

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The Nd-Yag laser Rod commonly used Laser Generation element in Optical Detection & Ranging System of Military Aircraft. This research paper points out different issues of Nd-Yag Laser rod during Laboratory test. The paper discuses the thermal lensing phenomenon in the Nd-Yag Laser Rod which causes a thermal fracture in a rod, variation in laser power, measurement error and commutative low accuracy effect in the higher optical assembly. The research find out major unavoidable reasons in the optical assembly which cause thermal lensing phenomenon and formulated a generic mathematical model f

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Zitzler, Eckart, Kalyanmoy Deb, and Lothar Thiele. "Comparison of Multiobjective Evolutionary Algorithms: Empirical Results." Evolutionary Computation 8, no. 2 (2000): 173–95. http://dx.doi.org/10.1162/106365600568202.

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In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in converging to the Pareto-optimal front (e.g., multimodality and deception). By investigating these different problem features separately, it is possible to predict the kind of problems to which a certain technique is or is not well suited. However, in contrast to what was suspected beforehand, the experim

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Coppa, Paolo, and Antonio La Malfa. "Light Extinction by Fire Smokes." Journal of Fire Sciences 15, no. 3 (1997): 180–202. http://dx.doi.org/10.1177/073490419701500302.

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Visibility of escape routes is most important to guarantee the safety of people indoors during fires. In the case of a fire, visibility is strongly in fluenced by the smoke present in the room. In the present work, the extinction co efficient of the visible light has been experimentally measured in the presence of the smoke produced by four different test fires, named TF2, TF3, TF4, and TF5. Tests have been carried out in a specially suited test room in the Italian Fire De partment Research Center, provided with instruments to measure the optical density of smoke and the spectral extinction co

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Zhao, Nai Zhi, Chang Tie Huang, and Xin Chen. "Structural Health Monitoring of Plate Structures Using Lamb Wave Methods." Advanced Materials Research 368-373 (October 2011): 2417–20. http://dx.doi.org/10.4028/www.scientific.net/amr.368-373.2417.

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In this paper，waveform is used to excite Lamb waves in the test plates during experimental testing. The optimal excitation frequency will depend on the test configuration. In order to select an excitation frequency, dispersion curves are first created to show what frequency range is best suited for Lamb wave excitation. According to dispersion curves were created for the aluminum test plates and it was concluded that a frequency below 1 MHz will be used in order to only excite the fundamental and modes. Experiments are performed on the aluminum test plates described. Experimental testing is fi

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Gavlina, A. E., D. A. Novikov, and M. V. Askerko. "Orthogonal ray scheme: a method for processing interference patterns and reconstructing the shape of a test convex mirror." Journal of Physics: Conference Series 2127, no. 1 (2021): 012066. http://dx.doi.org/10.1088/1742-6596/2127/1/012066.

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Abstract This report is devoted to the processing of the interference pattern of the tested mirror, obtained using the orthogonal ray scheme, where the convex testing surface is illuminated by a collimated beam, which is perpendicular to the optical axis of the surface. The interference pattern is created by two wavefronts, one of which is reflected from the mirror, while the other wavefront bypasses the mirror and travels directly to the detector plane. The result of interference pattern processing is a topography map formed by several tangential profiles. The proposed method is suited for la

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Ye, Chunling, Zhengyan Mao, and Mandan Liu. "A Novel Multi-Objective Five-Elements Cycle Optimization Algorithm." Algorithms 12, no. 11 (2019): 244. http://dx.doi.org/10.3390/a12110244.

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Inspired by the mechanism of generation and restriction among five elements in Chinese traditional culture, we present a novel Multi-Objective Five-Elements Cycle Optimization algorithm (MOFECO). During the optimization process of MOFECO, we use individuals to represent the elements. At each iteration, we first divide the population into several cycles, each of which contains several individuals. Secondly, for every individual in each cycle, we judge whether to update it according to the force exerted on it by other individuals in the cycle. In the case of an update, a local or global update i

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Chittka, Lars. "BEE COLOR VISION IS OPTIMAL FOR CODING FLOWER COLOR, BUT FLOWER COLORS ARE NOT OPTIMAL FOR BEING CODED—WHY?" Israel Journal of Plant Sciences 45, no. 2-3 (1997): 115–27. http://dx.doi.org/10.1080/07929978.1997.10676678.

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Model calculations are used to determine an optimal color coding system for identifying flower colors, and to see whether flower colors are well suited for being encoded. It is shown that the trichromatic color vision of bees comprises UV, blue, and green receptors whose wavelength positions are optimal for identifying flower colors. But did flower colors actually drive the evolution of bee color vision? A phylogenetic analysis reveals that UV, blue, and green receptors were probably present in the ancestors of crustaceans and insects 570 million years ago, and thus predate the evolution of fl

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Dahlke, D., M. Geßner, H. Meißner, et al. "CALIBRATING PHOTOGRAMMETRIC AIRBORNE CAMERA SYSTEMS WITH DIFFRACTIVE OPTICAL ELEMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 1637–42. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1637-2019.

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<p><strong>Abstract.</strong> This paper presents a laboratory approach for geometric calibration of airborne camera systems. The setup uses an incoming laser beam, which is split by Diffractive Optical Elements (DOE) into a number of beams with precisely-known propagation directions. Each point of the diffraction pattern represents a point at infinity and is invariant against translation. A single image is sufficient to allow a complete camera calibration in accordance with classical camera calibration methods using the pinhole camera model and a distortion model. The presen

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Sahin, Omur, Bahriye Akay, and Dervis Karaboga. "Archive-based multi-criteria Artificial Bee Colony algorithm for whole test suite generation." Engineering Science and Technology, an International Journal 24, no. 3 (2021): 806–17. http://dx.doi.org/10.1016/j.jestch.2020.12.011.

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Tuloli, Mohamad Syafri, Benhard Sitohang, and Bayu Hendradjaya. "Coevolution of Second-order-mutant." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 3238. http://dx.doi.org/10.11591/ijece.v8i5.pp3238-3249.

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<span>One of the obstacles that hinder the usage of mutation testing is its impracticality, two main contributors of this are a large number of mutants and a large number of test cases involves in the process. Researcher usually tries to address this problem by optimizing the mutants and the test case separately. In this research, we try to tackle both of optimizing mutant and optimizing test-case simultaneously using a coevolution optimization method. The coevolution optimization method is chosen for the mutation testing problem because the method works by optimizing multiple collection

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