A New Selective Neural Network Ensemble Method Based on Error Vectorization and Its Application in High-density Polyethylene (HDPE) Cascade Reaction Process

Chemical processes are complex, for which traditional neural network models usually can not lead to satisfactory accuracy. Selective neural network ensemble is an effective way to enhance the generalization accuracy of networks, but there are some problems, e.g., lacking of unified definition of diversity among component neural networks and difficult to improve the accuracy by selecting if the diversities of available networks are small. In this study, the output errors of networks are vectorized, the diversity of networks is defined based on the error vectors, and the size of ensemble is analyzed. Then an error vectorization based selective neural network ensemble (EVSNE) is proposed, in which the error vector of each network can offset that of the other networks by training the component networks orderly. Thus the component networks have large diversity. Experiments and comparisons over standard data sets and actual chemical process data set for production of high-density polyethylene demonstrate that EVSNE performs better in generalization ability.

Multi-camera calibration method based on minimizing the difference of reprojection error vectors

In order to achieve a high precision in three-dimensional（3D） multi-camera measurement system, an efficient multi-cameracalibration method is proposed. A stitching method of large scalecalibration targets is deduced, and a fundamental of multi-cameracalibration based on the large scale calibration target is provided.To avoid the shortcomings of the method, the vector differencesof reprojection error with the presence of the constraint conditionof the constant rigid body transformation is modelled, and mini-mized by the Levenberg-Marquardt （LM） method. Results of thesimulation and observation data calibration experiment show thatthe accuracy of the system calibrated by the proposed methodreaches 2 mm when measuring distance section of 20 000 mmand scale section of 7 000 mm × 7 000 mm. Consequently, theproposed method of multi-camera calibration performs better thanthe fundamental in stability. This technique offers a more uniformerror distribution for measuring large scale space.

Metrology of Optical Communication Systems Using Error Vector Magnitude

Error vector magnitude (EVM) as a performance metric for M-ary quadrature amplitude modulation (QAM) formats in optical coherent systems is presented. It is shown that the calibrated BER, which would otherwise be under-estimated without the correction factor, can reliably monitor the performance of optical coherent systems near the target BER of 10-3 for quadrature phase shift keying (QPSK), 16-QAM, and 64-QAM employing carrier phase recovery with differential decoding to compensate for laser phase noise. The impact on the number of symbols used to estimate the BER from EVM analysis is also presented and compared to the BER obtained by error counting.

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.

Determination of Total Vector Error of the Phasor Measurement Unit (PMU) Using the Phase Angle Error of a Constant Amplitude Voltage Signal

This paper investigates the effect of the Phase Angle Error of a Constant Amplitude Voltage signal in determining the Total Vector Error (TVE) of the Phasor Measurement Unit (PMU) using MATLAB/Simulink. The phase angle error is measured as a function of time in microseconds at four points on the IEEE 14-bus system. When the 1 pps Global Positioning System (GPS) signal to the PMU is lost, sampling of voltage signals on the power grid is done at different rates as it is a function of time. The relationship between the PMU measured signal phase angle and the sampling rate is established by injecting a constant amplitude signal at two different points on the grid. In the simulation, 64 cycles per second is used as the reference while 24 cycles per second is used to represent the fault condition. Results show that a change in the sampling rate from 64 bps to 24 bps in the PMUs resulted in phase angle error in the voltage signals measured by the PMU at four VI Measurement points. The phase angle error measurement that was determined as a time function was used to determine the TVE. Results show that (TVE) was more than 1% in all the cases.

Economics,fundamentals,technology,finance,speculation and geopolitics of crude oil prices:an econometric analysis and forecast based on data from 1990 to 2017

It is of real and direct significance for China to cope with oil price fluctuations and ensure oil security. This paper aims to quantitatively analyze the specific contribution ratios of the complex factors influencing international crude oil prices and to establish crude oil price models to forecast long-term international crude oil prices. Six explanatory influential variables, namely Dow Jones Indexes, the Organization for Economic Cooperation and Development oil stocks, US rotary rig count, US dollar index, total open interest, which is the total number of outstanding contracts that are held by market participants at the end of each day, and geopolitical instability are specified, and the samples, from January 1990 to August 2017, are divided into six sub-periods. Moreover, the co-integration relationship among variables shows that the contribution ratios of all the variables influencing Brent crude oil prices are in accordance with the corresponding qualitative analysis. Furthermore, from September 2017 to December 2022 outside of the sample, the Vector Autoregressive forecasts show that annually averaged Brent crude oil prices for 2017-2022 would be $53.0, $61.3, $74.4, $90.0, $105.5, and $120.7 per barrel, respectively. The Vector Error Correction forecasts show that annual average Brent crude oil prices for 2017-2022 would be $53.0, $56.5, $58.5, $60.7, $63.0 and $65.4 per barrel, respectively.

Quantitative analysis of the performance of vector tracking algorithms

Vector tracking changes the classical structure of receivers. Combining signal tracking and navigation solution,vector tracking can realize powerful processing capabilities by the fusion technique of receiving channel and feedback correction. In this paper,we try to break through the complicated details of numerical analysis,consider the overall influencing factors of the residual in observed data,and use the intrinsic link between a conventional receiver and a vector receiver. A simple method for performance analysis of the vector tracking algorithm is proposed. Kalman filter has the same steady performance with the classic digital lock loop through the analysis of the relation between gain and band width. The theoretical analysis by the least squares model shows that the reduction of range error is the basis for the superior performance realized by vector tracking. Thus,the bounds of its performance enhancement under weak signal and highly dynamic conditions can be deduced. Simulation results verify the effectiveness of the analysis presented here.

Analysis of the Bovespa Futures and Spot Indexes With High Frequency Data

Data from the World Federation of Exchanges show that Brazil＇s Sao Paulo stock exchange is one of the largest worldwide in terms of market value. Thus, the objective of this study is to obtain univariate and bivariate forecasting models based on intraday data from the futures and spot markets of the BOVESPA index. The interest is to verify if there exist arbitrage opportunities in Brazilian financial market. To this end, three econometric forecasting models were built： ARFIMA, vector autoregressive （VAR）, and vector error correction （VEC）. Furthermore, it presents the results of a Granger causality test for the aforementioned series. This type of study shows that it is important to identify arbitrage opportunities in financial markets and, in particular, in the application of these models on data of this nature. In terms of the forecasts made with these models, VEC showed better results. The causality test shows that futures BOVESPA index Granger causes spot BOVESPA index. This result may indicate arbitrage opportunities in Brazil.

The Connection of Vegetation with Tourism Development and Economic Growth： A Case Study for Aruba

Vegetation is an important ecosystem on earth. It influences the earth system in many ways. Any influences on this fragile variable should be investigated, especially in a changing climate. Humans can have a positive or a negative influence on plants. This paper investigates the possible impact of tourism development and economic growth on vegetation health using cointegration and causality for Aruba. The proposed framework contributes to a better understanding on the use of remote sensing of vegetation response to tourism development and economic growth. Thereby, provide opportunities for improving the overall strategy for achieving sustainable development on a small island state. The calculations showed that there were relationships between the tourism demand and economic growth on the vegetation health on Aruba for the western part of the island. On the other hand, for the central part of the island, no relationships were found.

Microwave Oscillator Phase Noise Requirement for TD-SCDMA Wireless Communication Systems

In time division synchronous code division multiple access （TD-SCDMA） wireless communication systems, QPSK or 8PSK has been employed to support high data rate services and high efficiency in available bandwidth. The performance of such systems is affected by the phase noise of the microwave local oscillator. The phase noise model of synthesizer and the RF transceiver model for the phase noise effect are proposed for applications of TD-SCDMA systems. The relationship between the power spectral density （PSD） and root mean square （RMS） phase error is given. Then, the error vector magnitude （EVM） performance is analytically evaluated by using the single side band （SSB） phase noise. Theoretical results show agreement with those obtained by measurement data and therefore can be used to derive the TD-SCDMA system performance.

Financial Development, Trade Openness, and Economic Growth in Zambia

This study investigates the causal relationship among financial development, trade openness, and economic growth in Zambia from 1965 to 2011. Two measures of financial development were used： broad money and domestic credit to the private sector, each as a ratio of gross domestic product （GDP）. In this regard, two models were developed for each indicator. The Augmented Dickey-Fuller （ADF） and Phillips-Perron （PP） tests were used to determine stationarity of all the variables. Furthermore, Johansen test was employed to ascertain possible cointegration among variables. The vector error correction model （VECM） was employed to examine the short-run and long-run dynamics among the variables in each model. The results indicate that the relationship among financial development, trade openness, and economic growth is sensitive to the financial development indicator chosen.

A LOW EVM ZERO-IF RF TRANSMITTER FOR COGNITIVE RADIO APPLICATION

A zero-IF transmitter for Cognitive Radio(CR) application is presented.To effectively reduce the interference between Power Amplifier(PA) and Voltage Controlled Oscillator(VCO),two VCOs are adopted,one is 450 MHz and the other is from 1148 MHz to 1252 MHz with an 8 MHz step,so the frequency of them are different from the operational frequency of PA.The Local Oscillator(LO) of the modulator generated by mixing the signals of the two VCOs has a low phase noise of-82 dBc/Hz with an offset of 1 kHz.The measurement result of the transmitter shows that the Adjacent Channel Power Ratio(ACPR) is less than-47.5 dBc at 27 dBm output,and the Error Vector Magnitude(EVM) is less than 1.7%.

The Optimization of Radio over Fiber Link by Proper Link Gain Control

we demonstrate the adjustability of optimal input power(OIP) of the radio over fiber(RoF) link by proper link gain control in the central unit(CU) and remote antenna unit(RAU).The experiment results show that the reading and writing distance(RWD)of the radio frequency identification(RFID)service and the throughput of the WiFi service have a max increase of 3cm and 6.975Mbit/s respectively when the OIP value equals to output power of commercial products,compared with OIP value with 5-dBm right/left shift to the output power.

A high-linearity InGaP/GaAs HBT power amplifier for IEEE 802.11a/n

A three-stage 4.8-6 GHz monolithic power amplifier（PA） compatible with IEEE 802.11a/n designed based on an advanced 2μm InGaP/GaAs hetero-junction bipolar transistor（HBT） process is presented.The PA integrates input matching and closed-loop power control circuits on chip.Under 3.3 V DC bias,the amplifier achieves a ~31 dB small signal gain,excellent wide band input and output matching among overall 1.2 GHz bandwidth,and up to 24.5 dBm linear output power below EVM 3%with IEEE 802.11a 64QAM OFDM input signal.

A highly linear power amplifier for WLAN

A three-stage power amplifier （PA） for WLAN application in 2.4-2.5 GHz is presented. The proposed PA employs an adaptive bias circuit to adjust the operating point of the PA to improve the linearity of the PA. Two methods to short the 2nd harmonic circuit are compared in the area of efficiency and gain of the PA. The PA is taped out in the process of 2/zm InGaP/GaAs HBT and is tested by the evaluation board. The measured results show that 31.5 dB power gain and 29.3 dBm PldB with an associated 40.4% power added efficiency （PAE） under the single tone stimulus. Up to 26.5 dBm output power can be achieved with an error vector magnitude （EVM） of lower than 3% under the 64QAM/OFDM WLAN stimulus.

Price Discovery Function of Index Futures in China: Evidence from Daily Closing Prices

Price discovery is one of the main functions of stock index futures.Using the daily closing prices of the CSI 300 index and its index futures from April 2010 to April 2012,this paper applies a vector error correction model(VECM)and an impulse response function to conduct an empirical analysis on the price discovery function of index futures in China.This paper has the following four findings:(1)a solid cointegration relationship between the CSI 300 index and its index futures exists in the long run;(2)when prices deviate from the longterm equilibrium,the stock index reverses weakly,while the reversal of index futures is much stronger;(3)the daily lead-lag relationship between the prices of the CSI 300 index and its index futures contracts is not significant in the short run;()shocks from the spot market have a lasting impact upon the futures market,but not vice versa,due to the limited short-term adjustment ability of the spot market.