Stochastic Investigations for the Fractional Vector-Host Diseased Based Saturated Function of Treatment Model

The goal of this research is to introduce the simulation studies of the vector-host disease nonlinear system(VHDNS)along with the numerical treatment of artificial neural networks(ANNs)techniques supported by Levenberg-Marquardt backpropagation(LMQBP),known as ANNs-LMQBP.This mechanism is physically appropriate,where the number of infected people is increasing along with the limited health services.Furthermore,the biological effects have fadingmemories and exhibit transition behavior.Initially,the model is developed by considering the two and three categories for the humans and the vector species.The VHDNS is constructed with five classes,susceptible humans Sh(t),infected humans Ih(t),recovered humans Rh(t),infected vectors Iv(t),and susceptible vector Sv(t)based system of the fractional-order nonlinear ordinary differential equations.To solve the number of variations of the VHDNS,the numerical simulations are performed using the stochastic ANNs-LMQBP.The achieved numerical solutions for solving the VHDNS using the stochastic ANNs-LMQBP have been described for training,verifying,and testing data to decrease the mean square error(MSE).An extensive analysis is provided using the correlation studies,MSE,error histograms(EHs),state transitions(STs),and regression to observe the accuracy,efficiency,expertise,and aptitude of the computing ANNs-LMQBP.

Utilizing the Vector Autoregression Model (VAR) for Short-Term Solar Irradiance Forecasting

Forecasting solar irradiance is a critical task in the renewable energy sector, as it provides essential information regarding the potential energy production from solar panels. This study aims to utilize the Vector Autoregression (VAR) model to forecast solar irradiance levels and weather characteristics in the San Francisco Bay Area. The results demonstrate a correlation between predicted and actual solar irradiance, indicating the effectiveness of the VAR model for this task. However, the model may not be sufficient for this region due to the requirement of additional weather features to reduce disparities between predictions and actual observations. Additionally, the current lag order in the model is relatively low, limiting its ability to capture all relevant information from past observations. As a result, the model’s forecasting capability is limited to short-term horizons, with a maximum horizon of four hours.

3D Vector Reconstruction of the Neck Skeleton from the Anatomical Sections of Korean Visible Human at the Anatomical Laboratory of Paris Descartes

Aim: To perform a vector 3D reconstruction of the neck skeleton from the anatomical sections of the “Korean Visible Human” for educational purposes. Material and Methods: The anatomical subject was a 33-year-old Korean male who died of leukemia. It measured 164 cm and weighed 55 kgs. The anatomical cuts were made in 2010 after an MRI and a CT scan. A special saw (cryomacrotome) made it possible to make cuts on the frozen body of 0.2 mm thick or 5960 slices. Sections numbered 1500 to 2000 (500 neck sections) were used for this study. Manual contouring segmentation of each anatomical element of the anterior neck area was done using Winsurf software version 3.5 on a PC. Results: Our vector 3D neck model includes the following: cervical vertebrae, hyoid bone, sternum manubrium and clavicles. This vector model has been integrated into the virtual dissection table Diva3d, a new educational tool used by universities and medical schools to learn anatomy. This model was also put online on the Sketchfab website and printed in 3D using an ENDER 3 printer. Conclusion: This original work is a remarkable educational tool for the study of the skeleton of the neck and can also serve as a 3D atlas for simulation purposes for training therapeutic gestures.

3D Vector Reconstruction of the Muscles of the Ventral Region of the Neck from Anatomical Sections of Korean Visible Human at the Paris Descartes Anatomy Laboratory

Objective: To carry out a 3D vector reconstruction of the muscles of the ventral region of the neck from anatomical sections of the “Korean Visible Human” for educational purposes. Materials and Methods: The anatomical subject was a 33-year-old Korean man who died of leukemia. He was 164 cm tall and weighed 55 kgs. The anatomical sections were made in 2010 after an MRI and a CT scan. A special saw (cryomacrotome) made it possible to make cuts 0.2 mm thick on the frozen body, i.e. 5960 cuts. Sections numbered 1500 to 2000 (or 500 cuts covering the neck) were used for our study. A segmentation by manual contouring of each anatomical element of the anterior neck region was done using Winsurf version 3.5 software on a laptop PC running Windows 7 equipped with an 8 gigabyte RAM. Results: We modeled the sternocleidomastoid muscles, the supra-hyoid muscles, the infra-hyoid muscles and the muscle structures of the anterior neck region, the aero-digestive axis of the anterior neck region and the vasculo-nervous axis of the neck. This model is easily manipulated using the Acrobat 3Dpdf interface. Each item accessible in a menu can be displayed, hidden or made transparent, and 3D labels are available as well as educational menus for learning anatomy. This vector model has been integrated into the Diva3d virtual dissection table, a new educational tool used by universities and medical schools to learn anatomy. This model was also uploaded to the Sketchfab? website and 3D printed using an ENDER? pro 3 printer. Conclusion: This original work constitutes a remarkable educational tool for the anatomical study of the anterior neck region and can also be used as a 3D atlas for simulation purposes for training in therapeutic gestures.

China’s Monetary Policy Impacts on Money and Stock Markets

This study investigated the impact of China’s monetary policy on both the money market and stock markets,assuming that non-policy variables would not respond contemporaneously to changes in policy variables.Monetary policy adjustments are swiftly observed in money markets and gradually extend to the stock market.The study examined the effects of monetary policy shocks using three primary instruments:interest rate policy,reserve requirement ratio,and open market operations.Monthly data from 2007 to 2013 were analyzed using vector error correction(VEC)models.The findings suggest a likely presence of long-lasting and stable relationships among monetary policy,the money market,and stock markets.This research holds practical implications for Chinese policymakers,particularly in managing the challenges associated with fluctuation risks linked to high foreign exchange reserves,aiming to achieve autonomy in monetary policy and formulate effective monetary strategies to stimulate economic growth.

Small-time scale network traffic prediction based on a local support vector machine regression model

In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.

A new magneto-cardiogram study using a vector model with a virtual heart and the boundary element method

A cardiac vector model is presented and verified, and then the forward problem for cardiac magnetic fields and electric potential are discussed based on this model and the realistic human torso volume conductor model, including lungs. A torso-cardiac vector model is used for a 12-lead electrocardiographic （ECG） and magneto-cardiogram （MCG） simulation study by using the boundary element method （BEM）. Also, we obtain the MCG wave picture using a compound four-channel HTc.SQUID system in a magnetically shielded room. By comparing the simulated results and experimental results, we verify the cardiac vector model and then do a preliminary study of the forward problem of MCG and ECG. Therefore, the results show that the vector model is reasonable in cardiac electrophysiology.

FAULT DIAGNOSIS APPROACH BASED ON HIDDEN MARKOV MODEL AND SUPPORT VECTOR MACHINE

Aiming at solving the problems of machine-learning in fault diagnosis, a diagnosis approach is proposed based on hidden Markov model （HMM） and support vector machine （SVM）. HMM usually describes intra-class measure well and is good at dealing with continuous dynamic signals. SVM expresses inter-class difference effectively and has perfect classify ability. This approach is built on the merit of HMM and SVM. Then, the experiment is made in the transmission system of a helicopter. With the features extracted from vibration signals in gearbox, this HMM-SVM based diagnostic approach is trained and used to monitor and diagnose the gearbox＇s faults. The result shows that this method is better than HMM-based and SVM-based diagnosing methods in higher diagnostic accuracy with small training samples.

High-rise building fire pre-warning model based on the support vector regression

Aiming at reducing the deficiency of the traditional fire pre-warning algorithms and the intelligent fire pre-warning algorithms such as artificial neural network,and then to improve the accuracy of fire prewarning for high-rise buildings,a composite fire pre-warning controller is designed according to the characteristic（ nonlinear,less historical data,many influence factors）,also a high-rise building fire pre-warning model is set up based on the support vector regression（ SV R）. Then the wood fire standard history data is applied to make empirical analysis. The research results can provide a reliable decision support framework for high-rise building fire pre-warning.

THE COMPREHENSION,SOME PROBLEMS AND SUGGES-TIONS TO SYMBOLIC VECTOR METHOD AND SOME DEFENSES FOR GIBBS'SYMBOL

The comprehension of Prof. Tai's symbolic vector method in vector analysis presented, some problems are found and some suggestions are provided to solve them. Some defenses for Gibbs' symbol have been made as well. Key words: symbolic vector(? ?; operator; vector product model

Numerical Analysis of Stochastic Vector Borne Plant Disease Model

We are associating the solutions of stochastic and deterministic vector borne plant disease model in this manuscript.The dynamics of plant model depends upon threshold number P^(∗).If P^(∗)<1 then condition helpful to eradicate the disease in plants while P^(∗)>1 explains the persistence of disease.Inappropriately,standard numerical systems do not behave well in certain scenarios.We have been proposed a structure preserving stochastic non-standard finite difference system to analyze the behavior of model.This system is dynamical consistent,positive and bounded as defined by Mickens.

Vector Affine Quantization Can Create Valid Quantum Field Theories

Affine quantization, a parallel procedure to canonical quantization, needs to use its principal quantum operators, specifically D = (PQ+QP)/2 and Q ≠ 0, to represent appropriate kinetic factors, such as P2, which involves only one canonical quantum operator. The need for this requirement stems from path integral quantizations of selected problems that affine quantization can solve but canonical quantization fails to solve. This task is resolved for simple examples, as well as examples that involve scalar, and vector, quantum field theories.

Application of Auto-regressive Linear Model in Understanding the Effect of Climate on Malaria Vectors Dynamics in the Three Gorges Reservoir

It is important to understand the dynamics of malaria vectors in implementing malaria control strategies. Six villages were selected from different sections in the Three Gorges Reservoir fc,r exploring the relationship between the climatic ｜：actors and its malaria vector density from 1997 to 2007 using the auto-regressive linear model regressi^n method. The result indicated that both temperature and precipitation were better modeled as quadratic rather than linearly related to the density of Anopheles sinensis.

Word Embeddings and Semantic Spaces in Natural Language Processing

One of the critical hurdles, and breakthroughs, in the field of Natural Language Processing (NLP) in the last two decades has been the development of techniques for text representation that solves the so-called curse of dimensionality, a problem which plagues NLP in general given that the feature set for learning starts as a function of the size of the language in question, upwards of hundreds of thousands of terms typically. As such, much of the research and development in NLP in the last two decades has been in finding and optimizing solutions to this problem, to feature selection in NLP effectively. This paper looks at the development of these various techniques, leveraging a variety of statistical methods which rest on linguistic theories that were advanced in the middle of the last century, namely the distributional hypothesis which suggests that words that are found in similar contexts generally have similar meanings. In this survey paper we look at the development of some of the most popular of these techniques from a mathematical as well as data structure perspective, from Latent Semantic Analysis to Vector Space Models to their more modern variants which are typically referred to as word embeddings. In this review of algoriths such as Word2Vec, GloVe, ELMo and BERT, we explore the idea of semantic spaces more generally beyond applicability to NLP.

On a Partially Non-Stationary Vector AR Model with Vector GARCH Noises:Estimation and Testing

This paper studies a partially nonstationary vector autoregressive(VAR)model with vector GARCH noises.We study the full rank and the reduced rank quasi-maximum likelihood estimators(QMLE)of parameters in the model.It is shown that both QMLE of long-run parameters asymptotically converge to a functional of two correlated vector Brownian motions.Based these,the likelihood ratio(LR)test statistic for cointegration rank is shown to be a functional of the standard Brownian motion and normal vector,asymptotically.As far as we know,our test is new in the literature.The critical values of the LR test are simulated via the Monte Carlo method.The performance of this test in finite samples is examined through Monte Carlo experiments.We apply our approach to an empirical example of three interest rates.

文本分类技术研究

文本分类作为机器学习和信息检索之间的交叉学科,涉及到多个领域的技术。它的完善有赖于各个相关领域的技术发展和提高,该文介绍了文本分类过程中的各个关键技术和存在的问题,讨论了文本表示模型、分类算法、分类器性能评价原理和方法,最后并对今后的发展进行了展望。

Constant Speed Control for Complex Cross-section Welding Using Robot Based on Angle Self-Test

Expandable profile liner（EPL） is a promising new oil well casing cementing technique, and welding is a major EPLs connection technology. Connection of EPL is still in the stage of manual welding so far, automatic welding technology is a hotspot of EPL which is one of the key technologies to be solved. A robot for automatic welding of＂8＂ type EPL is studied. Four quadrants of mathematical equations of the 8-shaped cross-section track of EPL, consisting of multiple arcs, are established. Mechanism program for complex cross-section welding of EPL based on angle detection is proposed according to characteristics of small size, small valleys, and large forming errors, etc. A welding velocity vector control model is established by linkage control of a welding vehicle, a small driven actuator, and a height tracking mechanism. A constant speed control model based on an angle and symmetrical analysis model of rectangular coordinate system for EPL is built. Constraint conditions of constant speed control between each section are analyzed with 4 sections in first quadrant as an example, and cooperation work mechanism of the welding vehicle and the small tracking actuator is established based on pressure detection. The constant speed control model using angle self-test can be used to avoid the need for a precise mathematical model for tracking control and to adapt manufacture and installation deviation of EPL workpiece. The model is able to solve constant speed and trajectory tracking problems of EPL cross-section welding. EPL seams welded by the studied robot are good in appearance, and non-destructive testing（NDT） shows the seams are good in quality with no welding defects. Bulge tests show that the maximum pressure of welded EPL is 35 MPa, which can fulfill expansion performance requirements.

An E-Commerce Recommender System Based on Content-Based Filtering

Content-based filtering E-commerce recommender system was discussed fully in this paper. Users＇ unique features can be explored by means of vector space model firstly. Then based on the qualitative value of products informa tion, the recommender lists were obtained. Since the system can adapt to the users＇ feedback automatically, its performance were enhanced comprehensively. Finally the evaluation of the system and the experimental results were presented.

Hybrid Chinese Information Retrieval Model Based on the Combination of Keyword and Concept

A hybrid model that is based on the Combination of keywords and concept was put forward. The hybrid model is built on vector space model and probabilistic reasoning network. It not only can exert the advantages of keywords retrieval and concept retrieval but also can compensate for their shortcomings. Their parameters can be adjusted according to different usage in order to accept the best information retrieval result, and it has been proved by our experiments.

A statistical analysis of spatiotemporal variations and determinant factors of forest carbon storage under China's Natural Forest Protection Program

The Natural Forest Protection Program(NFPP)is one of the key ecological forestry programs in China.It not only facilitates the improvement of forest ecological quality in NFPP areas,but also plays a significant role in increasing the carbon storage of forest ecosystems.The program covers 17 provinces,autonomous regions,and municipalities with correspondingly diverse forest resources and environments,ecological features,engineering measures and forest management regimes,all of which affect regional carbon storage.In this study,volume of timber harvest,tending area,pest-infested forest,firedamaged forest,reforestation,and average annual precipitation,and temperature were evaluated as factors that influence carbon storage.We developed a vector autoregression model for these seven indicators and we studied the dominant factors of carbon storage in the areas covered by NFPP.Timber harvest was the dominant factorinfluencing carbon storage in the Yellow and Yangtze River basins.Reforestation contributed most to carbon storage in the state-owned forest region in Xinjiang.In state-owned forest regions of Heilongjiang and Jilin Provinces,the dominant factors were forest fires and forest cultivation,respectively.For the enhancement of carbon sequestration capacity,a longer rotation period and a smaller timber harvest are recommended for the Yellow and Yangtze River basins.Trees should be planted in stateowned forests in Xinjiang.Forest fires should be prevented in state-owned forests in Heilongjiang,and greater forest tending efforts should be made in the state-owned forests in Jilin.