Volume 9 | Issue 2 |

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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MOS, Sio2, CMOS, SOI, CSA, GCA, FET.

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT Background: Today's Filipinas have made their legacy in each of their endeavors. (Convergys Corp., 2018). For years, Filipina women have been considered people who stayed at home, namely, homemakers or those who cannot do masculine jobs. Method: This study is a qualitative research design, in which the method used to gather the data is by interviewing the participants selected by the researchers. The type of qualitative research used is a phenomenological approach. It is related to the central question "How do Filipina leaders employed in a Qatar-based company adapt to their work environment?". In line with our title, "Women Empowerment: A Study of the lived experiences of Filipina Leaders in the State of Qatar," the researchers chose Filipina leaders who are currently working and are employed in Qatar as their target respondents for the study. The conducting of this research follows the IMRAD format and aims to be published and reproduced easily. The researchers deemed the target respondents sufficient and knowledgeable for this study. As students currently studying in Philippine School Doha, the researchers' research will be respectfully conducted in the host country, Qatar. Findings have revealed that Filipina leaders have encountered many challenges and have shown the advantages and disadvantages of being a Filipina leader as discussed through work parity, work conformity, work impartiality, and work proclivity. Conclusion: Women 's leadership is about continuing to implement changes that promote women 's advancement within their organizations and businesses, resolve implicit bias problems, and inspire women and men to create solutions.

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Creative Commons Attribution 4.0 and The Open Definition

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Leadership, Women Empowerment, Qatar-based Company, Workplace Discrimination, Lived Experiences, Phenomenological Approach

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Creative Commons Attribution 4.0 and The Open Definition

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Urban Politics refers to the diverse political structure that occurs in urban regions where there is diversity in caste, religion and socio-economic status of people. The present study includes the structure of politics of a geographic space and spatial variations in voter�s choice. Delhi is one of the fastest growing cities in the world, it offers vast economic opportunities, education and medical facilities etc, has thus created very strong attractive force pulling migrants not only from the immediate neighborhood but also from the far-off places in the country. The phenomenal growth rate of the city has creates many developmental issues. This study tells us how urban politics and urban development are interconnected. The political skyline in Delhi saw dramatic changes since 2013 assembly election when Aam Adami Party came out as a second largest party and after that in 2015 and recently in 2020 it won maximum 62 seats and all the old National Parties like INC and BJP failed to attract voters. The recent election of Delhi was the best example where in many constituencies people cast their votes without keeping in mind the history of political parties, caste and religion of candidates.

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Creative Commons Attribution 4.0 and The Open Definition

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Urban politics, Urbanization, Political parties, Voters, Constituencies.

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Creative Commons Attribution 4.0 and The Open Definition

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Melanoma is considered a fatal type of skin cancer. However, it is sometimes hard to distinguish it from Nevus due to their identical visual appearance and symptoms. The mortality rate because of this disease is higher than all other skin related consolidated malignancies. The number of cases is growing amongst young people but if it is diagnosed at its earlier stage then the survival rates become very high. The cost and time required for the doctors to diagnose all patients for Melanoma are very high. In this work, we propose an intelligent system to detect and distinguish Melanoma from Nevus by using state of the art image processing techniques. At first, Gaussian Filter is used for removing noise from the skin lesion of the acquired images followed by the use of fuzzy c-mean clustering to segment out the lesion. A distinctive hybrid super feature vector is formed by the extraction of textural and color features from the lesion. Support Vector Machine (SVM) is utilized for the classification of skin cancer into melanoma and nevus. Our aim is to test the effectiveness of the proposed segmentation technique, extract the most suitable features and compare the classification results with the kNN techniques present in the literature. The proposed methodology is tested on DERMIS dataset.

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Creative Commons Attribution 4.0 and The Open Definition

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Dermis dataset, Skin Cancer, kNN, SVM

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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The objective of this research is to develop a real-time system for hand gesture recognition that recognizes hand gestures, features of hands such as peak calculation and angle calculation, and then convert gesture images into text. To implement this system we use a sign language hand gesture dataset..The proposed system has four main modules such as preprocessing, segmentation, feature extraction, and classification. In the preprocessing module, the input image is converted into a grayscale image, noise removal, normalization, and rescale the image. After preprocessing, the image is segmented using an automatic threshold algorithm. Then the feature extraction is calculated using SIFT and SURF descriptors. The collected features are trained using an excel file. Finally, the input is classified using the SVM algorithm.

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Creative Commons Attribution 4.0 and The Open Definition

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SIFT, SURF

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

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Ozone dataset, Datamining Algorithms

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Creative Commons Attribution 4.0 and The Open Definition

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Bio-synthesis of nanoparticles is gaining huge importance, these days. Gold nanoparticles (GNPs) are widely used for various applications such as drug delivery, bioprobe, Imaging and drug targeting. Various sources such as plant extracts, fungi and microbes are used for the synthesis of GNPs. Algae are living in a sessile aquatic environment for its survival and it has certain bioactive compounds such as carbohydrates, aminoacids, proteins, fatty acids, flavonoids, antioxidants, saponins, etc. However, there are only limited studies for the synthesis of GNPs using algae. Hence, in this study, clinically potent GNPs were synthesized using fresh water green algae Charavulgaris. In the present study, the colour of the prepared solution changes from yellowish green to red wine indicates the synthesis of gold nanoparticles. In addition, UV-Vis spectrophotometer, SEM, XRD and FT-IR analysis was done for the analyses of gold nanoparticles. Furthermore, antibacterial study was done and it showed maximum sensitivity to the given bacterial species.

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Creative Commons Attribution 4.0 and The Open Definition

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Bio synthesis, gold nanoparticles, fresh water algae, Charavulgaris, anti-microbial study

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Creative Commons Attribution 4.0 and The Open Definition

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Detecting and classifying fetal brain abnormalities from magnetic resonance imaging (MRI) is important, as approximately 3 in 1000 women are pregnant with a fetal of abnormal brain. Early detection of fetal brain abnormalities using machine learning techniques can improve the quality of diagnosis and treatment planning. The literature has shown that most of the work made to classify brain abnormalities in a very early age is for preterm infants and neonates not fetuses. However, research papers that studied fetal brain MRI images have mapped these images with the neonates MRI images to classify an abnormal behaviour in newborns not fetal. In this work, a pipeline process is proposed for fetal brain classification (FBC) which uses machine learning techniques. The main contribution of this work is the classification of fetal brain abnormalities in early stage, before the fetal is born. The proposed algorithm is capable of detecting and classifying a variety of abnormalities from MRI images with a wide range of fetal gestational age (GA) (from 16 to 39 weeks) using a flexible and simple method with low computational cost. The novel proposed method consists of four phases; pre-processing, segmentation, feature extraction and classification. In the pre-process, the input image is converted into gray scale and apply the wiener filter for image enhancement. After pre-processing, the adaptive segmentation is applied for segmenting the image. Then DWT and statistical features are extracted from segmented images. Finally, the input image is classified using the Decision Tree algorithm.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fetal Brain Abnormalities, machine learning algorithms

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

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SVD, GLCM, certificate authentication

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Creative Commons Attribution 4.0 and The Open Definition