Abstract In 1995 an abrupt shift in the late-season (October–December) typhoon activity over western North Pacific (WNP) is detected by a Bayesian changepoint analysis. Interestingly, similar change also occurs sea surface temperature series Pacific, eastern and portions of Indian Ocean. All counts, lifespans, accumulated cyclone energy typhoons during 1995–2011 epoch decreased significantly, compared with that occurred 1979–94 epoch. The negative vorticity anomaly found to be leading...

We present a novel area-preservation mapping/flattening method using the optimal mass transport technique, based on Monge-Brenier theory. Our map approach is rigorous and solid in theory, efficient parallel computation, yet general for various applications. By comparison with conventional Monge-Kantorovich approach, our reduces number of variables from O(n2) to O(n), converts problem convex optimization problem, which can now be efficiently carried out by Newton's method. Furthermore,...

Abstract Bayesian analysis is applied to detect change points in the time series of annual tropical cyclone counts over central North Pacific. Specifically, a hierarchical approach involving three layers—data, parameter, and hypothesis—is formulated demonstrate posterior probability shifts throughout from 1966 2002. For data layer, Poisson process with gamma distributed intensity presumed. hypothesis “no intensity” “single are considered. Results indicate that there great likelihood point on...

Abstract In this study, a Poisson generalized linear regression model cast in the Bayesian framework is applied to forecast tropical cyclone (TC) activity central North Pacific (CNP) peak hurricane season (July–September) using large-scale environmental variables available up antecedent May and June. Specifically, five predictor are considered: sea surface temperatures, level pressures, vertical wind shear, relative vorticity, precipitable water. The Pearson correlation between seasonal TC...

Sepsis is an organ failure disease caused by infection resulting in extremely high mortality. Machine learning algorithms XGBoost and LightGBM are applied to construct two processing methods: mean method feature generation method, aiming predict early sepsis 6 hours advance. The methods constructed combining different features, including statistical strength window medical features. Miceforest multiple interpolation tackle large missing data problems. Results show that the outperforms...

Abstract A new approach to forecasting regional and seasonal tropical cyclone (TC) frequency in the western North Pacific using antecedent large-scale environmental conditions is proposed. This approach, based on TC track types, yields probabilistic forecasts its utility a smaller region demonstrated. Environmental variables used include monthly mean of sea surface temperatures, level pressures, low-level relative vorticity, vertical wind shear, precipitable water preceding May. The...

Abstract A Bayesian framework is developed to detect multiple abrupt shifts in a time series of the annual major hurricanes counts. The hurricane counts are modeled by Poisson process where intensity (i.e., rate) codified gamma distribution. Here, triple hypothesis space concerning rate considered: “a no change rate,” single and double rate.” hierarchical approach involving three layers—data, parameter, hypothesis—is formulated demonstrate posterior probability each possible its relevant...

coupled with low-latitude westerlies

Goal: The purpose of this study was to design a method for extracting the volitional EMG from recorded surface electromyography (EMG), contaminated by functional electrical stimulation (FES) artifact. Methods: Considering that FES artifact emerges periodically with rather large amplitude in nonstationary EMG, we designed an adaptive-matched filter (AMF) via genetic algorithm (GA) optimization. Both simulated and real data seven subjects were processed, using GA-AMF comb filter, respectively....

Real-time and accurate fault detection is essential to enhance the aircraft navigation system's reliability safety. The existent methods based on analytical model draws back at simultaneously detecting gradual sudden faults. On account of this reason, we propose an online solution non-analytical model. In article, system established belief rule base (BRB), where measuring residual its changing rate are used as inputs BRB function output. To overcome drawbacks current parameter optimization...

We present the conformal magnifier, a novel interactive focus+context visualization technique that magnifies region of interest (ROI) using mapping. Our framework supports arbitrary shape design magnifiers for user to enlarge ROI while globally deforming context without any cropping. By mathematically well-defined mapping theory and algorithm, is magnified with local preservation (angle distortion minimization), transition area between focus regions deformed smoothly continuously. After...

We introduce a modified dendrogram (MD) (with subtrees to represent clusters) and display it in 2D for multidimensional transfer function design. Such direct volume rendering employs space, termed attribute space. The MD reveals the hierarchical structure information of user can design an intuitive informative manner using interface instead where is hard ascertain relationship In addition, we provide capability interactively modify granularity MD. coarse-grained primarily shows global space...

Neuromuscular electrical stimulation (NMES) that stimulates skeletal muscles to induce contractions has been widely applied restore functions of paralyzed muscles. However, the architectural changes stimulated induced by NMES are still not well understood. The present study applies sonomyography (SMG) evaluate muscle architecture under NMES-induced and voluntary movements. quadriceps seven healthy subjects were tested for eight cycles during an extension exercise knee joint with/without...

Designing appropriate machine learning methods for identifying genes that have a significant discriminating power disease outcomes has become more and important our understanding of diseases at genomic level. Although many been developed applied to the area microarray gene expression data analysis, majority them are based on linear models, which however not necessarily underlying connection between target its associated explanatory genes. Linear model usually also bring in false positive...

This paper presents a Support Vector Regression (SVR) method for electric vehicle (EV) charging station load forecast based on genetic algorithm (GA) and particle swarm optimization (PSO). Fuzzy C-Means (FCM) clustering is used to establish similar day samples. GA global parameter searching PSO more accurately local searching. Load then regressed using SVR. The practical data of an EV were taken illustrate the proposed method. result indicates obvious improvement in forecasting accuracy...

The tongue diagnosis is an important diagnostic method in traditional chinese medicine (TCM). In this paper, we present a novel computerized inspection based on support vector machine (SVM). First, two kinds of quantitative features, chromatic and textural measures, are extracted from images by using popular image processing techniques. Then, Bayesian network employed to build the mapping relationships between these features diseases, respectively. Finally, comparison SVM BN classification....