Recurrent Network Based Protocol Design for Spectrum Sensing in Cognitive Users

Wireless Personal Communications - This work focuses on cognitive users and its utilization of spectrum with channel bonding. Recurrent Channel Bonding Cognitive Users protocol (RCBCU) has been...     

Selection of network and learning parameters for an adaptive neural robotic control scheme

This paper presents the results of a study in the design of a neural network based adaptive robotic control scheme. The neural network used here is a two hidden layer feedforward network and the learning scheme is the well-known backpropagation algorithm. The neural network essentially provides the inverse of the plant and acts in conjunction with a standard PD controller in the feedback loop. The objective of the controller is to accurately control the end position of a single link manipulator in the presence of large payload variations, variations in the link length and also variations in the damping constant. Based on results of this study, guidelines are presented in selecting the number of neurons in the hidden layers and also the parameters for the learning scheme used for training the network. Results also indicate that increasing the number of neurons in the hidden layer will improve the convergence speed of learning scheme up to a certain limit beyond which the addition of neurons will cause oscillations and instability. Guidelines for selecting the proper learning rate, momentum and fast backpropagation constant that ensure stability and convergence are presented. Also, a relationship between the r.m.s. error and the number of iterations used in training the neural network is established.     

Development of a mathematical model for multihearth roasters

A simultaneous heat and mass transfer model has been developed for the multiheart roasters, considering dead roasting of chalcopyrite as a typical roasting reaction. Various mass and energy balances have been worked out during the development of this model yielding coupled nonlinear partial differential equations with highly complex boundary conditions. These equations have been solved numerically using a line-by-line finite difference approach to obtain profiles of gas temperature, solid temperature, oxygen concentration, and solid fraction reacted in the roaster. The trend of the computed results appears to be realistic and can be easily explained from simple physical considerations. The effects of gas preheating and the heat transfer coefficient between the solid and the gas upon the roasting process are examined. The results show that gas preheating is beneficial for the roasting process, and the process parameters, such as particle size, gas flow rate,etc., must be adjusted so as to give the desirable value of the heat transfer coefficient needed for proper roasting.     

Parallel implementation of backpropagation neural networks on aheterogeneous array of transputers

This paper analyzes parallel implementation of the backpropagation training algorithm on a heterogeneous transputer network (i.e., transputers of different speed and memory) connected in a pipelined ring topology. Training-set parallelism is employed as the parallelizing paradigm for the backpropagation algorithm. It is shown through analysis that finding the optimal allocation of the training patterns amongst the processors to minimize the time for a training epoch is a mixed integer programming problem. Using mixed integer programming optimal pattern allocations for heterogeneous processor networks having a mixture of T805-20 (20 MHz) and T805-25 (25 MHz) transputers are theoretically found for two benchmark problems. The time for an epoch corresponding to the optimal pattern allocations is then obtained experimentally for the benchmark problems from the T805-20, TS805-25 heterogeneous networks. A Monte Carlo simulation study is carried out to statistically verify the optimality of the epoch time obtained from the mixed integer programming based allocations. In this study pattern allocations are randomly generated and the corresponding time for an epoch is experimentally obtained from the heterogeneous network. The mean and standard deviation for the epoch times from the random allocations are then compared with the optimal epoch time. The results show the optimal epoch time to be always lower than the mean epoch times by more than three standard deviations (3sigma) for all the sample sizes used in the study thus giving validity to the theoretical analysis.     

The hardness-flow stress correlation in metallic materials

Hardness is a measure of the resistance of a material to indentation and a wide variety of indentation tests have been devised to measure the hardness of materials. In the case of hardness tests which utilize spherical balls as the indentor, it is also possible to derive flow stress-strain relationships from hardness tests carried out either over a range of loads (static test) or over a range of impact velocities (dynamic test). This paper first describes the experimental procedure for obtaining stress-strain curves from hardness tests. In addition, the paper also analyzes in detail, the indentation test conditions under which the conversion of the hardness-average strain data to flow stress-strain data is simple and straightforward in the sense that the constraint factor which is the correlating parameter for the above conversion is not only independent of strain but also easily computable on the basis of known mechanical property data of the test material.     

Crystalline morphology of poly(dimethylsiloxane)

The crystalline morphology of poly(dimethylsiloxane) was studied using a scanning electron microscope equipped with a cold stage. Samples of two different molecular weights were used. In both cases, spherulitic morphology is seen, from −70 °C, with spherulites of about 100 μ in size. Small single crystals of about a micron in size are also seen, and these are attributed to the presence of cyclics.     

Diagnosis of Prostate Cancer and Prostatitis Using near Infra-Red Fluorescent AgInSe/ZnS Quantum Dots

The link between the microbiome and cancer has led researchers to search for a potential probe for intracellular targeting of bacteria and cancer. Herein, we developed near infrared-emitting ternary AgInSe/ZnS quantum dots (QDs) for dual bacterial and cancer imaging. Briefly, water-soluble AgInSe/ZnS QDs were synthesized in a commercial kitchen pressure cooker. The as-synthesized QDs exhibited a spherical shape with a particle diameter of 4.5 ± 0.5 nm, and they were brightly fluorescent with a photoluminescence maximum at 705 nm. The QDs showed low toxicity against mouse mammary carcinoma (FM3A-Luc), mouse colon carcinoma (C26), malignant fibrous histiocytoma-like (KM-Luc/GFP) and prostate cancer cells, a greater number of accumulations in Staphylococcus aureus, and good cellular uptake in prostate cancer cells. This work is an excellent step towards using ternary QDs for diagnostic and guided therapy for prostate cancer.     

Microstructure,mechanical properties and machining performance of spark plasma sintered Al2O3–ZrO2–TiCN nanocomposites

The effect of addition of nanocrystalline ZrO₂ and TiCN to ultrafine Al₂O₃ on mechanical properties and microstructure of the composites developed by spark plasma sintering (SPS) was investigated. The distribution of the nanoparticles was dependent on their overall concentration. Maximum hardness (21 GPa) and indentation toughness (5.5 MPa m^1/2) was obtained with 23 vol% nanoparticles, which was considered as the optimum composition. The Zener pinning criteria were also satisfied at this composition with grain size of the restraining nanoparticles ～63–65 nm. Hardness of the composites follows the rule of mixtures; crack deflection and crack arrest by nanoparticles at grain boundaries along with mixed fracture mode led to high toughness in the nanocomposites. Cutting tool inserts were developed by SPS with the optimized composition and their machining performance was compared with commercial alumina based inserts. Increased toughness in the nanocomposite inserts reflects in the machining performance as the tool life improves drastically compared to that of the commercial inserts at high cutting speeds ≥500 m min^?1. This was attributed to differences in their failure modes; the commercial inserts fail catastrophically by fracture due to their low toughness whereas the nanocomposite inserts reach the tool failure criteria by crater wear at all machining conditions.     

Synthesis of graphene paper from pyrolyzed asphalt

A new technique for the synthesis of large sheets (>10 cm²) of multi-layered graphene is presented. The condensation onto a heated surface (≈650 °C) of fumes from the thermal decomposition of asphalt in a ceramic crucible produces carbon films with a metallic sheen. Heating was done by a Fisher burner (natural gas/air) flame and the crucible was covered but exposed to laboratory atmosphere. These films were determined to be multi-layered graphene by scanning electron microscopy, atomic force microscopy, X-ray photoelectron spectroscopy (XPS), Raman and infrared spectroscopy and X-ray diffraction. XPS indicates that the films are primarily sp² hybridized carbon with small amounts of sp³ C–H and C–O or C–N functionalities. Based on the D band shift (1593 cm⁻¹) and the ratio of D band to G band (1354 cm⁻¹) of 0.93, the Raman spectrum also indicates that the material is sp² C with some nanocrystalline features. The infrared spectrum exhibits A_1U (868 cm⁻¹) and E_1U (1599 cm⁻¹) stretching of the intralayer bonds of graphene. This form of chemical vapor deposition may be a scalable to give much larger surface areas. Furthermore, the process does not require metal substrates. Deposition onto silica nanosprings and diatomites is demonstrated.     

Synthesis and characterization of polyimide/polyhedral oligomeric silsesquioxane nanocomposites containing quinolyl moiety

A series of functional polyhedral oligomeric silsesquioxane (POSS)/polyimide (PI) nanocomposites were prepared using a two‐step approach. First, octa(aminophenyl)silsesquioxane (OAPS) was mixed with poly(amic acid) (PAA) prepared by reacting bis(4‐amino‐3,5‐dimethylphenyl)‐3‐quinolylmethane and 3,3′,4,4′‐benzophenonetetracarboxylic dianhydride. Second, the resulting solution was subjected to thermal imidization. The well‐defined ‘hard particles’ (POSS) and the strong covalent bonds in the amide linkage between the carbon atom of the carboxyl side group in PAA and the nitrogen atom of the amino group in POSS lead to a significant improvement in the thermal and mechanical properties. Homogeneous dispersion of POSS cages in the PI is evident from scanning electron microscopy, which further confirms that the POSS molecule becomes an integral part of the organic‐inorganic inter‐crosslinked network system. Differential scanning calorimetry and dynamic mechanical analysis show that the glass transition temperatures of the POSS‐containing nanocomposites are higher than that of the corresponding neat PI system, owing to the significant increase of the crosslinking density in the PI/POSS nanocomposites. Increasing the concentration of OAPS in the PI networks decreases the dielectric constant. Pure PI and PI/POSS systems have good antimicrobial activity. Copyright © 2011 Society of Chemical Industry