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33 results for “Objective Function”
Patterns of object play behaviour and its functional implications in free-flying ravens (supplementary data)
<p>This resource contains the processed data sets and R scripts associated with the article titled "Patterns of object play behaviour and its functional implications in free-flying ravens" authored by Awani Bapat, Anna E Kempf, Salome Friry, Palmyre H Boucherie, Thomas Bugnyar, published in Scientific Reports on 02-01-2025.</p>
The Experimental Data for the Study "Frequency Fitness Assignment: Making Optimization Algorithms Invariant under Bijective Transformations of the Objective Function Value"
<p>The Experimental Data for the Study "Frequency Fitness Assignment: Making Optimization Algorithms Invariant under Bijective Transformations of the Objective Function Value"</p> <p><strong>1. Introduction</strong></p> <p>Frequency Fitness Assignment (FFA) replaces the objective value in the selection step of an optimization method with its encounter frequency in any selection step so far. It turns static problems into dynamic ones. Here we experimentally investigated this approach in two important contexts: First, we integrated it into a basic (1+1)-EA, obtaining the (1+1)-FEA. We applied both algorithms to several well-known benchmark problems with bit-string based search spaces, including the OneMax, LeadingOnes, TwoMax, Jump, Plateau, and W-Model functions. We also applied them to the Max-3-Sat instances from SATLib. We then also integrated FFA into a Memetic Algorithm for the Job Shop Problem.</p> <p><strong>2. Paper</strong></p> <p>This data is used as the basis for the following article: Thomas Weise, Zhize Wu, Xinlu Li, and Yan Chen. Frequency Fitness Assignment: Making Optimization Algorithms Invariant under Bijective Transformations of the Objective Function Value, originally submitted to <a href="https://arxiv.org/abs/2001.01416">arxiv</a> on 2020-01-06 (under the title Frequency Fitness Assignment: Making Optimization Algorithms Invariant under Bijective Transformations of the Objective Function), updated with the new data in June 2020, and submitted to the IEEE Transactions on Evolutionary Computation.</p> <p><strong>3. Data</strong></p> <p>This data set contains all the results of these experiments, the source codes used in the experiments (i.e., the algorithm implementations), as well as the scripts used for evaluating the results.</p> <p><strong>4. Version History</strong></p> <p>This is the second version of the data set, including extended experiments and more evaluation results. Most importantly, data for larger scales of OneMax and LeadingOnes has been added. The original version is at <a href="http://dx.doi.org/10.5281/zenodo.3598172">10.5281/zenodo.3598172</a>.</p> <p><strong>5. Contact</strong></p> <p>If you have any questions or suggestions, please contact <a href="http://iao.hfuu.edu.cn/team/director">Prof. Dr. Thomas Weise</a> of the <a href="http://iao.hfuu.edu.cn/">Institute of Applied Optimization</a> at <a href="http://www.hfuu.edu.cn">Hefei University</a> in Hefei, Anhui, China via email to <a href="mailto:tweise@hfuu.edu.cn">tweise@hfuu.edu.cn</a> with CC to <a href="mailto:tweise@ustc.edu.cn">tweise@ustc.edu.cn</a>.</p>
Data/Code: Objective monitoring of functional recovery after total knee and hip arthroplasty using sensor-derived gait measures
<p>Abstract</p> <p>Background: Inertial sensors hold the promise to objectively measure functional recovery after total knee (TKA) and hip arthroplasty (THA), but their value in addition to patient-reported outcome measures (PROMs) has yet to be demonstrated. This study investigated recovery of gait after TKA and THA using inertial sensors, and compared results to recovery of self-reported scores of pain and function.</p> <p>Methods: PROMs and gait parameters were assessed before and at two and fifteen months after TKA (n=24) and THA (n=24). Gait parameters were compared with healthy individuals (n=27) of similar age. Gait data were collected using inertial sensors on the feet, lower back, and trunk. Participants walked for two minutes back and forth over a 6m walkway with 180° turns. PROMs were obtained using the Knee Injury and Osteoarthritis Outcome Scores and Hip Disability and Osteoarthritis Outcome Score.</p> <p>Results: Gait parameters recovered to the level of healthy controls after both TKA and THA. Early improvements were found in gait-related trunk kinematics, while spatiotemporal gait parameters mainly improved between two and fifteen months after TKA and THA. Compared to the large and early improvements found in of PROMs, these gait parameters showed a different trajectory, with a marked discordance between the outcome of both methods at two months post-operatively.</p> <p>Conclusion: Sensor-derived gait parameters were responsive to TKA and THA, showing different recovery trajectories for spatiotemporal gait parameters and gait-related trunk kinematics. Fifteen months after TKA and THA, there were no remaining gait differences with respect to healthy controls. Given the discordance in recovery trajectories between gait parameters and PROMs, sensor-derived gait parameters seem to carry relevant information for evaluation of physical function that is not captured by self-reported scores.</p>
Support Material for: S.I. Mimilakis et al., ``Examining the Perceptual Effect of Alternative Objective Functions for Deep Learning Based Music Source Separation''
<p>The audio corpus used for conducting the listening tests reported in S.I. Mimilakis et al., ``Examining the Perceptual Effect of Alternative Objective Functions for Deep Learning Based Music Source Separation''.</p>
The dilemma of objective function selection for sensitivity and uncertainty analyses of semi-distributed hydrologic models across spatial and temporal scales
Open the record for dataset details and reuse information.
Implementation and Results of a Randomized Local Search on the 2D Rectangular Bin Packing Problem with Item Rotation using Different Objective Functions
<p><strong><em>1. Introduction</em></strong></p> <p>In this archive, we provide the implementation and experimental results of a Randomized Local Search (RLS) applied to the two-dimensional bin packing problem without orientation (where items can be rotated by 90 degrees). As benchmark dataset, we use the <code>beng</code>, <code>A</code>, and <code>class</code> instances from <a href="https://site.unibo.it/operations-research/en/research/2dpacklib">2DPackLib</a> as well as the four non-trivial Almost Squares in Almost Squares (<a href="https://math.vu.nl/~sbhulai/publications/data_analytics2016b.pdf"><code>Asqas</code></a>) instances</p> <p>These are the data used in the paper below, which contains the exact specification of all algorithms, objective functions, and the encoding we applied.</p> <p>Rui Zhao, Tianyu Liang, Zhize Wu, Daan van den Berg, Matthias Thürer, and Thomas Weise. 2024. Randomized Local Search on the 2D Rectangular Bin Packing Problem with Item Rotation. In <em>Genetic and Evolutionary Computation Conference (GECCO'24 Companion),</em> July 14–18, 2024, Melbourne, VIC, Australia. ACM, New York, NY, USA, 4 pages. doi:<a href="https://doi.org/10.1145/3638530.3654139">10.1145/3638530.3654139</a>.</p> <p>To run the experiments, you need <a href="https://thomasweise.github.io/moptipyapps">moptipyapps</a> version 0.8.34 and <a href="https://thomasweise.github.io/moptipy">moptipy</a> version 0.9.98, which contain the actual algorithm implementations. Both packages are available on GitHub and on PyPI. However, we include several versions of them in the folder <code>source/packages</code>, just in case.</p> <p><strong><em>2. Directory Structure</em></strong></p> <p>This archive contains the following directories:</p> <ul> <li><code>source</code> contains the Python source codes needed to run the experiment.</li> <li><code>source/packages</code> contains the source codes of the Python packages with the actual algorithm implementations.</li> <li><code>data</code> is the directory with the results and their evaluation.</li> <li><code>data/results</code> is the directory with the log files generated by the experiment. In this folder, there are two sub-folders, <code>ibf1</code> and <code>ibf2</code>. We tested two different encodings, but found that the second one (<code>ibf2</code>) is too slow to do meaningful experiments. Thus, the experiments with it were abandoned and only one objective function was tested. We include <code>ibf2</code> for the sake of completeness, whereas <code>ibf1</code> was used in our paper. Either way, both <code>ibfX</code> folders contain one directory for each objective function applied to them. In each such directory, there is one folder (for the single algorithm applied) and this folder, in return, contains one folder per benchmark instance. The benchmark instance folders contain the three log files of the three runs that we applied to each instance/algorithm/objective combination.<br>Each log file contains information of one run, i.e., one execution of one algorithm on one problem instance. All improving moves of a run as well as the final solution are stored in the log file.</li> <li><code>data/evaluator</code> is the folder containing Python scripts that were used to evaluate these results. Two scripts are provided: <code>evaluator_short.py</code> was used for generating the tables used in the final paper version. <code>evaluator_full.py</code> provides larger tables, which could not be included in the final paper due to space reasons.</li> <li>Folder <code>evaluation_full</code> was generated using <code>evaluator_full.py</code> and contains tables and figures and a result summary in CSV format.</li> <li>Folder <code>evaluation_short</code> was generated using <code>evaluator_short.py</code> and contains both the tables used in the paper as well as a result summary in CSV format.</li> </ul> <p><strong><em>3. License</em></strong></p> <p>The files in this repository are under the <a href="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</a>, with the exception of the files of <a href="https://site.unibo.it/operations-research/en/research/2dpacklib">2DPackLib</a> and other benchmark datasets included, which are under copyright of their respective owner (we believe that they are in the public domain, as they are provided by many sources, included in many software packages under various open source licenses, and on many websites). The license is contained as file <code>LICENSE.txt</code> in this archive.</p> <p><strong><em>4. Contact</em></strong></p> <p>If you have any questions or suggestions, please contact</p> <p>Mr. Rui ZHAO (赵睿) of the Institute of Applied Optimization (应用优化研究所, <a href="http://iao.hfuu.edu.cn">IAO</a>) of the School of Artificial Intelligence and Big Data (<a href="http://www.hfuu.edu.cn/aibd/">人工智能与大数据学院</a>) at <a href="http://www.hfuu.edu.cn/english/">Hefei University</a> (<a href="http://www.hfuu.edu.cn/">合肥大学</a>) in Hefei, Anhui, China (中国安徽省合肥市) via email to <a href="mailto:zr1329142665@163.com">zr1329142665@163.com</a>.</p>
Hydrograph and Recession Flows Predictions Simulations using Deep Learning: Watershed Uniqueness and Objective Functions
<p>This resource contains the results presented in the paper titled 'Hydrograph and Recession Flows Simulations using Deep Learning: Watershed Uniqueness and Objective Functions' by Abhinav Gupta and Sean McKenna.<span><span><br></span></span></p> <p>'</p>
Objective Brain Function Assessment of mTBI/Concussion
ClinicalTrials.gov study NCT03963804. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Which Tools Better Predict Fall Risk in Parkinson's Disease: A Comparative Study of Objective, Self-Reported, and Functional Balance Assessment
ClinicalTrials.gov study NCT07148700. IPD Sharing: YES. Countries: 1. Publications: 10.
Objective Brain Function Assessment of mTBI/Concussion in College Athletes
ClinicalTrials.gov study NCT02477943. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Six-Minute Walking Test (6WT) and Timed-Up-and-Go (TUG) Test as Measures of Objective Functional Impairment in Patients Undergoing Interlaminar or Transforaminal Epidural Steroid Injection for Lum
ClinicalTrials.gov study NCT04062942. IPD Sharing: NO. Countries: 1. Publications: 2.
Objective Brain Function Assessment of mTBI/Concussion in High School Athletes
ClinicalTrials.gov study NCT02661633. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Supporting data for "Reducing uncertainties in urban drainage models by explicitly accounting for timing errors in objective functions"
<p>Supporting data for "Reducing uncertainties in urban drainage models by explicitly accounting for timing errors in objective functions" submitted to Water Resources Research.</p> <p>Contains:</p> <ul> <li>SWMM template files.</li> <li>Objective function values for all model runs.</li> <li>Jupyter Notebooks used to create figures and tables for the article.</li> <li>Copy of rainfall runoff data available from <a href="https://doi.org/10.5281/zenodo.3931582">https://doi.org/10.5281/zenodo.3931582</a></li> </ul> <p>For python implementations of the Hydrograph Matching Algorithm (Ewen 2011) see <a href="https://doi.org/10.5281/zenodo.3923792">https://doi.org/10.5281/zenodo.3923792</a></p> <p>Ewen, John. “Hydrograph Matching Method for Measuring Model Performance.” <em>Journal of Hydrology</em> 408, no. 1–2 (September 2011): 178–87. <a href="https://doi.org/10.1016/j.jhydrol.2011.07.038">https://doi.org/10.1016/j.jhydrol.2011.07.038</a>.</p>
Motor skills and exercise capacity are associated with objective measures of cognitive functions and academic performance in preadolescent children
<p><strong>Objective: </strong>To investigate associations between motor skills, exercise capacity and cognitive functions, and evaluate how they correlate to academic performance in mathematics and reading comprehension using standardised, objective tests.</p> <p><strong>Methods: </strong>This cross-sectional study included 423 Danish children (age: 9.29±0.35 years, 209 girls). Fine and gross motor skills were evaluated in a visuomotor accuracy-tracking task, and a whole-body coordination task, respectively. Exercise capacity was estimated from the Yo-Yo intermittent recovery level 1 children's test (YYIR1C). Selected tests from the Cambridge Neuropsychological Test Automated Battery (CANTAB) were used to assess different domains of cognitive functions, including sustained attention, spatial working memory, episodic and semantic memory, and processing speed. Linear mixed-effects models were used to investigate associations between these measures and the relationship with standard tests of academic performance in mathematics and reading comprehension.</p>
Object 4-3 List of correlations between nutrients and gene functions
<p>List of spearman correlations with R> 0.7 or < -0.7 and P<0.05.</p>
Understanding the Preferences and Views of Older Adults on the Use of Geriatric and Objective Functional Assessments for Cancer Treatment Planning.
ClinicalTrials.gov study NCT06652347. IPD Sharing: NO. Countries: 1. Publications: 0.
Objective Assessment of Upper Extremity Functioning of Stroke Patients Before and After Rehabilitation
ClinicalTrials.gov study NCT02092662. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Function and flexibility of object exploration in kea and New Caledonian crows
Open the record for dataset details and reuse information.
Data from: The association between subjective memory complaint and objective cognitive function in older people with previous major depression
Open the record for dataset details and reuse information.
An Objective Assessment Tool for Evaluating Functioning in Older Adults
ClinicalTrials.gov study NCT06489847. IPD Sharing: NO. Countries: 1. Publications: 0.
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