scholarly journals An Analysis of Community Group Buying Behavior of Urban Residents Based on Big Data

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Nanxin Huang ◽  
Kexin Yu ◽  
Cheng Chen
Keyword(s):  
Big Data ◽  
Binary Logistic Regression ◽  
Shopping Behavior ◽  
Urban Residents ◽  
Buying Behavior ◽  
Binary Logistic Regression Model ◽  
Community Group ◽  
Group Buying ◽  
Different Types ◽  
Marketing Methods

By using keywords crawled by big data as a survey reference, this research applied latent category clustering method and binary logistic regression model analysis method to analyze the differences in community group buying behaviors of residents from different city scale and summarize the shopping behavior and features of different types of residents, for the purpose of offering advice on different marketing methods for different types of urban residents, so as to realize the precise marketing of community e-commerce and promote the further development of the industry.

scholarly journals Poverty trend among the lower class households in a rural area of Bangladesh

2016 ◽  
Vol 12 (2) ◽  
pp. 337-344
Author(s):  
MS Kabir ◽  
FR Seamoon ◽  
MA Rahman
Keyword(s):  
Rural Area ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Lower Class ◽  
Positive Change ◽  
Average Income ◽  
Binary Logistic Regression Model ◽  
Employment Opportunities ◽  
Yearly Average ◽  
Different Types

The study undertakes to determine poverty trend among the lower class households during the last five years in a rural area of Bangladesh. A sample of size 80 lower class households was selected from two villages of Sherpur District in Bangladesh. The finding shows that the yearly average income and expenditure of the households were Tk 30912.50 and Tk. 25925, respectively. The change of the socioeconomic status of the lower class households has played an important role on changing pattern of poverty. Occupation of the respondent was significantly associated with change in poverty situation. A shift from lower level to higher level of a characteristic indicates, as a whole, the community has experienced a positive change in their livelihood. In statistical analysis, binary logistic regression model was fitted best. Among the occupation categories handicrafts seemed to help overcome the poverty situation more than business. Respondents involved in handicrafts were 3.673 times more likely to have a positive change in poverty situation compared to those involved in business. The result further suggests that respondents involved in agriculture were 96% significantly less likely to gain positive change than respondents involved in business and other activities. Findings of the study suggest that government should provide different types of facilities to rural lower class people and increase employment opportunities emphasizing more in handicrafts including handicrafts training.J. Bangladesh Agril. Univ. 12(2): 337-344, December 2014

Credit constraints and Rural Migration: Evidence from Six Villages in Uttar Pradesh

2018 ◽  
Vol 15 (3) ◽  
pp. 389-398
Author(s):  
Ruchi Singh
Keyword(s):  
Credit Constraints ◽  
Uttar Pradesh ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Male Migration ◽  
Rural Economies ◽  
And Migration ◽  
The Relationship ◽  
The Empirical Analysis

Rural economies in developing countries are often characterized by credit constraints. Although few attempts have been made to understand the trends and patterns of male out-migration from Uttar Pradesh (UP), there is dearth of literature on the linkage between credit accessibility and male migration in rural Uttar Pradesh. The present study tries to fill this gap. The objective of this study is to assess the role of credit accessibility in determining rural male migration. A primary survey of 370 households was conducted in six villages of Jaunpur district in Uttar Pradesh. Simple statistical tools and a binary logistic regression model were used for analyzing the data. The result of the empirical analysis shows that various sources of credit and accessibility to them play a very important role in male migration in rural Uttar Pradesh. The study also found that the relationship between credit constraints and migration varies across various social groups in UP.

Prevalence of facemask use among general public when visiting wet market during Covid-19 pandemic: An observational study. (Preprint)

2020 ◽  
Author(s):  
Gobi Hariyanayagam ◽  
Sera Selvanthan Sundram Gunasekaran ◽  
Shargunan Selvanthan Gunasekaran ◽  
Nur Syafina Insyirah Zaimi ◽  
Nor Amirah Abdul Halim
Keyword(s):  
High Risk ◽  
General Population ◽  
Binary Logistic Regression ◽  
Final Analysis ◽  
High Risk Population ◽  
Binary Logistic Regression Model ◽  
Chi Square ◽  
Hygiene Measures ◽  
Wet Market ◽  
Medical Grade

BACKGROUND In late December 2019, an outbreak of a novel coronavirus disease (COVID-19; previously known as 2019-nCoV) was epidemiologically linked to seafood and wet animal market in Wuhan, Hubei, China. This event has instigated negative stigma among the general population to view the wet market as a high-risk location for potential transmission of coronavirus. OBJECTIVE This study investigated the prevalence of facemask use among general population visiting the wet market as well as factors contributing to unacceptable facemask practice. Setting The visitors to a district wet market selling range of live or freshly slaughtered animals during COVID-19 pandemic outbreak was observed for facemask practice. METHODS All Individuals visiting the market were observed for the type, category and practice of wearing facemas. Subjects were categorized into two groups of acceptable and unacceptable facemask practice. The Pearson chi-square was used to test for differences in investigated variables in the univariate setting and Binary Logistic regression model was used in the multivariate setting. Main outcome measure Prevalence, acceptance practice and odds ratio of unacceptance of facemask use. RESULTS Among 1697 individuals included in the final analysis, 1687 (99.7%) was observed wearing facemask with 1338 (78.8%) using medical-grade facemask. Among them, 1615 (95.7%) individuals facemask practice was acceptable while the reaming 72 (4.3%) individuals were observed with unacceptable facemask practice. Individuals using medical-grade facemask and high-risk age group are 6.4 times (OR=6.40; 95% CI, 2.00-20.43; p=.002) and 2.06 times practice (OR=2.06; 95% CI, 1.08-3.94; p=.028) more likely to have unacceptable facemask practice respectively. CONCLUSIONS High saturation of facemask among the general population is an adequate indicator of public hygiene measures strategy which can help to mitigate the COVID-19 epidemic impact. Alarmingly, the unacceptable facemask practice among high-risk population raises the need for a targeted approach by healthcare authorities to ensure satisfactory facemask use.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

scholarly journals Entomological survey for identification of Aedes larval breeding sites and their distribution in Chattogram, Bangladesh

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Md. Sahidur Rahman ◽  
Md. Omar Faruk ◽  
Sumiya Tanjila ◽  
Nur Mohammad Sabbir ◽  
Najmul Haider ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Field Survey ◽  
Mosquito Control ◽  
Multiple Logistic Regression Analysis ◽  
Binary Logistic Regression ◽  
Breeding Sites ◽  
Entomological Survey ◽  
Different Types ◽  
Coconut Shells ◽  
Positive Properties

Abstract Background Studying the characteristics of Aedes mosquito habitats is essential to control the mosquito population. The objective of this study was to identify the breeding sites of Aedes larvae and their distribution in Chattogram, Bangladesh. We conducted an entomological survey in 12 different sub-districts (Thana) under Chattogram City, during the late monsoon (August to November) 2019. The presence of different wet containers along with their characteristics and immature mosquitoes was recorded in field survey data form. Larvae and/or pupae were collected and brought to the laboratory for identification. Results Different indices like house index, container index, and the Breteau index were estimated. The multiple logistic regression analysis was applied to identify habitats that were more likely to be positive for Aedes larvae/pupae. A total of 704 wet containers of 37 different types from 216 properties were examined, where 52 (7.39%) were positive for Aedes larvae or pupae. Tire, plastic buckets, plastic drums, and coconut shells were the most prevalent container types. The plastic group possessed the highest container productivity (50%) whereas the vehicle and machinery group was found as most efficient (1.83) in terms of immature Aedes production. Among the total positive properties, 8% were infested with Aedes aegypti, 2% with Aedes albopictus, and 1% contained both species Ae. aegypti and A. albopictus. The overall house index was 17.35%, the container index was 7%, and the Breteau index was 24.49. Containers in multistoried houses had significantly lower positivity compared to independent houses. Binary logistic regression represented that containers having shade were 6.7 times more likely to be positive than the containers without shade (p< 0.01). Conclusions These findings might assist the authorities to identify the properties, containers, and geographical areas with different degrees of risk for mosquito control interventions to prevent dengue and other Aedes-borne disease transmissions.

scholarly journals Hyperchaotic Image Encryption Based on Multiple Bit Permutation and Diffusion

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 510
Author(s):  
Taiyong Li ◽  
Duzhong Zhang
Keyword(s):  
Big Data ◽  
Lyapunov Exponents ◽  
Image Encryption ◽  
Hyperchaotic System ◽  
Encryption Scheme ◽  
Image Content ◽  
Image Security ◽  
Level Data ◽  
Different Types ◽  
And Diffusion

Image security is a hot topic in the era of Internet and big data. Hyperchaotic image encryption, which can effectively prevent unauthorized users from accessing image content, has become more and more popular in the community of image security. In general, such approaches conduct encryption on pixel-level, bit-level, DNA-level data or their combinations, lacking diversity of processed data levels and limiting security. This paper proposes a novel hyperchaotic image encryption scheme via multiple bit permutation and diffusion, namely MBPD, to cope with this issue. Specifically, a four-dimensional hyperchaotic system with three positive Lyapunov exponents is firstly proposed. Second, a hyperchaotic sequence is generated from the proposed hyperchaotic system for consequent encryption operations. Third, multiple bit permutation and diffusion (permutation and/or diffusion can be conducted with 1–8 or more bits) determined by the hyperchaotic sequence is designed. Finally, the proposed MBPD is applied to image encryption. We conduct extensive experiments on a couple of public test images to validate the proposed MBPD. The results verify that the MBPD can effectively resist different types of attacks and has better performance than the compared popular encryption methods.

Predictive Factors for Patients’ Failure to Show for Initial Outpatient Physical Therapist Evaluation

2021 ◽  
Author(s):  
Matthew Briggs ◽  
Christine Ulses ◽  
Lucas VanEtten ◽  
Cody Mansfield ◽  
Anthony Ganim ◽  
...  
Keyword(s):  
Predictive Factors ◽  
Employment Status ◽  
Physical Therapist ◽  
Demographic Data ◽  
Binary Logistic Regression ◽  
Final Analysis ◽  
Outpatient Setting ◽  
Binary Logistic Regression Model ◽  
Number Of Patients ◽  
Payer Source

Abstract Objective The objective of this study was to xamine primary factors which may predict patients’ failure to show at initial physical therapist evaluation in an orthopedic and sports outpatient setting. Methods A retrospective analysis of patients’ demographic data for physical therapist evaluations between January 2013 and April 2015 was performed. A binary logistic regression model was used to evaluate the odds of a no-show at evaluation. Demographic variables of age, employment status, days waited for the appointment, payer source, and distance traveled to clinic were analyzed. Independent variables were considered significant if the 95% Cis of the odds ratios did not include 1.0. Results A total of 6971 patients were included in the final analysis with 10% (n = 698) of the scheduled patients having a no-show event for their initial evaluation. The following factors increased the odds of patients having a no-show event: days to appointment (OR = 1.058; 95% CI = 1.042 to 1.074), unemployment status (OR = 1.96; 95% CI = 1.41 to 2.73), unknown employment status (OR = 3.22; 95% CI = 1.12 to 8.69), Medicaid insurance (OR = 4.87; 95% CI = 3.43 to 6.93), Medicare insurance (OR = 2.22; 95% CI = 1.10 to 4.49), unknown payer source (OR = 262.84; 95% CI = 188.72 to 366.08), and distance traveled ≥5 miles (OR = 1.31; 95% CI = 1.01 to 1.70). Female sex [OR = 0.73; 95% CI = 0.57 to 0.95) and age ≥ 40 years (OR = 0.44; 95% CI = 0.33 to 0.60) decreased the odds of a no-show event. Conclusion Results from this study indicate there may be some demographic factors that are predictive of patients failing to attend their first physical therapist visit. Impact Understanding the predictive factors and identifying potential opportunities for improvements in scheduling processes might help decrease the number of patients failing to show for their initial physical therapy appointment, with the ultimate goal of positively influencing patient outcomes.

scholarly journals Hair Cortisol Concentrations Are Associated with Dental Anxiety during Pregnancy

2021 ◽  
Vol 9 (4) ◽  
pp. 42
Author(s):  
Hilja Viitaniemi ◽  
Auli Suominen ◽  
Linnea Karlsson ◽  
Paula Mustonen ◽  
Susanna Kortesluoma ◽  
...  
Keyword(s):  
Hair Sample ◽  
Psychological Symptoms ◽  
Smoking Status ◽  
Dental Anxiety ◽  
Binary Logistic Regression ◽  
Birth Cohort Study ◽  
Hair Cortisol ◽  
Binary Logistic Regression Model ◽  
Gestational Week ◽  
Independent Association

Dental anxiety (DA) and hair cortisol concentrations (HCC) are associated with psychological symptoms and vary during pregnancy. We aimed to examine the association between HCC and DA at two points of pregnancy. Participants were pregnant mothers (n = 533) drawn from the FinnBrain Birth Cohort Study donating a hair sample at gestational week (gwk) 24 (n = 442) and/or at delivery (n = 176) and completed questionnaires on DA. Two groups, HCC1 and HCC2, treated as separate in the analyses, were formed according to the hair sample donation time i.e., gwk24 and delivery. 85 subjects were included in both groups. MDAS, EPDS, and SCL-90 were used to measure DA, depressive and anxiety symptoms, respectively, at gwk14 for the HCC1 group and gwk34 for the HCC2 group. The association between DA and HCC was studied with a binary logistic regression model, adjusted for anxiety and depressive symptoms, age, BMI, and smoking status. Individuals with high DA had lower HCC levels at gwk24 (OR = 0.548; 95% CI = 0.35–0.86; p = 0.009), but the association was not statistically significant at the delivery (OR = 0.611; 95% CI = 0.28–1.33; p = 0.216). The independent association between HCC and DA in pregnant women suggests that long-term cortisol levels could play a role in the endogenous etiology of DA. Further studies are however, needed.

scholarly journals Liver-Metabolizing Genes and Their Relationship to the Performance of Elite Spanish Male Endurance Athletes; a Prospective Transversal Study

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
David Varillas Delgado ◽  
Juan José Tellería Orriols ◽  
Carlos Martín Saborido
Keyword(s):  
Binary Logistic Regression ◽  
Endurance Performance ◽  
Endurance Athletes ◽  
Genetic Profile ◽  
Glutathione S Transferase ◽  
Binary Logistic Regression Model ◽  
Genotypic Distribution ◽  
Endurance Runner ◽  
Cytochrome P450 Family ◽  
First Time

Abstract Background The genetic profile that is needed to define an endurance athlete has been studied during recent years. The main objective of this work is to approach for the first time the study of genetic variants in liver-metabolizing genes and their role in endurance performance by comparing the allelic and genotypic frequencies in elite endurance athletes to the non-athlete population. Methods Genotypic and allelic frequencies were determined in 123 elite endurance athletes (75 professional road cyclists and 48 endurance elite runners) and 122 male non-athlete subjects (sedentary). Genotyping of cytochrome P450 family 2 subfamily D member 6 (CYP2D6 rs3892097), glutathione-S transferase mu isoform 1 (GSTM1), glutathione S-transferase pi (GSTP rs1695) and glutathione S-transferase theta (GSTT) genes was performed by polymerase chain reaction (PCR). The combination of the polymorphisms for the “optimal” polygenic profile has been quantified using the genotype score (GS). Results Statistical differences were found in the genetic distributions between elite endurance athletes and non-athletes in CYP2D6 (p < 0.001) and GSTT (p = 0.014) genes. The binary logistic regression model showed a favourable OR (odds ratio) of being an elite endurance runner against a professional road cyclist (OR: 2.403, 95% CI: 1.213–4.760 (p = 0.002)) in the polymorphisms studied. Conclusions Genotypic distribution of liver-metabolizing genes in elite endurance athletes is different to non-athlete subjects, with a favourable gene profile in elite endurance athletes in terms of detoxification capacity.

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