Effect of cutting tool blunting on the performances of various mechanical excavators used in low- and medium-strength rocks

Full-scale laboratory cutting tests that measure the specific energy (SE) are widely used to evaluate rock cuttability by mechanical excavators, and in particular roadheaders fitted with radial or drag-type bits. Radial or drag-type bits are often changed during operation as they wear and become blunt. In this study, full-scale cutting tests were carried out on different rock types using bits with varying degrees of wear in order to assess the impacts of pick bluntness on cutting forces and the SE. The relationships between wear flats and cutting forces, SE, and various rock properties such as uniaxial compressive strength, tensile strength, indentation index, Shore hardness, Schmidt hammer hardness, and density were examined and are discussed in this paper. The mean cutting force increased 2- to 3-fold and the cutting SE rose 4- to 5-fold with a 4-mm wear flat as compared to a sharp pick. Critical wear flats were plotted for different rock property values, and 25 MJ/m³ was considered the threshold SE above which cutting performance was considered to be poor. Best-fit predictive models based on statistical analysis of the laboratory cutting test results are introduced as a means to estimate SE as a function of bit type, wear condition, and various mechanical properties of the rock. These models can be used to predict the performances of mechanical excavators that use radial tools, especially roadheaders, continuous miners, and longwall drum shearers.     

Viability and activity of bifidobacteria in yoghurt containing fructooligosaccharide during refrigerated storage

The viability of yoghurt bacteria and two commercial strains of bifidobacteria was assessed in either yoghurt containing chicory fructooligosaccharide (FOS) or without any prebiotic, during 28 days storage at 4 °C. All the products showed a decrease in the viable count of yoghurt bacteria and bifidobacteria during storage. Numbers of Lactobacillus delbrueckii ssp. bulgaricus decreased faster than those for Streptococcus thermophilus. The viability of bifidobacteria in yoghurt was affected by the strain type and the presence of FOS. Bifidobacterium animalis exhibited better stability in the yoghurt than B. longum. The recommended level of 1 million cells was exceeded for B. animalis throughout storage. The highest viable number of bifidobacteria (3.59–2.25 × 10⁷ CFU g^?1) was obtained in the product containing B. animalis and FOS. Viability of B. longum in yoghurt containing FOS remained above 10⁶ CFU g^?1 for up to 21 days, whereas this level was maintained for only 7 days for that organism in yoghurt without any prebiotic.     

Transmyocardial laser revascularization in allograft coronary artery disease

We used transmyocardial laser revascularization to treat accelerated cardiac allograft atherosclerosis in 2 patients. One patient received transmyocardial laser revascularization as sole therapy, the other as an adjunct to coronary artery bypass grafting. The systolic function improved in both patients, although the patient who had adjunctive transmyocardial laser revascularization died of systemic infection and renal failure on postoperative day 55. The second patient is alive and well 1 1/2 years after the laser procedure. We discuss 4 other patients who received transmyocardial laser revascularization treatment elsewhere in the United States. Transmyocardial laser revascularization has the potential to become important in the treatment of transplant atherosclerosis. Randomized clinical trials are warranted to assess the efficacy of transmyocardial laser revascularization in this setting.     

A hybrid option pricing model using a neural network for estimating volatility

The Black–Scholes (BS) model is the standard approach used for pricing financial options. However, although being theoretically strong, option prices valued by the model often differ from the prices observed in the financial markets. This paper applies a hybrid neural network which preprocesses financial input data for improving the estimation of option market prices. This model is comprised of two parts. The first part is a neural network developed to estimate volatility. The second part is an additional neural network developed to value the difference between the BS model results and the actual market option prices. The resulting option price is then a summation between the BS model and the network response. The hybrid system with a neural network for estimating volatility provides better performance in terms of pricing accuracy than either the BS model with historical volatility (HV), or the BS model with volatility valued by the neural network.     

Neural network training based on FPGA with floating point number format and it��s performance

In this paper, two-layered feed forward artificial neural network’s (ANN) training by back propagation and its implementation on FPGA (field programmable gate array) using floating point number format with different bit lengths are remarked based on EX-OR problem. In the study, being suitable with the parallel data-processing specification on ANN’s nature, it is especially ensured to realize ANN training operations parallel over FPGA. On the training, Virtex2vp30 chip of Xilinx FPGA family is used. The network created on FPGA is coded by using VHDL. By comparing the results to available literature, the technique developed here proved to consume less space for the subjected ANN training which has the same structure and bit length, it is shown to have better performance.     

Fuzzy logic based smart traffic light simulator design and hardware implementation

The objective of this study is to develop fuzzy logic based traffic junction light simulator system for design and smart traffic junction light controller purposes and also to observe its performance. Traffic junction simulator hardware is developed to overcome difficulties of working in a real environment and to easily test the performance of the controller. By using the traffic light simulator developed in this study, results of constant duration (conventional) traffic light controller and fuzzy logic based traffic light controller are compared where the vehicle inputs are supplied by the simulator. Statistical experimental results obtained from the implemented simulator show that the fuzzy logic traffic light controller dramatically reduced the waiting time at red lights since the controller adapts itself according to traffic density. It is obvious that the intelligent light controller is going to provide important advantages in terms of economics and environment.     

Preparation and characterization of Ni-nitrilotriacetic acid bearing poly(methacrylic acid) coated superparamagnetic magnetite nanoparticles

Stable superparamagnetic magnetite (Fe3O4) nanoparticles were synthesized via co-precipitation in the presence of poly(methacrylic acid) (PMAA) in aqueous solution. The polymer coated Fe3O4 nanoparticles were characterized using transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction, thermal analysis, and vibrating sample magnetometry (VSM) techniques. These measurements reveal the presence of magnetite nanoparticles with a size of approximately 8 nm inside the PMAA matrix. The magnetization value of these superparamagnetic nanoparticles at room temperarure and 7 T was measured as about 40 emu/g. PMAA-coated Fe3O4 nanoparticles were further assembled with Ni-chelate through a reaction between a primary amine-bearing NTA (nitrilotriacetic acid) ligand and carboxy-functional groups of PMAA. NTA-PMAA-coated magnetite nanoparticles were then loaded with nickel ions and characterized using FTIR. The average amount of binded Ni on the surface of the NTA-modified PMAA coated Fe3O4 was calculated as 1.65 +/- 0.3 x 10(-6) mol nickel(II) ions per g of the magnetic particles from the inductively coupled plasma optical emission spectroscopy (ICP-OES) measurements.     

HYPERBOLIC STEFAN PROBLEM WITH APPLIED SURFACE HEAT FLUX AND TEMPERATURE-DEPENDENT THERMAL CONDUCTIVITY

Abstract

The hyperbolic Stefan problem with an applied surface heat flux and temperature-dependent thermal conductivity is solved numerically for a semi-infinite slab using Mac-Cormack's predictor-corrector method. Solutions are presented for cases where the melt temperature is both below and above the instantaneous jump in surface temperature at time t = O⁺. The interface condition, surface temperature, and internal temperatures are presented for different Stefan numbers and melt temperatures, as well as thermal conductivity both increasing and decreasing with temperature. The results obtained from the hyperbolic solution are compared with those obtained from the parabolic solution.     

Characterization and mechanical properties of TiO2 nanotubes formed on titanium by anodic oxidation

The well-ordered titanium dioxide (TiO₂) nanotube array surfaces were formed at different voltages such as 20 V, 40 V, 60 V, 80 V and 100 V for 1 h on cp-Ti by anodic oxidation (AO) technique. And then, to improve crystallinity of the surface, heat treatment was applied at 450 °C for 1 h to all surfaces without any morphological changing. The surface and cross sectional morphology, elemental structure, phase composition, functional groups, roughness and thickness, wettability and mechanical results were investigated by SEM, EDX, XRD, FT-IR, AFM, contact angle measurement device and nanoindentation tester, respectively. Mainly, anatase- and rutile-TiO₂ phases were obtained at post-heat treatment whereas only, Ti phase was detected on AO surfaces at pre-heat treatment. All nanotube structures and the elements of Ti and O were uniformly distributed through the whole surface. The roughness and thickness of tube structures usually increased with increasing voltage values and measured. The roughness and thickness values were measured as 10.67–111.97 nm and 0.21–1.92 μm, respectively. TiO₂ nanotube surfaces exhibited hydrophobic behaviors with respect to plain Ti surface. Furthermore, mechanical properties such as hardness and elastic modulus of the coating produced at minimum voltage were great compared to ones at higher voltage and plain Ti surface under a Berkovich indenter due to phase structure, homogeneity and density of nanotube structures.     

Energy monitoring in residential spaces with audio sensor nodes: TinyEARS

Awareness on how and where energy is consumed is being increasingly recognized as the key to prevent waste in next-generation smart buildings. However, while several solutions exist to monitor energy consumption patterns for commercial and industrial users, energy reporting systems currently available to residential users require time-consuming and intrusive installation procedures, or are otherwise unable to provide device-level reports on energy consumption. To fill this gap, this paper discusses the design and performance evaluation of the Tiny Energy Accounting and Reporting System (TinyEARS), an energy monitoring system that generates device-level power consumption reports primarily based on the acoustic signatures of household appliances detected by wireless sensors. Experiments demonstrate that TinyEARS is able to report the power consumption of individual household appliances within a 10% error margin.