Offer Performance Improvements Research Articles

Observer based pitch control for load mitigation and power regulation of floating offshore wind turbines

Abstract Most commercial wind turbines use proportional-integral (PI) collective blade-pitch control to regulate rotor speed in the above-rated wind speed regime. A significant drawback of this type of controller is that it assumes that the blades have identical structural properties and are subject to similar aerodynamic loads, which is seldom the case. Also, these controllers are designed to regulate the rotor speed and are not designed for structural vibration/load reduction. However, it is well known that blade pitch control can reduce structural loads on wind turbines. This opens up the possibility of designing controllers that use existing actuators and sensors like the blade pitch actuators to reduce structural loads/vibrations while maintaining the required rotor speed. Recent studies have investigated individual blade pitch control (IPC) to address these shortcomings. However, the vast majority of studies published in the literature depend on the availability of state measurement. Although sensors are commonly placed on all wind turbines, and some information is readily available, the measurement required by the typical state-feedback controllers is usually not available. Displacements and velocities of the blade, the tower and the floating platform are difficult to measure. This paper develops an observer-based individual blade pitch controller for load mitigation and power regulation of floating offshore wind turbines. We propose to use a Kalman filter to estimate the state from the accelerometer and strain gauge measurement for use in the state-feedback controller. The state-feedback controller was proposed previously by the authors that showed excellent performance. This paper extends the capability of the state-feedback controller by designing an observer (Kalman filter) to estimate the state from limited measurements. The proposed observer based controller is compared against a baseline proportional integral collective blade pitch controller and full state-feedback controllers to evaluate its performance. Numerical results show that the proposed output feedback controller offers performance improvements over the baseline controller, similar to the full state-feedback controller.

Sleep Stage Classification in Children Using Self-Attention and Gaussian Noise Data Augmentation

The analysis of sleep stages for children plays an important role in early diagnosis and treatment. This paper introduces our sleep stage classification method addressing the following two challenges: the first is the data imbalance problem, i.e., the highly skewed class distribution with underrepresented minority classes. For this, a Gaussian Noise Data Augmentation (GNDA) algorithm was applied to polysomnography recordings to seek the balance of data sizes for different sleep stages. The second challenge is the difficulty in identifying a minority class of sleep stages, given their short sleep duration and similarities to other stages in terms of EEG characteristics. To overcome this, we developed a DeConvolution- and Self-Attention-based Model (DCSAM) which can inverse the feature map of a hidden layer to the input space to extract local features and extract the correlations between all possible pairs of features to distinguish sleep stages. The results on our dataset show that DCSAM based on GNDA obtains an accuracy of 90.26% and a macro F1-score of 86.51% which are higher than those of our previous method. We also tested DCSAM on a well-known public dataset-Sleep-EDFX-to prove whether it is applicable to sleep data from adults. It achieves a comparable performance to state-of-the-art methods, especially accuracies of 91.77%, 92.54%, 94.73%, and 95.30% for six-stage, five-stage, four-stage, and three-stage classification, respectively. These results imply that our DCSAM based on GNDA has a great potential to offer performance improvements in various medical domains by considering the data imbalance problems and correlations among features in time series data.

Improving the Dynamic Behavior of a Hybrid Electric Rotorcraft for Urban Air Mobility

A rising number of aerospace manufacturers are working on the development of new solutions in the field of Urban Air Mobility with increasing attention addressing electric and hybrid electric propulsive systems. Hybrid electric propulsive systems potentially offer performance improvements during transient maneuvers, as well as sustaining the engine during flight phases characterized by high power demands. Among the challenges of hybridization in rotorcraft, there is the necessity to predict the dynamic behavior and its effect on the control of rotor shaft speed. In the present study, the dynamic behavior of a parallel hybrid electric propulsive system for a coaxial-rotor air taxi is analyzed in response to a typical sequence of pilot commands that encompasses the range of operations from hover to forward flight. The system is modeled with a dynamic approach and includes sub-models for the coaxial rotors, the turboshaft engine, the electric machine, and the battery. The results of the investigation show a better performance during transients of the hybrid system than a conventional turboshaft configuration, especially if the electric contribution to the power request is coordinated to account for the lag due to slower engine dynamic response.

Performance of Non-Line of Sight Underwater Optical Wireless Communication Links with Spatial Diversity

Line-of-sight (LOS) underwater optical wireless communication (UOWC) transmission may suffer blocking and are not always possible due to obstructions from sea creatures, bubbles, large suspended particles and features of the seabed, especially in coastal and turbid water environments. Thus, we present the performance of a spatially diverse non-line-of-sight (NLOS) UOWC system employing continuous phase modulation (CPM), which is shown to offer sensitivity benefits of several dBs over on–off keying (OOK) without coherent reception. We obtain the channel impulse response (CIR) by using Monte Carlo simulation, including absorption and multiple scattering. Turbulence is included by conditioning the CIR on log-normal statistics. To mitigate the resultant fading, we exploit spatial diversity with equal gain combining at the receiver side. Photon counting at the receiver is employed to accommodate shot noise. We compare the saddlepoint and Gaussian approximations for bit error rate (BER) calculations, using the latter for later calculations as it delivers excellent results and is simpler. Our results show that spatial diversity offers performance improvements, for example an 8 dB sensitivity gain at 10^-9 BER using 1 Gbps 3×1 multiple-input single-output (MISO) transmission over a 20 m link with 0.16 log-amplitude variance. We determine using an upper bound that Intersymbol Interference (ISI) has a significant impact at high bit rates, producing error floors for multiple-output arrangements.

High capacity steganography based on IWT using eight-way CVD and [formula omitted]-LSB ensuring secure communication

The state-of-the-art integer wavelet transform (IWT) based steganographic techniques suffer from low embedding capacity. To overcome this limitation, an IWT based secure high capacity steganographic technique is proposed. The aim of this work is to develop and evaluate new technique to offer performance improvements over the existing approaches. The vertical and horizontal subbands are utilized by eight-way coefficient value differencing (CVD) technique. These subbands are fragmented into non-overlapping 3 × 3 blocks. The n-LSB method (n is the number of bits) is used in the diagonal subband. The distortion due to n-LSB method is reduced using 2n correction technique. The proposed technique accomplishes an average embedding capacity of 2.63 bpp which is better than the recent state-of-the-art works. To enhance the security of the system, secret data are embedded in a non-sequential manner in the horizontal and vertical subbands. The proposed technique withstands the steganalysis test. It also resists the series of tests provided by StirMark Benchmark 4.0.

Modelling Software Architecture for Visual Simultaneous Localization and Mapping

Visual simultaneous localization and mapping (VSLAM) is an essential technique used in areas such as robotics and augmented reality for pose estimation and 3D mapping. Research on VSLAM using both monocular and stereo cameras has grown significantly over the last two decades. There is, therefore, a need for emphasis on a comprehensive review of the evolving architecture of such algorithms in the literature. Although VSLAM algorithm pipelines share similar mathematical backbones, their implementations are individualized and the ad hoc nature of the interfacing between different modules of VSLAM pipelines complicates code reuseability and maintenance. This paper presents a software model for core components of VSLAM implementations and interfaces that govern data flow between them while also attempting to preserve the elements that offer performance improvements over the evolution of VSLAM architectures. The framework presented in this paper employs principles from model-driven engineering (MDE), which are used extensively in the development of large and complicated software systems. The presented VSLAM framework will assist researchers in improving the performance of individual modules of VSLAM while not having to spend time on system integration of those modules into VSLAM pipelines.

Complete Stacked Denoising Auto-Encoders for Regression

Complete modified stacked denoising auto-encoder (CMSDAE) machines constitute a version of stacked auto-encoders in which a target estimate is included at the input, and are trained layer-by-layer by minimizing a convex combination of the errors corresponding to the input sample and the target. This permits to carry out the transformation of the observation space without forgetting what the target is. It has been shown in recent publications that this method produces a clear performance advantage in classification tasks. The above facts motivate to explore whether CMSDAE machines also offer performance improvements in regression problems, and in particular for time series prediction where conventional discriminative machines find difficulties: The layer-by-layer reconstruction of the target (together with the input) can help to reduce these difficulties. This contribution presents the CMSDAE regression/prediction machines and their design, showing experimental evidence of their frequent superior performance —never lower— with respect to other machine architectures. Some subsequent research directions are indicated together with the conclusions.

LexGLUE: A Benchmark Dataset for Legal Language Understanding in English

Law, interpretations of law, legal arguments, agreements, etc. are typically expressed in writing, leading to the production of vast corpora of legal text. Their analysis, which is at the center of legal practice, becomes increasingly elaborate as these collections grow in size. Natural language understanding (NLU) technologies can be a valuable tool to support legal practitioners in these endeavors. Their usefulness, however, largely depends on whether current state-of-the-art models can generalize across various tasks in the legal domain. To answer this currently open question, we introduce the Legal General Language Understanding Evaluation (LexGLUE) benchmark, a collection of datasets for evaluating model performance across a diverse set of legal NLU tasks in a standardized way. We also provide an evaluation and analysis of several generic and legal-oriented models demonstrating that the latter consistently offer performance improvements across multiple tasks.

Hierarchical Bayesian CMB component separation with the No-U-Turn Sampler

ABSTRACT In this paper, we present a novel implementation of Bayesian cosmic microwave background (CMB) component separation. We sample from the full posterior distribution using the No-U-Turn Sampler (NUTS), a gradient-based sampling algorithm. Alongside this, we introduce new foreground modelling approaches. We use the mean shift algorithm to define regions on the sky, clustering according to naively estimated foreground spectral parameters. Over these regions we adopt a complete pooling model, where we assume constant spectral parameters, and a hierarchical model, where we model individual pixel spectral parameters as being drawn from underlying hyperdistributions. We validate the algorithm against simulations of the LiteBIRD and C-Band All-Sky Survey (C-BASS) experiments, with an input tensor-to-scalar ratio of r = 5 × 10−3. Considering multipoles 30 ≤ ℓ < 180, we are able to recover estimates for r. With LiteBIRD-only observations, and using the complete pooling model, we recover r = (12.9 ± 1.4) × 10−3. For C-BASS and LiteBIRD observations we find r = (9.0 ± 1.1) × 10−3 using the complete pooling model, and r = (5.2 ± 1.0) × 10−3 using the hierarchical model. Unlike the complete pooling model, the hierarchical model captures pixel-scale spatial variations in the foreground spectral parameters, and therefore produces cosmological parameter estimates with reduced bias, without inflating their uncertainties. Measured by the rate of effective sample generation, NUTS offers performance improvements of ∼103 over using Metropolis–Hastings to fit the complete pooling model. The efficiency of NUTS allows us to fit the more sophisticated hierarchical foreground model that would likely be intractable with non-gradient-based sampling algorithms.

U-slot patch antenna with low RCS based on a metaferrite substrate

Metamaterial ferrites or metaferrites are artificial magnetic materials which mimic the properties of ferrites at a certain frequency operation. Antenna engineers are therefore able to design and create artificial substrates which replicate the electrical properties of ferrites without actually using any in the construction. This is advantageous as ferrites can offer performance improvements to microstrip antennas, such as size reduction and wideband impedance matching. In this paper, a metaferrite substrate designed by the use of a genetic algorithm is presented. The metaferrite was optimized in order to obtain the magnetic responses at 9GHz, for its use as the substrate of a microstrip antenna. As an example, a U-slot patch antenna based on the metaferrite is demonstrated, which can achieve stable radiation and 14 dB radar cross section (RCS) reduction performance in the measurement.

Compander Design for OFDM PAPR Reduction Using Optimal Perturbation of Piecewise Linear Segments

In this paper, we develop an optimal perturbation approach to design companders to mitigate the peak-to-average power ratio problem experienced by orthogonal frequency division multiplexing (OFDM) signals. Specifically, we generalize single-linear component design approaches, which modify the Rayleigh-distributed OFDM signal amplitude tail, to use of multiple contiguous piecewise linear components. The new compander design approach defines and solves a constrained optimization problem to optimally perturb a given proposed multicomponent piecewise linear segment set to meet the power and probability density function constraints. The use of multiple piecewise linear components provides greater design flexibility to meet the constraints, thus providing solutions for pairs of inflection points and cutoff values where more rigidly designed companders fail to exist. We present examples of compander design, and demonstrate compander performance through numerical simulation. The new compander design approach can generate companders that offer performance improvements over current companders.

Time Complexity of an Distributed Algorithm for Load Balancing of Microservice-oriented Applications in the Cloud

Microservice architecture is a relatively new cloud application design pattern. Each microservice has a single responsibility in terms of functional requirement, and that can be managed independently from other microservices. This is done using automated cloud orchestration systems. In this paper we analyze the time complexity of an simple swarm-like decentralized load balancing algorithm for microservices running inside OpenVZ virtualization containers. We show that it can offer performance improvements with respect to the existing centralized container orchestration systems.

MobiCOP: A Scalable and Reliable Mobile Code Offloading Solution

Code offloading is a popular technique for extending the natural capabilities of mobile devices by migrating processor‐intensive tasks to resource‐rich surrogates. Despite multiple platforms for offloading being available in academia, these frameworks have yet to permeate the industry. One of the primary reasons for this is limited experimentation in practical settings and lack of reliability, scalability, and options for distribution. This paper introduces MobiCOP, a new code offloading framework designed from the ground up with these requirements in mind. It features a novel design fully self‐contained in a library and offers compatibility with most stock Android devices available today. Compared to local task executions, MobiCOP offers performance improvements of up to 17x and increased battery efficiency of up to 25x, shows minimum performance degradation in environments with unstable networks, and features an autoscaling module that allows its server counterpart to scale to an arbitrary number of offloading requests. It is compatible with the most relevant Android technologies optimized for heavy computation (NDK and Renderscript) and has so far been well received by fellow mobile developers. We hope MobiCOP will help bring mobile code offloading closer to the industry realm.

Use of DVB-T and DVB-S2 in telecardiology

Telemedicine uses telecommunication and information technologies and provides clinical health care for people who are at a distance. Telecardiology is a type of telemedicine that can send electrocardiogram (ECG) signals over a wireless network to remote healthcare professionals. The aim of this paper is to simulate the transmission of ECG signals over a communication system that uses digital video broadcasting –terrestrial (DVB-T) or digital video broadcasting –satellite version 2 (DVB-S2) technologies. Bit error rate (BER) performance of this system is analyzed over an additive Gaussian white noise (AWGN) channel and compared to theoretical results. Keeping in mind that wireless channel suffers from multipath propagation, multiple-input multiple-output (MIMO) antenna technology is additionally used along with DVB-T in a fading environment. It is shown that DVB-S2 technology offers performance improvements of up to 18 dB over DVB-T in an AWGN channel. It is also shown that using MIMO along with DVB-T mitigates the effects of multipath and improves the performance. This improvement is around 5 dB. Being a superior technology, however, does not necessarily mean DVB-S2 should be chosen over DVB-T in every circumstance. For example, in the case where less delay is important (i.e. in real-time transmission) DVB-T might still be the choice of transmission of ECG signals if performance degradation can be tolerated.

DECENTRALIZED ORCHESTRATION OF COMPOSITE OGC WEB PROCESSING SERVICES IN THE CLOUD

Current web-based GIS or RS applications generally rely on centralized structure, which has inherent drawbacks such as single points of failure, network congestion, and data inconsistency, etc. The inherent disadvantages of traditional GISs need to be solved for new applications on Internet or Web. Decentralized orchestration offers performance improvements in terms of increased throughput and scalability and lower response time. This paper investigates build time and runtime issues related to decentralized orchestration of composite geospatial processing services based on OGC WPS standard specification. A case study of dust storm detection was demonstrated to evaluate the proposed method and the experimental results indicate that the method proposed in this study is effective for its ability to produce the high quality solution at a low cost of communications for geospatial processing service composition problem.

Non-Binary LDPC Codes for Magnetic Recording Channels: Error Floor Analysis and Optimized Code Design

In this paper, we provide a comprehensive analysis of the error floor along with code optimization guidelines for structured and regular non-binary low-density parity-check (NB-LDPC) codes in magnetic recording (MR) applications. While the topic of the error floor performance of binary LDPC codes over additive white Gaussian noise (AWGN) channels has recently received considerable attention, very little is known about the error floor performance of NB-LDPC codes over other types of channels, despite the early results demonstrating superior characteristics of NB-LDPC codes relative to their binary counterparts. We first show that, due to the outer looping between the detector and the decoder in the receiver, the error profile of NB-LDPC codes over partial-response (PR) channels is qualitatively different from the error profile over AWGN channels—this observation motivates us to introduce new combinatorial objects aimed at capturing decoding errors that dominate the PR channel error floor region. We call these objects balanced absorbing sets (BASs), which are viewed as a special subclass of previously introduced absorbing sets (ASs). Aided by these new objects (BASs), we develop a method that combines analytical equations and biased simulations to predict the error floor performance of NB-LDPC codes over PR channels without the need to execute extensive Monte Carlo (MC) simulations. We show that explicitly incorporating the inter-symbol interference of MR channels into our prediction method makes the accuracy of the error floor estimate within 0.2 of an order of magnitude from the traditional MC simulation. In addition, we prove that, due to the more restrictive definition of BASs (relative to the more general class of ASs), an additional degree of freedom can be exploited in the code design for PR channels. We then demonstrate that the proposed code optimization aimed at removing dominant BASs offers performance improvements in the frame error rate in the error floor region by up to 2.5 orders of magnitude over the unoptimized designs. Our code optimization technique carefully, yet provably, removes BASs from the code while preserving its overall structure (node degree, quasi-cyclic property, regularity, and so forth). The resulting codes outperform the existing binary and NB-LDPC solutions for PR channels by about 2.5 and 1.25 orders of magnitude, respectively.

Improved Product Development Performance through Agile/Stage-Gate Hybrids: The Next-Generation Stage-Gate Process?

OVERVIEW:Product development at manufacturing companies is increasingly complex. Linear product development processes, including the traditional Stage-Gate process, cannot support the iterative cycles and external collaboration that characterize today's product development efforts. Hybrid processes combining elements of Agile and Stage-Gate models offer a more flexible alternative to conventional systems. A comparative case study of seven technology-intensive companies shows how combining Stage-Gate models, at the strategic level, with the Agile method Scrum, implemented at the execution level, can offer performance improvements and other advantages over even improved Stage-Gate processes. The key contribution of this study is a generic Agile/Stage-Gate hybrid process based on best practices as identified in the case companies.

General Closed-Form Family of Companders for PAPR Reduction in OFDM Signals Using Amplitude Distribution Modification

In this paper, we characterize a family of closed-form companders for peak-to-average power ratio (PAPR) reduction in orthogonal frequency-division multiplexing (OFDM) signals. This new family generalizes the current state-of-the-art companders that are based on modification of the OFDM signal amplitude statistics. We derive the compander and decompander forms for a specific, parameterized member of this family. The larger parameter set characterizing these new companders provides greater design flexibility. The new companders are shown to provide solutions over regions of the operating conditions space where other current companders fail to exist. These new solutions thus widen the application of companders for PAPR reduction, and expand the trade-space over demodulation performance, PAPR reduction, and out-of-band power rejection for compander design. Through numerical result generation and simulation, we generate performance results to show that the new companders offer performance improvements over current companders.

Quantile mechanics II: changes of variables in Monte Carlo methods and GPU-optimised normal quantiles

With financial modelling requiring a better understanding of model risk, it is helpful to be able to vary assumptions about underlying probability distributions in an efficient manner, preferably without the noise induced by resampling distributions managed by Monte Carlo methods. This paper presents differential equations and solution methods for the functions of the form Q(x) = F−1(G(x)), where F and G are cumulative distribution functions. Such functions allow the direct recycling of Monte Carlo samples from one distribution into samples from another. The method may be developed analytically for certain special cases, and illuminate the idea that it is a more precise form of the traditional Cornish–Fisher expansion. In this manner the model risk of distributional risk may be assessed free of the Monte Carlo noise associated with resampling. The method may also be regarded as providing both analytical and numerical bases for doing more precise Cornish–Fisher transformations. Examples are given of equations for converting normal samples to Student t, and converting exponential to normal. In the case of the normal distribution, the change of variables employed allows the sampling to take place to good accuracy based on a single rational approximation over a very wide range of sample space. The avoidance of branching statements is of use in optimal graphics processing unit (GPU) computations as it avoids the effect of branch divergence. We give a branch-free normal quantile that offers performance improvements in a GPU environment while retaining the best precision characteristics of well-known methods. We also offer models with low probability branch divergence. Comparisons of new and existing forms are made on Nvidia GeForce GTX Titan and Tesla C2050 GPUs. We argue that in both single- and double-precisions, the change-of-variables approach offers the most GPU-optimal Gaussian quantile yet, working faster than the Cuda 5.5 built-in function.

Fast and Efficient Adaptation Algorithms for Multi-Gigabit Wireless Infrared Systems

Multibeam angle adaptive systems (MBAAS) have been shown to offer performance improvements over traditional spot-diffusing optical wireless systems. However, an increase in the computational cost is incurred. This paper introduces a method to speed up the adaptation process through efficient use of a divide and conquer algorithm by recursively breaking down the scanning process and focusing it into a smaller region in each iteration. The new, fast and efficient angle adaptation algorithm offers the advantages of optimizing the number and pattern (positions) of the spots so as to maximize the receiver's signal-to-noise ratio (SNR), regardless of the transmitter's position, the receiver's orientation and its field of view. It can also adapt to environmental changes, providing a robust link against shadowing and signal blockage. Furthermore, a beam delay adaptation method is used to reduce the effect of multipath dispersion and inter-symbol interference. The combination of angle and delay adaptation adds a degree of freedom to the link design, resulting in a compact impulse response and a system that is able to achieve higher data rates (15 Gbit/s). Significant improvements in the SNR, with optical wireless channel bandwidths of more than 15 GHz are obtained, and eye safety is considered while operating at 15 Gbit/s with full mobility in a realistic environment where shadowing exists.