Standards Research Data
This dataset contains data from Experiments 1 and 2.
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Research cultures are crucial to fostering a culture of information sharing, cooperation, and learning in the sciences so that scientists can remain competitive and stay ahead of their rivals. Impact factors are essential metrics for evaluating the quality and significance of a journal's research. As a result, we can determine the relative value of various publications and promote a more competitive research environment.
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This data package（.zip） includes data of follower robots' motion track、errors and velocities in five simulatd experimental cases：(1),(2): set obstacle range on 0.8m and 1.0m，2 groups；(3): oneside situation, and the number of follower robots rises to 5. (4)：complex environment, which we place more obstacles. （5): change the lead-follower formation （6),(7)：two types of formation tracks, circle and straight line，compare follower1，2.
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This dataport will be useful to those interested in visual design for complex physics phenomena. We have included two quantum physics data sample datasets and our empirical study results.
(1) evaluation results from two experiments (20 participants in each and 40 in total) to empirically validate that separable bivariate pairs of large-magnitude-range vector
magnitude representations are more efficient than integral pairs.
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Code smells are the result of poor design choices within software systems that complexify source code and impede evolution and performance. Therefore, detecting code smells within software systems is an important priority to decrease technical debt. Furthermore, the emergence of mobile applications (apps) has brought new types of Android-specific code smells, which relate to limitations and constraints on resources like memory, performance and energy consumption.
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The dataset of stealth and nonstealth aircraft at 2 GHz is used in the simulation experiment of our paper.
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This data set is used for the test of 400 * 400 experiment in the paper. And, related parameters are set in the paper and code.
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Gestational diabetes is a type of high blood sugar that develops during pregnancy. It can occur at any stage of pregnancy and cause problems for both the mother and the baby, during and after birth. The risks can be reduced if they are early detected and managed, especially in areas where only periodic tests of pregnant women are available. Intelligent systems designed by machine learning algorithms are remodelling all fields of our lives, including the healthcare system. This study proposes a combined prediction model to diagnose gestational diabetes.
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Adhesion property measurements contribute to the comprehensive understanding of the mechanical properties of soft matters. Indentation tests are a common method for measuring adhesion force. However, indenters generally have a large volume and a small sensing angle and thus are not conducive to local detection in high-precision environments.
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4 Views