Patterning effects in WDM RZ-DBPSK SMF/DCF optical transmission at 40 Gbit/s channel rate

Summary form only given. In this paper an important new example of a system with strong and nontrivial patterning effects is presented. There has been much interest lately in the implementation of the differential phase shift-keying (PSK) modulation format for long-haul and ultra long-haul fibre communications and, in particular, the differential binary PSK (DBPSK) modulation format, where data is encoded into the optical phase. The results of a direct computation of the error statistics for an SMF/DCF RZ-DBPSK 5-channel WDM RZ-DBPSK link with hybrid Raman/EDFA amplification at 40 Gbit/s per channel, with a channel separation of 100 GHz are presented. The statistics of bit triplets and quantify strong pattern-dependent ISI are obtained.

Throughput-based rate adaptation algorithm for IEEE 802.11 vehicle networks

A key problem with IEEE 802.11 technology is adaptation of the transmission rates to the changing channel conditions, which is more challenging in vehicular networks. Although rate adaptation problem has been extensively studied for static residential and enterprise network scenarios, there is little work dedicated to the IEEE 802.11 rate adaptation in vehicular networks. Here, the authors are motivated to study the IEEE 802.11 rate adaptation problem in infrastructure-based vehicular networks. First of all, the performances of several existing rate adaptation algorithms under vehicle network scenarios, which have been widely used for static network scenarios, are evaluated. Then, a new rate adaptation algorithm is proposed to improve the network performance. In the new rate adaptation algorithm, the technique of sampling candidate transmission modes is used, and the effective throughput associated with a transmission mode is the metric used to choose among the possible transmission modes. The proposed algorithm is compared to several existing rate adaptation algorithms by simulations, which shows significant performance improvement under various system and channel configurations. An ideal signal-to-noise ratio (SNR)-based rate adaptation algorithm in which accurate channel SNR is assumed to be always available is also implemented for benchmark performance comparison.

Achievable performance gain of IEEE 802.11 multi-rate link adaptation algorithm with cross-layer design

Link quality-based rate adaptation has been widely used for IEEE 802.11 networks. However, network performance is affected by both link quality and random channel access. Selection of transmit modes for optimal link throughput can cause medium access control (MAC) throughput loss. In this paper, we investigate this issue and propose a generalised cross-layer rate adaptation algorithm. It considers jointly link quality and channel access to optimise network throughput. The objective is to examine the potential benefits by cross-layer design. An efficient analytic model is proposed to evaluate rate adaptation algorithms under dynamic channel and multi-user access environments. The proposed algorithm is compared to link throughput optimisation-based algorithm. It is found rate adaptation by optimising link layer throughput can result in large performance loss, which cannot be compensated by the means of optimising MAC access mechanism alone. Results show cross-layer design can achieve consistent and considerable performance gains of up to 20%. It deserves to be exploited in practical design for IEEE 802.11 networks.

Long-range, high bit-rate secure key distribution link utilizing Raman Ultra-long fiber laser (UFL)

The distribution of the secret key is the weakest link of many data encryption systems. Quantum key distribution (QKD) schemes provide attractive solutions [1], however their implementation remains challenging and their range and bit-rate are limited. Moreover, practical QKD systems, employ real-life components and are, therefore, vulnerable to diverse attack schemes [2]. Ultra-Long fiber lasers (UFLs) have been drawing much attention recently because of their fundamentally different properties compared to conventional lasers as well as their unique applications [3]. Here, we demonstrate a 100Bps, practically secure key distribution, over a 500km link, employing Raman gain UFL. Fig. 1(a) depicts a schematic of the UFL system. Each user has an identical set of two wavelength selective mirrors centered at l0 and l 1. In order to exchange a key-bit, each user independently choose one of these mirrors and introduces it as a laser reflector at their end. If both users choose identical mirrors, a clear signal develops and the bits in these cases are discarded. However if they choose complementary mirrors, (1, 0 or 0, 1 states), the UFL remains below lasing threshold and no signal evolves. In these cases, an eavesdropper can only detect noise and is unable to determine the mirror choice of the users, where the choice of mirrors represent a single key bit (e.g. Alice's choice of mirror is the key-bit). These bits are kept and added to the key. The absence of signal in the secure states faxilitates fast measurements to distinguish between the non-secure and the secure states and to determine the key-bit in the later case, Sequentially reapeating the single bit exchange protocol generate the entire keys of any desirable length. © 2013 IEEE.

Performance evaluation of adaptive context aware rate selection algorithm (ACARS) for road safety applications in vehicular network

One of the major drawbacks for mobile nodes in wireless networks is power management. Our goal is to evaluate the performance power control scheme to be used to reduce network congestion, improve quality of service and collision avoidance in vehicular network and road safety application. Some of the importance of power control (PC) are improving spatial reuse, and increasing network capacity in mobile wireless communications. In this simulation we have evaluated the performance of existing rate algorithms compared with context Aware Rate selection algorithm (ACARS) and also seen the performance of ACARS and how it can be applied to road safety, improve network control and power management. Result shows that ACARS is able to minimize the total transmit power in the presence of propagation processes and mobility of vehicles, by adapting to the fast varying channels conditions with the Path loss exponent values that was used for that environment which is shown in the network simulation parameter. Our results have shown that ACARS is a very robust algorithm which performs very well with the effect of propagation processes that is prone to every transmitted signal in mobile networks. © 2013 IEEE.

Error tolerance of topological codes with independent bit-flip and measurement errors

Topological quantum error correction codes are currently among the most promising candidates for efficiently dealing with the decoherence effects inherently present in quantum devices. Numerically, their theoretical error threshold can be calculated by mapping the underlying quantum problem to a related classical statistical-mechanical spin system with quenched disorder. Here, we present results for the general fault-tolerant regime, where we consider both qubit and measurement errors. However, unlike in previous studies, here we vary the strength of the different error sources independently. Our results highlight peculiar differences between toric and color codes. This study complements previous results published in New J. Phys. 13, 083006 (2011).

Improving minimum rate predictors algorithm for compression of volumetric medical images

Medical imaging technologies are experiencing a growth in terms of usage and image resolution, namely in diagnostics systems that require a large set of images, like CT or MRI. Furthermore, legal restrictions impose that these scans must be archived for several years. These facts led to the increase of storage costs in medical image databases and institutions. Thus, a demand for more efficient compression tools, used for archiving and communication, is arising. Currently, the DICOM standard, that makes recommendations for medical communications and imaging compression, recommends lossless encoders such as JPEG, RLE, JPEG-LS and JPEG2000. However, none of these encoders include inter-slice prediction in their algorithms. This dissertation presents the research work on medical image compression, using the MRP encoder. MRP is one of the most efficient lossless image compression algorithm. Several processing techniques are proposed to adapt the input medical images to the encoder characteristics. Two of these techniques, namely changing the alignment of slices for compression and a pixel-wise difference predictor, increased the compression efficiency of MRP, by up to 27.9%. Inter-slice prediction support was also added to MRP, using uni and bi-directional techniques. Also, the pixel-wise difference predictor was added to the algorithm. Overall, the compression efficiency of MRP was improved by 46.1%. Thus, these techniques allow for compression ratio savings of 57.1%, compared to DICOM encoders, and 33.2%, compared to HEVC RExt Random Access. This makes MRP the most efficient of the encoders under study.

Sea surface temperature (TEX86), marine GDGTs and BIT index from ODP Hole 161-977A

The TEX86H temperature proxy is a relatively new proxy based on crenarchaeotal lipids and has rarely been applied together with other temperature proxies. In this study, we applied the TEX86H on a sediment core from the Alboran Sea (western Mediterranean, core ODP-977A) covering the penultimate climate cycle, that is, from 244 to 130 ka, and compared this with previously published sea surface temperatures derived from the Uk'37 of alkenones of haptophyta and Mg/Ca records of planktonic foraminifera. The TEX86H temperature record shows remarkably similar stadial-interstadial patterns and abrupt temperature changes to those observed with the Uk'37 palaeothermometer. Absolute TEX86H temperature estimates are generally higher than those of Uk'37, though this difference (<3°C in 81% of the data points) is mainly within the temperature calibration error for both proxies, suggesting that crenarchaeota and haptophyta experienced similar temperature variations. During occasional events (<5% of the analyzed time span), however, the TEX86H exhibits considerably higher absolute temperature estimates than the Uk'37. Comparison with Mg/Ca records of planktonic foraminifera as well as other Mediterranean TEX86 and Uk'37 records suggests that part of this divergence may be attributed to seasonal differences, that is, with TEX86H reflecting mainly the warm summer season while Uk'37 would show annual mean. Biases in the global calibration of both proxies or specific biases in the Mediterranean are an alternative, though less likely, explanation. Despite differences between absolute TEX86H and Uk'37 temperatures, the correlation between the two proxies (r**2 = 0.59, 95% significance) provides support for the occurrence of abrupt temperature variations in the western Mediterranean during the penultimate interglacial-to-glacial cycle.

Bit-index sort: A fast non-comparison integer sorting algorithm for permutations

This paper describes a fast integer sorting algorithm, herein referred to as Bit-index sort, which does not use comparisons and is intended to sort partial permutations. Experimental results exhibit linear complexity order in execution time. Bit-index sort uses a bit-array to classify input sequences of distinct integers, and exploits built-in bit functions in C compilers, supported by machine hardware, to retrieve the ordered output sequence. Results show that Bit-index sort outperforms quicksort and counting sort algorithms when compared in their execution time. A parallel approach for Bit-index sort using two simultaneous threads is also included, which obtains further speedups of up to 1.6 compared to its sequential case.

Determination Of Detergent And Dispensant Additives In Gasoline By Ring-oven And Near Infrared Hypespectral Imaging.

A method using the ring-oven technique for pre-concentration in filter paper discs and near infrared hyperspectral imaging is proposed to identify four detergent and dispersant additives, and to determine their concentration in gasoline. Different approaches were used to select the best image data processing in order to gather the relevant spectral information. This was attained by selecting the pixels of the region of interest (ROI), using a pre-calculated threshold value of the PCA scores arranged as histograms, to select the spectra set; summing up the selected spectra to achieve representativeness; and compensating for the superimposed filter paper spectral information, also supported by scores histograms for each individual sample. The best classification model was achieved using linear discriminant analysis and genetic algorithm (LDA/GA), whose correct classification rate in the external validation set was 92%. Previous classification of the type of additive present in the gasoline is necessary to define the PLS model required for its quantitative determination. Considering that two of the additives studied present high spectral similarity, a PLS regression model was constructed to predict their content in gasoline, while two additional models were used for the remaining additives. The results for the external validation of these regression models showed a mean percentage error of prediction varying from 5 to 15%.

Event structure and double helicity asymmetry in jet production from polarized p plus p collisions at root s=200 GeV

We report on the event structure and double helicity asymmetry (A(LL)) of jet production in longitudinally polarized p + p collisions at root s = 200 GeV. Photons and charged particles were measured by the PHENIX experiment at midrapidity vertical bar eta vertical bar < 0.35 with the requirement of a high-momentum (> 2 GeV/c) photon in the event. Event structure, such as multiplicity, p(T) density and thrust in the PHENIX acceptance, were measured and compared with the results from the PYTHIA event generator and the GEANT detector simulation. The shape of jets and the underlying event were well reproduced at this collision energy. For the measurement of jet A(LL), photons and charged particles were clustered with a seed-cone algorithm to obtain the cluster pT sum (p(T)(reco)). The effect of detector response and the underlying events on p(T)(reco) was evaluated with the simulation. The production rate of reconstructed jets is satisfactorily reproduced with the next-to-leading-order and perturbative quantum chromodynamics jet production cross section. For 4< p(T)(reco) < 12 GeV/c with an average beam polarization of < P > = 49% we measured Lambda(LL) = -0.0014 +/- 0.0037(stat) at the lowest p(T)(reco) bin (4-5 GeV= c) and -0.0181 +/- 0.0282(stat) at the highest p(T)(reco) bin (10-12 GeV= c) with a beam polarization scale error of 9.4% and a pT scale error of 10%. Jets in the measured p(T)(reco) range arise primarily from hard-scattered gluons with momentum fraction 0: 02 < x < 0: 3 according to PYTHIA. The measured A(LL) is compared with predictions that assume various Delta G(x) distributions based on the Gluck-Reya-Stratmann-Vogelsang parameterization. The present result imposes the limit -a.1 < integral(0.3)(0.02) dx Delta G(x, mu(2) = GeV2) < 0.4 at 95% confidence level or integral(0.3)(0.002) dx Delta G(x, mu(2) = 1 GeV2) < 0.5 at 99% confidence level.

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

An accurate estimate of machining time is very important for predicting delivery time, manufacturing costs, and also to help production process planning. Most commercial CAM software systems estimate the machining time in milling operations simply by dividing the entire tool path length by the programmed feed rate. This time estimate differs drastically from the real process time because the feed rate is not always constant due to machine and computer numerical controlled (CNC) limitations. This study presents a practical mechanistic method for milling time estimation when machining free-form geometries. The method considers a variable called machine response time (MRT) which characterizes the real CNC machine`s capacity to move in high feed rates in free-form geometries. MRT is a global performance feature which can be obtained for any type of CNC machine configuration by carrying out a simple test. For validating the methodology, a workpiece was used to generate NC programs for five different types of CNC machines. A practical industrial case study was also carried out to validate the method. The results indicated that MRT, and consequently, the real machining time, depends on the CNC machine`s potential: furthermore, the greater MRT, the larger the difference between predicted milling time and real milling time. The proposed method achieved an error range from 0.3% to 12% of the real machining time, whereas the CAM estimation achieved from 211% to 1244% error. The MRT-based process is also suggested as an instrument for helping in machine tool benchmarking.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

Coarse-grid higher order finite-difference time-domain algorithm with low dispersion errors

Higher order (2,4) FDTD schemes used for numerical solutions of Maxwell`s equations are focused on diminishing the truncation errors caused by the Taylor series expansion of the spatial derivatives. These schemes use a larger computational stencil, which generally makes use of the two constant coefficients, C-1 and C-2, for the four-point central-difference operators. In this paper we propose a novel way to diminish these truncation errors, in order to obtain more accurate numerical solutions of Maxwell`s equations. For such purpose, we present a method to individually optimize the pair of coefficients, C-1 and C-2, based on any desired grid size resolution and size of time step. Particularly, we are interested in using coarser grid discretizations to be able to simulate electrically large domains. The results of our optimization algorithm show a significant reduction in dispersion error and numerical anisotropy for all modeled grid size resolutions. Numerical simulations of free-space propagation verifies the very promising theoretical results. The model is also shown to perform well in more complex, realistic scenarios.