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Millimeter-Wave Multilayer Common-Mode Filter With Robustness Enhancement Analysis Based on multiple linear regression equation

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IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 2025年

作者： Weng, Yijun Feng, Wenjie Shi, Yongrong Shen, Guangxu Cao, Yunfei Wu, Lin-Sheng Che, Wenquan Xue, Quan South China Univ Technol Sch Microelect Guangdong Prov Key Lab Millimeter Wave & Terahertz Guangdong Hong Kong Macao Joint Lab Millimeter Wav Hong Kong 510641 Guangdong Peoples R China Nanjing Univ Aeronaut & Astronaut Key Lab Dynam Cognit Syst Electromagnet Spectrum S Nanjing 211106 Peoples R China Nanjing Univ Posts & Telecommun Coll Elect & Opt Engn Nanjing 210023 Peoples R China Shanghai Jiao Tong Univ Key Lab High Speed Elect Syst Minist Educ Shanghai 200240 Peoples R China

Based on the proposed millimeter-wave multilayer common-mode filter (CMF) design, this article further presents an innovative parameter analysis method using multiple linear regression equations. Through importing data from parametric sweep into the statistical product and service solution (SPSS) software, the derived equations can be obtained by the significance level and regression coefficients. The proposed method provides applications as: 1) the S-parameters at needed frequency can be estimated when the processing capability is given;2) the derived equations can qualify and quantify the influence of each parameter on the performance;and 3) the specific guidance of parameter tuning can be obtained to enhance the robustness of the CMF. The estimated intervals include the measured intervals proving the validity of the proposed analysis method. For the proposed CMF, the 7.6-GHz bandwidth is realized and the 3-dB differential-mode (DM) cutoff frequency is higher than 40 GHz.

关键词： Mathematical models Microwave filters Nonhomogeneous media linear regression Filtering theory Scattering parameters Robustness Optical filters Millimeter wave technology Noise Common-mode filter (CMF) defected ground structure (DGS) electromagnetic shielding effects millimeter-wave multiple linear regression equation robustness

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Research and application of constructing football training linear programming based on multiple linear regression equation

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APPLIED MATHEMATICS AND NONlinear SCIENCES 2022年第1期7卷 143-154页

作者： Bai, YinZhuang Ren, Aizhen Khadidos, Adil Omar Abdulrazzqa, Mohammed Inner Mongolia Normal Univ Coll Phys Educ Hohhot 010020 Peoples R China Inner Mongolia Agr Univ Coll Sci Hohhot 010018 Peoples R China King Abdulaziz Univ Fac Comp & Informat Technol Dept Informat Technol Jeddah Saudi Arabia Appl Sci Univ Fac Adm Sci Dept Business Adm Al Eker Bahrain

Based on the factors affecting sports performance, from a more comprehensive and broad perspective, after consulting the literature, 52 factors that affect the outcome of football matches are selected, including technology, tactics, physical fitness and referees' penalties. By watching the video of the game, 52 influencing factors of 200 games and 400 teams were counted. The original data was statistically processed with correlation analysis and multiple linear regression analysis, and the statistics of the 26 European Cup games were substituted into the winning formula. To verify the scientific nature and objectivity of the formula, we aim to ascertain the core factors in the winning factors of a football game and the quantitative relationship between these factors and the result of the game, so as to provide a certain reference for football training, game analysis and scientific research. The technical and tactical ability of individuals and teams is the core competitive ability factor that affects the result of the game;from a single factor, 15 factor indicators have a significant impact on the result of a football match;on the whole, 10 factor indicators have a significant effect on the result of a football match. In addition, there is a certain quantitative relationship between these influencing factors and the results of the game;empirical evidence shows that the football game winning formula has a certain degree of science and objectivity.

关键词： football match winning factors winning formula multiple linear regression equation

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Travel Plan Design Based on Graph Theory and multiple linear regression equation Model

Travel Plan Design Based on Graph Theory and Multiple Linear...

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2016 3rd International Conference on Materials Engineering,Manufacturing Technology and Control(ICMEMTC 2016)

作者： Yifeng Dou Hailing Xiong College of Computer and Information Science Southwest University

Different families have different needs for tours. In order to solve the problem, this paper firstly creates a table which takes all determining varieties into consideration. By adopting principal component for analyzing and filtrating the main factors, the conclusion is as follow: the first principal component is time and the second one is cost;their factor contribution rate is respectively 58.95% and 38.93%. Moreover, the two weighted principal components can make the analysis process easier and reduce error rate. Secondly, in order to provide the best tour plan for different families, this paper selects eight tourist attractions in Xi'an and establishes the goal programming model which covers some factors, such as tour routes, costs and time. Finally, a multivariate linear regression equation is applied to test traveling plans and determine the best one.

关键词： Travel Plan Design Graph Theory Principal Component Analysis Goal Programming multiple linear regression equation

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Development of a Heart Rate Variability Prediction equation Through multiple linear regression Analysis Using Physical Characteristics and Heart Rate Variables

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INQUIRY-THE JOURNAL OF HEALTH CARE ORGANIZATION PROVISION AND FINANCING 2023年 60卷 469580231169416页

作者： Kim, Sung-Woo Park, Hun-Young Jung, Hoeryong Park, Sin-Ae Lim, Kiwon Konkuk Univ Phys Act & Performance Inst Seoul South Korea Konkuk Univ Grad Sch Dept Sports Med & Sci Seoul South Korea Konkuk Univ Dept Mech Engn Seoul South Korea Konkuk Univ Konkuk Inst Technol Dept Syst Biotechnol Seoul South Korea Konkuk Univ Dept Phys Educ Seoul South Korea Konkuk Univ Dept Phys Educ 120 Neungdong Ro Seoul 05029 South Korea

Heart rate variability (HRV) is an effective tool for objectively evaluating physiological stress indices in psychological states. This study aimed to develop multiple linear regression equations to predict HRV variables using physical characteristics, body composition, and heart rate (HR) variables (eg, sex, age, height, weight, body mass index, fat-free mass, percent body fat, resting HR, maximal HR, and HR reserve) in Korean adults. Six hundred eighty adults (male, n = 236, female, n = 444) participated in this study. HRV variable estimation multiple linear regression equations were developed using a stepwise technique. The regression equation's coefficient of determination for time-domain variables was significantly high (SDNN = adjusted R-2: 73.6%, P < .001;RMSSD = adjusted R-2: 84.0%, P < .001;NN50 = adjusted R-2: 98.0%, P < .001;pNN50 = adjusted R-2: 99.5%, P < .001). The coefficient of determination of the regression equation for the frequency-domain variables was high without VLF (TP = adjusted R-2: 75.0%, P < .001;LF = adjusted R-2: 77.6%, P < .001;VLF = adjusted R-2: 30.1%, P < .001;HF = adjusted R-2: 71.3%, P < .001). Healthcare professionals, researchers, and the general public can quickly evaluate their psychological conditions using the HRV variables prediction equation.

关键词： multiple linear regression equation mental health heart rate variability time-domain variables frequency-domain variables

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SOME SIMPLE multiple linear-regression equationS FOR ESTIMATION OF MAXIMAL AEROBIC POWER IN HEALTHY INDIAN MALES

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EUROPEAN JOURNAL OF APPLIED PHYSIOLOGY 1984年第3期52卷 336-339页

作者： VERMA, SS GUPTA, RK SENGUPTA, J DEF INST PHYSIOL & ALLIED SCI DELHI CANTT 110010 INDIA

An attempt was made to evolve some simple multiple linear regression equations for the prediction of .***2 max max [maximum O2 consumption] from body weight, time for 3.2 km run and exercise dyspnoeic index (DIstd Ex%). The predictor variables were selected by examining the product moment correlations of body weight, relative body weight indices, time for 3.2 km run, chest expansion, height and DIstd Ex% with .***2 max, based on data collected on 320 healthy Indian males (17-22 yr). It was observed that body weight, time for 3.2 km run and DIstd Ex% attained maximum correlations with .***2 max. Two regression equations with 2 and 3 predictor variables were established to predict .***2 max. The 1st yielded a multiple correlation of 0.608 (P < 0.001 SE 0.214 1 .cntdot. min-1]. In this equation, body weight and time for 3.2 km run were considered as significant predictors. To increase the precision of this equation, another multiple linear regression equation based on body weight, time for 3.2 km run and DIstd Ex% as predictors was developed. This equation yielded a multiple correlation of 0.658 (P < 0.001, SE 0.204 l .cntdot. min-1]. Applications of these regression equations will be of practical importance to biomedical scientists engaged in the development of a simple procedure for indirect assessment of .***2 max, and may serve well as preliminary screening procedures for personnel selection.

关键词： multiple linear regression equation Maximal aerobic power Analysis of variance multiple correlation Product moment correlation

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Influences of rainfall variables and antecedent discharge on urban effluent concentrations and loads in wet weather

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WATER SCIENCE AND TECHNOLOGY 2017年第7期75卷 1584-1598页

作者： Xu, Zuxin Xiong, Lijun Li, Huaizheng Liao, Zhengliang Yin, Hailong Wu, Jun Xu, Jin Chen, Hao Tongji Univ Key Lab Yangtze River Water Environm Minist Educ Shanghai 200092 Peoples R China

For storm drainages inappropriately connected with sewage, wet weather discharge is a major factor that adversely affects receiving waters. A study of the wet weather influences of rainfall-discharge variables on storm drainages connected with sewage was conducted in the downtown Shanghai area (374 ha). Two indicators, event mean concentration (EMC) and event pollutant load per unit area (EPL), were used to describe the pollution discharge during 20 rain events. The study showed that the total rainfall and discharge volume were important factors that affect the EMCs and EPLs of the chemical oxygen demand, total phosphorus, and especially those of NH4(+)-N. The pollutant concentrations at the beginning of the discharge and the discharge period were also major factors that influence the EMCs of these three pollutants. regression relationships between the rainfall-discharge variables and discharge volume/EPLs (R-2 = 0.824-0.981) were stronger than the relationships between the rainfall-discharge variables and EMCs. These regression equations can be considered reliable in the system, with a relative validation error of less than +/- 10% for the discharge volume, and less than +/- 20% for the EPLs. The results presented in this paper provide guidance for effectively controlling pollution in similar storm drainages.

关键词： correlation coefficients event mean concentration (EMC) event pollution load per unit area (EPL) multiple linear regression equation urban wet weather discharge (UWWD)

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The correlation and prediction of infinite dilution activity coefficients of compounds in water at 298.15 K

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FLUID PHASE EQUILIBRIA 2017年 449卷 117-129页

作者： Abraham, Michael H. Acree, William E., Jr. Zissimos, Andreas M. UCL Dept Chem 20 Gordon St London WC1H 0AJ England Univ North Texas Dept Chem POB 305070 Denton TX 76203 USA Minist Agr Rural Dev & Environm Geol Survey Dept Cyprus Lefkonos 1 CY-1415 Nicosia Cyprus

We have assembled infinite dilution activity coefficients in water at 298 K for 661 varied compounds. For 655 of these compounds we were able to construct a multiple linear regression equation using Abraham descriptors with a standard deviation of 0.29 log units in log gamma infinity. Unlike methods such as ASOG or UNIFAC, our equation does not rely on functional groups, and so we can predict further values of activity coefficients for compounds with functional groups not included in the 655 data base. These include ferrocene, terpenes such as alpha-pinene, and compounds containing phosphorous atoms such as trimethylphosphate and dibutylphosphinic acid. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Activity coefficient Solubility Abraham descriptors multiple linear regression equation

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The correlation and prediction of the temperature variation of infinite dilution activity coefficients of compounds in water

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FLUID PHASE EQUILIBRIA 2018年 455卷 1-5页

作者： Abraham, Michael H. Acree, William E., Jr. UCL Dept Chem 20 Gordon St London WC1H 0AJ England Univ North Texas Dept Chem POB 305070 Denton TX 76203 USA

We list infinite dilution activity coefficients, gamma infinity, in water for 81 compounds from 273.15 to 373.15 K, and we use our linear free energy relationship to obtain equations for log gamma infinity at 5 K intervals between 273.15 and 373.15 K. These equations, together with Abraham descriptors can then be used to calculate or predict the temperature variation of activity coefficient in water with an estimated error of 0.25-0.30 log unit. If an experimental value of log gamma infinity is available at 298.15 K (or at any specific temperature) this can be used as a reference point to adjust our calculated values at any other temperature, leading to an estimated error for the temperature variation of around 0.1 log units. This procedure is especially useful in extrapolating limited data on log gamma infinity over the entire range 273.15-373.15 K. The method requires no complicated software and calculations involve no more than simple arithmetic. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Activity coefficient Temperature variation of activity coefficients Abraham descriptors multiple linear regression equation linear free energy relationship

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Establishment of predicting equation for individual sufentanil dosage postoperatively based on gene polymorphisms (vol 22, pg 39, 2022)

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PAIN PRACTICE 2022年第3期22卷 416-416页

作者： Cheng, H. Zeng, R. Kong, L. Ding, C. He, Y. Zhuang, W. Sun, Yancai Univ Sci & Technol China Dept Pharm Affiliated Hosp USTC 1 Div Life Sci & Med Hefei 230031 Anhui Peoples R China Univ Sci & Technol China Dept Anesthesiol Affiliated Hosp USTC 1 Div Life Sci & Med Hefei Anhui Peoples R China Univ Sci & Technol China Dept Med Oncol Affiliated Hosp USTC 1 Div Life Sci & Med Hefei Anhui Peoples R China

Background Postoperative analgesia is widely used for patients undergoing major surgeries. Individual differences in genetic polymorphisms may be obstructive factors for accurately anesthetics using. However, the equation for predicting sufentanil dosage postoperatively based on genetic design has been established yet. Our aim was to establish sufentanil dosage postoperatively prediction equation based on patients’ genetic polymorphisms. Methods One hundred forty patients with total gastrectomy and radical resection of pulmonary carcinoma were included. To establish sufentanil dosage postoperatively for patients with gastric cancer, we collected patients’ basic information and CYP3A4*1G, COMTVal158Met, OPRM1A118G, and ABCB1C3435T gene sequencing results. To verify this equation, we put patients’ with lung cancer surgeries information into it. Results The sufentanil dosage prediction equation postoperatively was y = 4.104 − 0.222 × (gender) + 0.021 × (OPRM1A118G) + 0.249 × (ABCB1C3435T). Patients’ with lung cancer surgeries information were substituted into it. The results showed no significant differences between predicted and actual sufentanil dosage (p > 0.05). Conclusion We established the prediction equation for individual sufentanil dosage postoperatively based on gene polymorphisms. The results showed this prediction equation was valid, which might be used for different types of surgeries. We established an equation for individual dosage of sufentanil for postoperative analgesia based on gene polymorphisms. The results show that the prediction equation is valid, the information might be used for different types of postoperative analgesia, and the painful patients will have great potential safe and personalized pain control after analgesic therapy. It might also have potential as a clinical tool.

关键词： gene polymorphisms individual dosage multiple linear regression equation sufentanil

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NDVI prediction over Mongolian grassland using GSMaP precipitation data and JRA-25/JCDAS temperature data

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JOURNAL OF ARID ENVIRONMENTS 2009年第4-5期73卷 557-562页

作者： Iwasaki, H. Gunma Univ Fac Educ Gunma 3718510 Japan

An algorithm to predict the NDVI (Normalized Difference Vegetation Index) distribution over Mongolia, which is based on a stepwise multiple linear regression analysis, has been developed using global precipitation data obtained from satellites and global surface air temperature data obtained from the reanalysis data during the period 1998-2005. This algorithm can predict the NDVI value upto 1-3 months in advance for a grid with a spatial resolution of 0.25 degrees x 0.25 degrees. In order to validate the algorithm, the NDVI distribution was predicted for the period from May to November 2006 using 1 to 3-month prediction algorithms. The distributions of the predicted normalized anomalies agreed well with those of the observed normalized anomalies. It was found that these algorithms were effective for and and semi-arid regions, despite its low accuracy for August and regions with high vegetation activity. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： multiple linear regression equation Plant litter Reanalysis data Semi-arid region Steppe

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