Performance Analysis of Dual Unipolar/Bipolar Spectral Code in Optical CDMA Systems

This study analyzes and calculates dual unipolar and bipolar coded configurations of spectral-amplitude-coding opticalcode division multiple access (SAC-OCDMA) systems by using simulation methods. The important feature of theSAC-OCDMA systems is that multiple access interference (MAI) can be eliminated by code sequences of a fixed inphasecross-correlation value. This property can be effectively canceled multiple access interference by using balancedetection schemes. This study uses Walsh-Hadamard codes as signature codes for the unipolar and bipolar schemes.The coder and decoder structures are based on optical filters of fiber Bragg gratings (FBGs). The simulation results ofunipolar/bipolar coding structures are first presented by commercial simulation obtained using OptiSystem software.The simulation results show that the bit error rate (BER) through use of the bipolar coding method is superior to theunipolar scheme, especially when the received effect power is large. When the system needs good performance totransmit multimedia data, we can use bipolar scheme in the network. If the users only transmit voice data, the unipolarmethod can be employed. The eye diagram also shows that the bipolar encoding structure exhibits a wider openingthan the unipolar encoding structure. The flexible implementation of codewords assigns and integratable hardwaredesigns for the scheme with FBGs to realize dual coding OCDMA system is proposed

Singlet-triplet transitions in highly correlated nanowire quantum dots

We consider a quantum dot embedded in a three-dimensional nanowire with tunable aspect ratio a. A configuration interaction theory is developed to calculate the energy spectra of the finite 1D quantum dot systems charged with two electrons in the presence of magnetic fields B along the wire axis. Fruitful singlet-triplet transition behaviors are revealed and explained in terms of the competing exchange interaction, correlation interaction, and spin Zeeman energy. In the high aspect ratio regime, the singlet-triplet transitions are shown designable by tuning the parameters a and B. The transitions also manifest the highly correlated nature of long nanowire quantum dots.Comment: 4 pages, 4 figure

Radioactivity measurements using storage phosphor technology

We propose to apply a recently developed charged particle radiation imaging concept in bio-medical research for fast, cost-effective characterization of radionuclides in contaminated sites and environmental samples. This concept utilizes sensors with storage photostimulable phosphor (SPP) technology as radiation detectors. They exhibit high sensitivity for all types of radiation and the response is linear over a wide dynamic range (>10{sup 5}), essential for quantitative analysis. These new sensors have an active area of up to 35 cm x 43 cm in size and a spatial resolution as fine as 50 {mu}m. They offer considerable promise as large area detectors for fast characterization of radionuclides with an added ability to locate and identify hot spots

Calibration of linear contact stiffnesses in discrete element models using a hybrid analytical-computational framework

Efficient selections of particle-scale contact parameters in discrete element modelling remain an open question. The aim of this study is to provide a hybrid calibration framework to estimate linear contact stiffnesses (normal and tangential) for both two-dimensional and three-dimensional simulations. Analytical formulas linking macroscopic parameters (Young's modulus, Poisson's ratio) to mesoscopic particle parameters for granular systems are derived based on statistically isotropic packings under small-strain isotropic stress conditions. By taking the derived analytical solutions as initial approximations, the gradient descent algorithm automatically obtains a reliable numerical estimation. The proposed framework is validated with several numerical cases including randomly distributed monodisperse and polydisperse packings. The results show that this hybrid method practically reduces the time for artificial trials and errors to obtain reasonable stiffness parameters. The proposed framework can be extended to other parameter calibration problems in DEM

Characterization of Loading Responses and Failure Loci of a Boron Steel Spot Weld

Boron steel, classed as an ultra high-strength steel (UHSS), has been utilized in anti-intrusion systems in automobiles, providing high strength and weight-saving potential through gage reduction. UHSS spot welds exhibit unique hardness distributions, with a hard nugget and outlying base material, but with a soft heat-affected zone in-between these regions. This soft zone reduces the strength of the weld and makes it susceptible to failure. Due to the interaction of various weld zones that occurs during loading, there is a need to characterize the loading response of the weld for accurate failure predictions. The loading response of certain weld zones, as well as failure loci, was obtained through physical simulation of the welding process. The results showed a significant difference in mechanical behavior through the weld length. An important result is that instrumented indentation was shown to be a valid, quantitative method for verifying the accuracy with which weld microstructure has been recreated with regard to the target weld microstructure

A Framework for and Empirical Study of Algorithms for Traffic Assignment

Traffic congestion is an issue in most cities worldwide. Transportation engineers and urban planners develop various tra c management projects in order to solve this issue. One way to evaluate such projects is traffic assignment (TA). The goal of TA is to predict the behaviour of road users for a given period of time (morning and evening peaks, for example). Once such a model is created, it can be used to analyse the usage of a road network and to predict the impact of implementing a potential project. The most commonly used TA model is known as user equilibrium, which is based on the assumption that all drivers minimise their travel time or generalised cost. In this study, we consider the static deterministic user equilibrium TA model. The constant growth of road networks and the need of highly precise solutions (required for select link analysis, network design, etc) motivate researchers to propose numerous methods to solve this problem. Our study aims to provide a recommendation on what methods are more suitable depending on available computational resources, time and requirements on the solution. In order to achieve this goal, we implement a flexible software framework that maximises usage of common code and, hence, ensures comparison of algorithms on common ground. In order to identify similarities and differences of the methods, we analyse groups of algorithms that are based on common principles. In addition, we implement and compare several different methods for solving sub-problems and discuss issues related to accumulated numerical errors that might occur when highly accurate solutions are required

Clustering Algorithms: Their Application to Gene Expression Data

Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and iden-tify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure

Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation

We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 × 10-11 to 5.0 × 10-21). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that, at some of the loci identified, DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 new loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7 and TBX2) function. The new and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, and cardiovascular and all-cause mortality (P = 0.04 to 8.6 × 10-6). Our results provide new evidence for the role of DNA methylation in blood pressure regulation