val eeel · The Journal Of Test Deposits · 2013
Take a look at the topics on the right to browse and page through our documentation, or search using the box above the topic list Common questions; how do I…? Construct DOI suffixes Verify a metadata registration Update an existing metadata record Interpret and act on reports Query the API to retrieve metadata See system status and maintenance If you have questions please consult other users on our forum at community.
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va el · The Journal Of Test Deposits · 2013
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Frank Witte · 2022
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va el · The Journal Of Test Deposits · 2013
Take a look at the topics on the right to browse and page through our documentation, or search using the box above the topic list Common questions; how do I…? Construct DOI suffixes Verify a metadata registration Update an existing metadata record Interpret and act on reports Query the API to retrieve metadata See system status and maintenance If you have questions please consult other users on our forum at community.
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Hong Yu (6528), Jiaxuan Hao (21622982), Yongbo Li (6611780) · Figshare · 2025
<div> To solve the problems of low detection accuracy, large model size and slow reasoning speed of existing potato quality detection models, this paper proposes LPD-YOLOv7-Tiny, a lightweight potato sprout and spoilage detection model based on YOLOv7-Tiny. The proposed model introduces MobileNetV3 small, BiFormer, SimAM, and the Focal-EIOU loss function. MobileNetV3 small greatly reduces the number of parameters and computational complexity of the model, BiFormer enhances the multi-scale feature fusion capability of the model, and the SimAM module effectively suppresses irrelevant information and strengthens local features. The Focal-EIOU loss function improves the model’s attention to difficult classification samples and enhances its bounding box regression capability. LPD-YOLOv7-Tiny achieves excellent detection performance on potatoes under complex background conditions: mAP is increased to 90.3%, the number of parameters is reduced to 5.8 MB, the number of computations is reduced to 10.1 G, and the inference speed is increased to 142.5 fps. Compared with mainstream detection models such as the YOLO Basic series, SSD and speed-RCNN, LPD-YOLOv7-Tiny achieves significantly improved performance in terms of detection accuracy, positioning capability and computational efficiency, indicating it has wide application potential in resource-constrained and high-precision scenarios. </div>
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va el · The Journal Of Test Deposits · 2013
Take a look at the topics on the right to browse and page through our documentation, or search using the box above the topic list Common questions; how do I…? Construct DOI suffixes Verify a metadata registration Update an existing metadata record Interpret and act on reports Query the API to retrieve metadata See system status and maintenance If you have questions please consult other users on our forum at community.
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Giovanni Gigli · 1995
A VERTICAL BARRIER HAS BEEN DESIGNED WHICH, BECAUSE OF ITS SPECIAL ABILITY TO ABSORB SOUND, IS PARTICULARLY SUITABLE FOR USE AS AN ANTI-NOISE BARRIER. THE BARRIER IS MADE OF PREFABRICATED CONCRETE. IT SHOULD BE NOTED THAT THE GOOD VALUES REPORTED IN THIS ARTICLE WERE OBTAINED FROM TYPE 24 ELEMENTS WITH THE DIMENSIONS 90X40X60CM, AND FILL MATERIAL FROM SUPERFICIAL EXCAVATION, WITHOUT ANY VEGETATION. THE VOLUMES WILL BE HIGHER IF TYPE 20 ELEMENTS OF A DOUBLE THICKNESS ARE EMPLOYED, (90X40X120CM), AND WHEN VEGETATION HAS EVENTUALLY COVERED THE WHOLE BARRIER.
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Null Anvor · Zenodo (CERN European Organization for Nuclear Research) · 2025
This is the same formula if minced three trial questions that it has succeeded before..
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Null Anvor · Zenodo (CERN European Organization for Nuclear Research) · 2025
This is the same formula if minced three trial questions that it has succeeded before..
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Ling Yuan (374505), Xinyi Xu (505530), Ping Sun (59933) et al. · Figshare · 2024
<div><p>Multi-Label Text Classification (MLTC) is a crucial task in natural language processing. Compared to single-label text classification, MLTC is more challenging due to its vast collection of labels which include extracting local semantic information, learning label correlations, and solving label data imbalance problems. This paper proposes a model of Label Attention and Correlation Networks (LACN) to address the challenges of classifying multi-label text and enhance classification performance. The proposed model employs the label attention mechanism for a more discriminative text representation and uses the correlation network based on label distribution to enhance the classification results. Also, a weight factor based on the number of samples and a modulation function based on prediction probability are combined to alleviate the label data imbalance effectively. Extensive experiments are conducted on the widely-used conventional datasets AAPD and RCV1-v2, and extreme datasets EUR-LEX and AmazonCat-13K. The results indicate that the proposed model can be used to deal with extreme multi-label data and achieve optimal or suboptimal results versus state-of-the-art methods. For the AAPD dataset, compared with the suboptimal method, it outperforms the second-best method by 2.05% ∼ 5.07% in precision@k and by 2.10% ∼ 3.24% in NDCG@k for k = 1, 3, 5. The superior outcomes demonstrate the effectiveness of LACN and its competitiveness in dealing with MLTC tasks.</p></div>
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Joe A. Lynn · Defense Technical Information Center (DTIC) · 1993
This report contains information and results from dust tests and a salt fog test conducted on various military and commercially available Lubricants applied to rifles and phosphate coated steel plates. Lubricants that were tested included synthetic and petroleum-based oils, greases and dry film lubricants. Testing was performed to determine which lubricants would give the best performance in environments of airborne dust and fine sand, high temperature and corrosive airborne salts.... Small arms, Lubricants, Dust and salt fog tests.
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Pavel Baštecký · Digital Repository (National Repository of Grey Literature) · 2012
The graph is a mathematical structure which despite its simplicity has become a perfect instrument for modeling common processes of our world. This success would not have been possible without algorithms which give deeper meaning to static structure of graph itself. With never-ending expansion of informatics science there is need for solving problems which are easy to transform to the world of vertices and edges. The goal of this document is a description of the Graph Editor program which was created to support the design and testing of graph algorithms. Text doesn't describe only the function and implementation of the editor but reader will be also familiar with the way of creating extensible application with the possibility of loading additional modules and the communication among them.
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Andrew Charles Wantuch · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2017
Abstract not provided.
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R. F. Beckwith, Ben Wood, B. Rioux et al. · 2002
A pseudorandom test environment that utilizes existing self-checking directed tests is presented. A dynamic weighting scheme selects tests to run where the tests are independently configured and the configurations are subject to user constraints. To ensure reproducibility, test selection and configuration derive from a single random seed. The presented framework is capable of running several test instances concurrently. An amalgamation of tests running within the framework effectively synthesizes much more complex test scenarios, which need not be preconceived or generated in any other way. This approach provides the capability of more completely exercising a design with a pre-existing test suite. Additional features and capabilities are also discussed.
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2008
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Yves Le Traon, Tao Xie · Software Testing Verification and Reliability · 2023
This issue contains two papers. These papers focus on test infrastructure and testing environment, respectively. Falling into the category of Software Note, the first paper, “JUGE: An infrastructure for benchmarking Java unit test generators” by Xavier Devroey, Alessio Gambi, Juan Pablo Galeotti, René Just, Fitsum Kifetew, Annibale Panichella and Sebastiano Panichella, presents JUnit Generation Benchmarking Infrastructure (JUGE), which supports test generators (such as search-based, random-based and symbolic execution) by automating the production of unit tests for validation, regression testing, fault localization and so on. JUGE aims to reduce the overall benchmarking effort, ease the comparison of multiple generators and enhance the knowledge transfer between academia and industry. JUGE was used and evolved during multiple editions of a unit testing tool competition since 2013. The authors discuss the expected impact of JUGE in improving the knowledge transfer on tools and approaches for test generation between academia and industry (recommended by Marc Roper). Falling into the typical category of Research Article, the second paper, “Test environments for large-scale software systems—An industrial study of intrinsic and extrinsic success factors” by Torvald Mårtensson, Göran Ancher and Daniel Ståhl, presents a study that investigates the characteristics of a test environment to support an organisation's testing objectives. The study includes a series of interviews with 30 individuals, a series of focus groups with 31 individuals and a cross-company workshop with 30 participants from five large-scale companies in different industry segments. The study findings reveal a list of success factors, including (1) characteristics and capabilities existing within a test environment (intrinsic success factors) and (2) properties not inherent to the test environment, but still vital for a successfully implemented test environment (extrinsic success factors). All the five companies included in the study well acknowledge the reported list of intrinsic and extrinsic success factors (recommended by Per Runeson).
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Alapuranen, Samuel · Theseus (Ammattikorkeakoulujen) · 2024
This thesis project has been part of my work at Nokia. It has challenged me in many ways. I have learned about sustainability and that even challenging projects can be finished. The project was topical for our team because this project was the introduction of Multibox for our team. After the project Multibox can be involved in other test lines. The Multibox gave our team an opportunity to do tests where we make configuration for multiple calls. The goal of this project was to verify set test cases that use Multibox. This project is located to new test environment LaaS, which is an abbreviation for Lab as a Service. The environment is new and it means that there are still some challenges with it. The new environment brings good potential for test lines. This can be seen as LaaS makes the environment better for remote control. \nNokia’s internal material and manufacture’s specification for Multibox have been used in this project. \nAfter the test case verification test line moves to other team members to finish other test cases. To improve future advancements, there is room for optimizing the capitalization of Multibox. In example adding more phones to environment. \nThe results of the tests verify the functionality of Multibox.
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Yan Liu (25061), Yan Qu (682614) · Figshare · 2024
<div><p>The continuous development of science and technology has led to the gradual digitization and intelligence of campus construction. To apply facial recognition technology to construct smart libraries in higher education, this study optimizes traditional facial recognition algorithm models. Firstly, a smart management system for university libraries is designed with facial recognition as the core, and secondly, the traditional FaceNet network is optimized. Combined with MobileNet, Attention mechanism, Receptive field module and Mish activation function, the improved multitask face recognition convolutional neural network is built and used in the construction of university smart library. The performance verification of the constructed model shows that the feature matching error value of the model in a stable state is only 0.04. The recognition accuracy in the dataset is as high as 99.05%, with a recognition error as low as 0.51%. The facial recognition model used in university smart libraries can achieve 97.6% teacher satisfaction and 96.8% student satisfaction. In summary, the facial recognition model constructed by this paper has good recognition performance and can provide effective technical support for the construction of smart libraries.</p></div>
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Ferenc Domes, Martin Fuchs, Hermann Schichl et al. · Optimization and Engineering · 2013
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Naik, Trupti Deepak · CSUN ScholarWorks (California State University, Northridge) · 2015
Manual verification in industry testing is a very complex and tedious process.Verification test engineers need to carefully go through various application screens, make the correct oscilloscope setups to get the expected results, try various input combinations and compare the results with the expected behavior.Furthermore, this type of testing is repetitive in nature.With the introduction of the new chips and/or new firmware releases, Automatic Test Environment (ATE) is becoming widely used to address the limitations of the traditional verification testing methods.This project focuses on creating an automated test environment for Solid State Devices (SSD) hardware verification testing.The project will contribute in making the tedious process of manual testing simpler and more time efficient for verification engineers.The project is implemented using Python Scripting Language and Test Environment Suite libraries from Agilent Command Expert tool.It sends Standard v Commands for Programmable Instruments (SCPI) commands to instruments like Oscilloscope, power supplies, etc.The project automates both the test setup and the documentation of the test results.
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