The asymptotic relation between the first crossing point and the last exit time of Gaussian order statistics sequences

In this paper,we study the asymptotic relation between the first crossing point and the last exit time for Gaussian order statistics which are generated by stationary weakly and strongly dependent Gaussian sequences.It is shown that the first crossing point and the last exit time are asymptotically independent and dependent for weakly and strongly dependent cases,respectively.The asymptotic relations between the first crossing point and the last exit time for stationary weakly and strongly dependent Gaussian sequences are also obtained.

Comparative Analysis of Climatic Change Trend and Change-Point Analysis for Long-Term Daily Rainfall Annual Maximum Time Series Data in Four Gauging Stations in Niger Delta

The aim of this study is to establish the prevailing conditions of changing climatic trends and change point dates in four selected meteorological stations of Uyo, Benin, Port Harcourt, and Warri in the Niger Delta region of Nigeria. Using daily or 24-hourly annual maximum series (AMS) data with the Indian Meteorological Department (IMD) and the modified Chowdury Indian Meteorological Department (MCIMD) models were adopted to downscale the time series data. Mann-Kendall (MK) trend and Sen’s Slope Estimator (SSE) test showed a statistically significant trend for Uyo and Benin, while Port Harcourt and Warri showed mild trends. The Sen’s Slope magnitude and variation rate were 21.6, 10.8, 6.00 and 4.4 mm/decade, respectively. The trend change-point analysis showed the initial rainfall change-point dates as 2002, 2005, 1988, and 2000 for Uyo, Benin, Port Harcourt, and Warri, respectively. These prove positive changing climatic conditions for rainfall in the study area. Erosion and flood control facilities analysis and design in the Niger Delta will require the application of Non-stationary IDF modelling.

Unsupervised Time Series Segmentation: A Survey on Recent Advances

Time series segmentation has attracted more interests in recent years,which aims to segment time series into different segments,each reflects a state of the monitored objects.Although there have been many surveys on time series segmentation,most of them focus more on change point detection(CPD)methods and overlook the advances in boundary detection(BD)and state detection(SD)methods.In this paper,we categorize time series segmentation methods into CPD,BD,and SD methods,with a specific focus on recent advances in BD and SD methods.Within the scope of BD and SD,we subdivide the methods based on their underlying models/techniques and focus on the milestones that have shaped the development trajectory of each category.As a conclusion,we found that:(1)Existing methods failed to provide sufficient support for online working,with only a few methods supporting online deployment;(2)Most existing methods require the specification of parameters,which hinders their ability to work adaptively;(3)Existing SD methods do not attach importance to accurate detection of boundary points in evaluation,which may lead to limitations in boundary point detection.We highlight the ability to working online and adaptively as important attributes of segmentation methods,the boundary detection accuracy as a neglected metrics for SD methods.

Quasi-anti-parity–time-symmetric single-resonator micro-optical gyroscope with Kerr nonlinearity

Parity–time(PT) and quasi-anti-parity–time(quasi-APT) symmetric optical gyroscopes have been proposed recently which enhance Sagnac frequency splitting. However, the operation of gyroscopes at the exceptional point(EP) is challenging due to strict fabrication requirements and experimental uncertainties. We propose a new quasi-APT-symmetric micro-optical gyroscope which can be operated at the EP by easily shifting the Kerr nonlinearity. A single resonator is used as the core sensitive component of the quasi-APT-symmetric optical gyroscope to reduce the size, overcome the strict structural requirements and detect small rotation rates. Moreover, the proposed scheme also has an easy readout method for the frequency splitting. As a result, the device achieves a frequency splitting 10~5 times higher than that of a classical resonant optical gyroscope with the Earth's rotation. This proposal paves the way for a new and valuable method for the engineering of micro-optical gyroscopes.

Shifted first arrival point travel time NMO inversion

Serious stretch appears in shallow long offsset signals after NMO correction. In this article we study the generation mechanism of NMO stretch, demonstrate that the conventional travel time equation cannot accurately describe the travel time of the samples within the same reflection wavelet. As a result, conventional NMO inversion based on the travel time of the wavelet＇s central point occurs with errors. In this article, a travel time equation for the samples within the same wavelet is reconstructed through our theoretical derivation （the shifted first arrival point travel time equation）, a new NMO inversion method based on the wavelet＇s first arrival point is proposed. While dealing with synthetic data, the semblance coefficient algorithm equation is modified so that wavelet first arrival points can be extracted. After that, NMO inversion based on the new velocity analysis is adopted on shot offset records. The precision of the results is significantly improved compared with the traditional method. Finally, the block move NMO correction based on the first arrival points travel times is adopted on long offset records and non-stretched results are achieved, which verify the proposed new equation.

Perihematoma Damage at Different Time Points in Experimental Intracerebral Hemorrhage

The damage degree of neurons in perilesion at different time points was observed in order to explore the optimal operation occasion. Piglet lobar hematomas were produced by pressure-controlled infusions of 2.5 mL autonomous blood into the right frontal hemispheric white matter over 15 min, and the metabolic changes were ambulatorily detected with MRS at 3rd, 12th, 24th and 48th h after hematoma induction. Brain tissues of perihematoma were also obtained at different time points. The transcription level of Bax gene was detected by in situ hybridization and apoptosis by TUNEL technique, and the pathologic change of neurons was observed under an electron microscope. The results showed that the number of Bax positive cells reached the peak at 24 h （79.00± 4.243/5 fields）. There was no significant difference in A values between 3 h and 6 h, 12 h （P〉 0. 05）, but there significant difference between 24 h and 3 h, 6 h, 12 h （P〈0. 05）. The number of apoptotic cells reached the peak at 24 h （P〈0. 001）, and there was no significant difference between 3 h and 6 h （P=0. 999）. The area of the apoptotic cells showed no significant difference between 3 h and 6 h or among 3 h, 6 h and 6 h （P〉0.05）. Lac peak mainly occurred at 24 h and 48 h, while on the healthy side, no Lac peak was detectable. The ratio of NAA/Cr presented a descent tendency, but there was no significant difference among the groups before 12 h （P〉0. 05）, there was very significant difference between 3, 6 and 24, 48 h （P〈0. 01）. Under electronic microscopy, the neuronal damage surrounding hematoma in 3 to 6 h was milder than in 24 h to 48 h. It was concluded that the secondary apoptosis, damage and metabolic disturbance of the neurons surround- ing hematoma was milder in 3-6 h in acute intracerebral hemorrhage, while obviously aggravated in 24-48 h. An effective intervention is needed to reduce secondary damage as soon as possible.

A simulation study of sampling time point designing for therapeutic drug monitoring based on a population pharmacokinetic model

Aim To develop a method to estimate population pharmacokinetic parameters with the limited sampling time points provided clinically during therapeutic drug monitoring. Methods Various simulations were attempted using a one-compartment open model with the first order absorption to determine PK parameter estimates with different sampling strategies as a validation of the method. The estimated parameters were further verified by comparing to the observed values. Results The samples collected at the single time point close to the non-informative sampling time point designed by this method led to bias and inaccurate parameter estimations. Furthermore, the relationship between the estimated non-informative sampling time points and the values of the parameter was examined. The non-informative sampling time points have been developed under some typical occasions and the results were plotted to show the tendency. As a result, one non-informative time point was demonstrated to be appropriate for clearance and two for both volume of distribution and constant of absorption in the present study. It was found that the estimates of the non-informative sampling time points developed in the method increase with increases of volume of distribution and the decrease of clearance and constant of absorption. Conclusion A rational sampling strategy during therapeutic drug monitoring can be established using the method present in the study.

THE INFLUENCE OF ELECTRO-ACUPUNCTURE AT NEIGUAN AND FIVE SHU POINTS OF TWELVE REGULAR MERIDIANS AT DIFFERENT TIME ON SYSTOLIC TIME INTERVAL OF NORMAL YOUNG ADULTS

The influence of electro-acupuncture at Neiguan (PC 6)and five shu points of twelve regular meridians at different time on systolic time interval (ST I) of normal young adultswere studied with 6×6 Latin square design in this work.In 12 groups according to 12 regular merldlans,the STIs were measured respectively just before and after electro-acupuncture on Neiguan andfive shu points at 00:00,04:00,08:00,12:00,16:00 and 20:00 of a day.It was found thatexcept the PEPI and PEPI/LVETI ratio among Shenmen(HT 7),Shaochong(HT 9)and Neiguan,Guanchong(TE)and Yemen(TE 2)points,the effects of electro-acupuncture at Neiguan pointand five shu points of twelve regular meridians on the indices of STI of normal young adults wereshowing no slgnificant differences.There also was no difference in different sex.But the indices ofSTI were changed when electroacupuncture on the different points of different meridians at differenttime.

Analysis of Change Point in Surface Temperature Time Series Using Cumulative Sum Chart and Bootstrapping for Asansol Weather Observation Station, West Bengal, India

This paper aims to detect the short-term as well as long-term change point in the surface air temperature time series for Asansol weather observation station, West Bengal, India. Temperature data for the period from 1941 to 2010 of the said weather observatory have been collected from Indian Meteorological Department, Kolkata. Variations and trends of annual mean temperature, annual mean maximum temperature and annual minimum temperature time series were examined. The cumulative sum charts (CUSUM) and bootstrapping were used for the detection of abrupt changes in the time series data set. Statistically significant abrupt changes and trends have been detected. The major change point in the annual mean temperatures occurred around 1986 (0.57°C) at the period of 25 years in the long-term regional scale. On the other side, the annual mean maximum and annual mean minimum temperatures have distinct change points at level 1. There are abrupt changes in the year 1961 (Confidence interval 1961, 1963) for the annual mean maximum and 1994 (Confidence interval 1993, 1996) for the annual mean minimum temperatures at a confidence level of 100% and 98%, respectively. Before the change, the annual mean maximum and annual mean minimum temperatures were 30.90°C and 23.99°C, respectively, while after the change, the temperatures became 33.93°C and 24.84°C, respectively. Over the entire period of consideration (1941-2010), 11 forward and backward changes were found in total. Out of 11, there are 3 changes (1961, 1986 and 2001) in annual mean temperatures, 4 changes (1957, 1961, 1980 and 1994) in annual mean maximum temperatures, and rest 4 changes (1968, 1981, 1994 and 2001) are associated with annual mean minimum temperature data set.

Support vector regression modeling in recursive just-in-time learning framework for adaptive soft sensing of naphtha boiling point in crude distillation unit

Prediction of primary quality variables in real time with adaptation capability for varying process conditions is a critical task in process industries.This article focuses on the development of non-linear adaptive soft sensors for prediction of naphtha initial boiling point(IBP)and end boiling point(EBP)in crude distillation unit.In this work,adaptive inferential sensors with linear and non-linear local models are reported based on recursive just in time learning(JITL)approach.The different types of local models designed are locally weighted regression(LWR),multiple linear regression(MLR),partial least squares regression(PLS)and support vector regression(SVR).In addition to model development,the effect of relevant dataset size on model prediction accuracy and model computation time is also investigated.Results show that the JITL model based on support vector regression with iterative single data algorithm optimization(ISDA)local model(JITL-SVR:ISDA)yielded best prediction accuracy in reasonable computation time.

Data point selection for weighted least square fitting of cavity decay time constant

For the accurate extraction of cavity decay time, a selection of data points is supplemented to the weighted least square method. We derive the expected precision, accuracy and computation cost of this improved method, and examine these performances by simulation. By comparing this method with the nonlinear least square fitting （NLSF） method and the linear regression of the sum （LRS） method in derivations and simulations, we find that this method can achieve the same or even better precision, comparable accuracy, and lower computation cost. We test this method by experimental decay signals. The results are in agreement with the ones obtained from the nonlinear least square fitting method.

On-line outlier and change point detection for time series

The detection of outliers and change points from time series has become research focus in the area of time series data mining since it can be used for fraud detection, rare event discovery, event/trend change detection, etc. In most previous works, outlier detection and change point detection have not been related explicitly and the change point detections did not consider the influence of outliers, in this work, a unified detection framework was presented to deal with both of them. The framework is based on ALARCON-AQUINO and BARRIA's change points detection method and adopts two-stage detection to divide the outliers and change points. The advantages of it lie in that: firstly, unified structure for change detection and outlier detection further reduces the computational complexity and make the detective procedure simple; Secondly, the detection strategy of outlier detection before change point detection avoids the influence of outliers to the change point detection, and thus improves the accuracy of the change point detection. The simulation experiments of the proposed method for both model data and actual application data have been made and gotten 100% detection accuracy. The comparisons between traditional detection method and the proposed method further demonstrate that the unified detection structure is more accurate when the time series are contaminated by outliers.

Study on the development and usage of a cardiopulmonary resuscitation time point recorder

BACKGROUND: To invent a novel cardiopulmonary resuscitation(CPR) time point recorder to synchronously and automatically record the time and to identify its effectiveness in humans.METHODS: A CPR time point recorder was invented after the doctors were familiar with the traditional Utstein recovery registration mode and mastered the registration time points required. The progress of CPR was simulated. The standard and correct times were recorded, and the doctors performing the recovery collected the data about the times using our CPR time point recorder or the memory registration mode.RESULTS: The deviation times were 21.4±24.7 seconds for the memory group and 3.57±4.58 seconds for CPR time point recorder group. The deviation of times increased signifi cantly depending on the increase of the operation items in the memory group. A similar phenomenon was found in the timer group but with a smaller difference(P<0.01).CONCLUSION: A CPR time point recorder could reduce the deviation of operate-time, especially after a long-time operation, and for procedures with more operating items, compared with the memory mode. It was a more advantageous and accurate method for the Utstein registration.

Automatic Feature Point Detection and Tracking of Human Actions in Time-of-flight Videos

Detecting feature points on the human body in video frames is a key step for tracking human movements. There have been methods developed that leverage models of human pose and classification of pixels of the body image. Yet, occlusion and robustness are still open challenges. In this paper, we present an automatic, model-free feature point detection and action tracking method using a time-of-flight camera. Our method automatically detects feature points for movement abstraction. To overcome errors caused by miss-detection and occlusion, a refinement method is devised that uses the trajectory of the feature points to correct the erroneous detections. Experiments were conducted using videos acquired with a Microsoft Kinect camera and a publicly available video set and comparisons were conducted with the state-of-the-art methods. The results demonstrated that our proposed method delivered improved and reliable performance with an average accuracy in the range of 90 %.The trajectorybased refinement also demonstrated satisfactory effectiveness that recovers the detection with a success rate of 93.7 %. Our method processed a frame in an average time of 71.1 ms.

Optimal time point for the transplantation of neural stem cells induced to differentiate with retinoic acid

Previous studies have demonstrated that differentiated neural stem cells （NSCs） are more suitable for transplantation than non-differentiated NSCs. In this study, NSCs were expanded in vitro for two passages, induced with retinoic acid to differentiate, and harvested between 1 6 days later. They were subsequently cultured in artificial cerebrospinal fluid for an additional 3 days, dudng which their growth and morphology was monitored. NSCs induced for 4 days exhibited a peak rate of cells differentiating into neurons and robust growth. Our results indicate that the optimal time point for transplanting NSCs is following a 4-day period of induced differentiation.

Time Sequence Change-Point Model of Electrostatic State Parameters of Aircraft Engine

Electrostatic monitoring technology of particle charging information can facilitate online monitoring of aero-engine,which effectively enhances engine fault diagnosis and health managements.Unlike traditional engine state monitoring technologies,aircraft engine monitoring by gas path electrostatic monitoring not only covers the predicted information source itself,but also detects the information that can provide an early warnings for initial fault states through gas path charging levels.This paper establishes a non-stationary time sequence change-point model for anomaly recognition of electrostatic signals based on change-point theory combined with difference method of non-stationary time series.Finally,electrostatic induction data were utilized by the engine life test for a particular aircraft to validate the proposed algorithm.The results indicate that the activity level and the event rate were0.5—0.8(nc)and 50%,respectively,which were far greater than 4—12(pc)and 0—4% under normal working conditions of the engine.

Improving the detecting efficiency of suspected gastrointestinal tumors with dual-time-point 18F-FDG PET/CT

We conducted a retrospective analysis of 221 subjects with 256 suspected gastrointestinal lesions from2007 to 2015 to explore the detecting efficiency of dualtime-point fluorine-18 fludeoxyglucose(^(18)F-FDG) positron emission tomography/computed tomography(PET/CT)and pathology examination. The abdominal delayed PET/CT was performed within 45 min of the conventional scan.The change in maximum standardized uptake value(ASUV_(max)) and morphological features of the suspected lesions between the conventional and dual-time-point PET/CT were compared. The sensitivity, specificity, positive predictive value, and negative predictive value(NPV) of conventional PET/CT were 81.6%(84/103), 56.2%(86/153), 55.6%(84/151), and 81.9%(86/105), respectively.Those of dual-time-point PET/CT were 94.1%(97/103),78.4%(120/153), 74.6%(97/130), and 95.2%(120/126),respectively. There was a significant difference between the conventional and dual-time-point PET/CT(P < 0.005).The SUV_(early) and the %△SUV_(max) could not present more information in differential diagnoses, but the rate of tumors with increased SUVdelay accounted for 79.6%(82/103) and more than that of nonneoplastic lesions(15.5%, 29/187)(x^2= 115.5, P < 0.01). Therefore, the dual-time-point^(18)F-FDG PET/CT had a higher sensitivity and NPV than the conventional PET/CT to detect gastrointestinal tumors.The constant morphology and increased SUV_(delay) help to detect the tumors and adding delayed imaging on the locality will be an effective method when we accidentally find a suspected gastrointestinal tumor on the conventional PET/CT images.

Change Point Detection and Trend Analysis for Time Series

Trend analysis and change point detection in a time series are frequent analysis tools.Change point detection is the identification of abrupt variation in the process behaviour due to natural or artificial changes,whereas trend can be defined as estimation of gradual departure from past norms.We analyze the time series data in the presence of trend,using Cox-Stuart methods together with the change point algorithms.We applied the methods to the nearsurface wind speed time series for Australia as an example.The trends in near-surface wind speeds for Australia have been investigated based upon our newly developed wind speed datasets,which were constructed by blending observational data collected at various heights using local surface roughness information.The trend in wind speed at 10 m is generally increasing while at 2 m it tends to be decreasing.Significance testing,change point analysis and manual inspection of records indicate several factors may be contributing to the discrepancy,such as systematic biases accompanying instrument changes,random data errors(e.g.accumulation day error)and data sampling issues.Homogenization technique and multiple-period trend analysis based upon change point detections have thus been employed to clarify the source of the inconsistencies in wind speed trends.

Stereo Matching of Planar Curves Composed of Time Stamped Points

Matching features such as curve segments in stereo images play a very important role in scene recomtruction. In this paper, a stereo matching algorithm for the trajectories composed of time stamped points is proposed. Based on time stamped points, planar curve match measurements are given first, such as time constraint, cross-ratio invariant constraint and eplpolar geometry constraint; then, a trajectory matching method is proposed based on epipolar geometry constraint and cross-ratio invariant constraint. In order to match the planar curve segments projected by perspective projection system, the curve start time and end time are selected first to prepare match candidates. Then, the epipolar equation is used to discard the unmatched curve segment candidates. At last, a cross ratio invariant constxaint is used to find the most matched curve segments. If their match measurement is higher than the specialized threshold, a candidate with the least cross ratio difference is then selected as the match result; otherwise, no match is found. Unlike the conventional planar curve segments matching algorithm, this paper presents a weakly calibrated binocular stereo vision system which is based on wide baseline. The stamped points are obtained by targets detecting method of flying objects from image sequences. Due to wide baseline, there must exist the projection not in epipolar monotonic order or the curve segments located in very short distance and keeping the epipolar monotonic order. By using the method mentioned above, experiments are made to match planar curve segments not only in epipolar monotonic order but also not in epipolar monotonic order. The results show that the performance of our curve matching algorithm is effective for matching the arc-like planar trajectories composed of time stamped points.

Determination of a Cut-Off Point of a Scale for Achievement Motive in Geriatrics That Predicts the Frequency of Undertaking Instrumental Activities of Daily Living in Community-Dwelling Elderly People

Background: Among elderly people, rehabilitation is important for reducing the risk of falls and hospitalization and to maintain an independent life for longer. Motivation is a factor for elderly people to lead an active daily life and leave home more frequently. Purpose: The purposes of this study were to determine the optimal cut-off point in the Scale for Achievement Motive in Geriatrics (SAMG) that could identify individuals as inactive or active, based on the Frenchay Activities Index (FAI), and to compare characteristics between active and inactive groups classified by the cut-off point. Methods: A cross-sectional study of 285 community-dwelling elderly people measured SAMG and FAI and physical function. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) that was the optimal cut-off point for the SAMG total score, with the associated sensitivity and 1-specificity when compared with the FAI results. Demographic parameters and physical function were compared between two groups defined by cut-off point. Results: The AUC was 0.78, the optimal cut-off for SAMG total score for indicating inactivity was ≤48, the sensitivity was 77.98% and the 1-specificity was 75.00%. The group with SAMG score >48 was characterized by a significantly higher proportion of women, fewer people sharing a house, and participation in more hobbies. Discussion: A cut-off point of 48 in the SAMG could be a predictive index of motivation toward goals for individuals with inactive daily activities. The group with score higher than the cut-off was characterized by more women, fewer people living together, and more hobbies than the group with lower scores.