Quantized Compressive K-Means

The recent framework of compressive statistical learning aims at designing tractable learning algorithms that use only a heavily compressed representation-or sketch-of massive datasets. Compressive K-Means (CKM) is such a method: it estimates the centroids of data clusters from pooled, non-linear, random signatures of the learning examples. While this approach significantly reduces computational time on very large datasets, its digital implementation wastes acquisition resources because the learning examples are compressed only after the sensing stage. The present work generalizes the sketching procedure initially defined in Compressive K-Means to a large class of periodic nonlinearities including hardware-friendly implementations that compressively acquire entire datasets. This idea is exemplified in a Quantized Compressive K-Means procedure, a variant of CKM that leverages 1-bit universal quantization (i.e. retaining the least significant bit of a standard uniform quantizer) as the periodic sketch nonlinearity. Trading for this resource-efficient signature (standard in most acquisition schemes) has almost no impact on the clustering performances, as illustrated by numerical experiments

Analisis Kekuatan Lentur Balok Aplikasi Tulangan Komposit Dengan Perlakuan Bedamutu

Concrete has a very high compressive strength, while tensile strength only 10 % from compressive strength. Concrete as building materials have varying prices depending on the quality of the concrete. The use of different concrete quality is expected to reduce production costs with the same strength. Steel concrete is the product can not be update, whose existence will someday be exhausted. To overcome these problems, As a replacement alternative is the use of bamboo reinforcement with wire bendrat that cost cheaper and high strength. In this research steel concrete is replaced the bamboo reinforcement with give bendrat wire is used of a simple concrete beam reinforcement. All beams concrete are given bamboo reinforcement with wire bendrat. The final results of research will known how big and ability beam modification with reinforcement of bamboo petung with the wire bendrat in receive bending style. Slump test, the test result is 7 to 10 cm. From the test results strength urge concrete cubes can be deduced that the average compressive strength of concrete K-150 is 157 kg / cm2 means that the average concrete has a quality K-157, higher than the planning the quality of (K-150) , then to the quality of concrete K-225, the average compressive strength of concrete have the quality of K-229, higher than the plan that is the quality of (K-225). Results of testing the tensile strength of concrete steel Ø 6 mm obtained an average value of 15 kN, whereas tes result for the reinforcement of bamboo petung profile that diprofil with bendrat obtained average value of 12 kN. Flexure testing result revealed that the quality of concrete beam strength of K-225 gained an average of 36.67 kN, while to the quality of K-150 in get strength 27 kN. The modification concrete beam different quality concrete with reinforcement bamboo petung reinforcement with is given bendrat wire is average test results research of 28.33 kN,while for testing concrete beam reinforced steel with different quality, the research result of flexure test give results 36.33 kN

Magnetodielectric coupling and phonon properties of compressively strained EuTiO3 thin films deposited on LSAT

Compressively strained epitaxial (001) EuTiO3 thin films of tetragonal symmetry have been deposited on (001) (LaAlO3)_0.29-(SrAl_{1/2}Ta_{1/2}O3)_0.71 (LSAT) substrates by reactive molecular-beam epitaxy. Enhancement of the Neel temperature by 1 K with 0.9% compressive strain was revealed. The polar phonons ofthe films have been investigated as a function of temperature and magnetic field by means of infrared reflectance spectroscopy. All three infrared active phonons show strongly stiffened frequencies compared to bulk EuTiO3 in accordance with first principles calculations. The phonon frequencies exhibit gradual softening on cooling leading to an increase in static permittivity. A new polar phonon with frequency near the TO1 soft mode was detected below 150 K. The new mode coupled with the TO1 mode was assigned as the optical phonon from the Brillouin zone edge, which is activated in infrared spectra due to an antiferrodistortive phase transition and due to simultaneous presence of polar and/or magnetic nanoclusters. In the antiferromagnetic phase we have observed a remarkable softening of the lowest-frequency polar phonon under an applied magnetic field, which qualitatively agrees with first principles calculations. This demonstrates the strong spin-phonon coupling in EuTiO3, which is responsible for the pronounced dependence of its static permittivity on magnetic field in the antiferromagnetic phase.Comment: Submitted to Phys. Rev.

Coefficient of thermal expansion of nanostructured tungsten based coatings assessed by thermally induced substrate curvature method

The in plane coefficient of thermal expansion (CTE) and the residual stress of nanostructured W based coatings are extensively investigated. The CTE and the residual stresses are derived by means of an optimized ad-hoc developed experimental setup based on the detection of the substrate curvature by a laser system. The nanostructured coatings are deposited by Pulsed Laser Deposition. Thanks to its versatility, nanocrystalline W metallic coatings, ultra-nano-crystalline pure W and W-Tantalum coatings and amorphous-like W coatings are obtained. The correlation between the nanostructure, the residual stress and the CTE of the coatings are thus elucidated. We find that all the samples show a compressive state of stress that decreases as the structure goes from columnar nanocrystalline to amorphous-like. The CTE of all the coatings is higher than the one of the corresponding bulk W form. In particular, as the grain size shrinks, the CTE increases from 5.1 10$^{-6}$ K$^{-1}$ for nanocrystalline W to 6.6 10$^{-6}$ K$^{-1}$ in the ultra-nano-crystalline region. When dealing with amorphous W, the further increase of the CTE is attributed to a higher porosity degree of the samples. The CTE trend is also investigated as function of materials stiffness. In this case, as W coatings become softer, the easier they thermally expand.Comment: The research leading to these results has also received funding from the European Research Council Consolidator Grant ENSURE (ERC-2014-CoG No. 647554

Advancing Concrete Strength Prediction using Non-destructive Testing: Development and Verification of a Generalizable Model

Accurate prediction of concrete compressive strength is imperative for investigating the in-situ concrete quality. To avoid destructive testing, developing reliable predictive models for concrete compressive strength using nondestructive tests (NDTs) is an active area of research. However, many of the developed models are dependent on calibration and/or concrete past history (e.g. mixture proportion, curing history, concrete mechanical properties, etc.), which reduces their utility for in-situ predictions. This paper develops predictive models for concrete compressive strength that are independent of concrete past history. To this end, ultrasonic pulse velocity (UPV) and rebound hammer (RH) tests were performed on 84 concrete cylindrical samples. Next, compressive strengths were determined using destructive testing on these cylinders, and predictive models were developed using NDT results. Furthermore, to ensure generalizability to new data, all models were tested on independent data collected from six different research papers. The results support combined usage of UPV and RH in a quadratic polynomial model structure. Therefore, the final model was proposed based on combining models from a threefold cross-validation of the experimental data. This model predicted the independent data with very good accuracy. Finally, a concrete quality classification table using combined RH and UPV is proposed based on a variant of machine learning k-means clustering algorithm

Advancing Concrete Strength Prediction using Non-destructive Testing: Development and Verification of a Generalizable Model

Accurate prediction of concrete compressive strength is imperative for investigating the in-situ concrete quality. To avoid destructive testing, developing reliable predictive models for concrete compressive strength using nondestructive tests (NDTs) is an active area of research. However, many of the developed models are dependent on calibration and/or concrete past history (e.g. mixture proportion, curing history, concrete mechanical properties, etc.), which reduces their utility for in-situ predictions. This paper develops predictive models for concrete compressive strength that are independent of concrete past history. To this end, ultrasonic pulse velocity (UPV) and rebound hammer (RH) tests were performed on 84 concrete cylindrical samples. Next, compressive strengths were determined using destructive testing on these cylinders, and predictive models were developed using NDT results. Furthermore, to ensure generalizability to new data, all models were tested on independent data collected from six different research papers. The results support combined usage of UPV and RH in a quadratic polynomial model structure. Therefore, the final model was proposed based on combining models from a threefold cross-validation of the experimental data. This model predicted the independent data with very good accuracy. Finally, a concrete quality classification table using combined RH and UPV is proposed based on a variant of machine learning k-means clustering algorithm