scholarly journals Spatializing Area-Based Measures of Neighborhood Characteristics for Multilevel Regression Analyses: An Areal Median Filtering Approach

2016 ◽  
Vol 93 (3) ◽  
pp. 551-571 ◽  
Author(s):  
Masayoshi Oka ◽  
David W. S. Wong
Keyword(s):  
Median Filtering ◽  
Neighborhood Characteristics ◽  
Regression Analyses ◽  
Multilevel Regression ◽  
Filtering Approach

scholarly journals Preregistered replication of Stoeber (2012): Dyadic perfectionism in romantic relationships

2020 ◽  
Author(s):  
Matt Williams ◽  
Catelyn Gill
Keyword(s):  
Romantic Relationships ◽  
Relationship Satisfaction ◽  
Regression Analyses ◽  
Multilevel Regression ◽  
Dyadic Perfectionism

The present study reports a preregistered replication of a study by Stoeber (2012) investigating the relationships between dyadic perfectionism, relationship satisfaction and longterm commitment. Our study included 71 couples in a dyadic design that measured actor and partner effects using multilevel regression analyses. The findings were mixed: We were able to reproduce some of the relationships reported by Stoeber, some failed to reproduce, and some new relationships were found. Participants who perceived that their partners had perfectionistic expectations of them did tend to report lower relationship satisfaction and longterm commitment. However, there was no evidence of a relationship between the degree to which participants self-reported having perfectionistic standards towards their partners and their partners’ relationship satisfaction and longterm commitment.

Adaptive Median Filtering Based on Unsupervised Classification of Pixels

2013 ◽  
pp. 273-296 ◽  
Author(s):  
J. K. Mandal ◽  
Somnath Mukhopadhyay
Keyword(s):  
Clustering Algorithm ◽  
Digital Images ◽  
Unsupervised Classification ◽  
Median Filtering ◽  
Adaptive Window ◽  
Novel Approach ◽  
Weighted Median ◽  
Window Selection ◽  
Filtering Approach

This chapter deals with a novel approach which aims at detection and filtering of impulses in digital images through unsupervised classification of pixels. This approach coagulates directional weighted median filtering with unsupervised pixel classification based adaptive window selection toward detection and filtering of impulses in digital images. K-means based clustering algorithm has been utilized to detect the noisy pixels based adaptive window selection to restore the impulses. Adaptive median filtering approach has been proposed to obtain best possible restoration results. Results demonstrating the effectiveness of the proposed technique are provided for numeric intensity values described in terms of feature vectors. Various benchmark digital images are used to show the restoration results in terms of PSNR (dB) and visual effects which conform better restoration of images through proposed technique.

De-Noising of Binary Image Using Accelerated Local Median-Filtering Approach

2019 ◽  
pp. 164-185
Author(s):  
Amit Khan ◽  
Dipankar Majumdar
Keyword(s):  
Time Complexity ◽  
Window Size ◽  
Analytical Techniques ◽  
Approximate Solutions ◽  
Median Filtering ◽  
Binary Images ◽  
Noise Characteristics ◽  
Varied Size ◽  
Number Of Iterations ◽  
Filtering Approach

In the last few decades huge amounts and diversified work has been witnessed in the domain of de-noising of binary images through the evolution of the classical techniques. These principally include analytical techniques and approaches. Although the scheme was working well, the principal drawback of these classical and analytical techniques are that the information regarding the noise characteristics is essential beforehand. In addition to that, time complexity of analytical works amounts to beyond practical applicability. Consequently, most of the recent works are based on heuristic-based techniques conceding to approximate solutions rather than the best ones. In this chapter, the authors propose a solution using an iterative neural network that applies iterative spatial filtering technology with critically varied size of the computation window. With critical variation of the window size, the authors are able to show noted acceleration in the filtering approach (i.e., obtaining better quality filtration with lesser number of iterations).

scholarly journals Perceived personal deadlines for late-life preparation across adulthood

2020 ◽  
Author(s):  
Frieder R. Lang ◽  
Fiona S. Rupprecht
Keyword(s):  
Older Adults ◽  
Longitudinal Data ◽  
Social Connectedness ◽  
Late Life ◽  
Regression Analyses ◽  
Multilevel Regression ◽  
Younger Adults ◽  
Opportunity Structures ◽  
Self Rated Health ◽  
Over Time

Abstract Throughout adulthood, individuals follow personal timetables of deadlines that shape the course of aging. We examine 6-year-longitudinal data of perceived personal deadlines for starting with late-life preparation across adulthood. Findings are based on a sample of 518 adults between 18 and 88 years of age. Multilevel regression analyses were conducted to explore changes in personal deadlines for preparation in five domains (i.e., finances, end of life, housing, social connectedness, caregiving) in relation to calendar age, self-rated health, subjective position in life, and sociodemographic variables. Findings suggest that personal deadlines for starting preparatory activities differ depending on calendar age and domain of late-life preparation. Older adults as compared to younger adults are likely to report narrower deadlines for beginning with late-life preparation. Perceived deadlines for late-life preparation were furthermore found to be preponed and slightly dilated over time. Findings suggest that depending on age-graded opportunity structures, individuals flexibly adjust their personal deadlines for late-life preparation.

scholarly journals Belonging as Compensator

2020 ◽  
Vol 52 (3-4) ◽  
pp. 116-126 ◽  
Author(s):  
Tamara Marksteiner ◽  
Marc Philipp Janson ◽  
Hanna Beißert
Keyword(s):  
Negative Impact ◽  
Well Being ◽  
Regression Analyses ◽  
Multilevel Regression ◽  
Abuse Of Power ◽  
Being Bullied ◽  
Different Cultures ◽  
Health And Well Being ◽  
Practical Implications ◽  
Over Time

Abstract. Bullying is a serious issue among adolescents worldwide. It has been conceptualized as a type of physical or indirect peer victimization that occurs repeatedly over time and is characterized by a systematic abuse of power. Being bullied at school severely affects victims’ health and well-being. What protects students from these consequences? We investigate feelings of belonging –i. e., the feeling that one is accepted, included, respected, and valued in the respective social environment – as a possible compensator for bullying consequences across different cultures. We hypothesize that being bullied is less severe for students who have strong feelings of belonging. We use data from 319,057 15-year-old students across 47 countries. Multilevel regression analyses replicated that bullying and well-being are negatively associated. Further, the results indicated, as expected, that feelings of belonging compensate for the negative impact that bullying has on well-being. Practical implications as well as limitations are discussed.

scholarly journals Unstructured Noise Removal for Industrial Sensor Imaging Unit by Hybrid Adaptive Median Algorithm

2021 ◽  
Vol 3 (4) ◽  
pp. 284-297
Author(s):  
B. Vivekanandam
Keyword(s):  
Thermal Noise ◽  
Noise Removal ◽  
Common Type ◽  
Imaging Systems ◽  
Research Report ◽  
Median Filtering ◽  
Challenging Problem ◽  
Sensor Devices ◽  
Original Picture ◽  
Filtering Approach

Thermal noise is the most common type of contamination in digital image acquisition operations, and is caused by the temperature condition of the industrial sensor devices used in the process. When it comes to picture improvement, removing noise from the image is one of the most crucial steps. However, in image processing, it is more critical to retain the characteristics of the original picture while eliminating the noise. Thermal noise removal is a challenging problem in image denoising. This article provides a strategy based on a Hybrid Adaptive Median (HAM) filtering approach for removing thermal noise from the image output of an industrial sensor. The demonstration of this proposed approach's ability, is to successfully detect and reduce thermal noise. In addition, this study examines an adaptive hybrid adaptive median filtering approach that has significant computational advantages, making it highly practical. Finally, this research report on experiments shows the high-quality industrial sensor imaging systems that have been successfully implemented in the real world.

scholarly journals The Link between Parental Support and Adolescent Negative Mood in Daily Life: between-Person Heterogeneity in within-Person Processes

2020 ◽  
Author(s):  
Loes H. C. Janssen ◽  
Bernet M. Elzinga ◽  
Bart Verkuil ◽  
Manon H. J. Hillegers ◽  
Loes Keijsers
Keyword(s):  
Depressive Symptoms ◽  
Individual Differences ◽  
Parental Support ◽  
Daily Life ◽  
Negative Mood ◽  
Regression Analyses ◽  
Multilevel Regression ◽  
Perceived Parental Support ◽  
Micro Level ◽  
Ecological Momentary

Abstract Lack of parental support is related to more adolescent negative mood. However, little is known about how fluctuations of parental support relate to fluctuations of negative mood within adolescents in daily life. The current study aimed to elucidate these processes at a day to day micro-level and examined to which extent adolescents would differ in the association between perceived parental support and adolescent negative mood. The sample consisted of 242 Dutch adolescents (Mage = 13.82, 63.2% female) who completed ecological momentary assessments of 3 weeks 3 months apart. Results from the multilevel regression analyses showed that, on average, adolescents experienced higher levels of negative mood on days when they perceived their parents to be less supportive. Substantial individual differences were found in this association, however, these were partially explained by the level of depressive symptoms and perceived parental intrusiveness. These findings suggest that advice on parental support should be tailored to the unique characteristics of the adolescent.

scholarly journals The Role of Individual and Neighborhood Characteristics on Mental Health after a Period of Economic Crisis in the Lisbon Region (Portugal): A Multilevel Analysis

2019 ◽  
Vol 16 (15) ◽  
pp. 2647 ◽  
Author(s):  
Loureiro ◽  
Santana ◽  
Nunes ◽  
Almendra
Keyword(s):  
Mental Health ◽  
Economic Crisis ◽  
Cross Sectional Study ◽  
Poor Mental Health ◽  
Individual Characteristics ◽  
Neighborhood Environment ◽  
Neighborhood Characteristics ◽  
Multilevel Regression ◽  
Cross Sectional ◽  
The Individual

Mental health is an intrinsic dimension of health influenced by individual and contextual factors. This cross-sectional study analyzes the association between the individual, neighborhood characteristics, and one’s self-assessed mental health status in the Lisbon region after an economic crisis. Via the application of multilevel regression models, the study assesses the link between one’s neighborhood environment—deprivation, low self-assessed social capital, and low self-assessed satisfaction with the area of residence—and mental health regardless of one’s individual characteristics. Constraints related to the economic crisis play an important role in the explanation of poor mental health.

scholarly journals The Effects of Sampling Frequency and Questionnaire Length on Perceived Burden, Compliance, and Careless Responding in Experience Sampling Data in a Student Population

Assessment ◽  
2020 ◽  
pp. 107319112095710
Author(s):  
Gudrun Eisele ◽  
Hugo Vachon ◽  
Ginette Lafit ◽  
Peter Kuppens ◽  
Marlies Houben ◽  
...  
Keyword(s):  
Sampling Method ◽  
Experience Sampling ◽  
Sampling Frequency ◽  
Negative Consequences ◽  
Regression Analyses ◽  
Multilevel Regression ◽  
Insufficient Information ◽  
Item Questionnaire ◽  
Perceived Burden ◽  
Careless Responding

Currently, little is known about the association between assessment intensity, burden, data quantity, and data quality in experience sampling method (ESM) studies. Researchers therefore have insufficient information to make informed decisions about the design of their ESM study. Our aim was to investigate the effects of different sampling frequencies and questionnaire lengths on burden, compliance, and careless responding. Students ( n = 163) received either a 30- or 60-item questionnaire three, six, or nine times per day for 14 days. Preregistered multilevel regression analyses and analyses of variance were used to analyze the effect of design condition on momentary outcomes, changes in those outcomes over time, and retrospective outcomes. Our findings offer support for increased burden and compromised data quantity and quality with longer questionnaires, but not with increased sampling frequency. We therefore advise against the use of long ESM questionnaires, while high-sampling frequencies do not seem to be associated with negative consequences.

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