A unique approach of person reidentification using auto track regression framework

2021 ◽  
pp. 1-18
Author(s):  
M.L. Sworna Kokila ◽  
Dr. V. Gomathi
Keyword(s):  
Personal Growth ◽  
Detection Method ◽  
Probit Regression ◽  
Query Image ◽  
Dense Area ◽  
Data Set ◽  
Human Uniqueness ◽  
Unique Approach ◽  
Backpropagation Method ◽  
Auto Track

Automatic Person Re-identification by video surveillance is commonly used in different applications. Perhaps the human uniqueness criteria for tracking the presence of the same person across multiple camera views and a person’s growth identification is extremely challenging. To solve the above problem, we propose an efficient Auto Track Regression System (ATRF) based on a deep learning technique that uses an eminent representation strategy along with recognition. In this work, the Auto Wiley Detective (AWD) approach is proposed for the representation of features that can collect valuable information by monitoring individuals. After obtaining important information on the characteristics, it is possible to define the personal growth identity of the generation. The OPVC (Original Pick Virtual Classifier) is used for accurate classification of the queried person from a dense area by utilizing features of a person’s growth identity extracted from feature extraction by the Auto Wiley Detection Method. The proposed Originated Pick Virtual Classifier (OPVC) uses Platt scaling (originated pick) on probit regression (virtual) to train the featured data set for accurate person re-identification, which is boosted by the Karush–Kuhn–Tucker (KKT) conditions to reduce false re-identification. Since the gallery information is trained using the Backpropagation method and smoothened analysis through approximated output, the Auto Wiley Detection Method proficiently detects the required information automatically. This also helps to detect the person query image from the database, which contains a vast collection of video images based on the similarity features identified in the query image and the detailed features extracted from the query image. The classification is completed automatically, and then the Person Re-Identification from the databases is performed accurately and efficiently. Henceforth, the proposed work effectively extracts reliable height and age estimates with improved flexibility and individual re-identifying capabilities.

scholarly journals Analysis of Gender Differences in Internet Use of Children: Evidence from Turkey

2016 ◽  
Vol 8 (1) ◽  
pp. 199
Author(s):  
Ömer Alkan
Keyword(s):  
Mobile Phone ◽  
Information Technologies ◽  
Internet Use ◽  
Educational Status ◽  
Probit Regression ◽  
Chi Square ◽  
Data Set ◽  
Printed Media ◽  
Female Children ◽  
Chi Square Analysis

<p>In this study, factors in Internet use of female and male children in Turkey were determined with probit regression model by using micro data set in Household Information Technologies Usage Research of 2013 carried out by Turkish Statistical Institute. Dependent variable of the study is two category variable, namely Internet use and non-use of female and male children. Independent variables are socio-economic and demographic variables. According to chi-square analysis, there is a relation between Internet use of female and male children and socio-economic and demographic characteristics. According to probit regression analysis results, for female children, region, educational status, having computer or mobile phone on their own, frequency of watching TV, watching movie, series; floor show, music, game show; watching educational programs such as documentaries, culture, art, reading newspaper and journal in printed media, using mobile phone and frequency of using computer are variables effective in Internet use. Region, rural-urban difference, age, being literate, educational status, having mobile phone or game console on their own, watching entertainment, music, competition programs, reading newspaper and journal in printed media, using mobile phone and, frequency of using computer are variables effective in Internet use among male children. Frequency of using computer is the most effective variable in Internet use and it is more effective among female children compared to male children.</p>

scholarly journals Does Neighbourhood Design Impact Social Interactions Amongst Neighbours? Studying The Influence Of Neighbourhood Built-form & Type On Socialization Among Neighbours In Canadian Cities

2021 ◽  
Author(s):  
Wafaa Muzaffar
Keyword(s):  
Social Interactions ◽  
Probit Regression ◽  
Design Features ◽  
Data Set ◽  
Built Form ◽  
New Urbanist ◽  
Form Type ◽  
Neighbourhood Structure ◽  
Structure And Design ◽  
Significant Effort

Urban planning has devoted significant effort to exploring the linkages between neighbourhood design and social interactions. With the increasing popularity of New Urbanism, the role New Urbanist design features play in promoting neighbourly socialization and strengthening communal bonds have become widely debated. This thesis contributes to the existing literature by researching how socialization differs between New Urbanist and traditional suburban neighbourhoods and whether the socialization difference, if any, results from differences in neighbourhood structure and design. This thesis uses a data set comprised of eight neighbourhoods - four of which are New Urbanist neighbourhoods and the other four are traditional suburban neighbourhoods. Using ordered probit regression modelling, the extent of socialization that stems from households’ demographic characteristics and the housing-level and neighbourhood-level physical design features is determined. The results indicate that socialization is more likely to be influenced by the amalgamated effect of neighbourhood type, rather than design features alone.

scholarly journals DETERMINANTS OF DOMESTIC PHYSICAL VIOLENCE AGAINST WOMEN IN TURKEY

2021 ◽  
Vol 8 (6) ◽  
pp. 55-67
Author(s):  
Ömer Alkan ◽  
Şeyda Ünver
Keyword(s):  
Domestic Violence ◽  
Violence Against Women ◽  
Physical Violence ◽  
Intimate Partner ◽  
Intimate Partners ◽  
Probit Regression ◽  
Data Set ◽  
Factors Affecting ◽  
Number Of Children ◽  
Domestic Violence Against Women

Purpose of the study: This study aims to determine the factors affecting the exposure of women in Turkey 15 years of age and older to physical violence by their husband/intimate partner. Methodology: In this study, the micro-data set of the "Research on Domestic Violence against Women in Turkey" conducted by Hacettepe University Institute of Population Studies in 2008 and 2014 was used. In this data set, the data of 18518 women aged 15 and over were used, 11722 in 2008 and 6796 in 2014. Factors affecting women's physical violence were determined using binary logistic and probit regression analysis. This study focuses on the physical violence of the husband/partner, which is the most common type of domestic violence against women. Main Findings: The variables of survey year, region, education level, individual income, marital status, health status, the number of children, and being exposed to violence from first degree relatives are seen to be significant. According to the results obtained, the expected probability of exposure to physical violence women who were subjected to economic, verbal, and sexual violence by their husbands/intimate partners was more than 39.8%, 127.35%, and 83.68%, respectively. Applications of this study: The study outcome indicate that important steps to reduce domestic physical violence against women in Turkey should be taken. In order to prevent new cases of abuse, coordinated efforts to raise awareness of the problem of domestic physical violence against women will encourage action. Novelty/Originality of this study: In this study, factors affecting the exposure of women in Turkey, 15 years old and older, to physical violence by their husband/intimate partner were identified. In the study, the socio-demographic and economic characteristics of women and to what extent the various risk factors related to husband/intimate partners were critical for the women's exposure to physical violence.

scholarly journals Application of a WiFi/Geomagnetic Combined Positioning Method in a Single Access Point Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Hongbin Pan ◽  
Yang Xiang ◽  
Jian Xiong ◽  
Yifan Zhao ◽  
Ziwei Huang ◽  
...  
Keyword(s):  
Nearest Neighbor ◽  
Detection Method ◽  
Access Point ◽  
Combination Method ◽  
Data Set ◽  
Positioning Accuracy ◽  
Multipath Effects ◽  
Positioning Method ◽  
Fingerprint Database ◽  
Mismatch Rate

Because of the particularity of urban underground pipe corridor environment, the distribution of wireless access points is sparse. It causes great interference to a single WiFi positioning method or geomagnetic method. In order to meet the positioning needs of daily inspection staff, this paper proposes a WiFi/geomagnetic combined positioning method. In this combination method, firstly, the collected WiFi strength data was filtered by outlier detection method. Then, the filtered data set was used to construct the offline fingerprint database. In the following positioning operation, the classical k -nearest neighbor algorithm was firstly used for preliminary positioning. Then, a standard circle was constructed based on the points obtained by the algorithm and the actual coordinate points. The diameter of the standard circle was the error, and the geomagnetic data were used for more accurate positioning in this circle. The method reduced the WiFi mismatch rate caused by multipath effects and improved positioning accuracy. Finally, a positioning accuracy experiment was performed in a single AP distribution environment that simulates a pipe corridor environment. The results proves that the WiFi/geomagnetic combined positioning method proposed in this paper is superior to the traditional WiFi and geomagnetic positioning methods in terms of positioning accuracy.

Semi supervised inspection algorithm of automatic packaging curve based on deep learning

2021 ◽  
pp. 1-10
Author(s):  
Yong He
Keyword(s):  
Deep Learning ◽  
Supervised Learning ◽  
Optimization Algorithm ◽  
Posterior Probability ◽  
Detection Method ◽  
Detection System ◽  
Experimental Results ◽  
Detection Accuracy ◽  
Data Set ◽  
Packaging Process

The current automatic packaging process is complex, requires high professional knowledge, poor universality, and difficult to apply in multi-objective and complex background. In view of this problem, automatic packaging optimization algorithm has been widely paid attention to. However, the traditional automatic packaging detection accuracy is low, the practicability is poor. Therefore, a semi-supervised detection method of automatic packaging curve based on deep learning and semi-supervised learning is proposed. Deep learning is used to extract features and posterior probability to classify unlabeled data. KDD CUP99 data set was used to verify the accuracy of the algorithm. Experimental results show that this method can effectively improve the performance of automatic packaging curve semi-supervised detection system.

scholarly journals The Assisted Positioning Technology for High Speed Train Based on Deep Learning

2020 ◽  
Vol 10 (23) ◽  
pp. 8625
Author(s):  
Yali Song ◽  
Yinghong Wen
Keyword(s):  
Deep Learning ◽  
High Speed ◽  
Detection Method ◽  
Generative Adversarial Networks ◽  
Single Shot ◽  
High Speed Train ◽  
Data Set ◽  
Detection Model ◽  
Model Based ◽  
Cumulative Error

In the positioning process of a high-speed train, cumulative error may result in a reduction in the positioning accuracy. The assisted positioning technology based on kilometer posts can be used as an effective method to correct the cumulative error. However, the traditional detection method of kilometer posts is time-consuming and complex, which greatly affects the correction efficiency. Therefore, in this paper, a kilometer post detection model based on deep learning is proposed. Firstly, the Deep Convolutional Generative Adversarial Networks (DCGAN) algorithm is introduced to construct an effective kilometer post data set. This greatly reduces the cost of real data acquisition and provides a prerequisite for the construction of the detection model. Then, by using the existing optimization as a reference and further simplifying the design of the Single Shot multibox Detector (SSD) model according to the specific application scenario of this paper, the kilometer post detection model based on an improved SSD algorithm is established. Finally, from the analysis of the experimental results, we know that the detection model established in this paper ensures both detection accuracy and efficiency. The accuracy of our model reached 98.92%, while the detection time was only 35.43 ms. Thus, our model realizes the rapid and accurate detection of kilometer posts and improves the assisted positioning technology based on kilometer posts by optimizing the detection method.

Penalized Binary Regression for Gene Expression Profiling

2004 ◽  
Vol 43 (05) ◽  
pp. 439-444 ◽  
Author(s):  
Michae Schimek
Keyword(s):  
Microarray Analysis ◽  
Predictive Performance ◽  
Small Sample ◽  
Probit Regression ◽  
Binary Regression ◽  
Data Set ◽  
Small Sample Sizes ◽  
Bayesian Probit Regression

Summary Objectives: A typical bioinformatics task in microarray analysis is the classification of biological samples into two alternative categories. A procedure is needed which, based on the expression levels measured, allows us to compute the probability that a new sample belongs to a certain class. Methods: For the purpose of classification the statistical approach of binary regression is considered. High-dimensionality and at the same time small sample sizes make it a challenging task. Standard logit or probit regression fails because of condition problems and poor predictive performance. The concepts of frequentist and of Bayesian penalization for binary regression are introduced. A Bayesian interpretation of the penalized log-likelihood is given. Finally the role of cross-validation for regularization and feature selection is discussed. Results: Penalization makes classical binary regression a suitable tool for microarray analysis. We illustrate penalized logit and Bayesian probit regression on a well-known data set and compare the obtained results, also with respect to published results from decision trees. Conclusions: The frequentist and the Bayesian penalization concept work equally well on the example data, however some method-specific differences can be made out. Moreover the Bayesian approach yields a quantification (posterior probabilities) of the bias due to the constraining assumptions.

Hedonic value and crowdfunding project performance: a propensity score matching-based analysis

2017 ◽  
Vol 9 (2) ◽  
pp. 169-186 ◽  
Author(s):  
Liang Zhao ◽  
Tsvi Vinig
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Real Data ◽  
Project Performance ◽  
Probit Regression ◽  
Data Set ◽  
Content Type ◽  
Hedonic Value ◽  
Utilitarian Value ◽  
The Impact

Purpose In the existing literature on crowdfunding project performance, previous studies have given little attention to the impact of investors’ hedonic value and utilitarian value on project results. In a crowdfunding setting, utilitarian value is somehow hard to satisfy due to information asymmetry and adverse selection problem. Therefore, the projects with more hedonic value can be more attractive for potential investors. Lucky draw is a method to increase consumer hedonic value, and it can influence investors’ behavior as a result. The authors hypothesize that projects with hedonic treatment (lucky draw) may have higher probability to win their campaign than others. The paper aims to discuss these issues. Design/methodology/approach A unique self-extracted two-year Chinese crowdfunding platform real data set has been applied as the analysis sample. The authors first employ propensity score matching methods to control for the endogeneity of hedonic treatment adoption (lucky draw). The authors then run OLS regression and probit regression in order to test the hypotheses. Findings The analysis suggests a significant positive relationship not only between project lottery adoption and project results but also between project lottery adoption and project popularity. Originality/value The results suggest that an often ignored factor – hedonic treatment (lucky draw) – can play an important role in crowdfunding project performance.

Impediments on the way to entrepreneurship. Some new evidence from the EU's post-socialist world

2014 ◽  
Vol 21 (3) ◽  
pp. 385-402 ◽  
Author(s):  
Georgios K. Batsakis
Keyword(s):  
Structural Changes ◽  
Transition Process ◽  
Geographic Area ◽  
Tax Rates ◽  
The European Union ◽  
Probit Regression ◽  
Data Set ◽  
Policy Makers ◽  
Content Type ◽  
Rich Data

Purpose – The purpose of this paper is to shed light on traditionally important determinants (demographics, peoples’ perceptions, and environmental characteristics) of entrepreneurial engagement in the post-socialist region of the European Union (EU). Design/methodology/approach – A rich data set obtained from the Flash Eurobarometer Survey on Entrepreneurship 2007 is used, while a binomial probit regression model is employed. Findings – Gender, mother's occupation, unemployment, and economic growth are reported as significant determinants of entrepreneurship. The econometric results also suggest that lack of financial resources, individual's risk aversion, a large number of start-up procedures, and increased tax rates are all positively, rather than negatively related to entrepreneurial engagement. Research limitations/implications – It is suggested that the recent structural changes that have occurred in the examined region, as well as the transition process under which the examined countries operate have influenced the attitude of individuals towards entrepreneurial engagement. Originality/value – The study provides useful information in relation to the attitude of a post-socialist society towards structural issues which have possibly impeded its engagement to entrepreneurship. Both the geographic area (post-socialist European countries) and the time the data were collected (i.e. three years after the examined countries’ accession to the EU) can be perceived as factors of great interest for both policy makers and entrepreneurs.

scholarly journals The effect of ethical leadership on subjective wellbeing, given the moderator job satisfaction (a case study of private hospitals in Mashhad)

BMC Nursing ◽  
2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Azar Kaffashpoor ◽  
Samaneh Sadeghian
Keyword(s):  
Job Satisfaction ◽  
Ethical Leadership ◽  
Structural Equation ◽  
Subjective Wellbeing ◽  
Simple Random Sampling ◽  
Equation Modeling ◽  
Data Set ◽  
Private Hospitals ◽  
Managerial Efficiency ◽  
Unique Approach

Abstract Background The emerging ethical leadership, a unique approach in leadership viewpoint, has provided the ground for constructing and advancing individual and managerial efficiency by highlighting ethics in organizations. The present study aims to investigate the influence of Ethical Leadership on Subjective Wellbeing, Given the Moderator Job Satisfaction in Private Hospitals in Mashhad. Methods This descriptive-correlational research design stud was conducted in 2015–2016 to inspect the possible effect of ethical leadership on subjective wellbeing and job satisfaction, as dependent and mediator variables, among the Iranian private hospitals’ nurses in Mashhad. Simple random sampling method was used to select the sample of 166 nurses out of the population of 730 nurses, in total. The valid and reliable adapted version of the questionnaire designed by Yang (2014) was used to collect the data, and structural equation modeling (SEM) was used to analyze the data set. Results The results showed that there is a positive significant correlation between ethical leadership and job satisfaction. More specifically, the findings indicated that Ethical leadership affected the subjective wellbeing of nurses through job satisfaction both directly and indirectly. Conclusions The findings illustrated that focus on ethics and ethically-oriented leaders in hospitals, enriched by job satisfaction can lead to the nurses’ subjective wellbeing by providing them a positive climate.

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