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opencc-by-4.0Jun 2021View details →

Data for Solar Field Output Temperature Optimization Using a MILP Algorithm and a 0D Model in the Case of a Hybrid Concentrated Solar Thermal Power Plant for SHIP Applications

These data were generated for the Open-Acces Article : Kamerling, S.; Vuillerme, V.; Rodat, S. Solar Field Output Temperature Optimization Using a MILP Algorithm and a 0D Model in the Case of a Hybrid Concentrated Solar Thermal Power Plant for SHIP Applications. Energies 2021, 14, 3731. https://doi.org/10.3390/en14133731 In these dataset, the data for the Case Study and the Sensitivity Analysis are available. Jupyter Notebooks for further process of these data are also available. The NoteBooks AnalyseHourlyValues, AnalyseDailyValues and AnalyseMonthlyValues allow for easy change of variable, whereas CaseStudyAnalysis is for one specific set of data. The AnalyseSets were created in order to analyse the influence of the optimization on the solar fraction of the different datasets.

opencc-zeroJun 2015View details →

Combining Analytical Modeling, Realistic Simulation and Real Experimentation for the Optimization of Monte-Carlo Applications on the European Grid Infrastructure

Data and scripts used to generate figures presented in the paper "Combining Analytical Modeling, Realistic Simulation and Real Experimentation for the Optimization of Monte-Carlo Applications on the European Grid Infrastructure" submitted to the Future Generation Computer Systems Journal.

opencc-by-sa-4.0Feb 2016View details →

Communication Characterization and Optimization of Applications Using Topology-Aware Task Mapping on Large Supercomputers (Data)

Auxiliary materials for ICPE 2016 paper titled: "Communication Characterization and Optimization of Applications Using Topology-Aware Task Mapping on Large Supercomputers".

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Optimized SMRT-UMI protocol produces highly accurate sequence datasets from diverse populations – application to HIV-1 quasispecies

Pathogen diversity resulting in quasispecies can enable persistence and adaptation to host defenses and therapies. However, accurate quasispecies characterization can be impeded by errors introduced during sample handling and sequencing which can require extensive optimizations to overcome. We present complete laboratory and bioinformatics workflows to overcome many of these hurdles. The Pacific Biosciences single molecule real-time platform was used to sequence PCR amplicons derived from cDNA templates tagged with universal molecular identifiers (SMRT-UMI). Optimized laboratory protocols were developed through extensive testing of different sample preparation conditions to minimize between-template recombination during PCR and the use of UMI allowed accurate template quantitation as well as removal of point mutations introduced during PCR and sequencing to produce a highly accurate consensus sequence from each template. Handling of the large datasets produced from SMRT-UMI sequencing was facilitated by a novel bioinformatic pipeline, Probabilistic Offspring Resolver for Primer IDs (PORPIDpipeline), that automatically filters and parses reads by sample, identifies and discards reads with UMIs likely created from PCR and sequencing errors, generates consensus sequences, checks for contamination within the dataset, and removes any sequence with evidence of PCR recombination or early cycle PCR errors, resulting in highly accurate sequence datasets. The optimized SMRT-UMI sequencing method presented here represents a highly adaptable and established starting point for accurate sequencing of diverse pathogens. These methods are illustrated through characterization of human immunodeficiency virus (HIV) quasispecies.

opencc-zeroDec 2023View details →

Figure 4 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases

Figure 4. Identification of PCR inhibitors in 18 biological samples positive for Aspergillus. Graph A: Ct values obtained from pure and diluted DNA samples (dilution rate 1/20). Graph B: Ct values obtained with 20 copies of a plasmid DNA systematically added to the same biological samples (undiluted and diluted) and a negative control sample (NC).

Figure 2 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases

Figure 2. Influence of proteinase K digestion (56 °C overnight) on DNA extraction. Graph A shows the Ct values obtained by quantifying THP1 cell DNA derived from direct extraction with the NucliSENS easyMAG system and extraction performed on the same quantity of cells following overnight (ON) digestion with Proteinase K. Graph B shows Leishmania quantification after extraction with the NucliSENS easyMAG system both with and without PK and quantification after extraction using a QIAamp DNA Mini kit after ON digestion with PK.

Figure 7 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases

Figure 7. Variation of the ratio between kinetoplastic DNA and nuclear DNA extraction with various Leishmania quantities in the presence of 103 THP1 cells.

Figure 5 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases

Figure 5. Yield of DNA extraction from Leishmania and THP1 cells using the NucliSENS easyMAG system.

Figure 3 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases

Figure 3. Results of the extraction experiments performed on yeast (Candida albicans) and filamentous fungi (Aspergillus fumigatus). A presents the kinetics of the extraction process after vortexing and glass-bead treatment. B shows the differences in DNA quantity obtained from fungal cells using the FastPrep system (with) compared to the same process without grinding.

Figure 6 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases

Figure 6. Influence of the quantity of human cells (THP1 cells) on Leishmania quantification at various concentrations of host cells and parasites.

opencc-by-4.0Jan 2016View details →

Figure 4. A graphic on values of TP, TN, FP, and FN for each different application process.-Cognitive Development Optimization Algorithm Based Support Vector Machines for Determining Diabetes

This study has proposed a diabetes diagnosis system, which is formed via both Support Vector Machines (SVM) and Cognitive Development Optimization Algorithm (CoDOA). In this approach, the training process of the SVM has been supported with the CoDOA and after determining the most optimum sigma (σ) parameter of the Gauss (RBF) kernel function (so the most optimum SVM), a better classification formation has been tried to be achieved. In the context of the study, diabetes data set, which is related to Pima Indians, has been used for evaluating effectiveness of the proposed approach and after six different application processes, it was seen that the approach is well-enough on classification, which means being capable of determining diabetes. There are also some future works regarding the developed CoDOA-SVM based approach. In this context, there will be some more works for improving classification accuracy and also setting different optimization plans on i.e. different parameters of the kernel function. Additionally, it is aimed to evaluate the approach with datasets belonging to different diseases.

opencc-by-4.0Apr 2018View details →

Using the Genetic Algorithm for the Optimization of Dynamic School Bus Routing Problem-Figure 7. Application main form which includes route, bus stops and GA parameters

For this study, the school bus routes within the Ankara Province were used as case studies. The school bus routes were recorded by using the Android application and instantaneous GPS monitoring method. The home address of each student was taken as a stopping point. At the end of each route, the distances between the beginning and end points were recorded. After transferring the obtained route data into the database, the ill-adapted points were eliminated. By means of the developed application, the existing school bus routes are dynamically optimized using GA. It was developed both as a mobile and desktop application.  Using Android- based mobile software, the information regarding GPS locations of bus stops and school buses is transferred to the server on a real-time basis. Using the desktop software, where GAs are run, these coordinates are shown on a Google map, and the most suitable route is produced and sent to the school bus via server. This method provides the opportunity to dynamically reflect certain factors such as a different initial point for the school bus, some students being absent from the school on a particular day, and eventual changes on the existing roads on the route production process.

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Optimized SMRT-UMI protocol produces highly accurate sequence datasets from diverse populations – application to HIV-1 quasispecies

Open the record for dataset details and reuse information.

publicDec 2023View details →

opencc-by-4.0Apr 2022View details →

Application of optimized CNN to fixture layout in automotive parts. Training Dataset.

Fixture layout has aroused substantial interest in the research community during the last decades. It affects the design and production of fixtures themselves, and therefore manufacturing costs. While fixturing may seem simple in conception, it requires expertise and well-trained engineers.  A general principle, usually called the 3-2-1 locating principle, ensures fixing an object, restringing its degrees of freedom. Fixtures must always comply with the principle. While most research approaches automation of the fixture layout using optimization or rule-based frameworks, this paper proposes supervised learning. The presented framework solves the 3-2-1 locating principle for sheet metal designs based on the experience of previous designs, using automotive b-pillars as a test study. There are three main contributions. 1. A novel idea to introduce sheet metal design data in a Convolutional Neural Network (CNN), projecting the geometry over a plane. The Z coordinate transforms into gray-scale pixel values, generating a topographic map. 2. The framework reuses knowledge about fixturing to layout new workpieces. The framework is an add-in integrated with the CAD environment. 3. A hyperparameter-tuned CNN for regression generates the final output. The results show high accuracy (≈ 100%) in classifying b-pillars and fast convergence in regression, proving model usability for industrial cases.   Source Code: https://colab.research.google.com/drive/18lS83mZEdwY5S-41pvcGXgUP6GbKpun_?usp=sharing

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Optimization of cancer risk assessment model for PM2.5-bound PAHs Application in Shanxi of China SM

To optimize the models for cancer risk assessment of PM2.5-bound polycyclic aromatic hydrocarbons (PAHs), six models of three types utilized with high frequency in recent years, including the USEPA recommendation (Model I), inhalation carcinogen unit risk (Models IIA–IID), and three exposure pathways (inhalation, dermal, and oral) (Model III), were selected to calculate potential cancer risk using the benzo[a]pyrene toxicity equivalent method. The results indicated no significant differences in the risk values between Models IIA and III, and no significant differences were found among Models IIB, IIC, and IID. However, there were significant differences between Models I and II, and between Models I and III. Furthermore, the optimization of Model I indicated that the population exposure parameters for each country should be used and age differences should not be disregarded. However, no significant differences were observed with respect to gender. In conclusion, Model I was superior to the other models; when age differences were not considered, Model IID (the USEPA's integrated risk information system) was preferred to replace Models IIB and IIC. Models IIA and III may overestimate the risk of carcinogens, and their parameters need to be reoptimized to accurately assess cancer risks.

opencc-zeroApr 2022View details →

opencc-by-4.0Apr 2024View details →

Dataset related to "High-frequency optimally windowed chirp rheometry for rapidly evolving viscoelastic materials: Application to a crosslinking thermoset"

Knowledge of the evolution in the mechanical properties of a curing polymer matrix is of great importance in composite parts or structure fabrication. Conventional rheometry, based on small amplitude oscillatory shear, is limited by long interrogation times. In rapidly evolving materials, time sweeps can provide a meaningful measurement albeit at a single frequency. To overcome this constraint, we utilize a combined frequency- and amplitude-modulated chirped strain waveform in conjunction with a homemade sliding plate piezo-operated rheometer (PZR) and a dual-head commercial rotational rheometer (Anton Paar MCR 702) to probe the linear viscoelasticity of these time-evolving materials. The direct controllability of the PZR, resulting from the absence of any kind of firmware and the microsecond actuator-sensor response renders this device ideal for exploring the advantages of this technique. The high frequency capability allows us to extend the upper limits of the accessible linear viscoelastic spectrum and, most importantly, to shorten the length of the interrogating strain signal (OWCh-PZR) to subsecond scales, while retaining a high time-bandwidth product. This short duration ensures that the mutation number (NMu) is kept sufficiently low, even in fast-curing resins. The method is validated via calibration tests in both instruments, and the corresponding limitations are discussed. As a proof of concept, the technique is applied to a curing vinylester resin. The linear viscoelastic (LVE) spectrum is assessed every 20 s to monitor the rapid evolution in the time and frequency dependence of the complex modulus. Comparison of the chirp implementation, based on parameters such as duration of the experiment, sampling frequency, and frequency range, in a commercial rotational rheometer with the PZR provides further information on the applicability of this technique and its limitations. Finally, FTIR spectroscopy is utilized to gain insights into the evolution of the chemical network, and the gap dependence of the evolving material properties in these heterogeneous systems is also investigated

Figure 1 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases

Figure 1. Study design.