scholarly journals An Empirical Mode Decomposition for Establishing Spatiotemporal Air Quality Trends in Shandong Province, China

2021 ◽  
Vol 13 (22) ◽  
pp. 12901
Author(s):  
Huisheng Wu ◽  
Maogui Hu ◽  
Yaping Zhang ◽  
Yuan Han
Keyword(s):  
Air Quality ◽  
Empirical Mode Decomposition ◽  
Shandong Province ◽  
Analysis Method ◽  
Coal Consumption ◽  
Spatial And Temporal Scales ◽  
Mode Decomposition ◽  
Adaptive Data Analysis ◽  
The Government

Air pollution is a serious problem in China, and the government has taken a series of steps to solve it. However, it is still u2nclear how the situation has improved after years of atmospheric pollution control. Shandong Province, which has the second largest population and the highest coal consumption in China, was chosen to analyze the spatiotemporal air quality trends. We obtained daily air quality index (AQI) values from 91 stations in the province from 1 January 2014, to 31 December 2019, based on an adaptive data analysis method, empirical mode decomposition (EMD). The distribution of AQI in Shandong Province was heterogeneous at both spatial and temporal scales. All the stations could be divided into four clusters whose AQI trends decreased from 75 to 53, 95 to 68, 128 to 82, and 148 to 82, respectively. The overall trend of pollution became more serious from east to west in the province. The AQI is the largest in winter, followed by spring and autumn, and the smallest index occurs in summer. There are four types of annual trends of the AQI of each city. The overall downward trend indicates that the air quality of each city was improving annually.

scholarly journals Application research on the time–frequency analysis method in the quality detection of ultrasonic wire bonding

2021 ◽  
Vol 17 (5) ◽  
pp. 155014772110183
Author(s):  
Wuwei Feng ◽  
Xin Chen ◽  
Cuizhu Wang ◽  
Yuzhou Shi
Keyword(s):  
Empirical Mode Decomposition ◽  
Frequency Analysis ◽  
Recognition Accuracy ◽  
Wire Bonding ◽  
Analysis Method ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Mode Decomposition ◽  
Ultrasonic Wire Bonding

Imperfection in a bonding point can affect the quality of an entire integrated circuit. Therefore, a time–frequency analysis method was proposed to detect and identify fault bonds. First, the bonding voltage and current signals were acquired from the ultrasonic generator. Second, with Wigner–Ville distribution and empirical mode decomposition methods, the features of bonding electrical signals were extracted. Then, the principal component analysis method was further used for feature selection. Finally, an artificial neural network was built to recognize and detect the quality of ultrasonic wire bonding. The results showed that the average recognition accuracy of Wigner–Ville distribution and empirical mode decomposition was 78% and 93%, respectively. The recognition accuracy of empirical mode decomposition is obviously higher than that of the Wigner–Ville distribution method. In general, using the time–frequency analysis method to classify and identify the fault bonds improved the quality of the wire-bonding products.

scholarly journals Beach Development Strategy as Tourism Destination in Tabanan Bali

2019 ◽  
Vol 10 (01) ◽  
pp. 21219-21228
Author(s):  
Ni Luh Putu Suratini ◽  
I Ketut Arnawa ◽  
I Gusti Ngurah Alit Wiswasta
Keyword(s):  
Development Strategy ◽  
Swot Analysis ◽  
Community Leaders ◽  
Analysis Method ◽  
Tourist Destination ◽  
Factor Matrix ◽  
Tourist Destinations ◽  
The Government ◽  
Suitable Potential

The purpose of the study is to: (1). Analyzing the attractiveness of Pasut Beach as one of the tourist destinations in Tabanan Regency. (2). Analyze the strategy of developing Pasut Beach as a tourist destination in Tabanan Regency. The research location was determined by purposive sampling Pasut Beach, located in Tibubiu Village, Kerambitan District, Tabanan on the basis of having a very suitable potential to be developed into a tourist destination. The sample of the study was taken by 49 people consisting of elements from the Government, community leaders and tourism actors. This study uses qualitative qualitative analysis method (giving more detailed reviews and interpretations of the data obtained and SWOT analysis. Furthermore, in the SWOT method the External Strategy Factor Matrix (EFAS) model and the Internal Strategy Factor Matrix Model (IFAS) are used, followed by IFE matrix and EFE matrix to determine the weight, rating and score and to determine the strategy and position of the quadrant I - E matrix, Beach Pas po is in the position in quadrant I, with the S-O strategy where the values ​​of strength and opportunity are equally high ( use the power to get opportunities) by improving the quality of human resources, especially in the field of mastering technology, communication and information.

scholarly journals AIR QUALITY MONITORING OF KALABAHI-ALOR’S SEAPORT-EAST OF NUSA TENGGARA

2019 ◽  
Vol 3 (2) ◽  
pp. 130-133
Author(s):  
Rikson Siburian ◽  
Minsyahril Bukit ◽  
Herlince Sihotang ◽  
Saur Lumban Raja ◽  
Minto Supeno ◽  
...  
Keyword(s):  
Air Quality ◽  
Government Regulation ◽  
The Other ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Other Hand ◽  
The People ◽  
The Government

Evaluation of environment of seaport is needed as well as our responsibility to nature sustainability. The Alor’s seaport belongs to Pelindo III. In order to know the air quality of Alor’s seaport, we did this study. Our aims are to know level quality of air at Alor’s seaport and compare to the government regulation. This study refers to Pararosaniline (SOx), Saltzman (NOx), Particle Calculation (dust) and decibel (noisy) methods. We used four locations, those are A-1 (Entrance gate of PELINDO (8013’09.12”S, 124031’07.21”E)); A-2 (In front of passengers terminal (8013’08.75”S, 124031’01.60”E)); A-3 (Exit  gate Kalabahi’s seaport (8013’08.2”S, 124031’00.87”E)) and A-4 (In front of port of the people (8011’09.12”S, 124031’07.21”E)). Results show that the averages level of SOx, NOx and dust of A-1, A-2 and A-3 are 103.01, 104.65 and 107.47 (µg/Nm3), 37.87, 30.62, and 39.73 (µg/Nm3), 56.64, 47.47 and 50.72 (µg/Nm), respectively. On the other hand, the level of noisy of A-1, A-2, A-3 and A-4 are 68.76, 65.69, 65.20 and 73.60 (dBA), respectively. Base on all of data, we conclude that the air quality of Alor’s seaport is still appropriate according to government regulation (PP. No. 4, 1999).

scholarly journals Biomedical Photoacoustic Imaging Optimization with Deconvolution and EMD Reconstruction

2018 ◽  
Vol 8 (11) ◽  
pp. 2113 ◽  
Author(s):  
Chengwen Guo ◽  
Yingna Chen ◽  
Jie Yuan ◽  
Yunhao Zhu ◽  
Qian Cheng ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Empirical Mode Decomposition ◽  
Photoacoustic Imaging ◽  
Optimization Method ◽  
Positive Polarity ◽  
Image Optimization ◽  
Mode Decomposition ◽  
Phantom Studies ◽  
Micro Structures

A photoacoustic (PA) signal of an ideal optical absorbing particle is a single N-shape wave. PA signals are a combination of several individual N-shape waves. However, the N-shape wave basis leads to aliasing between adjacent micro-structures, which deteriorates the quality of final PA images. In this paper, we propose an image optimization method by processing raw PA signals with deconvolution and empirical mode decomposition (EMD). During the deconvolution procedure, the raw PA signals are de-convolved with a system dependent deconvolution kernel, which is measured in advance. EMD is subsequently adopted to further process the PA signals adaptively with two restrictive conditions: positive polarity and spectrum consistency. With this method, signal aliasing is alleviated, and the micro-structures and detail information, previously buried in the reconstructing images, can now be revealed. To validate our proposed method, numerical simulations and phantom studies are implemented, and reconstructed images are used for illustration.

scholarly journals Evaluation and Treatment Analysis of Air Quality Including Particulate Pollutants: A Case Study of Shandong Province, China

2020 ◽  
Vol 17 (24) ◽  
pp. 9476
Author(s):  
Bowen Jiang ◽  
Yuangang Li ◽  
Weixin Yang
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Pollution Control ◽  
Forecast Model ◽  
Maximum Error ◽  
Shandong Province ◽  
Air Pollution Control ◽  
Control Policies ◽  
Pm2.5 And Pm10

At present, China’s air pollution and its treatment effect are issues of general concern in the academic circles. Based on the analysis of the development stages of air pollution in China and the development history of China’s air quality standards, we selected 17 cities of Shandong Province, China as the research objects. By expanding China’s existing Air Quality Index System, the air quality of six major pollutants including PM2.5 and PM10 in 17 cities from February 2017 to January 2020 is comprehensively evaluated. Then, with a forecast model, the air quality of the above cities in the absence of air pollution control policies since June 2018 was simulated. The results of the error test show that the model has a maximum error of 4.67% when simulating monthly assessment scores, and the maximum mean error of the four months is 3.17%. Through the comparison between the simulation results and the real evaluation results of air quality, we found that since June 2018, the air pollution control policies of six cities have achieved more than 10% improvement, while the air quality of the other 11 cities declined. The different characteristics of pollutants and the implementation of governance policies are perhaps the main reasons for the above differences. Finally, policy recommendations for the future air pollution control in Shandong and China were provided.

Radar Echo Parameter Estimation Using Sparse Time-Frequency Analysis Method

2014 ◽  
Vol 543-547 ◽  
pp. 2229-2233
Author(s):  
Hao Chen ◽  
Jun Hai Guo
Keyword(s):  
Parameter Estimation ◽  
Frequency Analysis ◽  
Computational Cost ◽  
Velocity Estimation ◽  
Analysis Method ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Mode Decomposition ◽  
Empirical Wavelet Transform ◽  
Adaptive Data Analysis

The echoes of pulse radar from maneuvering targets are amplitude modulation and frequency modulation (AM-FM) signal. At present, the methods of estimating parameters of AM-FM signal are time-frequency analysis method, empirical mode decomposition and empirical wavelet transform based adaptive data analysis methods. This paper takes the idea of intrinsic mode function in guessing the initial phase, and applies the newly developed sparse time-frequency analysis method in AM-FM signal parameter estimation. Simulation results show that the estimating performance of this method in AM-FM signal is good under different SNR and it has low computational cost, and this method is applicable in target acceleration and velocity estimation.

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