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28 results for “Performance Engineering”
Acquired data necessary to perform the control algorithm introduced in the scientific paper: "Multilevel control of an anthropomorphic prosthetic hand for grasp and slip prevention" (Advances in Mechanical Engineering, 2016, vol. 8, pp. 1-13)
<p>Acquired data necessary to perform the control algorithm introduced in this paper.</p> <p>a) Figure 6: Calibration data for the three FSRs placed on the prosthetic hand and covered with silicon caps.<br> b) Figure 9: Data for the cost during the learning of two grasping tasks of an egg: bi-digital grasp and tri-digital grasp.<br> c) Figure 10 and Figure 11: Data for the experimental results with the plastic cup and with the highlighter shown in the paper.<br> </p> <p> </p>
Solvent Engineered Synthesis of SnO Nanoparticles for High-Performance Anodes
<p>Batteries are the most abundant form of electrochemical energy storage. Lithium and sodium ion batteries account for a significant portion of the battery market, but high-performance electrochemically active materials still need to be discovered and optimized for these technologies. Recently, tin(II) oxide (SnO) has emerged as a highly-promising battery electrode. In this work, we present a facile synthesis method to produce SnO nanoparticles whose size and shape can be tailored by changing the solvent nature. We study the complex relationship between wet chemistry synthesis conditions and resulting nanoparticle morphology. Furthermore, high-level electronic structure theory, including dispersion corrections to account for van der Waals forces, are employed to augment our understanding of the underlying chemical mechanisms. The electronic vacuum alignment and surface energies are determined, allowing the prediction of the thermodynamically-favoured crystal shape (Wulff construction) and surface-weighted work function. Finally, the synthesized nanomaterials were tested as Li-ion battery anodes, demonstrating significantly enhanced electrochemical performance for morphologies obtained from specific synthesis conditions. </p> <p>Open-access publication in npj 2D Mater & Appl <a href="https://rdcu.be/cgdWZ">here</a>.</p>
Performance results of different scheduling algorithms used in the simulation of a modern game engine
<p><strong>Performance results of different scheduling algorithms used in the simulation of a modern game engine</strong></p> <p>These results are a companion to the paper entitled "<em>Exploring scheduling algorithms for parallel task graphs: a modern game engine case study</em>" by M. Regragui et al.</p> <p><strong>General information</strong></p> <p>This dataset contains raw outputs and scripts to visualize and analyze the scheduling results from our game engine simulator.<br> The result analysis can be directly reproduced using the script run_analysis.sh. A series of Jupyter Notebook files are also available to help visualize the results.</p> <p><strong>File information</strong></p> <p>- All Scenario*.ipynb files contain python scripts to visualize and analyze the simulation results.<br> - The Scenario*.py files contain python scripts that can be run directly with Jupyter Notebook.<br> - The requirements.txt file contains the names and versions of python packages necessary to reproduce the analysis.<br> - The run_analysis.sh file contains a bash script to install the required python packages and run the Scenario*.py scripts.</p> <p>The results are organized in five folders:</p> <p>1. Result_1 contains the results for Scenario 1 generated using file input_scenario_1.txt.<br> 2. Result_2 contains the results for Scenario 2 generated using file input_scenario_2.txt.<br> 3. Result_3 contains the results for Scenario 3 generated using file input_scenario_3.txt.<br> 4. Result_CP_1 contains the results for the critical path of Scenarios 1 and 2 generated using file input_CP_scenario_1.txt.<br> 5. Result_CP_3 contains the results for the critical path of Scenario 3 generated using file input_CP_scenario_3.txt.</p> <p>Each result file (e.g., HLF_NonSorted_Random_1_200_10.txt) contains 200 lines representing information of the 200 frames that were simulated. Each line contains four values: the frame number, the duration of the frame (in microseconds), a critical path estimation for the previous frame (in microseconds), and the load parameter (value between 0 and 1).</p> <p>The outputs of this analysis include some PDF files representing the figures in the paper (in order) and some CSV files representing the values shown in tables. The standard output shows the p-values computed in parts of the statistical analysis.</p> <p><strong>Software and hardware information</strong></p> <p>The simulation results were generated on an Intel Core i7-1185G7 processor, with 32 GB of LPDDR4 RAM (3200 MHz). The machine ran on Ubuntu 20.04.3 LTS (5.14.0-1034-oem), and g++ 9.4.0 was used for the simulator's compilation (-O3 flag).</p> <p>The results were analyzed using Python 3.8.10, pip 20.0.2 and jupyter-notebook 6.0.3. The following packages and their respective versions were used:</p> <p>- pandas 1.3.2<br> - numpy 1.21.2<br> - matplotlib 3.4.3<br> - seaborn 0.11.2<br> - scipy 1.7.1<br> - pytz 2019.3<br> - python-dateutil 2.7.3<br> - kiwisolver 1.3.2 <br> - pyparsing 2.4.7 <br> - cycler 0.10.0 <br> - Pillow 7.0.0<br> - six 1.14.0 </p> <p><strong>Simulation information</strong></p> <p>Simulation results were generated from 4 to 20 resources. Each configuration was run with 50 different RNG seeds (1 up to 50).</p> <p>Each simulation is composed of 200 frames. The load parameter (lag) starts at zero and increases by 0.01 with each frame up to a value equal to 100% in frame 101. After that, the load parameter starts to decrease in the same rhythm down to 0.01 in frame 200.</p> <p><strong>Algorithms abbreviation in presentation order</strong></p> <p>FIFO serves as the baseline for comparisons.</p> <p>1. FIFO: First In First Out.<br> 2. LPT: Longest Processing Time First.<br> 3. SPT: Shortest Processing Time First.<br> 4. SLPT: LPT at a subtask level.<br> 5. SSPT: SPT at a subtask level.<br> 6. HRRN: Highest Response Ratio Next. <br> 7. WT: Longest Waiting Time First.<br> 8. HLF: Hu's Level First with unitary processing time of each task.<br> 9. HLFET: HLF with estimated times.<br> 10. CG: Coffman-Graham's Algorithm.<br> 11. DCP: Dynamic Critical Path Priority.</p> <p><strong>Metrics</strong></p> <p>* SF: slowest frame (maximum frame execution time)<br> * DF: number of delayed frames (with 16.667 ms as the due date)<br> * CS: cumulative slowdown (with 16.667 ms as the due date)<br> </p>
Dataset: Pacer BlueStar Engineering the Future ETF (BULD) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Data set of paper Model-Driven System-Performance Engineering for Cyber-Physical Systems
<p>This data set contains the raw and processed data of the paper <em>Model-Driven System-Performance Engineering for Cyber-Physical Systems</em>, published in the proceedings of ESWEEK’21.</p>
Engineering Fano-resonant hybrid metastructures with ultra-high sensing performances
<p>Here the data related to our recent work that uses metasurfaces designed on metamaterials to excite Fano resonances and Rabi Split analogue modes for sensing.</p> <p> </p> <p>In this repository the following data are available:</p> <ul> <li>The Reflectance, Transmittance and Absorbance (1-T-R) evaluated over all the diffraction angles (from 0° to 89°) for the proposed structure (ring + cross) and the other tested structures, available in the .mat file.</li> <li>The .m file to repeat all the simulations are available in main folder. The available Matlab codes allow reproducing numerical simulations using Reticolo (RCWA) as the main framework to do the computation.</li> <li>Use "getrefractiveindex.m" to interpolate refractive index on finest wavelength range. Please, note that according to the uploaded codes this function have to be in the same folder of the loaded refractive indices. </li> <li>You can use the function "textprogressbar.m" to get a progress bar in real time to know the status of the current simulation. Please, note that this function have to stay in the "/RETICOLO V8/reticolo_allege" folder. </li> <li>One of the available Matlab code allows displaying the electric and magnetic field evaluated in the structure section or on the top view. </li> <li>The sensing test performed for the reported structures using different surrounding medium, for this purpose it is possible to use the codes that allow studying the parameters variation, the incident angle variation or just a single run changing the refractive index of the surrounding medium. </li> </ul> <p>The proposed code works using the Reticolo main code. To download it please visit the following link <a href="https://www.lp2n.institutoptique.fr/light-complex-nanostructures">https://www.lp2n.institutoptique.fr/light-complex-nanostructures</a> or using Zenodo <a href="https://zenodo.org/record/5905381#.Y8rvbC9abpA">https://zenodo.org/record/5905381#.Y8rvbC9abpA</a></p> <p>Once Reticolo has been downloaded copy and paste its path in the proposed Matlab code for Fano resonances on ENZ cavities as reported in the example codes.</p> <p>In this repository you will find the refractive indices that have been used.</p>
HPC-GAP: Engineering a 21st-Century High-Performance Computer Algebra System
<p>Data for the experiments conducted in the paper</p>
Development of Novel Ultra-High Performance Engineered Cementitious Composites (UHP-ECC) for Durable and Resilient Transportation Infrastructure
<p>The objective of this study was to develop novel UHP-ECC materials utilizing readily available ingredients in Region 6 for the construction and repair of transportation infrastructure. Phase one of this study focused on the development of ultra-high strength cementitious matrices by evaluating the effects of ingredient selection and mixture proportioning on the materials’ compressive strength. Variables evaluated included the mass ratios of silica fume to fly ash (SF/FA), supplementary cementitious materials to cement (SCMs/C), and ordinary sand to microsilica sand (OS/MS). Phase two of the study focused on the development of UHP-ECC materials. To this end, based on the knowledge gained from phase one, two ultra-high strength cementitious matrices (one with and one without SF) were formulated and their fracture properties were evaluated through fracture toughness test. Furthermore, fiber-bridging properties of ultra-high-molecular-weight (UHMW) polyethylene (PE) fiber in the developed cementitious matrices were evaluated through single crack tensile test (SCTT). Four different composites were produced by reinforcing the selected cementitious matrices with 1.5 and 2 vol.% UHMW PE fiber. Fresh and hardened properties of the developed composites were assessed by means of flowability test, compressive strength test, uniaxial tensile test, and flexural performance test. Results from phase one showed that SF/FA had the most relevant effect on compressive strength, followed by SCMs/C, and OS/MS. Furthermore, increments in SF/FA produced improvements in strength, whereas increments in SCMs/C and OS/MS reduced strength. Experimental results from phase two indicated that the use of SF and the increase in fiber content generally had a negative effect on the fresh and hardened properties of the composites. These observations were credited to a worsening fiber distribution when using silica fume and/or increasing fiber content. Three UHP-ECC materials utilizing readily available ingredients were successfully developed (i.e., mixtures FA25-f1.5, FA25-f2, and FA20SF5-f2). These materials simultaneously exhibited ultra-high compressive strength (>120 MPa) and ECC-like ductility (tensile strain capacity >2%). The average crack width for all mixtures ranged between 61-131 μm. Mixture FA25-f1.5, which displayed the best mechanical properties, exhibited a compressive strength of 133.1 MPa, flexural strength of 21.4 MPa, tensile strength of 10.3 MPa, tensile strain capacity of 4.3%, and an average crack width of 115.3 μm. Importantly, this mixture did not incorporate silica fume or microsilica sand and used low fiber content (i.e., 1.5 vol.%).</p>
Evaluation of the Performance and Cost-Effectiveness of Engineered Cementitious Composites (ECC) Produced from Region 6 Local Materials
<p>Corresponding data set for Tran-SET Project No. 17CLSU05. Abstract of the final report is stated below for reference:</p> <p>"The project objective is to develop cost-effective Engineered Cementitious Composites (ECC) with locally available ingredients in Region 6 to address the deficiencies observed in ordinary concrete materials. The study explored the utilization of two types of river sands (coarse and fine), two types of PVA fibers (long and short), four levels of cement replacement with Class F fly ash, and the implementation of recycled crumb rubber in the performance of ECC materials. A total of 24 mix designs were prepared and evaluated in compression, tension, and bending to assess its mechanical properties. Furthermore, the cracking characteristics of the materials produced were evaluated to assess the durability potential of these composites. Lastly, the cost of each mix design and the feasibility of ECC implementation in transportation infrastructure were assessed. The experimental results showed that implementing crumb rubber and/or increasing contents of fly ash in the mixtures produced a positive impact in the ductility of the materials. However, a tradeoff between ductility and strength was observed. Furthermore, the utilization of the different types of sand evaluated in this study produced minor effects in the mechanical properties of ECCs evaluated. The properties of the materials developed in this study were exceedingly superior than that of regular concrete. It was concluded that ECC materials are promising for the future of transportation infrastructure."</p>
Development of Ultra-High Performance Engineered Geopolymer Composites (UHP-EGCs)
<p>This study investigated the possibility of developing novel UHP-EGC materials for the repair and new construction of transportation infrastructure in Region 6 by utilizing locally available resources. To this end, the geopolymers (GPs) in this study were synthesized by activating metakaolin (MK) with potassium silicate and sodium silicate solutions. The solutions were manufactured in the laboratory by dissolving silica fume and potassium hydroxide (KOH) or sodium hydroxide (NaOH) in deionized water. MK-based GP binders, mortars, and fiber-reinforced composites were manufactured and evaluated to determine their density, compressive strength, tensile properties, and slant shear bond strength to Portland cement concrete (PCC). Based on the experimental findings, it was concluded that both MG7500 and FA4404 admixtures improved the workability but reduced the compressive strength of the GP. The inclusion of both microsilica sand and UHMWPE fibers (i.e., plasma-treated and pristine UHMWPE fibers) led to an improvement in compressive strength. Plasma-treated UHMWPE fibers exhibited a higher compressive strength compared to pristine UHMWPE fibers. The uniaxial tensile test results revealed that the composites with pristine and plasma-treated UHMWPE fibers at 1.5 vol.% exhibited robust pseudo-strain hardening (PSH) behavior. Furthermore, the best-performing composite (i.e., composite with plasma-treated fibers) exhibited a tensile strength and strain capacity of 6.65 MPa and 6.26%, respectively. The slant shear test revealed that all the materials passed the minimum requirement (i.e., 28-day shear bond strength greater than 13 MPa) to be used as a repair material. While the compressive strength of the developed GP composites using different techniques reached up to 73 MPa, future research should be directed toward the evaluation of hybrid systems (such as MK and slag) to achieve a compressive strength greater than 120 MPa.</p>
Resilient 3D-Printed Civil Infrastructure with Ultra-High Performance Engineered Cementitious Composites (UHPECCs)
<p>This study aims to develop and evaluate UHP-ECC materials for 3DP applications. To achieve this, the rheological properties of the cementitious composites were designed to accommodate 3DP functionality. Additionally, this study aimed to evaluate the hardened properties of the 3D-printed UHP-ECCs and compare them to the cast UHP-ECCs. Furthermore, the effect of variables such as sand-to-binder (S/B), fly ash-to-cement ratio (FA/C), and high-range water reducer (HRWR) content on the fresh and hardened properties of the 3D printable mixtures were evaluated. Fresh properties of mixtures were assessed by means of the flowability test, setting time test, and printability test. Hardened properties were assessed utilizing the compressive strength test, uniaxial tensile test, and flexural performance test. Experimental results showed that the flow and setting time of the composites reduced as S/B incremented while having the opposite reaction with an increase in FA/C or HRWR. Additionally, a range of initial spread diameter values from 127 to 136 mm was related to the printable mixtures. Moreover, pseudo-strain-hardening (PSH) behavior was observed for all mixtures during the uniaxial tensile test. It is important to note that mixture FA<sub>67</sub>S/B<sub>1</sub>(2.2) developed in this study, showed an exceptional tensile strain of 2.1%, along with a compressive strength of 91.9 MPa, a tensile strength of 5.3 MPa, and flexural strength of 13.6 MPa. Finally, the printed specimens showed significant anisotropic behavior when compared to cast specimens, displaying a reduction in compressive strength ranging from 14.5% to 37.5% when tested in the perpendicular, longitudinal, and lateral directions, as well as an increment in flexural strength ranging from 4.8% to 11.7% when tested in the perpendicular and lateral directions.</p>
Experimental Data for "What Makes a Top-Performing Precision Medicine Search Engine? Tracing Main System Features in a Systematic Way" at SIGIR2020
<p>This deposit contains data used for the experiments reported in the paper "<a href="https://doi.org/10.1145/3397271.3401048">What Makes a Top-Performing Precision Medicine Search Engine? Tracing Main System Features in a Systematic Way</a>", most notably the ElasticSearch 5.4 indices used for the reported experiments.</p> <p>To load the indices into an ElasticSearch cluster of your own, use the restore function described in the <a href="https://www.elastic.co/guide/en/elasticsearch/reference/5.4/modules-snapshots.html">ElasticSearch documentation</a>.</p> <p>The names of the index snapshots contained here are</p> <ul> <li>ct1718 for the indexed ClinicalTrials data used in the TREC-PM challenges in <a href="http://www.trec-cds.org/2017.html">2017</a> and <a href="http://www.trec-cds.org/2018.html">2018</a>.</li> <li>ct19 for the indexed ClinicalTrials data used in the TREC-PM challenge in <a href="http://www.trec-cds.org/2019.html">2019</a>.</li> <li>ba1718 for the indexed PubMed data used in the TREC-PM challenges in <a href="http://www.trec-cds.org/2017.html">2017</a> and <a href="http://www.trec-cds.org/2018.html">2018</a>.</li> <li>ba19 for the indexed PubMed data used in the TREC-PM challenge in <a href="http://www.trec-cds.org/2019.html">2019</a>.</li> </ul> <p>The other file contains the original output that <a href="https://www.automl.org/automated-algorithm-design/algorithm-configuration/smac/">SMAC</a> wrote to disc during the parameter optimization process. There are directories for the biomedical abstracts (BA) and clinical trials (ct) and for each respective 10 fold cross validation split. Those file contain the exact parameter configurations and their evalation score (the infNDCG metric was used) in live-runXX.json files.</p> <p>The code to these files is located in <a href="https://zenodo.org/record/3856403">this Zenodo deposit</a>.</p>
Supplementary Data for "Exploring structure-function relationships in engineered receptor performance using computational structure prediction"
<p>These data are supplementary data for the manuscript "<strong>Exploring structure-function relationships in engineered receptor performance using computational structure prediction</strong>", which has been submitted for consideration for publication. These data include protein structure predictions used in this study.</p>
How Tertiary Studies perform Quality Assessment of Secondary Studies in Software Engineering - Replication Package
<p>Replication Package for the paper:</p> <p>D. Costal, C. Farré, X. Franch, C. Quer. 2021. How Tertiary Studies perform Quality Assessment of Secondary Studies in Software Engineering. CIbSE 2021.</p> <p>Please refer to the above paper if you want to cite/use this data.</p>
Supplementary Material for "Engineering of a β-galactosidase from Bacillus coagulans to relieve product inhibition and improve hydrolysis performance""
<p><a href="https://zenodo.org/record/5109535">Suppl. Information</a> Tab. S1<a href="https://zenodo.org/record/5109535">:</a> Primers of alanine scanning</p> <p><a href="https://zenodo.org/record/5109535">Suppl. Information</a> Tab. S2<a href="https://zenodo.org/record/5109535">:</a> Primers of N148 saturation mutation</p> <p><a href="https://zenodo.org/record/5109535">Suppl. Information</a> Fig. S1<a href="https://zenodo.org/record/5109535">:</a> Reaction mechanism of β-galactosidase.</p> <p> </p>
Automated refactoring actions for performance improvement in component-based software engineering
<p>Dataset of UML models randomly generated to validate the portfolio of refactoring actions.</p>
The Effect of Pilates exercıses on Engine Performance and Body Composition ın Primary School Children
ClinicalTrials.gov study NCT05520502. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Optimized modelling and application of exhaust gas recirculation performance evaluation of turbocharged diesel engine
Aimed at the problem of turbocharged diesel engine EGR (exhaust gas recirculation) performance evaluation and optimal EGR rate determination, especially in some cases with poor data because of the limit of conditions, an optimized multi-objective grey decision method based on grey theory and entropy weight is proposed. The internal combustion pressure ,fuel consumption rate, NOX ,CO and smoke degree were selected as the decision target, and the initial decision-making model was established based on traditional grey situation theory. According to the characteristics and optimization requirements of EGR, The optimal compromise between combustion and emission performance is proposed to transform into the decision-making target weight problem , then a subjective weight optimization method based on expert scoring and grey relational analysis is proposed. In addition, the entropy weight method was used to solve the subjective and objective weight vector and the optimized multi-objective grey situation decision making model was established, which can not weaken the human error of subjective empowerment, but also fully explore the intrinsic objective relationship of the evaluation index parameters. At last, an optimization simulation platform for EGR performance evaluation based MATLB/GUIDE is designed and established. The results show that the optimization simulation platform can effectively improve the efficiency of simulation calculation, which is more convenient for practical engineering applications; the optimized method can successfully solve the EGR performance evaluation and optimal EGR rate determination under different working conditions, the decision result is reasonable and consistent with the prevailing principle of the EGR determining, which provide a new research ideas for EGR performance optimization.
Data from: Experimental study on diesel engine EGR performance and Optimum EGR Rate Determination Method
In order to study deeply the Exhaust gas recirculation(EGR)performance of marine diesel engines,a venturi high-pressure exhaust gas recirculation device was established to overcome the exhaust gas reflow problem in a certain type turbocharged diesel engine. With the device, the EGR performance test is accomplished and an optimal EGR decision-making optimization method based on grey correlation coefficient modified is proposed. The results show that the venturi tube EGR can basically meet the injection requirements of high-pressure exhaust gas and makes good results to the diesel engine . Through the venturi tube EGR, the NOX emissions reduces significantly with the maximum drop of 30.6%. The explosive pressure in cylinder reduces with the EGR rate increases, and the cylinder pressure curve shows a single peak at low-speed conditions and double peaks at high-speed condition. However, the fuel consumption rate, NO, and smoke have been negatively affected. Due to small samples, the traditional evaluation method is difficult to determine the optimal EGR rate reasonably, while the proposed method can effectively solve this problem. It can weaken the shortcomings of subjective judgment and greatly improve the rationality of decision-making results.
Dataset: Altair Engineering Inc. (ALTR) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.