Informatics Publishing Limited

Muhammad Siddique , Sehrish Saleem , Mazhar Ali Abbasi

Abstract

The present study aims at to analyze the feminization poverty in Hazara Division of Khyber PakhtunKhwa province of Pakistan. Sample of 200 respondents both from rural as well as urban has been selected for 50 female headed house holds and 150 male headed house holds. The study employs logistic regression estimation technique to find the correlates of poverty. The findings of study suggest that probability of a house hold being poor is positively and significantly correlated with house hold size, dependency ratio, and single parenthood, living of house hold head in rural area, female headed house hold ship. Variables that are negatively and significantly correlated with probability of being poor are: Age of house hold head, Secondary and post secondary education, employment and residing in urban area. The study recommends policy interventions necessary to reduce poverty particularly focusing female-headed households including direct transfer of cash to such families and access to free education to their children.

Keywords

Feminization of poverty, Logistic regression, Hazara Division

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Shahzad Ashraf ¹, Tauqeer Ahmed ¹, Sehrish Saleem ², Zeeshan Aslam ³

Affiliations
1 College of Internet of Things Engineering, Hohai University Changzhou Jiangsu, CN
2 Muhammad Nawaz Sharif University of Engineering & Technology Multan, PK
3 Petroweld Oilfield Services Kurdistan, IQ

Abstract

The sustainability and environmental considera-tions have slowly become divergences, but having greatest influence in the supply chain management that must be contemplates to examine the environmental and organizational factors. The research considers environmental and sustainable strategies within companies, the efficient supply chain management strategies for manufacturers and consumers, and to the environment friendly product design and services, taking a case-by-case perspective and concentrating on enterprise businesses scale. Our finding reveals that green supply chain management firms are delivering exuberant environmental efficiency at an added cost. Among the identified obstacles we identified different obstacles and conceptual relations and barriers are graded based on dependency and driving sand. In future, green policies have greater customer services avenues thereby, appeal for suppliers, manufacturers and officials.

Keywords

Bodacious Management, Diverging Trends, Green Management, Supply Chain.

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Sehrish Saleem ¹, Shahzad Ashraf ², Muhammad K. Basit ¹

Affiliations
1 Department of Computer Science, Muhammad Nawaz Sharif University of Engineering and Technology, PK
2 College of Internet of Things Engineering, Hohai University, Changzhou Campus, CN

Abstract

All humans are born with unique physically identified body characteristics to other persons which remains unchanged throughout life. These characteristics are taken into account by the emerging technology to get recognized from person to person. The technology used by the traditional human identification system sometimes becomes inefficient when data or images received are not up to the acceptable quality mark or when a person has a face covered with mask-like during epidemic virus fistula. In order to overcome the human recognition challenges, a Candid Multi-purpose Biometric Approach (CMBA) has been proposed which can make human identification easier and approachable. The CMBA human recognition approach uses two uniquely identified modalities such as foot and iris. This approach shrewdly identifies and makes the bodacious recognition among humans and suggests the sagacious result which is foremost better than the traditional biometric system. The CMBA is offering opportunity to take more than two biometric features, by combining them to overcome unimodal biometric system limitations and to achieve optimal results. Using sagacious edge detector and Hough transformation technique, the Iris and foot part are segmented into easy and quick extraction voting system which produce succulent output. In fact, this technique is new in biometric identification era.

Keywords

Biometric System, Face Recognition, Modalities, Face Mask.

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