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Anil Kumar Singh ◽  
Anant Kumar Jain

The study investigates the factors influencing business continuity during adversities like COVID-19. It further sheds light on priorities for preparedness measures that need to be taken to ensure continuity during these adversities. Exploratory research was conducted in the form of focussed interviews with 20 senior management industry professionals, and these were analyzed using N-Vivo, and four important determinants of business continuity were identified based on which a research model was conceptualized using business continuity as dependent variable and others as independent variables. The model was further tested using quantitative research. For this purpose, a questionnaire was prepared, and a total of 200 responses were collected representing 26 sectors. These responses were analyzed using factor and variance analysis, and a multiple regression analysis was performed to test the role of these variables on business continuity. It was further concluded that the factors that ensure business continuity differ according to the industry in which the business is operating.

Suraya Masrom ◽  
Norhayati Baharun ◽  
Nor Faezah Mohamad Razi ◽  
Rahayu Abdul Rahman ◽  

Particle Swarm Optimization is a metaheuristics algorithm widely used for optimization problems. This paper presents the research design and implementation of using Particle Swarm Optimization to automate the features selections in the machine learning models for Airbnb price prediction. Today, Airbnb is changing the business models of the hospitality industry globally. While a bigger impact has been given by the Airbnb community to the local economic development of each country, there has been very little effort that investigates on Airbnb pricing issue with machine learning techniques. Focusing on Airbnb Singapore, the main problem on the dataset is the low correlation of the independent variables to the hospitality price. Choosing the best combination of the independent variables is essential, which can be achieved through features selection optimization. Particle Swarm Optimization is useful to optimize the best variables combination for automating the features selection in machine learning models. By comparing the magnitude of change of the R squared values before and after the use of PSO feature selection, the result showed that the automated features selection has improved the results of all the machine learning algorithms mainly in the linear-based machine learning (Linear Regression, Lasso, Ridge). Keywords—Machine Learning, Automated Features Selection, Particle Swarm Optimization, Airbnb

Y. Gevrekçi ◽  
Ö.İ. Güneri ◽  
Ç. Takma ◽  
A. Yeşilova

Background: The objective of this study is comparing different count data models for stillbirth data. In modeling this type of data, Poisson regression or alternative models can be preferred. Methods: The poisson, negative binomial, zero-inflated poisson, zero-inflated negative binomial, poisson-logit hurdle and negative binomial-logit hurdle regressions were compared and used to examine the effects of the gender, parity and herd-year-season independent variables on stillbirth. Furthermore, the Log-Likelihood statistics, Akaike Information Criteria, Bayesian Information Criteria and rootogram graphs were used as comparison criteria for performance of the models. According to these criteria, Negative Binomial-Logit Hurdle Regression model was chosen as the best model. Result: The parameter estimates obtained by Negative Binomial-Logit Hurdle Regression model in relation to the effects of the gender, parity and herd-year-season independent variables on stillbirth were found to be significant (p less than 0.01). It was found that while stillbirth incidence was higher in males than females, it was found to decrease as the parity increased. As a result, the Negative Binomial Logit Hurdle model was found the best model for stillbirth count data with overdispersion.

2022 ◽  
Arkady Poliakovsky

We investigate Lorentzian structures in the four-dimensionalspace-time, supplemented either by a covector field of thetime-direction or by a scalar field of the global time. Furthermore,we propose a new metrizable model of the gravity. In contrast to theusual Theory of General Relativity where all ten components of thesymmetric pseudo-metrics are independent variables, the presentedhere model of the gravity essentially depend only on singlefour-covector field, restricted to have only three-independentcomponents. However, we prove that the Gravitational field, ruled bythe proposed model and generated by some massive body, resting andspherically symmetric in some coordinate system, is given by apseudo-metrics, which coincides with thewell known Schwarzschild metric from the General Relativity. TheMaxwell equations and Electrodynamics are also investigated in theframes of the proposed model. In particular, we derive the covariantformulation of Electrodynamics of moving dielectrics andpara/diamagnetic mediums.

2022 ◽  
Vol 4 (1) ◽  
Karsum Usman ◽  
Usman Moonti ◽  
Sri Endang Saleh

This study aims to determine the effect of price, land area and production costs on the income of rice farmers in North Toto Village, Tilongkabila District, Bone Bolango Regency. Data collection techniques used in this study were observation, interviews, questionnaires, and documentation. With a total sample of 44 farmers in North Toto Village. This research method uses a quantitative approach with multiple linear regression model analysis. The results showed that the price had a negative and insignificant effect on the income of rice farmers in North Toto Village. This means that every 1% increase in price can reduce income by 0.237. Land area has a positive and significant effect on the income of rice farmers in North Toto Village. This means that every 1% increase in land area can increase income by 0.682. Production costs have a negative and significant effect on the income of rice farmers in North Toto Village. This means that every 1% increase can reduce income by -0.254. The coefficient of determination (R Square) is 0.596, this shows that the percentage of rice farmers' income variation which is explained by the variation of the independent variables, namely price, land area and production costs is 59.6% for the remaining 40.4% influenced by other variables.

2022 ◽  
Vol 10 (4) ◽  
pp. 617-623
Silvia Elsa Suryana ◽  
Budi Warsito ◽  
Suparti Suparti

Telemarketing is another form of marketing which is conducted via telephone. Bank can use telemarketing to offer its products such as term deposit. One of the most important strategy to the success of telemarketing is opting the potential customer to create effective telemarketing. Predicting the success of telemarketing can use machine learning. Gradient boosting is machine learning method with advanced decision tree. Gardient boosting involves many classification trees which are continually upgraded from previous tree. The optimal classification result cannot be separated from the role of the optimal hyperparameter.  Hyperopt is Python library that can be used to tune hyperparameter effectively because it uses Bayesian optimization. Hyperopt uses hyperparameter prior distribution to find optimal hyperparameter. Data in this study including 20 independent variables and binary dependent variable which has ‘yes’ and ‘no’ classes. The study showed that gradient boosting reached classification accuracy up to 90,39%, precision 94,91%, and AUC 0,939. These values describe gradient boosting method is able to predict both classes ‘yes’ and ‘no’ relatively accurate.

F1000Research ◽  
2022 ◽  
Vol 11 ◽  
pp. 39
Tamiru Yazew

Background Acute and chronic child undernutrition is a continuous problem in Ethiopia. Therefore, this study was initiated to compare the prevalence of underweight and its associated factors among children aged 6-23 months in the Kuyu district, North Shewa zone, Oromia, Ethiopia. Methods An observational community-based study was conducted on 612 children (304 from household security and 308 from household food insecurity). A structured and standardize questionnaire was used in this study. Anthropometric measurements were generated using WHO standardize. Data was analyzed using SPSS version 20.0. Bivariate and multivariate logistic regression analysis was used to identify the independent variables associated with underweight (weight-for-age) among children in household food security and insecurity, a p value less than 0.05 with 95%CI was considered as statistically significant. Results The results indicated that 30.9% [95%CI; 25.7, 36.2] and 36.7% [95% CI; 31.8, 42.5] of children were underweight for their age in household food security and insecurity. Low wealth status (AOR=3.2; 95%CI: 1.099, 9.275), poor dietary diets (AOR=5.2; 95%CI: 2.046, 13.27), and lack of breastfeeding for two years (AOR= 2.1; 95%CI= 1.78, 5, 42) were associated with underweight children in household food security. Whereas lack of antenatal care visits (AOR=0.52; 95%CI: 0.12, 0.68) and poor dietary diets (AOR=3.01; 95%CI= 2.1, 17.4) were other independent variables associated with underweight children in household food insecurity. Conclusions This study established that there was a high prevalence of underweight in children from Oromia.  Therefore, introducing household income generating activities are vital interventions in order to overcome the problem of undernutrition in this region.

2022 ◽  
Vol 15 (1) ◽  
pp. 34
Xiu Wei Yeap ◽  
Hooi Hooi Lean

Trading activities represent the flow of market information to the investors. This paper examines the effect of trading activities, i.e., trading volume and open interest, on the volatility of return for Malaysian Crude Palm Oil Futures. The GARCH model is applied by adding the expected and unexpected elements of trading activities (trading volume and open interest) as the independent variables. The results show that there is a negative contemporaneous relationship between the expected volume and volatility, but that a positive relationship exists between unexpected volume and volatility. On the contrary, the expected and unexpected open interest mitigate the volatility. Therefore, both trading volume and open interest should be considered together when information flows into the market.

2022 ◽  
Vol 72 (4) ◽  
pp. e437
Ş. S. Seçilmiş ◽  
D. Koçak Yanık ◽  
S. Fadıloğlu ◽  
F. Göğüş

The factors affecting the microwave bleaching of sunflower oil and the interaction between them were investigated and optimized by response surface methodology using a three-factor five-level central composite rotatable design. Microwave power, time and the amount of bleaching clay were selected as independent variables studied in the range of 70-120 W, 2-15 min, and 0.01-0.5%. The dependent variables that measure the bleaching efficiency and oil quality were evaluated as hue angle, chroma and totox value. Optimization was carried out by minimizing totox and chroma and maximizing hue angle. Hue angle, chroma and totox were found as 96.91, 37.66 and 23.31 under optimal conditions. Optimal microwave bleaching was successfully performed by using less bleaching clay (0.4%) and a shorter time (8 min) compared to the current industrial application without any adverse effect on oil quality. Hence, microwave bleaching is thought to be an alternative method for the bleaching of edible oils.

2022 ◽  
Vol 12 (1) ◽  
pp. 94
Juan F. Dorado ◽  
Javier C. Angulo

(1) Background: The adjustable transobturator male system (ATOMS) device serves to treat post-prostatectomy incontinence, as it enhances residual urinary sphincteric function by dorsal compression of the bulbar urethra. We investigated the clinical parameters affecting continence recovery using this device and developed a decision aid to predict success. (2) Methods: We reviewed consecutive men treated with first-time ATOMS for post-prostatectomy incontinence from 2014 to 2021 at our institution. Patient demographics, reported pads per day (PPD), 24-h pad-test and Standing Cough Test (SCT), results’ grades 1–4, according to Male Stress Incontinence Grading Scale (MSIGS), and the International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF) questionnaire were assessed. Treatment success was defined as no pads or a single PPD with ≤20-mL 24-h pad-test. Logistic regression was performed using a stepwise model (entry 0.15 and stay criterium 0.1) to evaluate independent variables’ determinant of dryness. Receiver-operating characteristic (ROC) curves for predictive variables were evaluated and their area under curve (AUC) was compared. A nomogram was generated and internally validated to predict probability of treatment success. (3) Results: Overall, 149 men (median age 70 years, IQR 7) were evaluated with a median follow-up of 45 months (IQR 26). Twelve patients (8%) had previous devices for incontinence, and 21 (14.1%) had pelvic radiation. Thirty-five men (23.5%) did not achieve continence after ATOMS adjustment (use of no or one security PPD with ≤20-mL 24-h pad-test). In univariate analysis, Charlson comorbidity index (p = 0.0412), previous urethroplasty (p = 0.0187), baseline PPD (p < 0.0001), 24-h pad-test (p < 0.0001), MSIGS (p < 0.0001), and ICIQ-SF questionnaire score (p < 0.0001) predicted ATOMS failure. In a multivariable model, 24-h pad-test (p = 0.0031), MSIGS (p = 0.0244), and radiotherapy (p = 0.0216) were independent variables, with AUC 0.8221. The association of MSIGS and 24-h pad-test was the superior combination (AUC 0.8236). A nomogram to predict the probability of ATOMS failure using the independent variables identified was proposed. (4) Conclusions: Several variables were identified as predictive of success for ATOMS using clinical history, physical examination (MSIGS), and factors that evaluate urine loss severity (PPD, 24-h pad-test, and ICIQ-SF questionnaire). MSIGS adds prognostic value to 24-h pad-test in assessing success of ATOMS device to treat post-prostatectomy incontinence. A nomogram was proposed to calculate the risk of ATOMS failure, which could be of interest to personalize the decision to use this device or not in the individual patient.

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