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In this study, Pt-M (M = Ru, Sn, and Au) nanoparticle catalysts on MWNTs for detection of glucose were synthesized by a one-step radiation reduction.
Results and Discussion Fig. 2 shows the TEM images and ICP-AES data for the catalysts prepared by γ-irradiation.
This is because the standard reduction potential of the Pt ion is higher than that of other metal ions, leading to quicker reduction of the Pt ions compared with the other metals.
The crystalline nature of the Pt-M nanostructures was confirmed from XRD data.
The corresponding data of the sensor with Pt-Sn catalyst in PBS electrolyte were 0.810, 3.00  100, and 3.0.

Therefore, I hope not reduce the classification accuracy of the premise for a feature dimension reduction method to reduce the space dimension, to improve classification efficiency.
Feature selection and feature extraction is the main feature dimension reduction method, this paper will be different methods of feature selection research and analysis.
Distribution of training documents and test text Class topics Education Computer Environment Traffic Economic Military Art Real estate Training set 122 111 108 116 189 143 136 124 Test set 58 53 56 64 91 68 61 69 Corpus is the corpus used Sogou web site, this choice of seven types of text data, including education, computer, environment, transportation, military, economic, real estate, from which randomly selected 1049 documents as training set, 520 documents as the test set.
KNN is considered the more superior classification performance, so this experiment using KNN classifier to test data, the sample type is known to be classified with the sample to find the K most similar samples.
Obviously, experimental data show that the mutual information [6] the worst effects of the classification, information gain, better cross-entropy classification.

Boron Content (ppm) Absorbed Energy (J) Yield Strength (MPa) Tensile Strength (MPa) Tensile Strength 600 650 700 0.02% Offset Yield Strength 0 30 60 90 120 0 30 60 Impact Absorbed Energy 540 560 580 593 oC Boron Content (ppm) Reduction of Area (%) Yield Strength (MPa) Tensile Strength (MPa) Tensile Strength 460 480 0.2% Offset Yield Strength 0 30 60 90 120 60 70 80 Reduction of Area Test Results Tensile and Impact Properties Tensile strength and impact absorbed energy at room temperature of DS2B2 were superior to those of COST B2.
At 593oC for COST B2, as boron content increased, tensile strength increased and elongation and reduction of area decreased as shown in Fig.2.
DS2B2 Pseudo COST B2 BE (B : 0.030ppm) COST B2 DE (B : 0.093~0.100ppm) EE (B : 0.105~0.110ppm) 0.15 0.30 0.45 0.60 200 300 400 500 593 oC Cyclic Stress (MPa) Cyclic Strain (%) DS2B2 Pseudo COST B2 BE (B : 0.030ppm) CE (B : 0.075ppm) COST B2 DE (B : 0.093~0.100ppm) EE (B : 0.105~0.110ppm) 0 500 1000 1500 2000 2500 0 100 200 300 400 500 600 Pseudo COST B2 CE COST B2 DE COST B2 EE DS2B2 Peak Stress (MPa) Number of Cycles 593 oC ∆ ε t = 0.8% DS2B2 Pseudo COST B2 CE( B : 0.075%) COST B2 DE( B : 0.093~0.100%) EE( B : 0.105~0.110%) Fig. 7 Cyclic stress response curves for total strain range of 0.8% at 593oC Fig. 6 The cyclic stress strain data at 593oC Fig. 8 SEM of fatigue fracture surface for COST B2 (DE) Fig.5 The cyclic stress strain data at room temperature Fig. 3 Low cycle fatigue characteristics at room temperature Fig.4 Low cycle fatigue characteristics at 593oCFig.5 and 6 show cyclic stress strain
data for the tested materials at room and elevated temperatures, respectively.
For COST B2, the reduction of maximum stress with number of cycles was similar regardless of boron content.

The Pidgeon process, invented by Pidgeon LM in 1940s [3, 4], is a thermal process for MgO reduction by using Si metal (FeSi) at temperature near 1200°C under pressure of 2-10 Pa.
Fluorite, ranging 2-3%, is often mixed in raw materials to catalyze the MgO reduction in Pidgeon process [5, 6].
Results and discussion Table 2 Data from fluoride evaporation tests with heating time of 3 hours Test temperature [°C] F in slag sample [mass%] F evaporation rate [%] 1000 1.09 33.9 1100 1.54 6.7 1150 0.98 40.6 1200 1.06 35.8 1250 1.29 21.8 1300 1.25 24.2 1400 1.14 30.9 F content is 1.65% in the original slag sample from the Mg factory and decreases to 0.98-1.54% in the samples after heated in 3 hours at 1000-1400°C, Table 2 and Fig. 1.
Using the F content data in Eq. 1, values of F evaporation rate are calculated with the results also shown in Table 2.
Contents of major components in the Mg slag in Table 1 are used as input data for FactSage 6.2 software to compute equilibrium amounts of gaseous fluorides formed at high temperature.

The inlet pipe exhibits reduction ranging 68 to 72 HRB in the hardness comparing to the outlet pipe ranging 77 to 78 HRB from the coarse filters Introduction Biomass implies organic matter formed from plants by converting plant material through photosynthesis.
The incorporation of multi-integrated gas cleaner has resulted in significant amount of tar reduction [3].
Material selection based on kinetic data indicates choosing materials with chromium elements has better resistance against sulfidation [8].
Hardness Trial 1(HRB) Trial 2(HRB) Trial 3(HRB) As Received Material 91 93 92 Inlet 72 70 68 Outlet 77 78 77 The hardness test result implies the resistance towards indentation been affected due to flow of Producer gas with moisture content as inlet pipe suffers reduction in hardness as opposed to outlet pipe.

Reductions of lateral deviation error by 15% and longitudinal spacing error by 7% have been achieved.
The NN controller automatically trains itself with the initial set of data presented and subsequently, starts functioning with the optimized weights.
This improved controller performance translates into the reduction of lateral deviation error by 15% and longitudinal spacing error by 7%.
Tran-Cong: Indirect RBFN Method with Thin Plate Splines for Numerical Solution of Differential Equations, CMES, vol.4, no.1, p. 85-102, 2003 [9] P.Suresh and P.V.Manivannan: Reduction of Vehicular Pollution Through Fuel Economoy Improvement with the Use of Autonomous Self-Driving Passenger Cars, Proceedings of 6th International Congress of Environmental Research (ICER-13,2013), p.780, 2013 [10] Indica Vista TDi Quadrajet Safire Owner’s Manual and Service Book, Tata Motors Limited Passenger Car Business Unit, No. 2871 5840 99 01, 2011.

The machine’s rotor, crushing chamber, hammers, sieves, and prime mover were strategically engineered to achieve precise size reduction while maintaining operational efficiency and durability.
The main objective of this research was to examine palm kernel shells' energy potential by analysing the impact of particle size reduction on their energy content.
Despite these valuable contributions, limited research has systematically examined how particle size reduction of biomass influences solid biomass fuels' energy content and combustion efficiency.
This research addresses this imperative by enhancing the energy content of solid biomass through a particle size reduction approach.
Aspects regarding miscanthus cutting process FEM simulation and some experimental data.

After normalizing data,wefigured out ranges of synthetic parameters.
In order to obtain more accurate experimental signals, noise reduction is required.
Weighted Comprehensive Analysis Method Dimensions of the extracted characteristic parameters are not unified, which makes data analysis inconvenient, data processing is needed.
Distinction of duration and amplitude is relatively small, and the data is more dispersed.
Another group of experimental data for Verification: Table 4.

In this work, a kernel principle component analysis network (KPCANet) is proposed for classification of the facial expression in unconstrained images, which comprises only the very basic data processing components: cascaded kernel principal component analysis (KPCA), binary hashing, and block-wise histograms.
By constructing the same matrix for all input images and putting them together, we get (1) Standard PCA only allows linear dimensionality reduction.
However, if the data has more complicated structures which cannot be well represented in a linear subspace, standard PCA will not be very helpful.
Fortunately, kernel PCA allows us to generalize standard PCA to nonlinear dimensionality reduction.
Then each data point is projected to a point.

Fig. 1 and Table 1 show drawing, prototype and specifications of gearbox (reduction gear) in independent wheel drive installed at 2nd and 3rd axles of the tram.
The aluminum alloy has been chosen as housing material to consider pressure-resistance, corrosion-resistance, processing, casting characteristics, weight-reduction, and etc. [1] Fig. 2 Motor-gearbox set in independent wheel drive of the tram Table 1 Specifications of the gearbox in independent wheel drive pinion gear (input) transmission output gear driven driving gear type 2-steps helical gear (reduction ratio : 14.42:1) input torque 420 Nm input speed 6,000 rpm number of teeth 16 63 25 92 module 5 tooth width 50 mm Table 2 Mechanical properties of the gearbox housing material tensile strength (N/mm2) elongation (%) hardness (HB) aluminum (AC4C-T6) more than 220 more than 2 75 Temperature Characteristics Measurement.
Figs. 4 and 5 show measured data (vehicle running speed, temperatures) in the gearboxes in 2nd axle while the tram was running in summer or winter season.
Conclusions On the basis of measured data, maximum temperatures occurred on housing surface and in lubricant of the gearbox were 60~80 degree in the allowable limit (about 100 degree).