scholarly journals Partial Least Square Analyses of Landscape and Surface Water Biota Associations in the Savannah River Basin

ISRN Ecology ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Maliha S. Nash ◽  
Deborah J. Chaloud
Keyword(s):  
Surface Water ◽  
Small Sample Size ◽  
Surface Water Quality ◽  
Spatial Location ◽  
Small Sample ◽  
Partial Least Square ◽  
Least Square ◽  
Data Sets ◽  
Savannah River ◽  
Remotely Sensed Data

Ecologists are often faced with problem of small sample size, correlated and large number of predictors, and high noise-to-signal relationships. This necessitates excluding important variables from the model when applying standard multiple or multivariate regression analyses. In this paper, we present the results of applying PLS to explore relationships among biotic indicators of surface water quality and landscape conditions accounting for the above problems. Available field sampling and remotely sensed data sets for the Savannah Basin are used. We were able to develop models and compare results for the whole basin and for each ecoregion (Blue Ridge, Piedmont, and Coastal Plain) in spite of the data constraints. The amount of variability in surface water biota explained by each model reflects the scale, spatial location, and the composition of contributing landscape metrics. The landscape-biota model developed for the whole basin using PLS explains 43% and 80% of the variation in water biota and landscape data sets, respectively. Models developed for each of the three ecoregions indicate dominance of landscape variables which reflect the geophysical characteristics of that ecoregion.

scholarly journals Factors Affecting Whistleblowing Intention: Case Study on the Implementation of Village Funds

2020 ◽  
pp. 18-29
Author(s):  
Ulin Nuha Alfani ◽  
Fajar Gustiawaty Dewi ◽  
Susi Sarumpaet
Keyword(s):  
Locus Of Control ◽  
Latent Variables ◽  
Behavioral Control ◽  
Small Sample Size ◽  
Small Sample ◽  
Partial Least Square ◽  
Least Square ◽  
Path Model ◽  
Whistle Blowing ◽  
Consultative Body

This study aims to analyze the factors that influence the individual's intention to do whistle blowing. This study uses a questionnaire to gather the information needed. The variables used in this study are Subjective Norms, Attitudes Towards Behavior, Perceptions About Behavioral Control, Locus of Control, and Reward as independent variables and Intentions as dependent variables. The total samples in this study were 112 samples and using random sampling techniques in data collection. Respondents in this study were the Village Consultative Body in 7 Sub-districts in South Lampung District. Data were analyzed using Partial Least Square (PLS). The Partial Least Squares (PLS) technique was chosen because this tool is widely used to estimate the path model with a small sample size [1] then it is used for a very complex model (consisting of many latent variables and manifests) without problems [2]. The results of this study indicate that the subjective norm, attitudes toward behavior and the reward variable does not affect the individual's intention to do whistle blowing. Then, the behavioral control and locus of control variables indicate that the two variables affect the individual's intention to do whistleblowing.

scholarly journals The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study

Molecules ◽  
2019 ◽  
Vol 24 (13) ◽  
pp. 2367 ◽  
Author(s):  
Barberini ◽  
Noto ◽  
Fattuoni ◽  
Satta ◽  
Zucca ◽  
...  
Keyword(s):  
Healthy Subjects ◽  
Small Sample Size ◽  
B Cell Lymphoma ◽  
Small Sample ◽  
Partial Least Square ◽  
Lymphocytic Leukemia ◽  
Least Square ◽  
Gas Chromatography Mass Spectrometry ◽  
Metabolomic Analysis ◽  
Population Controls

Lymphoma defines a group of different diseases. This study examined pre-treatment plasma samples from 66 adult patients (aged 20–74) newly diagnosed with any lymphoma subtype, and 96 frequency matched population controls. We used gas chromatography-mass spectrometry (GC-MS) to compare the metabolic profile by case/control status and across the major lymphoma subtypes. We conducted univariate and multivariate analyses, and partial least square discriminant analysis (PLS-DA). When compared to the controls, statistically validated models were obtained for diffuse large B-cell lymphoma (DLBCL), chronic lymphocytic leukemia (CLL), multiple myeloma (MM), and Hodgkin lymphoma (HL), but not follicular lymphoma (FL). The metabolomic analysis highlighted interesting differences between lymphoma patients and population controls, allowing the discrimination between pathologic and healthy subjects: Important metabolites, such as hypoxanthine and elaidic acid, were more abundant in all lymphoma subtypes. The small sample size of the individual lymphoma subtypes prevented obtaining PLS-DA validated models, although specific peculiar features of each subtype were observed; for instance, fatty acids were most represented in MM and HL patients, while 2-aminoadipic acid, 2-aminoheptanedioic acid, erythritol, and threitol characterized DLBCL and CLL. Metabolomic analysis was able to highlight interesting differences between lymphoma patients and population controls, allowing the discrimination between pathologic and healthy subjects. Further studies are warranted to understand whether the peculiar metabolic patterns observed might serve as early biomarkers of lymphoma.

scholarly journals KAJIAN SIMULASI PERBANDINGAN METODE REGRESI KUADRAT TERKECIL PARSIAL, SUPPORT VECTOR MACHINE, DAN RANDOM FOREST

2020 ◽  
Vol 4 (1) ◽  
pp. 203-215
Author(s):  
Asep Andri Fauzi ◽  
Agus M. Soleh ◽  
Anik Djuraidah
Keyword(s):  
Random Forest ◽  
Small Sample Size ◽  
Small Sample ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Support Vector ◽  
Ordinary Least Square ◽  
Highly Correlated ◽  
Correlated Predictors

Highly correlated predictors and nonlinear relationships between response and predictors potentially affected the performance of predictive modeling, especially when using the ordinary least square (OLS) method. The simple technique to solve this problem is by using another method such as Partial Least Square Regression (PLSR), Support Vector Regression with kernel Radial Basis Function (SVR-RBF), and Random Forest Regression (RFR). The purpose of this study is to compare OLS, PLSR, SVR-RBF, and RFR using simulation data. The methods were evaluated by the root mean square error prediction (RMSEP). The result showed that in the linear model, SVR-RBF and RFR have large RMSEP; OLS and PLSR are better than SVR-RBF and RFR, and PLSR provides much more stable prediction than OLS in case of highly correlated predictors and small sample size. In nonlinear data, RFR produced the smallest RMSEP when data contains high correlated predictors.

scholarly journals Matching organizational frame of reference and business strategy with contemporary marketing practices

2016 ◽  
Vol 11 (4) ◽  
pp. 533-549 ◽  
Author(s):  
Allam Abu Farha
Keyword(s):  
Business Strategy ◽  
Survey Methodology ◽  
Assessment Tool ◽  
Small Sample Size ◽  
Small Sample ◽  
Frame Of Reference ◽  
Partial Least Square ◽  
Least Square ◽  
Marketing Practice ◽  
Content Type

Purpose The purpose of this paper is to investigate diversity of marketing practices of firms operating in the same environment, by identifying how management perception and business strategy (BS) fits with the choice of the marketing practice. Design/methodology/approach A model was developed and tested using survey methodology based on three well-validated research instruments. Data were analyzed using the partial least square approach. Findings The results showed that different marketing practice were coupled with different frame of reference, as well as different BS. These forces were found to be inter related, and internally coherent, resulting in viable configurational profiles. Research limitations/implications The research is unique and exploratory, and was conducted in three Arabic countries with a small sample size. For these reasons, generalizability is somewhat constrained. Practical implications The findings would help managers to carefully examine the internal logic of their marketing-related profiling; it can be used as an assessment tool, where performance should be enhanced if the variables are coherent. Originality/value To author’s knowledge this is the first study that inspect three variables that had been associated with decision making, but not integrated together in a holistic framework to explain marketing diversity. Additionally it identified four viable types of marketing practices with its corresponding frame of reference and BS. Therefore, the paper reports a work in an area not previously researched.

scholarly journals Assessing the Performance of Deep Learning Algorithms for Short-Term Surface Water Quality Prediction

2021 ◽  
Vol 13 (19) ◽  
pp. 10690
Author(s):  
Heelak Choi ◽  
Sang-Ik Suh ◽  
Su-Hee Kim ◽  
Eun Jin Han ◽  
Seo Jin Ki
Keyword(s):  
Water Quality ◽  
Deep Learning ◽  
Surface Water ◽  
Learning Algorithms ◽  
Arima Model ◽  
Surface Water Quality ◽  
Percentage Error ◽  
Data Sets ◽  
Learning Models ◽  
Dependent Variables

This study aimed to investigate the applicability of deep learning algorithms to (monthly) surface water quality forecasting. A comparison was made between the performance of an autoregressive integrated moving average (ARIMA) model and four deep learning models. All prediction algorithms, except for the ARIMA model working on a single variable, were tested with univariate inputs consisting of one of two dependent variables as well as multivariate inputs containing both dependent and independent variables. We found that deep learning models (6.31–18.78%, in terms of the mean absolute percentage error) showed better performance than the ARIMA model (27.32–404.54%) in univariate data sets, regardless of dependent variables. However, the accuracy of prediction was not improved for all dependent variables in the presence of other associated water quality variables. In addition, changes in the number of input variables, sliding window size (i.e., input and output time steps), and relevant variables (e.g., meteorological and discharge parameters) resulted in wide variation of the predictive accuracy of deep learning models, reaching as high as 377.97%. Therefore, a refined search identifying the optimal values on such influencing factors is recommended to achieve the best performance of any deep learning model in given multivariate data sets.

scholarly journals THE INFLUENCE OF COMPENSATION SUITABILITY AND INTERNAL CONTROL SYSTEM TO FRAUDWITH MORALITY AS MODERATING VARIABLE

2018 ◽  
Vol 1 (1) ◽  
pp. 226
Author(s):  
Junaidi Junaidi ◽  
Maulidani Ubaidillah
Keyword(s):  
Control System ◽  
Control Systems ◽  
Internal Control ◽  
Small Sample ◽  
Partial Least Square ◽  
Least Square ◽  
Government Organizations ◽  
Internal Control System ◽  
Negative Effect ◽  
Sample Testing

This study aims to observe the effect of compensation suitability and internal control system on fraud. Testing is done directly and indirectly. Indirect influence is made through moderating variable of morality as a moderator of the influence of compensation suitability and internal control system on fraud. Data obtained by purposive sampling. As many as 79 processed data were obtained through the distribution of questionnaires to stakeholders in local government organizations in Pemekasan District of East Java. The parametric test fails because the residual data is not normally distributed even though the outliers’data has been removedfrom the observation. The test was performed using partial least square due to the small sample. Testing the hypothesis proves that the three variables have a significant negative effect on fraud. This confirms the importance of internal control system and compensation suitability as a means of anticipating fraud. Conversely, moderating variable of expected morality may reinforce the nonlinear influence of compensatory suitability and internal control systems not significantly explain fraud.

scholarly journals An investigation into the effectiveness of energy savings performance contracting (ESPC) structure : how to fill the opportunity to implementation gap

2016 ◽  
Author(s):  
◽  
Chatchai Pinthuprapa
Keyword(s):  
Structural Equation ◽  
Online Survey ◽  
Energy Savings ◽  
The United States ◽  
Small Sample ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Implementation Success ◽  
Performance Contracting

This dissertation introduce and empirically verify a structure of Energy Savings Performance Contracting (ESPC) perspective among clients, Energy Service Companies (ESCOs) and governments. The new approach ESPC structure model presented herein is built on the Motivation-Opportunity-Ability (MOA) theory where key influences are identified. An important component of performance contracting, the performance measurement, has been incorporated in the structure to monitor the effect on ESPC implementation success. The proposed structure and hypothesis were verified as a current ESPC practice in the United States through an online survey. The proposed structure was analyzed to understand relationships between the stakeholders, key factors, barriers and/or practices among the constructs through the structural equation modeling (SEM) approach. Due to the complex relationship of non-normal data and small sample size compared to the number of variables, the Partial Least Square SEM (PLS-SEM) method was chosen. The survey statistical results were used to verify the ESPC-MOA structure, develop an implementation guide and identify the ESPC critical factors to help establish its implementation success.

Neoadjuvant bevacizumab: Surgical complications of mastectomy with and without reconstruction.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 1100-1100
Author(s):  
Kari Joanne Kansal ◽  
Laura Stewart Dominici ◽  
Sara M. Tolaney ◽  
Steven J. Isakoff ◽  
Ian E. Krop ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Therapy ◽  
Surgical Complications ◽  
Small Sample Size ◽  
Small Sample ◽  
P Value ◽  
Data Sets ◽  
Complication Rates ◽  
Similar Time ◽  
Time Period

1100 Background: Neoadjuvant therapy is commonly used in operable breast cancer. We prospectively evaluated the surgical complications in a cohort of patients who underwent mastectomy following neoadjuvant doxorubucin hydrochloride/cyclophosphamide/paclitaxel (AC/T) plus bevacizumab and compared the rate of complications to a matched cohort of neoadjuvant AC/T without bevacizumab. Methods: One hundred patients with HER2-negative breast cancer enrolled in a single-arm trial of neoadjuvant AC/T plus bevacizumab (cohort 1), 60 of these patients underwent mastectomy and were matched with 59 patients who received standard neoadjuvant AC/T (cohort 2) over a similar time period in the same healthcare system. All patients underwent mastectomy with or without reconstruction. Fisher’s exact tests were used to compare complication rates, with a p<0.05 was considered significant. Results: Patients were matched well in terms of demographics. The overall complication rate was 33% in cohort 1 and 31% in cohort 2 (P-value=0.84; Table). In cohort 1, 7 of 23 (30%) patients who underwent immediate expander/implant reconstruction had complications, including 2 patients who had explantation of their reconstructions. In cohort 2, 0 of 8 (0%) had complications (p value=0.15). Conclusions: Nearly a third of patients undergoing neoadjuvant therapy with AC/T with or without bevacizumab developed a postoperative complication after mastectomy. The use of bevacizumab was not associated with a significant increase in surgical complications, although this is a non-randomized data with a small sample size. As larger data sets become available with the use of neoadjuvant bevacizumab with mastectomy, further refinement may be necessary. [Table: see text]

The influence of Islamic attributes on tourist satisfaction with pull motivation as an intervening variables

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hilda Monoarfa ◽  
Agus Rahayu ◽  
Fitranty Adirestuty ◽  
Rizuwan Abu Karim ◽  
Azlin Zanariah Bahtar ◽  
...  
Keyword(s):  
Structural Equation ◽  
Quantitative Methods ◽  
Small Sample ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Content Type ◽  
Tourist Attractions ◽  
Tourist Satisfaction ◽  
The Impact

Purpose The purpose of this study is to find out the level of influence of Islamic attributes and pull motivation to the satisfaction of Muslim tourists visiting Indonesia. Furthermore, this study may reveal where variables have a strong influence on the variable satisfaction of Muslim tourists. In addition, this study also wanted to know if Islamic attributes can influence the satisfaction of Muslim tourists with pull motivation as a moderating variable. Design/methodology/approach Using quantitative methods, this study analyzed the results of questionnaires that have been distributed to 200 Muslim tourist respondents who have visited Indonesia. To declare the hypotheses, the collected data were analyzed with structural equation modeling-partial least square using SmartPLS application version 3.2.7. Findings From this study, it was discovered that pull motivation has more effect on the satisfaction of Muslim tourists visiting Indonesia. Other results showed that both Islamic attributes and pull motivation simultaneously affect the satisfaction of Muslim tourists. Furthermore, Islamic attributes can affect pull motivation and pull motivation can also become an intermediary variable in bridging the impact of Islamic attributes on the satisfaction of Muslim tourists. Research limitations/implications The limitations of this study include the relatively small sample used and not yet taking foreign tourists as respondents. Besides that, you can also add several variables to complement this research in the future either as an intervening variable or a mediator variable. Practical implications To increase the satisfaction of Muslim tourists traveling to Indonesia, policymakers in Indonesia must further improve the facilities of the pull motivation aspect such as the cleanliness of tourist attractions, exotic locations and hygienic shopping centers. In addition, aspects of Islamic attributes must also be updated, such as aspects of adequate worship facilities and tourist attractions that apply the concept of halal for Muslims. Originality/value The originality of this study on the pull motivation variable as an intervening variable and adding the Islamic attribute variable in the case of Muslim tourist satisfaction.

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