scholarly journals MODELLING THE CARBON STOCKS ESTIMATION OF THE TROPICAL LOWLAND DIPTEROCARP FOREST USING LIDAR AND REMOTELY SENSED DATA

2016 ◽  
Vol III-7 ◽  
pp. 187-194 ◽  
Author(s):  
N. A. M. Zaki ◽  
Z. A. Latif ◽  
M. N. Suratman ◽  
M. Z. Zainal
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Correlation Coefficient ◽  
Remotely Sensed ◽  
Carbon Stocks ◽  
Projection Area ◽  
Linear Regression Method ◽  
Remotely Sensed Data ◽  
Tropical Lowland ◽  
Crown Projection Area

Tropical forest embraces a large stock of carbon in the global carbon cycle and contributes to the enormous amount of above and below ground biomass. The carbon kept in the aboveground living biomass of trees is typically the largest pool and the most directly impacted by the anthropogenic factor such as deforestation and forest degradation. However, fewer studies had been proposed to model the carbon for tropical rain forest and the quantification still remain uncertainties. A multiple linear regression (MLR) is one of the methods to define the relationship between the field inventory measurements and the statistical extracted from the remotely sensed data which is LiDAR and WorldView-3 imagery (WV-3). This paper highlight the model development from fusion of multispectral WV-3 with the LIDAR metrics to model the carbon estimation of the tropical lowland <i>Dipterocarp</i> forest of the study area. The result shown the over segmentation and under segmentation value for this output is 0.19 and 0.11 respectively, thus D-value for the classification is 0.19 which is 81%. Overall, this study produce a significant correlation coefficient (r) between Crown projection area (CPA) and Carbon stocks (CS); height from LiDAR (H_LDR) and Carbon stocks (CS); and Crown projection area (CPA) and height from LiDAR (H_LDR) were shown 0.671, 0.709 and 0.549 respectively. The CPA of the segmentation found to be representative spatially with higher correlation of relationship between diameter at the breast height (DBH) and carbon stocks which is Pearson Correlation p = 0.000 (p < 0.01) with correlation coefficient (r) is 0.909 which shown that there a good relationship between carbon and DBH predictors to improve the inventory estimates of carbon using multiple linear regression method. The study concluded that the integration of WV-3 imagery with the CHM raster based LiDAR were useful in order to quantify the AGB and carbon stocks for a larger sample area of the Lowland <i>Dipterocarp</i> forest.

scholarly journals MODELLING THE CARBON STOCKS ESTIMATION OF THE TROPICAL LOWLAND DIPTEROCARP FOREST USING LIDAR AND REMOTELY SENSED DATA

2016 ◽  
Vol III-7 ◽  
pp. 187-194 ◽  
Author(s):  
N. A. M. Zaki ◽  
Z. A. Latif ◽  
M. N. Suratman ◽  
M. Z. Zainal
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Correlation Coefficient ◽  
Remotely Sensed ◽  
Carbon Stocks ◽  
Projection Area ◽  
Linear Regression Method ◽  
Remotely Sensed Data ◽  
Tropical Lowland ◽  
Crown Projection Area

Tropical forest embraces a large stock of carbon in the global carbon cycle and contributes to the enormous amount of above and below ground biomass. The carbon kept in the aboveground living biomass of trees is typically the largest pool and the most directly impacted by the anthropogenic factor such as deforestation and forest degradation. However, fewer studies had been proposed to model the carbon for tropical rain forest and the quantification still remain uncertainties. A multiple linear regression (MLR) is one of the methods to define the relationship between the field inventory measurements and the statistical extracted from the remotely sensed data which is LiDAR and WorldView-3 imagery (WV-3). This paper highlight the model development from fusion of multispectral WV-3 with the LIDAR metrics to model the carbon estimation of the tropical lowland &lt;i&gt;Dipterocarp&lt;/i&gt; forest of the study area. The result shown the over segmentation and under segmentation value for this output is 0.19 and 0.11 respectively, thus D-value for the classification is 0.19 which is 81%. Overall, this study produce a significant correlation coefficient (r) between Crown projection area (CPA) and Carbon stocks (CS); height from LiDAR (H_LDR) and Carbon stocks (CS); and Crown projection area (CPA) and height from LiDAR (H_LDR) were shown 0.671, 0.709 and 0.549 respectively. The CPA of the segmentation found to be representative spatially with higher correlation of relationship between diameter at the breast height (DBH) and carbon stocks which is Pearson Correlation p = 0.000 (p &lt; 0.01) with correlation coefficient (r) is 0.909 which shown that there a good relationship between carbon and DBH predictors to improve the inventory estimates of carbon using multiple linear regression method. The study concluded that the integration of WV-3 imagery with the CHM raster based LiDAR were useful in order to quantify the AGB and carbon stocks for a larger sample area of the Lowland &lt;i&gt;Dipterocarp&lt;/i&gt; forest.

PENGARUH SIMPANAN, PEMBIAYAAN DAN MODAL TERHADAP LABA PADA BTM WAHANA MENTARI KABUPATEN INDRAGIRI HULU

2018 ◽  
Vol 7 (4) ◽  
pp. 200-208
Author(s):  
Angga Hapsila
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Correlation Coefficient ◽  
Research Study ◽  
Secondary Data ◽  
Process Data ◽  
Strong Ties ◽  
Paper Work

The research was conducted by the writer on BTM Mentari in sub districts rengat - indragiri upstream. District. The research phase lasting three months. This research study is to find savings, influence financing and capital to profit in the district btm mentari Indragiri upstream. This research used secondary data , writer process data by using multiple linear regression the it using spss ( statistic package for social scince ) 24 version to get output to summarizing the research. The research that is simultaneously a conclusion can be drawn is the significant savings, between financing and capital to profit. This can be seen that the f count greater than the f table ( 29,873 > 2,36 ) When viewed from the table a model summary so r which means a correlation coefficient obtained value of 0,984 which means the amount of savings mobilized , the financing of the and capital had strong ties against spider does not permit the .Was in the middle of the value of the coefficients detrminasi as much as 0,968 paper work showing that the amount of savings mobilized , the financing of the and capital affect of the spider that has been accepted by the BTM the spacecraft mentari as much as 96,80 % the remaining of 3,20 % influenced by the fact that of other variables that do not writer you wherever you may be.

An application of QSRR approach and multiple linear regression method for lipophilicity assessment of flavonoids

2019 ◽  
Vol 164 ◽  
pp. 681-689 ◽  
Author(s):  
Mariusz Zapadka ◽  
Mateusz Kaczmarek ◽  
Bogumiła Kupcewicz ◽  
Przemysław Dekowski ◽  
Agata Walkowiak ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Method ◽  
Linear Regression Method ◽  
Multiple Linear Regression Method

scholarly journals Prevalence of asymptomatic hyperuricemia and its association with prediabetes, dyslipidemia and subclinical inflammation markers among young healthy adults in Qatar

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Yasemin Al Shanableh ◽  
Yehia Y. Hussein ◽  
Abdul Haseeb Saidwali ◽  
Maryam Al-Mohannadi ◽  
Budoor Aljalham ◽  
...  
Keyword(s):  
Young Adults ◽  
Uric Acid ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Correlation Coefficient ◽  
Uric Acid Level ◽  
Acid Level ◽  
Linear Regression Analysis ◽  
Subclinical Inflammation ◽  
Cross Sectional

Abstract Aim The aim of this study is to investigate the prevalence of asymptomatic hyperuricemia in Qatar and to examine its association with changes in markers of dyslipidemia, prediabetes and subclinical inflammation. Methods A cross-sectional study of young adult participants aged 18 - 40 years old devoid of comorbidities collected between 2012 and 2017. Exposure was defined as uric acid level, and outcomes were defined as levels of different blood markers. De-identified data were collected from Qatar Biobank. T-tests, correlation tests and multiple linear regression were all used to investigate the effects of hyperuricemia on blood markers. Statistical analyses were conducted using STATA 16. Results The prevalence of asymptomatic hyperuricemia is 21.2% among young adults in Qatar. Differences between hyperuricemic and normouricemic groups were observed using multiple linear regression analysis and found to be statistically and clinically significant after adjusting for age, gender, BMI, smoking and exercise. Significant associations were found between uric acid level and HDL-c p = 0.019 (correlation coefficient -0.07 (95% CI [-0.14, -0.01]); c-peptide p = 0.018 (correlation coefficient 0.38 (95% CI [0.06, 0.69]) and monocyte to HDL ratio (MHR) p = 0.026 (correlation coefficient 0.47 (95% CI [0.06, 0.89]). Conclusions Asymptomatic hyperuricemia is prevalent among young adults and associated with markers of prediabetes, dyslipidemia, and subclinical inflammation.

scholarly journals Accident Prediction Model at Unsignalized Intersection Using Multiple Linear Regression Method

2017 ◽  
Vol 1 (2) ◽  
pp. 379-389
Author(s):  
N. K. Oghoyafedo ◽  
J. O. Ehiorobo ◽  
Ebuka Nwankwo
Keyword(s):  
Linear Regression ◽  
Prediction Model ◽  
Multiple Linear Regression ◽  
Regression Method ◽  
Linear Regression Method ◽  
Design Standards ◽  
Accident Prediction ◽  
Geometric Characteristics ◽  
Unsignalized Intersections ◽  
Multiple Linear Regression Method

The issue of road accidents is an increasing problem in developing countries. This could be due to increasing road traffic/vehicle occupancy, geometric characteristics and road way condition. The factors influencing accidents occurrence are to be analysed for remedies. The purpose of this research is to develop an accident prediction model as a measure for future study, aid planning phase preceding the designed intervention, enhance the production of updated design standards to enable practitioners design unsignalized intersection for optimal safety, reduce the number of accidents at unsignalized intersections. Five intersections were selected randomly within Benin City and traffic count carried out at these intersections as well as geometric characteristics and roadway conditions. The prediction model was developed using multiple linear regression method and the standard error of estimate was computed to show how close the observed value is to the regression line. The model was validated using coefficient of multiple determination. The establishment of the relationship between accidents and traffic flow site characteristics on the other hand would enable improvement to be more realistically accessed. This study will also enhance the production of updated design standards to enable practitioners design unsignalized intersection for optimal safety, reduce the number of accidents at unsignalized intersections.

scholarly journals THE EFFECT OF LEADERSHIP, JOB SATISFACTION AND ORGANIZATIONAL COMMITMENT ON EMPLOYEE PERFORMANCE AT RUMAH SAKIT UMUM DAERAH BESUKI SITUBONDO, INDONESIA

2018 ◽  
Vol 6 (6) ◽  
pp. 322-334
Author(s):  
Amrozi ◽  
Zarah Puspitaningtyas ◽  
Djoko Poernomo
Keyword(s):  
Job Satisfaction ◽  
Organizational Commitment ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Random Sampling ◽  
Employee Performance ◽  
Sampling Technique ◽  
Regression Method ◽  
Linear Regression Method ◽  
Multiple Linear Regression Method

This study is to examine the influence of leadership, job satisfaction and organizational commitment on employee performance. Population in this research was the entire employees of Rumah Sakit Umum Daerah (RSUD) Besuki, Situbondo, Indonesia which was about 295 peoples. Then, the researcher applied probability random sampling technique to select 170 respondents as the sampling. The researcher analyzed the data by applying multiple linear regression method. The result shows that leadership and job satisfaction contribute positive and significant effect on employee performance, while organizational commitment has no effect on employee performance.

scholarly journals Pengaruh Disiplin Kerja dan Pemberian Insentif terhadap Kinerja Karyawan PT Putra Karisma Palembang

2021 ◽  
Vol 2 (1) ◽  
pp. 25-42
Author(s):  
Andini Dwi Saputri ◽  
Susi Handayani ◽  
Muhammad Kurniawan DP
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Employee Performance ◽  
Regression Method ◽  
Linear Regression Method ◽  
Multiple Linear Regression Method ◽  
Sample Technique ◽  
Saturated Sample ◽  
Analyze Data

This study aims to analyze the effects of work discipline and incentives on the performance of employees of PT Putra Karisma Palembang. The sample was selected using the saturated sample technique. Data from 57 respondents were collected through interviews, documentation, and questionnaires. This study implemented the multiple linear regression method to analyze data. The results prove that partially each of work discipline and incentives has no significant effect on employee performance. However, simultaneously work discipline and incentives have a significant effect on employee performance. This insight is beneficial for PT Putra Karisma Palembang. To improve employees' performance, the company should consider both work discipline and incentives factors together.   Penelitian ini bertujuan untuk menganalisis pengaruh disiplin kerja dan pemberian insentif terhadap kinerja karyawan PT Putra Karisma Palembang. Sampel dipilih menggunakan teknik sampel jenuh. Data 57 responden dikumpulkan melalui wawancara, dokumentasi, dan kuesioner. Studi ini mengimplementasikan metode regresi linier berganda untuk menganalisis data. Hasil investigasi membuktikan bahwa secara parsial baik disiplin kerja maupun pemberian insentif masing-masing tidak berpengaruh signifikan terhadap kinerja karyawan. Tetapi, secara simultan disiplin kerja dan pemberian insentif berpengaruh signifikan terhadap kinerja karyawan. Fakta ini bermanfaat bagi PT Putra Karisma Palembang. Untuk meningkatkan kinerja karyawan, maka perusahaan harus mempertimbangkan faktor disiplin kerja dan pemberian insentif secara bersama-sama.

scholarly journals ANALYSIS OF FACTORS AFFECTING THE PRICE FLUCTUATION OF CAYENNE PEPPER IN MALANG REGENCY

2021 ◽  
Vol 5 (1) ◽  
pp. 19-26
Author(s):  
Nurul Laili ◽  
Sri Hindarti ◽  
Dwi Susilowati
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Research Method ◽  
Commodity Prices ◽  
Secondary Data ◽  
Regression Method ◽  
Linear Regression Method ◽  
Factors Affecting ◽  
Independent Variables ◽  
Multiple Linear Regression Method

 This study aims to 1) Analyze the pattern of changes in commodity prices for spanish pepper in Malang District. 2) Analyzing the factors that influence fluctuations in the price of spanish pepper in Malang District. The research method used is quantitative method that uses secondary data in the form of time series obtained from several related agencies, namely the Central Statistics Agency of Malang District, Department of Industry and Trade, and Department of food crops, horticulture, and plantation in Malang District. Analysis of the data used is multiple linear regression with the dependent variable is the price at the consumer level from 2009-2018, while the independent variables use the data of the price of spanish pepper at the producer level, the amount of production, and the amount of consumption from 2009-2018. The study found that: 1) The development of the price of spanish pepper had a trend that tended to increase during the last 10 years. 2) From the results of data processing using multiple linear regression method with Eviews 9.0 application, it is found that the factor that significantly influences changes in the price of spanish pepper is the price at the producer level, while the amount of production of spanish pepper and the number of requests does not significantly affect the change in spanish pepper prices in Malang District. 

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