Iron Filings as PRB Media Binary Regression Analysis of Remediation of Chromium-Contaminated Groundwater

2013 ◽  
Vol 838-841 ◽  
pp. 2673-2676
Author(s):  
Zhi Yong Han ◽  
Wang Bing Du ◽  
Xiao Bin Wei ◽  
Li Li Ma ◽  
Bo Qu ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Flow Velocity ◽  
Removal Rate ◽  
Initial Concentration ◽  
Data Regression ◽  
Binary Regression Analysis ◽  
Iron Filing ◽  
Change Trend ◽  
The One

Regarding the iron filing as PRB padding media, this experiment researched the repair effect of iron filing to the groundwater polluted by Cr+6on condition that different initial concentration of Cr6+and different flow velocity, and then with the help of the data regression analysis software SPSS1stOptExcel etc, it studied the regression analysis of Cr6+removal rate with binary linear and binary nonlinear of the initial concentration and the flow velocity. The results indicated that: the change process of Cr6+removal rate with initial concentration and flow velocity can adopt regression model analysis of binary linear and binary nonlinear, and in this test, the decision coefficient of the regression model of binary linear (0.825) was smaller than the decision coefficient R2of binary nonlinear (0.955), which illustrated, comparing with the regression model of binary linear, the one of binary nonlinear z=(p1+p3*x+p5*Ln (y)+p7*x^2+p9*(Ln (y))^2+p11*x *Ln (y))/(1+p2*x+p4*Ln (y)+p6*x^2+p8*(Ln (y))^2+p10*x*Ln (y)) can simulate the change trend of Cr6+removal rate with initial concentration and flow velocity better.

Iron Filings as PRB Media Regression Analysis of Remediation of Chromium-Contaminated Groundwater

2013 ◽  
Vol 864-867 ◽  
pp. 1178-1182
Author(s):  
Zhi Yong Han ◽  
Xiao Bin Wei ◽  
Wang Bing Du
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Flow Velocity ◽  
Removal Rate ◽  
Contaminated Groundwater ◽  
Analysis Software ◽  
Initial Concentration ◽  
Data Regression ◽  
Cubic Polynomial ◽  
Iron Filing

Regarding the iron filing as PRB padding media, this experiment researched the repair effect of iron filing to the groundwater polluted by Cr on condition that different initial concentration of Cr6+ and different flow velocity, and then with the help of the data regression analysis software SPSS、1stOpt、Excel etc, it studied the regression analysis of Cr6+ removal rate with the change of initial concentration and the flow velocity. The results indicated that: under the certain flow velocity, cubic polynomial is the best regression model of Cr6+ removal rate with the change of initial concentration;under the certain initial Cr6+ concentration, the change of Cr6+ removal rate with flow velocity can be fitted in the regression model of unitary linear well, and the decision coefficient R2of it can be up to above 0.9.

A Review of Regression Models in Machine Learning

2021 ◽  
Vol 2 (2) ◽  
pp. 40-47
Author(s):  
Sunil Kumar ◽  
Vaibhav Bhatnagar
Keyword(s):  
Machine Learning ◽  
Regression Analysis ◽  
Regression Model ◽  
Regression Models ◽  
Machine Learning Algorithms ◽  
Data Sets ◽  
Analysis Model ◽  
Data Set ◽  
Data Regression ◽  
Different Types

Machine learning is one of the active fields and technologies to realize artificial intelligence (AI). The complexity of machine learning algorithms creates problems to predict the best algorithm. There are many complex algorithms in machine learning (ML) to determine the appropriate method for finding regression trends, thereby establishing the correlation association in the middle of variables is very difficult, we are going to review different types of regressions used in Machine Learning. There are mainly six types of regression model Linear, Logistic, Polynomial, Ridge, Bayesian Linear and Lasso. This paper overview the above-mentioned regression model and will try to find the comparison and suitability for Machine Learning. A data analysis prerequisite to launch an association amongst the innumerable considerations in a data set, association is essential for forecast and exploration of data. Regression Analysis is such a procedure to establish association among the datasets. The effort on this paper predominantly emphases on the diverse regression analysis model, how they binning to custom in context of different data sets in machine learning. Selection the accurate model for exploration is the most challenging assignment and hence, these models considered thoroughly in this study. In machine learning by these models in the perfect way and thru accurate data set, data exploration and forecast can provide the maximum exact outcomes.

scholarly journals Faktor-Faktor Yang Mempengaruhi Initial Return 1 Hari, Return 1 bulan, dan Pengaruh Terhadap Return 1 Tahun Setelah IPO

2008 ◽  
Vol 1 (1) ◽  
pp. 116-140
Author(s):  
Emilia Emilia ◽  
Lucky Sulaiman ◽  
Roy Sembel
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Multiple Regression Analysis ◽  
Stock Exchange ◽  
Secondary Market ◽  
Exchange Market ◽  
Earnings Per Share ◽  
Initial Return ◽  
One Year ◽  
The One

There are some anomalies happenning when the shares are traded in the secondary market or stock exchange. When the shares price at the secondary market is higher than the primary market, then we say that there is a positive initial return or underpricing happened. The opposite is negative initial return or overpricing. The purpose of this research is to to study whether the underwriter’s reputation, auditor’s reputation, value of the share offering, percentage of the share offering, and earnings per share towards the IPO price influence the one day initial return, one month return, and one year return after the IPO. The objects of the research are 92 companies that went public through the Jakarta stock exchange market during 1999-2005 that had either positive or negative initial return. This research is done using multiple regression analysis with F Test, t Test, R2 Test, and classic assumption testing. The result indicates that only the value of the share offering variable that significantly influence the one day initial return and one month initial return negatively. For the one year return regression model, only the one month return that significantly influence the return one year after the IPO positively. It can be concluded that the higher the value of the share offering the smaller the one day initial return and one month initial return will be, and thus minimizing the positive initial return. Furthermore, the higher the one month initial return the higher also the one year return after the IPO.

scholarly journals PENGARUH UPAH MINIMUM REGIONAL DAN RASIO INFRASTRUKTUR TERHADAPKESENJANGAN DISTRIBUSI PENDAPATAN DI INDONESIA

2020 ◽  
Vol 1 (2) ◽  
pp. 116-135
Author(s):  
Siti Nurul Noviana
Keyword(s):  
Regression Analysis ◽  
Minimum Wage ◽  
Gini Index ◽  
The Other ◽  
Data Regression ◽  
Independent Variable ◽  
The One ◽  
The Individual ◽  
The Impact ◽  
Distribution Of Income

This study aims to examine the impact of region minimum wage and infrastructure ratio onIncomeDistribution Gap in Indonesia. This study uses panel data for the period 2011-2017 and consists of 33provinces, except North Kalimantan Province because it is a new province. By using fixed effectpanel data regression analysis, with dependent variable is gini index. While independent variable areregional minimum wage and infrastructure ratio.On the one hand, based on hypothetical test, theresults show that the regional minimum wage and infrastructure ratio have a negative and significanteffect on the income distribution gap in Indonesia. On the other hand, based on the individual effectstest, the large islands such as Sumatera, Java, Kalimantan, Sulawesi, Bali, Maluku, and Papua have apositive effect on the gini ratio. This shows that there is an impact of the infrastructure ratio functionand regional minimum wages in increasing the distribution of income as measured by the gini index.

Determinants Of Capital Structure For Multinational And Domestic Companies In India: Panel Data Regression Model

2019 ◽  
Vol 118 (7) ◽  
pp. 147-154
Author(s):  
K. Maheswari ◽  
Dr. J. Gayathri ◽  
Dr. M. Babu ◽  
Dr.G. Indhumathi
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Regression Model ◽  
Business Risk ◽  
Return On Assets ◽  
Panel Data Regression ◽  
Data Regression ◽  
Return On Capital ◽  
Domestic Companies ◽  
The Capital Structure

The capital structure refers to the components of capital needed to establish and expand its business activities. The study was made with an objective to examine the determinants of capital structure of multinational and domestic companies listed in S&P BSE automobile sector. The study concluded that there is significant impact on capital structure determinants such as size, business risk, non debt shield tax, return on assets, tangibility, profit, return on capital employed and liquidity on the capital structure of multinational and domestic companies of Indian Automobile Sector.  

Relations between carbon removal rates, biofilm size and density of a novel anaerobic reactor: the inverse turbulent bed

2000 ◽  
Vol 41 (4-5) ◽  
pp. 253-260 ◽  
Author(s):  
P. Buffière ◽  
R. Moletta
Keyword(s):  
Removal Rate ◽  
Removal Rates ◽  
Carbon Removal ◽  
Biofilm Growth ◽  
Loading Rates ◽  
Biomass Activity ◽  
High Turbulence ◽  
The One ◽  
High Level ◽  
Very High

An anaerobic inverse turbulent bed, in which the biogas only ensures fluidisation of floating carrier particles, was investigated for carbon removal kinetics and for biofilm growth and detachment. The range of operation of the reactor was kept within 5 and 30 kgCOD· m−3· d−1, with Hydraulic Retention Times between 0.28 and 1 day. The carbon removal efficiency remained between 70 and 85%. Biofilm size were rather low (between 5 and 30 μm) while biofilm density reached very high values (over 80 kgVS· m−3). The biofilm size and density varied with increasing carbon removal rates with opposite trends; as biofilm size increases, its density decreases. On the one hand, biomass activity within the reactor was kept at a high level, (between 0.23 and 0.75 kgTOC· kgVS· d−1, i.e. between 0.6 and 1.85 kgCOD·kgVS · d−1).This result indicates that high turbulence and shear may favour growth of thin, dense and active biofilms. It is thus an interesting tool for biomass control. On the other hand, volatile solid detachment increases quasi linearly with carbon removal rate and the total amount of solid in the reactor levels off at high OLR. This means that detachment could be a limit of the process at higher organic loading rates.

scholarly journals Effect of permanent magnetic field on scale inhibition property of circulating water

2017 ◽  
Vol 76 (8) ◽  
pp. 1981-1991 ◽  
Author(s):  
Lili Jiang ◽  
Xiayan Yao ◽  
Haitao Yu ◽  
Xingang Hou ◽  
Zongshu Zou ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Hydrogen Bonds ◽  
Flow Velocity ◽  
Magnetic Field Intensity ◽  
Water Molecules ◽  
Relative Variation ◽  
Initial Concentration ◽  
Circulating Water ◽  
Scale Inhibition ◽  
Inhibition Property

Effect of a permanent magnet field on the scale inhibition property of circulating water was investigated. Orthogonal experiments of L16(45) were performed and analyzed using the range analysis method. The operating parameters included magnetic field intensity, initial concentration of Ca2+ and Mg2+, magnetic treatment time, temperature, and flow velocity. Scale inhibition rate, hardness, relative variation in the proportion of free water molecules, electrical conductivity, and relative variation of molecular energy were chosen as the objectives. In addition, the morphology and the composition of CaCO3 and MgCO3 scale were studied by X-ray diffraction analysis. The optimal conditions were initial concentration of 900 mg/L, magnetic field intensity of 0.5 T, temperature of 303 K, time of 54 h and flow velocity of 0.17 m/s. The nuclear magnetic resonance results demonstrated that the number of hydrogen bonds increased between water molecules and hydrated ions. The magnetic field can promote the increase in the number of hydrogen bonds, which can inhibit the formation of calcium and magnesium carbonate precipitation. Moreover, the ratio of calcite, aragonite and vaterite will be changed at different magnetic field intensities, and the aragonite ratio will reach the peak at the optimum conditions.

Granular biomass capable of partial nitritation and anammox

2008 ◽  
Vol 58 (5) ◽  
pp. 1113-1120 ◽  
Author(s):  
S. E. Vlaeminck ◽  
L. F. F. Cloetens ◽  
M. Carballa ◽  
N. Boon ◽  
W. Verstraete
Keyword(s):  
Removal Rate ◽  
Batch Reactor ◽  
Ammonium Oxidation ◽  
Autotrophic Nitrification ◽  
Partial Nitritation ◽  
One Stage ◽  
Biomass Retention ◽  
Granular Biomass ◽  
The One

A novel and efficient way of removing nitrogen from wastewater poor in biodegradable organic carbon, is the combination of partial nitritation and anoxic ammonium oxidation (anammox), as in the one-stage oxygen-limited autotrophic nitrification/denitrification (OLAND) process. Since anoxic ammonium-oxidizing bacteria grow very slowly, maximum biomass retention in the reactor is required. In this study, a lab-scale sequencing batch reactor (SBR) was used to develop granular, rapidly settling biomass. With SBR cycles of one hour and a minimum biomass settling velocity of 0.7 m/h, OLAND granules were formed in 1.5 months and the nitrogen removal rate increased from 50 to 450 mg N L−1 d−1 in 2 months. The granules had a mean diameter of 1.8 mm and their aerobic and anoxic ammonium-oxidizing activities were well equilibrated to perform the OLAND reaction. Fluorescent in-situ hybridization (FISH) demonstrated the presence of both β-proteobacterial aerobic ammonium oxidizers and planctomycetes (among which anoxic ammonium oxidizers) in the granules. The presented results show the applicability of rapidly settling granular biomass for one-stage partial nitritation and anammox.

scholarly journals The double-edged sword of corporatisation in the hospital sector: evidence from Indonesia

2016 ◽  
Vol 12 (1) ◽  
pp. 61-80 ◽  
Author(s):  
Asri Maharani ◽  
Gindo Tampubolon
Keyword(s):  
Regression Analysis ◽  
Panel Data ◽  
Financial Performance ◽  
System Performance ◽  
Hospital Performance ◽  
Public Hospitals ◽  
Health System Performance ◽  
The Past ◽  
Panel Data Regression ◽  
Data Regression

AbstractHoping to improve their health system performance, many countries have corporatised their hospitals in the past 20 years. What this means for hospital performance remains as yet largely unknown. This study looks into the association of corporatisation and hospital performance in Indonesia. We apply panel data regression analysis to survey data on 54 public hospitals in East Java province. Our analysis suggests that corporatisation is associated with higher hospital income and expenditure, but fails to improve efficiency and equity. These findings suggest that hospital corporatisation policy in Indonesia should increase emphasis on efficiency and equity rather than on financial performance alone.

Rainfall data regression model using fuzzy set logic

2016 ◽  
pp. 1060-1064
Author(s):  
Christos Tzimopoulos ◽  
Chris Evangelides ◽  
Basilios Papadopoulos
Keyword(s):  
Regression Model ◽  
Fuzzy Set ◽  
Rainfall Data ◽  
Data Regression
Sign in / Sign up

Export Citation Format

Share Document