Strong Performance Improvement Research Articles

Image Deraining Algorithm Based on Multi-Scale Features

In target detection, tracking, and recognition tasks, high-quality images can achieve better results. However, in actual scenarios, the visual effects and data quality of images are greatly reduced due to the influence of environmental factors, which affect subsequent detection, recognition, and other tasks. Therefore, this paper proposes an image rain removal algorithm based on multi-scale features, which can effectively remove rain streaks. First of all, this paper proposes a deraining algorithm that combines spatial information to improve the network’s generalization ability on real images, aiming at the problem of synthetic datasets used by previous deraining algorithms. Then, by proposing a multi-scale rain removal algorithm, it improves the feature extraction capabilities of existing deraining algorithms. Before extracting deep rain features, a preliminary fusion of multi-scale shallow features can be performed, which can show better performance in images of different sizes. In addition, a spatial attention module and channel are introduced. The attention module increases the ability to extract rain information at each scale; the resulting multi-scale feature image rain removal algorithm is called MFD. Finally, the rain removal algorithm is validated on the rain removal dataset, and the proposed method can effectively remove rain patterns, provide strong performance improvement on several datasets in the image rain removal task, and provide high-quality images for subsequent detection and recognition tasks.

Seismically Informed Reference Models Enhance AI‐Based Earthquake Prediction Systems

AbstractGiven the robust nonlinear regression capabilities of Artificial Intelligence (AI) technology, its commendable performance in numerous geophysical tasks is expected. Yet, AI technology suffers from (a) its “black box” nature and (b) the fact that some complicated artificial neural networks (ANNs) claiming superior performance do not surpass some simple geophysical models that clearly describe the underlying physical processes. Numerous reports rely on standard machine learning metrics, often using a spatially uniform Poisson (SUP) distribution as their reference. A good performance just means that the artificial neural network (ANN) outperforms this basic reference, potentially offering little novelty to the scientific community. Worse, this can lead to spurious inference. We demonstrate this by using the monthly average human‐made Nighttime Light Map and the cumulative energy of earthquakes in various space‐time units as inputs for an Long short‐term memory model. The goal is to predict earthquakes with a magnitude of M ≥ 5.0 across the entire Chinese Mainland. With the SUP reference model, the ANN concludes that human‐made Nighttime Light possesses substantial earthquake prediction capability. This is evidently flawed reasoning. We show that this stems from the poor reference model and this spurious inference disappears when using a better benchmark consisting of a spatially varying Poisson (SVP) model informed from statistical seismology. This is implemented by weighting the punishments/rewards of our ANN associated with failed/successful predictions by prior probabilities provided by the stronger SVP model. Scores obtained with the time‐space Molchan diagram demonstrate the strong performance improvement obtained by training ANN with a better reference model.

OERL: Enhanced Representation Learning via Open Knowledge Graphs

The sparseness and incompleteness of knowledge graphs (KGs) trigger considerable interest in enhancing the representation learning with external corpora. However, the difficulty of aligning entities and relations with external corpora leads to inferior performance improvement. Open knowledge graphs (OKGs) consist of entity-mentions and relation-mentions that are represented by noncanonicalized freeform phrases, which generally do not rely on the specification of ontology schema. The roughness of the nonontological construction method leads to a specific characteristic of OKGs: diversity, where multiple entity-mentions (or relation-mentions) have the same meaning but different expressions. The diversity of OKGs can provide potential textual and structural features for the representation learning of KGs. We speculate that leveraging OKGs to enhance the representation learning of KGs can be more effective than using pure text or pure structure corpora. In this paper, we propose a new <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">OERL</b> , <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</b> pen knowledge graph <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">E</b> nhanced <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</b> epresentation <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</b> earning of KGs. OERL automatically extracts textual and structural connections between KGs and OKGs, models and transfers refined profitable features to enhance the representation learning of KGs. The strong performance improvement and exhaustive experimental analysis prove the superiority of OERL over state-of-the-art baselines.

Microstructure evolution and mechanical properties of severely deformed TA15 alloy by multi‐directional forging and annealing

AbstractMulti‐directional forging technology, as a representative severe plastic deformation technology, is urgent to be developed because it has strong microstructure refinement and performance improvement effects. In this paper, multi‐directional forging experiments of TA15 titanium alloy with different passes were carried out at 700 °C using unrestricted multi‐directional forging die structure. Then the samples of TA15 titanium alloy after multi‐directional forging deformation were subjected to a high‐temperature vacuum annealing treatment. The test results reveal TA15 alloy was effectively refined through multi‐directional forging without any cracking with the increasing of deformation passes. The mechanism of grain refinement during multi‐directional forging included dynamic recrystallization, grain crushing and adiabatic shear deformation bands refinement. The amount and grain size of recrystallization grains increased when the annealing time increased from 1 hour to 4 hours. Supplemented by annealing, the adiabatic shear deformation bands microstructure with the mixed microstructure of coarse αp and fine αs were obtained and the hardness after multi‐directional forging and annealing was investigated. The yield strength and ultimate tensile strength increased by 26.1 % and 25.5 % respectively when the deformation pass increased to 3 passes compared with the initial specimen. The present work revealed that multi‐directional forging deformation combined with appropriate annealing could represent an efficient route to improve the microstructure and mechanical property of TA15 alloy.

Smartphone-Based Technology to Help Individuals with Intellectual Disability and Blindness Manage Basic Indoor Travel

The present study assessed a new intervention strategy to help individuals with severe to profound intellectual disability and blindness (i.e., total blindness or minimal residual vision) to travel to different rooms located on both sides of long hallways. The intervention strategy was based on the use of a smartphone (i.e., a Samsung Galaxy J4 Plus with Android 9.0 operating system) and battery-powered light sources. The smartphone was programmed to encourage the participant to walk forward alongside a wall of the hallway until its light sensor was activated by a light source positioned before a room entrance. At that point, the smartphone encouraged the participant to stop and then enter. Nine participants were involved in the study. Each session involved seven travels. During the baseline phase, the participants’ mean frequencies of correct travels per session varied between zero and slightly above 2. During the intervention phase, with the smartphone-based cues, all participants showed a strong performance improvement. Their mean frequencies of correct travels varied between about 6.5 and (virtually) 7 per session during the second half of the intervention phase. This smartphone-based intervention strategy might help support indoor travel of people with intellectual disability and blindness.

Kalman Filter-Based Channel Estimation for Mobile-to-Mobile and Relay Networks

This letter deals with channel estimation in mobile-to-mobile communications, possibly including amplify and forward mobile relays, assuming a two-dimensional scattering environment. A second-order autoregressive [AR(2)] model with the Kalman filter is used to estimate the channel gain of the global multihop channel. The parameters of the AR(2) model can be tuned by using a classic correlation matching criterion. Alternatively, the use of a minimization of the asymptotic variance criterion permits a strong performance improvement, although the corresponding analytical study is still missing in the literature—which is the topic of this letter. The closed-form expressions for the optimal tuning of the AR(2) parameters and mean square error performance have been first established as a function of the second and fourth moments of the Doppler spectrum of the global channel. Because the analytical formulas of these moments were not given in the literature, we derive them by exploiting cumulant property of convolution of density functions, after decomposition of the global channel as a cascade of Jakes Doppler power spectral density channels. Consequently, the provided closed-form formula are helpful for the design of Kalman filters for a given state of the source, destination, and mobile relays [Doppler spread and signal to noise ratio].

Push to Avoid Rehospitalization Has Unintended Outcomes

Push to Avoid Rehospitalization Has Unintended Outcomes

Allocation folding based on dominance

Memory management system performance is of increasing importance in today's managed languages. Two lingering sources of overhead are the direct costs of memory allocations and write barriers. This paper introduces it allocation folding, an optimization technique where the virtual machine automatically folds multiple memory allocation operations in optimized code together into a single, larger it allocation group. An allocation group comprises multiple objects and requires just a single bounds check in a bump-pointer style allocation, rather than a check for each individual object. More importantly, all objects allocated in a single allocation group are guaranteed to be contiguous after allocation and thus exist in the same generation, which makes it possible to statically remove write barriers for reference stores involving objects in the same allocation group. Unlike object inlining, object fusing, and object colocation, allocation folding requires no special connectivity or ownership relation between the objects in an allocation group. We present our analysis algorithm to determine when it is safe to fold allocations together and discuss our implementation in V8, an open-source, production JavaScript virtual machine. We present performance results for the Octane and Kraken benchmark suites and show that allocation folding is a strong performance improvement, even in the presence of some heap fragmentation. Additionally, we use four hand-selected benchmarks JPEGEncoder, NBody, Soft3D, and Textwriter where allocation folding has a large impact.

Oxygen Reduction Reaction Activity of Aerosol Jet Printed Layers of Graphite and Graphene

Graphene and graphene-based materials have shown great promise in a broad range of applications including electrochemical sensors, supercapacitors, and lithium ion batteries. However, practical realization of the potential utility of graphene requires development of low cost, high volume methods of material synthesis and manufacturing-ready methods of device fabrication. This work aims to address the second challenge by demonstrating the use of aerosol jet printing for the fabrication of catalytically active electrodes.Graphene and graphite were formulated into high concentration inks (10mg/mL). These inks were aerosol jet printed to create micron scale layers (2 – 10 microns). The catalytic activity of the aerosol jet printed electrodes was evaluated in oxygen saturated basic solution. It was found that the oxygen reduction reaction activity of the aerosol jet printed graphene electrode was ~ 5 times higher times than the activity of the same material when drop cast. Electrochemical impedance spectroscopy showed that the activity difference correlated with a large decrease in the charge transfer resistance of aerosol jet printed graphene as opposed to drop cast graphene. Further, the activity of the aerosol jet printed graphene electrode was ~ 3 times greater than the activity of the aerosol jet printed graphite. In contrast, the drop cast materials did not show a measurable difference in performance. These results indicate that aerosol jet printing is a viable way to deposit micron scale layers of graphene and related materials. In addition, the activity of the graphene electrode is strongly dependent on the deposition method, with aerosol jet deposited electrodes showing a strong performance improvement over their drop cast counterparts.

Predicting cell-type–specific gene expression from regions of open chromatin

Complex patterns of cell-type–specific gene expression are thought to be achieved by combinatorial binding of transcription factors (TFs) to sequence elements in regulatory regions. Predicting cell-type–specific expression in mammals has been hindered by the oftentimes unknown location of distal regulatory regions. To alleviate this bottleneck, we used DNase-seq data from 19 diverse human cell types to identify proximal and distal regulatory elements at genome-wide scale. Matched expression data allowed us to separate genes into classes of cell-type–specific up-regulated, down-regulated, and constitutively expressed genes. CG dinucleotide content and DNA accessibility in the promoters of these three classes of genes displayed substantial differences, highlighting the importance of including these aspects in modeling gene expression. We associated DNase I hypersensitive sites (DHSs) with genes, and trained classifiers for different expression patterns. TF sequence motif matches in DHSs provided a strong performance improvement in predicting gene expression over the typical baseline approach of using proximal promoter sequences. In particular, we achieved competitive performance when discriminating up-regulated genes from different cell types or genes up- and down-regulated under the same conditions. We identified previously known and new candidate cell-type–specific regulators. The models generated testable predictions of activating or repressive functions of regulators. DNase I footprints for these regulators were indicative of their direct binding to DNA. In summary, we successfully used information of open chromatin obtained by a single assay, DNase-seq, to address the problem of predicting cell-type–specific gene expression in mammalian organisms directly from regulatory sequence.

Performance Improvement of AlN–GaN-Based Intersubband Detectors by Using Quantum Dots

We report a strong performance improvement for 1.55- <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$\mu$</tex></formula> m AlN–GaN-based intersubband photodetectors. Thanks to the use of quantum dots (QDs) instead of quantum wells (QWs), a factor of 60 could be gained in terms of maximum responsivity. In addition, this performance was achieved at a considerably higher temperature of 160 K instead of 80 K as typically seen for QWs. The responsivity of these photodetectors, which are based on optical rectification, is strongly influenced by their excited state lifetime. We believe that a much longer electron lifetime in the upper QD states and an increased lateral electron displacement are responsible for the observed improvement.

Quantitative, qualitative, and quasitative inquiries in human performance technology: Measure the past, observe the present, and imagine the potential

Performance ImprovementVolume 45, Issue 9 p. 8-13 Research Article Quantitative, qualitative, and quasitative inquiries in human performance technology: Measure the past, observe the present, and imagine the potential Sharon L. Bender PhD, Sharon L. Bender PhD Sharon L. Bender,: PhD, holds a doctorate in Organization and Management, an MSIM, an MBA, and a graduate certificate in Social Work and Community Service. She has a strong performance improvement, qualitative assurance, and policies and procedures background. As a professor, she has served on an institutional review board, and she has taught a wide range of subjects for multiple universities. As an author, she has produced such works as the Producing the Capstone Project textbook. She also serves as a business and academic advisor. She may be reached at admin@sharonbender.com.Search for more papers by this author Sharon L. Bender PhD, Sharon L. Bender PhD Sharon L. Bender,: PhD, holds a doctorate in Organization and Management, an MSIM, an MBA, and a graduate certificate in Social Work and Community Service. She has a strong performance improvement, qualitative assurance, and policies and procedures background. As a professor, she has served on an institutional review board, and she has taught a wide range of subjects for multiple universities. As an author, she has produced such works as the Producing the Capstone Project textbook. She also serves as a business and academic advisor. She may be reached at admin@sharonbender.com.Search for more papers by this author First published: 12 October 2006 https://doi.org/10.1002/pfi.4930450913 AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume45, Issue9October 2006Pages 8-13 RelatedInformation

Strong Performance Improvement of La0.6Sr0.4Co0.8Fe0.2O3 − δ SOFC Cathodes by Electrochemical Activation

It is shown that the electrochemical resistance of mixed conducting solid oxide fuel cell (SOFC) model cathodes can be reduced drastically by a short but strong dc polarization of the cell. The samples investigated are dense thin-film microelectrodes of on a yttria-stabilized zirconia solid electrolyte. Relative performance improvements of more than two orders of magnitude can be achieved with a cathodic dc bias of the order of 1 V, applied for a few minutes at fuel cell operating temperature. The positive effect on the electrode performance corresponds to an acceleration of the oxygen surface exchange reaction, initially the resistance determining process. For this surface-related resistance, absolute values as low as at 700°C have been obtained. After such an activation, the resistance slowly increases again on a much larger time scale, indicating the possibility of a steady performance enhancement by a periodic activation with short dc pulses. X-ray photoelectron spectra show that a strong cathodic polarization severely changes the cation concentrations within the outermost surface layer of the electrode, and these field-induced surface compositional changes are assumed to be the main cause of the performance improvement.

Critical Success Factors for Performance Improvement Programs

Most health care organizations struggle with the design and implementation of effective, systemwide improvement programs. In 2000, the University HealthSystem Consortium initiated a benchmarking project to identify the organizational elements that predict a successful perfermance improvement (PI) program and that are best suited to support change initiatives. Forty-one organizations completed a survey about the presence of critical components, processes used to improve performance, and organizational PI structures. Follow-up site visits were conducted at three organizations. CRITICAL SUCCESS FACTORS FOR A PI PROGRAM: Eight organizational success factors for an effective performance improvement program were identified: (1) Strong Administrative Fxecutive and Performance Improvement Leadership, (2) Active Involvement of the Board of Trustees, (3) Effective Oversight Structure, (4) Expert Performance Improvement Staff, (5) Physician Involvement and Accountability, (6) Active Staff Involvement, (7) Effective Use of Information Resources-Data Used for Decision Making, and (8) Effective Communication Strategy. The approach offered is grounded in the belief that effective organizational structures and processes are prerequisites to improving health care delivery. Although some empirical support for the proposed model is provided, additional research will be required to determine the effectiveness of this approach.

A multiple-population evolutionary approach to gate matrix layout

This paper deals with a Very-Large-Scale Integrated systems design problem that belongs to the NP(Nondeterministic Polynomial)-hard class. The Gate Matrix Layout problem has numerous applications in the chip-manufacturing industry and in other industrial settings. A memetic algorithm is employed to solve a set of benchmark instances, and numerical comparisons with a highly competitive method—a microcanonical optimization approach—are performed. Beyond the effectiveness of the method, shown by the results obtained for these instances, an additional goal of this work is to study how the performance of the algorithm is affected by the use of multiple populations and of different individual-migration policies between such populations. The results signal a strong performance improvement of multiple populations over single population approaches. Finally, the proposed algorithm presents several refinements, like structured populations and a specially tailored local search.